https://orcid.org/0009-0004-6335-329X
Figures
Abstract
Effective soil and water conservation is critical in fragile watersheds prone to erosion. However, assessing erosion susceptibility in ungauged watersheds remains challenging due to the lack of observed hydrological data This study addresses this gap by employing a comprehensive morphometric analysis integrated with remote sensing (RS) and Geographic Information Systems (GIS) to prioritize erosion-prone sub-watersheds within the ecologically sensitive and data-scarce Urpash watershed. Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) data and ArcGIS 10.7 were used to analyze a 21.37 km² area. Key morphometric parameters—including linear, areal, and relief aspects—were assessed to understand watershed hydrology and erosion susceptibility. A total of 32 streams were identified, categorized into 1st to 3rd orders. Watershed shape indices, such as elongation ratio (Re = 0.65), form factor (Rf = 0.33) and circularity ratio (Rc = 0.295), indicate an elongated shape, indicative of reduced surface runoff and erosion potential, along with higher sub-soil permeability. However, drainage parameters like drainage density (Dd = 1.67 km/km2), stream frequency (Fs = 1.49 km-2) and drainage intensity (Di = 0.89 km-1) pointed to the watershed’s susceptibility to flooding, gully erosion, and landslides due to slow surface runoff dispersion. Relief parameters such as basin relief (H = 1742.87 m), relief ratio (Rh = 0.22) and ruggedness number (Rn = 2.9) reflect the watershed’s high relief and steep terrain, indicating a greater susceptibility to erosion. Using a compound parameter approach, the sub-watershed prioritisation ranked WS3 as the highest priority, followed by WS4, WS5, WS6, WS2, and WS1. By using RS and GIS-based morphometric analysis in an ungauged Urpash watershed, this study provides a geospatial framework for targeted soil and water conservation strategies, contributing to more precise watershed management in data-scarce and erosion-vulnerable regions.
Citation: Attar MI, Naseer S, Pandey Y, Khan JN, Bangroo SA, Hasan MA, et al. (2025) Morphometric analysis for prioritizing critical areas of Urpash watershed in Sindh catchment of the lesser Himalayas using RS and GIS approach. PLoS One 20(9): e0330503. https://doi.org/10.1371/journal.pone.0330503
Editor: Jamil Alexandre Ayach Anache, Escola de Engenharia de São Carlos da Universidade de São Paulo: Universidade de Sao Paulo Escola de Engenharia de Sao Carlos, BRAZIL
Received: December 4, 2024; Accepted: August 1, 2025; Published: September 12, 2025
Copyright: © 2025 Attar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper.
Funding: The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through a Large Research Project under grant number RGP2/195/46 (to MH).
Competing interests: The authors have declared that no competing interests exist.
Introduction
Watershed prioritization has become a crucial focus in hydrology and natural resource management, particularly in regions vulnerable to soil erosion and flooding [1,2]. Morphometric analysis, the quantitative assessment of a watershed’s physical characteristics [3], has emerged as an essential tool for understanding the geomorphology and hydrological behaviour of river basins [4,5]. By examining aspects such as size, shape, and relief, this approach helps identify erosion-prone areas and guide soil and water conservation efforts [6,7]. Due to the watershed’s significance as the fundamental unit in hydrology [8,9] and its ability to show the interaction of soil and water resources, morphometry at the basin level is preferred, rather than conducting it on isolated channels [10]. This preference arises from the fact that a watershed represents an area where the primary runoff is directed towards a singular outlet [11,12] and acts as a vital unit in hydrology and plays a crucial part in determining the Earth’s landscape and governing the flow of water across various terrains [10]. Morphometric features of a catchment encompass its measurable and physical attributes, representing inherent features [13]. Additionally, they play a pivotal role in prioritizing erosion-prone zones for optimal soil and water management [14]. The study of morphometric analysis within watersheds has garnered significant attention from researchers and environmentalists due to its potential to unravel the intricate relationships between landforms, hydrological processes, and ecological systems [15]. By quantitatively assessing various aspects of a watershed, morphometric analysis offers valuable insights into the basin’s geomorphological characteristics, making it a powerful tool for understanding the dynamic interactions that shape landscapes and influence environmental processes [16].
Research on morphometry has progressed significantly, utilizing both conventional [17–19] and advanced techniques such as Remote Sensing (RS) and Geographic Information Systems (GIS) [4,20–22]. However, RS and GIS techniques allow for more effective evaluation of drainage basin changes and offer greater flexibility in spatial information analysis [23]. Image interpretation techniques of RS save time compared to ground surveys and when combined with field investigations, produce valuable outcomes [24]. The process of prioritizing watersheds holds paramount importance within natural resource management systems [25]. Various researchers have undertaken morphometric analyses to prioritize critical subwatersheds in different regions worldwide. For instance, Balasubramanian et al. [26] focused on the lower Bhavani basin in Tamil Nadu, India; Nwilo et al. [27] conducted their study in the Imo River Basin; Nasir et al. [28] examined subwatersheds of the Swat River; Inyele et al. [29] investigated the Thiririka Watershed in Kenya; Shekar et al. [30] analyzed the Peddavagu River Basin in India and Topno et al. [31] studied the Rarhu watershed. These studies utilized morphometric analysis techniques to identify and prioritize areas vulnerable to soil erosion, contributing to the understanding and management of erosion risks in diverse geographical contexts. Additionally, land use changes significantly influence the morphometry of a watershed by altering drainage characteristics, runoff patterns, and erosion susceptibility. Several studies have explored these interactions using remote sensing and GIS techniques. Worachairungreung et al. [32] examined agricultural land loss by analyzing changes in land use and land cover, while Hassan et al. [33] assessed the effect of climate change on wetland areas in West Iraq using satellite data and GIS techniques. Furthermore, Rattanarat et al. [34] investigated how government policies influence land use and land cover changes over a 30-year period.
Despite significant advancements in watershed prioritization research, studies specifically addressing the ecologically fragile and ungauged Urpash watershed remain scarce. This region faces increasing environmental pressures, highlighting the urgent need to prioritize sub-watersheds for targeted conservation efforts. The lack of comprehensive research in the Urpash watershed further underscores the necessity for a detailed analysis. This study goes beyond conventional morphometric analysis by integrating erosion risk assessment through the Revised Universal Soil Loss Equation (RUSLE) model, thereby validating the prioritization derived from morphometric parameters. By employing both the compound parameter method [17] and RUSLE [35,36], the research ensures a more robust evaluation of sub-watershed vulnerability to erosion, enhancing the reliability of prioritization results. This novel approach not only bridges the knowledge gap in watershed prioritization for the Urpash watershed but also establishes a scientifically validated framework that can be applied to other ecologically sensitive and understudied regions. The findings aim to contribute to sustainable natural resource management and inform future conservation strategies.
Study area
The study focuses on the assessment of various morphometric features of the Urpash Watershed, located in the district of Ganderbal, J&K, India, covering an area of approximately 21.37 km². Fig 1 displays the location map of the basin. The region’s topography is characterized by diverse landforms, ranging from rugged mountainous terrain in the northeastern regions to gently rolling hills and plains in the southwestern. Mountain, grainy, karewa and soils rich in organic matter are the primary soil types present in the watershed and the predominant soil texture class found is clayey loam [36,37]. The watershed has 124 wet days on average every year, with an average rainfall of 1242 mm [36]. Regarding site access and permits, no specific permissions were required for conducting field checks in this study. The selection of the Urpash watershed was based on its fragile nature and susceptibility to erosion, making it a suitable candidate for morphometric and hydrological assessments. Since the study did not involve restricted or protected areas, nor did it require any interventions affecting the local environment, obtaining formal permits was not necessary.
The Urpash Watershed, entirely rural in nature, supports a diverse landscape dominated by agricultural land use, covering 7.81 km² (47.84%) of the total area, followed by evergreen forest, which occupies 4.74 km² (32.96%). Other significant land uses include barren land at 4.24 km² (38.32%), built-up areas covering 1.11 km² (32.27%), and orchards/horticulture, which span 1.07 km² (9.42%). Additional land use categories include maize fields at 1.06 km² (7.82%), mixed plantations at 0.20 km² (5.80%), scrubland at 0.81 km² (4.96%), and grassland/meadows at 0.19 km² (2.56%). Open forest and water bodies account for 0.15 km² (2.17%) and 0.02 km² (0.74%), respectively (Fig 2). Agriculture and horticulture, particularly apple and walnut production, along with crops like paddy, maize, and mustard, are central to the local economy.
Hydrologically, the Urpash Watershed is part of the Sindh River catchment, with the Urpash Canal (locally known as the Bijli Canal) serving as the principal watercourse traversing the area. The canal sustains diverse aquatic and terrestrial ecosystems within its riparian zones and is important in supplying water for residential and agricultural purposes. While no direct river discharge data is available for the canal, the region’s high average rainfall and the watershed’s small area contribute to its fast hydrological response, meaning rainwater reaches the main channel quickly due to limited travel distance [37]. Additionally, the watershed is enriched by several smaller streams and tributaries, contributing to its extensive hydrological network. Water demand in the Urpash Watershed is increasing due to agricultural expansion and population growth, leading to seasonal water shortages. Land use changes and climate variability further stress the ecosystem [32,34,38]. A geomorphological study is essential to assess the watershed’s characteristics and guide sustainable soil and water conservation efforts.
Materials and methods
SRTM DEM of 30m resolution and ArcGIS were employed for assessing various morphometric parameters. The choice of a 30m DEM is appropriate for a watershed of 21.37 km², as it provides a balanced resolution for capturing the necessary topographic details without overwhelming computational requirements. The DEM was further validated using SOI toposheets. This process involved aligning the DEM with the topographic features represented in the toposheets to correct any discrepancies and ensure that the digital elevation model accurately reflects the terrain. Additionally, any sinks within the DEM were identified and filled to prevent errors in hydrological analysis. The methodology adopted to evaluate various parameters is presented in Fig 3. The morphometric analysis starts with the creation of flow direction and flow accumulation maps (Fig 4 a, b) in ArcMap which are later used to obtain other parameters. By establishing a pour point for each sub-basin, the boundaries of the 6 subwatersheds were derived which are shown in Fig 4c. The pour point represents the specific spot in the basin where water from the entire basin converges and joins the primary stream.
In this study, several morphometric features that have been evaluated are presented in Table 1 along with their respective formulae and references. The selection of these parameters was guided by their proven relevance in influencing watershed hydrology, runoff characteristics, and soil erosion. Multicollinearity among the selected morphometric parameters was checked using correlation analysis to ensure that highly correlated parameters did not skew the results. Additionally, alternative parameter sets were tested to evaluate their impact on the outcomes, and the findings remained consistent, reinforcing the reliability of the chosen parameters. Finally, the identification of the priority of sub-basins was conducted using a compound parameter approach and RUSLE (Revised Universal Soil Loss Equation) model [36]. The reason for defining watershed prioritization classes is to identify critical areas most vulnerable to erosion, allowing for targeted conservation efforts. The rationale for choosing the compound parameter approach over other widely used prioritization techniques (e.g., Weighted Overlay Analysis, AHP, Fuzzy Logic, or MCDM) is grounded in its simplicity, transparency, and established application in morphometric studies [39,40]. In this study, the relevant linear, relief and areal parameters were selected to assess the critical areas of the Urpash watershed since these parameters influence the surface runoff and soil loss occurring in the watershed [41,42]. Linear and relief features have a direct influence on soil loss, with higher values indicating more erosion in a basin [43–45]. Conversely, areal/shape parameters demonstrate an inverse relationship with soil loss, with lower values signifying more erosion [46]. Accordingly, sub-watersheds with the highest values in linear and relief parameters are ranked first, followed by those with successively lower values. Conversely, sub-watersheds with the lowest values in areal/shape parameters are ranked first, with higher values receiving lower ranks [47,48]. Prioritisation using the RUSLE model was employed to evaluate the priority of sub-watersheds of Urpash based on soil loss values. These data sources, combined with limited field checks, have enabled us to capture crucial morphometric features, such as channel length, basin area, relief parameters, and drainage patterns. Understanding these features is vital for comprehending the geomorphological processes that influence the formation and dynamics of the watershed [49]. It is anticipated that the study’s findings will significantly contribute to the scientific understanding of watershed dynamics and guide policymakers and environmentalists in developing effective strategies for sustainable watershed management and conservation.
Results and discussion
Quantification of linear features
The linear morphometric characteristics are calculated in Table 2.
Stream order (u).
The initial step in the examination of the drainage basin is to designate stream orders [15,57]. Stream order is the ordinal designation given to a segment of a stream within a river network, determined by its placement in the hierarchical branching configuration of the drainage system [58]. Using Strahler’s method [59], the Urpash watershed is identified as a 3rd order basin exhibiting a dendritic drainage pattern, where higher stream orders signify greater discharge (Fig 5). This dendritic configuration indicates uniformity in the geological substrate and the absence of structural control [60,61].
(Source: generated from the data obtained from https://earthexplorer.usgs.gov/).
Stream number (Nu).
Stream number denotes the number of stream segments that exist in each order [62]. The results revealed that the Urpash watershed had 32 streams linked with all 3 orders covering an area of 21.37 km2. The majority of the total stream count (17) is comprised of 1st order streams while 2nd order constitutes 10 streams and 3rd order constitutes five streams. Hence, the principle that a lower stream order corresponds to a greater number of streams is consistently observed across the entire watershed [18,63]. A higher stream number is associated with lesser permeability and infiltration and vice-versa [20]. Moreover, watersheds with a higher number of first-order streams are more prone to flash flooding during intense rainfall events compared to those with fewer first-order streams [64].
Stream length (Lu).
Stream length represents the average length of streams within various orders present in a drainage basin [65]. The overall stream length of the Urpash watershed was found to be 35.80 km, in which the 1st order stream length was 20.80 km, the 2nd order length was 10.75 km and the 3rd order stream length was found to be 4.25 km. The study has shown that results adhere to Horton’s Law of Lu and Nu [18] (Fig 6), indicating that the shorter lengths of higher-order streams compared to lower-order streams suggest a steeper basin profile, which contributes to faster runoff within the watershed [66,67].
Mean stream length (Lsm).
Lsm, a dimension-based attribute, reveals the dimensions of elements within a drainage channel and the corresponding contributing areas [51]. In the Urpash watershed, the Lsm for first, second and third-order streams was calculated as 1.22, 1.07 and 0.85 respectively.
Stream length ratio (Lur).
The ratio of Lsm of a given order to the next higher order is defined as the stream length ratio [6]. Lur values of the Urpash watershed varied from 0.79–0.87, indicating that the watershed is in an early stage of geomorphic development [68].
Bifurcation ratio (Rb).
Rb is associated with the branching arrangement of the streams of the watershed. According to Schumm [52], it is calculated by dividing the sum of streams (Nu) of any order by the streams of the next higher order (Nu + 1). The Rb of the Urpash watershed varies from 1.7 to 2, with a mean bifurcation ratio of 1.85 which suggests less structural disturbance [69]. The slightly higher bifurcation ratio indicates the high overland flow and thus high erosion risk. In addition, high Rb values suggest an elongated shape, whereas lower values suggest a more circular or rounded shape [70,71]. This indicates that WS4, WS5, and WS6 experience relatively higher levels of disturbance compared to other sub-watersheds, while WS1 and WS2 are relatively more sustainable. Therefore, based on the Rb the Urpash watershed can be considered as a watershed which has a low to medium runoff generation potential.
Basin length (Lb).
Lb represents the greatest extent of the basin or displacement between stream confluence and the farthest point on the watershed boundary [72,73]. Employing ArcGIS 10.7, the computed basin length in our study area was found to be 8 km. Subsequently, the analysis revealed that within the subwatersheds, WS3 exhibited the highest Lb value at 4.54 km, while WS5 showcased the lowest value, measuring 2.92 km, suggesting that runoff water in WS5 would travel longer than other subwatersheds. These findings underscore the significant variability in basin length across different subwatersheds, highlighting potential implications for hydrological processes and land management strategies within the study area.
Quantification of areal parameters
The estimated areal morphometric features of Urpash are presented in Tables 3 and 4 respectively.
Basin area (A).
Watershed area (A) denotes the entirety of the land surface within a watershed projected onto a horizontal plane. The calculated basin area of the Urpash watershed using ArcGIS 10.7 software was obtained as 21.37 km2. Based on the area, WS3 had the largest area (5.18 km2) and WS6 was the smallest one (1.38 km2). The area of the basin stands as a paramount watershed attribute in drainage study as it directly correlates with the volume of water contained within the watershed [74,75]. Considering the relationship outlined between watershed area and other hydrological factors, larger watersheds such as WS1, WS3, and WS4 are expected to exhibit higher mean discharge and mean annual runoff [76], while smaller watersheds like WS2, WS5, and WS6 are anticipated to demonstrate lower values of these parameters.
Basin perimeter (P).
The perimeter defines the outer border of the watershed, encompassing its total area. It serves as an indicator of the watershed’s size and shape. The perimeter of the Urpash watershed using ArcGIS 10.7 was found to be 30.16 km. Subsequently, within the subwatersheds, WS1 exhibited the highest P value, while WS6 showcased the lowest value.
Elongation ratio (Re).
Re is the ratio of the diameter of a circle having the same areal extent as a study area to Lb of the study area [52,77]. The value of the Re in the Urpash was calculated as 0.65, which indicates the elongated shape of the Urpash watershed [67,78]. WS6 had the lowest Re value indicating its vulnerability while the remaining five subwatersheds exhibited similar Re values.
Circularity ratio (Rc).
Re represents the ratio of the watershed’s area to the area of a circle with a perimeter equal to that of the watershed [79,3]. It is influenced by factors such as stream length, geological formations, LULC, climatic conditions, stream frequency, topography, and watershed gradient. The value of Rc was found to be 0.295, which means Urpash is an elongated-shaped basin [80], implying low peaked runoff and reduced erosion potential [81]. Among the subwatersheds, WS1, WS4 and WS6 showed lower values of Rc, while the remaining subwatersheds exhibited higher values.
Form factor (Rf) and shape factor (Sf).
It is defined as the ratio of basin area (A) to basin length (Lb) [53]. The low Rf value of 0.33 indicates that the elongated shape of the Urpash watershed [51] results in lower runoff, a longer concentration time, and reduced susceptibility to flooding and erosion [82]. The Shape factor (Sf) which is defined as the reciprocal of Rf is also used to evaluate basin shapes, and its value was 2.995. The Rf values with the watershed are higher in WS5 and lower in the rest of the subwatersheds.
Drainage density (Dd).
Dd represents the ratio of the combined length of all streams within a watershed to the area of that watershed (km/km2) [53,3,83]. It indicates the proximity of drainage lines [13,84]. The assessment of drainage density serves as a valuable quantitative measure of surface-water flow and sediment potential from the watershed [85–87]. The lower Dd value of 1.67 km/km2 suggests that the Urpash watershed is either situated on erosion-resistant surfaces or has a highly permeable substratum, reducing surface runoff [50]. It ranged from 1.09 in WS5 to 2.36 in WS4. The drainage density map is displayed in Fig 7a.
Stream frequency (Fs).
It represents the total count of stream channels within a specified area [18,3]. Fs of the Urpash watershed was obtained as 1.49 km-2, which indicates rich vegetation cover. In this study, Fs ranged from 1.01 in WS5 to 2.17 in WS6. A direct correlation between Fs and Dd was observed [69]. Lower Fs and Dd values correspond to reduced runoff rates, consequently lower erosion risks.
Drainage intensity (Di).
It is defined as the ratio of Fs and Dd [54,3,83]. The calculated Di value of Urpash was 0.89 km-1. The low values of Dd, Fs and Di indicate that watershed runoff can not immediately be taken out which is the cause of Urpash being more prone to hazards such as soil loss, swamping and landslips.
Infiltration number (If).
It is the product of Dd and Fs and serves as an indicator of the infiltration characteristics of the basin [88,87,89]. The If of the Urpash watershed was estimated to be around 2.48 which indicates runoff will be low. The If values in the Urpash watershed ranged from 1.02 in WS5 and 4.10 in WS4.
Length of overland flow (Lo).
Lo refers to the distance travelled by overland flow across the terrain before it gathers into main channels [18,86], exhibits an inverse relationship with the gradient of the channel and is significantly influenced by soil properties [74,90]. A higher Lo value signifies that water has to traverse a relatively longer path before joining the stream channels [91]. In the Urpash watershed, the Lo was obtained as 0.29 km indicating a lower distance to the main channel. The Lo value is highest at WS5 and lowest at WS4.
Drainage texture (Dt).
Dt signifies the comparative arrangement of the stream network and is defined as the ratio of total streams and Perimeter [18,85]. It reflects the topography’s underlying lithology, infiltration capacity, and overall relief characteristics [92]. In the Urpash watershed, the drainage texture value was 1.06, classifying it within the coarse drainage texture group [18]. This implies favourable permeability, efficient infiltration rate, reduced runoff capacity, and notable groundwater recharge. The Dt values with the watershed are higher in WS2, WS3 and WS4 and lower in WS1, WS5, and WS6.
Quantification of relief parameters
The calculated relief morphometric features are presented in Table 4.
Basin relief (H).
Basin relief (H) represents the greatest vertical span between the lowest point (outlet) and the highest elevation within the basin [93]. A larger vertical span implies a steeper basin. Basin relief directly influences runoff and sediment transport [94,95]. Consequently, watersheds such as WS3 and WS4, characterized by greater relief, are at a heightened risk of soil erosion. The basin relief of the Urpash watershed was 1742.87 m, which indicates the steeper nature of the Urpash watershed.
Relief ratio (Rh).
Rh is the ratio of basin relief (H) to maximum basin length (Lb) [44,52]. This ratio serves as an indicator of slope gradient and erosion intensity within a watershed. As the watershed area and its dimensions decrease, Rh value starts to increase [96]. The relief ratio serves as a gauge for the steepness of the terrain, erosion intensity, and the potential energy available for water and sediment movement [1,97]. In the Urpash watershed, the relief ratio was found to be 0.22, which indicates more relief and slope of the Urpash watershed. In this study, the higher and lower values of the Rh have been found at WS5 and WS1 respectively.
Relative relief ratio (Rhp).
Rhp is the ratio of basin relief (H) to the basin perimeter [45,98]. The Rhp of the Urpash watershed was 5.77, which indicates more relief and steepness of the Urpash.
Ruggedness number (Rn).
It is a measure of surface unevenness [3,99]. A quantitative metric known as the “ruggedness number” or “ruggedness index,” is used to evaluate the topographic complexity or roughness of a terrain or landscape. The Rn uses the gradient and span of slope to measure the instability of the basin [99]. The ruggedness number of the Urpash watershed was calculated as 2.9, which indicates that the study area has an uneven landscape and is highly prone to soil loss. In this study, the higher and lower values of the Rn have been found at WS4 and WS1 respectively, indicating that WS1 is more suitable for agricultural activities compared to the other subwatersheds [100].
Prioritization of subwatersheds and recommendation
This study bridges this gap by integrating conventional morphometric analysis with soil erosion assessment using the Revised Universal Soil Loss Equation (RUSLE) model, ensuring a more comprehensive and scientifically validated prioritization approach. Table 5 presents a summary of the selected morphometric parameters of the six subwatersheds within the Urpash region. The prioritization of these subwatersheds was determined using the compound parameter approach [101]. In this assessment, a lower value indicates a higher priority. As depicted in Table 6, the prioritization order of critical subwatersheds in the Urpash area is as follows: WS3 > WS4 > WS5 > WS6 > WS2 > WS1, as illustrated in Fig 7b. Furthermore, the results of soil erosion assessment (Fig 7c) within the Urpash watershed utilizing the RUSLE model revealed a priority order of WS6 > WS3 > WS2 > WS5 > WS4 > WS1 (Fig 7d). This ranking reflects the varying degrees of soil loss across different subbasins of the watershed, providing valuable insights for targeted management and conservation strategies.
A comparison between this priority order and the one obtained from morphometric analysis reveals discrepancies. The difference in orders arises from the exclusion of critical parameters like Rainfall, Runoff, and soil properties in morphometry-based prioritization. Hence, prioritization based solely on morphometry should not supersede priority based on soil loss. However, a slight similarity in trends between the two prioritization orders is worth noting. Therefore, prioritizing critical subwatersheds based on morphometric analysis of a basin offers an effective solution for assessing vulnerable areas, particularly in situations where physical sampling is challenging or expensive, or in hydrologically similar watersheds. By employing both methodologies, this study establishes a validated framework that enhances the reliability of subwatershed prioritization. The findings provide valuable insights for targeted management and conservation strategies, which are crucial given the increasing environmental pressures in the Urpash watershed. This integrated approach can be adapted for other ecologically sensitive and understudied regions, offering a scalable and transferable method for watershed management. These may include the construction of loose rock-filled dams strategically placed along 1st-order streams with lengths exceeding 100 meters, earthen embankment bunds designed for 2nd-order streams, and small concrete masonry dams suitable for 3rd-order streams with adequate runoff [36]. These structures aim to mitigate soil erosion and manage water resources effectively within the watershed [102]. By adopting such measures, policymakers and land managers can enhance the sustainability of land use practices and safeguard the ecological integrity of the Urpash watershed and similar hydrological regions.
Conclusion
This study provides a comprehensive morphometric analysis of the Urpash watershed, an ungauged and ecologically sensitive area, offering crucial insights into its hydrological behaviour, landform characteristics, and erosion susceptibility.. Using GIS and remote sensing, key morphometric parameters were analyzed, revealing that sub-watersheds with higher linear and relief parameters are more prone to erosion. The integration of the compound parameter method and RUSLE model enabled the prioritization of erosion-prone areas, guiding targeted conservation efforts. While the prioritization order derived from morphometric analysis may differ from soil erosion assessment, both approaches offer valuable insights for targeted management. Furthermore, this research fills a significant gap, particularly as it addresses the under-researched Urpash watershed. Despite its contributions, the study is constrained by the use of a 30m resolution DEM, and the absence of field-based soil validation. Future research should incorporate higher-resolution datasets and AI/ML techniques for improved watershed assessment The outcomes of this study extend beyond the Urpash watershed, offering a methodology applicable to other watersheds with similar topographic and hydrological characteristics. The insights gained here are especially relevant in regions facing land degradation and water scarcity, providing a data-driven approach for optimizing conservation measures. Policymakers and conservationists can use these findings to implement focused, cost-effective interventions, thereby enhancing the resilience of watersheds to both human-induced and climate-related challenges. In conclusion, this study underscores the importance of morphometric analysis as a foundational tool for watershed prioritization and management, paving the way for informed decision-making in land and water conservation practices.
Acknowledgments
The authors acknowledge SKUAST Kashmir for their support in conducting this study. The authors also express their sincere gratitude to the unknown referee for critically reviewing the manuscript and suggesting useful changes.
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