细沟
WEPP公司
环境科学
含水量
土壤科学
岩土工程
土壤水分
地质学
地理
水土保持
农业
考古
作者
Fikret Arı,Selen Deviren Saygın,Çağla Temiz,Şefika Arslan,Mehmet Altay Ünal,Günay Erpul,Dennis C. Flanagan
标识
DOI:10.1016/j.iswcr.2024.10.001
摘要
ABSTRACT Rill erosion, a significant issue in agricultural regions, is intricately linked to initial soil moisture conditions, affecting the development of concentrated flow erosion processes. However, understanding its dynamics amidst varying soil moisture conditions remain challenging. This study aimed to assess the impact of different soil moisture levels on rill erodibility parameters in the Water Erosion Prediction Project (WEPP) model and to evaluate soil cohesion across a spectrum of soils. Through laboratory experiments employing a small V-shaped rill channel, we investigated rill erodibility ( K r ) and critical hydraulic shear stress ( τ cr ), under three soil moisture scenarios: initially dry, saturated, and drainage, with incremental surface inflow rates. Additionally, we examined the efficiency of soil cohesion obtained from an Automated Soil Cohesion Measurement Apparatus in predicting K r and τ cr across various soil textures. Our analysis encompassed twenty soils representing nine texture classes, revealing significant correlations between basic soil properties, cohesion parameters, and WEPP model rill erodibility. Notably, initial soil moisture conditions exerted substantial influence on erodibility potentials. Soils with higher silt contents demonstrated better fits in terms of Nash-Sutcliffe model efficiency, particularly under initially dry and saturated conditions. However, predictions for initially drained soils yielded poor fits, emphasizing the intricate interplay between soil properties and hydrological conditions. In conclusion, our findings emphasize the critical role of topsoil water dynamics in rill erodibility. We propose that soil cohesion serves as a valuable predictor, complementing friction forces within the soil and enhancing simulations of rill erodibility under shallow flow conditions in rills, particularly in next-generation process-based modeling approaches.
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