Optimizing soil erosion estimates of RUSLE model by analyzing land use/cover dynamics in upper Awash River Basin, Central Ethiopia

Mekonnen, Eyasu; Kebede, Asfaw; Asfaw, Solomon; Feyissa, Samuel

doi:10.1080/19475705.2023.2257363

Cited by 3 publications

(1 citation statement)

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“…Such delineation enables the implementation of targeted conservation strategies, allowing for focused efforts on land-use categories that are most vulnerable. The evaluation of the effectiveness of existing conservation strategies through the conservation practice (P) factor plays a pivotal role in guiding the enhancement and optimization of erosion control measures [33].…”

Section: Discussionmentioning

confidence: 99%

Integrating RUSLE Model with Cloud-Based Geospatial Analysis: A Google Earth Engine Approach for Soil Erosion Assessment in the Satluj Watershed

Sud,

Sajan,

Kanga

et al. 2024

Water

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This study employed an advanced geospatial methodology using the Google Earth Engine (GEE) platform to assess soil erosion in the Satluj Watershed thoroughly. To achieve this, the Revised Universal Soil Loss Equation (RUSLE) model was integrated into the study, which was revealed through several analytical tiers, each with a unique function. The study commenced with estimating the R factor, which was carried out using annual precipitation data from the Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS). The erodibility of the soil, which the K factor describes, was then calculated using the USDA soil texture classifications taken from the Open Land Map. The third layer emphasizes the LS factor, which analyzes slope data and how they affect soil erosion rates, using digital elevation models. To understand the impact of vegetation on soil conservation, the fourth layer presents the C factor, which evaluates changes in land cover, and the Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2 data. The P factor incorporates MODIS data to assess the types of land cover and slope conditions. Combining these layers with the RUSLE model produces a thorough soil loss map, revealing different levels of soil erosion throughout the Satluj Watershed. The preliminary findings indicate that 3.3% of the watershed had slight soil loss, 0.2% had moderate loss, and 1.2% had high soil erosion rates. And 92% had severe rates of soil erosion. After a thorough investigation, the detected regions were divided into risk classifications, providing vital information for the watershed’s land management and conservation plans. The mean soil loss throughout the watershed was determined to be 10,740 tons/ha/year. This novel method creates a strong foundation for evaluating soil erosion, while also highlighting the value of the cloud-based geospatial analysis and the RUSLE model in comprehending intricate environmental processes.

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Section: Discussionmentioning

confidence: 99%