机构地区：[1]Department of Civil Engineering, Faculty of Engineering, Fayoum University, Fayoum, Egypt
出 处：《Journal of Geoscience and Environment Protection》2022年第1期109-122,共14页地球科学和环境保护期刊（英文）
摘 要：One of the most commonly used equations to estimate soil erosion is the revised universal soil loss equation (RUSLE). Based on the early approach developed by the Soil Conservation Service of USA, the rainfall erosivity factor (R-factor) in the RUSLE equation requires sub-daily rainfall data, which is usually not available. Other empirical equations estimate R-factor based on available rainfall data like annual and monthly rainfall data. In arid regions such as the Arabian Peninsula, several studies estimated the R-factor based on these empirical equations without calibration. We propose in this paper to assess the applicability of some of these empirical equations against R-factor values calculated using as a reference the RUSLE approach. For this data, data from 104 stations with sub-daily rainfall was collected. The reference R-factor w<span><span><span style="font-family:;" "="">as</span></span></span><span><span><span style="font-family:;" "=""> calculated for the 104 stations. The results of seven empirical equations were tested against the reference R-factor. Most of the tested equations significantly underestimated the R-factor. Furthermore, the obtained RMSE and MAE values were almost as high as the average R-factor, with MAPE exceeding 100%. Therefore, it is recommended not to apply these equations in arid regions. A recalibration of the form of equation that gave the best results, gave a</span></span></span><span><span><span style="font-family:;" "="">n</span></span></span><span><span><span style="font-family:;" "=""> RMSE of 280 (Mj<span style="color:#4F4F4F;font-family:-apple-system, "font-size:16px;white-space:normal;background-color:#F7F7F7;">·</span>mm/(ha<span style="color:#4F4F4F;font-family:-apple-system, "font-size:16px;white-space:normal;background-color:#F7F7F7;">·</span>hr)) and the MAPE dropped to 47.6%.</span></span></span>One of the most commonly used equations to estimate soil erosion is the revised universal soil loss equation (RUSLE). Based on the early approach developed by the Soil Conservation Service of USA, the rainfall erosivity factor (R-factor) in the RUSLE equation requires sub-daily rainfall data, which is usually not available. Other empirical equations estimate R-factor based on available rainfall data like annual and monthly rainfall data. In arid regions such as the Arabian Peninsula, several studies estimated the R-factor based on these empirical equations without calibration. We propose in this paper to assess the applicability of some of these empirical equations against R-factor values calculated using as a reference the RUSLE approach. For this data, data from 104 stations with sub-daily rainfall was collected. The reference R-factor w<span><span><span style="font-family:;" "="">as</span></span></span><span><span><span style="font-family:;" "=""> calculated for the 104 stations. The results of seven empirical equations were tested against the reference R-factor. Most of the tested equations significantly underestimated the R-factor. Furthermore, the obtained RMSE and MAE values were almost as high as the average R-factor, with MAPE exceeding 100%. Therefore, it is recommended not to apply these equations in arid regions. A recalibration of the form of equation that gave the best results, gave a</span></span></span><span><span><span style="font-family:;" "="">n</span></span></span><span><span><span style="font-family:;" "=""> RMSE of 280 (Mj<span style="color:#4F4F4F;font-family:-apple-system, "font-size:16px;white-space:normal;background-color:#F7F7F7;">·</span>mm/(ha<span style="color:#4F4F4F;font-family:-apple-system, "font-size:16px;white-space:normal;background-color:#F7F7F7;">·</span>hr)) and the MAPE dropped to 47.6%.</span></span></span>
关 键 词：Soil Erosion RUSLE R-Factor Arid Region Arabian Peninsula
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