date: 2021-05-11T10:32:09Z
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pdf:docinfo:title: Spatio-Temporal Hydrological Model Structure and Parametrization Analysis
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Keywords: conceptual-distributed model; raster-based; model structure analysis; Muskingum routing; OAT sensitivity analysis; HBV
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subject: Many grid-based spatial hydrological models suffer from the complexity of setting up a coherent spatial structure to calibrate such a complex, highly parameterized system. There are essential aspects of model-building to be taken into account: spatial resolution, the routing equation limitations, and calibration of spatial parameters, and their influence on modeling results, all are decisions that are often made without adequate analysis. In this research, an experimental analysis of grid discretization level, an analysis of processes integration, and the routing concepts are analyzed. The HBV-96 model is set up for each cell, and later on, cells are integrated into an interlinked modeling system (Hapi). The Jiboa River Basin in El Salvador is used as a case study. The first concept tested is the model structure temporal responses, which are highly linked to the runoff dynamics. By changing the runoff generation model description, we explore the responses to events. Two routing models are considered: Muskingum, which routes the runoff from each cell following the river network, and Maxbas, which routes the runoff directly to the outlet. The second concept is the spatial representation, where the model is built and tested for different spatial resolutions (500 m, 1 km, 2 km, and 4 km). The results show that the spatial sensitivity of the resolution is highly linked to the routing method, and it was found that routing sensitivity influenced the model performance more than the spatial discretization, and allowing for coarser discretization makes the model simpler and computationally faster. Slight performance improvement is gained by using different parameters? values for each cell. It was found that the 2 km cell size corresponds to the least model error values. The proposed hydrological modeling codes have been published as open-source.
dc:creator: Mostafa Farrag, Gerald Corzo Perez and Dimitri Solomatine
dcterms:created: 2021-05-11T10:17:26Z
Last-Modified: 2021-05-11T10:32:09Z
dcterms:modified: 2021-05-11T10:32:09Z
dc:format: application/pdf; version=1.7
title: Spatio-Temporal Hydrological Model Structure and Parametrization Analysis
Last-Save-Date: 2021-05-11T10:32:09Z
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pdf:docinfo:keywords: conceptual-distributed model; raster-based; model structure analysis; Muskingum routing; OAT sensitivity analysis; HBV
pdf:docinfo:modified: 2021-05-11T10:32:09Z
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dc:title: Spatio-Temporal Hydrological Model Structure and Parametrization Analysis
modified: 2021-05-11T10:32:09Z
cp:subject: Many grid-based spatial hydrological models suffer from the complexity of setting up a coherent spatial structure to calibrate such a complex, highly parameterized system. There are essential aspects of model-building to be taken into account: spatial resolution, the routing equation limitations, and calibration of spatial parameters, and their influence on modeling results, all are decisions that are often made without adequate analysis. In this research, an experimental analysis of grid discretization level, an analysis of processes integration, and the routing concepts are analyzed. The HBV-96 model is set up for each cell, and later on, cells are integrated into an interlinked modeling system (Hapi). The Jiboa River Basin in El Salvador is used as a case study. The first concept tested is the model structure temporal responses, which are highly linked to the runoff dynamics. By changing the runoff generation model description, we explore the responses to events. Two routing models are considered: Muskingum, which routes the runoff from each cell following the river network, and Maxbas, which routes the runoff directly to the outlet. The second concept is the spatial representation, where the model is built and tested for different spatial resolutions (500 m, 1 km, 2 km, and 4 km). The results show that the spatial sensitivity of the resolution is highly linked to the routing method, and it was found that routing sensitivity influenced the model performance more than the spatial discretization, and allowing for coarser discretization makes the model simpler and computationally faster. Slight performance improvement is gained by using different parameters? values for each cell. It was found that the 2 km cell size corresponds to the least model error values. The proposed hydrological modeling codes have been published as open-source.
pdf:docinfo:subject: Many grid-based spatial hydrological models suffer from the complexity of setting up a coherent spatial structure to calibrate such a complex, highly parameterized system. There are essential aspects of model-building to be taken into account: spatial resolution, the routing equation limitations, and calibration of spatial parameters, and their influence on modeling results, all are decisions that are often made without adequate analysis. In this research, an experimental analysis of grid discretization level, an analysis of processes integration, and the routing concepts are analyzed. The HBV-96 model is set up for each cell, and later on, cells are integrated into an interlinked modeling system (Hapi). The Jiboa River Basin in El Salvador is used as a case study. The first concept tested is the model structure temporal responses, which are highly linked to the runoff dynamics. By changing the runoff generation model description, we explore the responses to events. Two routing models are considered: Muskingum, which routes the runoff from each cell following the river network, and Maxbas, which routes the runoff directly to the outlet. The second concept is the spatial representation, where the model is built and tested for different spatial resolutions (500 m, 1 km, 2 km, and 4 km). The results show that the spatial sensitivity of the resolution is highly linked to the routing method, and it was found that routing sensitivity influenced the model performance more than the spatial discretization, and allowing for coarser discretization makes the model simpler and computationally faster. Slight performance improvement is gained by using different parameters? values for each cell. It was found that the 2 km cell size corresponds to the least model error values. The proposed hydrological modeling codes have been published as open-source.
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pdf:docinfo:creator: Mostafa Farrag, Gerald Corzo Perez and Dimitri Solomatine
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creator: Mostafa Farrag, Gerald Corzo Perez and Dimitri Solomatine
meta:author: Mostafa Farrag, Gerald Corzo Perez and Dimitri Solomatine
dc:subject: conceptual-distributed model; raster-based; model structure analysis; Muskingum routing; OAT sensitivity analysis; HBV
meta:creation-date: 2021-05-11T10:17:26Z
created: Tue May 11 12:17:26 CEST 2021
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meta:keyword: conceptual-distributed model; raster-based; model structure analysis; Muskingum routing; OAT sensitivity analysis; HBV
Author: Mostafa Farrag, Gerald Corzo Perez and Dimitri Solomatine
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