Rendering Lineament Induced Stream alignment in Upper Krishna Basin, India: A Geospatial Approach

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Pardeshi, Sudhakar Pardeshi, Sumant Eknath Autade, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3363790/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Lineaments play an important role in drainage development, stream alignment and groundwater recharge. These are traced as surface or subsurface features. A linear feature that is associated with dislocation and deformation is known as lineament. The present study aimed to identify the influence of lineaments extracted from satellite images in the Upper Krishna River basin in India. Remote sensing datasets are considered the best option when using image enhancement techniques for extracting lineaments. Lineament studies are useful for groundwater and mineral exploration and also in the field of engineering geology. The availability of high-resolution satellite data and image processing techniques have rendered it further convenient to map lineaments. In the present study, lineaments were extracted from Sentinel–2 images with a resolution of 10 m, using various image processing techniques. A total of 1314 lineaments were extracted from the study area with a total length of 3983.44 km. The analysis of the extracted lineaments revealed that the lineament density was higher in the upper reaches of the basin, where the undulating hilly region is located in the Western Ghats. This finding implied that these regions have a high structural deformation and a higher groundwater infiltration potential. Moreover, approximately 15% of the total stream length was observed to be influenced by the lineaments. The maximum influence of lineaments was observed in the source region. The lineament extraction results of the present study would assist in understanding the geomorphology of this region and the structural control on the streams and groundwater potential zones, particularly as a contribution to water resource management in this region. Lineament Drainage network Upper Krishna basin DEM Sentinel-2 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1. Introduction Lineament extraction was performed manually until the introduction of the digital elevation model (DEM). However, lineament extraction from hardcopy geological maps or from aerial photo interpretation like observing linear features from the aerial photographs and interpreting visually was a time-consuming process and suffer from a high degree of subjectivity like it needs to be interpreted manually which may create an extra subject matter and it might get obstructed only up to the visible range of spectrum because of human eyesight limitation. The advent of remote sensing technology enabled the extraction of geological features, such as lineament, dike, and fracture zone from satellite images. The advancements in satellite technology, data processing, and data visualization techniques rendered it further convenient to extract lineaments. Lineament extraction and mapping are useful in various fields of scientific research and in-demand applications such as geographical information system (GIS) and remote sensing (RS) technology. Accordingly, remote sensing data also have wide applicability in geological mapping for various scientific research fields, such as geomorphology, geology, mineral exploration, etc. The present study is significant in understanding the geological setting and the structural deformation caused by lineaments, which would help to understand the influence of lineaments on the alignment of the drainage network. The present study is also important for improving the understanding of the level of structural control on landscape evolution in general and stream alignment in particular. Such studies also reveal the level of changes that have occurred in the drainage network due to structural deformation caused by lineaments. 1.1 Study Background: Hopkins mapped lineaments in 1841 and was a pioneer in describing the relationship between lineaments and topographical characteristics (Tiren, 2010). The term lineament was first used by Hobbs in 1904 to describe a linear characteristic that represented the ‘significant lines of a landscape’. Lineaments may include linear, lineation, geo-fracture, suture, mega fracture, and shear zones formed by several tectonic processes and the associated activitie (Rakshit et al., 1985), Lineament magnitude is a scale-dependent parameter it may range in the length from a few centimetres to kilometres and may vary from small as a cleavage in minerals to large as the inter-plate boundaries. The term lineament is, however, most often used for describing Earth’s unidirectional features of larger magnitude (Bhave et al., 1989). Lineament patterns might be correlated to the structural, geomorphic events and results of tectonic deformation. A lineament represents the features such as faults, fractures, master joints, axial plane fractures, dyke systems, long and linear lithologies, straight courses of streams, vegetation alignment, or topographic linearity (Basavarajappa et al., 2015). Until the last decade, researchers used aerial photogrammetry and topographic maps to extract lineaments manually. Since the availability of aerial photos is very limited and the process of extracting lineaments through photogrammetry is tedious, the satellite data such as the Digital Terrain Model (DTM) or high-resolution satellite images are also used when the objective of the study was limited to the geological aspec (Henderson et al. 1996; Chaabouni et al. 2012;Raj et al. 2017; Das and Pardeshi 2018;Das). In the late twentieth century, automatic lineament extraction techniques were developed, which enabled an improved approach to conduct several work (Zlatopolsky 1992;, Majumdar and Bhattacharya 1998;, Mostafa and Bishta 2005;, Costa and Starkey 2001). The automatic extraction process using GIS techniques has enabled the extraction of the geological surfaces and subsurface features and the subsequent integration of the derived information (Das et al., 2018). The major lineaments, faults, and fractures of a region may be identified and mapped through visual analysis of satellite images. Since the lineaments are straight and linear in nature, Digital Elevation Model (DEM) and satellite images have been applied widely for the identification and extraction of lineaments (Mathew and Ariffin, 2018; Das et al 2018). The mapping of the surface features of the Earth has become further convenient with the availability of huge amounts of remote sensing data and several image processing techniques, including the extensive use of various remote sensing databases and the GIS software for data (Qari 1991; Qari and Şen 1994; Chang et al.1998; Leech et al. 2003; Farina et al. 2005 Chandrasekhar et al. 2011; Teixeira et al. 2013; Das and Pardeshi 2018;). Digital Elevation Model (DEM) with the good spatial resolution is the key input for a GIS-based analysis of the lineaments and extraction of drainage networks. Digital Image Processing (DIP) and Geographic information system (GIS) are two important tools that enable a convenient, accurate, and efficient understanding and interpretation of geotectonic activities. In the present study, lineament extraction was performed using remote sensing data and GIS technology to understand the influence of lineaments on the drainage network in the upper Krishna River basin. The objective of the study was to signify the spatial distribution of the lineaments and their influence on the drainage network in the study region. 1.2 Study Area : The Upper Krishna River basin is located in the Deccan Volcanic Province of the Maharashtra plateau, on the eastern side of theWestern Ghats. The study area extended from 73°50´ E to 75°05´ E longitudes and 16°02´ N to 18°07´ N latitudes (Fig. 1 ). The total area of the Upper Krishna River basin is approximately 19331 km 2 . River Krishna and all its tributaries originate in the Western Ghats region, from where these flow in the North-West to South-East direction. The relief variation of the study area is 505 m to 1440 m above the MSL, which indicates steep to moderate relief. The Upper Krishna River basin is characterized by three major physical divisions: i) the Ghats, hills, and plateaus, ii) the foothill zones and iii) the plains. 1.3 Geology: The Upper Krishna River basin is formed on the Deccan trap lava flows of the Late Cretaceous Paleocene period. In certain regions of the river basin, extensive alluvium depositions of the Quaternary period are observed along the main river channel (Bondre et al., 2006). It is in these regions that agricultural practices are dominant. The broad classification of the geology of the Upper Krishna River basin is provided in Table 1 below. Table:1 The age and formation of the geology of the study area. Formation Age Alluvium Holocene Laterite Pleistocene to Holocene Deccan Basalt Upper Cretaceous to Lower Eocene Source: Geological Survey of India (1975) Alluvium Alluvium formations normally lay over the Deccan basalt and comprise loose to semi-consolidated material, such as sand, silt, gravels, clayey, etc. Certain isolated patches of recent alluvium depositions, which vary from 2 to 20 m in thickness, are also formed along the banks of the Krishna River and its major tributaries (Table 1). In total, there is 2% alluvium soil in the Upper Krishna River basin (GSDA, 1975). Laterite Laterite crusts are observed in the study area on the plateau top and the form of tableland with a reddish-brown colour and coarse texture. The laterite formation in the Panchgani region is well exposed (Fig. 2 ). This has been considered to have been developed on a large plain surface with a gentle gradient in the direction of southerly to southwesterly established on the sequence of the Cretaceous-Eocene Deccan lava flows (Sahasrabudhe and Deshmukh 1981). Deccan Basalt The maximum of the study area belongs to the Deccan trap geological formation of the Late Cretaceous-Paleocene period and comprises basalt rock. In the Deccan basalt region, two types of basalt rocks are present – one massive and the other vesicular basalt. In the study area occurrence of vesicular basalt is limited while massive basalts are common. The Deccan Basalt comprises various thicknesses, which are differentiated based on the presence of a red-bole, a weathered layer of basalt covered with dense basalt, and a vesicular basalt layer covered with dense basalt. In the study area, generally NNE- SSW lineaments are observed (Figs. 4 and 5 ). Similar observations are made by [ 20 ] . 1.4 Climate : The climate of the Upper Krishna River basin is of a tropical and sub-tropical monsoon type. The rainfall in the sub-basin region varies from 500 mm to 6208 mm as per IMD rainfall data for the period 1951 to 2015. The average annual rainfall recorded in the Upper Krishna River basin is 1300 mm. The temperature of the study area varies from 14°C in winter to 36°C in summer. The average annual mean temperature in this region is 28°C (IMD, 2020). 2. Database and Methodology The study focused mainly on lineament extraction and visualization of the influence of lineaments on the drainage network of a large river basin area. Therefore, satellite-derived data were required to obtain the output. Remote sensing technology serves as a concrete source for spatial data to be used as an input for GIS and generate a detailed map using other collateral data derived from different sources. A systematic analysis of a satellite image generally involves consideration of the image and terrain elements (Basavarajappa., 2014). In the present study, satellite images and DEM were used for the extraction of lineaments and the drainage network. These datasets were also utilized to visualize the terrain of the region and map the feature such as lineaments. The details regarding the data and methods used are as below (Fig. 3 ). 2.1 Lineament Extraction: In previous studies use of aerial photogrammetry was a common approach to identifying and extracting lineaments. Satellite images such as multispectral or digital elevation models and aerial photography are commonly used for lineament extraction in different studies, including those concerned with defining geological structures and tectonic activities. In several recent studies, DEM has been used for lineament extraction. In other recent studies, researchers have performed lineament extraction to ensure the mapping of the entire set of lineaments available for the study area (Abdullah et al.2010; Tahir et al. 2015; Muhammad and Awdal 2012; Raj et al. 2017; Das et al. 2018). To improve the interpretation and analysis, Digital Image Processing has been used together with various algorithms to enhance the surface or linear features. In the present study, edge detection, threshold setting, curve extraction, and principal component analysis (PCA) were used for image analysis (Satish 2002; Basavarajappa et al. 2015), Edge enhancement is useful for delineating the edges and sharpening the lineaments. Spatial filtering techniques were used to sharpen the images with linear features and edge-highlighting convolution methods were used. Finally, the PCA technique was used in the lineament extraction. Sentinel 2 Image data were downloaded, and atmospheric correction was performed on the retrieved data. Afterwards, the image data were processed for layer stacking and then converted to raster .tiff file format. The raster .tiff format files were then processed using the ENVI 5.0 software to generate PCA imageries, which were then exported with 8-bit grey-scale resolution in the GeoTIFF/TIFF file format. The automatic lineament extraction was performed using the PCI Geomatics 2016 software. The line module in the algorithm library was used for processing the final data product by running the lineament extraction command. The generated lineament map, depicted in Fig. 3 , was verified using the lineament data available on the Bhuvan portal of NRSC, India. 2.2 Lineament Orientation: The lineaments range in length from a few meters to tens of kilometres. Generally, they appear as a rectilinear feature based on the dip of the structural plane. It has been observed that all the lineament in the study area either meet almost perpendicular at large lengths or intersect each other or are parallel to each other. In total 1314 lineaments are identified (Fig. 4 ). The orientation of maximum lineaments is observed in the direction of NE 45° to SW 225° and minimum orientation in the direction of NW 345° - SE 165° (Fig. 5 ). 2.3 Stream Network Generation: Water tries to remain in equilibrium and follows the easiest way through the lineaments and fracture zones. In this process, lineaments act as conduits. This causes the water to follow a lineament course that is generally linearly aligned. To better understand the influence of lineament on stream behaviour, the pattern followed by the streams has to be analyzed, which is achieved by generating a stream network. In the present study, the stream network was generated using data from ASF-DEM, which had a spatial resolution of 12.5 m (Fig. 4 ). ASF-DEM provides high-resolution elevation data and therefore, results in better accuracy as well as better surface details in the outcomes of data analysis. The GIS software was then employed to process these data and generate the stream network in the following steps – ‘DEM fills’, ‘flow direction’, ‘flow accumulation’, ‘stream order’, and ‘raster calculation. In the ‘stream order’ step, Strahler’s (1952) method of ‘stream ordering’ was used. Next, the stream order raster was converted to the vector format for the analysis of the linear morphometric properties of the drainage network. 2.3 Streams Influenced by Lineaments: The streams influenced by lineaments were identified using a buffer tool. A buffer of 100 m was first drawn along the lineaments. The streams located within the buffer limits were considered as streams influenced by lineaments (Fig. 7 A and 7 B). These streams were selected and extracted for further analysis. The respective lengths of the influenced streams were calculated and separated according to the stream order. 3. Results and Discussion Lineament mapping and analysis were significant components of the present study. The parameters associated with lineaments and the number of streams influenced by lineaments, along with their respective lengths, are discussed below in detail. 3.1 Lineament analysis: The lineament analysis mainly included the categorization of lineaments based on their respective lengths, lineament density, and influence. 3.2 Lineament Categorization: A total of 1314 lineaments were identified for the study area in the present study. The total length of these lineaments was 3983.44 km. The identified lineaments were categorized into three groups based on their length. Among all lineaments identified, 998 lineaments were categorized into the dominant group of minor lineaments, for which the length ranged from 0.64 km to 3.55 km, thereby covering a total length of 1983.82 km (49.80%). The second dominant group of lineaments was the intermediate lineaments, with a length range of 3.59–8.88 km, covering a total length of 1386.94 km (34.82%). A total of 269 lineaments were categorized into this second dominant group. The third group was that of major lineaments, with a length range of 9.31–36.0 km and a total length of 612.68 km (15.36%). A total of 47 lineaments were categorized into this third group. The major lineaments are straight and control the streamflow. The intermediate lineaments are abundant along the regional strike. The minor lineaments are higher in number and smaller in magnitude, thereby forming a network across the study area (Table 2 ; Fig. 4 ). The orientation of lineaments and their impact on the orientation of streams is also an important outcome of this study. The majority of streams are influenced by the lineaments oriented in NNE to SSW and WNW to ESE directions. The second important direction of the lineaments that influenced the streams is NE to SW (Fig. 8 ). Other important direction of stream orientation is NW to SE. Table 2 Lineament categories are based on stream length. Lengthwise categories No. of Lineaments (%) Total length (km) (%) 0.64–3.55 (Minor) 998 75.95 1983.82 49.80 3.59–8.88 (Intermediate) 269 20.47 1386.94 34.82 9.31–36.0 (Major) 47 3.57 612.68 15.36 ∑1314 ∑100 ∑3983.44 ∑100 3.3 Analysis of the Influence of Lineaments on the drainage network: The study area was drained by streams of one to seventh order. The total length of all streams in the sub-basin region was 11145 km, of which approximately 1642.81 km of stream length of all orders was structurally controlled, i.e., it was influenced by lineaments (Fig. 7 B). Among all the streams influenced by lineaments, the first-, second-, and third-order streams received the maximum influence of (51.04%), (28.95%) and (11.09%) respectively (Fig. 6 ). This was mainly because of the loss of stream power, because of which the streams were not able to cross the structurally controlled threshold limit set by the lineaments. The streams from the fourth order to the seventh order received the minimum influence of (5.11%), (3.19%), (0.61%), and (0.003%) respectively. The fourth-, fifth-, and sixth-order streams exhibited minor lineament control, while those of the seventh-order exhibited negligible control by lineament (Table 3 ). This might be because of the increased water volume and stream power. Therefore, it was inferred that rather than following the structural control, these streams followed the slope of the terrain. The results of the present study distinctly indicated that the maximum influence of lineaments was exerted on the streams of the first, second, and third order all of which are located in the source region (Fig. 9 ). The influence of lineaments on the streams of the fourth order and higher was relatively lower and the influence became negligible for the streams of the seventh order. The structural control of lineaments on the streams could be observed distinctly by overlaying the extracted lineaments on the Koyna Dam region using the Google Earth Pro software (Fig. 10). Table 3 Influence of lineaments on the drainage network in the Upper Krishna River basin. Stream order Stream length influenced by lineaments (km) Total stream length influenced in (%) 1 838.47 51.04 2 475.75 28.95 3 182.19 11.09 4 83.92 5.11 5 52.39 3.19 6 10.03 0.61 7 0.06 .003 ∑ 1642.81 ∑ 100 4. Conclusion DEM comprising high-resolution data is an important dataset for analyzing structural landforms. DEM has been proven as a suitable input for lineament extraction. The results of the present study revealed that lineaments guided the flow of streams with low stream power. This was observed mainly for the streams of the lower order, including the streams of the first and second order, which together accounted for approximately 80% of the total length of the whole drainage network in the study area. The streams of the middle and higher orders were relatively less influenced by lineaments. The streams of the third, fourth and fifth order together accounted for only 20% of the influenced streams in terms of total length. In the case of third-order streams, less than 5% of stream length was controlled by lineaments. Negligible control of lineaments was observed on the streams of higher order. This could be attributed to the increased volume of water and steam power in higher-order streams. The water flow and stream power probably overcame the threshold of resistance caused due to the presence of lineaments. Therefore, based on the analysis of lineaments conducted in the present study, it was concluded that the influence of the structural control set by lineaments was higher on the lower-order streams compared to the higher-order streams. The present study used image analysis techniques for lineament extraction and the study of the influence of lineaments on streams. The change in the course of higher-order streams is mainly attributed to the control caused by the lineaments and the subsurface lithology. The structural complexity of a river basin renders it necessary to understand the level of influence of lineaments. In the present study, the influence of lineaments on lower-order streams was observed to have manifested mainly in the form of stream routing or alignment according to the orientation of the lineaments. The overall landscape development was also influenced by the dense network of lineaments. The findings of the present study are significant as they revealed the geological setting and its structural deformation caused by lineaments, which would, in turn, assist in further exploration of the drainage network and also in water resource management. The present study and other similar ones are important for improving the understanding of the level of structural control on landscape evolution in general and stream alignment in particular. Such studies also reveal the changes that have occurred in the drainage network due to structural deformation caused by lineaments. Declarations Acknowledgement The authors thankfully acknowledge the Indian Council of Social Science Research (ICSSR) New Delhi for supporting this research under the IMPRESS scheme. The authors are also thankful to the authorities of Pune District Education Association’s Prof. Ramkrishna More College Akurdi, Pune, and Department of Geography, Savitribai Phule Pune University, Pune. Conflict of Interest: On behalf of all authors, the corresponding author states that there is no conflict of interest. Data Availability Statement: The data used for the assessment of lineaments is available supplementary files section in the submission system. It is also available with the corresponding author on request. References Abdullah A., Akhir J.M., Abdullah I. (2010). Automatic mapping of lineaments using shaded relief images derived from digital elevation model (DEMs) in the Maran–Sungi Lemving area, Malaysia. EJGE 15:949–957 Basavarajappa H. T., Dinkar S., Satish M. V., Manjunatha M. C. (2015). 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Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 19 Nov, 2023 Reviews received at journal 29 Oct, 2023 Reviewers agreed at journal 23 Sep, 2023 Reviewers invited by journal 21 Sep, 2023 Editor assigned by journal 20 Sep, 2023 Submission checks completed at journal 20 Sep, 2023 First submitted to journal 17 Sep, 2023 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-3363790","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":234945210,"identity":"911155e0-3d3e-45c9-b00d-caf17e54594a","order_by":0,"name":"Suchitra S. Pardeshi","email":"","orcid":"","institution":"Prof. Ramkrishna More College (Affiliated to Savitribai Phule Pune University)","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Suchitra","middleName":"S.","lastName":"Pardeshi","suffix":""},{"id":234945211,"identity":"cb52c583-4925-4ce4-9a38-9b5eb3e04cba","order_by":1,"name":"Sudhakar Pardeshi","email":"","orcid":"","institution":"Savitribai Phule Pune University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sudhakar","middleName":"","lastName":"Pardeshi","suffix":""},{"id":234945212,"identity":"c851f6c5-de2b-4416-979c-8589da24324b","order_by":2,"name":"Sumant Eknath Autade","email":"","orcid":"","institution":"Sami Vivekanand Night College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sumant","middleName":"Eknath","lastName":"Autade","suffix":""},{"id":234945213,"identity":"ae754f73-255a-4d3d-a8ab-ae230d362477","order_by":3,"name":"Tushar Prakash Raut","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYHACNijN2HDwQwWQZmZuwKueB66FjbnxscQZkBZGorWwNxvwtkGsw6vFXiL92YOfe+7JG9xvbJOQnFcbzd8O1PKjYhtuWyRyzA17nhUbbjjG2CZRuO147ozDjA2MPWdu49PCJsFzIIERrEVy27HcBqAWZsY2fFrSn0n+OZBgD9bCO+dY7nzCWhLMpIG2JAK1AL3fUJO7gaCWM2/MpGUOJCTPPJYIDORjB3I3ArUcxOcX9nagw94cSLDtO3z8wcEPNXW5884fPvjgRwVuLejgMJg8QLR6IKgjRfEoGAWjYBSMEAAAPWFdjAYLKqQAAAAASUVORK5CYII=","orcid":"","institution":"Prof. Ramkrishna More College (Affiliated to Savitribai Phule Pune University)","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Tushar","middleName":"Prakash","lastName":"Raut","suffix":""}],"badges":[],"createdAt":"2023-09-17 17:29:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3363790/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3363790/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":43771730,"identity":"668670aa-960e-413c-8f18-eb120c2db940","added_by":"auto","created_at":"2023-09-27 14:34:28","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":360689,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLocation map of the study area. The major streams depicted in the figure are flowing in the North-West to South-East direction.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3363790/v1/b7b72248acece03f0d04da91.jpeg"},{"id":43771729,"identity":"db3ac5d2-49d5-4ffb-bd1f-c5a8116bc7af","added_by":"auto","created_at":"2023-09-27 14:34:27","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":368263,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGeological map of the study area. Source: (based on: www.gsi.gov.in)\u003c/strong\u003e\u003csup\u003e [21]\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3363790/v1/f4f304bed722684c1281ef36.jpeg"},{"id":43770738,"identity":"cc1f3312-0372-42d4-a0a0-461680cf7bc2","added_by":"auto","created_at":"2023-09-27 14:26:27","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":182677,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe methodology adopted in lineament extraction and interpretation\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3363790/v1/05ec3f883697433a609dce76.jpeg"},{"id":43770741,"identity":"ae82c67d-3ac2-4f9a-924f-900b53ea8563","added_by":"auto","created_at":"2023-09-27 14:26:28","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":445573,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLineament map of the study area.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3363790/v1/6c1503675f92fbf6e95f5350.jpeg"},{"id":43770739,"identity":"40512718-5fe8-4ac2-8ff1-954d5aa88c24","added_by":"auto","created_at":"2023-09-27 14:26:27","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":471349,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLineament Orientation Map of Study Area.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-3363790/v1/8b237d8292fba70ebd0c3543.png"},{"id":43773699,"identity":"9af37188-ffd6-4c25-b241-3218109af6ec","added_by":"auto","created_at":"2023-09-27 14:42:28","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":387695,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe methodology used for generating the stream network of the study area and these steps are usually followed to extract drainage network using DEM and also in the delineation of the watersheds. are the mandatory steps in the hydrological analysis tool\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3363790/v1/03069c169efaffef2bed4360.jpeg"},{"id":43770736,"identity":"2ea6ab0e-df10-439f-92f2-3b579f2c612d","added_by":"auto","created_at":"2023-09-27 14:26:27","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":716161,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA) Lineament density map of the study area. B) The streams infare luenced by lineaments in the Upper Krishna River Basin. The red segment indicates the streams that could be structurally controlled.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-3363790/v1/5d1ea7c7133b2b7e4e007194.png"},{"id":43770737,"identity":"4350ae25-f92a-4739-bbfe-d1a0a4abebc1","added_by":"auto","created_at":"2023-09-27 14:26:27","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":147409,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe rose diagram is used to depict streams and their orientation in a particular direction influenced by the lineaments and the orientation in a particular direction.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3363790/v1/351a745407f092de45b21b3f.jpeg"},{"id":43770744,"identity":"1d114aac-afa8-4ea6-9cae-b003c6f6f1af","added_by":"auto","created_at":"2023-09-27 14:26:28","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":42506,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe stream order vs. stream length graph illustrates the influence of lineaments on the length of the streams. It is distinctly visible that more streams of the lower order were influenced by lineaments compared to those of the higher order.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-3363790/v1/df804970172a29120d7fc5ca.png"},{"id":43770731,"identity":"ddc7d6ec-5251-4345-b0bd-193cf0a4ea7e","added_by":"auto","created_at":"2023-09-27 14:26:27","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":1746319,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe image shows an overlay of extracted lineaments on the Koyna Dam region using Google Earth Pro. The control of lineaments on the streams is distinctly visible. The streams are aligned according to the lineaments.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-3363790/v1/f19a24b2a0e51348b78ee335.png"},{"id":43775570,"identity":"f1c7ff63-7c42-4a4c-be1c-c69d9f41a177","added_by":"auto","created_at":"2023-09-27 14:50:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4599209,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3363790/v1/19f4ab3f-ef54-4075-b820-b39b52aa8542.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rendering Lineament Induced Stream alignment in Upper Krishna Basin, India: A Geospatial Approach","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLineament extraction was performed manually until the introduction of the digital elevation model (DEM). However, lineament extraction from hardcopy geological maps or from aerial photo interpretation like observing linear features from the aerial photographs and interpreting visually was a time-consuming process and suffer from a high degree of subjectivity like it needs to be interpreted manually which may create an extra subject matter and it might get obstructed only up to the visible range of spectrum because of human eyesight limitation. The advent of remote sensing technology enabled the extraction of geological features, such as lineament, dike, and fracture zone from satellite images. The advancements in satellite technology, data processing, and data visualization techniques rendered it further convenient to extract lineaments. Lineament extraction and mapping are useful in various fields of scientific research and in-demand applications such as geographical information system (GIS) and remote sensing (RS) technology. Accordingly, remote sensing data also have wide applicability in geological mapping for various scientific research fields, such as geomorphology, geology, mineral exploration, etc.\u003c/p\u003e \u003cp\u003eThe present study is significant in understanding the geological setting and the structural deformation caused by lineaments, which would help to understand the influence of lineaments on the alignment of the drainage network. The present study is also important for improving the understanding of the level of structural control on landscape evolution in general and stream alignment in particular. Such studies also reveal the level of changes that have occurred in the drainage network due to structural deformation caused by lineaments.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Study Background:\u003c/h2\u003e \u003cp\u003eHopkins mapped lineaments in 1841 and was a pioneer in describing the relationship between lineaments and topographical characteristics (Tiren, 2010). The term lineament was first used by Hobbs in 1904 to describe a linear characteristic that represented the \u0026lsquo;significant lines of a landscape\u0026rsquo;. Lineaments may include linear, lineation, geo-fracture, suture, mega fracture, and shear zones formed by several tectonic processes and the associated activitie (Rakshit et al., 1985), Lineament magnitude is a scale-dependent parameter it may range in the length from a few centimetres to kilometres and may vary from small as a cleavage in minerals to large as the inter-plate boundaries. The term lineament is, however, most often used for describing Earth\u0026rsquo;s unidirectional features of larger magnitude (Bhave et al., 1989). Lineament patterns might be correlated to the structural, geomorphic events and results of tectonic deformation. A lineament represents the features such as faults, fractures, master joints, axial plane fractures, dyke systems, long and linear lithologies, straight courses of streams, vegetation alignment, or topographic linearity (Basavarajappa et al., 2015).\u003c/p\u003e \u003cp\u003eUntil the last decade, researchers used aerial photogrammetry and topographic maps to extract lineaments manually. Since the availability of aerial photos is very limited and the process of extracting lineaments through photogrammetry is tedious, the satellite data such as the Digital Terrain Model (DTM) or high-resolution satellite images are also used when the objective of the study was limited to the geological aspec (Henderson et al. 1996; Chaabouni et al. 2012;Raj et al. 2017; Das and Pardeshi 2018;Das). In the late twentieth century, automatic lineament extraction techniques were developed, which enabled an improved approach to conduct several work (Zlatopolsky 1992;, Majumdar and Bhattacharya 1998;, Mostafa and Bishta 2005;, Costa and Starkey 2001). The automatic extraction process using GIS techniques has enabled the extraction of the geological surfaces and subsurface features and the subsequent integration of the derived information (Das et al., 2018).\u003c/p\u003e \u003cp\u003eThe major lineaments, faults, and fractures of a region may be identified and mapped through visual analysis of satellite images. Since the lineaments are straight and linear in nature, Digital Elevation Model (DEM) and satellite images have been applied widely for the identification and extraction of lineaments (Mathew and Ariffin, 2018; Das et al 2018). The mapping of the surface features of the Earth has become further convenient with the availability of huge amounts of remote sensing data and several image processing techniques, including the extensive use of various remote sensing databases and the GIS software for data (Qari 1991; Qari and Şen 1994; Chang et al.1998; Leech et al. 2003; Farina et al. 2005 Chandrasekhar et al. 2011; Teixeira et al. 2013; Das and Pardeshi 2018;). Digital Elevation Model (DEM) with the good spatial resolution is the key input for a GIS-based analysis of the lineaments and extraction of drainage networks. Digital Image Processing (DIP) and Geographic information system (GIS) are two important tools that enable a convenient, accurate, and efficient understanding and interpretation of geotectonic activities.\u003c/p\u003e \u003cp\u003eIn the present study, lineament extraction was performed using remote sensing data and GIS technology to understand the influence of lineaments on the drainage network in the upper Krishna River basin. The objective of the study was to signify the spatial distribution of the lineaments and their influence on the drainage network in the study region.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.2 \u003cb\u003eStudy Area\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eThe Upper Krishna River basin is located in the Deccan Volcanic Province of the Maharashtra plateau, on the eastern side of theWestern Ghats. The study area extended from 73\u0026deg;50\u0026acute; E to 75\u0026deg;05\u0026acute; E longitudes and 16\u0026deg;02\u0026acute; N to 18\u0026deg;07\u0026acute; N latitudes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The total area of the Upper Krishna River basin is approximately 19331 km\u003csup\u003e2\u003c/sup\u003e. River Krishna and all its tributaries originate in the Western Ghats region, from where these flow in the North-West to South-East direction. The relief variation of the study area is 505 m to 1440 m above the MSL, which indicates steep to moderate relief. The Upper Krishna River basin is characterized by three major physical divisions: i) the Ghats, hills, and plateaus, ii) the foothill zones and iii) the plains.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.3 Geology:\u003c/h2\u003e \u003cp\u003eThe Upper Krishna River basin is formed on the Deccan trap lava flows of the Late Cretaceous Paleocene period. In certain regions of the river basin, extensive alluvium depositions of the Quaternary period are observed along the main river channel (Bondre et al., 2006). It is in these regions that agricultural practices are dominant.\u003c/p\u003e \u003cp\u003eThe broad classification of the geology of the Upper Krishna River basin is provided in Table\u0026nbsp;1 below.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable:1 The age and formation of the geology of the study area.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlluvium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHolocene\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaterite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePleistocene to Holocene\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeccan Basalt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUpper Cretaceous to Lower Eocene\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSource: Geological Survey of India (1975)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAlluvium\u003c/strong\u003e \u003cp\u003eAlluvium formations normally lay over the Deccan basalt and comprise loose to semi-consolidated material, such as sand, silt, gravels, clayey, etc. Certain isolated patches of recent alluvium depositions, which vary from 2 to 20 m in thickness, are also formed along the banks of the Krishna River and its major tributaries (Table\u0026nbsp;1). In total, there is 2% alluvium soil in the Upper Krishna River basin (GSDA, 1975).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eLaterite\u003c/strong\u003e \u003cp\u003eLaterite crusts are observed in the study area on the plateau top and the form of tableland with a reddish-brown colour and coarse texture. The laterite formation in the Panchgani region is well exposed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This has been considered to have been developed on a large plain surface with a gentle gradient in the direction of southerly to southwesterly established on the sequence of the Cretaceous-Eocene Deccan lava flows (Sahasrabudhe and Deshmukh 1981).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDeccan Basalt\u003c/strong\u003e \u003cp\u003eThe maximum of the study area belongs to the Deccan trap geological formation of the Late Cretaceous-Paleocene period and comprises basalt rock. In the Deccan basalt region, two types of basalt rocks are present \u0026ndash; one massive and the other vesicular basalt. In the study area occurrence of vesicular basalt is limited while massive basalts are common. The Deccan Basalt comprises various thicknesses, which are differentiated based on the presence of a red-bole, a weathered layer of basalt covered with dense basalt, and a vesicular basalt layer covered with dense basalt. In the study area, generally NNE- SSW lineaments are observed (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Similar observations are made by\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1.4 \u003cb\u003eClimate\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eThe climate of the Upper Krishna River basin is of a tropical and sub-tropical monsoon type. The rainfall in the sub-basin region varies from 500 mm to 6208 mm as per IMD rainfall data for the period 1951 to 2015. The average annual rainfall recorded in the Upper Krishna River basin is 1300 mm. The temperature of the study area varies from 14\u0026deg;C in winter to 36\u0026deg;C in summer. The average annual mean temperature in this region is 28\u0026deg;C (IMD, 2020).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"2. Database and Methodology","content":"\u003cp\u003eThe study focused mainly on lineament extraction and visualization of the influence of lineaments on the drainage network of a large river basin area. Therefore, satellite-derived data were required to obtain the output. Remote sensing technology serves as a concrete source for spatial data to be used as an input for GIS and generate a detailed map using other collateral data derived from different sources. A systematic analysis of a satellite image generally involves consideration of the image and terrain elements (Basavarajappa., 2014). In the present study, satellite images and DEM were used for the extraction of lineaments and the drainage network. These datasets were also utilized to visualize the terrain of the region and map the feature such as lineaments.\u003c/p\u003e \u003cp\u003eThe details regarding the data and methods used are as below (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Lineament Extraction:\u003c/h2\u003e \u003cp\u003eIn previous studies use of aerial photogrammetry was a common approach to identifying and extracting lineaments. Satellite images such as multispectral or digital elevation models and aerial photography are commonly used for lineament extraction in different studies, including those concerned with defining geological structures and tectonic activities. In several recent studies, DEM has been used for lineament extraction. In other recent studies, researchers have performed lineament extraction to ensure the mapping of the entire set of lineaments available for the study area (Abdullah et al.2010; Tahir et al. 2015; Muhammad and Awdal 2012; Raj et al. 2017; Das et al. 2018).\u003c/p\u003e \u003cp\u003eTo improve the interpretation and analysis, Digital Image Processing has been used together with various algorithms to enhance the surface or linear features. In the present study, edge detection, threshold setting, curve extraction, and principal component analysis (PCA) were used for image analysis (Satish 2002; Basavarajappa et al. 2015), Edge enhancement is useful for delineating the edges and sharpening the lineaments. Spatial filtering techniques were used to sharpen the images with linear features and edge-highlighting convolution methods were used. Finally, the PCA technique was used in the lineament extraction.\u003c/p\u003e \u003cp\u003eSentinel 2 Image data were downloaded, and atmospheric correction was performed on the retrieved data. Afterwards, the image data were processed for layer stacking and then converted to raster .tiff file format. The raster .tiff format files were then processed using the ENVI 5.0 software to generate PCA imageries, which were then exported with 8-bit grey-scale resolution in the GeoTIFF/TIFF file format. The automatic lineament extraction was performed using the PCI Geomatics 2016 software. The line module in the algorithm library was used for processing the final data product by running the lineament extraction command. The generated lineament map, depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, was verified using the lineament data available on the Bhuvan portal of NRSC, India.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Lineament Orientation:\u003c/h2\u003e \u003cp\u003eThe lineaments range in length from a few meters to tens of kilometres. Generally, they appear as a rectilinear feature based on the dip of the structural plane. It has been observed that all the lineament in the study area either meet almost perpendicular at large lengths or intersect each other or are parallel to each other. In total 1314 lineaments are identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The orientation of maximum lineaments is observed in the direction of NE 45\u0026deg; to SW 225\u0026deg; and minimum orientation in the direction of NW 345\u0026deg; - SE 165\u0026deg; (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Stream Network Generation:\u003c/h2\u003e \u003cp\u003eWater tries to remain in equilibrium and follows the easiest way through the lineaments and fracture zones. In this process, lineaments act as conduits. This causes the water to follow a lineament course that is generally linearly aligned. To better understand the influence of lineament on stream behaviour, the pattern followed by the streams has to be analyzed, which is achieved by generating a stream network.\u003c/p\u003e \u003cp\u003eIn the present study, the stream network was generated using data from ASF-DEM, which had a spatial resolution of 12.5 m (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). ASF-DEM provides high-resolution elevation data and therefore, results in better accuracy as well as better surface details in the outcomes of data analysis. The GIS software was then employed to process these data and generate the stream network in the following steps \u0026ndash; \u0026lsquo;DEM fills\u0026rsquo;, \u0026lsquo;flow direction\u0026rsquo;, \u0026lsquo;flow accumulation\u0026rsquo;, \u0026lsquo;stream order\u0026rsquo;, and \u0026lsquo;raster calculation. In the \u0026lsquo;stream order\u0026rsquo; step, Strahler\u0026rsquo;s (1952) method of \u0026lsquo;stream ordering\u0026rsquo; was used. Next, the stream order raster was converted to the vector format for the analysis of the linear morphometric properties of the drainage network.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Streams Influenced by Lineaments:\u003c/h2\u003e \u003cp\u003eThe streams influenced by lineaments were identified using a buffer tool. A buffer of 100 m was first drawn along the lineaments. The streams located within the buffer limits were considered as streams influenced by lineaments (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). These streams were selected and extracted for further analysis. The respective lengths of the influenced streams were calculated and separated according to the stream order.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cp\u003eLineament mapping and analysis were significant components of the present study. The parameters associated with lineaments and the number of streams influenced by lineaments, along with their respective lengths, are discussed below in detail.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Lineament analysis:\u003c/h2\u003e \u003cp\u003eThe lineament analysis mainly included the categorization of lineaments based on their respective lengths, lineament density, and influence.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Lineament Categorization:\u003c/h2\u003e \u003cp\u003eA total of 1314 lineaments were identified for the study area in the present study. The total length of these lineaments was 3983.44 km. The identified lineaments were categorized into three groups based on their length. Among all lineaments identified, 998 lineaments were categorized into the dominant group of minor lineaments, for which the length ranged from 0.64 km to 3.55 km, thereby covering a total length of 1983.82 km (49.80%). The second dominant group of lineaments was the intermediate lineaments, with a length range of 3.59\u0026ndash;8.88 km, covering a total length of 1386.94 km (34.82%). A total of 269 lineaments were categorized into this second dominant group. The third group was that of major lineaments, with a length range of 9.31\u0026ndash;36.0 km and a total length of 612.68 km (15.36%). A total of 47 lineaments were categorized into this third group. The major lineaments are straight and control the streamflow. The intermediate lineaments are abundant along the regional strike. The minor lineaments are higher in number and smaller in magnitude, thereby forming a network across the study area (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The orientation of lineaments and their impact on the orientation of streams is also an important outcome of this study. The majority of streams are influenced by the lineaments oriented in NNE to SSW and WNW to ESE directions. The second important direction of the lineaments that influenced the streams is NE to SW (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e ). Other important direction of stream orientation is NW to SE.\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 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLineament categories are based on stream length.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLengthwise categories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo. of Lineaments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal length (km)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.64\u0026ndash;3.55 (Minor)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1983.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.59\u0026ndash;8.88 (Intermediate)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1386.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9.31\u0026ndash;36.0 (Major)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e612.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026sum;1314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026sum;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026sum;3983.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026sum;100\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=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Analysis of the Influence of Lineaments on the drainage network:\u003c/h2\u003e \u003cp\u003eThe study area was drained by streams of one to seventh order. The total length of all streams in the sub-basin region was 11145 km, of which approximately 1642.81 km of stream length of all orders was structurally controlled, i.e., it was influenced by lineaments (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). Among all the streams influenced by lineaments, the first-, second-, and third-order streams received the maximum influence of (51.04%), (28.95%) and (11.09%) respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). This was mainly because of the loss of stream power, because of which the streams were not able to cross the structurally controlled threshold limit set by the lineaments. The streams from the fourth order to the seventh order received the minimum influence of (5.11%), (3.19%), (0.61%), and (0.003%) respectively. The fourth-, fifth-, and sixth-order streams exhibited minor lineament control, while those of the seventh-order exhibited negligible control by lineament (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This might be because of the increased water volume and stream power. Therefore, it was inferred that rather than following the structural control, these streams followed the slope of the terrain.\u003c/p\u003e \u003cp\u003eThe results of the present study distinctly indicated that the maximum influence of lineaments was exerted on the streams of the first, second, and third order all of which are located in the source region (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). The influence of lineaments on the streams of the fourth order and higher was relatively lower and the influence became negligible for the streams of the seventh order. The structural control of lineaments on the streams could be observed distinctly by overlaying the extracted lineaments on the Koyna Dam region using the Google Earth Pro software (Fig.\u0026nbsp;10).\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 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInfluence of lineaments on the drainage network in the Upper Krishna River basin.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStream order\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStream length influenced by lineaments (km)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal stream length influenced in (%)\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\u003e838.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.04\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\u003e475.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.95\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\u003e182.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.09\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\u003e83.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.11\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\u003e52.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.19\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\u003e10.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.61\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\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026sum; 1642.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026sum; 100\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"},{"header":"4. Conclusion","content":"\u003cp\u003eDEM comprising high-resolution data is an important dataset for analyzing structural landforms. DEM has been proven as a suitable input for lineament extraction. The results of the present study revealed that lineaments guided the flow of streams with low stream power. This was observed mainly for the streams of the lower order, including the streams of the first and second order, which together accounted for approximately 80% of the total length of the whole drainage network in the study area. The streams of the middle and higher orders were relatively less influenced by lineaments. The streams of the third, fourth and fifth order together accounted for only 20% of the influenced streams in terms of total length. In the case of third-order streams, less than 5% of stream length was controlled by lineaments. Negligible control of lineaments was observed on the streams of higher order. This could be attributed to the increased volume of water and steam power in higher-order streams. The water flow and stream power probably overcame the threshold of resistance caused due to the presence of lineaments. Therefore, based on the analysis of lineaments conducted in the present study, it was concluded that the influence of the structural control set by lineaments was higher on the lower-order streams compared to the higher-order streams.\u003c/p\u003e \u003cp\u003eThe present study used image analysis techniques for lineament extraction and the study of the influence of lineaments on streams. The change in the course of higher-order streams is mainly attributed to the control caused by the lineaments and the subsurface lithology. The structural complexity of a river basin renders it necessary to understand the level of influence of lineaments. In the present study, the influence of lineaments on lower-order streams was observed to have manifested mainly in the form of stream routing or alignment according to the orientation of the lineaments. The overall landscape development was also influenced by the dense network of lineaments. The findings of the present study are significant as they revealed the geological setting and its structural deformation caused by lineaments, which would, in turn, assist in further exploration of the drainage network and also in water resource management. The present study and other similar ones are important for improving the understanding of the level of structural control on landscape evolution in general and stream alignment in particular. Such studies also reveal the changes that have occurred in the drainage network due to structural deformation caused by lineaments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thankfully acknowledge the Indian Council of Social Science Research (ICSSR) New Delhi for supporting this research under the IMPRESS scheme. The authors are also thankful to the authorities of Pune District Education Association’s Prof. Ramkrishna More College Akurdi, Pune, and Department of Geography, Savitribai Phule Pune University, Pune. \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn behalf of all authors, the corresponding author states that\u0026nbsp;\u003cstrong\u003ethere is no conflict of interest.\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used for the assessment of lineaments is available supplementary files section in the submission system. It is also available with the corresponding author on request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdullah A., Akhir J.M., Abdullah I. (2010). Automatic mapping of lineaments using shaded relief images derived from digital elevation model (DEMs) in the Maran\u0026ndash;Sungi Lemving area, Malaysia. EJGE 15:949\u0026ndash;957\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBasavarajappa H. T., Dinkar S., Satish M. V., Manjunatha M. C. (2015). Lineament extraction analysis for geotectonic implications around Biligiri-Rangan hill ranges in Southern Karnataka, India Using IRS-1D, LISS-III Image. Journal of Geomatics; vol\u0026nbsp;9 No. 2 October 2015.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBasavarajappa H.T, Pushpavathi K.N. and Manjunatha M.C. (2014). 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Program LESSA (lineament extraction and stripe statistical analysis) automated linear image features analysis experimental results. Comput Geosci 18(9):1121\u0026ndash;1126. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0098-3004(92)90036-Q\u003c/span\u003e\u003cspan address=\"10.1016/0098-3004(92)90036-Q\" 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":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-geoscience","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Geoscience](https://www.springer.com/journal/44288)","snPcode":"44288","submissionUrl":"https://submission.nature.com/new-submission/44288","title":"Discover Geoscience","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Lineament, Drainage network, Upper Krishna basin, DEM, Sentinel-2","lastPublishedDoi":"10.21203/rs.3.rs-3363790/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3363790/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLineaments play an important role in drainage development, stream alignment and groundwater recharge. These are traced as surface or subsurface features. A linear feature that is associated with dislocation and deformation is known as lineament. The present study aimed to identify the influence of lineaments extracted from satellite images in the Upper Krishna River basin in India. Remote sensing datasets are considered the best option when using image enhancement techniques for extracting lineaments. Lineament studies are useful for groundwater and mineral exploration and also in the field of engineering geology. The availability of high-resolution satellite data and image processing techniques have rendered it further convenient to map lineaments. In the present study, lineaments were extracted from Sentinel\u0026ndash;2 images with a resolution of 10 m, using various image processing techniques. A total of 1314 lineaments were extracted from the study area with a total length of 3983.44 km. The analysis of the extracted lineaments revealed that the lineament density was higher in the upper reaches of the basin, where the undulating hilly region is located in the Western Ghats. This finding implied that these regions have a high structural deformation and a higher groundwater infiltration potential. Moreover, approximately 15% of the total stream length was observed to be influenced by the lineaments. The maximum influence of lineaments was observed in the source region. The lineament extraction results of the present study would assist in understanding the geomorphology of this region and the structural control on the streams and groundwater potential zones, particularly as a contribution to water resource management in this region.\u003c/p\u003e","manuscriptTitle":"Rendering Lineament Induced Stream alignment in Upper Krishna Basin, India: A Geospatial Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-09-27 14:26:21","doi":"10.21203/rs.3.rs-3363790/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2023-11-20T01:24:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-10-29T16:51:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"b9700e0e-58b3-4561-b63c-284ffa68e7c3","date":"2023-09-23T18:19:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-09-21T11:02:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-09-20T11:33:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-09-20T11:32:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Geoscience","date":"2023-09-17T17:18:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-geoscience","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Geoscience](https://www.springer.com/journal/44288)","snPcode":"44288","submissionUrl":"https://submission.nature.com/new-submission/44288","title":"Discover Geoscience","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3fc33141-ce26-43fc-beaa-f3a9bbd14200","owner":[],"postedDate":"September 27th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-01-10T09:29:29+00:00","versionOfRecord":[],"versionCreatedAt":"2023-09-27 14:26:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3363790","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3363790","identity":"rs-3363790","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}