Exploring the Geological and Climatic Influences on Land Subsidence in Joshimath

Exploring the Geological and Climatic Influences on Land Subsidence in Joshimath | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exploring the Geological and Climatic Influences on Land Subsidence in Joshimath R. Bhatla, Deepak Kumar Raj, Richa Singh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4274910/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The town of Joshimath, situated in the Chamoli district of Uttarakhand and is located in a fragile Himalayan ecosystem which is highly prone to land subsidence due to its geological features. This study evaluates the climatic factors driving the subsidence problem in Joshimath by analysing rainfall data and geological data. The Normalized Difference Vegetation Index (NDVI) analysis for the years 2000, 2011, and 2022 revealed a declining trend in vegetation cover over time, indicating deforestation which suggests a reduction in soil-binding capacity due to the absence of tree and plant roots acting as anchors. The Land Use Land Cover (LULC) map for 2022 further substantiated this observation, with 35.8% of the area classified as rangeland, implying a lack of soil-binding vegetation cover. Rainfall data analysis unveiled an increasing trend in heavy precipitation events, particularly during the monsoon months (June-September). The frequency and intensity of these heavy downpours have escalated in recent years, contributing to soil erosion, water accumulation, and diminished soil stability. The combination of deforestation, heavy rainfall, and reduced soil-binding capacity has created a perfect storm for land subsidence in Joshimath. This research sheds light on the critical role of climatic factors, particularly changes in precipitation patterns and vegetation cover, in facilitating land subsidence in the ecologically sensitive Joshimath region. Understanding these dynamics is crucial for developing effective mitigation strategies, implementing sustainable land management practices, and ensuring the long-term stability of this Himalayan area. LULC( land use land cover) NDVI( Normalized difference vegetative index) Aquifer Puncture soil subsidence Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1. Introduction Land subsidence is a gradual settling or sudden sinking of the earth's surface known as global geological hazard that have severe consequences results into severe damage to buildings, infrastructure, and agricultural land. Along with these, it has associated risk of massive flooding and soil erosion. According to the United States Geological Survey (USGS), land subsidence generally occurs due to the sudden removal or displacement of subsurface earth materials. This can be attributed to various factors, including groundwater scarcity, soil compaction, underground mining activities, and the natural compaction of soft sedimentary soils over time. The collapse or subsidence of land can arise from natural phenomena such as earthquakes, as well as human activities like the underground extraction of water, oil, gas, and minerals. These events are considered global geological hazards that can have severe consequences. However, climate change has been identified as a significant contributor to land subsidence events worldwide (Higgins et al., 2014). At a global scale, climate change has led to an increased frequency and intensity of extreme weather events, such as heavy rainfall, droughts, and heatwaves (IPCC, 2021). These climatic changes contribute to significant impact on soil dynamics, vegetation cover, and groundwater levels, which potentially influencing land subsidence (Rahmati et al. 2019 ). In particular, heavy precipitation events can cause soil erosion, water accumulation, and a reduction in soil stability, ultimately leading to subsidence (Bagheri et al. 2021). Unregulated groundwater pumping, driven by rapid urbanization and population growth, has been blamed for the constant collapse and subsidence of major cities like Jakarta, Indonesia, which are grappling with similar crises. In the Himalayan region, the effects of climate change have been particularly severe, with rapidly melting glaciers, changes in precipitation patterns, and an increased risk of natural disasters such as landslides and flash floods (Dimri et al. 2021 ). These changes have significant implications for the fragile mountain ecosystems and the communities residing in these areas. The Himalayan orogenic belt is a geological formation that has resulted from the continuous north-northeast movement of the Indian landmass towards the Eurasian landmass over millions of years. This tectonic plate movement led to the subduction of the Indian plate under the Eurasian plate, eventually causing a collision between the two landmasses, which gave rise to the majestic Himalayan Mountain range through an upheaval process. The Uttarakhand region of the Himalayas is home to approximately 850–900 glaciers, covering an extensive geographical area of around 2,900 sq. km. These glaciers, which have been receding over time, have left behind an enormous number of glacial debris at an altitude of around 2,400 m. The rocks and landforms in this region have undergone extensive metamorphism, thrusting, faulting, and folding, reflecting the complex geological evolution history of the Himalayas. The Kunwari Pass area in the central Himalayas is the source of several streams, including the Daknala, Kalmanatha, Patalganga, Berakuchi, and Garuruganga, which are known for causing devastating flash floods due to landslide-induced blockages (Srivastava et al., 2013 ). The composition of these streams is structurally controlled, with the Munshari and Vaikrita Thrusts playing a significant role in the geology of the region (Rawat et al., 2020 ). The sudden collapse of Bhenti (mountain front) in the Madhya Maheswari Valley, the recent flash floods in the Chamoli district in 2021, and the Bhagirathi and Alaknanda floods of the 1970s, which were triggered by glacial activities or debris blocking the river channels, ultimately leading to catastrophic flash floods. The town of Joshimath, located in the Chamoli district of Uttarakhand, is situated in a region that has been identified as highly susceptible to land subsidence due to its complex geological and climatic conditions (Patel et al. 2023 ). The area's steep terrain, loose soil composition, and proximity to the Himalayan fold and fault systems make it prone to seismic activities and terrain instability, which can trigger subsidence events (Rawat et al., 2020 ; Mishra Committee Report, 1976 ). In recent years, Joshimath has experienced an increasing trend in heavy rainfall events, particularly during the monsoon months (June-September) (Srivastava et al., 2013 ). This pattern is consistent with the broader regional and global trends of climate change-induced changes in precipitation patterns. Additionally, the decline in vegetation cover, as evidenced by the decreasing Normalized Difference Vegetation Index (NDVI) values, suggests deforestation and reduced soil-binding capacity (Bhandari et al., 2021). Land subsidence can cause significant damage to buildings, infrastructure, and agricultural land, while also increasing the risk of flooding and soil erosion. This study aims to provide a comprehensive analysis of the climatic factors contributing to land subsidence in Joshimath by evaluating parameters such as rainfall data, vegetation cover changes, land use change and geological features. By analysing the interaction of factors such as terrain slope, soil composition, vegetation cover, rainfall patterns, drainage systems, and geological formations, the study aims to provide a holistic understanding of the complex dynamics contributing to soil subsidence in the Joshimath region. This understanding would aid in developing mitigation strategies and sustainable land management practices to address the subsidence risk and ensure the long-term stability of the area. 2. Data and Methodology 2.1 Study Area The Joshimath is taken as study area is a town located in the Chamoli district of Uttarakhand (Fig. 1 ), situated at an elevation of 1,890 meters above sea level (30.550552°N, 79.565964°E) (Chakraborty et al., 2021 ). It lies in the northeastern part of the Chamoli district, which is bounded by the Tethyan Himalayas to the north, northwest, east, and northeast (Rautela and Lakhera, 2000 ). Geologically, the Joshimath area belongs to the Lesser Himalayas and is located in the tectonic foredeep (Rawat et al., 2020 ). The Lesser Himalayas in this region are composed of rocks such as fanglomerates, quartzite, phyllite, and low-grade shale, ranging from greenschist to lower amphibolite facies (Srivastava et al., 2013 ; Rawat et al., 2020 ). The Joshimath Formation itself comprises pelitic compositions of quartz-muscovite-biotite-garnet-kyanite ± plagioclase and quartz-muscovite-biotite-kyanite + fibrolite (-plagioclase), as well as quartzofeldspathic compositions of quartz-K feldspar-plagioclase-biotite-muscovite (Rawat et al., 2020 ). The area falls under seismic zone V, which is a very high damage risk zone, and is also considered a vividly settled landslide zone due to the relatively soft and unstable lithology (Mishra Committee Report, 1976 ; Rautela and Lakhera, 2000 ). Joshimath's proximity to the Himalayan region makes it prone to folding, faulting, and landslide and subsidence activities, as the lithology and geological processes acting on the area led to such catastrophic events (Chakraborty et al., 2021 ). Besides these Joshimath town is located on an ancient landslide debris zone, making the terrain inherently unstable. The area is characterized by highly jointed and fractured rocks, with low shear strength, increasing susceptibility to slope failures (Rawat et al., 2020 ). The presence of thrusts like the Munsiari Thrust and Vaikrita Thrust has caused significant deformation and destabilization of the terrain (Sajwan et al. 2018). The steep topography, highly fractured and weathered rock formations, tectonic activity, and heavy precipitation make the Joshimath region highly vulnerable to landslides and terrain instability issues (Pathak et al. 2016). Human activities like construction and deforestation have also been identified as contributing factors to the geohazard risk in this area. 2.2 Methodology: The study utilized various data sources, including Landsat satellite imagery, meteorological data (rainfall records), digital elevation models (DEMs), and land use/land cover (LULC) data from ESRI. The satellite imagery and other spatial data were pre-processed for tasks such as band sub setting, atmospheric correction, and resampling/reprojection to ensure consistency and compatibility. Several spatial analyses were performed, including NDVI calculation to assess vegetation cover, LULC classification, terrain analysis (slope, aspect), and hydrology mapping to delineate drainage networks. Remote sensing data from Landsat 4, 5, and 8 satellites were utilized, for calculating the Normalized Difference Vegetation Index (NDVI) and Digital Elevation Models (DEMs). NDVI maps were generated for the years 2000, 2011, and 2022 to assess the spatial and temporal patterns of vegetation health, which plays a crucial role in soil stability. The pre-processed data and derived spatial layers were integrated and analysed within a GIS environment (ArcGIS) using overlay analysis techniques. The outputs from the spatial analyses were interpreted, and patterns and trends related to land subsidence were identified. Hydrology mapping was performed using ArcGIS, involving the calculation of flow direction, flow accumulation, snap pour points, and stream order to delineate the drainage network and potential areas of erosion. Terrain analysis was conducted to determine slope inclinations and hill shade values, providing insights into the topographic characteristics of the study area (Wen et al. 2018). Land Use Land Cover (LULC) data obtained from ESRI were integrated into the analysis. LULC maps were created and refined using ArcGIS, depicting various land cover categories such as built-up areas, vegetation, snow/ice cover, rangelands, valleys, and water bodies. These maps facilitated the assessment of land use patterns and their potential influence on soil stability and subsidence. The study utilized data from multiple sources, including the USGS Earth Explorer, Sentinel, and ESRI websites, to ensure a comprehensive understanding of the factors contributing to soil subsidence in the Joshimath region. By combining remote sensing, meteorological, and GIS data and techniques, this research aimed to provide a holistic analysis of the complex interplay between natural and anthropogenic factors shaping the soil dynamics in this ecologically sensitive Himalayan region. Additionally, meteorological data, specifically daily rainfall records from 1971 to 2022 for the Joshimath region, were analysed to understand the impact of rainfall on soil dynamics. The gridded rainfall data is gathered from India Meteorological Department (IMD) and then processed for analysis. The rainfall data is analysed for monthly averaged annual study for last twelve years since 2011 to 2022 and decadal analysis is done for five decades. Decadal analysis is represented in D1 (1970–1981), D2 (1980–1991), D3 (1990–2001), D4 (2000–2011) and D5 (2010–2022). 3. Results and Discussion The Joshimath area has an inclination angle ranging from 17 to 47 degrees, according to the slope analysis (Fig. 2 ) which indicate a topography that is particularly prone to landslides and soil instability. The region's weak soil composition makes slope failures and soil sinking even more dangerous. The region's unstable soil nature makes landslides and subsidence more likely to occur. The gravitational forces acting on soil and rock formations are increased on steep slopes, which increases their susceptibility to sliding and downward movement. This is especially true when combined with other destabilizing variables like intense rainfall or seismic activity. Joshimath's steep terrain makes landslides and other related risks like land subsidence extremely dangerous. A number of basins or catchment areas within the research region are delineated in Joshimath (Fig. 3 ). The regions from which water flows into a shared outlet or stream are represented by these basins. Different colours are used to delineate the basins, signifying different drainage systems. The topography and elevation data most likely define the basin boundaries, with ridgelines and high points serving as divisions between neighbouring basins. A dendritic drainage pattern is shown by the streams in Joshimath (Fig. 4 ), where numerous smaller streams and tributaries merge to form larger streams or rivers. Larger rivers or streams are shown by longer lines in the blue depiction of the streams. This dendritic pattern, which is typical of the Joshimath region, is prevalent in regions with generally uniform geology. A watershed is a section of land that empties into a common outlet, like a lake, river, or stream, all of the water that flows over or under it. The topography and drainage patterns serve as the basis for defining the watershed boundaries, which divide the areas that supply water to various outlets or streams (Band et al. 1989). A more thorough view of the stream network, including the hierarchy or stream order, can be found in Streams and Watershed (Fig. 4 ). The primary rivers or streams are shown by the thickest blue lines, whereas lesser tributaries and streams of lower order are shown by the thinner lines. It is possible to see where these streams converge, where smaller one’s merge with larger ones to form a larger river system. Considering that the studied area includes many watersheds, it is likely that the area's drainage system is complex, with different streams and rivers coming from different catchment areas. Hydrological analysis, water resource management, and evaluating the possible effects of land use changes or development on the drainage network and water flow patterns all depend on an understanding of the basin, stream, and watershed characteristics. The Joshimath region has a dendritic drainage pattern, as shown by the hydrology mapping (Figs. 3 and 4 ), with numerous streams and tributaries joining to form bigger rivers. Although carefully designed drainage systems can reduce erosion and landslides, any disruption or change to the natural drainage patterns can cause water to build up, flooding, and compaction of the soil, which raises the danger of subsidence. The Normalized Difference Vegetation Index (NDVI) analysis for the years 2000, 2011, and 2022 (Fig. 5 , 6 , and 7 ) demonstrated a declining trend in vegetation cover over time. The decreasing vegetation orientation suggests deforestation, leading to a reduction in soil-binding capacity due to the absence of tree and plant roots acting anchors for the soil. The decreasing vegetation orientation suggests deforestation, which reduces soil binding capacity due to the absence of tree and plant roots acting as anchor. Vegetation cover plays a crucial role in stabilizing soil and preventing erosion. The loss of vegetation due to deforestation reduces the soil's ability to bind and resist erosion forces, making it more susceptible to subsidence (Zhang et al. 2021). The declining NDVI values indicate a diminishing capacity of the soil to withstand subsidence, especially in the presence of other destabilizing factors like heavy rainfall or seismic activities. A declining pattern in vegetation cover over time was shown by the Normalized Difference Vegetation Index (NDVI) analysis for the years 2000, 2011, and 2022 (Fig. 5 , 6 , and 7 ). The presence of vegetation cover is essential for maintaining soil stability and halting erosion. Deforestation causes the soil to lose its ability to bind and withstand erosion forces, which increases the soil's susceptibility to subsidence. The NDVI values are showing a decline in the soil's ability to resist subsidence, particularly when other destabilizing variables such as intense rainfall or seismic activity are present. The 35.8% of the area is designated as rangeland on the Land Use Land Cover (LULC) map for 2022 (Fig. 10 ). This indicates a lack of vegetation cover that binds soil, which increases the area's susceptibility to soil subsidence. According to the LULC map for 2022 (Fig. 10 ), rangeland makes up a sizeable share (35.8%) of the research region. According to the NDVI analysis, the high proportion of rangelands suggests a lack of plant cover that binds soil, making the region more vulnerable to processes that cause soil erosion and subsidence (Table 1 ). Deep-rooted plants and thick vegetation—both necessary for stable soil—are rare in rangelands. This deficiency in soil-binding components makes soil erosion and sinking more likely, particularly after periods of intense rainfall or other disturbances. Heavy precipitation occurrences are on the rise, especially during the monsoon months of June through September, according to the rainfall data study (Figs. 8 and 9 ). Instability and soil erosion are caused in part by the increased frequency and intensity of these intense downpours. The stability of the soil and subsidence are significantly impacted by heavy rainfall occurrences. Heavy rainfall occurrences are on the rise, especially during the monsoon months of June through September, according to the rainfall data study (Figs. 8 and 9 ). Table 1 Showing the total area and its percentage for different land use characterisation Area Characterisation Sum of Area % Area Built up 1.43 0.03 Cloud Cover 1099.10 24.10 Rangeland 1633.78 35.80 snow 0.22 0.05 trees 310.38 6.80 valley 1507.98 33.04 water body 7.73 0.17 The rainfall data analysis (Figs. 8 and 9 ) demonstrates an increasing trend in heavy precipitation events, particularly during the monsoon months (June-September). The frequency and intensity of these heavy downpours have been on the rise, contributing to soil erosion and instability (Table 2 ). Heavy rainfall events have a significant impact on soil stability and subsidence. The rainfall data analysis (Figs. 8 and 9 ) demonstrates an increasing trend in heavy rainfall events, particularly during the monsoon months (June-September). The frequency and intensity of these heavy downpours have been on the rise, contributing to soil erosion and instability. Intense precipitation leads to water accumulation, soil saturation, and erosion, reducing the soil's bearing capacity and increasing the risk of subsidence. The observed increasing trend in heavy rainfall events, coupled with the effects of climate change, poses an additional threat to the already vulnerable Joshimath region, potentially exacerbating the land subsidence problem. Table 2 Monthly Averaged data of rainfall (IMD) Months 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Jan 0.81 2.27 2.47 0.32 1.90 0.24 1.43 0.78 3.72 4.69 0.98 1.88 Feb 3.25 0.84 7.23 3.13 2.85 0.72 0.40 0.44 5.02 0.66 0.74 2.35 March 0.47 2.71 1.07 2.25 3.09 1.80 2.95 1.13 1.19 4.91 0.91 1.14 April 1.56 1.07 0.68 1.84 1.20 0.43 3.36 3.20 3.56 1.75 2.79 1.23 May 2.11 0.23 0.48 2.37 0.98 4.04 6.29 3.14 0.96 4.67 7.57 2.22 June 7.49 1.01 17.27 1.90 6.69 11.85 10.79 8.97 2.46 5.02 14.74 5.26 July 8.94 8.48 18.33 13.98 13.39 22.95 19.30 17.83 9.01 14.53 12.89 13.66 Aug 12.97 18.18 15.20 11.03 9.45 20.96 16.49 21.91 17.45 21.72 10.88 12.36 Sept 3.20 3.61 4.82 2.68 1.40 7.49 9.38 8.13 11.85 3.06 10.16 3.55 Oct 0.12 0.01 1.10 1.25 0.66 1.06 0.02 0.00 0.63 0.00 4.73 1.32 Nov 0.02 0.00 0.04 0.00 0.03 0.00 0.02 0.51 1.39 0.55 0.02 0.01 Dec 0.16 0.38 0.00 2.20 0.09 0.05 1.04 0.02 2.70 0.28 0.61 1.23 The combination of steep slopes, loose soil composition, deforestation, and heavy rainfall events makes the Joshimath region highly susceptible to landslides and soil subsidence. The declining vegetation cover, as indicated by the NDVI analysis, reduces the soil's ability to bind and resist erosion, further exacerbating the subsidence risk (Jiang et al. 2022 ). The significant proportion of rangeland in the LULC map suggests a lack of soil-binding vegetation, which can contribute to soil instability and subsidence, especially during heavy downpour events or seismic activities. The increasing frequency and intensity of heavy rainfall, particularly during the monsoon season, can lead to soil erosion, water accumulation, and a reduction in soil bearing capacity, ultimately resulting in subsidence. The dendritic drainage pattern, while generally efficient in draining water, can be disrupted by human activities or natural events, leading to water pooling and soil compaction. Temperature fluctuations can also contribute to soil subsidence through thermal expansion and contraction of soil particles, changes in soil moisture content, and increased susceptibility to erosion and landslides. Additionally, groundwater extraction and aquifer puncturing can lower the water table, reducing soil support and leading to compaction and subsidence. Anthropogenic factors like groundwater overexploitation, can further exacerbate the soil subsidence problem in the Joshimath region. The Joshimath Aquifer Occurrence in 2009 and the Bone Chilling Lake Surge (GLOF) in 2021 exemplify the potential consequences of such events, causing significant damage to infrastructure, disrupting water supplies, and posing socio-economic challenges. To mitigate the risk of soil subsidence and ensure the long-term stability of the Joshimath region, a comprehensive approach is required, involving sustainable land management practices, afforestation efforts, responsible urban planning, groundwater regulation, and disaster preparedness measures. The findings of this study align with and complement previous research on land subsidence in the Himalayan region, particularly in the Joshimath area. The observed declining trend in vegetation cover, as indicated by the NDVI analysis, is consistent with the findings of Bhandari et al. (2021), who reported deforestation and vegetation loss in the Garhwal Himalayas, including Joshimath. This deforestation has led to a reduction in soil-binding capacity, increasing the susceptibility to soil erosion and subsequent subsidence, as also noted by Rautela and Lakhera ( 2000 ). The increasing trend in heavy precipitation events, particularly during the monsoon months, is consistent with the broader regional and global patterns of climate change-induced changes in precipitation patterns (Shrestha et al., 2015; IPCC, 2021). This trend has been observed in several studies conducted in the Himalayan region, including the work of Srivastava et al. ( 2013 ), who reported an increase in the frequency and intensity of extreme rainfall events. These heavy downpours can lead to soil erosion, water accumulation, and a reduction in soil stability, ultimately contributing to land subsidence, as documented in the present study and supported by the findings of Bru et al. (2013). 4. Conclusion The present study highlights the multifaceted nature of soil subsidence in the Joshimath region, where a combination of geographical, geological, and anthropogenic factors is contributing to this critical issue. The area's slanting terrain, with slopes ranging from 17 to 47 degrees, and the presence of loose, landslide-prone rock formations, make the region inherently susceptible to soil instability and subsidence. Furthermore, Joshimath's location in seismic zone V, associated with the folding and faulting processes of the Himalayan region, increases the risk of soil and rock movement, which can trigger subsidence events. The declining vegetation cover, as evidenced by the NDVI analysis, indicates a reduction in soil-binding capacity, exacerbating the subsidence risk, especially when coupled with heavy precipitation or seismic activities. The dendritic drainage pattern, while generally efficient for water drainage, can be disrupted by rapid urbanization and poor drainage management, leading to water accumulation, soil erosion, and subsequent subsidence. The LULC data shows a significant proportion of rangeland, further emphasizes the lack of soil-binding vegetation, compromising the area's natural capacity to withstand subsidence. Anthropogenic factors including groundwater overexploitation contribute to the subsidence problem, as demonstrated by incidents like the Joshimath Aquifer Occurrence in 2009 and the Bone Chilling Lake Surge (GLOF) in 2021 (Tiwari et al. 2018 ). The increasing frequency and intensity of heavy rainfall events, coupled with the effects of climate change, pose an additional threat, amplifying the risk of soil erosion and subsidence in the Joshimath region. To mitigate the risk of soil subsidence and ensure the long-term stability and sustainability of the Joshimath area, a comprehensive approach is required. This should involve sustainable land management practices, afforestation efforts to increase soil-binding vegetation, responsible urban planning, groundwater regulation, and disaster preparedness measures. Additionally, continuous monitoring and research are crucial to understand the dynamic interplay of factors contributing to soil subsidence and develop effective mitigation strategies. By addressing these issues proactively and implementing appropriate measures, the Joshimath region can be protected from the devastating consequences of soil subsidence, safeguarding the well-being of local communities and preserving the ecological integrity of this sensitive Himalayan environment. Declarations Funding Sources: The research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution R Bhatla developed the research idea, framed the manuscript and provided the flow in the manuscript and has subsequently supervised and modified the paper. Deepak Kumar Raj and Richa Singh has completed the data collection, analysis, plotting and written the manuscript. Acknowledgement: The authors would like to express their gratitude towards Banaras Hindu University for providing facilities to carry out research work. The authors also acknowledge IoE Grant (Scheme No. 6031) BHU to provide research grant. The authors acknowledge USGS, DIVA-GIS, IMD and other data source for providing data. Conflict of Interest: The authors declare that there is no conflict of interest associated with this publication. References Bagheri-Gavkosh, M., Hosseini, S. M., Ataie-Ashtiani, B., Sohani, Y., Ebrahimian, H., Morovat, F., & Ashrafi, S. (2021). Land subsidence: A global challenge. Science of The Total Environment, 778, 146193. Band, L. E. (1989). A terrain-based watershed information system. Hydrological Processes, 3 (2), 151–162. Bru, G., González, P. J., Mateos, R. M., Roldán, F. J., Herrera, G., Béjar-Pizarro, M., & Fernández, J. (2017). A-DInSAR monitoring of landslide and subsidence activity: A case of urban damage in Arcos de la Frontera, Spain. Remote Sensing, 9(8), 787. Chakraborty, A., Tiwari, S. K., & Pant, P. D. (2021). Landslide susceptibility mapping and risk assessment using geospatial techniques in Joshimath and Tapovan area, Garhwal Himalayas, India. Geomatics, Natural Hazards and Risk, 12(1), 3029–3050. Dimri, A. P., Allen, S., Huggel, C., Mal, S., Ballesteros-Canovas, J. A., Rohrer, M., … Pandey, A. (2021). Climate change, cryosphere and impacts in the Indian Himalayan Region. Current Science. Higgins, S. A. (2016). Advances in delta-subsidence research using satellite methods. Hydrogeology Journal, 24 (3), 587. IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, In press, doi: 10.1017/9781009157896 . Jiang, H., Fan, G., Zhang, D., Zhang, S., & Fan, Y. (2022). Evaluation of eco-environmental quality for the coal-mining region using multi-source data. Scientific Reports, 12 (1), 6623. Joshi, V., & Goyal, D. (2011). Aquifer water inflow in the under-construction Vishnugad Pipalkoti Hydro Electric Project in Garhwal Himalaya. Uttarakhand. Journal of the Geological Society of India, 78(1), 17–23. Mishra Committee Report (1976). Report of the Committee Constituted to Probe into the Causes of the Landslide at Joshimath, Uttar Pradesh. Patel, S. S., Routray, A., Dutta, D., Bhatla, R., Singh, V., & George, J. P. (2023). Studying the evolution of Uttarkashi cloudburst event from reanalysis datasets–A case study. Dynamics of Atmospheres and Oceans, 103, 101387. Pathak, D. (2016). Knowledge based landslide susceptibility mapping in the Himalayas. Geoenvironmental Disasters, 3, 1–11. Rahmati, O., Golkarian, A., Biggs, T., Keesstra, S., Mohammadi, F., & Daliakopoulos, I. N. (2019). Land subsidence hazard modeling: Machine learning to identify predictors and the role of human activities. Journal of Environmental Management, 236, 466–480. Rautela, P., & Lakhera, R. C. (2000). Landslide risk analysis between Ghat and Munsiari in Garhwal Himalayas. International Journal of Applied Earth Observation and Geoinformation, 2(3–4), 153–162. Rawat, M., Joshi, V., & Tiwari, G. C. (2020). Structural analysis of Munsiari Thrust and its 59–71. Sajwan, K. S. (2018). Assessment of land subsidence and mass wasting around lata-malla and bhatwari area, bhagirathi valley, Garhwal himalaya, Uttarakhand. International Journal of Basic and Applied Research, 8(7), 439–455. Srivastava, P., Tripathi, J. N., & Islam, T. (2013). Landslides of Uttarakhand Himalaya with special reference to flash floods of June 2013. International Journal of Geomatics and Geosciences, 4(1), 202–212. Tiwari, P. C., Tiwari, A., & Joshi, B. (2018). Urban growth in Himalaya: understanding the process and options for sustainable development. Journal of Urban and Regional Studies on Contemporary India, 4(2), 15–27. Wen, J., Liu, Q., Xiao, Q., Liu, Q., You, D., Hao, D., … Lin, X. (2018). Characterizing land surface anisotropic reflectance over rugged terrain: A review of concepts and recent developments. Remote Sensing , 10 (3), 370. Zhang, J., Wang, N., Wang, Y., Wang, L., Hu, A., Zhang, D., … Chen, J. (2021). Responses of soil erosion to land-use changes in the largest tableland of the Loess Plateau.Land Degradation & Development, 32(13), 3598–3613. 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-4274910","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":296224959,"identity":"a6ca9799-7f92-4dde-beba-5827b1eaf2bc","order_by":0,"name":"R. Bhatla","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAu0lEQVRIiWNgGAWjYDACCR4gUcAgZyAB4fMQp+WAAYMx6VoSN0gQ6y7z2b0HP38wsEvfLt1jwPCjhkHGnJAWmTvnkiUOGCTn7pxzxoCx5xgDj2UDIXdJ5BgAtTDnbriRY8DA28DAY3CAsBbjHwcM6tMNgFoY/xKpxQxoy+EEkBZm4myROWNmccbguOHOGWkFh2WOSRChRbrH+EZFRbW8uUTyxodvamzsCWpBAUDFRMfOKBgFo2AUjAJ8AACpRTrUR/N2WAAAAABJRU5ErkJggg==","orcid":"","institution":"Banaras Hindu University","correspondingAuthor":true,"prefix":"","firstName":"R.","middleName":"","lastName":"Bhatla","suffix":""},{"id":296224962,"identity":"6592f8a2-7a05-4c7f-981a-35258c8b466f","order_by":1,"name":"Deepak Kumar Raj","email":"","orcid":"","institution":"Banaras Hindu University","correspondingAuthor":false,"prefix":"","firstName":"Deepak","middleName":"Kumar","lastName":"Raj","suffix":""},{"id":296224965,"identity":"9c610d1b-d774-4e8e-ac7e-88f324e34a87","order_by":2,"name":"Richa Singh","email":"","orcid":"","institution":"Banaras Hindu University","correspondingAuthor":false,"prefix":"","firstName":"Richa","middleName":"","lastName":"Singh","suffix":""}],"badges":[],"createdAt":"2024-04-16 09:35:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4274910/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4274910/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55736451,"identity":"1f1f02d2-a8fd-4580-8969-e65d5978e9b1","added_by":"auto","created_at":"2024-05-02 12:30:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":82850,"visible":true,"origin":"","legend":"\u003cp\u003eStudy Area Map of Chamoli District and violet shaded part shows Joshimath\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4274910/v1/e6737105b3a33434cf5b6d9b.png"},{"id":55736453,"identity":"339fbd92-9bf4-4c26-89e0-30b746cd11eb","added_by":"auto","created_at":"2024-05-02 12:30:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":182763,"visible":true,"origin":"","legend":"\u003cp\u003eSlope of Joshimath in which green colour showing flat slope while red colour showing steep slope\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4274910/v1/7349a4e9aba794b278822ca9.png"},{"id":55736457,"identity":"1f680b20-dccf-469d-bdbe-a502c9eff87d","added_by":"auto","created_at":"2024-05-02 12:30:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":100592,"visible":true,"origin":"","legend":"\u003cp\u003eBasins in Joshimath\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4274910/v1/555753cd9b022ba999482991.png"},{"id":55736452,"identity":"6840ca5e-612e-4215-923d-3df6eb0e9427","added_by":"auto","created_at":"2024-05-02 12:30:29","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":94089,"visible":true,"origin":"","legend":"\u003cp\u003eStreams and Watershed\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4274910/v1/8bfb232165b3e3aa25c7537d.png"},{"id":55736458,"identity":"88deecd8-504e-4eab-bc8a-0744654b3cbe","added_by":"auto","created_at":"2024-05-02 12:30:30","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":169922,"visible":true,"origin":"","legend":"\u003cp\u003eNDVI for year 2000\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4274910/v1/e9f05378e3f760e9a08f4b8a.png"},{"id":55737091,"identity":"6b034306-5915-468a-ac34-c78cf4d5c90e","added_by":"auto","created_at":"2024-05-02 12:38:30","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":161582,"visible":true,"origin":"","legend":"\u003cp\u003eNDVI for year 2011\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4274910/v1/863c28a3eeb8f6c4cb9aba74.png"},{"id":55736454,"identity":"12eecf45-77b5-431d-a509-122a0aae6143","added_by":"auto","created_at":"2024-05-02 12:30:29","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":169935,"visible":true,"origin":"","legend":"\u003cp\u003eNDVI for year 2022\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4274910/v1/74b76141d65096b18c8f1575.png"},{"id":55737090,"identity":"460e7c6f-0e42-4f14-b97d-0bda428f1269","added_by":"auto","created_at":"2024-05-02 12:38:30","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":52209,"visible":true,"origin":"","legend":"\u003cp\u003eAnnual variation of average rainfall over the last decade in study area. The daily gridded rainfall data has been taken from IMD.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-4274910/v1/495443eb874f51b1ae415a26.png"},{"id":55736459,"identity":"3430cac1-c18b-43e8-8a8b-f0735c150acd","added_by":"auto","created_at":"2024-05-02 12:30:30","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":79348,"visible":true,"origin":"","legend":"\u003cp\u003eDecade wise average for each month.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-4274910/v1/b06f9ebe00f3dccf98b2f249.png"},{"id":55736460,"identity":"8d5cfe81-5ddb-454d-a2bf-385e048a2027","added_by":"auto","created_at":"2024-05-02 12:30:30","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":219578,"visible":true,"origin":"","legend":"\u003cp\u003eLULC map for year 2022 of Joshimath.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-4274910/v1/0501547f8cfdf330659778ae.png"},{"id":62053156,"identity":"3366ba33-b53e-49da-8358-c0634e61e0b4","added_by":"auto","created_at":"2024-08-08 18:30:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1562651,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4274910/v1/42ef5d2c-9526-4418-a2ca-1ba4c37239e4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring the Geological and Climatic Influences on Land Subsidence in Joshimath","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLand subsidence is a gradual settling or sudden sinking of the earth's surface known as global geological hazard that have severe consequences results into severe damage to buildings, infrastructure, and agricultural land. Along with these, it has associated risk of massive flooding and soil erosion. According to the United States Geological Survey (USGS), land subsidence generally occurs due to the sudden removal or displacement of subsurface earth materials. This can be attributed to various factors, including groundwater scarcity, soil compaction, underground mining activities, and the natural compaction of soft sedimentary soils over time. The collapse or subsidence of land can arise from natural phenomena such as earthquakes, as well as human activities like the underground extraction of water, oil, gas, and minerals. These events are considered global geological hazards that can have severe consequences. However, climate change has been identified as a significant contributor to land subsidence events worldwide (Higgins et al., 2014). At a global scale, climate change has led to an increased frequency and intensity of extreme weather events, such as heavy rainfall, droughts, and heatwaves (IPCC, 2021). These climatic changes contribute to significant impact on soil dynamics, vegetation cover, and groundwater levels, which potentially influencing land subsidence (Rahmati et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In particular, heavy precipitation events can cause soil erosion, water accumulation, and a reduction in soil stability, ultimately leading to subsidence (Bagheri et al. 2021). Unregulated groundwater pumping, driven by rapid urbanization and population growth, has been blamed for the constant collapse and subsidence of major cities like Jakarta, Indonesia, which are grappling with similar crises.\u003c/p\u003e \u003cp\u003eIn the Himalayan region, the effects of climate change have been particularly severe, with rapidly melting glaciers, changes in precipitation patterns, and an increased risk of natural disasters such as landslides and flash floods (Dimri et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These changes have significant implications for the fragile mountain ecosystems and the communities residing in these areas. The Himalayan orogenic belt is a geological formation that has resulted from the continuous north-northeast movement of the Indian landmass towards the Eurasian landmass over millions of years. This tectonic plate movement led to the subduction of the Indian plate under the Eurasian plate, eventually causing a collision between the two landmasses, which gave rise to the majestic Himalayan Mountain range through an upheaval process. The Uttarakhand region of the Himalayas is home to approximately 850\u0026ndash;900 glaciers, covering an extensive geographical area of around 2,900 sq. km. These glaciers, which have been receding over time, have left behind an enormous number of glacial debris at an altitude of around 2,400 m. The rocks and landforms in this region have undergone extensive metamorphism, thrusting, faulting, and folding, reflecting the complex geological evolution history of the Himalayas. The Kunwari Pass area in the central Himalayas is the source of several streams, including the Daknala, Kalmanatha, Patalganga, Berakuchi, and Garuruganga, which are known for causing devastating flash floods due to landslide-induced blockages (Srivastava et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The composition of these streams is structurally controlled, with the Munshari and Vaikrita Thrusts playing a significant role in the geology of the region (Rawat et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe sudden collapse of Bhenti (mountain front) in the Madhya Maheswari Valley, the recent flash floods in the Chamoli district in 2021, and the Bhagirathi and Alaknanda floods of the 1970s, which were triggered by glacial activities or debris blocking the river channels, ultimately leading to catastrophic flash floods. The town of Joshimath, located in the Chamoli district of Uttarakhand, is situated in a region that has been identified as highly susceptible to land subsidence due to its complex geological and climatic conditions (Patel et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The area's steep terrain, loose soil composition, and proximity to the Himalayan fold and fault systems make it prone to seismic activities and terrain instability, which can trigger subsidence events (Rawat et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mishra Committee Report, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1976\u003c/span\u003e). In recent years, Joshimath has experienced an increasing trend in heavy rainfall events, particularly during the monsoon months (June-September) (Srivastava et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This pattern is consistent with the broader regional and global trends of climate change-induced changes in precipitation patterns. Additionally, the decline in vegetation cover, as evidenced by the decreasing Normalized Difference Vegetation Index (NDVI) values, suggests deforestation and reduced soil-binding capacity (Bhandari et al., 2021). Land subsidence can cause significant damage to buildings, infrastructure, and agricultural land, while also increasing the risk of flooding and soil erosion.\u003c/p\u003e \u003cp\u003eThis study aims to provide a comprehensive analysis of the climatic factors contributing to land subsidence in Joshimath by evaluating parameters such as rainfall data, vegetation cover changes, land use change and geological features. By analysing the interaction of factors such as terrain slope, soil composition, vegetation cover, rainfall patterns, drainage systems, and geological formations, the study aims to provide a holistic understanding of the complex dynamics contributing to soil subsidence in the Joshimath region. This understanding would aid in developing mitigation strategies and sustainable land management practices to address the subsidence risk and ensure the long-term stability of the area.\u003c/p\u003e"},{"header":"2. Data and Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Area\u003c/h2\u003e \u003cp\u003eThe Joshimath is taken as study area is a town located in the Chamoli district of Uttarakhand (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), situated at an elevation of 1,890 meters above sea level (30.550552\u0026deg;N, 79.565964\u0026deg;E) (Chakraborty et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It lies in the northeastern part of the Chamoli district, which is bounded by the Tethyan Himalayas to the north, northwest, east, and northeast (Rautela and Lakhera, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Geologically, the Joshimath area belongs to the Lesser Himalayas and is located in the tectonic foredeep (Rawat et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The Lesser Himalayas in this region are composed of rocks such as fanglomerates, quartzite, phyllite, and low-grade shale, ranging from greenschist to lower amphibolite facies (Srivastava et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Rawat et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The Joshimath Formation itself comprises pelitic compositions of quartz-muscovite-biotite-garnet-kyanite\u0026thinsp;\u0026plusmn;\u0026thinsp;plagioclase and quartz-muscovite-biotite-kyanite\u0026thinsp;+\u0026thinsp;fibrolite (-plagioclase), as well as quartzofeldspathic compositions of quartz-K feldspar-plagioclase-biotite-muscovite (Rawat et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The area falls under seismic zone V, which is a very high damage risk zone, and is also considered a vividly settled landslide zone due to the relatively soft and unstable lithology (Mishra Committee Report, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Rautela and Lakhera, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Joshimath's proximity to the Himalayan region makes it prone to folding, faulting, and landslide and subsidence activities, as the lithology and geological processes acting on the area led to such catastrophic events (Chakraborty et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Besides these Joshimath town is located on an ancient landslide debris zone, making the terrain inherently unstable. The area is characterized by highly jointed and fractured rocks, with low shear strength, increasing susceptibility to slope failures (Rawat et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The presence of thrusts like the Munsiari Thrust and Vaikrita Thrust has caused significant deformation and destabilization of the terrain (Sajwan et al. 2018). The steep topography, highly fractured and weathered rock formations, tectonic activity, and heavy precipitation make the Joshimath region highly vulnerable to landslides and terrain instability issues (Pathak et al. 2016). Human activities like construction and deforestation have also been identified as contributing factors to the geohazard risk in this area.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Methodology:\u003c/h2\u003e \u003cp\u003eThe study utilized various data sources, including Landsat satellite imagery, meteorological data (rainfall records), digital elevation models (DEMs), and land use/land cover (LULC) data from ESRI. The satellite imagery and other spatial data were pre-processed for tasks such as band sub setting, atmospheric correction, and resampling/reprojection to ensure consistency and compatibility. Several spatial analyses were performed, including NDVI calculation to assess vegetation cover, LULC classification, terrain analysis (slope, aspect), and hydrology mapping to delineate drainage networks. Remote sensing data from Landsat 4, 5, and 8 satellites were utilized, for calculating the Normalized Difference Vegetation Index (NDVI) and Digital Elevation Models (DEMs). NDVI maps were generated for the years 2000, 2011, and 2022 to assess the spatial and temporal patterns of vegetation health, which plays a crucial role in soil stability. The pre-processed data and derived spatial layers were integrated and analysed within a GIS environment (ArcGIS) using overlay analysis techniques. The outputs from the spatial analyses were interpreted, and patterns and trends related to land subsidence were identified.\u003c/p\u003e \u003cp\u003eHydrology mapping was performed using ArcGIS, involving the calculation of flow direction, flow accumulation, snap pour points, and stream order to delineate the drainage network and potential areas of erosion. Terrain analysis was conducted to determine slope inclinations and hill shade values, providing insights into the topographic characteristics of the study area (Wen et al. 2018). Land Use Land Cover (LULC) data obtained from ESRI were integrated into the analysis. LULC maps were created and refined using ArcGIS, depicting various land cover categories such as built-up areas, vegetation, snow/ice cover, rangelands, valleys, and water bodies. These maps facilitated the assessment of land use patterns and their potential influence on soil stability and subsidence. The study utilized data from multiple sources, including the USGS Earth Explorer, Sentinel, and ESRI websites, to ensure a comprehensive understanding of the factors contributing to soil subsidence in the Joshimath region. By combining remote sensing, meteorological, and GIS data and techniques, this research aimed to provide a holistic analysis of the complex interplay between natural and anthropogenic factors shaping the soil dynamics in this ecologically sensitive Himalayan region. Additionally, meteorological data, specifically daily rainfall records from 1971 to 2022 for the Joshimath region, were analysed to understand the impact of rainfall on soil dynamics. The gridded rainfall data is gathered from India Meteorological Department (IMD) and then processed for analysis. The rainfall data is analysed for monthly averaged annual study for last twelve years since 2011 to 2022 and decadal analysis is done for five decades. Decadal analysis is represented in D1 (1970\u0026ndash;1981), D2 (1980\u0026ndash;1991), D3 (1990\u0026ndash;2001), D4 (2000\u0026ndash;2011) and D5 (2010\u0026ndash;2022).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cp\u003eThe Joshimath area has an inclination angle ranging from 17 to 47 degrees, according to the slope analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) which indicate a topography that is particularly prone to landslides and soil instability. The region's weak soil composition makes slope failures and soil sinking even more dangerous. The region's unstable soil nature makes landslides and subsidence more likely to occur. The gravitational forces acting on soil and rock formations are increased on steep slopes, which increases their susceptibility to sliding and downward movement. This is especially true when combined with other destabilizing variables like intense rainfall or seismic activity. Joshimath's steep terrain makes landslides and other related risks like land subsidence extremely dangerous. A number of basins or catchment areas within the research region are delineated in Joshimath (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The regions from which water flows into a shared outlet or stream are represented by these basins. Different colours are used to delineate the basins, signifying different drainage systems. The topography and elevation data most likely define the basin boundaries, with ridgelines and high points serving as divisions between neighbouring basins. A dendritic drainage pattern is shown by the streams in Joshimath (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), where numerous smaller streams and tributaries merge to form larger streams or rivers. Larger rivers or streams are shown by longer lines in the blue depiction of the streams. This dendritic pattern, which is typical of the Joshimath region, is prevalent in regions with generally uniform geology. A watershed is a section of land that empties into a common outlet, like a lake, river, or stream, all of the water that flows over or under it. The topography and drainage patterns serve as the basis for defining the watershed boundaries, which divide the areas that supply water to various outlets or streams (Band et al. 1989). A more thorough view of the stream network, including the hierarchy or stream order, can be found in Streams and Watershed (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The primary rivers or streams are shown by the thickest blue lines, whereas lesser tributaries and streams of lower order are shown by the thinner lines. It is possible to see where these streams converge, where smaller one\u0026rsquo;s merge with larger ones to form a larger river system. Considering that the studied area includes many watersheds, it is likely that the area's drainage system is complex, with different streams and rivers coming from different catchment areas. Hydrological analysis, water resource management, and evaluating the possible effects of land use changes or development on the drainage network and water flow patterns all depend on an understanding of the basin, stream, and watershed characteristics. The Joshimath region has a dendritic drainage pattern, as shown by the hydrology mapping (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), with numerous streams and tributaries joining to form bigger rivers. Although carefully designed drainage systems can reduce erosion and landslides, any disruption or change to the natural drainage patterns can cause water to build up, flooding, and compaction of the soil, which raises the danger of subsidence.\u003c/p\u003e \u003cp\u003eThe Normalized Difference Vegetation Index (NDVI) analysis for the years 2000, 2011, and 2022 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) demonstrated a declining trend in vegetation cover over time. The decreasing vegetation orientation suggests deforestation, leading to a reduction in soil-binding capacity due to the absence of tree and plant roots acting anchors for the soil. The decreasing vegetation orientation suggests deforestation, which reduces soil binding capacity due to the absence of tree and plant roots acting as anchor. Vegetation cover plays a crucial role in stabilizing soil and preventing erosion. The loss of vegetation due to deforestation reduces the soil's ability to bind and resist erosion forces, making it more susceptible to subsidence (Zhang et al. 2021). The declining NDVI values indicate a diminishing capacity of the soil to withstand subsidence, especially in the presence of other destabilizing factors like heavy rainfall or seismic activities. A declining pattern in vegetation cover over time was shown by the Normalized Difference Vegetation Index (NDVI) analysis for the years 2000, 2011, and 2022 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The presence of vegetation cover is essential for maintaining soil stability and halting erosion. Deforestation causes the soil to lose its ability to bind and withstand erosion forces, which increases the soil's susceptibility to subsidence. The NDVI values are showing a decline in the soil's ability to resist subsidence, particularly when other destabilizing variables such as intense rainfall or seismic activity are present.\u003c/p\u003e \u003cp\u003eThe 35.8% of the area is designated as rangeland on the Land Use Land Cover (LULC) map for 2022 (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). This indicates a lack of vegetation cover that binds soil, which increases the area's susceptibility to soil subsidence. According to the LULC map for 2022 (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e), rangeland makes up a sizeable share (35.8%) of the research region. According to the NDVI analysis, the high proportion of rangelands suggests a lack of plant cover that binds soil, making the region more vulnerable to processes that cause soil erosion and subsidence (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Deep-rooted plants and thick vegetation\u0026mdash;both necessary for stable soil\u0026mdash;are rare in rangelands. This deficiency in soil-binding components makes soil erosion and sinking more likely, particularly after periods of intense rainfall or other disturbances. Heavy precipitation occurrences are on the rise, especially during the monsoon months of June through September, according to the rainfall data study (Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Instability and soil erosion are caused in part by the increased frequency and intensity of these intense downpours. The stability of the soil and subsidence are significantly impacted by heavy rainfall occurrences. Heavy rainfall occurrences are on the rise, especially during the monsoon months of June through September, according to the rainfall data study (Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\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\u003eShowing the total area and its percentage for different land use characterisation\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArea Characterisation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSum of Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% Area\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuilt up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCloud Cover\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1099.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRangeland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1633.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esnow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etrees\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e310.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003evalley\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1507.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ewater body\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.17\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 \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe rainfall data analysis (Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e) demonstrates an increasing trend in heavy precipitation events, particularly during the monsoon months (June-September). The frequency and intensity of these heavy downpours have been on the rise, contributing to soil erosion and instability (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Heavy rainfall events have a significant impact on soil stability and subsidence. The rainfall data analysis (Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e) demonstrates an increasing trend in heavy rainfall events, particularly during the monsoon months (June-September). The frequency and intensity of these heavy downpours have been on the rise, contributing to soil erosion and instability. Intense precipitation leads to water accumulation, soil saturation, and erosion, reducing the soil's bearing capacity and increasing the risk of subsidence. The observed increasing trend in heavy rainfall events, coupled with the effects of climate change, poses an additional threat to the already vulnerable Joshimath region, potentially exacerbating the land subsidence problem.\u003c/p\u003e \u003ctable id=\"Tab2\" border=\"1\" style=\"margin-right: calc(33%); \"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMonthly Averaged data of rainfall (IMD)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eMonths\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eJan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e4.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eFeb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e3.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e7.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e3.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e5.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eMarch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e3.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e4.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eApril\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e3.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eMay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e4.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e6.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e7.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eJune\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e7.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e17.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e6.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e11.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e10.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e8.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e5.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e14.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e5.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eJuly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e8.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e8.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e18.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e13.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e13.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e22.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e19.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e17.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e9.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e14.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e12.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e13.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eAug\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e12.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e18.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e15.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e11.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e9.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e20.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e16.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e21.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e17.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e21.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e10.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e12.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eSept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e3.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e4.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e7.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e9.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e8.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e11.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e10.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e3.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eOct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e4.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eNov\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 10.687%;\"\u003e\n \u003cp\u003eDec\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e2.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" style=\"width: 7.4427%;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003cp\u003eThe combination of steep slopes, loose soil composition, deforestation, and heavy rainfall events makes the Joshimath region highly susceptible to landslides and soil subsidence. The declining vegetation cover, as indicated by the NDVI analysis, reduces the soil's ability to bind and resist erosion, further exacerbating the subsidence risk (Jiang et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The significant proportion of rangeland in the LULC map suggests a lack of soil-binding vegetation, which can contribute to soil instability and subsidence, especially during heavy downpour events or seismic activities. The increasing frequency and intensity of heavy rainfall, particularly during the monsoon season, can lead to soil erosion, water accumulation, and a reduction in soil bearing capacity, ultimately resulting in subsidence. The dendritic drainage pattern, while generally efficient in draining water, can be disrupted by human activities or natural events, leading to water pooling and soil compaction. Temperature fluctuations can also contribute to soil subsidence through thermal expansion and contraction of soil particles, changes in soil moisture content, and increased susceptibility to erosion and landslides. Additionally, groundwater extraction and aquifer puncturing can lower the water table, reducing soil support and leading to compaction and subsidence. Anthropogenic factors like groundwater overexploitation, can further exacerbate the soil subsidence problem in the Joshimath region. The Joshimath Aquifer Occurrence in 2009 and the Bone Chilling Lake Surge (GLOF) in 2021 exemplify the potential consequences of such events, causing significant damage to infrastructure, disrupting water supplies, and posing socio-economic challenges. To mitigate the risk of soil subsidence and ensure the long-term stability of the Joshimath region, a comprehensive approach is required, involving sustainable land management practices, afforestation efforts, responsible urban planning, groundwater regulation, and disaster preparedness measures. The findings of this study align with and complement previous research on land subsidence in the Himalayan region, particularly in the Joshimath area. The observed declining trend in vegetation cover, as indicated by the NDVI analysis, is consistent with the findings of Bhandari et al. (2021), who reported deforestation and vegetation loss in the Garhwal Himalayas, including Joshimath. This deforestation has led to a reduction in soil-binding capacity, increasing the susceptibility to soil erosion and subsequent subsidence, as also noted by Rautela and Lakhera (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). The increasing trend in heavy precipitation events, particularly during the monsoon months, is consistent with the broader regional and global patterns of climate change-induced changes in precipitation patterns (Shrestha et al., 2015; IPCC, 2021). This trend has been observed in several studies conducted in the Himalayan region, including the work of Srivastava et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), who reported an increase in the frequency and intensity of extreme rainfall events. These heavy downpours can lead to soil erosion, water accumulation, and a reduction in soil stability, ultimately contributing to land subsidence, as documented in the present study and supported by the findings of Bru et al. (2013).\u003c/p\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThe present study highlights the multifaceted nature of soil subsidence in the Joshimath region, where a combination of geographical, geological, and anthropogenic factors is contributing to this critical issue. The area's slanting terrain, with slopes ranging from 17 to 47 degrees, and the presence of loose, landslide-prone rock formations, make the region inherently susceptible to soil instability and subsidence. Furthermore, Joshimath's location in seismic zone V, associated with the folding and faulting processes of the Himalayan region, increases the risk of soil and rock movement, which can trigger subsidence events. The declining vegetation cover, as evidenced by the NDVI analysis, indicates a reduction in soil-binding capacity, exacerbating the subsidence risk, especially when coupled with heavy precipitation or seismic activities. The dendritic drainage pattern, while generally efficient for water drainage, can be disrupted by rapid urbanization and poor drainage management, leading to water accumulation, soil erosion, and subsequent subsidence. The LULC data shows a significant proportion of rangeland, further emphasizes the lack of soil-binding vegetation, compromising the area's natural capacity to withstand subsidence. Anthropogenic factors including groundwater overexploitation contribute to the subsidence problem, as demonstrated by incidents like the Joshimath Aquifer Occurrence in 2009 and the Bone Chilling Lake Surge (GLOF) in 2021 (Tiwari et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The increasing frequency and intensity of heavy rainfall events, coupled with the effects of climate change, pose an additional threat, amplifying the risk of soil erosion and subsidence in the Joshimath region. To mitigate the risk of soil subsidence and ensure the long-term stability and sustainability of the Joshimath area, a comprehensive approach is required. This should involve sustainable land management practices, afforestation efforts to increase soil-binding vegetation, responsible urban planning, groundwater regulation, and disaster preparedness measures. Additionally, continuous monitoring and research are crucial to understand the dynamic interplay of factors contributing to soil subsidence and develop effective mitigation strategies. By addressing these issues proactively and implementing appropriate measures, the Joshimath region can be protected from the devastating consequences of soil subsidence, safeguarding the well-being of local communities and preserving the ecological integrity of this sensitive Himalayan environment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding Sources:\u003c/h2\u003e \u003cp\u003eThe research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eR Bhatla developed the research idea, framed the manuscript and provided the flow in the manuscript and has subsequently supervised and modified the paper. Deepak Kumar Raj and Richa Singh has completed the data collection, analysis, plotting and written the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement:\u003c/h2\u003e \u003cp\u003eThe authors would like to express their gratitude towards Banaras Hindu University for providing facilities to carry out research work. The authors also acknowledge IoE Grant (Scheme No. 6031) BHU to provide research grant. The authors acknowledge USGS, DIVA-GIS, IMD and other data source for providing data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there is no conflict of interest associated with this publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBagheri-Gavkosh, M., Hosseini, S. M., Ataie-Ashtiani, B., Sohani, Y., Ebrahimian, H., Morovat, F., \u0026amp; Ashrafi, S. (2021). Land subsidence: A global challenge. Science of The Total Environment, 778, 146193.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBand, L. E. (1989). A terrain-based watershed information system. Hydrological Processes, \u003cem\u003e3\u003c/em\u003e(2), 151\u0026ndash;162.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBru, G., Gonz\u0026aacute;lez, P. J., Mateos, R. M., Rold\u0026aacute;n, F. J., Herrera, G., B\u0026eacute;jar-Pizarro, M., \u0026amp; Fern\u0026aacute;ndez, J. (2017). A-DInSAR monitoring of landslide and subsidence activity: A case of urban damage in Arcos de la Frontera, Spain. Remote Sensing, 9(8), 787.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChakraborty, A., Tiwari, S. K., \u0026amp; Pant, P. D. (2021). Landslide susceptibility mapping and risk assessment using geospatial techniques in Joshimath and Tapovan area, Garhwal Himalayas, India. Geomatics, Natural Hazards and Risk, 12(1), 3029\u0026ndash;3050.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDimri, A. P., Allen, S., Huggel, C., Mal, S., Ballesteros-Canovas, J. A., Rohrer, M., \u0026hellip; Pandey, A. (2021). Climate change, cryosphere and impacts in the Indian Himalayan Region. Current Science.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiggins, S. A. (2016). Advances in delta-subsidence research using satellite methods. Hydrogeology Journal, \u003cem\u003e24\u003c/em\u003e(3), 587.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. P\u0026eacute;an, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelek\u0026ccedil;i, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, In press, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/9781009157896\u003c/span\u003e\u003cspan address=\"10.1017/9781009157896\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiang, H., Fan, G., Zhang, D., Zhang, S., \u0026amp; Fan, Y. (2022). Evaluation of eco-environmental quality for the coal-mining region using multi-source data. Scientific Reports, \u003cem\u003e12\u003c/em\u003e(1), 6623.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoshi, V., \u0026amp; Goyal, D. (2011). Aquifer water inflow in the under-construction Vishnugad Pipalkoti Hydro Electric Project in Garhwal Himalaya. Uttarakhand. Journal of the Geological Society of India, 78(1), 17\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMishra Committee Report (1976). Report of the Committee Constituted to Probe into the Causes of the Landslide at Joshimath, Uttar Pradesh.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatel, S. S., Routray, A., Dutta, D., Bhatla, R., Singh, V., \u0026amp; George, J. P. (2023). Studying the evolution of Uttarkashi cloudburst event from reanalysis datasets\u0026ndash;A case study. Dynamics of Atmospheres and Oceans, 103, 101387.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePathak, D. (2016). Knowledge based landslide susceptibility mapping in the Himalayas. Geoenvironmental Disasters, 3, 1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRahmati, O., Golkarian, A., Biggs, T., Keesstra, S., Mohammadi, F., \u0026amp; Daliakopoulos, I. N. (2019). Land subsidence hazard modeling: Machine learning to identify predictors and the role of human activities. Journal of Environmental Management, 236, 466\u0026ndash;480.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRautela, P., \u0026amp; Lakhera, R. C. (2000). Landslide risk analysis between Ghat and Munsiari in Garhwal Himalayas. International Journal of Applied Earth Observation and Geoinformation, 2(3\u0026ndash;4), 153\u0026ndash;162.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRawat, M., Joshi, V., \u0026amp; Tiwari, G. C. (2020). Structural analysis of Munsiari Thrust and its 59\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSajwan, K. S. (2018). Assessment of land subsidence and mass wasting around lata-malla and bhatwari area, bhagirathi valley, Garhwal himalaya, Uttarakhand. International Journal of Basic and Applied Research, 8(7), 439\u0026ndash;455.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSrivastava, P., Tripathi, J. N., \u0026amp; Islam, T. (2013). Landslides of Uttarakhand Himalaya with special reference to flash floods of June 2013. International Journal of Geomatics and Geosciences, 4(1), 202\u0026ndash;212.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTiwari, P. C., Tiwari, A., \u0026amp; Joshi, B. (2018). Urban growth in Himalaya: understanding the process and options for sustainable development. Journal of Urban and Regional Studies on Contemporary India, 4(2), 15\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWen, J., Liu, Q., Xiao, Q., Liu, Q., You, D., Hao, D., \u0026hellip; Lin, X. (2018). Characterizing land surface anisotropic reflectance over rugged terrain: A review of concepts and recent developments. \u003cem\u003eRemote Sensing\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(3), 370.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang, J., Wang, N., Wang, Y., Wang, L., Hu, A., Zhang, D., \u0026hellip; Chen, J. (2021). Responses of soil erosion to land-use changes in the largest tableland of the Loess Plateau.Land Degradation \u0026amp; Development, 32(13), 3598\u0026ndash;3613.\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":"LULC( land use land cover), NDVI( Normalized difference vegetative index), Aquifer Puncture, soil subsidence","lastPublishedDoi":"10.21203/rs.3.rs-4274910/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4274910/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe town of Joshimath, situated in the Chamoli district of Uttarakhand and is located in a fragile Himalayan ecosystem which is highly prone to land subsidence due to its geological features. This study evaluates the climatic factors driving the subsidence problem in Joshimath by analysing rainfall data and geological data. The Normalized Difference Vegetation Index (NDVI) analysis for the years 2000, 2011, and 2022 revealed a declining trend in vegetation cover over time, indicating deforestation which suggests a reduction in soil-binding capacity due to the absence of tree and plant roots acting as anchors. The Land Use Land Cover (LULC) map for 2022 further substantiated this observation, with 35.8% of the area classified as rangeland, implying a lack of soil-binding vegetation cover. Rainfall data analysis unveiled an increasing trend in heavy precipitation events, particularly during the monsoon months (June-September). The frequency and intensity of these heavy downpours have escalated in recent years, contributing to soil erosion, water accumulation, and diminished soil stability. The combination of deforestation, heavy rainfall, and reduced soil-binding capacity has created a perfect storm for land subsidence in Joshimath. This research sheds light on the critical role of climatic factors, particularly changes in precipitation patterns and vegetation cover, in facilitating land subsidence in the ecologically sensitive Joshimath region. Understanding these dynamics is crucial for developing effective mitigation strategies, implementing sustainable land management practices, and ensuring the long-term stability of this Himalayan area.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e","manuscriptTitle":"Exploring the Geological and Climatic Influences on Land Subsidence in Joshimath","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-02 12:30:25","doi":"10.21203/rs.3.rs-4274910/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":"06f3b298-6c63-4a7f-8070-561209eb0bfd","owner":[],"postedDate":"May 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-08T18:22:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-02 12:30:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4274910","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4274910","identity":"rs-4274910","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}