Assessment of soil erosion rate and hotspot areas using RUSLE and multi-criteria evaluation technique at Jedeb watershed, Upper Blue Nile, Amhara Region, Ethiopia

An understanding of the spatial variation and influence factors of soil nutrients in mining areas can provide a reference for land reclamation and ecological restoration. Daliuta was used as the study area. The spatial variability of soil nutrients was analyzed using traditional statistics and geostatistics. The effects of topography, mining history, and soil erosion were discussed. The results indicate that the soil pH of the Daliuta mining area is slightly acidic to slightly alkaline, and the soil organic matter, available nitrogen, available phosphorus, and available potassium belonged to the five levels (very low), six (extremely low), five (extremely low), and four (moderately low), respectively. The soil water and salt content indicated that the soil environment in the mining area is arid and has normal levels of salinity. The organic matter, available nitrogen, available phosphorus, available potassium, and soil salt varied moderately, and the pH did not change much, while the soil water varied strongly. The organic matter, pH, and soil salinity are moderately spatially autocorrelated, and the available nitrogen, available phosphorus, available potassium, and soil water are weakly spatially autocorrelated. Each nutrient index had a certain spatial trend effect. The slope, aspect, elevation, and topographic wetness index are the primary topographic factors that control the spatial distribution of soil nutrients. The organic matter, pH, and soil salinity are moderately spatially autocorrelated, and the available nitrogen, available phosphorus, available potassium, and soil water are weakly spatially autocorrelated. Each nutrient index had a certain spatial trend effect. The slope, aspect, elevation, and topographic wetness index are the primary topographic factors that control the spatial distribution of soil nutrients. Soil erosion and mining history are also important factors that lead to the spatial variation of soil nutrients.

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“…To extract the soil erosion information, the revised universal soil loss equation RUSLE model [46] was used, and the formula was as follows:…”

Section: Data Processing Methodsmentioning

confidence: 99%

Analysis of Spatial Variability and Influencing Factors of Soil Nutrients in Western China: A Case Study of the Daliuta Mining Area

et al. 2022

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“…Different researchers classify land use/land cover in different ways. In the Geleda watershed, soil loss severity is classified as low (0-11), moderate (11)(12)(13)(14)(15)(16)(17)(18), high (18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), very high (30-50), and severe (50-237) in tons per hectare per year [34]. According to [35], there are four types of soil loss in tons per hectare per year: very slight (0-4), slight (5-9.99), moderate (10-24.99), and severe (25-44.99).…”

Section: Sediment Yield Hotspot Area Classificationmentioning

confidence: 99%

“…According to [35], there are four types of soil loss in tons per hectare per year: very slight (0-4), slight (5-9.99), moderate (10-24.99), and severe (25-44.99). Soil erosion in the Wondo Genet watershed is classified as low (0-5), moderate (5)(6)(7)(8)(9)(10)(11), high (11)(12)(13)(14)(15)(16)(17)(18)(19)(20), very high (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), severe (45-60), and very severe (>60) in tons per hectare per year [36]. erefore, there are no distinct intervals between soil severity classes.…”

Section: Sediment Yield Hotspot Area Classificationmentioning

confidence: 99%

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Sediment Yield Modeling and Mapping of the Spatial Distribution of Soil Erosion-Prone Areas

Sime

Abebe

2022

Applied and Environmental Soil Science

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Sediment movement is the most critical problem in Ethiopia, notably in the Ketar River watershed, which is located in the Rift Valley Basin. The Ketar River flows through rugged terrain with steep slopes and high sediment movement. The purpose of the study is to evaluate the Soil and Water Assessment Tool's (SWAT) ability to simulate sediment and to identify areas that are vulnerable to soil erosion. This will aid water resource planners in determining the appropriate corrective action. In SWAT sediment sensitivity analysis, the USLE soil erodibility factor (USLE-K) is found to be the most sensitive sediment parameter. The SWAT model sediment simulation performance is evaluated using the coefficient of determination (R2) and Nash-Sutcliffe Efficiency (NSE). The model performance results in R2 and NSE values of 0.69 and 0.55 for calibration and 0.73 and 0.51 for validation, respectively, using the SWAT Calibration and Uncertainty Program (SWAT-CUP). The sediment-prone area subbasins have steep slopes and were mostly covered by cultivated land. Annual sediment yield from cultivated land was approximately 1872.12 t/y, while yield for moderately cultivated grassland was 171.45 t/y. Woodland and forest land have less soil erosion rate. The subbasin highly covered by Eutric Nitisols is found in very high soil erosion-prone areas. Sediment yield from a slight slope is almost zero, whereas sediment yield from steep and very steep slopes is very high. The slope of the subbasin is an important factor in determining sediment yield, followed by land cover and soil types. The very high sediment yield rate area accounted for 39.64% of the total subbasin and it needs soil conservation planning.

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“…This region belongs to oxisol laterite, which is more convinced by weathering and erosion by climatic properties. This soil category is one of the significant aspects that induced the erosion procedure (Getnet et. al 2021).…”

Section: Soil Loss In the Gully Formation Areasmentioning

confidence: 99%

Assessment of Intensity and Susceptibility of Gully Erosion through Multiple Discriminate Factors Analysis using Geospatial Techniques in Birbhum District of Rarh Region of West Bengal

Mondal

Basu

Lee

2022

Preprint

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The present study focuses on the identification of the intensity and susceptibility of gully erosion and induced soil erosion in the selected areas of Birbhum district of West Bengal, India. The geospatial techniques have been employed using the meticulous remotely sensed satellite data of Birbhum district. The composite gully erosion susceptibility maps have been prepared based on the aggregation of the normalized values of each indicator using factor analysis of the year 2001. It reveals from the maps that Rampurhat-I and Bolpur-Santiniketan blocks of Birbhum district have faced an excessive loss of lateritic soil cover mostly by the gully erosion during the monsoon season concerning the relationship between soil erosivity and other factors. About 23.45 percent and 20.59 percent area of the total area under Rampurhat-I and Bolpur-Santiniketan blocks are under gully erosion susceptibility zones. The LULC and landholding sizes are despoiled with an increasing rate of soil erosion in the gully areas during the study period. The identification of gully erosion hot spot areas, intensity mapping, and accurate prediction will help to formulate highly insightful, well-developed strategies for adaptation of imperative planning to rectify the soil loss, and soil degradation and assist in eco-efficient agriculture and improves the agri-environmental conditions.

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Assessment of soil erosion rate and hotspot areas using RUSLE and multi-criteria evaluation technique at Jedeb watershed, Upper Blue Nile, Amhara Region, Ethiopia

Cited by 33 publications

References 29 publications

Analysis of Spatial Variability and Influencing Factors of Soil Nutrients in Western China: A Case Study of the Daliuta Mining Area

Analysis of Spatial Variability and Influencing Factors of Soil Nutrients in Western China: A Case Study of the Daliuta Mining Area

Sediment Yield Modeling and Mapping of the Spatial Distribution of Soil Erosion-Prone Areas

Assessment of Intensity and Susceptibility of Gully Erosion through Multiple Discriminate Factors Analysis using Geospatial Techniques in Birbhum District of Rarh Region of West Bengal

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