1. A simple geomorphic-based analytical model for predicting the spatial distribution of soil thickness in headwater hillslopes and catchments
- Author
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Xi Chen, Hu Liu, Huiqing Song, Jintao Liu, and Henry Lin
- Subjects
geography ,geography.geographical_feature_category ,010504 meteorology & atmospheric sciences ,Mean squared error ,Hydrological modelling ,0207 environmental engineering ,Drainage basin ,Soil science ,Terrain ,02 engineering and technology ,15. Life on land ,Spatial distribution ,01 natural sciences ,6. Clean water ,Field (geography) ,Critical Zone Observatories ,Catchment hydrology ,020701 environmental engineering ,Geomorphology ,Geology ,0105 earth and related environmental sciences ,Water Science and Technology - Abstract
[1] Soil thickness acts as an important control for headwater hydrologic processes. Yet, its spatial distribution remains one of the least understood in catchment hydrology. Analytic methods are desirable to provide a simple way for predicting soil thickness distribution over a hillslope or a catchment. In this paper, a simple geomorphic-based analytical model is derived from the dynamic equations of soil thickness evolution in areas with no tectonic uplift or lowering since the recent geological past. The model employs terrain attributes (slope gradient, curvature, and upstream contributing area) as inputs on grid-based DEMs for predicting soil thickness evolution over time. The analytic model is validated first on nine abstract hillslopes through comparing 10 kyr simulation results between our proposed model and the numerical solution. The model is then applied to predict soil thickness evolution over 13 kyr in the 7.9 ha Shale Hills catchment (one of the Critical Zone Observatories in the U.S. located in central Pennsylvania). Field observed and model predicted values of soil thickness are in good agreement (with a root mean squared error of 0.39 m, R2 = 0.74, and absolute errors
- Published
- 2013
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