Prioritization Of Sub-watersheds Research Articles

Comparative Prioritization of Sub-Watersheds in Flood Generation Using Co-Management Best-Worst Method and Game Theory Algorithm

Comparative Prioritization of Sub-Watersheds in Flood Generation Using Co-Management Best-Worst Method and Game Theory Algorithm

Soil erosion-based sub-watershed prioritization through coupling various crop management and erosivity scenarios using game theory

The soil erosion of the watershed is different in temporal and spatial scales due to complex climatic and environmental conditions and their dynamic state over time. Accordingly, it is necessary to prioritize sub-watersheds based on their dynamic conditions to reduce the destructive effects of soil erosion. However, this issue has to be sufficiently reported on the scale of the watershed. Towards that, a game theory-based prioritization approach was planned concerning changes in vegetation cover and rainfall in the Shazand Watershed of the Markazi Province, Iran. To achieve the purpose of the study, the amount of soil erosion was first estimated in different scenarios resulting from the changes in rainfall erosivity and vegetation cover using the RUSLE model. Next, pairwise comparisons between 24 sub-watersheds in all scenarios were made based on the sub-watersheds' ranks in soil erosion in each scenario. Considering all scenarios, the priority of the sub-watersheds was assessed using the Condorcet approach. The results showed that the mean soil erosion in the watershed ranged from 5.4 and 36 t ha−1 y−1 while applying various scenarios. It is worth mentioning that the prioritization results obtained from the Condorcet algorithm and the current soil erosion rate are highly similar. On the other hand, sub-watersheds 2 and 9 were selected as the first and last priority, providing an appropriate roadmap for managers and relevant departments to adopt appropriate soil erosion inhibition measures.

Prioritization of sub-watersheds and subsequent site identification for soil water and conservation practices using the SWAT-AHP integrated model in the Lower Sutlej Sub-basin, India.

Prioritization of watersheds is a crucial step in integrated river basin management. It guides resource allocation, planning, decision-making, stakeholder engagement, targeted interventions, and monitoring and evaluation efforts. By identifying and addressing priority watersheds, comprehensive and sustainable management of water resources can be achieved within a river basin. The aim of the current study is to prioritize watersheds using the Soil and Water Assessment Tool (SWAT) and site suitability analysis for the implementation of soil and water conservation structures (SWCS) in the prioritized watersheds by using an analytical hierarchy process (AHP) of the Lower Sutlej Sub-basin, India. The model was calibrated with observed data from 2017 to 2019 with the first 2years (2015-16) as a warm-up period. Furthermore, validation of the model was done using 2-year data from 2020 to 2021. The model showed successful performance in terms of the R2 range from 0.72 to 0.89, the NSE range from 0.67 to 0.73, the PBIAS range from - 26.70 to 11.30, and the RSR range from 0.51 to 0.57 for stream flow and sediment yield during calibration and validation period. The basin's average annual soil loss ranged from 3.08 to 21.63 t/ha/year, a watershed with the WS2 index seeing the highest rate of soil erosion (21.63 t/ha/year). Hence, WS2 was found to be a top priority. In addition, the site suitability analysis of the prioritized watershed (WS2) reveals that about 1.42% of the area is extremely suitable, 16.14% is highly suitable, and 35.58% is moderately suitable for SWCS. According to the site suitability map validation, both dam locations were found in highly suitable areas, so the developed site suitability map is accurate. This research will help sustainability planners and managers make more informed decisions when building SWCS at suitable sites for better land and water conservation.

Prioritization of sub-watersheds for soil conservation management using morphometric, biophysical and socioeconomic characteristics: a fuzzy AHP approach

Prioritization of sub-watersheds for soil conservation management using morphometric, biophysical and socioeconomic characteristics: a fuzzy AHP approach

Quantitative Morphometric Analysis and Prioritization of Sub-Watersheds for Soil Erosion Susceptibility: A Comparison between Fuzzy Analytical Hierarchy Process and Compound Parameter Analysis Method

Quantitative Morphometric Analysis and Prioritization of Sub-Watersheds for Soil Erosion Susceptibility: A Comparison between Fuzzy Analytical Hierarchy Process and Compound Parameter Analysis Method

Sub-Watershed Prioritization for Erosion Susceptibility based On Drainage Morphometric Characters

Watershed located in a Hilly-plain environment is more susceptible for soil erosion. Loss of fertile soil in agricultural land hampers the life of the farmers of the region. Identification of the vulnerable areas and devising strategies to minimize the damage caused due to soil erosion are important to address the problems faced by the agrarian society. In our current work, drainage morphometric parameters were evaluated to assess the soil erosion susceptibility of the four sub-watersheds (SW01, SW02, SW03 and SW04) of the Yagachi watershed located in the Hemavathi river basin in Karnataka State using Remote Sensing (RS) and Geographical Information System (GIS). Seventeen morphometric parameters namely Area, Stream Order, Mean Bifurcation Ratio, Drainage Density, Stream Frequency, Texture Ratio, Infiltration Number, Compactness Co-Efficient, Length of Overland Flow, Elongation Ratio, Circulatory Ratio, Form Factor, Relief Ratio, Shape Factor, Basin Relief, Dissection Index and Ruggedness Number were considered. The priority rank and category for each sub-watershed were assigned based on Compound Factor (CF) value. The sub-watersheds with the lowest CF value are most susceptible to erosion and need highest priority for the soil conservation measures. Based on CF values, the sub-watersheds were categorized into 4 priority groups: ‘Very High’ priority (<2.00), ‘High’ priority (2.01–2.50), ‘Moderate’ priority (2.51–3.00) and ‘Low’ priority (≥3). Out of 4 sub-watersheds, SW03 falls in ‘Very High’ priority category in terms of erosion susceptibility and needs appropriate soil conservation measures in order to arrest fertile soil erosion and increase agricultural produce output.

Gully erosion susceptibility mapping and prioritization of gully-dominant sub-watersheds using machine learning algorithms: Evidence from the Silabati River (tropical river, India)

Gully erosion is a severe environmental issue that poses threats to agriculture, human safety, habitats, infrastructure, and soil integrity. Selecting the right machine learning model is vital for accurate Gully Erosion Susceptibility Mapping (GESM) due to varying environmental hazard performance. This study employed a comparative analysis of two machine learning techniques, Random Forest (RF) and Extreme Gradient Boost (XGBoost), to develop a highly precise GESM for the Silabati watershed (India). The analysis incorporated 24 controlling factors and examined a dataset of 460 sample points, with equal representation of gullies and non-gullies. Variance Inflation Factors (VIF) and Information Gain Ratio (IGR) techniques were applied to assess multicollinearity test among the controlling factors. Lithology, elevation, distance from the road, LULC, geomorphology, rainfall, drainage density, and coarse fragments emerged as crucial factors in determining GESM. Statistical tests, including the Kappa index, Root Mean Square Error (RMSE), Accuracy (ACC), Mean Absolute Error (MAE), Coefficient of Determination (R2), and Receiver Operating Characteristic (ROC), were employed to evaluate the RF and XGB models on training and testing data. Both models demonstrated strong performance, with the XGBoost and RF models achieving ROC values of 84.1% and 83.2%, respectively. The applied quantile classification method resulted in the creation of five distinct GESMs, categorized as very high (VH), high (H), moderate (M), low (L), and very low (VL). We found that the very high GESM areas of the watershed were 4.10% in the XGBoost model and 4.61%. in the RF model. Out of the 26 sub-watersheds, the results have identified five sub-watersheds as highly prioritized for sustainable management. Therefore, the present study provides an accurate gully erosion identification using advanced models, offering valuable insights for policymakers to proper management implementation.

A comparative study of morphometric, hydrologic, and semi-empirical methods for the prioritization of sub-watersheds against flash flood-induced landslides in a part of the Indian Himalayan Region.

The flash flood-induced erosion is the primary contributor to soil loss within the Indian Himalayan Region (IHR). This phenomenon is exacerbated by a confluence of factors, including extreme precipitation events, undulating topographical features, and suboptimal soil and water conservation practices. Over the past few decades, several flash flood events have led to the significant degradation of pedosphere strata, which in turn has caused landslides along with fluvial sedimentation in the IHR. Researchers have advocated morphometric, hydrologic, and semi-empirical methods for assessing flash flood-induced soil erosion in hilly watersheds. This study critically examines these methods and their applicability in the Alaknanda River basin of the Indian Himalayan Region. The entire basin is delineated into 12 sub-watersheds, and 13 morphometric parameters are analyzed for each sub-watershed. Thereafter, the ranking of sub-watersheds vulnerability is assigned using the Principal Component Analysis (PCA), compounding method (CM), Geomorphological Instantaneous Unit Hydrograph (GIUH), and Revised Universal Soil Loss Equations (RUSLE) approaches. While the CM method uses all 13 parameters, the PCA approach suggests that the first four principal components are the most important ones, accounting for approximately 89.7% of the total variance observed within the dataset. The GIUH approach highlights the hydrological response of the catchment, incorporating dynamic velocity and instantaneous peak magnifying the flash flood susceptibility, lag time, and the time to peak for each sub-watershed. The RUSLE approach incorporates mathematical equations for estimating annual soil loss utilizing rainfall-runoff erosivity, soil erodibility, topographic, cover management, and supporting practice factors. The variations in vulnerability rankings across various methods indicate that each method captures distinct aspects of the sub-watersheds. The decision-maker can use the weighted average to assign the overall vulnerability to each sub-watershed, aggregating the values from various methods. This study considers an equal weight to the morphometric, hydrological GIUH, and semi-empirical RUSLE techniques to assess the integrated ranking of various sub-watersheds. Vulnerability to flash flood-induced landslides in various sub-watersheds is categorized into three classes. Category I (high-priority) necessitates immediate erosion control measures and slope stabilization. Category II (moderate attention), where rainwater harvesting and sustainable agricultural practices are beneficial. Category III (regular monitoring) suggests periodic community-led soil assessments and afforestation. Sub-watersheds WS11, WS8, WS5, and WS12 are identified under category I, WS7, WS4, WS9, and WS6 under category II, and WS1, WS3, WS2, and WS10 under category III. The occurrence of landslides and flash-flood events and field observations validates the prioritization of sub-watersheds, indicating the need for targeted interventions and regular monitoring activities to mitigate environmental risks and safeguard surrounding ecosystems and communities.

Determination of the potential soil losses and prioritization of sub-watersheds: Insight from North African highland system

Soil erosion has negative effects on people and property, hinders the sustainable development of natural resources, and poses a threat to the economic growth of territories worldwide, and is particularly acute for African countries. Consequently, identifying and prioritizing areas susceptible to this phenomenon is crucial for the implementation of efficient preventative measures. In this study, the empirical Erosion Potential Method (EPM) was used to quantify soil losses, and two Game Theory (GT) algorithms (Borda and Condorcet) were employed to identify locations prone to soil erosion and prioritize sub-watershed (SW) based on hydromorphometric characteristics in a hydrological system from High Atlas in Morocco. For this purpose, 26 factors were calculated, subsequently, a linear correlation analysis was conducted to assess the relationship between potential soil erosion and various influencing factors. The EPM model findings indicated average loss rates of roughly 3356 m3/km2/year, which are corroborated by 217 inventory points gathered in the most productive sediment locations, with an AUC value of 80 %. The results of prioritization using GT algorithms show that the SW6 and SW8 are classified as areas with high vulnerability to soil erosion, and the sub-watersheds located upstream of the Lakhdar river watershed are the units that deserve prioritization in terms of planning intervention. The validation of results indicates that the Borda algorithm performed better (AUC= 92 %) than the Condorcet algorithm (AUC= 72 %). This innovative approach enhances our understanding of erosive processes within specific spatial units, enabling informed decision-making and making a substantial contribution to the sustainable and efficient management of water resources. This represents a significant advancement compared to previous studies in the region.

GIS-based morphometric analysis with emphasis on hypsometric appraisal for sub-watershed prioritization: a case study of the Shyamari River Basin, Central India

GIS-based morphometric analysis with emphasis on hypsometric appraisal for sub-watershed prioritization: a case study of the Shyamari River Basin, Central India

Prioritizing sub-watersheds for soil erosion using geospatial techniques based on morphometric and hypsometric analysis: a case study of the Indian Wyra River basin

The hydrological availability and scarcity of water can be affected by geomorphological processes occurring within a watershed. Hence, it is crucial to perform a quantitative evaluation of the watershed’s geometry to determine the impact of such processes on its hydrology. Geographic information systems (GIS) and remote sensing (RS) techniques have become increasingly significant because they enable decision-makers and strategists to make accurate and efficient decisions. To prioritize sub-watersheds within the Wyra watershed, this research employs two methods: morphometric analysis and hypsometric analysis. The watershed was divided into eleven sub-watersheds (SWs). The prioritization of sub-watersheds in the Wyra watershed involved assessing several morphometric parameters, such as relief, linear, and areal features, for each sub-watershed. Furthermore, the importance of the sub-watersheds was determined by computing hypsometric integral (HI) values using the elevation–relief ratio method. The final prioritization of sub-watersheds based on morphometric analysis was determined through the integration of principal component analysis (PCA) and weighted sum approach (WSA). SW2 and SW9 have had higher priorities using morphometric analysis, whereas SW6, SW7, and SW10 have obtained higher priorities using hypsometric analysis. SW4 is the most common SW that shares the same priority. The most vulnerable sub-watersheds are those with the highest priority, and therefore, programmes for soil and water conservation should pay more attention to them. The conclusions of the study may prove useful to various stakeholders involved in initiatives related to watershed development and management.

Developing a new multi-criteria decision-making for flood prioritization of sub-watersheds using concept of D numbers

Developing a new multi-criteria decision-making for flood prioritization of sub-watersheds using concept of D numbers

Sub-watershed prioritization using morphometric analysis, principal component analysis, hypsometric analysis, land use/land cover analysis, and machine learning approaches in the Peddavagu River Basin, India

Abstract Water resource management is critical in the face of climate change to reduce water scarcity and meet the demands of an expanding population. Prioritization of watersheds has gained significance in natural resource management, particularly in the context of watershed management. This study prioritizes sub-watersheds for the Peddavagu basin using five methods. The four methods mentioned above can be estimated utilizing remote sensing (RS) and geographic information system (GIS) approaches, while linear discriminant analysis (LDA) is estimated using machine learning techniques. The catchment resulted in the formation of 13 sub-watersheds. The quantitative measurements of morphometric analysis, including linear, relief, and areal, were considered, and 18 morphometric characteristics were chosen to rank and prioritize sub-watersheds. Principal component analysis (PCA) was used to rank and prioritize sub-watersheds based on four highly correlated morphometric parameters. The land use/land cover (LULC) analysis used four features to prioritize sub-watersheds. The LDA analysis used two features to prioritize sub-watersheds. Using hypsometric integral (HI) values, prioritization has been done. Sub-watersheds were prioritized. Based on five methods, the sub-watersheds were classified as low, medium, and high. Among the sub-watersheds identified as high priority, immediate priority is assigned to SW10. Decision-makers in the research region can use the findings to plan and implement watershed management techniques.

Prioritization of soil erosion prone sub-watersheds through morphometric analysis using geospatial and weighted sum approach: a case study of Boranakanive reservoir catchment in Tumkur district, Karnataka, India

Prioritization of soil erosion prone sub-watersheds through morphometric analysis using geospatial and weighted sum approach: a case study of Boranakanive reservoir catchment in Tumkur district, Karnataka, India

Prioritization of sub-watersheds of Teesta River according to soil erosion susceptibility using multi-criteria decision-making in Sikkim and West Bengal

Prioritization of sub-watersheds of Teesta River according to soil erosion susceptibility using multi-criteria decision-making in Sikkim and West Bengal

Assessment of soil erosion using WSA and SPR techniques for Giri watershed, Himachal Pradesh, NW Himalaya, India

A watershed is the result of several geomorphic processes such as weathering, erosion, degradation and aggradation which are influenced by several factors viz. tectonics, lithology, climate, landslides and mass wasting processes etc. In a tropical climate, watersheds contribute a significant amount of eroded material which is reflecting the impact of lithology, precipitation, tectonics, relief and anthropogenic activities. In the Himalayan region besides significant heterogeneity in lithology, stratigraphy, structure and tectonics, it is observed that variability is exhibited in climatic conditions over a small region. These factors contribute to the development of geomorphic landforms and are best studied in watersheds or river basins. In the present study, Giri Watershed (GW) is assessed to contemplate susceptibility to erosion for 66 sub-watersheds using geomorphic parameters. The prioritization of subwatersheds has been done using Weighted Sum Analysis (WSA) and Sediment Production Rate (SPR) methods. The quantitative analysis of subwatersheds is categorized into different priority classes viz. very high, high, moderate, low and very low, among which 27 subwatersheds have very high to high susceptibility to erosion.

Significance of geomorphic indicators for identification of groundwater recharge potential in the Khapri watershed of Deccan Volcanic Province (DVP), district Dangs, western India

The district Dangs of western India, marks the extension of Western Ghats in Gujarat state. It is characterized by less transmissible basaltic lithology of Deccan Volcanic Province (DVP), rugged trappean highlands and moderate to very steeply sloping surfaces. Despite receiving high average annual rainfall (2000 mm) the terrain framework produces high runoff than infiltration (recharge), leading to groundwater crisis. In such terrains, where lithology is homogenous, the natural groundwater recharge is significantly influenced by geomorphic indicators (landforms, drainage characteristics and slope). Therefore, identification of groundwater recharge potential (here after referred as GWRPOT) is crucial for the sustainable development of groundwater resource. In the present study GWRPOT is identified on the basis of geomorphic indicators (Gi) in sub-watersheds of Khapri, district Dangs of DVP. To generate the database on geomorphic indicators the IRS-LISS-III (24 m) satellite data, Survey of India topographic maps (1:50,000), and SRTM-DEM are used. The ranks are assigned to geomorphic indicators of each sub-watershed by considering their aerial coverage, influence on GWRPOT and field studies. The summation of average ranks of each geomorphic indicator viz., landform (Gc), drainage characteristics (Dc) and slope (Sc) is used to compute Gi value. On the basis of Gi, the GWRPOT is identified and categorized as very poor (SW-5), poor (SW-3, SW-2, SW-10), moderate (SW-7, SW-4), good (SW-11), very good (SW-1, SW-8, SW-9) and excellent (SW-6). These results are validated with seasonal groundwater level fluctuations in 33 dug-wells, which shows positive correlation between Gi and groundwater fluctuation (R2 = 0.77). Further, the sub-watershed prioritization is carried out to highlight the need of improving the GWRPOT and thereby sustainability.

Prioritization of Sub-watersheds for the Categorization of Surface Runoff and Sediment Production Rate Based on Geo-spatial Modeling and PCA Approach: A Case from Upper Beas River, Himachal Pradesh, India

Prioritization of Sub-watersheds for the Categorization of Surface Runoff and Sediment Production Rate Based on Geo-spatial Modeling and PCA Approach: A Case from Upper Beas River, Himachal Pradesh, India

Sub-Watershed Prioritization of Kariangote River in Kerala Based on Drainage Morphometry and Geomorphology – A Remote Sensing and GIS Approach

Objectives: This article examines the geohydrological behaviour of the Kariangote watershed and prioritizes its subwatersheds based on groundwater presence. Methods: Remote sensing and GIS techniques were used to study the morphometric and geomorphologic characteristic of the watershed. Six sub-watersheds were identified, and various morphometric and geomorphic parameters were calculated. Based on the relative importance to groundwater occurrence, sub-watersheds were prioritized by giving suitable weightage to morphometric and geomorphological units. Findings: Sub-watershed IV is the most deficit one and is given priority followed by III the next, V, II, I, and VI. Sub-watershed VI is with surplus groundwater and is given the last priority. Novelty: Higher priority should be given to conservation practices in sub-watersheds to prevent surface runoff and soil erosion and to increase groundwater levels. Sub-watersheds with highly permeable subsurface formation could be suggested for rainwater harvesting and artificial recharge of groundwater. Planning further groundwater development projects and managing watersheds would be aided by this study. Keywords: Morphometry; Coastal Alluvium; Flood Plain; Groundwater; Prioritization

Prioritization of Sub-watersheds through morphometric analysis in the Lower Hiranyakeshi Sub-basin, Karnataka

In the present study, eight sub-watersheds are prioritized in Hiranyakeshi lower sub-basin based on the morphometric analysis using Remote Sensing and Geographical Information System. An evaluation of morphometric parameters is conducted to determine the potential of sub-watersheds. Sub-watersheds were prioritised as they are the most vulnerable and require more attention for water conservation and exploration measures. According to the results, three sub-watersheds are falling under high category, four are moderate and one sub-watershed falls under low category. The findings of this study may be useful to numerous stakeholders involved in watershed development and management projects.