Application of an improved distributed Xinanjiang hydrological model for flood prediction in a karst catchment in South‐Western China
Abstract Hydrological processes in karst aquifer systems are controlled by highly permeable media, so studying flood processes in karst‐dominated regions is very important; however, it is still a challenge to model the hydrological dynamics in such strongly heterogeneous conditions. This study propo...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-12-01
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| Series: | Journal of Flood Risk Management |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/jfr3.12649 |
| _version_ | 1818453633079967744 |
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| author | Wenzhe Yang Lihua Chen Fangfang Deng Shuting Lv |
| author_facet | Wenzhe Yang Lihua Chen Fangfang Deng Shuting Lv |
| author_sort | Wenzhe Yang |
| collection | DOAJ |
| description | Abstract Hydrological processes in karst aquifer systems are controlled by highly permeable media, so studying flood processes in karst‐dominated regions is very important; however, it is still a challenge to model the hydrological dynamics in such strongly heterogeneous conditions. This study proposed a distributed Xinanjiang karst hydrological model (DXAJKHM) for simulating the flood processes in karst catchments, which was based on topographical information extracted from a digital elevation model. Considering the dual‐porosity in karst aquifer systems, the DXAJKHM was coupled with a traditional Xinanjiang conceptual hydrological model and utilized two karst reservoirs that simulated both the rapid underground run‐off and the slow underground run‐off in each grid cell. The uncertainty in the model parameters is estimated by the generalized likelihood uncertainty estimation method, and the parameters are determined by the shuffled complex evolution approach optimization algorithm. The simulation results demonstrated that the proposed DXAJKHM satisfactorily simulated the flood processes, and the model has better simulation effects for floods with larger flood peaks. In order to analyse the flood recession error, one run‐off signature index was employed to improve the model runs. This study thus provides a new approach to simulating and predicting floods in karst areas. |
| first_indexed | 2024-12-14T21:42:05Z |
| format | Article |
| id | doaj.art-6c2670ee43ff484d81719aa2505dcb13 |
| institution | Directory Open Access Journal |
| issn | 1753-318X |
| language | English |
| last_indexed | 2024-12-14T21:42:05Z |
| publishDate | 2020-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Flood Risk Management |
| spelling | doaj.art-6c2670ee43ff484d81719aa2505dcb132022-12-21T22:46:27ZengWileyJournal of Flood Risk Management1753-318X2020-12-01134n/an/a10.1111/jfr3.12649Application of an improved distributed Xinanjiang hydrological model for flood prediction in a karst catchment in South‐Western ChinaWenzhe Yang0Lihua Chen1Fangfang Deng2Shuting Lv3College of Civil Engineering and Architecture Guangxi University ChinaCollege of Civil Engineering and Architecture Guangxi University ChinaCollege of Civil Engineering and Architecture Guangxi University ChinaCollege of Civil Engineering and Architecture Guangxi University ChinaAbstract Hydrological processes in karst aquifer systems are controlled by highly permeable media, so studying flood processes in karst‐dominated regions is very important; however, it is still a challenge to model the hydrological dynamics in such strongly heterogeneous conditions. This study proposed a distributed Xinanjiang karst hydrological model (DXAJKHM) for simulating the flood processes in karst catchments, which was based on topographical information extracted from a digital elevation model. Considering the dual‐porosity in karst aquifer systems, the DXAJKHM was coupled with a traditional Xinanjiang conceptual hydrological model and utilized two karst reservoirs that simulated both the rapid underground run‐off and the slow underground run‐off in each grid cell. The uncertainty in the model parameters is estimated by the generalized likelihood uncertainty estimation method, and the parameters are determined by the shuffled complex evolution approach optimization algorithm. The simulation results demonstrated that the proposed DXAJKHM satisfactorily simulated the flood processes, and the model has better simulation effects for floods with larger flood peaks. In order to analyse the flood recession error, one run‐off signature index was employed to improve the model runs. This study thus provides a new approach to simulating and predicting floods in karst areas.https://doi.org/10.1111/jfr3.12649catchmentsforecasting and warninghydrological modellingmodelling |
| spellingShingle | Wenzhe Yang Lihua Chen Fangfang Deng Shuting Lv Application of an improved distributed Xinanjiang hydrological model for flood prediction in a karst catchment in South‐Western China Journal of Flood Risk Management catchments forecasting and warning hydrological modelling modelling |
| title | Application of an improved distributed Xinanjiang hydrological model for flood prediction in a karst catchment in South‐Western China |
| title_full | Application of an improved distributed Xinanjiang hydrological model for flood prediction in a karst catchment in South‐Western China |
| title_fullStr | Application of an improved distributed Xinanjiang hydrological model for flood prediction in a karst catchment in South‐Western China |
| title_full_unstemmed | Application of an improved distributed Xinanjiang hydrological model for flood prediction in a karst catchment in South‐Western China |
| title_short | Application of an improved distributed Xinanjiang hydrological model for flood prediction in a karst catchment in South‐Western China |
| title_sort | application of an improved distributed xinanjiang hydrological model for flood prediction in a karst catchment in south western china |
| topic | catchments forecasting and warning hydrological modelling modelling |
| url | https://doi.org/10.1111/jfr3.12649 |
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