4.7 Article

Rainfall/runoff simulation with 2D full shallow water equations: Sensitivity analysis and calibration of infiltration parameters

期刊

JOURNAL OF HYDROLOGY
卷 536, 期 -, 页码 496-513

出版社

ELSEVIER
DOI: 10.1016/j.jhydrol.2016.03.021

关键词

Finite volumes; Shallow-water equations; Hydrologic modeling; Infiltration models; Rain-runoff generation

资金

  1. Aragon Government through the Fondo Social Europeo

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One of the most difficult issues in the development of hydrologic models is to find a rigorous source of data and specific parameters to a given problem, on a given location that enable reliable calibration. In this paper, a distributed and physically based model (2D Shallow Water Equations) is used for surface flow and runoff calculations in combination with two infiltration laws (Horton and Green-Ampt) for estimating infiltration in a watershed. This technique offers the capability of assigning a local and time dependent infiltration rate to each computational cell depending on the available surface water, soil type or vegetation. We investigate how the calibration of parameters is affected by transient distributed Shallow Water model and the complexity of the problem. In the first part of this work, we calibrate the infiltration parameters for both Horton and Green-Ampt models under flat ponded soil conditions. Then, by means of synthetic test cases, we perform a space-distributed sensitivity analysis in order to show that this calibration can be significantly affected by the introduction of topography or rainfall. In the second part, parameter calibration for a real catchment is addressed by comparing the numerical simulations with two different sets of experimental data, corresponding to very different events in terms of the rainfall volume. We show that the initial conditions of the catchment and the rainfall pattern have a special relevance in the quality of the adjustment. Hence, it is shown that the topography of the catchment and the storm characteristics affect the calibration of infiltration parameters. (C) 2016 Elsevier B.V. All rights reserved.

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