RESUMEN
The Soil & Water Assessment Tool (SWAT) has been calibrated over a 33-year period to evaluate the Gojeb watershed's hydrological processes, sediment yield with downstream loading to the Gibe III dam, and erosion hotspot locations. Best management practices (BMPs) were run through the model to simulate the effects of watershed intervention scenarios on sediment yield and runoff. Simulation results of BMP intervention were compared with the reference and worst-case scenarios. The simulation of sediment production indicates a clear growing trend. Temporally, the maximum amount of sediment transported out of the watershed is experiential from June to September, and the minimum is in February. A plainly defined similar orientation is observed between precipitation, surface runoff, and sediment load in the landscape. Spatially, the maximum sediment transported out of the watershed is from agricultural landscape units with a slope of over 50%, annual precipitation above 1592 mm, and surface runoff over 151 mm. This signifies that the watershed is under serious threat from erosion due to vegetation loss, steep slope farming, and high surface runoff. Gibe III is a 243-m high roller compacted gravity dam built on the Omo-Gibe River basin in Ethiopia for hydroelectric power and downstream flood control. It is one of Africa's tallest dams, with an annual electric output of 1870 MW that began operation in 2016. Thus, Gibe III could see a loss of storage capacity due to higher-than-expected sedimentation resulting from worsening environmental degradation, which implies that the beneficial uses that depend on this dam - electricity production, regulated irrigation water supply, and flood control - will decline with significant economic losses. Despite that, selected sustainable land management interventions and the application of BMPs to critical erosion-prone hotspot areas can support the overall reduction in total sediment yield and surface runoff.
Asunto(s)
Suelo , Agua , Etiopía , Agricultura/métodos , Abastecimiento de AguaRESUMEN
Earlier studies on land change (LC) have focused on size and magnitude, gains and losses, or land transfers between categories. Therefore, these studies have failed to simultaneously show the complete LC processes. This paper examines LCs in the Legedadie-Dire catchments in Oromia State, Ethiopia, using land-category maps with intensity analysis (IA) at three points in time. We comprehensively analyze LC to jointly encompass the rate, intensity, transition, and process. Thirty-meter US Geological Survey (USGS) Landsat imagery from 1986, 2000, and 2015 (< 10% cloud) is processed using TerrSet-LCM and ArcGIS. Six categories are identified using a maximum likelihood classification technique: settlement, cultivation, forest, water, grassland, and bare land. Then, classified maps are superimposed on the images to statistically examine changes with an IA. Considerable changes are observed among categories, except for water, between 1986-2000 and 2000-2015. Overall land change occurred quickly at first and then slowly in the second time interval. The total land area that exhibited change (1st ≈ 54% and 2nd ≈ 51%) exceeded the total area of persistence (1st ≈ 46% and 2nd ≈ 49%) across the landscape. Cultivation and human settlements were the most intensively increased categories, at the expense of grassland and bare ground. Hence, when grassland was lost, it tended to be displaced by cultivation more than other categories, which was also true with bare land. Annual intensity gains were active for forest but minimal for cultivation, implying that the gains of forest were associated with in situ reforestation practices and that the gains in cultivation were caused by its relatively large initial area under a uniform intensity concept. This study demonstrates that IA is valuable for investigating LC across time intervals and can help distinguish dormant vs. active and targeted vs. avoided land categories.