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River Nzoia basin is predisposed to degradation attributed to poor anthropogenic land use practices, soil erosion and sedimentation. The objective of this study was to model soil erosion hazard and estimate sediment yield for river Nzoia basin. Database of the basin comprised of 90 m DEM, LandSat imagery, rainfall, and soil data. Simulated RUSLE mo...
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... It describes soil safety by type of land cover and thickness. It ranges from 1 in the severe to 1/1000 in bare soil, 1/100 in grassland and undercover plants, and 1-9/10 in root and tuber crops (Moses 2017). A feature used in the RUSLE model to understand how the percentage of C-factor affects the soil cover erosion. ...
Soil degradation is a significant global problem for multiple infrastructures with negative commercial and ecological influences. The loss of productive soil is frequently triggered by surficial land depletion, farming escalation, erosion, and poor anthropogenic land-use practices. In watershed analyses, estimating soil erosion is useful for future planning and development. It is also important in designing hydropower projects as it yields sedimentation influx in the dam reservoirs. The manual assessment of soil loss is always challenging due to serious safety issues and limited resources; therefore, Geographical Information System and Remote sensing techniques are considered the best tools for this purpose. Current research applies an empirical method, namely the Revised Universal Soil Loss Equation model, to compute the Mohmand Dam watershed soil loss represented by A in tonnes per hectare per year. The parameters of the RUSLE model are empirically calculated using a raster calculator, and the final map shows an aggregated impact on soil loss. The study revealed that the maximum annual soil loss of the study area was approximately 30–1913 tonnes h−1 year−1 which covers only 1.5% of the total watershed area. However, the frequent erosion values lie between 0 and 10 tonnes h−1 year−1. The soil loss is almost negligible in 75% of the Watershed, less than 5 tons h−1 year−1. This comprises about 11179.22 sq. km or 2,762,440 acres area of the Watershed. This study revealed that the area is not hazardously prone to soil erosion with a low sedimentation rate indicating a prolonged storing capacity.
... Erosion is a major issue in various local and regional areas, particularly those with extensive arid and semiarid regions, such as KSA, which are characterized by long dry seasons [65,66]. Rainfall erosivity, soil erodibility, and LULC factors, which are the primary parameters for estimating soil loss in the RUSLE model, contribute to soil erosion [67,68]. Separate spatial maps of RUSLE parameters were prepared for this study and used in TerrSet software to estimate sediment retention. ...
This study examines the sediment retention in Wadi Baysh using the Revised Universal Soil Loss Equation (RUSLE) and TerrSet models, accompanied by integrated remote sensing and Geographic Information System (GIS) techniques. The contribution of this study is mainly associated with the application of TerrSet integrated with high resolution datasets to precisely estimate sediments load, which provide useful information to operate dams and improve the operational efficiency of dams. The Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data are utilized to delineate the basin and have been used as an input to the TerrSet model. The rainfall erosivity (R factor) was calculated using the Climate Hazards Center Infrared Precipitation with Stations (CHIRPS) in the research area during 2015–2020. The soil erodibility (K factor) and LULC categorization are calculated using the digital soil map of the world (DSMW) and Sentinel-2 datasets, respectively. The R factor calculated for Wadi Baysh ranges between 91.35 and 115.95 MJ mm/ha/h/year, while the estimated K factor ranges from 0.139 to 0.151 t ha h/ha M. The Support Vector Machine (SVM) method categorized LULC of the study area into four major classes including barren land (81% of the total area), built-up area (11%), vegetation (8%), and water bodies (1%). Results from the sediment retention module (TerrSet) indicated that each year, 57.91 million tons of soil loss occurred in the basin. The data show that soil loss is greater in the northeast and south, whereas it is typical in the middle of Wadi Baysh. It is concluded from the current analyses that the dam lake of Wadi Baysh, located downstream, will be filled soon in the coming few years if sediment loads are carried to the lake at the same rate. Surface dam operators can obtain a full understanding of sedimentation and take proactive measures to reduce its influence on dam operations by leveraging TerrSet’s sophisticated capabilities.
... Depending on soil type, the amount of energy required to extract and transport soil varies a soil's ability to erode is low if it has a low silt content, even if it has a high sand and clay concentration. The digital soil map of the study area identified seven distinct soil types with unique features [24][25][26][27][28]. With K-factor values ranging from 0.05 to 0.36 tons per hour, ha -1 , MJ -1 , mm -1 , the erodibility of the existing soils in the study area varied. ...
... Hence the researchers from various countries rely on Google Earth images to validate their models. A number of researchers have validated their results from the RUSLE model with the help of Google Earth images (Behera et al. 2020;Balasubramani et al. 2015;Moses 2017;Khan and Govil 2020). ...
Water-induced soil erosion is one of the challenging threats in various parts of the world, thus systematic investigations of soil loss risk are more crucial for sustainable agricultural production and water management. The present study was carried out to estimate the average soil loss in the Amravati watershed of Tamil Nadu state in South India using Revised Universal Soil Loss Equation (RUSLE) along with Geographical Information System (GIS) and Remote Sensing techniques. In this study, the rain gauge-based rainfall data were completely substituted with the CHIRPS datasets to compute the R factor, since it gives continuous surface rainfall data rather than location-based measurement. The estimated soil loss in the watershed was found to be in the range of 0–280.2 t/ha−1/yr−1, in which about 64.7% of the watershed under very low erosion risk whilst about 12.9% of the area prone to moderately high-to-very high erosion risk. The maximum soil loss rate was identified in the Degraded forest with a mean loss of 59.51 t/ha−1/yr−1 followed by the Degraded plantation (32.17 t/ha−1/yr−1), Scrubland/Wasteland (17.75 t/ha−1/yr−1), Current fallow (12.08 t/ha−1/yr−1), and Rainfed cropland (10.03 t/ha−1/yr−1). The study shows that the present land use / land cover and the landscape of the watershed have a great influence on soil loss. To check the efficiency of the RUSLE model for the assessment of soil erosion risk, the final derived output was validated with the use of 4k UHD Google Earth images.
... The highest values correspond to the more dense vegetation cover.Numerous empirical relationships or equations have been established to relate the values of NDVI to the values of factor C (Phinzi and Ngetar 2019). These equations have been applied in several studies around the world, namely, regression equation to calculate the C factor(Dutta et al. 2015;Moses 2017;Uddin et al. 2016) who used De jong (1994. ...
The Moroccan High Atlas is very sensitive to soil erosion due to its steep slopes, torrential rains, and degraded plant cover. The degradation of fertile soils in this mountainous watershed influences negatively upon agricultural productivity. The objective of this study is to quantify soil erosion in the Tifnout Askaoun watershed in southern Morocco. The Revised Universal Soil Loss Equation (RUSLE), the geographic information system (GIS) techniques, and the Tropical Rainfall Measuring Mission (TRMM) data were adopted for mapping the annual rate of soil loss in this watershed area of around 1488 km2. The spatial distribution of annual soil erosion rates was obtained by integrating the geo-environmental variables into a GIS. These variables are the rainfall erosivity (R) generated from the TRMM data, the soil erodibility factor (K), the length and slope inclination (LS), the vegetation and management factor (C), and the practice support factor (P). Results reveal an average annual soil erosion rate of 14.44 t/ha/year and a good correlation with the slope length and steepness factor (r = 0.72) and in a lesser extent with the rainfall erosivity factor (r = 0.63). The sub-catchments of the study area were mapped and grouped into five classes of vulnerability to soil erosion risk, with results indicating that the Toubkal sub-catchment is the most threatened by water erosion risk as reflected by an average erosion rate of 48.05 t/ha/year. Approaches and results from this study, which was conducted between 2017 and 2019, may benefit researchers and decision-makers concerned with soil management primarily in mountainous areas where soil degradation impacts the activities of the rural population.
... Ethiopia is susceptible to soil erosion hazards due to torrential rains, steep slopes, improper land support practices, and lack of soil covers [6,66]. From the main parameters of estimating soil loss in the RUSLE model, rainfall erosivity, soil erodibility, and slopesteepness factors contribute to soil erosion [82,83] and the cover-management and the controlling practice factors play a preventive function [84]. Fort this study, the spatial data sets of RUSLE factors were prepared separately and used for the estimation of the soil loss. ...
... The higher slopes (0-260%) of the Kirindi Oya catchment provide a higher LS-factor (0-725) which results in a higher soil loss than the Anjeb watershed. The soil loss of Anjeb watershed is higher than Nzoia basin in Mountain Elgon (0.51 t ha −1 yr −1 ) [82] of Kenya which has a mountainous and hilly topography in its upper part and flat plains in its lower part with a mean elevation of 2300 m a.s.l and an average annual rainfall of 1375 mm. Nzoia basin has a lower R-factor (339.4-855 ...
Soil erosion is a serious and continuous environmental problem in Ethiopia. Lack of land use planning, environmental protection, over-cultivation, and overgrazing are prominent causes of erosion and sedimentation. This study is conducted in Anjeb watershed located in the Upper Blue Nile Basin, Ethiopia. In this study, the quantity and distribution of soil erosion, sediment delivery ratio (SDR), and sediment yield of the watershed were assessed by employing remote sensing, geographic information system (GIS), and revised universal soil loss equation analysis capabilities. Important data sets of topography, soil, conservations practices, cover management, and rainfall factors were processed and superimposed in GIS analysis, and soil loss rate, SDR, and sediment yield of the watershed were derived. Based on the result found, the watershed was categorized into six classes of erosion: slight (0–5), moderate (5–10), high (10–15), very high (15–30), severe (30–50), and very severe (> 50) t ha−1 yr−1. The estimated average annual soil loss was 17.3 t ha−1 yr−1. The soil loss rate is higher in the steeper and topographically dissected part of the watershed. The average sediment delivery capacity was about 0.122. The result showed that the average sediment yield in the watershed was grouped into classes of low (< 2.5), moderate (2.5–7.5), high (7.5–12.5), very high (12.5–22.5), severe (22.5–40), and very severe (> 40) t ha−1 yr−1. It is found that from a total of 20,125.5 t yr−1 eroded soil over the whole watershed 2254.5 t yr−1 of sediment has been brought and deposited to the channels. Sediment accumulation from the watershed threatens the storage capacity and life span of Anjeb reservoir which is the source of irrigation water downstream. The study provides an insight to planners and resource managers to design and implement practices of watershed management to reduce erosion and enhance land productivity and to minimize the reservoir sediment accumulation.
... Ethiopia is susceptible to soil erosion hazards due to torrential rains, steep slopes, improper land support practices, and lack of soil covers [6,66]. From the main parameters of estimating soil loss in the RUSLE model, rainfall erosivity, soil erodibility, and slopesteepness factors contribute to soil erosion [82,83] and the cover-management and the controlling practice factors play a preventive function [84]. Fort this study, the spatial data sets of RUSLE factors were prepared separately and used for the estimation of the soil loss. ...
... The higher slopes (0-260%) of the Kirindi Oya catchment provide a higher LS-factor (0-725) which results in a higher soil loss than the Anjeb watershed. The soil loss of Anjeb watershed is higher than Nzoia basin in Mountain Elgon (0.51 t ha −1 yr −1 ) [82] of Kenya which has a mountainous and hilly topography in its upper part and flat plains in its lower part with a mean elevation of 2300 m a.s.l and an average annual rainfall of 1375 mm. Nzoia basin has a lower R-factor (339.4-855 ...
Soil erosion is a serious and continuous environmental problem in Ethiopia. Lack of land use planning, environmental protection, over-cultivation, and overgrazing are prominent causes of erosion and sedimentation. This study is conducted in Anjeb watershed located in the Upper Blue Nile Basin, Ethiopia. In this study, the quantity and distribution of soil erosion, sediment delivery ratio (SDR), and sediment yield of the watershed were assessed by employing remote sensing, geographic information system (GIS), and revised universal soil loss equation analysis capabilities. Important data sets of topography, soil, conservations practices, cover management, and rainfall factors were processed and superimposed in GIS analysis, and soil loss rate, SDR, and sediment yield of the watershed were derived. Based on the result found, the watershed was categorized into six classes of erosion: slight (0–5), moderate (5–10), high (10–15), very high (15–30), severe (30–50), and very severe (> 50) t ha⁻¹ yr⁻¹. The estimated average annual soil loss was 17.3 t ha⁻¹ yr⁻¹. The soil loss rate is higher in the steeper and topographically dissected part of the watershed. The average sediment delivery capacity was about 0.122. The result showed that the average sediment yield in the watershed was grouped into classes of low (< 2.5), moderate (2.5–7.5), high (7.5–12.5), very high (12.5–22.5), severe (22.5–40), and very severe (> 40) t ha⁻¹ yr⁻¹. It is found that from a total of 20,125.5 t yr⁻¹ eroded soil over the whole watershed 2254.5 t yr⁻¹ of sediment has been brought and deposited to the channels. Sediment accumulation from the watershed threatens the storage capacity and life span of Anjeb reservoir which is the source of irrigation water downstream. The study provides an insight to planners and resource managers to design and implement practices of watershed management to reduce erosion and enhance land productivity and to minimize the reservoir sediment accumulation.
... The highest values correspond to the more dense vegetation cover.Numerous empirical relationships or equations have been established to relate the values of NDVI to the values of factor C (Phinzi and Ngetar 2019). These equations have been applied in several studies around the world, namely, regression equation to calculate the C factor(Dutta et al. 2015;Moses 2017;Uddin et al. 2016) who used De jong (1994. ...
Etablir la carte prévisionnelle de l’aléa lié aux mouvements de terrain en utilisant l’analyse multicritère hiérarchique (ahp) intégrée dans un (sig).
... Phinzi and Ngetar (2019) presented a detailed review about a series of equations used in different RUSLE factors over the time period. RUSLE is capable of calculating the sediment yield of any river basin efficiently (Moses 2017). However, in monsoon-dominated areas of India RUSLE along with AHP yields good results in estimating sediment delivery ratio (Thomas et al. 2018). ...
This paper integrates drought and soil erosion problems of Puruliya district of West Bengal. The space-time dynamics of vegetative drought is assessed based on the mean monthly time-series MODIS data for the period of 2000–2013. The drought recurrence ranges from 0 to 29 months, and the mean frequency was assessed to be 7.09 months for the entire period under deliberation. The potential soil disintegration of the district was estimated using the Revised Universal Soil Loss Equation in the geo-spatial environment. The locale has been arranged into six potential soil erosion classes ranging from low-to-severe risk depending upon the computed soil erosion amount. The mean soil erosion rate of the district was anticipated as 76.29 t ha−1 year−1. The erosion amount is high in gently sloping grounds covering mainly harvested agricultural fields and open fields. These areas contribute mostly the soil erosion in this district. It is found that in this area the slope length-steepness factor is the major erosion-controlling factor. About one-fourth of the total area comes under the threat of a very high-to-severe erosion zone. Also, it was observed that the drought condition of the district is strongly correlated with the soil moisture condition in the drought-affected months and the precipitation amount. The study likewise distinguished the conceivable interrelationship between the soil erosion problem and drought frequency for better monitoring and policy decision making. A considerable increasing trend is observed in mean soil erosion with increasing frequency of drought-affected months for the study period.
... Most of this land was rainfed agricultural land. Even though primary dryland forests contribute to reducing the erosion rate (Moses, 2017), it was the smallest part covering Krueng Baro watershed (86.63 Ha). ...
Rapid erosion is a complex problem that affects regional environments and economies worldwide. Soil erosion should be spatially evaluated to develop effective land management strategies. In recent decades, soil erosion models have been integrated with geographic information systems (GISs) for the temporal-spatial analysis of soil erosion transport. The Universal Soil Loss Equation (USLE) has been used in many countries, and its input parameter data have been well established. In this study, a GIS was used to generate accurate estimates of the spatial distributions of the USLE parameters. According to the modeling of soil erosion, the watershed of the Krueng Baro river exhibited a spatially varied level of erosion. The interaction between the USLE factors significantly influenced the average of annual rate of soil loss. Evidently, the regions experiencing severe and very severe soil loss were closely correlated with steep gradients and deforestation. The low and very low rates of soil loss were associated with conservation practices and protected areas. The results of this study can be used by decision makers and planners to simulate regional scenarios and design interventions to reduce erosion.
