Effectiveness of physical soil and water conservation measures under simulated and observed dataset in Ethiopia: Meta-analysis

To combat land degradation through conserving soil and water resources, Ethiopia has undergone vigorous implementation of soil and water conservation (SWC) measures, predominantly physical structures. To evaluate the effectiveness of these implemented structures, various researches have been conducted through using both measured and simulated approaches. This study was initiated to analyze the reliability of SWAT-based simulated studies results on the effectiveness of SWC measures toward erosion reduction potential against the measured dataset using unpaired t-test statistical analysis. In this study, 123 published papers were downloaded, of which 70 were found to be more related to the objective of the review. After applying four refining criteria, only 43 were found more compatible with the study objective and used for data analysis. Studies conducted by different scholars show up to 98% and 93.50% soil loss reduction effectiveness by SWC measures in measured and simulated approaches, respectively. The simulated SWC measure efficiency output was also evaluated with respect to the ground-measured data of the same structure within the same agroecology class. Finally, the unpaired t-test results indicated that the grass strip in the mid-highland agroecology showed a significant difference from the measured one at a 95% significance level. However, none of the other measures showed significant differences between the measured and simulated datasets. Hence, the SWAT model can effectively simulate the effectiveness of physical SWC measures on soil loss reduction if it is well-calibrated and validated with sediment yield data. Refining model parameters that can be sufficiently captured and represent biological measures (grass strip), incorporating additional field data for calibration and validation coupled with exploring alternative modeling approaches that efficiently simulate biological SWC was set as a recommendation to obtain an effective biological measure simulation.