Abstract
This study examined how different nonhomogeneous soil characteristics affected hydrologic responses in rainfall-runoff models. The cell-based FLO-2D and lumped Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) were setup. Then, water loss parameters of both the Green-Ampt infiltration approach and curve number method were prescribed and applied in three different ways: (i) a separate value for each cell (mosaic; (ii) a representative as a most frequent occurring value for a large area (predominant); (iii) and a representative as an arithmetic mean value for a watershed (arithmetic mean). The spatial variability of nonhomogeneous catchment parameters was disregarded in lumped models, while each cell had distinct surface parameters in the distributed models. This study shows that the hydrologic response was meaningfully different in different representations. For the study site, the mosaic method was recommended for distributed models, and arithmetic mean was recommended for lumped models.
Highlights
Direct runoff is rainfall minus all abstractions, including interception by vegetation, depression storage, and infiltration into the soil
All soil-related parameters are adequately represented by a single parameter [2,3,4], but engineers continually struggle with single runoff parameters and curve numbers, such as rational equations
There is a concern of losing the heterogeneity of the hydrologic parameters used in large-scale hydrologic modeling
Summary
Direct runoff is rainfall minus all abstractions, including interception by vegetation, depression storage (i.e., the only storage that never runs off), and infiltration into the soil. Direct runoff is controlled by underlying soil texture, as well as abundance and type of vegetation. Soil texture is represented by a model parameter to describe the surface soil characteristics [1]. All soil-related parameters are adequately represented by a single parameter [2,3,4], but engineers continually struggle with single runoff parameters and curve numbers, such as rational equations. There is a concern of losing the heterogeneity of the hydrologic parameters used in large-scale hydrologic modeling. Spatial variations are sometimes hard to include. This concern is partly overcome using a distributed hydrologic model that captures some of the effect of spatial variability
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