地表径流
分水岭
裂谷
水文学(农业)
构造盆地
腐蚀
土地覆盖
强度(物理)
环境科学
土地利用
封面(代数)
地理
地质学
自然地理学
地貌学
生态学
物理
古生物学
量子力学
生物
工程类
机械工程
岩土工程
计算机科学
机器学习
作者
Assefa Gedle,T.H.M. Rientjes,Alemseged Tamiru Haile,Wolde Mekuria,Paul D. Hallett,Jo Smith
标识
DOI:10.1016/j.ejrh.2025.102289
摘要
Study Region: Shilansha is a watershed located in the Upper Bilate River of the Rift Valley Lake Basin in southern Ethiopia. The region experiences extreme soil water-erosion among the greatest rates globally at 498 tons ha−1 yr−1 leading to large quantities of sediment accumulation in Lake Abaya. Study Focus: Surface runoff, soil water-erosion, and sediment loads in the region vary with agricultural seasons and rainfall intensities but are often poorly quantified in modeling studies. This study assessed these effects using the event-based physically based distributed open-source Limburg Soil Water Erosion Model (OpenLISEM), incorporating local field data and multi-sensor satellite data processed with machine learning techniques. New Hydrological Insights: During the fallow season, simulated surface runoff and total soil loss were 9.7 % and 47 % larger than the growing season and 0.9 % and 42 % larger than the harvest season, respectively. Compared to moderate intensity, an 87 % increase in high rainfall intensity increased surface runoff by 159 % and soil loss by 295 %, while a 45 % decrease in low rainfall intensity reduced surface runoff by 49 % and soil loss by 85 %. High rainfall intensity had a greater impact when combined with fallow season land cover, while effects were smallest when low rainfall intensity combined with growing season land cover. A calibrated model parameter set for a particular season resulted in deteriorated model performance when applied to other seasons. These findings offer insights on the importance of considering seasonal changes in land cover and rainfall intensity when developing soil and water conservation strategies.
科研通智能强力驱动
Strongly Powered by AbleSci AI