Development and testing of a simple physically-based distributed rainfall-runoff model for storm runoff simulation in humid forested basins

摘要

A distributed rainfall-runoff model was developed to predict storm runoff from humid forested catchments. The model. is physically based and takes into account the saturation excess overland flow mechanism and preferential subsurface flow. The watershed is discretized into a number of square grids, which then are classified into overland flow and channel flow elements based on water flow properties. On the overland elements, Infiltration, overland flow and lateral subsurface flow are estimated, while on channel flow elements river flow routing is performed. Lateral subsurface flow is calculated using Darcy's law and the continuity equation, whereas overland flow and channel flow are modeled using a one dimensional kinematic wave approximation to the St. Venant equations. The model governing equations are solved by an implicit finite difference scheme. While using process-based equations and physically meaningful parameters, the model. still maintains a relatively simple structure. Most of the model. parameters can be derived from digital elevation models (DEMs), digital soil and land use data, and the remainder of the parameters that are comparatively sensitive can be determined by model calibration. The model is tested using nine storm events in the Jiaokou watershed, a sub-basin of Yongjiang River in Zhejiang Province, China. Of these storms, one storm is used for calibrating the model parameters and the remaining eight storms are used to verify the model. When judged by the model, efficiency coefficient (R-2), volume conversation index (VCI), absolute error of the time to peak (Delta T), and relative error of the peak flow rate (delta P-max), acceptable results are achieved. Sensitivity analysis shows that the model is sensitive to saturated hydraulic conductivity (Ks), Manning's roughness coefficients (n) and the initial soil moisture content. (c) 2007 Elsevier B.V. All rights reserved.