Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling
Each year, extreme floods, which appear to be occurring more frequently in recent years (owing to climate change), lead to enormous economic damage and human suffering around the world. It is therefore imperative to be able to accurately predict both the occurrence time and magnitude of peak dischar...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-03-01
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| Series: | Water |
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| Online Access: | http://www.mdpi.com/2073-4441/9/3/186 |
| _version_ | 1811262689555513344 |
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| author | Kwok-wing Chau |
| author_facet | Kwok-wing Chau |
| author_sort | Kwok-wing Chau |
| collection | DOAJ |
| description | Each year, extreme floods, which appear to be occurring more frequently in recent years (owing to climate change), lead to enormous economic damage and human suffering around the world. It is therefore imperative to be able to accurately predict both the occurrence time and magnitude of peak discharge in advance of an impending flood event. The use of meta-heuristic techniques in rainfall-runoff modeling is a growing field of endeavor in water resources management. These techniques can be used to calibrate data-driven rainfall-runoff models to improve forecasting accuracies. This Special Issue of the journal Water is designed to fill the analytical void by including papers concerning advances in the contemporary use of meta-heuristic techniques in rainfall-runoff modeling. The information and analyses can contribute to the development and implementation of effective hydrological predictions, and thus, of appropriate precautionary measures. |
| first_indexed | 2024-04-12T19:31:10Z |
| format | Article |
| id | doaj.art-da3edf3a0bc94b709478daafea8bab4a |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-04-12T19:31:10Z |
| publishDate | 2017-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-da3edf3a0bc94b709478daafea8bab4a2022-12-22T03:19:20ZengMDPI AGWater2073-44412017-03-019318610.3390/w9030186w9030186Use of Meta-Heuristic Techniques in Rainfall-Runoff ModellingKwok-wing Chau0Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hunghom, Kowloon, Hong KongEach year, extreme floods, which appear to be occurring more frequently in recent years (owing to climate change), lead to enormous economic damage and human suffering around the world. It is therefore imperative to be able to accurately predict both the occurrence time and magnitude of peak discharge in advance of an impending flood event. The use of meta-heuristic techniques in rainfall-runoff modeling is a growing field of endeavor in water resources management. These techniques can be used to calibrate data-driven rainfall-runoff models to improve forecasting accuracies. This Special Issue of the journal Water is designed to fill the analytical void by including papers concerning advances in the contemporary use of meta-heuristic techniques in rainfall-runoff modeling. The information and analyses can contribute to the development and implementation of effective hydrological predictions, and thus, of appropriate precautionary measures.http://www.mdpi.com/2073-4441/9/3/186rainfall-runoffmeta-heuristicdata-drivenmodelingfloodprediction |
| spellingShingle | Kwok-wing Chau Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling Water rainfall-runoff meta-heuristic data-driven modeling flood prediction |
| title | Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling |
| title_full | Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling |
| title_fullStr | Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling |
| title_full_unstemmed | Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling |
| title_short | Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling |
| title_sort | use of meta heuristic techniques in rainfall runoff modelling |
| topic | rainfall-runoff meta-heuristic data-driven modeling flood prediction |
| url | http://www.mdpi.com/2073-4441/9/3/186 |
| work_keys_str_mv | AT kwokwingchau useofmetaheuristictechniquesinrainfallrunoffmodelling |