Efficiency of soil and water conservation practices in different agro-ecological environments in the Upper Blue Nile Basin of Ethiopia

In developing countries such as Ethiopia, research to develop and promote soil and water conservation practices rarely addressed regional diversity. Using a water-balance approach in this study, we used runoff plots from three sites, each representing a different agro-ecological environment, e.g., high, mid and low in both elevation and rainfall, in the Upper Blue Nile Basin of Ethiopia to examine the runoff response and runoff conservation efficiency of a range of different soil and water conservation measures and their impacts on soil moisture. The plots at each site represented common land use types（cultivated vs. non-agricultural land use types） and slopes（gentle and steep）. Seasonal runoff from control plots in the highlands ranged 214–560 versus 253–475 mm at midlands and 119–200 mm at lowlands. The three soil and water conservation techniques applied in cultivated land increased runoff conservation efficiency by 32% to 51%, depending on the site. At the moist subtropical site in a highland region, soil and water conservation increased soil moisture enough to potentially cause waterlogging, which was absent at the lowrainfall sites. Soil bunds combined with Vetiveria zizanioides grass in cultivated land and short trenches in grassland conserved the most runoff（51% and 55%, respectively）. Runoff responses showed high spatial variation within and between land use types, causing high variation in soil and water conservation efficiency. Our results highlight the need to understand the role of the agro-ecological environment in the success of soil and water conservation measures to control runoff and hydrological dynamics. This understanding will support policy development to promote the adoption of suitable techniques that can be tested at other locations with similar soil, climatic, and topographic conditions.

Global analysis of cover management and support practice factors that control soil erosion and conservation

Cover management and support practices largely control the magnitude and variability of soil erosion.Although soil erosion models account for their importance(particularly by C-and P-factors in the Revised Universal Soil Loss Equation),obtaining spatially explicit quantitative field data on these factors remains challenging.Hence,also our insight into the effects of soil conservation measures at larger spatial scales remains limited.We analyzed the variation in C-and P-factors caused by human activities and climatic variables by reviewing 255 published articles reporting measured or calculated C-and P-factor values.We found a wide variation in both factor values across climatic zones,land use or cover types,and support practices.The average C-factor values decreased from arid(0.26)to humid(0.15)climates,whereas the average P-factor values increased(from 0.33 to 0.47,respectively).Thus,support practices reduce soil loss more effectively in drylands and drought-prone areas.The global average C-factor varies by one order of magnitude from cropland(0.34)to forest(0.03).Among the major crops,the average C-factor was highest for maize(0.42)followed by potato(0.40),among the major orchard crops,it was highest for olive(0.31),followed by vineyards(0.26).The P-factor ranged from 0.62 for contouring in cropland plots to 0.19 for trenches in uncultivated land.The C-factor results indicate that cultivated lands requiring intensive site preparation and weeding are most vulnerable to soil loss by sheet and rill erosion.The low P-factor for trenches,reduced tillage cultivation,and terraces suggests that significantly decreased soil loss is possible by implementing more efficient management practices.These results improve our understanding of the variation in C-and P-factors and support large-scale integrated catchment management interventions by applying soil erosion models where it is difficult to empirically determine the impact of particular land use or cover types and support practices:the datasets compiled in this study can support further modeling and land management attempts in different countries and geographic regions.