Spatiotemporal dynamics of soil loss and sediment export in Upper Bilate River Catchment (UBRC), Central Rift Valley of Ethiopia

Land use land cover change as a casual factor for climate variability and trends in the Bilate River Basin, Ethiopia

Land use and land cover (LULC) changes are crucial in influencing regional climate patterns and environmental dynamics. However, the long-term impacts of these changes on climate variability in the Bilate River Basin remain poorly understood. This study examines the spatiotemporal changes in LULC and their influence on climate variability in the Bilate River Basin, Ethiopia, over the period from 1994 to 2024. Utilizing multispectral satellite imagery from Landsat 5, 7, and 8, along with meteorological data from five stations, LULC was classified using the Random Forest algorithm on the Google Earth Engine platform. Climate variability and trends were assessed using the Mann-Kendall trend test, the Standardized Precipitation Index (SPI), and the Standardized Temperature Index (STI). The results reveal a consistent decline in forest cover, with a rapid annual loss of 4,681.2 hectares between 2014 and 2024. Concurrently, agricultural land expanded at an annual rate of approximately 1,141 hectares, while urban areas grew by 24.3 hectares annually in recent years. These LULC changes have contributed to significant climate variability in the region. The upper catchment experienced notable declines in rainfall and warming across all seasons. In the middle catchment, spring rainfall increased, accompanied by moderate summer warming. The lower catchment saw significant increases in spring and autumn rainfall, with no notable temperature trends. These findings highlight the critical impact of LULC changes on the region's climate and emphasize the need for sustainable land management and conservation practices to address deforestation, urbanization, and agricultural expansion.

Land use land cover change as a casual factor for climate variability and trends in the Bilate Watershed, Ethiopia

Climate change and land use dynamics are critical issues facing many regions worldwide, particularly in developing countries. This study examines the spatiotemporal changes in land use and land cover (LULC) and their impact on climate variability in the Bilate Watershed, Ethiopia, from 1994 to 2024. Utilizing multispectral satellite imagery from Landsat 5, 7, and 8, along with meteorological data from five weather stations, LULC classification was performed using the Random Forest algorithm on the Google Earth Engine platform. To analyze climatic variability and trends, the Mann-Kendall trend test, the Standardized Precipitation Index (SPI), and the Standardized Temperature Index (STI) were employed. The findings indicate a significant decline in forest cover, with an accelerated annual loss of approximately 4681.2 hectares between 2014 and 2024. Concurrently, agricultural land expanded by about 1141 hectares annually, and urban areas grew by 24.3 hectares per year in recent years. Seasonal mean rainfall variation showed significant declines in the upper catchment, with Bega (p = 0.004, Sen's slope =  - 3.819 mm), Belg (p = 0.006, Sen's slope =  - 7.972 mm), and Kiremt (p = 0.005, Sen's slope =  - 7.117 mm), while the lower catchment experienced a notable increase during the Belg season (p = 0.025, Sen's slope = 6.424 mm), highlighting uneven water availability across the watershed. Furthermore, pronounced warming trends were observed in the upper catchment (Bega: p = 0.002, Sen's slope = 0.029; Belg: p = 0.001, Sen's slope = 0.030; Kiremt: p = 0.004, Sen's slope = 0.018), with moderate warming noted in the middle catchment during the Kiremt season (p = 0.020, Sen's slope = 0.016). These LULC changes have significantly impacted climate variability, emphasizing the critical influence of human activities on regional climate dynamics. This study underscores the urgent need for sustainable land management and conservation strategies to mitigate the challenges posed by deforestation, urbanization, and agricultural expansion.

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.

Quantification of soil erosion and sediment yield using the RUSLE model in Boyo watershed, central Rift Valley Basin of Ethiopia

Changes in land use and land cover (LULC) are becoming recognized as critical to sustainability research, particularly in the context of changing landscapes. Soil erosion is one of the most important environmental challenges today, particularly in developing countries like Ethiopia. The objective of this study was evaluating the dynamics of soil loss, quantifying sediment yield, and detecting soil erosion hotspot fields in the Boyo watershed. To quantify the soil erosion risks, the Revised Universal Soil Loss Equation (RUSLE) model was used combined with remote sensing (RS) and geographic information system (GIS) technology, with land use/land cover, rainfall, soil, and management approaches as input variables. The sediment yield was estimated using the sediment delivery ratio (SDR) method. In contrast to a loss in forest land (1.7 %), water bodies (3.0 %), wetlands (1.5 %), and grassland (1.7 %), the analysis of LULC change (1991-2020) showed a yearly increase in the area of cultivated land (1.4 %), built-up land (0.8 %), and bare land (3.5 %). In 1991, 2000, and 2020, respectively, the watershed's mean annual soil loss increases by 15.5, 35.9, and 38.3 t/ha/y. Approximately 36 cm of the watershed's economically productive topsoil was lost throughout the study's twenty-nine-year period (1991-2020). According to the degree of erosion, 16 % of the watershed was deemed seriously damaged, while 70 % was deemed slightly degraded. Additionally, it is estimated for the year 2020 that 74,147.25 t/y of sediment (8.52 % of the total annual soil loss of 870,763.12 t) reach the Boyo watershed outlet. SW4 and SW5 were the two sub-watersheds with the highest erosion rates, requiring immediate conservation intervention to restore the ecology of the Boyo watershed.

Assessment of the impact of conservation measures by modeling soil loss in Minas Gerais, Brazil

Gullies are significant contributors to soil degradation in several regions of Brazil, including Minas Gerais, where erosion processes have caused soil loss. The characterization of erosion processes is crucial for the application of measures for recovering degraded areas and reducing erosion impacts. This study models soil loss with the use of InVEST software and assesses the impact of three different scenarios, namely (1) implementation of soil conservation practices and replacement of pasture areas for temporary agriculture, (2) reforestation of pasture areas, and (3) preservation of ciliary forests. Soil loss, sediment exportation, retention, and deposition for the present scenario (2019), as well as the three aforementioned hypothetical scenarios, were estimated. In the present scenario, the estimated mean annual soil loss was 2.75 t/ha year, with 1,449.54 t/year sediment exportation, 9,042.13 t/year retention, and 1,449.54 t/year deposition. The model predicted scenario 1 would result in 2.23 t/ha year mean annual soil loss, 1,300.59 t/year sediment exportation, 9,191.08 t/year retention, and 11,755.76 t/year deposition. Scenario 2 showed 1.92 t/ha year mean annual soil loss, 1,046.69 t/year sediment exportation, 9,444.98 t/year retention, and 10,229.77 t/year deposition, whereas the results for scenario 3 were 2.36 t/ha year, 616.65 t/year, 9,862.06 t/year, and 13,206.47 t/year, respectively. Reforestation and preservation of ciliary forests, along with soil conservation practices, were effective measures for reducing soil loss. Such findings are valuable for the management of areas degraded by erosion processes.

A spatio-temporal analysis of the magnitude and trend of land use/land cover changes in Gilgel Gibe Catchment, Southwest Ethiopia

Analyzing alterations in land use/land cover is crucial for water Scientists, planners, and decision-makers in watershed management. This examination enables the development of effective solutions to mitigate the adverse impacts resulting from such changes. The focus of this research was analyzing alterations in land use/land cover within the Gilgel Gibe Catchment in 1991 - 2021. LULC data of 1991-2021 were derived from multispectral Landsat images. Data were also gathered using field observations and key informant interview. Data of LULC classes (1991-2021) were generated utilizing supervised classification with maximum likelihood algorithm of ENVI 5.1 and ArcGIS 10.5. Change detection analysis and accuracy assessment were done where accuracy levels all the study periods were > 85 %, and the overall Kappa statistics of the periods were > 0.89. Built-up area and cultivated land of the catchment are increasing with increasing magnitude of change; whereas, while forest cover and grazing land of the catchment are shrinking with declining magnitudes of change, shrubland covers and water body are declining with increasing magnitude of change in the catchment. The net increase in degraded land is a reflection of the increasing degradation of natural resources in the catchment. Swift escalation of population and the subsequent raising demand for farmland and forest and shrub (e.g. fuel-wood and construction) products, decline yield, unemployment and lack of alternative income source, and open access and limited conservation of resources are the principal factors for the dramatic shrinkages of grazing, forest, water body and shrubland resources. Thus, concerned bodies should take rehabilitation measures to restore degraded lands, improve production and yield of farmland by increasing improved farm-inputs and irrigation, and create employment and alternative income sources for the youth, women and the poor so as to ensure sustainable rural livelihoods and to curb the impacts on forest, shrubland and other resources.