Assessment of soil loss rate using GIS–RUSLE interface in Tashat Watershed, Northwestern Ethiopia

Mengie, Mequanent Abathun; Hagos, Yonas Gebresilasie; Malede, Demelash Ademe; Andualem, Tesfa Gebrie

doi:10.1007/s43217-022-00112-8

Cited by 23 publications

(8 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, different erosion rates in the Rift Valley Basin have been recorded. Degife et al (2021) discovered 37 t/ha/year in the Lake Hawassa watershed, and Jothimani et al (2022) estimated 68 t/ha/year in the Weito watershed, Woldesenbet et al (2020) found 30.5 t/ha/year in Meki river watershed, Meshesha et al (2012) reported 56 t/ha/year in Central Rift Valley, Wolka et al (2015) found 45 t/ha/year in the central rift valley, Abebe (2015) reported 68.7 t/ha/year in the Cheraqe Watershed Bilate Sub Basin, Mengie et al (2022) investigated 64.2 t/ha/year in Tashat Watershed, Northwestern Ethiopia, Negese et al (2021) found 38.7 t/ha year for Chereti Watershed, Northeastern Ethiopia, and Elnashar et al (2021) estimated 39.7 t/ha/year for the Blue Nile Basin.…”

Section: Resultsmentioning

confidence: 99%

Soil erosion variations along land use and land cover dynamics in Matenchose watershed, Rift Valley Basin, Southern Ethiopia

Mathewos

Tsegaye

Wondrade

2023

Natural Resource Modeling

View full text Add to dashboard Cite

The global community recognizes land use and land cover change (LULC) as a primary cause of ecological modification that has a considerable impact on natural resources, particularly soil and water resources. The aim of this research was to investigate land use change's influences on soil erosion in the Matenchose watershed of Ethiopia in 1991, 2003, and 2020. The maximum likelihood classification (MLC) method was used in the study for supervised image analysis. Soil erosion was estimated using the geographic information system (GIS), remote sensing, and the Revised Universal Soil Loss Equation (RUSLE) model. According to the LULC data from 1991, the watershed was mostly covered by grassland (35%), while in 2003 and 2020, it was typically enclosed by cultivated land (36%) and (52%), respectively. The watershed's mean annual soil erosion rate grew significantly from 13 t/ha in 1991 to 18 t/ha in 2003 to 21 t/ha in 2020. Based on the current soil loss rate result, the Matenchose watershed was divided into five priority groups for soil management practices. In contrast, the watershed is made up of 2052 ha (21%) of areas with high to very high erosion risk, 3304 ha (33%) of areas with moderate erosion risk, and 2866 ha (29%) of areas with severe erosion risk. Based on the average annual rate of soil erosion, several vital subwatersheds were identified for potential future land management‐related actions. Over the 29 years, the area of grassland and forest decreased while agricultural and settlement areas expanded, and they contributed to the enhanced hazards of soil erosion. Particularly vulnerable to erosion are the watershed's hilly and steeper areas. The identified subwatersheds that are most at risk of erosion should be given priority for upcoming LULC initiatives, proper participatory watershed planning and management, and measures to conserve soil and water to preserve the Matenchose watershed's soil resources.

show abstract

Section: Resultsmentioning

confidence: 99%

Soil erosion variations along land use and land cover dynamics in Matenchose watershed, Rift Valley Basin, Southern Ethiopia

Mathewos

Tsegaye

Wondrade

2023

Natural Resource Modeling

View full text Add to dashboard Cite

show abstract

“…For this investigation, the R factor was estimated using average annual precipitation data for the 21 years from 1990 to 2021. Equation (2) [3,33] was used to estimate the relationship between yearly precipitation and the R factor.…”

Section: Rainfall-runof Erosivity Factor (R)mentioning

confidence: 99%

“…Te Revised Universal Soil Loss Equation (RUSLE), established by [33], is widely utilized as an empirical method for calculating soil loss, specifcally in rill and inter-rill erosion situations. Te RUSLE model distinguishes itself from others due to its simplicity, adaptability, cost-efectiveness, and efciency.…”

Section: Introductionmentioning

confidence: 99%

Quantifying Soil Erosion in Drought-Impacted Central Odisha, India, through Geospatial Mapping with RUSLE

Dandapat,

Panda,

Sankalp

et al. 2024

Applied and Environmental Soil Science

View full text Add to dashboard Cite

Soil degradation in Odisha poses a significant conservation concern for the local environment. The present research focused on a region in central Odisha State, India, affected by drought conditions. Several models have emerged to assess soil loss, with the Revised Universal Soil Loss Equation (RUSLE) standing out as the most suitable option. The erosion computation process entails utilizing the digital elevation model (DEM), Landsat-9 imagery, and soil data from several sources accessible in different forms and scales. The present analysis took into account various elements, namely, crop management factor (C), practice management factor (P), slope length factor (LS), steepness factor of the slope (S), and rainfall factor (R). Multiplying these factors yielded the average rate of soil erosion. Areas with a high slope length factor, such as those in Kandhamal, Kalahandi, and Nuapada, have a high erosion rate. The study reveals that 57% of the land in the study area experiences very low to moderate soil erosion at a rate of 2–10 tons per hectare per year, while 43% faces moderately to very severe erosion at a rate of 10–25 tons per hectare per year. Erosion hotspots, covering 32,205 square kilometers, are mainly identified in agricultural and forested hilly areas where slopes exceed 10°, such as those in Kandhamal, Kalahandi, and Nuapada, which have a high erosion rate. These districts are especially vulnerable to soil loss and resulting climate action (Sustainable Development Goals-13) because of frequent and severe rainfall, shifting agricultural practices, a thin surface soil covering, natural erosion, and barren hills. The research emphasizes the urgent need for implementing conservation and management measures to protect high-risk areas from further degradation. In conclusion, the study underscores the effectiveness of the RUSLE-GIS model in conducting quantitative and spatial assessments of soil erosion on a river watershed scale. The model is deemed crucial in formulating conservation strategies to address the identified erosion issues in the tropical highlands of the area.

show abstract

“…Because of this difficulty, several models and techniques have been developed to simplify SE modelling and better our knowledge of the pattern and processes of SE. Previous researchers have found that RUSLE model outperformed other models in terms of accuracy and simplicity to estimate the potential soil erosion (Mengie at al., 2022;Somasiri et al, 2022). Therefore, in the present study, we used the RUSLE model to estimate the potential soil erosion for current and future scenarios.…”

Section: Introductionmentioning

confidence: 99%

Identifying Most Suitable Priority Areas for Soil-Water Conservation Using Coupling Mechanism in Guwahati Urban Watershed

Ahmed¹,

Talukdar²,

Naikoo³

et al. 2022

Preprint

View full text Add to dashboard Cite

The urban watershed of Guwahati, Assam, has witnessed a rapid urbanization in recent years, making it to one of the most deteriorated cities in terms of environmental issues. Therefore, this work focused on finding the most suitable soil-water conservation areas at a micro-scale using coupling coordination mechanism. Principal component analysis (PCA) was used to create a priority model for sub-watershed basin based on nineteen morphometric parameters. We then quantified the soil erosion using the revised universal soil loss equation (RUSLE) for current and future scenarios based on the representative concentration pathway (RCP) 2.6 and 8.5 models (RCP2.6 and 8.5). In addition, we proposed the fuzzy logic and analytical hierarchy process (AHP) model-based soil-water conservation suitability (SWPC) model for current and future scenarios. Finally, the most suitable soil-water conservation areas for current and future scenarios were identified using coupling coordination degree model (CCD). To the author’s knowledge, this is the first in-depth study that identifies the most suitable conservation areas by analyzing the watershed prioritization, soil erosion, and topographic, hydrologic, land cover, and climatic parameters-based soil-water conservation suitability models. Sub-watersheds comprising Silsako, Bharalu, Deepor Beel, and North Guwahati have been identified as high-priority sub-watersheds. According to the current RUSLE model, soil erosion in the study area varies from 140 to 181.64 tonnes per hectare per year. In contrast, soil erosion would continue to increase in the future as per the RCP8.5 model, which varies from 305 to 332 tonnes per hectare per year. The current SWPC model predicted 46.92 km2 area as high and 54.40 km2 area as very high suitable zones. However, under the RCP 2.6 and RCP 8.5 models, the high and very high SWPC zones will experience extended areas in the future due to increased soil erosion intensity. According to the CCDM results, Bharalu, Deepor Beel, and North-Guwahati sub-watersheds have observed a very high to medium coupling degrees, which are considered the most suitable areas for conservation. The findings of this study will significantly help stakeholders and experts in long-term land-water resource management and effectively address environmental degradation issues in urban watersheds around the world.

show abstract

Assessment of soil loss rate using GIS–RUSLE interface in Tashat Watershed, Northwestern Ethiopia

Cited by 23 publications

References 36 publications

Soil erosion variations along land use and land cover dynamics in Matenchose watershed, Rift Valley Basin, Southern Ethiopia

Soil erosion variations along land use and land cover dynamics in Matenchose watershed, Rift Valley Basin, Southern Ethiopia

Quantifying Soil Erosion in Drought-Impacted Central Odisha, India, through Geospatial Mapping with RUSLE

Identifying Most Suitable Priority Areas for Soil-Water Conservation Using Coupling Mechanism in Guwahati Urban Watershed

Contact Info

Product

Resources

About