Morphometric Signature and Geomorphic Attributes of the Mula and Pravara River Basins (Maharashtra, India)

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The Shuttle Radar Topographic Mission- Digital Elevation Model (SRTM-DEM) data and GIS techniques were used to derive over 60 morphometric parameters, including linear, aerial, basin, and relief characteristics. These parameters were analysed to assess structural controls, erosion potential, and watershed behaviour. Results reveal distinct contrasts: the Mula River Basin (MRB) exhibits a mature 7th-order drainage network with higher infiltration capacity (If = 4.80) and gentler slopes (5.75%). At the same time, the Pravara River Basin (PRB) displays stronger tectonic influence through elevated bifurcation (7.5°) and ruggedness indices (MRn = 28.99), coupled with greater runoff potential (Dd = 2.1 km/km²). Both basins exhibit elongated profiles (Re = 0.29–0.32) and youthful-to-mature characteristics, with hypsometric integrals (HI = 0.26–0.29) indicating advanced erosional maturity. Longitudinal profiles highlight knick points associated with Deccan basalt lithology, whereas meandering patterns reflect shifting fluvial regimes. The study underscores the PRBs’ heightened vulnerability to flash floods and erosion, providing critical insights for sustainable watershed management. This integrated approach demonstrates the efficacy of GIS and remote sensing in decoding landscape evolution and guiding resilience-focused planning in semi-arid fluvial systems. Morphometry analysis Geospatial Technique Watershed management Mula-Pravara River Basin Maharashtra India Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 1. Introduction A watershed is an area where all water flows to a single common outlet. It serves as a basic hydrological unit that directs surface runoff into a stream network (Swallow et al. 2001 ; Johnson et al. 2013 ; Gaikwad and Bhagat 2017 ; Meierdiercks et al. 2024 ). Since a watershed collects runoff to a single outlet, studying it as a whole is more effective than analysing individual channels or small segments (Altaf et al. 2013 ). Rivers are sensitive features of the landscape, and their long-term changes reflect fluvial systems under different climates, rock types, and tectonic conditions (Nile et al . 2025). Morphometric analysis is a key research method for understanding hydrologic and geomorphic processes in river basins (Kale et al. 2014 ; Das and Pardeshi 2018; Gaikwad et al. 2024 ; Memon et al. 2024 ). Additionally, a watershed is a natural system encompassing soil, water, and vegetation, and it also influences social, economic, and cultural aspects (Ghanbarpour and Hipel 2011 ). It involves measuring key parameters, including drainage density, bifurcation ratio, watershed slope, channel length, and relief (Javed et al . 2011; Thomas et al. 2011 ; Vieceli et al . 2015; Rai et al . 2017). Additionally, morphometric analysis plays a crucial role in geological mapping and hazard assessments, including flood and landslide susceptibility (Kale and Rajaguru 1986 ). Rivers also record landscape changes over time, with longitudinal profiles reflecting faulting, tectonic activity, and landform evolution. This analysis enhances geological understanding and complements traditional morphometric methods (Das et al. 2018 ; Kudnar 2020 ; Gaikwad et al. 2024 ). Hence, past land changes can be understood by analysing these variables through a morphometric study. The morphometric analysis is a fundamental approach to drainage quantification and has been widely applied in surface geology studies (Horton 1932 , 1945 ; Strahler 1957 , 1964 ; Schumm 1956 ; Gregory 1966 ; Manu and Anirudhan 2008 ; Sreedevi et al. 2005 ; Thomas et al. 2011 ; Dusan et al . 2017; Kumar et al. 2015 ; Das and Pardeshi 2018; Mohammed et al .2025). It plays a crucial role in examining drainage patterns, terrain deformation, and structural changes over time (Kale and Rajaguru 1986 ; Moussa 2003 ; Mesa 2006 ). Recent studies define morphometric analysis as the measurement and assessment of linear, aerial, and elevation features of the land surface, including shape and dimensions. With advancements in GIS and DEMs, hydrological and geomorphological studies now achieve greater accuracy and efficiency. DEMs provide high-resolution elevation data, enhancing the analysis of drainage patterns and terrain morphology. These technologies have become essential tools for modern geomorphic research, enabling precise spatial analysis and modelling of landform evolution and geological structures (Singh and Singh 2011 ; Sreedevi et al. 2013 ; Iqbal and Sajjad 2014 ; Raja and Karibasappa 2016; Gaikwad and Bhagat 2017 ; Das et al. 2018 ; Kudnar 2020 ; Gaikwad et al. 2024 ). Additionally, the use of RS data within a GIS environment significantly enhances the precision of morphometric and morphotectonic studies, making it a consistent approach for watershed assessment, particularly in regions with few ground-truth sites for validation (Gaikwad 2019 ; Gaikwad et al. 2023 ). In the past, morphometric analysis relied on traditional methods such as topographic sheets and field surveys. Today, RS and GIS technologies, especially the use of DEMs, have made this process faster, more accurate, and widely applicable for studying watershed and morphotectonic features. These tools significantly enhance spatial data analysis for effective basin evaluation (Kudnar and Rajashekhar 2020; Pigazzi et al. 2024 ; Gaikwad et al. 2026 ). This study applies morphometric analysis to investigate the geomorphic characteristics of the MPRBs, focusing on drainage patterns, basin shape, and landform features. To better understand the influence of tectonic and structural forces on landscape development, longitudinal profiles of the PRB and MRB were examined as well. The GIS and DEMs have significantly advanced hydrology and geomorphology by providing accurate and accessible spatial data, making them indispensable for analysing landforms, drainage networks, and geological structures (Al-Saady et al. 2016 ; Das et al . 2017a; Das and Pardeshi 2018a , b ; Gaikwad et al. 2023 ; Pigazzi et al. 2024 ). Therefore, the present study aims to analyse the morphometric characteristics of the MPRBs using GIS and remote sensing to understand landform evolution and assess the influence of tectonic processes. 2. Study Area The MPRBs are located in the eastern region of the Western Ghat, within the Ahilyanagar district of Maharashtra, India, and cover approximately 2,637 km². Geographically, the basin lies between latitudes 19°25′N and 19°45′N and longitudes 74°30′E and 74°0′E, forming part of the larger Godavari River system (Fig. 1 ). The Mula is a major tributary of the Pravara, and both rivers discharge a large amount of water into the Godavari River Basin. This makes the Godavari Basin the second-largest in peninsular India, after the Ganges. The land in the study area varies in height from 404 to 1424 m above mean sea level and has moderate slopes. Geographically, the area can be divided into three parts: hilly terrain in the west (Western Ghat), a gently sloping pediment in the centre, and a plateau with a slight slope in the east (Das et al. 2018 a). As a sub-basin within this region, the MRB occupies the southwestern portion of the Pravara catchment. The Mula and Pravara Rivers originate from the high-altitude escarpments of the Western Ghat. It flows through varied terrain, transitioning from rugged, elevated landscapes in the west to gently sloping plains in the east. The western region of the MPRBs is characterised by elevated topography, forming a dissected plateau that significantly influences drainage patterns and the spatial distribution of fluvial activity within the basin. This area encompasses several prominent volcanic peaks, including Kalsubai (1646 m), Harishchandragad (1428 m), Ajoba Dongar (1375 m), Ratangad (1297 m), and the Alang-Madan-Kulang mountain range (1464–1494 m), all of which are products of the Deccan Volcanic Province (Fig. 2 ). As it progresses eastward, the terrain transitions to a middle-level plateau, with elevations ranging from 550 to 900 m above mean sea level. Watmai (876 m) and Dudheshwar (833 m) are the major peaks in the plateau area of ​​the Pravara Basin, whereas Baleshwar (1100 m) is the major peak in the plateau area of ​​the Mula Basin. The middle of the basin is an old plain formed by ancient erosion. The younger floodplain has developed along the riverbanks due to the recent sediment deposition from the river flood (Fig. 2 ). These basins are formed by Upper Cretaceous basaltic flows (Wellman and McElhinny 1970 ; Widdowson and Mitchel 1999; Hooper et al .2010; Das and Pardeshi 2018b ) (Fig. 1 ). Geographically, these basins lie east of the Western Ghat. This central geomorphic zone displays moderate relief and is primarily shaped by denudational processes acting upon the basaltic Deccan Trap. The prolonged fluvial activity of MPRBs has significantly contributed to the dissection and modification of the landscape, leading to the classification of this region as a denudational slope. In the easternmost part of the basin, the slope gradient decreases substantially, resulting in depositional features such as alluvial terraces and broad floodplains. This geomorphic setting is characterised by flat riverbeds and sediment-accumulation zones. The transition from rugged highlands to subdued floodplains reflects spatial variation in geomorphological and geological characteristics across the basin. The study area experiences a predominantly hot and dry climate, with peak temperatures during the summer months (March to early June). The southwest monsoon (June to September) accounts for most of the annual rainfall, whereas the post-monsoon season occurs in October and November. Winters (November to February) are mild and dry. Rainfall is highest in the western hilly region and decreases gradually toward the east, with an average annual rainfall of 501.8 mm (Fig. 3 ). The MPRBs have a semi-arid climate due to their position in the rain shadow of the Western Ghat, which blocks much of the southwest monsoon. This results in low rainfall and elevated temperatures, particularly from October to May, when dry conditions prevail (Doke et al. 2018 ). 3. Methodology Since the late 20th century, the use of remote sensing and Geographic Information Systems (GIS) has significantly improved the ability to evaluate large drainage basins (Das and Pardeshi 2018). This study presents a comprehensive morphometric analysis of the MPRBs using topographic maps and remote sensing data. A total of 17 Survey of India (SOI) ( https://surveyofindia.gov.in ) toposheets (47 E/10, 47 E/11, 47 E/14, 47 E/15, 47 I/1, 47 I/2, 47 I/3, 47 I/4, 47 I/6, 47 I/7, 47 I/8, 47 I/10, 47 I/11, 47 I/12, 47 I/14, 47 I/15, and 47 I/16) on the scale of 1:50000 were acquired from the SOI and georeferenced using ArcMap 10.8.2 GIS platform. These toposheets were then mosaicked to generate a continuous spatial dataset, which enabled the manual digitisation of the entire river courses. To delineate the drainage network of the MPRBs, GIS software was employed along with DEM data. Initially, the DEM was pre-processed by filling sink areas to eliminate topographic depressions and ensure hydrological consistency (Schumm 1973 ; Gaikwad et al. 2024 ). Additionally, SRTM DEM data with a 30 m spatial resolution, obtained from the United States Geological Survey ( https://earthexplorer.usgs.gov ), were used to derive relief-based morphometric parameters (Fig. 4 ). This integrated approach, combining topographic sheets, remote sensing data, and GIS techniques, enabled detailed morphometric characterisation of the study area, providing a scientific foundation for further geographical interpretation and watershed management. 4. Linear Aspects 4.1 Stream Order (Su) Stream order serves as a foundational parameter in the quantitative analysis of watershed characteristics. The concept was first introduced by Horton ( 1932 ), who defined stream order as a hierarchical classification of streams based on their position within the drainage network. First-order streams are the smallest tributaries with no upstream connections and generally exhibit intermittent flow, particularly during the wet season. In the present study, stream networks were delineated from SOI Toposheets, and stream ordering was performed using Strahler’s ( 1957 ) method. According to the analysis, the MPRBs have stream orders of 7 and 6, respectively (Table 1 ). Typically, higher-order streams indicate larger drainage basins and are associated with substantial water discharge. Figure 5 illustrates the stream-order distribution for the MPRB watersheds. Consistent with Horton’s observations (1945), the highest frequency of streams occurs at the first order. Furthermore, the number of streams decreases progressively with increasing stream order, indicating an inverse relationship. 4.2 Stream Number (Nu) Stream number is a key hydrological parameter that provides valuable insights into surface runoff characteristics within a drainage basin (Kumar et al. 2015 ). A general observation, consistent with Horton’s laws, is that the number of streams decreases as stream order increases (Gezahegn and Mengistu 2025 ) (Fig. 5 A). This trend reflects the hierarchical nature of drainage networks. In this study, stream numbers were calculated using ArcGIS 10.8 for the MPRBs. Stream numbers generally decrease with increasing stream order and are influenced by the basin's lithology and structure. The MPRBs contain 11,064 and 6,919 streams, respectively. A significant proportion of these are first-order streams: the MRB has 8,566 and the PRB 5,387 (Table 1 ; Fig. 5 ). The high concentration of first-order streams indicates a dense drainage texture, which may increase the risk of flash floods during periods of intense rainfall (Chitra et al. 2011 ). 4.3 Stream Length (Lu) Stream length reflects the development of stream segments over time, including the impact of tectonic activity (Magesh et al. 2013 ). It represents the total stream length in each order within a basin and generally follows a geometric progression (Horton 1945 ). Areas with higher permeability tend to have longer and denser stream networks. In this study, stream lengths were calculated using ArcGIS software through the 'Calculate Geometry' tool. The results support Horton’s law, which states that geometrical similarity is usually maintained across increasing stream orders (Strahler 1964 ). The total stream length in the MRB is about 8,035 km, and in the PRB, about 6,000 km. Shorter stream lengths are associated with steeper slopes, whereas longer stream lengths are associated with lower gradients (Table 2 ). Thus, the longer stream lengths in the MRB indicate a gentler slope than in the PRB. 4.4 Mean Stream Length (Lum) Mean stream length (Lum) represents the average length of stream segments within a specific order and reflects the characteristic size of drainage components and their contributing area (Strahler 1964 ). Lum is calculated by dividing the total stream length of a given order by the number of streams in that order. It typically increases with stream order and is influenced by watershed size and topography. In this study, Lum values were 1,147.90 km for the MRB and 1,000 km for the PRB. As shown in Fig. 6 B, mean stream length increases with stream order, indicating a direct relationship. Table 1 Stream Order, Stream Number, and Bifurcation Ratios (A) Mula (B) Pravara Watershed. B) Su Nu Rb Nu-r Rb* Nu-r Rbwm Su Nu Rb Nu-r Rb* Nu-r Rbwm I 8566 4.43 I 5387 4.08 II 1951 4.4 10517 46175.6 II 1318 4.09 6705 27405.03 III 423 4.6 2374 10949.6 III 339 3.89 1657 6442.26 IV 99 4.3 522 2230.4 IV 89 3.81 428 1630.25 V 20 5.0 119 589.1 V 20 4.45 109 485.05 VI 4 5.0 24 120.0 VI 1 20.00 21 420.00 VII 1 4.0 5 20.0 Total 11064 27.2 13561 60084.6 Total 7154 36.2 8920 36382.5 Mean 4.5 2260.2 10014.1 Mean 7.2 4.5 Stream Length Ratio (Lur) Stream length ratio is the ratio of the mean stream length of one order to that of the next lower order (Horton 1945 ). According to Horton’s law, mean stream length increases in a geometric pattern with higher stream orders. Variations in this ratio can indicate the basin’s geomorphic stage, with noticeable changes often reflecting the late youth stage. In this study, the Mula Watershed exhibits a stream length ratio of 2.6, while the Pravara Watershed shows a higher ratio of 5.3 (Table 2 ; Fig. 6 B). 4.6 Bifurcation Ratio (Rb) The bifurcation ratio (Rb), defined by Schumm ( 1956 ), is the ratio of the number of stream segments in a given order (Nu) to those in the next higher order (Nu + 1). It helps assess the branching pattern and connectivity of a drainage network. Horton ( 1945 ) described Rb as an index reflecting relief and landscape dissection, while Strahler ( 1957 ) noted that Rb values are generally consistent except where geological controls are dominant. As a dimensionless parameter, Rb indicates the degree of integration between stream orders and varies with geological and lithological settings. Generally, Rb ranges from 3.0 to 5.0, with higher values pointing to structural influence (Strahler 1964 ; Nag 1998 ). For the present analysis, the mean Rb is 4.4 for the MRB and 7.25 for the PRB (Table 1 ). The higher Rb value for Pravara suggests it is more affected by structural disturbances than the MRB. 4.7 Weighted Mean Bifurcation Ratio (Rbwm) Strahler ( 1952 ) introduced the Rbwm to provide a more accurate assessment of drainage network branching. This method accounts for the bifurcation ratios between successive stream orders, weighted by the number of streams in each order. Based on this method, the Rbwm values for the MPRBs are calculated as 4.43 and 4.08, respectively, indicating a moderately dissected drainage pattern influenced by geological and geomorphological factors (Tables 1 and 3 ). Table 2 Stream length and stream length ratios of the MPRB Watershed. A) Su Nu Lu Lu/Nu Lur Lur-r Lur*Lur-r Luwm I 8566 4806.0 0.6 1.9 II 1951 1478.3 0.8 1.4 6284.3 8487.3 III 423 880.4 2.1 2.7 2358.8 6479.3 IV 99 425.1 4.3 2.1 1305.5 2693.1 V 20 212.2 10.6 2.5 637.3 1574.7 VI 4 116.1 29.0 2.7 328.3 898.2 VII 1 117.0 117.0 4.0 233.1 939.1 Total 11064 8035.1 164.3 15.4 11147.3 21071.9 Mean 1147.9 2.6 B) Su Nu Lu Lu/Nu Lur Lur-r Lur*Lur-r Luwm I 5387 3428.4 0.6 2.4 II 1318 1153.2 0.9 1.4 4581.7 6299.1 III 339 698.1 2.1 2.4 1851.3 4357.0 IV 89 368.6 4.1 2.0 1066.7 2145.0 V 20 182.4 9.1 2.2 551.0 1213.4 VI 1 169.0 169.0 18.5 351.4 6512.3 Total 7154 5999.71 185.8418 26.4734 8402 20526.81 Mean 1000.0 31.0 5.3 1680.4 4105.4 4.8 Valley Index (Vi) and Channel Index (Ci) Miller ( 1953 ) proposed sinuosity as a measure of the degree of meandering in a river's course. To calculate this, the river channel is divided into segments, and indices are derived from the channel length (Cl), the valley length (Vl), and the straight-line distance from the source to the mouth (Adm). For the Mula Watershed, the Ci is 1.63, and Vi is 0.21. In the Pravara Watershed, the Ci is 1.42, and Vi is 0.10 (Table 3 ). These values suggest that the Mula River has a slightly more sinuous course than the Pravara. 4.9 Rho Coefficient Horton ( 1945 ) defined the Rho coefficient as an essential parameter that links drainage density to the physiographic development of a watershed (Gautam et al. 2020 ; Dimple et al. 2022 ; Gautam et al. 2025 ). It helps assess the storage capacity of the drainage network and the level of drainage development within a watershed. For the Mula Watershed, the Rho value is 3.39, and for the Pravara Watershed, it is 3.65 (Table 3 ). 5. Basin Geometry 5.1 Basin Length (Lb) According to Schumm ( 1956 ), basin length is the longest dimension of a watershed, running parallel to the principal drainage line. This dimension provides insight into the watershed’s extent along its primary drainage course. Gregory and Walling (1973) define basin length as the maximum distance from the basin’s source to its mouth (Gaikwad et al. 2024 ). This length indicates the watershed’s overall extent. In this study, basin lengths for both the MPRB watersheds were determined. The basin length for the Mula Watershed is 121.5 km, while that for the Pravara Watershed is 115.4 km (Table 3 ). 5.2 Basin Area (A) Basin area is essential for understanding a watershed’s shape and size. It helps in analysing hydrological processes, runoff, and water distribution. Schumm ( 1956 ) noted a relationship between a watershed's total area and the total length of its streams, influenced by the contributing areas that feed into the streams. The Mula Watershed covers 2900.6 km 2 while the Pravara Watershed covers 2650.7 km 2 (Table 3 ). 5.3 Basin Perimeter (P) The basin perimeter is the total length of the boundary enclosing the watershed, measured along the dividing line separating it from adjacent watersheds (Pareta and Pareta 2011 ). For the Pravara Watershed, the basin perimeter is 351 km, while for the Mula it is 382.1 km (Table 3 ). 5.4 Length Area Relation (Lar) The length-area relationship in a watershed is a key concept in hydrology that explains the relationship between river or stream length and its corresponding drainage area. This relationship is vital for hydrological modelling, flood forecasting, and watershed management. It helps predict how rivers will respond to changes in land use, climate, and other environmental factors. Hack ( 1957 ) observed that for a large number of basins, the stream length and basin area are related by a simple power function: Lar = 1.4 * A 0.6 . The observed Lar values are 167.5 for the Mula Watershed and 159.22 for the Pravara Watershed (Table 3 ). 5.5 Lemniscate’s (k) Chorley ( 1957 ) formulated the Lemniscate’s value to assess the slope of a basin. The k value is calculated using the formula: k = Lb² / 4 * A, where Lb represents the basin length in km, and A is the basin area in km 2 . For the Mula Watershed, the k value is 5.09, while for the Pravara Watershed, it is 5.03. A higher k value indicates a more elongated basin (Table 3 ). Therefore, the MRB is more elongated than the PRB. 5.6 Form Factor Ratio (Rf) The form factor, as defined by Horton ( 1932 ), helps describe the shape of a watershed. It is the ratio of the basin area to the square of the basin length. The form factor ranges from 0 (for an elongated, straight watershed) to 0.754 (for a circular watershed). Smaller Rf values indicate greater elongation, while larger values suggest a more compact shape. Watersheds with low Rf values typically experience longer-duration, lower peak flows, while those with higher Rf values have shorter-duration, higher peak flows (Pareta and Pareta 2011 ). The Rf value for the MRB is 0.20. For the PRB, it is 0.20, indicating that both basins are elongated. The peak flow characteristics are homogeneous due to their similar geographical features (Table 3 ). 5.7 Elongation Ratio (Re) The elongation ratio (Re), defined by Schumm ( 1956 ), compares the diameter of a circle with the same area as the basin to its maximum length. Strahler categorised this ratio as 0.6-1 across different environments. The Re values for Mula and Pravara are 0.29 and 0.32. This is due to the river’s linear topography, which results in lengths longer than widths. Therefore, both watersheds are highly elongated, which influences their drainage and runoff patterns (Table 3 ). 5.8 Texture Ratio (Rt) Schumm ( 1956 ) demonstrates that the texture ratio (Rt) is a significant parameter in drainage morphometric analysis, as it reflects the influence of underlying lithology, infiltration capacity, and terrain relief. The texture ratio is the ratio of the number of first-order streams (N1) to the basin perimeter (P), expressed as Rt = N1 / P. In the present study, the Rt value for the Mula Watershed is 22.41, indicating a relatively coarse drainage texture. In contrast, the Pravara watershed exhibits a lower Rt value of 13.80, suggesting a finer drainage texture. These variations in texture ratio highlight the geomorphological and lithological differences between the two basins (Table 3 ). 5.9 Circularity Ratio (Rc) Strahler ( 1964 ) and Miller ( 1953 ) introduced the circularity ratio (Rc), a dimensionless parameter used to quantify watershed shape. Rc is the ratio of basin area to the area of a circle with the same perimeter, reflecting lithological characteristics and geomorphic development. Miller ( 1953 ) noted that Rc values between 0.4 and 0.5 indicate elongated basins with permeable, homogeneous geologic materials. Values near 1 suggest circular basins with uniform infiltration, while lower Rc values indicate youthful basins with faster runoff (Strahler, 1964 ). In this study, the Rc values for the MPRBs Watersheds are 0.25 and 0.26, respectively, indicating elongated basin shapes (Table 3 ). 5.10 Drainage Texture (Dt) Horton ( 1945 ) characterised drainage texture (Dt) as the total number of stream segments of all orders per unit perimeter, reflecting the relative spacing of streamlines. It is influenced by lithology, infiltration capacity, and terrain relief. Smith (1950) classified Dt into five categories: very coarse ( 8). In the present study, Dt values for the MPRBs Watersheds are 21.03 and 20.35, respectively, indicating a very fine drainage texture (Table 3 ). 5.11 Compactness Coefficient (Cc) Gravelius ( 1914 ) proposed the compactness coefficient (Cc) to assess the complexity of watershed shape. It is the ratio of the watershed perimeter to the perimeter of a circle with the same area. A Cc value of 1 indicates a perfect circular basin, while values greater than 1 suggest a more elongated and less compact shape. Higher Cc values correspond to longer flow paths and greater runoff, thereby potentially increasing flood susceptibility. In contrast, lower Cc values indicate shorter flow paths and quicker drainage. In the present investigation, the Mula Watershed has a Cc of 2.02, and the Pravara Watershed has a value of 1.98, both indicating moderately elongated shapes (Table 3 ). 5.12 Fitness Ratio (Rf) The fitness ratio (Rf) is the ratio of the main channel length to the watershed perimeter (Melton,1965). The Rf values for the MPRBs Watersheds are 0.51 and 0.49, respectively (Table 3 ). An Rf close to 1 indicates an efficient drainage network, with the main channel length proportionate to the perimeter. Lower Rf values indicate an inefficient channel network that is poorly matched to the watershed shape, potentially reducing drainage efficiency. 5.13 Wandering Ratio (Rw) Smart and Surkan ( 1967 ) introduced the wandering ratio (Rw) to assess the relationship between the main stream length (Cl) and the valley length (Lb). A value close to 1 indicates a straight stream, whereas higher values indicate greater meandering. The Rw values for the MPRBs Watersheds are 1.74 and 1.53, respectively, indicating relatively direct flow paths with limited meandering (Table 3 ). Rw is controlled by factors such as channel gradient, bedrock lithology, tectonic structures, and floodplain geomorphology, which collectively influence channel sinuosity and planform dynamics. 5.14 Watershed Eccentricity (τ) Black ( 1972 ) introduced watershed eccentricity (τ) as a dimensionless parameter that quantifies basin elongation. Higher τ values indicate a more elongated basin, whereas lower values indicate a more circular or compact basin. In the present study, the eccentricity values are 0.95 for the Mula Watershed and 0.97 for the Pravara Watershed, indicating that Pravara is moderately elongate, whereas Mula is relatively more compact (Table 3 ). 5.15 Centre of Gravity of Watershed (Gc) Gc is the length of the channel measured from the outlet of the watershed to a point on the stream nearest to the centre of the watershed (Pareta and Pareta 2011 ). In the present study, Gc was computed using ArcGIS-10.8.2. The Gc point for Mula is at 18˚49’19” N and 74˚02’20” E, and the Gc point for Pravara is at 74˚59’52” E and 15˚13’25” N (Table 3 ). 5.16 Standard Sinuosity Index (Ssi) Sinuosity describes the pattern and degree of curvature in a river channel within a drainage basin. It is expressed as the sinuosity index (Ssi), defined as the ratio of channel length to straight-line valley length. According to Wolman and Miller (1964), rivers with an Ssi of 1.5 are considered sinuous, while values exceeding 1.5 indicate meandering channels. Sinuosity is a vital morphometric parameter in fluvial geomorphology, as it reflects channel behaviour and planform development. The MPRBs Watersheds exhibit Ssi values of 1.76 and 1.42, respectively, indicating that the Mula River follows a more meandering course, whereas the Pravara River shows a relatively straighter alignment (Table 3 ). Therefore, the observed sinuosity may be attributed to variations in valley slope, underlying lithology, structural controls, and sediment load. Hence, these factors significantly influence the degree of meandering and the development of channel patterns in both watersheds. 6. Drainage Texture Analysis 6.1 Stream Frequency (Fs) Stream frequency (Fs), initially defined by Horton ( 1932 ), represents the number of stream segments per unit area and is commonly used to assess the drainage texture of a watershed. For the present analysis, the MPRBs Watersheds exhibit Fs values of 2.5 and 2.62, respectively (Table 3 ). This parameter is primarily influenced by the underlying geology, particularly the permeability and resistance of surface materials. The higher Fs generally correspond to a more closely spaced, well-connected drainage network. The PRB (Fs = 2.62) exhibits a denser drainage network than the MRB (Fs = 2.5), suggesting higher runoff and lower infiltration. 6.2 Drainage Density (Dd) Drainage density (Dd), expressed as stream length per unit area, reflects the degree of dissection and runoff potential in a watershed (Strahler 1964 ). In the present study, Dd was calculated using ArcGIS, yielding 1.92 km/km² for the Mula and 2.1 km/km² for the PRB (Fig. 7 ; Table 3 ). These values suggest a moderately developed drainage network, influenced by homogeneous lithology across both basins. The slightly higher Dd in the PRB indicates steeper slopes and greater runoff potential, whereas the MRB suggests gentler terrain and higher infiltration capacity. 6.3 Constant of Channel Maintenance (C) The constant of channel maintenance (C), introduced by Schumm ( 1956 ), quantifies the relationship between basin size and channel length, indicating the basin area required to maintain a 1-km-long channel. It is used to quantify the efficiency with which a watershed generates and sustains its channels. Schumm focused on the inverse of drainage density, where Strahler related it to landform-unit size. In this study, the C values for the MPRBs watersheds are 0.52 km²/km and 0.48 km²/km, respectively, reflecting the basin area needed to support a 1 km channel (Table 3 ). These values suggest that both watersheds maintain relatively efficient channel networks, with the PRB showing slightly higher efficiency. 6.4 Drainage Intensity (Di) Drainage intensity (Di), defined as the ratio of stream frequency to drainage density, was introduced by Faniran ( 1968 ). The study shows Di values of 1.3 for the Mula and 1.25 for the Pravara watersheds (Table 3 ). These values, along with low Dd and Fs, indicate that surface runoff is not efficiently managed in these watersheds. Consequently, both watersheds may be more prone to flooding, gully erosion, and landslides. 6.5 Infiltration Number (If) According to Faniran ( 1968 ), the infiltration number, calculated as the product of Dd and stream frequency, is a key metric for assessing a watershed’s infiltration characteristics. Higher infiltration numbers typically correspond to lower infiltration capacity and higher surface runoff (Pareta and Pareta 2011 ). The Infiltration Factor (If) values for the MPRBs watersheds are 4.80 and 5.50, respectively (Table 3 ). These values suggest that the Pravara Watershed has a slightly lower infiltration capacity than the Mula Watershed, resulting in greater runoff and reduced groundwater recharge. Understanding these dynamics is crucial for managing water movement, flood risk, and soil erosion in these regions. 6.6 Length of Overland Flow (Lg) Horton ( 1945 ) introduced the concept of length of overland flow (Lg) as the average distance precipitation travels over the land before entering a defined stream channel. It is estimated as half the reciprocal of drainage density and is a key indicator of surface runoff efficiency. In the present study, Lg values are 0.22 km for the Mula and 0.24 km for the Pravara watersheds (Table 3 ). The shorter Lg in the MRB suggests a quicker response to rainfall and more immediate runoff generation. In comparison, the slightly longer Lg in the PRB may indicate a more delayed runoff response. These values are crucial in assessing runoff potential, infiltration capacity, and flood risk. 7. Relief Characteristics 7.1 Relief Ratio (Rhl) Total relief represents the elevation difference between the highest and lowest points in a watershed. Schumm ( 1956 ) introduced the relief ratio (Rhl), calculated as the total relief divided by the maximum basin length parallel to the main drainage line. This metric reflects the overall steepness and erosional potential of a basin, often correlating with runoff intensity and sediment yield. In the current study, Rhl values are 5.22 for the Mula and 5.38 for the Pravara Watershed, indicating that both basins exhibit moderate relief, with the PRB having slightly higher erosional potential. 7.2 Absolute Relief (Ra) Absolute relief refers to the elevation of a location above sea level and reflects the vertical extent of terrain within a watershed (Strahler 1964 ). In this study, the Mula Watershed exhibits an absolute relief of 1410 m, while the Pravara Watershed shows a slightly higher value of 1420 m. These elevations indicate that the PRB lies at a generally higher altitude, potentially influencing climatic conditions, runoff characteristics, and erosion dynamics more prominently than the MRB (Fig. 8 ). 7.3 Dissection Index (Dis) The dissection index (Dis), introduced by Nir ( 1957 ), measures the extent of vertical erosion in a landscape. It helps to understand how deeply rivers and streams have cut into a region. Dis values range from 0 to 1, with values near 0 indicating flat terrain and values near 1 indicating steep, highly eroded landscapes (Singh and Dubey 1994 ). In this study, both the MPRB watersheds exhibit a Dis value of 0.67, indicating that the region is moderately dissected, with a plateau landscape undergoing gradual erosion. This indicates that both watersheds are in a mature stage of geomorphic evolution, with balanced erosion and deposition processes shaping the terrain (Fig. 9 ; Table 3 ). 7.4 Gradient Ratio (Rg) The gradient ratio (Rg) is a useful indicator of channel slope and helps assess runoff characteristics within a watershed (Sreedevi et al. 2005 ). In this study, the Rg values are 5.22 for the Mula Watershed and 5.38 for the Pravara Watershed, suggesting slightly steeper channel gradients in the PRB. This implies that runoff is likely to be faster in the PRB, leading to greater erosion potential, whereas the MRB may experience more moderate flow and improved infiltration. 7.5 Ruggedness Number (Rn) Strahler ( 1964 ) defined the ruggedness number (Rn) as the product of basin relief and drainage density, indicating terrain complexity and erosion potential. In this study, Rn values of 1.94 for Mula and 2.01 for Pravara suggest that Pravara is slightly more susceptible to erosion and runoff due to its higher ruggedness (Table 3 ). 7.6 Melton Ruggedness Number (MRn) Melton ( 1965 ) defined the Ruggedness Number (MRn) as a slope-based index that represents the relief ruggedness of a watershed. In this study, MRn values are 28.56 for Mula and 28.99 for Pravara, reflecting high relief variation and rugged terrain in both watersheds. The slightly higher MRn in the PRB suggests a more dissected, steeper landscape, indicating greater geomorphic activity and erosion susceptibility than the Mula Watershed (Table 3 ) 7.7 Average Slope (S) Wentworth ( 1930 ) proposed that the erodibility of a watershed can be evaluated based on its average slope. The formula for calculating the average slope is: S = (Z * (Ctl / H)) / (10 * A) where Z is the Maximum Height of the basin, Ctl is the Total Contour Length, H represents the total basin relief, and A is the area of the watershed. In the Mula Watershed, the average slope is 5.75%, whereas in the Pravara Watershed it is 4.56%. These values indicate that Mula has a slightly steeper average slope, suggesting greater susceptibility to erosion than Pravara (Fig. 10 ). In conclusion, the Mula Watershed's steeper slopes suggest a higher rate of surface runoff and increased erosion potential. In contrast, the Pravara Watershed, with its gentler slopes, may experience relatively lower erosion rates. Table 3 Morphometric parameters and corresponding formulae considered in this study Sr No. Parameter Formula Result References Mula Pravara A. Linear Aspect 1 Stream order (Su) Hierarchical Rank 1 to 7 1 to 6 Strahler ( 1952 ) 2 1st Order Stream (Suf) Suf=N1 8566 5387.00 Strahler ( 1952 ) 3 Stream Number (Nu) Nu=N1 + N2+….Nn 11064 6919 Hortan (1945) 4 Stream Length (Lu) km Lu=L1 + L2+….Ln 8035.10 6000 Strahler ( 1964 ) 5 Mean Stream Length (Lurm) 1147.90 1000.00 Strahler ( 1964 ) 6 Stream Length Ratio (Lur) 15.39 26.47 Hortan (1945) 7 Mean Stream Length Ratio (Lurm) 2.57 5.30 Hortan (1945) 8 Weighted Mean Stream Length Ratio (Lurwm) 1.90 2.40 Strahler ( 1964 ) 9 Bifurcation Ratio (Rb) 4.3 to 5 3.81 to 20 Strahler ( 1964 ) 10 Mean Bifurcation ratio (Rbm) 4.54 7.25 Strahler (1953) 11 Weighted Mean Bifurcation Ratio (Rbwm) 4.43 4.08 Strahler (1953) 12 Main channel Length (Cl) km GIS Software Analysis 210.90 177.14 - 13 Valley Length (Vl) km GIS Software Analysis 24.58 11.86 - 14 Minimum Aerial Distance (Adm) km GIS Software Analysis 119.06 124.62 - 15 Channel Index (Ci) Ci = Cl / Adm 1.63 1.42 Miller (1968) 16 Valley Index (Vi) Vi = Vl / Adm 0.21 0.10 Miller (1968) 17 Rho Coefficient (p) p = Lur / Rb 3.39 3.65 Horton ( 1945 ) B. Aerial Aspect 18 Length from W's Centre to Mouth of W's (Lcm) km GIS Software Analysis 62.74 62.32 Black ( 1972 ) 19 Width of W's at Centre of Mass (Wcm) km GIS Software Analysis 17.94 14.39 Black ( 1972 ) 20 Basin Length (Lb) km Lb = 1.312×A0.568 121.5 115.4 Sreedevi et al. ( 2005 ) 21 Mean Basin Width (Wb) Wb = A / Lb 13.75 14.96 Horton ( 1932 ) 22 Basin Area (A) km² GIS Software Analysis 2900.6 2650.7 Schumm ( 1956 ) 23 Basin Perimeter (P) km GIS Software Analysis 382.1 359.0 Schumm ( 1956 ) 24 Relative Perimeter (Pr) Pr = A / P 7.59 7.38 Schumm ( 1956 ) 25 Length Area Relation (Lar) Lar = 1.4 * A^0.6 167.34 159.22 Hack ( 1957 ) 26 Lemniscate's (k) k = Lb² /A 15.33 11.83 Chorley ( 1957 ) 27 Form Factor Ratio (Rf) Rf = A / Lb² 0.07 0.08 Horton ( 1932 ) 28 Shape Factor Ratio (Rs) Sf = Lb² / A 15.33 11.83 Horton ( 1932 ) 29 Elongation Ratio (Re) Re = 2 / Lb * (A / π)^0.5 0.29 0.32 Schumm ( 1956 ) 30 Elipticity Index (Ie) Ie = π * Vl² / 4 A 0.16 0.04 Schumm ( 1956 ) 31 Texture Ratio (Rt) Rt= N1 / P 22.41 13.80 Schumm ( 1956 ) 32 Circularity Ratio (Rc) Rc = 12.57 * (A / P² ) 0.25 0.26 Miller ( 1953 ) 33 Circularity Ration (Rcn) Rcn = A / P 7.59 7.38 Strahler ( 1964 ) 34 Drainage Texture (Dt) Dt = Nu / P 28.95 19.92 Horton ( 1945 ) 35 Compactness Coefficient (Cc) Cc = 0.2841 * P / A^0.5 2.02 1.98 Gravelius ( 1914 ) 36 Fitness Ratio (Rf) Rf = Cl / P 0.51 0.49 Melton (1957) 37 Wandering Ratio (Rw) Rw = Cl / Lb 1.00 1.00 Smart and Sukan (1967) 38 Watershed Eccentricity (e) 0.95 0.97 Black ( 1972 ) 39 Centre of Gravity of Watershed (Gc) GIS Software Analysis 74°02'20'' E 74°59'52'' E Rao (1998) 18°49'19'' N 15°13'25'' N 40 Hydraulic Sinuosity Index (Hsi) % Hsi = ((Ci -Vi)/(Ci − 1))*100 52.8 39.14 Mueller ( 1968 ) 41 Standard Sinuosity Index (Ssi) Ssi = Ci / Vi 1.52 1.39 Mueller ( 1968 ) C. Relief Aspect 42 Stream Frequency (Fs) Fs = Nu / A 3.81 2.70 Horton ( 1932 ) 43 Drainage Density (Dd) km/km ² Dd = Lu / A 2.77 2.26 Horton ( 1932 ) 44 Constant of Channel Maintenance C km/km² C = 1 / Dd 0.36 0.44 Schumm ( 1956 ) 45 Drainage Intensity (Di) Di = Fs / Dd 1.38 1.19 Faniran ( 1968 ) 46 Infiltration Number (If) If = Fs * Dd 10.55 6.10 Faniran ( 1968 ) 47 Length of Overland Flow (Lg) Km Lg = A / 2 * Lu 0.18 0.19 Horton ( 1945 ) 48 Height of the Basin Mouth (z) m GIS Analysis / DEM 405.00 405.00 - 49 Maximum Height of the Basin (Z) m GIS Analysis / DEM 1414.00 1424.00 - 50 Total Basin Relief (H) m H = Z - z 1009.00 1019.00 Strahler ( 1952 ) 51 Relief Ratio (Rhl) Rhl = H / Lb 4.78 5.75 Schumm ( 1956 ) 52 Absolute Relief (Ra) m GIS Software Analysis 1414.00 1424.00 - 53 Relative Relief Ratio (Rhp) Rhp = H * 100 / P 0.26 0.28 Melton (1957) 54 Dissection Index (Dis) Dis = H / Ra 0.71 0.72 Singh and Dubey ( 1994 ) 55 Gradient Ratio (Rg) Rg=(Z -z) / Lb 4.78 5.75 Sreedevi (2004) 56 Watershed Slope (Sw) Sw = H / Lb 4.78 5.75 - 57 Ruggedness Number (Rn) Rn = Dd * (H / 1000) 2.79 2.30 Strahler ( 1964 ) 58 Melton Ruggedness Number (MRn) MRn = H / A^0.5 0.59 18.58 Melton ( 1965 ) 59 Total Contour Length (Ctl) km GIS Software Analysis 17159.47 13814.00 - 60 Contour Interval (Cin) m GIS Software Analysis 20.00 20.00 - 61 Length of Two Successive Contours (L1 + L2) km GIS Software Analysis 1585.06 970.61 Strahler ( 1952 ) 62 Average Slope Width of Contour (Swc) Swc = A / {(L1 + L2) / 2} 3.67 5.44 Strahler ( 1952 ) 63 Average Slope (S) Degree S=(Z * (Ctl / H)) / (10 * A) 5.17 4.56 Wenthworth’s (1930) 64 Mean Slope of Overall basin (Ѳs) Ѳs=(Ctl * Cin) / A 0.86 0.78 Wenthworth’s (1930) 7.8 Longitudinal Profile The Pravara River, about 180 km long, exhibits a concave longitudinal profile (Fig. 11 a) that descends from nearly 950 to 420 m, shaped by differential erosion, tectonics, and lithological controls (Leopold and Maddock 1953 ; Schumm 1977 ). In the upper course from 0 to 20 km, a steep gradient of 12.5 m/km drives vertical erosion, with a major knick point at Randha fall around 15 km, marked by a 60 m drop, indicating structural or lithological influence (Fig. 11 b) (Castillo et al. 2013 ). The middle course, spanning 20 to 100 km, features a moderate gradient of approximately 2.25 m/km, dominated by lateral erosion and sediment transport; the Randha fall nick point suggests geomorphic disequilibrium, likely due to resistant Deccan basalt or a change in base level (Hack 1957 ; Wobus et al. 2006 ). In the lower course, from 100 to 180 km, a gentle gradient of approximately 1 m/km promotes meandering and sediment deposition, with high sinuosity indicative of an old-age river nearing its base level (Mackin 1948 ; Whipple and Tucker 1999 ). The Mula River’s longitudinal profile spans about 210 km, descending from approximately 900 to 400 m (Fig. 11 e) (Hooke 2003). In the first 20 km, the river flows steeply through the Western Ghat, exhibiting intense vertical erosion (Montgomery and Buffington 1997 ). The Pachnai Waterfall, located between 10 and 15 km, marks a sharp drop due to resistant geological structures as shown in Fig. 11 c (Leopold et al. 2020 ). From 20 to 140 km, the river enters a gentler middle course, with elevation decreasing from 800 to 500 m. This stage is characterised by lateral erosion, broader valleys, and developing floodplains that support agriculture (Bridge 2003 ; Schumm 1977 ). At about 160 km, the Mula Dam introduces a sudden break in slope, altering sediment flow and channel form (Petts and Gurnell 2005 ). Beyond the dam, from 160 to 210 km, the river gently descends to around 420 m, showing increased deposition. The profile reflects the natural progression of fluvial processes from headwaters to mouth, shaped by topography, gradient, and geological structure (Tooth 2000 ). 7.9 Hypsometric Curve Hypsometric analysis is a fundamental geomorphic technique for quantifying watershed development and erosional status (Strahler 1952 ). The hypsometric integral (HI) values of 0.29 for the Pravara River and 0.26 for the Mula River (Fig. 12 a, b) indicate that both basins are in a mature stage of fluvial evolution. Their distinctly concave hypsometric curves reflect extensive surface lowering and slope retreat, characteristic of advanced landscape dissection and reduced relief (Moglen and Bras 1995). This suggests that the basins are approaching geomorphic equilibrium, with reduced potential for vertical incision. Google Earth imagery (Fig. 12 c) further supports this interpretation, showing clear evidence of well-developed meanders and lateral channel migration—features typical of rivers with low gradients and diminished stream power (Schumm 1977 ). The presence of tight meanders in the middle reaches (Fig. 12 c), along with broader channels near the Mula-Pravara confluence, indicates a shift from erosional dominance to greater sediment deposition. In this context, Leopold and Wolman (1957) emphasise that low-gradient rivers tend to form meanders due to sediment deposition and flow characteristics, while Smith et al. (2019) explore the influence of channel migration and sediment transport, further supporting the observed features. These hypsometric and morphological features indicate that the river system is approaching a later stage, in which deposition predominates over erosion. This change reflects lower stream energy and balance with the base level. 8. Discussion This study demonstrates the effectiveness of GIS-based morphometric analysis using SRTM-DEM data by quantifying more than 60 parameters to evaluate watershed characteristics. The results reveal significant variation in hydrological behaviour among the MPRBs. The quantitative morphometric analysis is fundamentally based on the relationships between drainage network patterns and morphometric patterns, including linear, aerial, and basin attributes, which help to understand watershed dynamics and hydrological responses (Fenta et al. 2017 ). The nature of the drainage network in each watershed is influenced by variations in physiographic and climatic conditions. The morphometric parameters also vary accordingly (Erosemiah and Viji 2023 ). This research focused on analysing the main morphometric parameters of MPRBs observed in the 7th - and 6th -order streams of the watershed (Krishnan and Arjun 2024 ). Higher-order stream basins exhibit a more developed, integrated drainage system with numerous tributaries and sub-tributaries, resulting in increased discharge and runoff (Godsey and Kirchner 2014 ; Das and Pardeshi 2018). Figure 6 (A; B) indicates the relationship between stream order, stream number, and mean stream length. As the stream order increases, the number of streams decreases, while the mean stream length increases (Downing et al. 2012 ). In the present study, the relationship between stream number and stream length is illustrated in Fig. 6 A. The plot shows an approximately linear trend, indicating a strong positive correlation between the two parameters. A strong relationship exists between stream order and basin area, as the basin area increases, stream order tends to increase. Since the basin area of MRB is greater than that of PRB, higher stream orders are observed in MRB. Rb is considered an essential parameter in morphometric analysis, as it shows the structural control over the drainage network (Waikar and Nilawar 2014 ). According to previous studies, the mean bifurcation ratio (Rbm) can fluctuate even in the absence of geological control, but generally ranges from 3 to 5 (Anish et al. 2021 ; Mohammed et al. 2025 ). In this study, the mean bifurcation ratio of MRB is 7.2, whereas that of PRB is 4.5. The higher value in the Mula watershed indicates stronger structural control over the drainage network, whereas the Pravara watershed reflects a more natural, less structurally influenced drainage development (Choudhari et al . 2021). According to Nag ( 1998 ), the drainage network pattern and surface runoff intensity are directly influenced by the lithology, climatic characteristics, geological activities, and geomorphic history of the drainage basin. Dd is an essential areal parameter that depends primarily on lithological characteristics, slope, soil permeability, and weathering (Mahala 2020 ; Wang et al. 2024). In regions where rigid, compact lithologies such as granite, gneiss, and schist are found, Dd is typically low (Sufyan et al. 2024 ; Subramaniyan 2026 ). The MPRBs in this study are primarily underlain by basaltic rocks, and the lithology of both watersheds is relatively similar. So, the distribution of Dd in this area also shows a uniform trend. According to the results, the Dd for the Mula watershed is 2.77, and for the Pravara watershed, it is 2.26. The drainage density is relatively higher in the lower catchments of both river basins (Fig. 6 ) (Lin et al. 2021 ). Loose and alluvial deposits in these areas indicate a higher potential for erosion (Sampath and Radhakrishnan 2024 ). On the contrary, areas with low drainage density indicate good subsurface permeability and filtration capacity of the soil. According to Kumar et al. ( 2015 ), the relationships among Dd, surface runoff, and lithology were explained. Similarly, Magesh and Chandrasekar (2014) have explained that Dd is an indicator of subsurface material permeability in the Western Ghat region. Thus, analysis of drainage density in the MPRBs is useful for understanding the lithology, geomorphological processes, and hydrological response of the area. According to numerous researchers worldwide, Circularity Ratio and Elongation Ratio are considered significant morphometric indices for determining the size and shape of a drainage basin (Waikar and Nilawar 2014 ; Bogale 2021 ; Das et al. 2022 ; Tassew et al. 2023 ; Ocheri et al. 2025 ). If the values of these indices are close to 0, it indicates that the respective basin is elongated (Moussa 2003 ; Rudraiah 2008; Sharma and Sarma 2017 ). On the contrary, if the value of the indices is close to one (1), then the shape of that watershed is circular (Adhikari 2020 ; Asfaw and Workineh 2019 ). Therefore, by evaluating the morphology of a basin based on circularity and elongation ratio, its hydrological and geomorphic characteristics can be effectively assessed. In addition to analysing the drainage network, this research also evaluated relief parameters in detail (Cazorzi et al. 2013 ; Al-Saady et al. 2016 ). Relief parameters are influenced by the combined effects of climate, lithology, and tectonic setting in understanding landform development and landscape evolution (Zheng et al. 2025 ; Singh et al . 2025 ). Such analysis can serve as a guide for future water resource management and environmental planning. Rainfall in a region plays an important role in shaping the streamflow, groundwater recharge, and geomorphic characteristics (Yan et al. 2025 ). Several studies indicate that the Western Ghat region underwent periodic uplift from the Middle Mesozoic to the Cenozoic era (Rajkumar et al . 2017; R Mohamed 2019; Padmalal et al. 2021 ; Scaria 2023). This mountain range acts as a natural barrier to the southwest monsoon winds, resulting in heavy orographic rainfall in the region. Consequently, rainfall is the primary water source for the MPRBs, with high stream flow during the monsoon season and reduced or seasonal flow during the dry period (Gunnel 1998; Das and Pardeshi 2018a ). Both the river basins have a significant presence of dykes, fault lines, and lineaments. These structures create favourable conditions for the infiltration of surface water into the subsurface layers. However, permeability is limited to some extent by the region’s predominantly basaltic lithology. As a result, there are limitations to groundwater storage capacity and potential (Doke et al. 2021 ; Birajdar and Shaikh 2024 ). On the contrary, in areas where alluvial deposits are found in large quantities, the infiltration capacity of the soil is relatively high. Such alluvial areas are mainly found in the lower reaches of rivers (Dobrovol’ski et al. 2011 ; Kamali and Haghighi 2025 ). The narrow, sloping Western Ghat mountain range lies in the western part of both basins. This area is the source region of both the river basins. In contrast, the eastern part of the basin is mainly known as the Plateau region, which is characterised by a scattered pattern of dissected hills and slopes. In this plateau region, mechanical weathering processes are active and strongly influenced by heat, wind, and precipitation (Ye et al . 2025; Zeng et al . 2025). At the same time, slope processes, especially hill-slope and denudational processes, are occurring rapidly. Since the action of these processes is constantly changing in space and time, and based on hypsometric curve analysis, both river systems are in the old-to-mature stage (Fig. 12 a, b) (Ayalew and Yamagishi 2004 ; Timalsina 2021; Mandal et al . 2025). Therefore, analysing relief parameters in the MPRBs is important for understanding the landscape evolution of this region by clarifying the interrelationships among climate, lithology, structural control, and geomorphic processes. 9. Conclusions Remote sensing and GIS technologies have emerged as powerful and reliable tools for geospatial and geomorphological analysis. The application of DEM has significantly enhanced the accuracy, reliability, and efficiency of watershed studies. Compared with conventional methods, these modern techniques provide a comprehensive framework for morphometric analysis in less time. Because river systems are widely distributed across the globe, except in polar and high-latitude regions, morphometric evaluation plays a significant role in effective watershed management and hydrological planning. The present study focuses on the morphometric analysis of the MPRBs of Maharashtra, India. The analysis reveals that the Mula River has a 7th-order drainage system, whereas the Pravara River has a 6th-order drainage system. The areal extent of the MRB is approximately 2900.6 km², whereas the PRB is about 2650.7 km². The dendritic drainage pattern observed in the study area reflects a relatively homogeneous geological structure and minimal structural control over channel development. A comparative evaluation of the bifurcation ratio indicates higher values in the PRB, reflecting a greater influence of structural disturbances than in the MRB. Drainage density values are generally low, indicating the presence of hard-rock lithology with low permeability. However, the relatively higher drainage density in the PRB indicates steeper slopes and greater surface runoff, whereas the gentler slope of the MRB exhibits greater infiltration capacity. Evaluation of areal parameters, such as form factor, circularity ratio, and elongation ratio, confirms that the basins are elongated. These morphological characteristics indicate lower peak discharge during floods and promote more effective infiltration. Furthermore, stream frequency and drainage texture analyses indicate a coarse drainage network with sparse vegetation cover under semi-arid climatic conditions. Despite this similarity, the PRBs drainage network is comparatively denser, reflecting variations in slope and runoff response. Relief-based parameters indicate that the terrain exhibits a moderate gradient, consistent with a moderately active erosional regime. The wandering ratio and sinuosity index indicate a moderate degree of channel meandering, reflecting a balance between lateral erosion and deposition. Moreover, the dissection index and hypsometric analysis indicate that the river systems have reached a mature-to-old geomorphic stage, characterised by reduced relief, slower surface runoff, and greater dominance of depositional processes. This stage represents an advanced phase in basin evolution. Overall, the morphometric assessment results indicate a valuable interplay among climate, lithology, geomorphology, and tectonic controls governing basin development. The present study provides a scientific basis for future watershed management strategies, water conservation planning, and sustainable development initiatives within the study area. Declarations Ethics consent to participate and not consent to publish declaration Not applicable Conflict of interest statement: The authors reported no potential conflict of interest. Funding Declaration: This research received no external funding. Author Contribution Mr. Vinod Gaikwad: Conceptualization, methodology, data curation, formal analysis, investigation, writing – original draft preparation.Dr. Sanjay Navale: Supervision, validation, methodology refinement, critical review and editing of the manuscript.Ms. Ashwini Jadhav: Data collection, data curation, visualization, literature review, and assistance in manuscript preparation.Dr. Vasudev Salunke: Project administration, supervision, resources, and final review and approval of the manuscript.All authors have read and approved the final version of the manuscript. Acknowledgement The authors sincerely thank Prof. Attila Ciner, Founding Editor-in-Chief of Mediterranean Geoscience Reviews, for his valuable guidance, constructive suggestions, and support that helped improve the quality of this manuscript. 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Int J Earth Sci 114(2):333–345. https://doi.org/10.1007/s00531-024-02487-7 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9093116","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":605014852,"identity":"84b2efe9-4d7a-4267-be99-5d975e2e9338","order_by":0,"name":"Vinod Gaikwad","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIiWNgGAWjYFACxmYgwczABiSlf/DYyIHEDjwgWguDTJoxWEsCfmuYoRikxeZwYgOIhU+LvPvhZmOeGuvEPunmg7cLcg6nzw87/BBoi52cbgN2LYZnEpuTeY6lJ7bJHEu2nnEmPXfj7TQDoJZkY7MDOLQ0JDYfzmE7bMwmkWMmwdtjnbtxdgJIy4HEbbi09D8EavkH0/KPOd1wdvoHvFrkJYAOy207LAfSIs3D45wgL52D3xYDiYfNxn/70oFa0pItZ/CkGW6Qzik4kGCA2y/y/emPJWd8s+aRn5F88MYHHht5+dnpmz98qLCTw6XFAEMcImKAXTnYlgbCIqNgFIyCUTDSAQCDFl/aVTnK4AAAAABJRU5ErkJggg==","orcid":"","institution":"Sangamner Nagarpalika Arts, Damodar Jagananath Malpani Commerce, and Bastiram. Narayan Sarda Science College (Autonomous)","correspondingAuthor":true,"prefix":"","firstName":"Vinod","middleName":"","lastName":"Gaikwad","suffix":""},{"id":605014856,"identity":"3f0edfce-2b32-42c3-abe8-0a375c2f020e","order_by":1,"name":"Sanjay Navale","email":"","orcid":"","institution":"Sangamner Nagarpalika Arts, Damodar Jagananath Malpani Commerce, and Bastiram. Narayan Sarda Science College (Autonomous)","correspondingAuthor":false,"prefix":"","firstName":"Sanjay","middleName":"","lastName":"Navale","suffix":""},{"id":605014858,"identity":"97f2ef61-4074-440f-89dd-9d50f506c909","order_by":2,"name":"Ashwini Jadhav","email":"","orcid":"","institution":"Sangamner Nagarpalika Arts, Damodar Jagananath Malpani Commerce, and Bastiram. Narayan Sarda Science College (Autonomous)","correspondingAuthor":false,"prefix":"","firstName":"Ashwini","middleName":"","lastName":"Jadhav","suffix":""},{"id":605014860,"identity":"bbef3640-8a98-413d-a1d7-8221b821997d","order_by":3,"name":"Vasudev Salunke","email":"","orcid":"","institution":"Karamshibhai Jethabhai Somaiya College of Arts, Commerce and Science Mohnirajnagar","correspondingAuthor":false,"prefix":"","firstName":"Vasudev","middleName":"","lastName":"Salunke","suffix":""}],"badges":[],"createdAt":"2026-03-11 10:25:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9093116/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9093116/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105441198,"identity":"1030a811-1e60-4523-8a1e-af8339eaeff2","added_by":"auto","created_at":"2026-03-26 05:56:49","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":495818,"visible":true,"origin":"","legend":"\u003cp\u003eLocation map of the study area Mula-Pravara River Basin\u003c/p\u003e","description":"","filename":"image1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9093116/v1/dd8aca5eba2bbcce8ce2bc4d.jpeg"},{"id":105441190,"identity":"7be3b5ca-38f5-40d0-ad42-9496ce7ad590","added_by":"auto","created_at":"2026-03-26 05:56:46","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":284339,"visible":true,"origin":"","legend":"\u003cp\u003eGeomorphology map of MPRB\u003csub\u003eS\u003c/sub\u003e\u003c/p\u003e","description":"","filename":"image2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9093116/v1/472ecbbb472dcc005d42351d.jpeg"},{"id":105441182,"identity":"50da9958-36f9-4443-8585-30c5e3d7499f","added_by":"auto","created_at":"2026-03-26 05:56:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":26342,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly rainfall distribution of the study area.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9093116/v1/5eb4ef5434c7f3c7d07bb6cc.png"},{"id":105441201,"identity":"ca207795-7815-43a8-a8d9-7333d4124634","added_by":"auto","created_at":"2026-03-26 05:56:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":437206,"visible":true,"origin":"","legend":"\u003cp\u003eMethodology flowchart to prepare morphometric analysis of MPRBs\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9093116/v1/a0263036b20363cd05e5d073.png"},{"id":105441186,"identity":"09484c62-679c-4c13-bd9f-69877c474682","added_by":"auto","created_at":"2026-03-26 05:56:46","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":427149,"visible":true,"origin":"","legend":"\u003cp\u003eThe stream order and drainage of the MPRBs watershed.\u003c/p\u003e","description":"","filename":"image5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9093116/v1/dfd08f90f5f6a82202c1ffd2.jpeg"},{"id":105441196,"identity":"9e5a7266-b303-4d51-b02b-a68cbc07b796","added_by":"auto","created_at":"2026-03-26 05:56:49","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":41705,"visible":true,"origin":"","legend":"\u003cp\u003e(A) The relationship between stream order and stream number. (B) stream order and mean stream length.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-9093116/v1/71104871a5487e18c8dadcb8.png"},{"id":105441202,"identity":"7f3f43e9-ce36-435a-b04b-82cb160d094c","added_by":"auto","created_at":"2026-03-26 05:56:50","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":386626,"visible":true,"origin":"","legend":"\u003cp\u003eDrainage density maps of Mula-Pravara River basins.\u003c/p\u003e","description":"","filename":"image7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9093116/v1/055916004655f74fe80353b8.jpeg"},{"id":105441192,"identity":"de04d4f2-6d7b-4d1f-a6ac-0b7ad62a6c98","added_by":"auto","created_at":"2026-03-26 05:56:46","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":285645,"visible":true,"origin":"","legend":"\u003cp\u003eAbsolute relief maps for MPRBs.\u003c/p\u003e","description":"","filename":"image8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9093116/v1/88142e61b9fe2827365d220c.jpeg"},{"id":105441183,"identity":"b27df70a-c125-4af3-81fa-beece6646041","added_by":"auto","created_at":"2026-03-26 05:56:46","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":401137,"visible":true,"origin":"","legend":"\u003cp\u003eDissection index maps for MPRBs.\u003c/p\u003e","description":"","filename":"image9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9093116/v1/3227d416b359838caac2914a.jpeg"},{"id":105441191,"identity":"293c06f6-285b-42b7-8052-b690895b53f4","added_by":"auto","created_at":"2026-03-26 05:56:46","extension":"jpeg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":395634,"visible":true,"origin":"","legend":"\u003cp\u003eSlope maps for MPRBs.\u003c/p\u003e","description":"","filename":"image10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9093116/v1/89479028b70c7175d858681e.jpeg"},{"id":105441193,"identity":"15fff5e3-ffb0-43cf-92d2-1d82110cbd6c","added_by":"auto","created_at":"2026-03-26 05:56:47","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":1667893,"visible":true,"origin":"","legend":"\u003cp\u003eThe longitudinal profiles of the Mula River (e), 210 km long, and the Pravara River (a), 177 km long, were created using software by extracting elevation data at 100 m intervals through SRTM. Prominent features like the \u003cem\u003eRandha \u003c/em\u003eWaterfall (b) in the Pravara and the \u003cem\u003ePachnai \u003c/em\u003eWaterfall (c) in the Mula are clearly visible. Both rivers merge at \u003cem\u003eSangameshwar\u003c/em\u003e (d) in Rahuri taluka, where the channel broadens, forming extensive floodplains that are gently sloping.\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-9093116/v1/121423ea9a427224e32d5d2d.png"},{"id":105441194,"identity":"0a444512-fe90-4721-99df-6e0804e031b1","added_by":"auto","created_at":"2026-03-26 05:56:47","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":3631043,"visible":true,"origin":"","legend":"\u003cp\u003eHypsometric integral curves show the stages of PRB (a) and MRB (b, c) White rectangles delineate the prominent meander loops in both river channels\u003c/p\u003e","description":"","filename":"image12.png","url":"https://assets-eu.researchsquare.com/files/rs-9093116/v1/af95af6c66108c4222dc5183.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Morphometric Signature and Geomorphic Attributes of the Mula and Pravara River Basins (Maharashtra, India)","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eA watershed is an area where all water flows to a single common outlet. It serves as a basic hydrological unit that directs surface runoff into a stream network (Swallow et al. \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Johnson et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Gaikwad and Bhagat \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Meierdiercks et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Since a watershed collects runoff to a single outlet, studying it as a whole is more effective than analysing individual channels or small segments (Altaf et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Rivers are sensitive features of the landscape, and their long-term changes reflect fluvial systems under different climates, rock types, and tectonic conditions (Nile \u003cem\u003eet al\u003c/em\u003e. 2025). Morphometric analysis is a key research method for understanding hydrologic and geomorphic processes in river basins (Kale et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Das and Pardeshi 2018; Gaikwad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Memon et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Additionally, a watershed is a natural system encompassing soil, water, and vegetation, and it also influences social, economic, and cultural aspects (Ghanbarpour and Hipel \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). It involves measuring key parameters, including drainage density, bifurcation ratio, watershed slope, channel length, and relief (Javed \u003cem\u003eet al\u003c/em\u003e. 2011; Thomas et al. \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Vieceli \u003cem\u003eet al\u003c/em\u003e. 2015; Rai \u003cem\u003eet al\u003c/em\u003e. 2017). Additionally, morphometric analysis plays a crucial role in geological mapping and hazard assessments, including flood and landslide susceptibility (Kale and Rajaguru \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). Rivers also record landscape changes over time, with longitudinal profiles reflecting faulting, tectonic activity, and landform evolution. This analysis enhances geological understanding and complements traditional morphometric methods (Das et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kudnar \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Gaikwad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Hence, past land changes can be understood by analysing these variables through a morphometric study.\u003c/p\u003e \u003cp\u003eThe morphometric analysis is a fundamental approach to drainage quantification and has been widely applied in surface geology studies (Horton \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1932\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1945\u003c/span\u003e; Strahler \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e1957\u003c/span\u003e, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e; Schumm \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e; Gregory \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1966\u003c/span\u003e; Manu and Anirudhan \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Sreedevi et al. \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Thomas et al. \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Dusan \u003cem\u003eet al\u003c/em\u003e. 2017; Kumar et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Das and Pardeshi 2018; Mohammed \u003cem\u003eet al\u003c/em\u003e.2025). It plays a crucial role in examining drainage patterns, terrain deformation, and structural changes over time (Kale and Rajaguru \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Moussa \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Mesa \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Recent studies define morphometric analysis as the measurement and assessment of linear, aerial, and elevation features of the land surface, including shape and dimensions. With advancements in GIS and DEMs, hydrological and geomorphological studies now achieve greater accuracy and efficiency. DEMs provide high-resolution elevation data, enhancing the analysis of drainage patterns and terrain morphology. These technologies have become essential tools for modern geomorphic research, enabling precise spatial analysis and modelling of landform evolution and geological structures (Singh and Singh \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Sreedevi et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Iqbal and Sajjad \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Raja and Karibasappa 2016; Gaikwad and Bhagat \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Das et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kudnar \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Gaikwad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Additionally, the use of RS data within a GIS environment significantly enhances the precision of morphometric and morphotectonic studies, making it a consistent approach for watershed assessment, particularly in regions with few ground-truth sites for validation (Gaikwad \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Gaikwad et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the past, morphometric analysis relied on traditional methods such as topographic sheets and field surveys. Today, RS and GIS technologies, especially the use of DEMs, have made this process faster, more accurate, and widely applicable for studying watershed and morphotectonic features. These tools significantly enhance spatial data analysis for effective basin evaluation (Kudnar and Rajashekhar 2020; Pigazzi et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Gaikwad et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2026\u003c/span\u003e). This study applies morphometric analysis to investigate the geomorphic characteristics of the MPRBs, focusing on drainage patterns, basin shape, and landform features. To better understand the influence of tectonic and structural forces on landscape development, longitudinal profiles of the PRB and MRB were examined as well. The GIS and DEMs have significantly advanced hydrology and geomorphology by providing accurate and accessible spatial data, making them indispensable for analysing landforms, drainage networks, and geological structures (Al-Saady et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Das \u003cem\u003eet al\u003c/em\u003e. 2017a; Das and Pardeshi \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003eb\u003c/span\u003e; Gaikwad et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Pigazzi et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTherefore, the present study aims to analyse the morphometric characteristics of the MPRBs using GIS and remote sensing to understand landform evolution and assess the influence of tectonic processes.\u003c/p\u003e"},{"header":"2. Study Area","content":"\u003cp\u003eThe MPRBs are located in the eastern region of the Western Ghat, within the Ahilyanagar district of Maharashtra, India, and cover approximately 2,637 km\u0026sup2;. Geographically, the basin lies between latitudes 19\u0026deg;25\u0026prime;N and 19\u0026deg;45\u0026prime;N and longitudes 74\u0026deg;30\u0026prime;E and 74\u0026deg;0\u0026prime;E, forming part of the larger Godavari River system (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The Mula is a major tributary of the Pravara, and both rivers discharge a large amount of water into the Godavari River Basin. This makes the Godavari Basin the second-largest in peninsular India, after the Ganges. The land in the study area varies in height from 404 to 1424 m above mean sea level and has moderate slopes. Geographically, the area can be divided into three parts: hilly terrain in the west (Western Ghat), a gently sloping pediment in the centre, and a plateau with a slight slope in the east (Das et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003ea). As a sub-basin within this region, the MRB occupies the southwestern portion of the Pravara catchment. The Mula and Pravara Rivers originate from the high-altitude escarpments of the Western Ghat. It flows through varied terrain, transitioning from rugged, elevated landscapes in the west to gently sloping plains in the east.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe western region of the MPRBs is characterised by elevated topography, forming a dissected plateau that significantly influences drainage patterns and the spatial distribution of fluvial activity within the basin. This area encompasses several prominent volcanic peaks, including \u003cem\u003eKalsubai\u003c/em\u003e (1646 m), \u003cem\u003eHarishchandragad\u003c/em\u003e (1428 m), \u003cem\u003eAjoba Dongar\u003c/em\u003e (1375 m), \u003cem\u003eRatangad\u003c/em\u003e (1297 m), and the \u003cem\u003eAlang-Madan-Kulang\u003c/em\u003e mountain range (1464\u0026ndash;1494 m), all of which are products of the Deccan Volcanic Province (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). As it progresses eastward, the terrain transitions to a middle-level plateau, with elevations ranging from 550 to 900 m above mean sea level. \u003cem\u003eWatmai\u003c/em\u003e (876 m) and \u003cem\u003eDudheshwar\u003c/em\u003e (833 m) are the major peaks in the plateau area of ​​the Pravara Basin, whereas \u003cem\u003eBaleshwar\u003c/em\u003e (1100 m) is the major peak in the plateau area of ​​the Mula Basin. The middle of the basin is an old plain formed by ancient erosion. The younger floodplain has developed along the riverbanks due to the recent sediment deposition from the river flood (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These basins are formed by Upper Cretaceous basaltic flows (Wellman and McElhinny \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e1970\u003c/span\u003e; Widdowson and Mitchel 1999; Hooper \u003cem\u003eet al\u003c/em\u003e.2010; Das and Pardeshi \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Geographically, these basins lie east of the Western Ghat. This central geomorphic zone displays moderate relief and is primarily shaped by denudational processes acting upon the basaltic Deccan Trap. The prolonged fluvial activity of MPRBs has significantly contributed to the dissection and modification of the landscape, leading to the classification of this region as a denudational slope.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the easternmost part of the basin, the slope gradient decreases substantially, resulting in depositional features such as alluvial terraces and broad floodplains. This geomorphic setting is characterised by flat riverbeds and sediment-accumulation zones. The transition from rugged highlands to subdued floodplains reflects spatial variation in geomorphological and geological characteristics across the basin. The study area experiences a predominantly hot and dry climate, with peak temperatures during the summer months (March to early June). The southwest monsoon (June to September) accounts for most of the annual rainfall, whereas the post-monsoon season occurs in October and November. Winters (November to February) are mild and dry. Rainfall is highest in the western hilly region and decreases gradually toward the east, with an average annual rainfall of 501.8 mm (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The MPRBs have a semi-arid climate due to their position in the rain shadow of the Western Ghat, which blocks much of the southwest monsoon. This results in low rainfall and elevated temperatures, particularly from October to May, when dry conditions prevail (Doke et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eSince the late 20th century, the use of remote sensing and Geographic Information Systems (GIS) has significantly improved the ability to evaluate large drainage basins (Das and Pardeshi 2018). This study presents a comprehensive morphometric analysis of the MPRBs using topographic maps and remote sensing data. A total of 17 Survey of India (SOI) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://surveyofindia.gov.in\u003c/span\u003e\u003cspan address=\"https://surveyofindia.gov.in\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) toposheets (47 E/10, 47 E/11, 47 E/14, 47 E/15, 47 I/1, 47 I/2, 47 I/3, 47 I/4, 47 I/6, 47 I/7, 47 I/8, 47 I/10, 47 I/11, 47 I/12, 47 I/14, 47 I/15, and 47 I/16) on the scale of 1:50000 were acquired from the SOI and georeferenced using ArcMap 10.8.2 GIS platform. These toposheets were then mosaicked to generate a continuous spatial dataset, which enabled the manual digitisation of the entire river courses. To delineate the drainage network of the MPRBs, GIS software was employed along with DEM data. Initially, the DEM was pre-processed by filling sink areas to eliminate topographic depressions and ensure hydrological consistency (Schumm \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e1973\u003c/span\u003e; Gaikwad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdditionally, SRTM DEM data with a 30 m spatial resolution, obtained from the United States Geological Survey (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://earthexplorer.usgs.gov\u003c/span\u003e\u003cspan address=\"https://earthexplorer.usgs.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), were used to derive relief-based morphometric parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This integrated approach, combining topographic sheets, remote sensing data, and GIS techniques, enabled detailed morphometric characterisation of the study area, providing a scientific foundation for further geographical interpretation and watershed management.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"4. Linear Aspects","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Stream Order (Su)\u003c/h2\u003e \u003cp\u003eStream order serves as a foundational parameter in the quantitative analysis of watershed characteristics. The concept was first introduced by Horton (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1932\u003c/span\u003e), who defined stream order as a hierarchical classification of streams based on their position within the drainage network. First-order streams are the smallest tributaries with no upstream connections and generally exhibit intermittent flow, particularly during the wet season. In the present study, stream networks were delineated from SOI Toposheets, and stream ordering was performed using Strahler\u0026rsquo;s (\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e1957\u003c/span\u003e) method. According to the analysis, the MPRBs have stream orders of 7 and 6, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Typically, higher-order streams indicate larger drainage basins and are associated with substantial water discharge. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrates the stream-order distribution for the MPRB watersheds. Consistent with Horton\u0026rsquo;s observations (1945), the highest frequency of streams occurs at the first order. Furthermore, the number of streams decreases progressively with increasing stream order, indicating an inverse relationship.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Stream Number (Nu)\u003c/h2\u003e \u003cp\u003eStream number is a key hydrological parameter that provides valuable insights into surface runoff characteristics within a drainage basin (Kumar et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). A general observation, consistent with Horton\u0026rsquo;s laws, is that the number of streams decreases as stream order increases (Gezahegn and Mengistu \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). This trend reflects the hierarchical nature of drainage networks. In this study, stream numbers were calculated using ArcGIS 10.8 for the MPRBs. Stream numbers generally decrease with increasing stream order and are influenced by the basin's lithology and structure. The MPRBs contain 11,064 and 6,919 streams, respectively. A significant proportion of these are first-order streams: the MRB has 8,566 and the PRB 5,387 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The high concentration of first-order streams indicates a dense drainage texture, which may increase the risk of flash floods during periods of intense rainfall (Chitra et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Stream Length (Lu)\u003c/h2\u003e \u003cp\u003eStream length reflects the development of stream segments over time, including the impact of tectonic activity (Magesh et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). It represents the total stream length in each order within a basin and generally follows a geometric progression (Horton \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1945\u003c/span\u003e). Areas with higher permeability tend to have longer and denser stream networks. In this study, stream lengths were calculated using ArcGIS software through the 'Calculate Geometry' tool. The results support Horton\u0026rsquo;s law, which states that geometrical similarity is usually maintained across increasing stream orders (Strahler \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e). The total stream length in the MRB is about 8,035 km, and in the PRB, about 6,000 km. Shorter stream lengths are associated with steeper slopes, whereas longer stream lengths are associated with lower gradients (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Thus, the longer stream lengths in the MRB indicate a gentler slope than in the PRB.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Mean Stream Length (Lum)\u003c/h2\u003e \u003cp\u003eMean stream length (Lum) represents the average length of stream segments within a specific order and reflects the characteristic size of drainage components and their contributing area (Strahler \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e). Lum is calculated by dividing the total stream length of a given order by the number of streams in that order. It typically increases with stream order and is influenced by watershed size and topography. In this study, Lum values were 1,147.90 km for the MRB and 1,000 km for the PRB. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB, mean stream length increases with stream order, indicating a direct relationship.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStream Order, Stream Number, and Bifurcation Ratios (A) Mula (B) Pravara Watershed. \u003cb\u003eB)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv 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align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46175.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eII\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e27405.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIII\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10949.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eIII\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6442.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e 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\u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11064\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e27.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e13561\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e60084.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e7154\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e36.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e8920\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e36382.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2260.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e10014.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e7.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Stream Length Ratio (Lur)\u003c/h2\u003e \u003cp\u003eStream length ratio is the ratio of the mean stream length of one order to that of the next lower order (Horton \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1945\u003c/span\u003e). According to Horton\u0026rsquo;s law, mean stream length increases in a geometric pattern with higher stream orders. Variations in this ratio can indicate the basin\u0026rsquo;s geomorphic stage, with noticeable changes often reflecting the late youth stage. In this study, the Mula Watershed exhibits a stream length ratio of 2.6, while the Pravara Watershed shows a higher ratio of 5.3 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Bifurcation Ratio (Rb)\u003c/h2\u003e \u003cp\u003eThe bifurcation ratio (Rb), defined by Schumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e), is the ratio of the number of stream segments in a given order (Nu) to those in the next higher order (Nu\u0026thinsp;+\u0026thinsp;1). It helps assess the branching pattern and connectivity of a drainage network. Horton (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1945\u003c/span\u003e) described Rb as an index reflecting relief and landscape dissection, while Strahler (\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e1957\u003c/span\u003e) noted that Rb values are generally consistent except where geological controls are dominant. As a dimensionless parameter, Rb indicates the degree of integration between stream orders and varies with geological and lithological settings. Generally, Rb ranges from 3.0 to 5.0, with higher values pointing to structural influence (Strahler \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e; Nag \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). For the present analysis, the mean Rb is 4.4 for the MRB and 7.25 for the PRB (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The higher Rb value for Pravara suggests it is more affected by structural disturbances than the MRB.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.7 Weighted Mean Bifurcation Ratio (Rbwm)\u003c/h2\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e1952\u003c/span\u003e) introduced the Rbwm to provide a more accurate assessment of drainage network branching. This method accounts for the bifurcation ratios between successive stream orders, weighted by the number of streams in each order. Based on this method, the Rbwm values for the MPRBs are calculated as 4.43 and 4.08, respectively, indicating a moderately dissected drainage pattern influenced by geological and geomorphological factors (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStream length and stream length ratios of the MPRB Watershed. \u003cb\u003eA)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLu/Nu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLur\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLur-r\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLur*Lur-r\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLuwm\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4806.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eII\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1478.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6284.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8487.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIII\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e880.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2358.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6479.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e425.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1305.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2693.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e212.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e637.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1574.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e116.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e328.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e898.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVII\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e117.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e117.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e233.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e939.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11064\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e8035.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e164.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e15.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e11147.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e21071.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1147.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cb\u003eB)\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLu/Nu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLur\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLur-r\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLur*Lur-r\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLuwm\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3428.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eII\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1153.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4581.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6299.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIII\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e698.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1851.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4357.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e368.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1066.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2145.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e182.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e551.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1213.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e169.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e169.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e351.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6512.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e7154\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5999.71\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e185.8418\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e26.4734\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e8402\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e20526.81\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1000.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1680.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4105.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.8 Valley Index (Vi) and Channel Index (Ci)\u003c/h2\u003e \u003cp\u003eMiller (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1953\u003c/span\u003e) proposed sinuosity as a measure of the degree of meandering in a river's course. To calculate this, the river channel is divided into segments, and indices are derived from the channel length (Cl), the valley length (Vl), and the straight-line distance from the source to the mouth (Adm). For the Mula Watershed, the Ci is 1.63, and Vi is 0.21. In the Pravara Watershed, the Ci is 1.42, and Vi is 0.10 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These values suggest that the Mula River has a slightly more sinuous course than the Pravara.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.9 Rho Coefficient\u003c/h2\u003e \u003cp\u003eHorton (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1945\u003c/span\u003e) defined the Rho coefficient as an essential parameter that links drainage density to the physiographic development of a watershed (Gautam et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Dimple et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Gautam et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). It helps assess the storage capacity of the drainage network and the level of drainage development within a watershed. For the Mula Watershed, the Rho value is 3.39, and for the Pravara Watershed, it is 3.65 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Basin Geometry","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Basin Length (Lb)\u003c/h2\u003e \u003cp\u003eAccording to Schumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e), basin length is the longest dimension of a watershed, running parallel to the principal drainage line. This dimension provides insight into the watershed\u0026rsquo;s extent along its primary drainage course. Gregory and Walling (1973) define basin length as the maximum distance from the basin\u0026rsquo;s source to its mouth (Gaikwad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This length indicates the watershed\u0026rsquo;s overall extent. In this study, basin lengths for both the MPRB watersheds were determined. The basin length for the Mula Watershed is 121.5 km, while that for the Pravara Watershed is 115.4 km (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Basin Area (A)\u003c/h2\u003e \u003cp\u003eBasin area is essential for understanding a watershed\u0026rsquo;s shape and size. It helps in analysing hydrological processes, runoff, and water distribution. Schumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e) noted a relationship between a watershed's total area and the total length of its streams, influenced by the contributing areas that feed into the streams. The Mula Watershed covers 2900.6 km\u003csup\u003e2\u003c/sup\u003e while the Pravara Watershed covers 2650.7 km\u003csup\u003e2\u003c/sup\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Basin Perimeter (P)\u003c/h2\u003e \u003cp\u003eThe basin perimeter is the total length of the boundary enclosing the watershed, measured along the dividing line separating it from adjacent watersheds (Pareta and Pareta \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). For the Pravara Watershed, the basin perimeter is 351 km, while for the Mula it is 382.1 km (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e5.4 Length Area Relation (Lar)\u003c/h2\u003e \u003cp\u003eThe length-area relationship in a watershed is a key concept in hydrology that explains the relationship between river or stream length and its corresponding drainage area. This relationship is vital for hydrological modelling, flood forecasting, and watershed management. It helps predict how rivers will respond to changes in land use, climate, and other environmental factors. Hack (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1957\u003c/span\u003e) observed that for a large number of basins, the stream length and basin area are related by a simple power function: Lar\u0026thinsp;=\u0026thinsp;1.4 * A\u003csup\u003e0.6\u003c/sup\u003e. The observed Lar values are 167.5 for the Mula Watershed and 159.22 for the Pravara Watershed (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e5.5 Lemniscate\u0026rsquo;s (k)\u003c/h2\u003e \u003cp\u003eChorley (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1957\u003c/span\u003e) formulated the Lemniscate\u0026rsquo;s value to assess the slope of a basin. The k value is calculated using the formula: k\u0026thinsp;=\u0026thinsp;Lb\u0026sup2; / 4 * A, where Lb represents the basin length in km, and A is the basin area in km\u003csup\u003e2\u003c/sup\u003e. For the Mula Watershed, the k value is 5.09, while for the Pravara Watershed, it is 5.03. A higher k value indicates a more elongated basin (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Therefore, the MRB is more elongated than the PRB.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e5.6 Form Factor Ratio (Rf)\u003c/h2\u003e \u003cp\u003eThe form factor, as defined by Horton (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1932\u003c/span\u003e), helps describe the shape of a watershed. It is the ratio of the basin area to the square of the basin length. The form factor ranges from 0 (for an elongated, straight watershed) to 0.754 (for a circular watershed). Smaller Rf values indicate greater elongation, while larger values suggest a more compact shape. Watersheds with low Rf values typically experience longer-duration, lower peak flows, while those with higher Rf values have shorter-duration, higher peak flows (Pareta and Pareta \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The Rf value for the MRB is 0.20. For the PRB, it is 0.20, indicating that both basins are elongated. The peak flow characteristics are homogeneous due to their similar geographical features (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e5.7 Elongation Ratio (Re)\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eThe elongation ratio (Re), defined by Schumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e), compares the diameter of a circle with the same area as the basin to its maximum length. Strahler categorised this ratio as 0.6-1 across different environments. The Re values for Mula and Pravara are 0.29 and 0.32. This is due to the river\u0026rsquo;s linear topography, which results in lengths longer than widths. Therefore, both watersheds are highly elongated, which influences their drainage and runoff patterns (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e5.8 Texture Ratio (Rt)\u003c/h2\u003e \u003cp\u003eSchumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e) demonstrates that the texture ratio (Rt) is a significant parameter in drainage morphometric analysis, as it reflects the influence of underlying lithology, infiltration capacity, and terrain relief. The texture ratio is the ratio of the number of first-order streams (N1) to the basin perimeter (P), expressed as Rt\u0026thinsp;=\u0026thinsp;N1 / P. In the present study, the Rt value for the Mula Watershed is 22.41, indicating a relatively coarse drainage texture. In contrast, the Pravara watershed exhibits a lower Rt value of 13.80, suggesting a finer drainage texture. These variations in texture ratio highlight the geomorphological and lithological differences between the two basins (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e5.9 Circularity Ratio (Rc)\u003c/h2\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e) and Miller (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1953\u003c/span\u003e) introduced the circularity ratio (Rc), a dimensionless parameter used to quantify watershed shape. Rc is the ratio of basin area to the area of a circle with the same perimeter, reflecting lithological characteristics and geomorphic development. Miller (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1953\u003c/span\u003e) noted that Rc values between 0.4 and 0.5 indicate elongated basins with permeable, homogeneous geologic materials. Values near 1 suggest circular basins with uniform infiltration, while lower Rc values indicate youthful basins with faster runoff (Strahler, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e). In this study, the Rc values for the MPRBs Watersheds are 0.25 and 0.26, respectively, indicating elongated basin shapes (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e5.10 Drainage Texture (Dt)\u003c/h2\u003e \u003cp\u003eHorton (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1945\u003c/span\u003e) characterised drainage texture (Dt) as the total number of stream segments of all orders per unit perimeter, reflecting the relative spacing of streamlines. It is influenced by lithology, infiltration capacity, and terrain relief. Smith (1950) classified Dt into five categories: very coarse (\u0026lt;\u0026thinsp;2), coarse (2\u0026ndash;4), moderate (4\u0026ndash;6), fine (6\u0026ndash;8), and very fine (\u0026gt;\u0026thinsp;8). In the present study, Dt values for the MPRBs Watersheds are 21.03 and 20.35, respectively, indicating a very fine drainage texture (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e5.11 Compactness Coefficient (Cc)\u003c/h2\u003e \u003cp\u003eGravelius (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1914\u003c/span\u003e) proposed the compactness coefficient (Cc) to assess the complexity of watershed shape. It is the ratio of the watershed perimeter to the perimeter of a circle with the same area. A Cc value of 1 indicates a perfect circular basin, while values greater than 1 suggest a more elongated and less compact shape. Higher Cc values correspond to longer flow paths and greater runoff, thereby potentially increasing flood susceptibility. In contrast, lower Cc values indicate shorter flow paths and quicker drainage. In the present investigation, the Mula Watershed has a Cc of 2.02, and the Pravara Watershed has a value of 1.98, both indicating moderately elongated shapes (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e5.12 Fitness Ratio (Rf)\u003c/h2\u003e \u003cp\u003eThe fitness ratio (Rf) is the ratio of the main channel length to the watershed perimeter (Melton,1965). The Rf values for the MPRBs Watersheds are 0.51 and 0.49, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). An Rf close to 1 indicates an efficient drainage network, with the main channel length proportionate to the perimeter. Lower Rf values indicate an inefficient channel network that is poorly matched to the watershed shape, potentially reducing drainage efficiency.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e5.13 Wandering Ratio (Rw)\u003c/h2\u003e \u003cp\u003eSmart and Surkan (\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e1967\u003c/span\u003e) introduced the wandering ratio (Rw) to assess the relationship between the main stream length (Cl) and the valley length (Lb). A value close to 1 indicates a straight stream, whereas higher values indicate greater meandering. The Rw values for the MPRBs Watersheds are 1.74 and 1.53, respectively, indicating relatively direct flow paths with limited meandering (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Rw is controlled by factors such as channel gradient, bedrock lithology, tectonic structures, and floodplain geomorphology, which collectively influence channel sinuosity and planform dynamics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e5.14 Watershed Eccentricity (τ)\u003c/h2\u003e \u003cp\u003eBlack (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1972\u003c/span\u003e) introduced watershed eccentricity (τ) as a dimensionless parameter that quantifies basin elongation. Higher τ values indicate a more elongated basin, whereas lower values indicate a more circular or compact basin. In the present study, the eccentricity values are 0.95 for the Mula Watershed and 0.97 for the Pravara Watershed, indicating that Pravara is moderately elongate, whereas Mula is relatively more compact (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e5.15 Centre of Gravity of Watershed (Gc)\u003c/h2\u003e \u003cp\u003eGc is the length of the channel measured from the outlet of the watershed to a point on the stream nearest to the centre of the watershed (Pareta and Pareta \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In the present study, Gc was computed using ArcGIS-10.8.2. The Gc point for Mula is at 18˚49\u0026rsquo;19\u0026rdquo; N and 74˚02\u0026rsquo;20\u0026rdquo; E, and the Gc point for Pravara is at 74˚59\u0026rsquo;52\u0026rdquo; E and 15˚13\u0026rsquo;25\u0026rdquo; N (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003e5.16 Standard Sinuosity Index (Ssi)\u003c/h2\u003e \u003cp\u003eSinuosity describes the pattern and degree of curvature in a river channel within a drainage basin. It is expressed as the sinuosity index (Ssi), defined as the ratio of channel length to straight-line valley length. According to Wolman and Miller (1964), rivers with an Ssi of 1.5 are considered sinuous, while values exceeding 1.5 indicate meandering channels. Sinuosity is a vital morphometric parameter in fluvial geomorphology, as it reflects channel behaviour and planform development. The MPRBs Watersheds exhibit Ssi values of 1.76 and 1.42, respectively, indicating that the Mula River follows a more meandering course, whereas the Pravara River shows a relatively straighter alignment (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Therefore, the observed sinuosity may be attributed to variations in valley slope, underlying lithology, structural controls, and sediment load. Hence, these factors significantly influence the degree of meandering and the development of channel patterns in both watersheds.\u003c/p\u003e \u003c/div\u003e"},{"header":"6. Drainage Texture Analysis","content":"\u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003e6.1 Stream Frequency (Fs)\u003c/h2\u003e \u003cp\u003eStream frequency (Fs), initially defined by Horton (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1932\u003c/span\u003e), represents the number of stream segments per unit area and is commonly used to assess the drainage texture of a watershed. For the present analysis, the MPRBs Watersheds exhibit Fs values of 2.5 and 2.62, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This parameter is primarily influenced by the underlying geology, particularly the permeability and resistance of surface materials. The higher Fs generally correspond to a more closely spaced, well-connected drainage network. The PRB (Fs\u0026thinsp;=\u0026thinsp;2.62) exhibits a denser drainage network than the MRB (Fs\u0026thinsp;=\u0026thinsp;2.5), suggesting higher runoff and lower infiltration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec33\" class=\"Section2\"\u003e \u003ch2\u003e6.2 Drainage Density (Dd)\u003c/h2\u003e \u003cp\u003eDrainage density (Dd), expressed as stream length per unit area, reflects the degree of dissection and runoff potential in a watershed (Strahler \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e). In the present study, Dd was calculated using ArcGIS, yielding 1.92 km/km\u0026sup2; for the Mula and 2.1 km/km\u0026sup2; for the PRB (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These values suggest a moderately developed drainage network, influenced by homogeneous lithology across both basins. The slightly higher Dd in the PRB indicates steeper slopes and greater runoff potential, whereas the MRB suggests gentler terrain and higher infiltration capacity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section2\"\u003e \u003ch2\u003e6.3 Constant of Channel Maintenance (C)\u003c/h2\u003e \u003cp\u003eThe constant of channel maintenance (C), introduced by Schumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e), quantifies the relationship between basin size and channel length, indicating the basin area required to maintain a 1-km-long channel. It is used to quantify the efficiency with which a watershed generates and sustains its channels. Schumm focused on the inverse of drainage density, where Strahler related it to landform-unit size. In this study, the C values for the MPRBs watersheds are 0.52 km\u0026sup2;/km and 0.48 km\u0026sup2;/km, respectively, reflecting the basin area needed to support a 1 km channel (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These values suggest that both watersheds maintain relatively efficient channel networks, with the PRB showing slightly higher efficiency.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec35\" class=\"Section2\"\u003e \u003ch2\u003e6.4 Drainage Intensity (Di)\u003c/h2\u003e \u003cp\u003eDrainage intensity (Di), defined as the ratio of stream frequency to drainage density, was introduced by Faniran (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1968\u003c/span\u003e). The study shows Di values of 1.3 for the Mula and 1.25 for the Pravara watersheds (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These values, along with low Dd and Fs, indicate that surface runoff is not efficiently managed in these watersheds. Consequently, both watersheds may be more prone to flooding, gully erosion, and landslides.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec36\" class=\"Section2\"\u003e \u003ch2\u003e6.5 Infiltration Number (If)\u003c/h2\u003e \u003cp\u003eAccording to Faniran (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1968\u003c/span\u003e), the infiltration number, calculated as the product of Dd and stream frequency, is a key metric for assessing a watershed\u0026rsquo;s infiltration characteristics. Higher infiltration numbers typically correspond to lower infiltration capacity and higher surface runoff (Pareta and Pareta \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The Infiltration Factor (If) values for the MPRBs watersheds are 4.80 and 5.50, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These values suggest that the Pravara Watershed has a slightly lower infiltration capacity than the Mula Watershed, resulting in greater runoff and reduced groundwater recharge. Understanding these dynamics is crucial for managing water movement, flood risk, and soil erosion in these regions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec37\" class=\"Section2\"\u003e \u003ch2\u003e6.6 Length of Overland Flow (Lg)\u003c/h2\u003e \u003cp\u003eHorton (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1945\u003c/span\u003e) introduced the concept of length of overland flow (Lg) as the average distance precipitation travels over the land before entering a defined stream channel. It is estimated as half the reciprocal of drainage density and is a key indicator of surface runoff efficiency. In the present study, Lg values are 0.22 km for the Mula and 0.24 km for the Pravara watersheds (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The shorter Lg in the MRB suggests a quicker response to rainfall and more immediate runoff generation. In comparison, the slightly longer Lg in the PRB may indicate a more delayed runoff response. These values are crucial in assessing runoff potential, infiltration capacity, and flood risk.\u003c/p\u003e \u003c/div\u003e"},{"header":"7. Relief Characteristics","content":"\u003cdiv id=\"Sec39\" class=\"Section2\"\u003e \u003ch2\u003e7.1 Relief Ratio (Rhl)\u003c/h2\u003e \u003cp\u003eTotal relief represents the elevation difference between the highest and lowest points in a watershed. Schumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e) introduced the relief ratio (Rhl), calculated as the total relief divided by the maximum basin length parallel to the main drainage line. This metric reflects the overall steepness and erosional potential of a basin, often correlating with runoff intensity and sediment yield. In the current study, Rhl values are 5.22 for the Mula and 5.38 for the Pravara Watershed, indicating that both basins exhibit moderate relief, with the PRB having slightly higher erosional potential.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec40\" class=\"Section2\"\u003e \u003ch2\u003e7.2 Absolute Relief (Ra)\u003c/h2\u003e \u003cp\u003eAbsolute relief refers to the elevation of a location above sea level and reflects the vertical extent of terrain within a watershed (Strahler \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e). In this study, the Mula Watershed exhibits an absolute relief of 1410 m, while the Pravara Watershed shows a slightly higher value of 1420 m. These elevations indicate that the PRB lies at a generally higher altitude, potentially influencing climatic conditions, runoff characteristics, and erosion dynamics more prominently than the MRB (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec41\" class=\"Section2\"\u003e \u003ch2\u003e7.3 Dissection Index (Dis)\u003c/h2\u003e \u003cp\u003eThe dissection index (Dis), introduced by Nir (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e1957\u003c/span\u003e), measures the extent of vertical erosion in a landscape. It helps to understand how deeply rivers and streams have cut into a region. Dis values range from 0 to 1, with values near 0 indicating flat terrain and values near 1 indicating steep, highly eroded landscapes (Singh and Dubey \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). In this study, both the MPRB watersheds exhibit a Dis value of 0.67, indicating that the region is moderately dissected, with a plateau landscape undergoing gradual erosion. This indicates that both watersheds are in a mature stage of geomorphic evolution, with balanced erosion and deposition processes shaping the terrain (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec42\" class=\"Section2\"\u003e \u003ch2\u003e7.4 Gradient Ratio (Rg)\u003c/h2\u003e \u003cp\u003eThe gradient ratio (Rg) is a useful indicator of channel slope and helps assess runoff characteristics within a watershed (Sreedevi et al. \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). In this study, the Rg values are 5.22 for the Mula Watershed and 5.38 for the Pravara Watershed, suggesting slightly steeper channel gradients in the PRB. This implies that runoff is likely to be faster in the PRB, leading to greater erosion potential, whereas the MRB may experience more moderate flow and improved infiltration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec43\" class=\"Section2\"\u003e \u003ch2\u003e7.5 Ruggedness Number (Rn)\u003c/h2\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e) defined the ruggedness number (Rn) as the product of basin relief and drainage density, indicating terrain complexity and erosion potential. In this study, Rn values of 1.94 for Mula and 2.01 for Pravara suggest that Pravara is slightly more susceptible to erosion and runoff due to its higher ruggedness (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec44\" class=\"Section2\"\u003e \u003ch2\u003e7.6 Melton Ruggedness Number (MRn)\u003c/h2\u003e \u003cp\u003eMelton (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1965\u003c/span\u003e) defined the Ruggedness Number (MRn) as a slope-based index that represents the relief ruggedness of a watershed. In this study, MRn values are 28.56 for Mula and 28.99 for Pravara, reflecting high relief variation and rugged terrain in both watersheds. The slightly higher MRn in the PRB suggests a more dissected, steeper landscape, indicating greater geomorphic activity and erosion susceptibility than the Mula Watershed (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec45\" class=\"Section2\"\u003e \u003ch2\u003e7.7 Average Slope (S)\u003c/h2\u003e \u003cp\u003eWentworth (\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e1930\u003c/span\u003e) proposed that the erodibility of a watershed can be evaluated based on its average slope. The formula for calculating the average slope is:\u003c/p\u003e \u003cp\u003eS = (Z * (Ctl / H)) / (10 * A)\u003c/p\u003e \u003cp\u003ewhere Z is the Maximum Height of the basin, Ctl is the Total Contour Length, H represents the total basin relief, and A is the area of the watershed. In the Mula Watershed, the average slope is 5.75%, whereas in the Pravara Watershed it is 4.56%. These values indicate that Mula has a slightly steeper average slope, suggesting greater susceptibility to erosion than Pravara (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). In conclusion, the Mula Watershed's steeper slopes suggest a higher rate of surface runoff and increased erosion potential. In contrast, the Pravara Watershed, with its gentler slopes, may experience relatively lower erosion rates.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMorphometric parameters and corresponding formulae considered in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSr No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFormula\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eResult\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eReferences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMula\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePravara\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eA. Linear Aspect\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStream order \u003cb\u003e(Su)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHierarchical Rank\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 to 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 to 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e1952\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1st Order Stream \u003cb\u003e(Suf)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuf=N1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5387.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e1952\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStream Number \u003cb\u003e(Nu)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNu=N1\u0026thinsp;+\u0026thinsp;N2+\u0026hellip;.Nn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHortan (1945)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStream Length \u003cb\u003e(Lu)\u003c/b\u003e km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLu=L1\u0026thinsp;+\u0026thinsp;L2+\u0026hellip;.Ln\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8035.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean Stream Length (Lurm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1147.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1000.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStream Length Ratio \u003cb\u003e(Lur)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHortan (1945)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean Stream Length Ratio \u003cb\u003e(Lurm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHortan (1945)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeighted Mean Stream Length Ratio \u003cb\u003e(Lurwm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBifurcation Ratio \u003cb\u003e(Rb)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.3 to 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.81 to 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean Bifurcation ratio \u003cb\u003e(Rbm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (1953)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeighted Mean Bifurcation Ratio \u003cb\u003e(Rbwm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (1953)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMain channel Length \u003cb\u003e(Cl)\u003c/b\u003e km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Software Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e210.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e177.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValley Length \u003cb\u003e(Vl)\u003c/b\u003e km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Software Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimum Aerial Distance \u003cb\u003e(Adm)\u003c/b\u003e km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Software Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e119.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e124.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChannel Index \u003cb\u003e(Ci)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCi\u0026thinsp;=\u0026thinsp;Cl / Adm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMiller (1968)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValley Index \u003cb\u003e(Vi)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVi\u0026thinsp;=\u0026thinsp;Vl / Adm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMiller (1968)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRho Coefficient \u003cb\u003e(p)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;Lur / Rb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHorton (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1945\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eB. \u003cb\u003eAerial Aspect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLength from W's Centre to Mouth of W's \u003cb\u003e(Lcm)\u003c/b\u003e km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Software Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlack (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1972\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidth of W's at Centre of Mass \u003cb\u003e(Wcm)\u003c/b\u003e km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Software Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlack (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1972\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBasin Length \u003cb\u003e(Lb)\u003c/b\u003e km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLb\u0026thinsp;=\u0026thinsp;1.312\u0026times;A0.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e115.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSreedevi et al. (\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2005\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean Basin Width \u003cb\u003e(Wb)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWb\u0026thinsp;=\u0026thinsp;A / Lb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHorton (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1932\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBasin Area \u003cb\u003e(A)\u003c/b\u003e km\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Software Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2900.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2650.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSchumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBasin Perimeter \u003cb\u003e(P)\u003c/b\u003e km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Software Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e382.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e359.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSchumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRelative Perimeter \u003cb\u003e(Pr)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePr\u0026thinsp;=\u0026thinsp;A / P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSchumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLength Area Relation \u003cb\u003e(Lar)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLar\u0026thinsp;=\u0026thinsp;1.4 * A^0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e167.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e159.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHack (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1957\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLemniscate's \u003cb\u003e(k)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ek\u0026thinsp;=\u0026thinsp;Lb\u0026sup2; /A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eChorley (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1957\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForm Factor Ratio \u003cb\u003e(Rf)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRf\u0026thinsp;=\u0026thinsp;A / Lb\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHorton (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1932\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShape Factor Ratio \u003cb\u003e(Rs)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSf\u0026thinsp;=\u0026thinsp;Lb\u0026sup2; / A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHorton (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1932\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElongation Ratio \u003cb\u003e(Re)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRe\u0026thinsp;=\u0026thinsp;2 / Lb * (A / π)^0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSchumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElipticity Index (Ie)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIe\u0026thinsp;=\u0026thinsp;π * Vl\u0026sup2; / 4 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSchumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTexture Ratio \u003cb\u003e(Rt)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRt= N1 / P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSchumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCircularity Ratio \u003cb\u003e(Rc)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRc\u0026thinsp;=\u0026thinsp;12.57 * (A / P\u0026sup2; )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMiller (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1953\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCircularity Ration \u003cb\u003e(Rcn)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRcn\u0026thinsp;=\u0026thinsp;A / P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrainage Texture \u003cb\u003e(Dt)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDt\u0026thinsp;=\u0026thinsp;Nu / P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHorton (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1945\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompactness Coefficient \u003cb\u003e(Cc)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCc\u0026thinsp;=\u0026thinsp;0.2841 * P / A^0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGravelius (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1914\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFitness Ratio \u003cb\u003e(Rf)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRf\u0026thinsp;=\u0026thinsp;Cl / P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMelton (1957)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWandering Ratio \u003cb\u003e(Rw)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRw\u0026thinsp;=\u0026thinsp;Cl / Lb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSmart and Sukan (1967)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWatershed Eccentricity \u003cb\u003e(e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlack (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1972\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCentre of Gravity of Watershed \u003cb\u003e(Gc)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGIS Software Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74\u0026deg;02'20'' E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74\u0026deg;59'52'' E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRao (1998)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u0026deg;49'19'' N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u0026deg;13'25'' N\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHydraulic Sinuosity Index (Hsi) %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHsi = ((Ci -Vi)/(Ci\u0026thinsp;\u0026minus;\u0026thinsp;1))*100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMueller (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e1968\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard Sinuosity Index (Ssi)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSsi\u0026thinsp;=\u0026thinsp;Ci / Vi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMueller (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e1968\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eC. \u003cb\u003eRelief Aspect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStream Frequency \u003cb\u003e(Fs)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFs\u0026thinsp;=\u0026thinsp;Nu / A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHorton (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1932\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrainage Density \u003cb\u003e(Dd)\u003c/b\u003e km/km\u003cb\u003e\u0026sup2;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDd\u0026thinsp;=\u0026thinsp;Lu / A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHorton (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1932\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstant of Channel Maintenance \u003cb\u003eC\u003c/b\u003e km/km\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC\u0026thinsp;=\u0026thinsp;1 / Dd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSchumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrainage Intensity \u003cb\u003e(Di)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDi\u0026thinsp;=\u0026thinsp;Fs / Dd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFaniran (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1968\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfiltration Number \u003cb\u003e(If)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIf\u0026thinsp;=\u0026thinsp;Fs * Dd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFaniran (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1968\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLength of Overland Flow \u003cb\u003e(Lg)\u003c/b\u003e Km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLg\u0026thinsp;=\u0026thinsp;A / 2 * Lu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHorton (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1945\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeight of the Basin Mouth \u003cb\u003e(z)\u003c/b\u003e m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Analysis / DEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e405.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e405.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaximum Height of the Basin \u003cb\u003e(Z)\u003c/b\u003e m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Analysis / DEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1414.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1424.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Basin Relief \u003cb\u003e(H)\u003c/b\u003e m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eH\u0026thinsp;=\u0026thinsp;Z - z\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1009.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1019.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e1952\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRelief Ratio \u003cb\u003e(Rhl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRhl\u0026thinsp;=\u0026thinsp;H / Lb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSchumm (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1956\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbsolute Relief \u003cb\u003e(Ra)\u003c/b\u003e m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Software Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1414.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1424.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRelative Relief Ratio \u003cb\u003e(Rhp)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRhp\u0026thinsp;=\u0026thinsp;H * 100 / P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMelton (1957)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDissection Index \u003cb\u003e(Dis)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDis\u0026thinsp;=\u0026thinsp;H / Ra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSingh and Dubey (\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e1994\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGradient Ratio \u003cb\u003e(Rg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRg=(Z -z) / Lb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSreedevi (2004)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWatershed Slope \u003cb\u003e(Sw)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSw\u0026thinsp;=\u0026thinsp;H / Lb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRuggedness Number \u003cb\u003e(Rn)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRn\u0026thinsp;=\u0026thinsp;Dd * (H / 1000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e1964\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMelton Ruggedness Number \u003cb\u003e(MRn)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMRn\u0026thinsp;=\u0026thinsp;H / A^0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMelton (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1965\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Contour Length \u003cb\u003e(Ctl)\u003c/b\u003e km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Software Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17159.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13814.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContour Interval \u003cb\u003e(Cin)\u003c/b\u003e m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Software Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLength of Two Successive Contours \u003cb\u003e(L1\u0026thinsp;+\u0026thinsp;L2)\u003c/b\u003e km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIS Software Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1585.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e970.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e1952\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage Slope Width of Contour \u003cb\u003e(Swc)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSwc\u0026thinsp;=\u0026thinsp;A / {(L1\u0026thinsp;+\u0026thinsp;L2) / 2}\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrahler (\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e1952\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage Slope \u003cb\u003e(S)\u003c/b\u003e Degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eS=(Z * (Ctl / H)) / (10 * A)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWenthworth\u0026rsquo;s (1930)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean Slope of Overall basin \u003cb\u003e(Ѳs)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eѲs=(Ctl * Cin) / A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWenthworth\u0026rsquo;s (1930)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec46\" class=\"Section2\"\u003e \u003ch2\u003e7.8 Longitudinal Profile\u003c/h2\u003e \u003cp\u003eThe Pravara River, about 180 km long, exhibits a concave longitudinal profile (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003ea) that descends from nearly 950 to 420 m, shaped by differential erosion, tectonics, and lithological controls (Leopold and Maddock \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e1953\u003c/span\u003e; Schumm \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). In the upper course from 0 to 20 km, a steep gradient of 12.5 m/km drives vertical erosion, with a major knick point at \u003cem\u003eRandha\u003c/em\u003e fall around 15 km, marked by a 60 m drop, indicating structural or lithological influence (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eb) (Castillo et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The middle course, spanning 20 to 100 km, features a moderate gradient of approximately 2.25 m/km, dominated by lateral erosion and sediment transport; the \u003cem\u003eRandha\u003c/em\u003e fall nick point suggests geomorphic disequilibrium, likely due to resistant Deccan basalt or a change in base level (Hack \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1957\u003c/span\u003e; Wobus et al. \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In the lower course, from 100 to 180 km, a gentle gradient of approximately 1 m/km promotes meandering and sediment deposition, with high sinuosity indicative of an old-age river nearing its base level (Mackin \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1948\u003c/span\u003e; Whipple and Tucker \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Mula River\u0026rsquo;s longitudinal profile spans about 210 km, descending from approximately 900 to 400 m (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003ee) (Hooke 2003). In the first 20 km, the river flows steeply through the Western Ghat, exhibiting intense vertical erosion (Montgomery and Buffington \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). The \u003cem\u003ePachnai\u003c/em\u003e Waterfall, located between 10 and 15 km, marks a sharp drop due to resistant geological structures as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003ec (Leopold et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). From 20 to 140 km, the river enters a gentler middle course, with elevation decreasing from 800 to 500 m. This stage is characterised by lateral erosion, broader valleys, and developing floodplains that support agriculture (Bridge \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Schumm \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). At about 160 km, the Mula Dam introduces a sudden break in slope, altering sediment flow and channel form (Petts and Gurnell \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Beyond the dam, from 160 to 210 km, the river gently descends to around 420 m, showing increased deposition. The profile reflects the natural progression of fluvial processes from headwaters to mouth, shaped by topography, gradient, and geological structure (Tooth \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec47\" class=\"Section2\"\u003e \u003ch2\u003e7.9 Hypsometric Curve\u003c/h2\u003e \u003cp\u003eHypsometric analysis is a fundamental geomorphic technique for quantifying watershed development and erosional status (Strahler \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e1952\u003c/span\u003e). The hypsometric integral (HI) values of 0.29 for the Pravara River and 0.26 for the Mula River (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003ea, b) indicate that both basins are in a mature stage of fluvial evolution. Their distinctly concave hypsometric curves reflect extensive surface lowering and slope retreat, characteristic of advanced landscape dissection and reduced relief (Moglen and Bras 1995). This suggests that the basins are approaching geomorphic equilibrium, with reduced potential for vertical incision.\u003c/p\u003e \u003cp\u003eGoogle Earth imagery (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003ec) further supports this interpretation, showing clear evidence of well-developed meanders and lateral channel migration\u0026mdash;features typical of rivers with low gradients and diminished stream power (Schumm \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). The presence of tight meanders in the middle reaches (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003ec), along with broader channels near the Mula-Pravara confluence, indicates a shift from erosional dominance to greater sediment deposition. In this context, Leopold and Wolman (1957) emphasise that low-gradient rivers tend to form meanders due to sediment deposition and flow characteristics, while Smith \u003cem\u003eet al.\u003c/em\u003e (2019) explore the influence of channel migration and sediment transport, further supporting the observed features.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThese hypsometric and morphological features indicate that the river system is approaching a later stage, in which deposition predominates over erosion. This change reflects lower stream energy and balance with the base level.\u003c/p\u003e \u003c/div\u003e"},{"header":"8. Discussion","content":"\u003cp\u003eThis study demonstrates the effectiveness of GIS-based morphometric analysis using SRTM-DEM data by quantifying more than 60 parameters to evaluate watershed characteristics. The results reveal significant variation in hydrological behaviour among the MPRBs. The quantitative morphometric analysis is fundamentally based on the relationships between drainage network patterns and morphometric patterns, including linear, aerial, and basin attributes, which help to understand watershed dynamics and hydrological responses (Fenta et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The nature of the drainage network in each watershed is influenced by variations in physiographic and climatic conditions. The morphometric parameters also vary accordingly (Erosemiah and Viji \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This research focused on analysing the main morphometric parameters of MPRBs observed in the 7th - and 6th -order streams of the watershed (Krishnan and Arjun \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Higher-order stream basins exhibit a more developed, integrated drainage system with numerous tributaries and sub-tributaries, resulting in increased discharge and runoff (Godsey and Kirchner \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Das and Pardeshi 2018).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e (A; B) indicates the relationship between stream order, stream number, and mean stream length. As the stream order increases, the number of streams decreases, while the mean stream length increases (Downing et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In the present study, the relationship between stream number and stream length is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA. The plot shows an approximately linear trend, indicating a strong positive correlation between the two parameters.\u003c/p\u003e \u003cp\u003eA strong relationship exists between stream order and basin area, as the basin area increases, stream order tends to increase. Since the basin area of MRB is greater than that of PRB, higher stream orders are observed in MRB. Rb is considered an essential parameter in morphometric analysis, as it shows the structural control over the drainage network (Waikar and Nilawar \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). According to previous studies, the mean bifurcation ratio (Rbm) can fluctuate even in the absence of geological control, but generally ranges from 3 to 5 (Anish et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mohammed et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In this study, the mean bifurcation ratio of MRB is 7.2, whereas that of PRB is 4.5. The higher value in the Mula watershed indicates stronger structural control over the drainage network, whereas the Pravara watershed reflects a more natural, less structurally influenced drainage development (Choudhari \u003cem\u003eet al\u003c/em\u003e. 2021).\u003c/p\u003e \u003cp\u003eAccording to Nag (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), the drainage network pattern and surface runoff intensity are directly influenced by the lithology, climatic characteristics, geological activities, and geomorphic history of the drainage basin. Dd is an essential areal parameter that depends primarily on lithological characteristics, slope, soil permeability, and weathering (Mahala \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wang et al. 2024). In regions where rigid, compact lithologies such as granite, gneiss, and schist are found, Dd is typically low (Sufyan et al. \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Subramaniyan \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2026\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe MPRBs in this study are primarily underlain by basaltic rocks, and the lithology of both watersheds is relatively similar. So, the distribution of Dd in this area also shows a uniform trend. According to the results, the Dd for the Mula watershed is 2.77, and for the Pravara watershed, it is 2.26. The drainage density is relatively higher in the lower catchments of both river basins (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) (Lin et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Loose and alluvial deposits in these areas indicate a higher potential for erosion (Sampath and Radhakrishnan \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). On the contrary, areas with low drainage density indicate good subsurface permeability and filtration capacity of the soil. According to Kumar et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), the relationships among Dd, surface runoff, and lithology were explained. Similarly, Magesh and Chandrasekar (2014) have explained that Dd is an indicator of subsurface material permeability in the Western Ghat region. Thus, analysis of drainage density in the MPRBs is useful for understanding the lithology, geomorphological processes, and hydrological response of the area.\u003c/p\u003e \u003cp\u003eAccording to numerous researchers worldwide, Circularity Ratio and Elongation Ratio are considered significant morphometric indices for determining the size and shape of a drainage basin (Waikar and Nilawar \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Bogale \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Das et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tassew et al. \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ocheri et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). If the values of these indices are close to 0, it indicates that the respective basin is elongated (Moussa \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Rudraiah 2008; Sharma and Sarma \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). On the contrary, if the value of the indices is close to one (1), then the shape of that watershed is circular (Adhikari \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Asfaw and Workineh \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Therefore, by evaluating the morphology of a basin based on circularity and elongation ratio, its hydrological and geomorphic characteristics can be effectively assessed.\u003c/p\u003e \u003cp\u003eIn addition to analysing the drainage network, this research also evaluated relief parameters in detail (Cazorzi et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Al-Saady et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Relief parameters are influenced by the combined effects of climate, lithology, and tectonic setting in understanding landform development and landscape evolution (Zheng et al. \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Singh \u003cem\u003eet al\u003c/em\u003e. 2025\u003cb\u003e).\u003c/b\u003e Such analysis can serve as a guide for future water resource management and environmental planning.\u003c/p\u003e \u003cp\u003eRainfall in a region plays an important role in shaping the streamflow, groundwater recharge, and geomorphic characteristics (Yan et al. \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Several studies indicate that the Western Ghat region underwent periodic uplift from the Middle Mesozoic to the Cenozoic era (Rajkumar \u003cem\u003eet al\u003c/em\u003e. 2017; R Mohamed 2019; Padmalal et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Scaria 2023). This mountain range acts as a natural barrier to the southwest monsoon winds, resulting in heavy orographic rainfall in the region. Consequently, rainfall is the primary water source for the MPRBs, with high stream flow during the monsoon season and reduced or seasonal flow during the dry period (Gunnel 1998; Das and Pardeshi \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e). Both the river basins have a significant presence of dykes, fault lines, and lineaments. These structures create favourable conditions for the infiltration of surface water into the subsurface layers. However, permeability is limited to some extent by the region\u0026rsquo;s predominantly basaltic lithology. As a result, there are limitations to groundwater storage capacity and potential (Doke et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Birajdar and Shaikh \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). On the contrary, in areas where alluvial deposits are found in large quantities, the infiltration capacity of the soil is relatively high. Such alluvial areas are mainly found in the lower reaches of rivers (Dobrovol\u0026rsquo;ski et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Kamali and Haghighi \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The narrow, sloping Western Ghat mountain range lies in the western part of both basins. This area is the source region of both the river basins. In contrast, the eastern part of the basin is mainly known as the Plateau region, which is characterised by a scattered pattern of dissected hills and slopes. In this plateau region, mechanical weathering processes are active and strongly influenced by heat, wind, and precipitation (Ye \u003cem\u003eet al\u003c/em\u003e. 2025; Zeng \u003cem\u003eet al\u003c/em\u003e. 2025). At the same time, slope processes, especially hill-slope and denudational processes, are occurring rapidly. Since the action of these processes is constantly changing in space and time, and based on hypsometric curve analysis, both river systems are in the old-to-mature stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003ea, b) (Ayalew and Yamagishi \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Timalsina 2021; Mandal \u003cem\u003eet al\u003c/em\u003e. 2025). Therefore, analysing relief parameters in the MPRBs is important for understanding the landscape evolution of this region by clarifying the interrelationships among climate, lithology, structural control, and geomorphic processes.\u003c/p\u003e"},{"header":"9. Conclusions","content":"\u003cp\u003eRemote sensing and GIS technologies have emerged as powerful and reliable tools for geospatial and geomorphological analysis. The application of DEM has significantly enhanced the accuracy, reliability, and efficiency of watershed studies. Compared with conventional methods, these modern techniques provide a comprehensive framework for morphometric analysis in less time. Because river systems are widely distributed across the globe, except in polar and high-latitude regions, morphometric evaluation plays a significant role in effective watershed management and hydrological planning.\u003c/p\u003e \u003cp\u003eThe present study focuses on the morphometric analysis of the MPRBs of Maharashtra, India. The analysis reveals that the Mula River has a 7th-order drainage system, whereas the Pravara River has a 6th-order drainage system. The areal extent of the MRB is approximately 2900.6 km\u0026sup2;, whereas the PRB is about 2650.7 km\u0026sup2;. The dendritic drainage pattern observed in the study area reflects a relatively homogeneous geological structure and minimal structural control over channel development.\u003c/p\u003e \u003cp\u003eA comparative evaluation of the bifurcation ratio indicates higher values in the PRB, reflecting a greater influence of structural disturbances than in the MRB. Drainage density values are generally low, indicating the presence of hard-rock lithology with low permeability. However, the relatively higher drainage density in the PRB indicates steeper slopes and greater surface runoff, whereas the gentler slope of the MRB exhibits greater infiltration capacity. Evaluation of areal parameters, such as form factor, circularity ratio, and elongation ratio, confirms that the basins are elongated. These morphological characteristics indicate lower peak discharge during floods and promote more effective infiltration.\u003c/p\u003e \u003cp\u003eFurthermore, stream frequency and drainage texture analyses indicate a coarse drainage network with sparse vegetation cover under semi-arid climatic conditions. Despite this similarity, the PRBs drainage network is comparatively denser, reflecting variations in slope and runoff response. Relief-based parameters indicate that the terrain exhibits a moderate gradient, consistent with a moderately active erosional regime. The wandering ratio and sinuosity index indicate a moderate degree of channel meandering, reflecting a balance between lateral erosion and deposition. Moreover, the dissection index and hypsometric analysis indicate that the river systems have reached a mature-to-old geomorphic stage, characterised by reduced relief, slower surface runoff, and greater dominance of depositional processes. This stage represents an advanced phase in basin evolution.\u003c/p\u003e \u003cp\u003eOverall, the morphometric assessment results indicate a valuable interplay among climate, lithology, geomorphology, and tectonic controls governing basin development. The present study provides a scientific basis for future watershed management strategies, water conservation planning, and sustainable development initiatives within the study area.\u003c/p\u003e "},{"header":"Declarations","content":"\u003ch2\u003eEthics consent to participate and not consent to publish declaration\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eConflict of interest statement:\u003c/h2\u003e\n\u003cp\u003eThe authors reported no potential conflict of interest.\u003c/p\u003e\n\u003ch2\u003eFunding Declaration: \u003c/h2\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eMr. Vinod Gaikwad: Conceptualization, methodology, data curation, formal analysis, investigation, writing \u0026ndash; original draft preparation.Dr. Sanjay Navale: Supervision, validation, methodology refinement, critical review and editing of the manuscript.Ms. Ashwini Jadhav: Data collection, data curation, visualization, literature review, and assistance in manuscript preparation.Dr. Vasudev Salunke: Project administration, supervision, resources, and final review and approval of the manuscript.All authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThe authors sincerely thank Prof. Attila Ciner, Founding Editor-in-Chief of Mediterranean Geoscience Reviews, for his valuable guidance, constructive suggestions, and support that helped improve the quality of this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdhikari S (2020) Morphometric analysis of a drainage basin: A study of Ghatganga River, Bajhang District, Nepal. 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Int J Earth Sci 114(2):333\u0026ndash;345. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00531-024-02487-7\u003c/span\u003e\u003cspan address=\"10.1007/s00531-024-02487-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Morphometry analysis, Geospatial Technique, Watershed management, Mula-Pravara River Basin, Maharashtra, India","lastPublishedDoi":"10.21203/rs.3.rs-9093116/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9093116/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study employs advanced geospatial techniques to conduct a comprehensive morphometric analysis of the Mula-Pravara River Basins (MPRBs) in Maharashtra, India, elucidating their geomorphic evolution and hydrological dynamics. The Shuttle Radar Topographic Mission- Digital Elevation Model (SRTM-DEM) data and GIS techniques were used to derive over 60 morphometric parameters, including linear, aerial, basin, and relief characteristics. These parameters were analysed to assess structural controls, erosion potential, and watershed behaviour. Results reveal distinct contrasts: the Mula River Basin (MRB) exhibits a mature 7th-order drainage network with higher infiltration capacity (If\u0026thinsp;=\u0026thinsp;4.80) and gentler slopes (5.75%). At the same time, the Pravara River Basin (PRB) displays stronger tectonic influence through elevated bifurcation (7.5\u0026deg;) and ruggedness indices (MRn\u0026thinsp;=\u0026thinsp;28.99), coupled with greater runoff potential (Dd\u0026thinsp;=\u0026thinsp;2.1 km/km\u0026sup2;). Both basins exhibit elongated profiles (Re\u0026thinsp;=\u0026thinsp;0.29\u0026ndash;0.32) and youthful-to-mature characteristics, with hypsometric integrals (HI\u0026thinsp;=\u0026thinsp;0.26\u0026ndash;0.29) indicating advanced erosional maturity. Longitudinal profiles highlight knick points associated with Deccan basalt lithology, whereas meandering patterns reflect shifting fluvial regimes. The study underscores the PRBs\u0026rsquo; heightened vulnerability to flash floods and erosion, providing critical insights for sustainable watershed management. This integrated approach demonstrates the efficacy of GIS and remote sensing in decoding landscape evolution and guiding resilience-focused planning in semi-arid fluvial systems.\u003c/p\u003e","manuscriptTitle":"Morphometric Signature and Geomorphic Attributes of the Mula and Pravara River Basins (Maharashtra, India)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-26 05:55:59","doi":"10.21203/rs.3.rs-9093116/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5f174cfc-93fe-4768-831a-5e4c1bd792cb","owner":[],"postedDate":"March 26th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-16T13:23:23+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-26 05:55:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9093116","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9093116","identity":"rs-9093116","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}