Soil erosion assessment in the Blue Nile Basin driven by a novel RUSLE-GEE framework.

Assessment of soil loss and understanding its major drivers are essential to implement targeted management interventions. We have proposed and developed a Revised Universal Soil Loss Equation framework fully implemented in the Google Earth Engine cloud platform (RUSLE-GEE) for high spatial resolution (90 m) soil erosion assessment. Using RUSLE-GEE, we analyzed the soil loss rate for different erosion levels, land cover types, and slopes in the Blue Nile Basin. The results showed that the mean soil loss rate is 39.73, 57.98, and 6.40 t ha-1 yr-1 for the entire Blue Nile, Upper Blue Nile, and Lower Blue Nile Basins, respectively. Our results also indicated that soil protection measures should be implemented in approximately 27% of the Blue Nile Basin, as these areas face a moderate to high risk of erosion (>10 t ha-1 yr-1). In addition, downscaling the Tropical Rainfall Measuring Mission (TRMM) precipitation data from 25 km to 1 km spatial resolution significantly impacts rainfall erosivity and soil loss rate. In terms of soil erosion assessment, the study showed the rapid characterization of soil loss rates that could be used to prioritize erosion mitigation plans to support sustainable land resources and tackle land degradation in the Blue Nile Basin.

Elnashar A ，Zeng H ，Wu B ，Fenta AA ，Nabil M ，Duerler R ... -  《-》

The nexus between land use, land cover dynamics, and soil erosion: a case study of the Temecha watershed, upper Blue Nile basin, Ethiopia.

At the current times, soil erosion is the major problem that affects land and water resources, especially in Ethiopia's highlands. Due to the dynamics of land use land cover change, land degradation, and soil erosion increase significantly and result in a loss of fertile soil every year and lead reduction in agricultural production. This study was therefore designed to explore the land use land cover (LULC) dynamics from 1986 to 2020, to estimate mean annual soil erosion rates and identify erosion hotspot areas from 1986 to 2020, and finally, to evaluate the impacts of land use land cover change on soil loss of 1986 to 2020. For this, Landsat imageries of 4 years from 1986 to 2020 were used. Maximum likelihood supervised classification methods were used to classify LULCs. The dynamics of LULC change were used as an input for measuring soil loss by employing the combination of geospatial technologies with the revised universal soil loss equation (RUSLE). The LULC maps of 1986, 1997, 2009, and 2020 were used for identifying crop management (C) factor and conservation practice (P) factor. Rainfall erosivity factor (R), soil erodibility factor (K), and slope length and steepness factor (LS) were also used as sources of data. Based on the five factors, soil erosion intensity maps were prepared for each year. Results showed that the annual soil loss in the watershed ranged from 0 to 3938.66 t/ha/year in 1986, 0 to 4550.94 t/ha/year in 1997, 0 to 5011.21 t/ha/year in 2009, and 0 to 6953.23 t/ha/year in 2020. The annual soil loss for the entire watershed was estimated at 36.889, 42.477, 47.805, and 48.048 t/ha/year in 1986, 1997, 2009, and 2020, respectively. The mean soil loss of 1986, 1997, 2009, and 2020 was higher in cultivated land followed by shrub land, grazing land, and forest land. Mean soil loss increased from 1986 to 1997, from 1997 to 2009, and from 2009 to 2020. This is because of the expansion of agricultural land at the expense of grazing land and shrub land. Therefore, urgent soil and water conservation practices should be made in hotspot areas.

Tilahun A ，Asmare T ，Nega W ，Gashaw T ... -  《-》

Soil erosion assessment and identification of erosion hotspot areas in the upper Tekeze Basin, Northern Ethiopia.

Soil erosion is a major environmental problem in Ethiopia, reducing topsoil and agricultural land productivity. Soil loss estimation is a critical component of sustainable land management practices because it provides important information about soil erosion hotspot areas and prioritizes areas that require immediate management interventions. This study integrates the Revised Universal Soil Loss Equation (RUSLE) with Google Earth Engine (GEE) to estimate soil erosion rates and map soil erosion in the Upper Tekeze Basin, Northern Ethiopia. SoilGrids250 m, CHIRPS-V2, SRTM-V3, MERIT Hydrograph, NDVI from sentinel collections and land use land cover (LULC) data were accessed and processed in the GEE Platform. LULC was classified using Random forest (RF) classification algorithm in the GEE platform. Landsat surface reflectance images from Landsat 8 Operational land imager (OLI) sensors (2021) was used for LULC classification. Besides, different auxiliary data were utilized to improve the classification accuracy. Using the RUSLE-GEE framework, we analyzed the soil loss rate in different agroecologies and LULC types in the upper Tekeze basin in Waghimra zone. The results showed that the average soil loss rate in the Upper Tekeze basin is 25.5 t ha-1 yr-1. About 63 % of the basin is experiencing soil erosion above the maximum tolerable rate, which should be targeted for land management interventions. Specifically, 55 % of the study area, which is covered by unprotected shrubland is experiencing mean annual soil loss of 34.75 t ha-1 yr-1 indicating the need for immediate soil conservation intervention. The study also revealed evidence that this high mean soil loss rate of the basin can be reduced to a tolerable rate by implementing integrative watershed management and exclosures. Furthermore, this study demonstrated that GEE could be a good source of datasets and a computing platform for RUSLE, in particular for data scarce semi-arid and arid environments. The results from this study are reliable for decision-making for rapid soil erosion assessment and intervention prioritization.

Fentaw AE ，Abegaz A 《Heliyon》

Geospatial technology for assessment of soil erosion and prioritization of watersheds using RUSLE model for lower Sutlej sub-basin of Punjab, India.

Erosion of soil by water coupled with human activities is considered as one of the most serious agents of land degradation, posing severe threat to agricultural productivity, soil health, water quality, and ecological setup. The assessment of soil erosion and recognition of problematic watersheds are pre-requisite for management of erosion hazards. In the present study, Revised Universal Soil Loss Equation (RUSLE) integrated with remote sensing (RS) and geographic information system (GIS) has been used to assess the soil erosion in lower Sutlej River basin of Punjab, India, and prioritize the watersheds for implementation of land and water conservation measures. The total basin area was about 8577 km2 which was divided into 14 sub-watersheds with the area ranging from 357.8 to 1354 km2. The data on rainfall (IMD gridded data), soil characteristics (FAO soil map), topography (ALOS PALSAR DEM) and land use (ESRI land use and land cover map) were prepared in the form of raster layers and overlaid together to determine the average annual soil loss. The results revealed that the average annual soil loss varied from 1.26 to 25 t ha-1, whereas total soil loss was estimated to be 2,441,639 tonnes. The spatial distribution map of soil erosion showed that about 94.4% and 4.7% of the total area suffered from very slight erosion (0-5 t ha-1 year-1) and slight erosion (5-10 t ha-1 year-1), respectively, whereas 0.11% (9.38 km2) experienced very severe soil loss (> 25 t ha-1 year-1). Based on estimated average annual soil loss of sub-watersheds, WS8 was assigned the highest priority for implementation of soil and water conservation measures (323.5 t ha-1 year-1), followed by WS9 (303.8 t ha-1 year-1), whereas WS2 was given last priority owing to its lowest value of soil loss (122.02 t ha-1 year-1). The present study urges that conservation strategies should be carried out in accordance with the priority ranking of diverse watersheds. These findings can certainly be used to implement soil conservation plans and management practices in order to diminish soil loss in the river basin.

Sharma N ，Kaushal A ，Yousuf A ，Sood A ，Kaur S ，Sharda R ... -  《-》

Assessment of environmentally sensitive areas to desertification in the Blue Nile Basin driven by the MEDALUS-GEE framework.

Assessing environmentally sensitive areas (ESA) to desertification and understanding their primary drivers are necessary for applying targeted management practices to combat land degradation at the basin scale. We have developed the MEditerranean Desertification And Land Use framework in the Google Earth Engine cloud platform (MEDALUS-GEE) to map and assess the ESA index at 300 m grids in the Blue Nile Basin (BNB). The ESA index was derived from elaborating 19 key indicators representing soil, climate, vegetation, and management through the geometric mean of their sensitivity scores. The results showed that 43.4%, 28.8%, and 70.4% of the entire BNB, Upper BNB, and Lower BNB, respectively, are highly susceptible to desertification, indicating appropriate land and water management measures should be urgently implemented. Our findings also showed that the main land degradation drivers are moderate to intensive cultivation across the BNB, high slope gradient and water erosion in the Upper BNB, and low soil organic matter and vegetation cover in the Lower BNB. The study presented an integrated monitoring and assessment framework for understanding desertification processes to help achieve land-related sustainable development goals.

Elnashar A ，Zeng H ，Wu B ，Gebremicael TG ，Marie K ... -  《-》