Addressing Spatial Heterogeneity in the Discrete Generalized Nash Model for Flood Routing

River flood routing is one of the key components of hydrologic modeling and the topographic heterogeneity of rivers has great effects on it. It is beneficial to take into consideration such spatial heterogeneity, especially for hydrologic routing models. The discrete generalized Nash model (DGNM) ba...

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Autores principales:	Bao-Wei Yan, Yi-Xuan Zou, Yu Liu, Ran Mu, Hao Wang, Yi-Wei Tang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	river flood routing semidistributed model spatial heterogeneity ungauged basins Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
Acceso en línea:	https://doaj.org/article/24f681e5d8544f4fb8d163f5e65279dd
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id	oai:doaj.org-article:24f681e5d8544f4fb8d163f5e65279dd
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spelling	oai:doaj.org-article:24f681e5d8544f4fb8d163f5e65279dd2021-11-11T19:58:22ZAddressing Spatial Heterogeneity in the Discrete Generalized Nash Model for Flood Routing10.3390/w132131332073-4441https://doaj.org/article/24f681e5d8544f4fb8d163f5e65279dd2021-11-01T00:00:00Zhttps://www.mdpi.com/2073-4441/13/21/3133https://doaj.org/toc/2073-4441River flood routing is one of the key components of hydrologic modeling and the topographic heterogeneity of rivers has great effects on it. It is beneficial to take into consideration such spatial heterogeneity, especially for hydrologic routing models. The discrete generalized Nash model (DGNM) based on the Nash cascade model has the potential to address spatial heterogeneity by replacing the equal linear reservoirs into unequal ones. However, it seems impossible to obtain the solution of this complex high order differential equation directly. Alternatively, the strict mathematical derivation is combined with the deeper conceptual interpretation of the DGNM to obtain the heterogeneous DGNM (HDGNM). In this work, the HDGNM is explicitly expressed as a linear combination of the inflows and outflows, whose weight coefficients are calculated by the heterogeneous S curve. Parameters in HDGNM can be obtained in two different ways: optimization by intelligent algorithm or estimation based on physical characteristics, thus available to perform well in both gauged and ungauged basins. The HDGNM expands the application scope, and becomes more applicable, especially in river reaches where the river slopes and cross-sections change greatly. Moreover, most traditional routing models are lumped, whereas the HDGNM can be developed to be semidistributed. The middle Hanjiang River in China is selected as a case study to test the model performance. The results show that the HDGNM outperforms the DGNM in terms of model efficiency and smaller relative errors and can be used also for ungauged basins.Bao-Wei YanYi-Xuan ZouYu LiuRan MuHao WangYi-Wei TangMDPI AGarticleriver flood routingsemidistributed modelspatial heterogeneityungauged basinsHydraulic engineeringTC1-978Water supply for domestic and industrial purposesTD201-500ENWater, Vol 13, Iss 3133, p 3133 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	river flood routing semidistributed model spatial heterogeneity ungauged basins Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500
spellingShingle	river flood routing semidistributed model spatial heterogeneity ungauged basins Hydraulic engineering TC1-978 Water supply for domestic and industrial purposes TD201-500 Bao-Wei Yan Yi-Xuan Zou Yu Liu Ran Mu Hao Wang Yi-Wei Tang Addressing Spatial Heterogeneity in the Discrete Generalized Nash Model for Flood Routing
description	River flood routing is one of the key components of hydrologic modeling and the topographic heterogeneity of rivers has great effects on it. It is beneficial to take into consideration such spatial heterogeneity, especially for hydrologic routing models. The discrete generalized Nash model (DGNM) based on the Nash cascade model has the potential to address spatial heterogeneity by replacing the equal linear reservoirs into unequal ones. However, it seems impossible to obtain the solution of this complex high order differential equation directly. Alternatively, the strict mathematical derivation is combined with the deeper conceptual interpretation of the DGNM to obtain the heterogeneous DGNM (HDGNM). In this work, the HDGNM is explicitly expressed as a linear combination of the inflows and outflows, whose weight coefficients are calculated by the heterogeneous S curve. Parameters in HDGNM can be obtained in two different ways: optimization by intelligent algorithm or estimation based on physical characteristics, thus available to perform well in both gauged and ungauged basins. The HDGNM expands the application scope, and becomes more applicable, especially in river reaches where the river slopes and cross-sections change greatly. Moreover, most traditional routing models are lumped, whereas the HDGNM can be developed to be semidistributed. The middle Hanjiang River in China is selected as a case study to test the model performance. The results show that the HDGNM outperforms the DGNM in terms of model efficiency and smaller relative errors and can be used also for ungauged basins.
format	article
author	Bao-Wei Yan Yi-Xuan Zou Yu Liu Ran Mu Hao Wang Yi-Wei Tang
author_facet	Bao-Wei Yan Yi-Xuan Zou Yu Liu Ran Mu Hao Wang Yi-Wei Tang
author_sort	Bao-Wei Yan
title	Addressing Spatial Heterogeneity in the Discrete Generalized Nash Model for Flood Routing
title_short	Addressing Spatial Heterogeneity in the Discrete Generalized Nash Model for Flood Routing
title_full	Addressing Spatial Heterogeneity in the Discrete Generalized Nash Model for Flood Routing
title_fullStr	Addressing Spatial Heterogeneity in the Discrete Generalized Nash Model for Flood Routing
title_full_unstemmed	Addressing Spatial Heterogeneity in the Discrete Generalized Nash Model for Flood Routing
title_sort	addressing spatial heterogeneity in the discrete generalized nash model for flood routing
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/24f681e5d8544f4fb8d163f5e65279dd
work_keys_str_mv	AT baoweiyan addressingspatialheterogeneityinthediscretegeneralizednashmodelforfloodrouting AT yixuanzou addressingspatialheterogeneityinthediscretegeneralizednashmodelforfloodrouting AT yuliu addressingspatialheterogeneityinthediscretegeneralizednashmodelforfloodrouting AT ranmu addressingspatialheterogeneityinthediscretegeneralizednashmodelforfloodrouting AT haowang addressingspatialheterogeneityinthediscretegeneralizednashmodelforfloodrouting AT yiweitang addressingspatialheterogeneityinthediscretegeneralizednashmodelforfloodrouting
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Addressing Spatial Heterogeneity in the Discrete Generalized Nash Model for Flood Routing

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