Prioritization Of Sub-watersheds Research Articles

Application of the Analytic Network Process for Sub-Watershed Prioritization in the Huehuetan River Basin, Chiapas, Mexico

Sub-watershed prioritization is essential for developing watershed management plans that maximize impact with minimal resources. This study used a multicriteria decision-making approach to rank sub-watersheds by degradation status in the Huehuetan River Basin, Chiapas, Mexico. The eight sub-watersheds in the basin were classified using the Analytic Network Process (ANP) model, evaluating morphometry, hydrology, hillslope stability, soil water saturation, land-use change, and socioeconomic factors. The results identified hydrology and land-use change as the most influential criteria, with weights of 20.62% and 19.82%, respectively, driven mainly by surface runoff and deforestation. Swtr 08 and Swtr 07 were identified as the highest-priority sub-watersheds, covering 24.31% of the basin area, with 55.31% of Swtr 08 classified as unstable and showing a combined high-vegetation loss of 16.46 km2. The entire watershed showed an annual vegetation loss rate of 146 ha year−1. Increasing the weighting by 50% resulted in greater variability in priority rankings, with runoff and low vegetation showing maximum global ranges of −44.33% and 30.25%, respectively, instability decreasing by 33.94%, and peak flow increasing by 18.20%. These findings emphasize the need for focused interventions in the vulnerable subwatersheds of the upper basin to manage runoff, curb deforestation, and reduce soil instability.

The combination of Multi-Criteria Decision-Making (MCDM) and morphometric parameters for prioritizing the erodibility of sub-watersheds in the Ouljet Es Soltane basin (North of Morocco)

Preserving water and soil resources ranks among the top priorities outlined in the national water strategy. Indeed, the integrated management of water resources in vulnerable territories, particularly in Morocco, requires a deep knowledge of the hydrological functioning and use of water resources in these regions. The diverse hydroclimatic and morphological features within the Ouljet Es Soltane watershed, which is a sub-basin of the extensive Oued Sebou watershed, present significant challenges in managing its water and soil resources. Identifying areas susceptible to soil erosion is crucial for implementing preventive measures in the Ouljet Es Soltane basin and ensuring its sustainable development. Morphometric analysis plays an important role in the effective management and sustainable utilization of the basin's resources. This study used four MCDM models, including the CF (Compound Factor), VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and SAW (Simple Additive Weighing), to prioritize 20 sub-watersheds of the Ouljet Es Soltane watershed.Based on the sub-watershed prioritization results obtained from the VIKOR, TOPSIS, and SAW models, sub-watershed 16 achieved scores of 0, 0.59, and 0.8, respectively, positioning it as the first rank. These findings highlight that sub-watershed 16 exhibits a high susceptibility to erosion and is classified as one of the most vulnerable areas in terms of erosion risk.Based on the results obtained from the VIKOR, TOPSIS, and SAW models, the susceptibility of the sub-watersheds to erosion can be classified into four categories: low, moderate, high, and very high. On the other hand, the CF model only has two categories: low and moderate susceptibility. Overall, the findings suggest that morphometric parameters are highly effective in identifying areas at risk of erosion. Furthermore, the VIKOR, TOPSIS, and SAW methods exhibit greater predictive accuracy compared to the CF model. The comparison of these models involved the use of Spearman correlation coefficient test (SCCT).The findings of this study can provide valuable insights for making informed decisions in developing an effective framework for soil erosion control strategies.

Panzara River Watershed Prioritization Based on Geomorphometric and LULC Change Analysis using Geo-Spatial Techniques

Human activities can significantly influence the quality of water flowing from a watershed, either positively or negatively. As water moves through the system, these impacts accumulate, with all land-based activities having the potential to affect the water quality and quantity experienced by downstream stakeholders. Similarly, the actions of upstream landowners impact the water that flows across others' properties. Geospatial techniques like remote sensing and geographic information systems (GIS) are invaluable tools for analysing drainage patterns within a watershed and the associated changes in land use and cover. This study focuses on the Panzara river basin, a principal tributary of the larger Tapi river basin, situated in central India between the westward-flowing Godavari and Narmada river systems, which both ultimately discharge into the Arabian Sea. The study area spans latitudes from 20°42'0" N to 21°18'0" N and longitudes from 74°06'0" E to 75°00'0" E, covering a geographical area of 2,986.05 square kilometers with a perimeter of 570.51 kilometers. The watershed delineation was carried out using Shuttle Radar Terrain Mapper (SRTM) data with a 30-meter resolution. For land use and land cover (LULC) analysis, Landsat 5 TM C2L1 and Landsat 8 OLI/TIRS C2L1 datasets, both with 30-meter resolution, were utilized. The present study conducts a morphometric analysis and assesses LULC changes within the Panzara river basin between 2000 and 2021. Morphometric parameters such as linear parameters [Drainage density (Dd), Stream frequency (Fs), Mean bifurcation ratio (Rbm), Drainage texture ratio (Dt), Length of overland flow (Lo)] and areal parameters [Elongation ratio (Re), Circulatory ratio (Cr), Form factor (Rf), Compactness coefficient (Cc)] were used to prioritize sub-watersheds. Furthermore, the study classifies the observed LULC changes between satellite imagery datasets from 2000 and 2021, quantifying the percentage changes in the respective LULC classes across the sub-watersheds over the two decades. The overall accuracy of the LULC classification was 81.82% for 2000 and 88.88% for 2021, with Kappa coefficients of 0.772 and 0.85, respectively. In terms of prioritizing sub-watersheds, common sub- watersheds such as SW-1, SW-10, and SW-15 were classified under moderate priority, while SW-5, SW-8, and SW-14 were classified under the lowest priority. The results of this study, particularly the prioritization of sub-watersheds, can be instrumental for hydraulic engineers in planning and managing water resources in the Panzara river basin.

Morphometric Analysis and Prioritization of Sub-Watersheds Located in Heterogeneous Geographical Units—Case Study: The Buzău River Basin

The present study evaluates selected morphometric characteristics of 39 direct tributaries of the Buzău River (area of 4112 km2) to prioritize development actions in these sub-watersheds, which are distributed in three geographical regions within the full Buzău River watershed: the Carpathian, Subcarpathian, and plains regions. By combining a variable number of morphometric parameters, using various mathematical models, we can evaluate the state of balance or imbalance in a watershed and identify sub-watersheds vulnerable to natural processes. Prioritization was achieved using composite (Cp) values by comparing two scenarios. In the first scenario, 11 derived morphometric parameters were used, and in the second scenario, another 7 parameters were added. The obtained values were grouped into five classes (very high, high, medium, low, and very low). Due to the heterogeneity of relief units among geographical regions, there are classification differences for sub-watersheds among those regions. Watersheds classed as very high priority for intervention actions are located in the Carpathian (SW1, SW2, SW15, SW16) and Subcarpathian areas (SW24, SW30), which are characterized by high relief energy and pronounced slope instability, which leads to an increase in the risk of flooding and land degradation. For comparison, all sub-watersheds in the plains region, are classified as very low or low priority. Since the arithmetic mean is sensitive to extreme values, its use in the calculation of composite (Cp) values causes the values to be “eclipsed” and the sub-watersheds to be placed in different prioritization classes (SW18 and SW34), depending on the analyzed scenario, due to the large number of parameters and classified sub-watersheds.

Sub-watershed Prioritization Based on Watershed Hydrological Security Using Different Multi-Criteria Decision-Making Methods

Sub-watershed Prioritization Based on Watershed Hydrological Security Using Different Multi-Criteria Decision-Making Methods

Soil erosion risk assessment of the Lakhmess watershed (northwestern Tunisia) via the SEAGIS model: Inferred prioritization of risky sub-watersheds

Water erosion in Tunisian semi-arid regions causes harmful effects by silting reservoirs and reducing agricultural lands and soil fertility. Several factors are involved in the erosion process: rain erosivity, soil fragility, and degraded land cover on steep slopes associated with the intensification of inappropriate human practices. Thus, identifying erosion vulnerable sub-watersheds based on the assessed soil loss rate is very important to apply suitable conservation measures. The current research aimed to prioritize risky areas in the Lakhmess watershed, north-west Tunisia via the Soil Erosion Assessment using Geographical Information System (SEAGIS) model. To prioritize sub-watersheds vulnerable to soil erosion and sediment yield, the Lakhmess watershed, covering an area of 162 km2, was divided into 16 sub-watersheds (L1–L16), according to the hydrographic network. Then, the mean annual soil erosion rate and the mean annual sediment yield in the watershed were estimated by integrating the Revised Universal Soil Loss Equation (RUSLE) and the Sediment Delivery Ratio (SDR) in the SEAGIS model and their spatial distribution was determined. The obtained results indicate that the estimated average annual soil erosion rate is 4.2 t/ha/y and the annual sediment yield is 2.6 t/ha/y. Maner's SDR model was selected as the best model for estimating SY, with standard error, standard deviation, and coefficient of variation values of 0.75%, 0.01, and 0.45%, respectively. The prioritization of the Lakhmess sub-watersheds based on the estimated soil loss rate reveals that among the 16 sub-watersheds, three sub-watersheds (L10, L12, and L15) were identified as being in a very high priority soil erosion class. The high soil erosion rate and sediment yield in these sub-watersheds is explained by the steep slope and a high rainfall erosivity factor. Six sub-watersheds (L2, L4, L5, L6, L7, and L16) were found to belong to a very low priority soil erosion class, as they are characterized by a very gentle slope, which appears to be an extremely determining factor. These findings constitute a basis for decision makers to plan effective conservation measures to conserve agricultural lands, soil, and water resources in northwestern Tunisia.

Morphometric analysis: sub-watershed prioritization in the temcha watershed, upper Blue Nile Basin, Ethiopia

Morphometric analysis: sub-watershed prioritization in the temcha watershed, upper Blue Nile Basin, Ethiopia

Comparative analysis of RUSLE and SWPT for sub-watershed conservation prioritization in the Ayu watershed, Abay basin, Ethiopia

Ethiopia is currently facing a major environmental problem caused by soil erosion. In order to tackle this problem, it is essential to implement a comprehensive watershed management approach and give priority to conservation efforts depending on the level of severity. Therefore, the objective of this research is to evaluate the mean annual soil erosion and rank the sub-watersheds for conservations in the Ayu watershed, utilizing the Revised Universal Soil Loss Equation (RUSLE) model and the Sub-Watershed Prioritization Tool (SWPT). RUSLE was utilized to predict the annual average soil erosion rate, while SWPT was applied to conduct Weighted Sum Analysis (WSA) for ranking sub-watersheds. Support Vector Machine (SVM) was employed for classifying land use and land cover. The Relative importance of morphometric and topo-hydrologic features in the SWPT was analyzed using a Random Forest model. The Bland-Altman plot and Wilcoxon Signed Rank Test were employed to assess the agreement in prioritizing watersheds between RUSLE results and the SWPT. Furthermore, field observations were conducted to validate the land use classification by collecting ground data. In addition, the study was enhanced with local viewpoints by conducting focus group discussions with agricultural experts and farmers to obtain qualitative insights and validation of resuts. The findings showed that soil loss varied from 0 to 110 t/ha/yr, with an average of 8.95 t/ha/yr, resulting in a total loss of 384365.3 tons annually. The comparison of RUSLE and SWPT showed a moderate positive relationship (r = 0.59). The results of the Bland-Altman plot indicate a consistent agreement between the two methods. However, there is inconsistency among the five sub watersheds. This study enhances the knowledge of soil erosion patterns and offers useful guidance for watershed conservation techniques. It can be also used as a beneficial framework for managing watersheds, with possible uses outside of the Ayu watershed.

Morphometric analysis and prioritization of sub-watersheds of the Inaouene River upstream of the Idris I dam using the GIS techniques

Morphometric analysis and prioritization of sub-watersheds of the Inaouene River upstream of the Idris I dam using the GIS techniques

Prioritization of sub-watersheds in Tuirial river basin through geo-environment integration and morphometric parameters

Prioritization of sub-watersheds in Tuirial river basin through geo-environment integration and morphometric parameters

Prioritization of sub-watersheds based on quantitative morphometric analysis of the Narmada River, India, using SRTM-DEM and GIS techniques

Investigating the contribution of basin to the cycle of hydrological and the area's size, shape, and creation through quantitative analysis of these characteristics of the local scenery. Additionally, estimates of the denudation rate and hypsometric analysis were made in order to comprehend the sub-basin's quantitative geomorphological properties. The link between the morphometric parameters shows that the local geological and geomorphological features significantly influence the drainage system. On a less elevated surface with a moderate slope, stream geometry displays a pattern as semi-dendritic in greater stream order flow. On mountainous terrain surfaces, main-order streams display a dendritic drainage pattern combined with a coarse texture of drainage. The center zone of the Narmada River basin's sub-watersheds area (9461 km2) underwent morphometric investigation utilizing geographical information systems (GIS) with remote sensing methods. It highlights the usefulness of using Shuttle Radar Topographic Mission – Digital Elevation Model (SRTM-DEM) and satellite images to enhance basin management to evaluate and comprehend many geo-hydrological aspects, like topographic & drainage analyses. ArcGIS hydrological modeling has been used to identify and study basins utilizing SRTM-DEM having 10 m resolution. For the micro-level research of its physiographic characteristics and flow structural control along with runoff, using morphometric parameters like relief, aerial, and linear is also beneficial. This may assist in predicting floods, their extent, and their severity.

Applications of advanced technology for Prioritization of Watershed

Prioritization of sub-watersheds is critical in strategic planning for incorporating management practices in delicate semi-arid regions. Geomorphometric as well as land use/cover data sets are essential for determining subwatershed priorities for integrated watershed management. Prioritizing watersheds entails ranking of sub-watersheds according to their susceptibility based on several variables, including the average yearly soil loss, the depletion of water resources, and ecological deterioration. The sub-watershed prioritization for the study area Muzaffarpur district was done by combining Principal Component Analysis (PCA) and Weighted Sum Approach (WSA). PCA was used to differentiate important parameters but WSA was used to measure compound values for priority ranking and determining weights for significant parameters. The PCA was effective in obtaining the most crucial values (i.e., WB, Dt, Re, and Rb). A load of each significant parameter was successfully defined by the WSA application. Traditional prioritizing procedures uses numerous criteria in a complex manner and presumptively contribute equally but PCA-WSA integration results in more dynamic, effective, and efficient solutions.

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

Use of geomatics and multi-criteria methods to assess water erosion in the Tigrigra watershed (Azrou region, Morocco)

In Morocco, the capacity of dam reservoirs has decreased in recent years due to water erosion. This study aims to identify the sub-watersheds most vulnerable to soil erosion in the Tigrigra watershed by utilizing morphometric analysis of linear, landscape, and shape parameters and various multi-criteria decision models. These approaches allow for the prioritization of areas or sub-watersheds at high erosion risk. In the study area, erosion assessment is conducted using multi-criteria decision support models (MCDM) such as MOORA, VIKOR, TOPSIS, COPRAS, WASPAS, and SAW within a GIS environment. This approach highlights the significant role of morphometric parameters and multi-criteria methods in identifying sub-watersheds susceptible to erosion. Overall, the results indicate that morphometric parameters are highly effective in identifying erosion-prone areas. The Tigrigra watershed generally exhibits low to medium sensitivity to erosion, except for certain sub-watersheds. Subcatchment 28 showed significant erosion in most methods used.

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.