Journal
SOIL AND WATER RESEARCH
Volume 7, Issue 2, Pages 52-63Publisher
CZECH ACADEMY AGRICULTURAL SCIENCES
DOI: 10.17221/25/2011-SWR
Keywords
conditional simulation; Faucon; hydrograph; kriging; LISEM; soil depth
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Funding
- Faculty of Geo-Information Science and Earth Observation of University of Twente
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Soil depth is an important parameter for models of surface runoff. Commonly used models require not only accurate estimates of the parameter but also its realistic spatial distribution. The objective of this study was to use terrain and environmental variables to map soil depth, comparing different spatial prediction methods by their effect on simulated runoff hydrographs. The study area is called Faucon, and it is located in the southeast of the French Alps. An additive linear model of land cover class and overland flow distance to channel network predicted the soil depth in the best way. Regression kriging (RK) used in this model gave better accuracy than ordinary kriging (OK). The soil depth maps, including conditional simulations, were exported to the hydrologic model of LISEM, where three synthetic rainfall scenarios were used. The hydrographs produced by RK and OK were significantly different only at rainfalls of low intensity or short duration.
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