Erosion-prone Areas Research Articles

Modelling Impact of Land Use Changes and Climate on Soil Erosion in the Uma Oya River Basin, Sri Lanka

Soil erosion is a significant environmental issue in most mountainous areas and is further exacerbated due to ongoing climatic changes and anthropogenic activities. Soil erosion not only triggers natural disasters like landslides but also degrades the fertile topsoil layers. Therefore, modeling and evaluation of soil erosion in mountainous areas and river basins are highly important. The Uma Oya River Basin (UORB), Sri Lanka is an area with rich biodiversity and is also important for agricultural production. Moreover, this area is frequently discussed due to the ongoing developments of the Uma Oya Project. This paper presents a comprehensive evaluation of soil erosion in the UORB and results are compared for two decades from 2000 to 2020. The Revised Universal Soil Loss Equation (RUSLE) was used to determine the annual soil erosion rates. In addition, the spatial-temporal variation of land use and land cover was assessed in the UORB. Results revealed that extreme soil erosion scenarios occur when forests and other vegetation lands are converted to agricultural lands and farmlands. We found that soil loss in the area largely happened due to steep slopes, reduction of vegetation and forest covers, and growth of cultivation lands. Erosion-prone areas in the river basin are identified and conservation strategies are discussed. In addition, the impact of the ongoing climate change on the UORB is highlighted.

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.

Soil erosion vulnerability and soil loss estimation for Siran River watershed, Pakistan: an integrated GIS and remote sensing approach.

Soil erosion is a problematic issue with detrimental effects on agriculture and water resources, particularly in countries like Pakistan that heavily rely on farming. The condition of major reservoirs, such as Tarbela, Mangla, and Warsak, is crucial for ensuring an adequate water supply for agriculture in Pakistan. The Kunhar and Siran rivers flow practically parallel, and the environment surrounding both rivers' basins is nearly identical. The Kunhar River is one of KP's dirtiest rivers that carries 0.1 million tons of suspended sediment to the Mangla reservoir. In contrast, the Siran River basin is largely unexplored. Therefore, this study focuses on the Siran River basin in the district of Manshera, Pakistan, aiming to assess annual soil loss and identify erosion-prone regions.Siran River average annual total soil loss million tons/year is 0.154. To achieve this, the researchers integrate Geographical Information System (GIS) and remote sensing (RS) data with the Revised Universal Soil Loss Equation (RUSLE) model. Five key variables, rainfall, land use land cover (LULC), slope, soil types, and crop management, were examined to estimate the soil loss. The findings indicate diverse soil loss causes, and the basin's northern parts experience significant soil erosion. The study estimated that annual soil loss from the Siran River basin is 0.154 million tons with an average rate of 0.871 tons per hectare per year. RUSLE model combined with GIS/RS is an efficient technique for calculating soil loss and identifying erosion-prone areas. Stakeholders such as policymakers, farmers, and conservationists can utilize this information to target efforts and reduce soil loss in specific areas. Overall, the study's results have the potential to advance initiatives aimed at safeguarding the Siran River watershed and its vital resources. Protecting soil resources and ensuring adequate water supplies are crucial for sustainable agriculture and economic development in Pakistan.

Identification of soil erosion-prone areas for effective mitigation measures using a combined approach of morphometric analysis and geographical information system

The current worldwide effects of soil erosion are a result of natural and human activities, and it had serious consequences on ecosystems, agriculture, and water quality in the watershed. As a result, quantifying the physical characteristics of a watershed can be used to identify areas that are more susceptible to soil erosion and require immediate mitigation measures. This study prioritizes the fourteen sub-watersheds in the Dabus Watershed, Ethiopia using a Geographical Information System based on the variety of parameters for implementing short and long-term effective watershed management practices. For each sub-watershed (SW), the compound parameter was calculated from different morphometric parameters and used to rank the areas. The findings show that SW1, SW7, and SW10 are contributing very high soil erosion in the study area with its 2390.75 km2, 2555.77 km2, and 1642.71 km2 covering area; however, SW2, SW8, SW9, and SW14 are the areas lowly degraded due its soil erosion is low. Thus, mitigation measures such as contouring, terracing, filter strips, and other structural/non-structural effective approaches should be implemented in the area where high soil erosion was contributed.

Toprak Kayıp Modellerinin Somali İçin Değerlendirilmesi

Soil erosion stands as a significant environmental concern impacting both agricultural productivity and natural ecosystems across various regions worldwide. The soil losses attributed to erosion exacerbate concerns about food security and land degradation in Somalia, a country already grappling with numerous socio-economic challenges. This study aims to evaluate the erosion risk in Somalia by examining potential techniques that offer valuable insights for sustainable land management and resource planning. Emphasizing the utilization of remote sensing data, geographic information system (GIS) techniques, and hydrological modeling, the research highlights the exploration of erosion risk factors and their spatial distribution nationwide. Topographic data, soil properties, land use and land cover data, precipitation models, and vegetation indices could be employed to identify erosion-prone areas and sensitive points in Somalia. Furthermore, analyzing historical erosion data can aid in calibrating and validating predictive models. Continuous monitoring of sensitive areas over the years is recommended, considering the role of human activities such as ongoing deforestation, poor agricultural practices, and excessive grazing, which contribute to escalating erosion risks on Somali lands. Decision-makers should focus on methodologies that can be utilized to implement efficient erosion management techniques ensuring environmental sustainability across Somalia.

Application of Revised Universal Soil Loss Equation (RUSLE) model for the estimation of soil erosion and prioritization of erosion-prone areas in Majuli Island, Assam, India

Soil erosion is a serious issue, causing loss of agricultural productivity, increase in sediment deposit in the riverbeds, and damage to the ecological balance of the affected areas. Proper assessment of the soil erosion rate is essential for managing natural resources. The present study employs a GIS-based RUSLE (Revised Universal Soil Loss Equation) model to estimate annual soil loss in Majuli River Island of Assam, India. Annual average rainfall, soil properties, topographic characteristics, and LULC were taken as inputs to identify the soil erosion susceptible areas. The result revealed that annual soil loss of the study area ranges between 0 to 711 t ha−1 yr−1, with a mean annual soil loss of 23.02 t ha−1 yr−1. The entire region was classified into six soil loss severity classes, around 90 % of the area was found to be very slightly affected (< 5 t ha−1 yr−1) by soil erosion, around 5 % slightly affected (5 – 10 t ha−1 yr−1), roughly 3% moderately affected (10 – 20 t ha−1 yr−1), around 1% moderate high (20 – 40 t ha−1 yr−1), nearly 0.3 % area affected severely (40 -80 t ha−1 yr−1) and very severely affected areas (> 80 t ha−1 yr−1) contributes 0.1 %. A total of six priority levels of conservation were demarcated village-wise; priority level I requires immediate attention, and so on. The research outcome can help effectively implement conservation and management practices to check soil erosion in the study area.

Experimental and numerical investigation of hydro-abrasive erosion in the Pelton turbine buckets for multiphase flow

Sediment erosion-corrosion is a critical threat to the safe operation of hydro turbines, which may lead to component damage or even complete failure of the turbine. A lack of understanding of the mechanism of sand erosion is a barrier to developing an erosion model to exactly quantify sand erosion in the Pelton turbine. The preeminent objectives of this research work are to determine parameters that influence sand erosion, identify erosion-prone areas in Pelton turbine buckets, quantify the erosive wear experimentally and numerically, determine the impact of erosive wear, and analyze the microscopic mechanism of erosion. Five Pelton buckets made of aluminum, carbon steel, stainless steel, polylactic acid (PLA), and acrylonitrile butadiene styrene (ABS) were used to perform erosion experiments under two-phase, solid-liquid flow conditions. Multi-layer paint modelling technique was used to identify erosion-prone areas. Optical profilometry was used to perform surface roughness analysis and Scanning Electron Microscopy was used to evaluate the microscopic degree of damage due to erosive wear in the Pelton bucket. Mass loss and thickness reduction analyses were performed to quantify the erosive wear. The erosion rates of aluminum, carbon steel, stainless steel, and ABS were 190 %, 86.73 %, 48.79 %, and 5.61 % higher, respectively, compared to PLA and both PLA and ABS demonstrated exceptional resistance.

Landscape Pattern of Sloping Garden Erosion Based on CSLE and Multi-Source Satellite Imagery in Tropical Xishuangbanna, Southwest China

Inappropriate soil management accelerates soil erosion and thus poses a serious threat to food security and biodiversity. Due to poor data availability and fragmented terrain, the landscape pattern of garden erosion in tropical Xishuangbanna is not clear. In this study, by integrating multi-source satellite imagery, field investigation and visual interpretation, we realized high-resolution mapping of gardens and soil conservation measures at the landscape scale. The Chinese Soil Loss Equation (CSLE) model was then performed to estimate the garden erosion rates and to identify critical erosion-prone areas; the landscape pattern of soil erosion was further discussed. Results showed the following: (1) For the three major plantations, teas have the largest degree of fragmentation and orchards suffer the highest soil erosion rate, while rubbers show the largest patch area, aggregation degree and soil erosion ratio. (2) The average garden erosion rate is 1595.08 t·km−2a−1, resulting in an annual soil loss of 9.73 × 106 t. Soil erosion is more susceptible to elevation and vegetation cover rather than the slope gradient. Meanwhile, irreversible erosion rates only occur in gardens with fraction vegetation coverage (FVC) lower than 30%, and they contribute 68.19% of total soil loss with the smallest land portion, indicating that new plantations are suffering serious erosion problems. (3) Garden patches with high erosion intensity grades and aggregation indexes should be recognized as priorities for centralized treatment. For elevations near 1900 m and lowlands (<950 m), the decrease in the fractal dimension index of erosion-prone areas indicates that patches are more regular and aggregated, suggesting a more optimistic conservation situation.

Evaluating the impact of land use and land cover changes on sediment yield dynamics in the upper Awash basin, Ethiopia the case of Koka reservoir

Land Use and Land Cover changes (LULC) are the driving forces to change the hydrological response of the watershed. In this study, the Quantum Geography Information System Interference Soil and Water Assessment Tool Plus (QSWAT-PLUS) model was applied to evaluate the effects of LULC on sediment load at the Upper Awash River Basin (UARB) which are causing sedimentation problems in Koka reservoir. The LULC data for 2005, 2010, and 2015 were obtained from historical satellite images using Earth Resources Observation and Science (ERDAS) 2014. The classification of LULC changes showed that the agricultural practice, and the settlement land both increased by 6.7 % and 6.3 %, respectively. In contrast, the forest area, woodland, shrubland, and water bodies decreased by 5.47 %,0.93 %,0.96 %, and 1.34 % from 2000 to 2015 respectively. The model evaluation results were satisfactory for the three LULC scenarios. The average annual surface runoff volume for the 2005 LULC data was 182.2 mm, which increased to 193.29 mm in 2010 and 205.3 mm in 2015. Similarly, the average annual sediment yield that would enter to the Koka reservoir under the 2005, 2010, and 2015 LULC scenarios were 26.03 t/ha/yr, 26.34 t/ha/yr, and 28.33 t/ha/yr respectively. In general, streamflow, surface runoff, and sediment output increased by 4.55 %, 12.68 %, and 8.84 %, respectively due to the rapid change of LULC from 2000 to 2015. Temporarily, the sediment load at the upstream side of the Koka Dam watershed was 60.8 % during the wet season. The southwest direction of the watershed was identified as the primary erosion-prone area. Based on the simulation results, the filter strip, contour, and terraces reduced the watershed sediment yield by up to 60 %, 65 %, and 80 %, respectively. Therefore, the selected best management practices are highly effective in reducing silt along the entire upstream side of the Koka Dam watershed.

Spatiotemporal changes of land use in response to runoff and sediment yield for environmental sustainability in the upper Blue Nile Basin, Oromiyaa, Ethiopia

Abstract Modeling and mapping hydrological responses of runoff and sediment yield to spatiotemporal land use changes are crucial concerning environmental sustainability. The research was aimed at quantifying the spatiotemporal effects of land use on runoff and sediment yields using three land use satellite images and the SWAT+ model. The increase in agriculture, settlement, and decreasing forest goes to the possibility of increasing sediment yield and runoff by 53.2 and 56.5%, respectively, affecting ecosystems. The areas vulnerable to high runoff were found at the lower and middle reaches with the annual average runoff of 10,825.1, 11,972.9, and 13,452 mm for each respective scenario. On the other hand, most of the soil erosion-prone areas designated as severe in the second and third scenarios were covered by agriculture and shrubland, with annual sediment yields of 301.5 and 267.5 tons, respectively. Deforestation for agricultural expansion has a significant role in environmental degradation, as forests play an irreplaceable role in ecological resilience. Generally, the dominant land uses that instigate soil erosion, runoff, and sediment yield are agriculture, shrubland, and deforestation. The simulation of runoff and sediment yield in response to land use change using the SWAT+ model is more scientifically reliable and acceptable.

Comparative Analysis of MCDA Techniques for Identifying Erosion-Prone Areas in the Burhanpur Watershed in Central India for the Purposes of Sustainable Watershed Management

The degradation of land and increasing water scarcity are existing challenges for agricultural sustainability, necessitating the implementation of improved soil-conservation practices at the watershed scale. The identification and selection of critical/prone areas based on erosion-governing criteria is essential and helps in the execution of the management process for determining priority. This study prioritizes erosion-prone sub-watersheds (alternatives) based on morphometric parameters (multiple criteria) via five Multi-Criteria Decision Analysis (MCDA) approaches, i.e., AHP: Analytical Hierarchy Process; TOPSIS: Technique for Order of Preference by Similarity to Ideal Solution; VIKOR: VIseKriterijumska Optimizacija I Kompromisno Resenje; SAW: Simple Additive Weighting; and CF: Compound Factor. Based on their priority score, 19 sub-watersheds were classified into four priority classes: low priority (0–0.25), moderate priority (0.25–0.50), high priority (0.50–0.75), and very high priority (0.75–1). The results revealed that about 8.34–30.15% area of the Burhanpur watershed is critically prone to erosion, followed by 23.38–52.05% area classed as high priority, 7.47–49.99% area classed as moderate priority, and 10.33–18.28% area classed as low priority. Additionally, four indices—percentage of changes (∆P), intensity of changes (∆I), the Spearman rank correlation coefficient test (SCCT), and the Kendall tau correlation coefficient test (KTCCT)—were employed to compare the models. This study confirms the efficacy of morphometric parameters for prioritizing sub-watersheds to preserve soil and the environment, particularly in areas for which limited information is available.

Geodetic control extension at erosion prone areas using integrated CORS-GNSS in Benin City, Edo State Nigeria

This study addresses the imperative expansion of geodetic controls in erosion-prone areas of Benin City, with a focus on establishing controls in specific schools. Two observation campaigns were conducted on nine monumented controls with 36 baselines and another set of eight controls with 28 baselines. Data adjustments were successfully carried out using Trimble Business Centre software, at 10.00σ confidence level and 1.00% significance for the tau test in the second iteration of both campaigns. Analysis revealed varying accuracy levels among stations. Notably, stations ADLC_01, ADLC_02, and QSS_01 demonstrated a minimum latitude accuracy of 1.3 mm, while AGGS_01 and AGGS_02 showcased the highest accuracy at 1.7 mm. Similar trends were observed in longitude and height measurements. For longitude, the maximum standard deviation (3.3 mm) was recorded at ENV_101D station, while the minimum accuracy (1.7 mm) was obtained at station AGGS_01. The minimum accuracy in height (3.5 mm) was recorded at station AGGS_01, while the maximum accuracy (6.7 mm) was recorded at station SMGGS_01. These findings provide essential insights into the accuracy of geodetic controls in Benin City based on purposeful selected schools, serving as valuable information for future research, infrastructure development, and engineering projects execution

Enhancing soil ecological security through phytomanagement of tailings in erosion-prone areas

Revegetation is effective in improving soil quality in ecologically fragile areas. However, little is known about the impact of diverse phytomanagement strategies of tailings on soil quality and ecological security in erosion-prone areas. We investigated the water stability, soil aggregate nutrients, and the risk of heavy metal contamination of abandoned tailings under phytomanagement and in adjacent bare land on the Loess Plateau. The results showed that phytomanagement significantly enhanced soil aggregate stability, as demonstrated by higher contents of soil organic carbon (SOC), glomalin-related soil protein (GRSP), aromatic-C, and alkene-C in macro-aggregates. The pollution load index (PLI) and ecological risk index (RI) of soil heavy metals were lower in shrub/herbaceous mixed forests than in natural grasslands and planted forests. The risk of heavy metal contamination was higher in macro-aggregates (>0.25 mm) than in micro-aggregates (<0.25 mm) and was significantly and positively correlated with the SOC and GRSP contents of the aggregates. Our study demonstrates that soil aggregate quality is closely related to the fate of heavy metals. Diversified tailing revegetation measures can improve soil quality and ensure ecological security.

Identification of soil erosion-prone areas and annual average soil loss of Siddheswari River basin, Eastern India

Identification of soil erosion-prone areas and annual average soil loss of Siddheswari River basin, Eastern India

Integrated Use of Remote Sensing and GIS in estimating Soil Erosion in the Tukvar Tea Plantation Area, Darjeeling, India by RUSLE Modelling

Soil erosion is one of the major threats to food security and agricultural sustainability worldwide. Numerous factors including relief, slope, land use, land cover, rainfall pattern, soil texture, conservation techniques and anthropogenic factors, combine to cause soil erosion. The enormity and spatial distribution of soil erosion should be known for effectively assessing and mapping erosion-prone areas. In the hill region, soil loss is a significant component in decreasing stability and persistent loss causes landslides. So in order to study this, various soil erosion models have come up amongst which RUSLE has been adopted by many researchers. The goal of the current study is to forecast the projected soil loss in Tukvar tea plantations of the Darjeeling district. This study will provide an estimate of the amount and rate of erosion in the Darjeeling district's Tukvar tea plantations. This study revealed that the leading factors to soil erosion are slope factors and rainfall erosivity. The geo-coded reference of the geographic extent of soil erosion-prone areas will be useful for micro-level planning and will serve as a useful tool for managing and conserving soil.

Soil Erosion Estimation of Kunthippuzha Watershed Using GIS and RUSLE Model

Soil erosion is an environmental crisis in the world today that threatens the natural environment and also agriculture. Erosion removes the top fertile soil, degrades soil fertility, water quality and soil productivity. The soil erosion risk assessment is helpful for land evaluation in the regions where soil erosion is a major threat for sustainable agriculture. Modelling can provide a quantitative and consistent approach to estimate soil erosion and sediment yield under a wide range of conditions. The soil erosion and erosion prone areas in the Kunthippuzha sub-watershed of Bharathapuzha river basin, Kerala, India was estimated using RUSLE. The study area is having a drainage area of 950 km2 up to the gauging station. The estimation was done for 1990 to 2021. The estimated rainfall erosivity, soil erodibility, Slope length and slope steepness factor and crop management factors range from 929.36 and 980.38 MJ mm ha-1 h-1 yr-1, 0.01387 to 0.0385 t ha h ha−1 MJ−1 mm−1, 0 to 9.77 and 0.057796 to 1.0999. The results indicate that the estimated total annual potential soil loss of about 842175 t/y is comparable with the measured sediment of 845500 t/yr during the years 1990-2021. The soil erosion rate categorized into six classes based on the erosion severity, the major portion (60%) of the study area comes under very slight erosion zone and only a small portion (14%) comes under severe and very severe erosion zone. Result suggests the area of the north-eastern part suffers from a high soil erosion risk due to steep slope. The results can certainly aid in implementation of soil management and conservation practices to reduce the soil erosion in the Kunthippuzha sub-watershed.

Impacts of Land Use Changes on Soil Functions and Water Security: Insights from a Three-Year-Long Study in the Cantareira System, Southeast of Brazil

Maintaining soil functions is crucial for human well-being, but there is a lack of integration between soil, water security, ecosystem services, and climate change. To bridge this knowledge gap and address erosion-induced soil and water losses and considering intrinsic impacts of soil structure, a three-year-long study was conducted focused on three dominant soil types (Typic Hapludult, Typic Dystrudept, and Typic Usthortent) combined with different land uses (native forest, eucalyptus plantation, rotational grazing, and extensive grazing) in a critical water supply region for the São Paulo metropolitan area in Southeastern Brazil. Surface runoff, evaluated for erosion resistance, was measured using the Cornell infiltrometer, and soil electrical resistivity tomography estimated soil water content to a depth of 1.5 m for groundwater recharge analysis. Soil hydraulic properties were also measured. The results revealed that native forest soils had higher hydraulic conductivity, particularly in the surface layer, compared to eucalyptus and pastures. Native forests in Typic Hapludult showed a higher runoff rate (200 to 250 mm h−1) due to a naturally dense subsoil layer that negatively impacted water infiltration and recharge with a high erosion potential, therefore reducing the amount of water stored. Typic Usthortent maintained a higher soil water content in pastures than in other land uses and also showed a low rate of water infiltration, resulting in perched water in the surface layer. In Typic Dystrudept, the native forest presented higher hydraulic conductivity (0–5 cm: 115.9 cm h−1) than eucalyptus (0–5 cm: 36.4 cm h−1), rotational grazing (0–5 cm: 19.4 cm h−1), and extensive grazing (0–5 cm: 2.6 cm h−1), but there were no significant differences in soil water content among land uses. This work illustrates the crucial role of native forests in affecting deep water recharge, reducing the soil surface erosion, mainly in soils without naturally subsoil layer, maintaining recharge potential. For Ultisols, pastures preserved soil structure and are therefore less impacted by soil management. With these results, a contribution is made to soil and water conservation, providing support for sustainable management practices in erosion-prone areas.

Spatial and Temporal Patterns of Ecosystem Services and Trade-Offs/Synergies in Wujiang River Basin, China

Analysis of the relationships among ecosystem services (ESs) can help ensure that benefits from ecosystems are consistent over time. This study explored the spatial and temporal patterns of water supply (WS), grain supply (GS), carbon storage (CS), water conservation (WC), soil conservation (SC), and habitat quality (HQ) in the Wujiang River Basin (WJRB) from 2000 to 2020 and the trade-off/synergy relationships of ESs. The ESs in the WJRB are downstream &gt; midstream &gt; upstream in space, with the greatest increase and decrease in the upstream and midstream temporal dimensions, respectively. The WS, WC, and SC underwent a trend shift in 2005 due to climatic influences, whereas GS and HQ underwent a trend shift in 2010 due to human social development. GS formed a trade-off with other ESs in the spatial pattern, whereas WS formed a trade-off with CS and WC in the temporal dimension. Adjusting the GS spatial pattern reduces the trade-off between ESs in the spatial pattern, allowing for focusing on monitoring soil and water erosion-prone areas to prevent extensive soil erosion during heavy precipitation years; this reduces the trade-off between ESs in the time dimension in the WJRB. This provides a theoretical basis for achieving high-quality WJRB development.

Identification of erosion-prone areas using morphometric, hypsometric, and compound factor approaches in the Ruvu River Basin, Tanzania

Identification of erosion-prone areas using morphometric, hypsometric, and compound factor approaches in the Ruvu River Basin, Tanzania

Application of geospatial technique and hydrological modelling in evaluating reservoir sedimentation in Chhattisgarh state of India

ABSTRACT Soil erosion and sediment deposition in the reservoirs are both consequences of the change in precipitation pattern that has been observed over the past decade. For the purpose of storing water in reservoirs built before the 1980s, the Indian state of Chhattisgarh has a few irrigation projects. As the state has grown, agricultural land has increased while the proportion of forest area has decreased. Due to this development, runoff is introducing more sediment into the reservoirs, resulting in a reduction in intended storage. The effects of sediment deposition in the Kodar reservoir, located in the Mahasamund district of Chhattisgarh State, are evaluated in present study. Prior to five years, the reservoir reported a 30% deficit in actual irrigation. To quantify the sediment load, Remote Sensing (RS), Geographic Information System (GIS), and the Hydrologic Engineering Centre – Hydrologic Modelling System (HEC-HMS) were effectively employed. From 2012 to 2014, the reservoir received an average sediment load of 1.11 million tonnes. In order to preserve soil in the watershed’s erosion-prone area, a treatment plan is developed. It includes numerous thematic maps that are overlaid in order to provide preventive measures against reservoir sedimentation and is further proposed in the form of best management practices.