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Developing a Web-based decision support system for reservoir flood management
Author(s) -
Mokhtar Ghobadi,
Hesam Seyed Kaboli
Publication year - 2020
Publication title -
journal of hydroinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.654
H-Index - 50
eISSN - 1465-1734
pISSN - 1464-7141
DOI - 10.2166/hydro.2020.185
Subject(s) - flood myth , flood control , operator (biology) , environmental science , decision support system , control (management) , computer science , petroleum engineering , hydrology (agriculture) , engineering , data mining , geotechnical engineering , geography , artificial intelligence , biochemistry , chemistry , archaeology , repressor , transcription factor , gene
Proper management of reservoirs in flood conditions minimizes flood damage and keeps the reservoir in a stable condition. This paper presents a Web-based decision support system of reservoir flood management (WDRFM) for reservoirs with gated spillways. WDRFM is capable of estimating the current situation of the reservoir and before the flood reaches the reservoir, provides the operator with suggestions to have optimal control over gates, using multistage simulation-optimization models to minimize flood damage downstream. Investigating the possibility of changing the dam's discharge gates, carrying out dam pre-release, and announcing relevant flood control warnings can all be performed by WDRFM, while allowing the operator to determine such observations and make final decisions on a time step basis. To assess the performance of WDRFM, 15 scenarios in four groups for flood management were defined on April 14, 2016 at Dez Dam, Iran. A comparison of one scenario with similar initial conditions with the occurrence of flood event has shown that a daily peak discharge shows 997 m3/s decrease from that recorded by the operator. The ability to examine different scenarios based on the conditions at any time in the WDRFM enables the decision-makers and operators to confront various circumstances.

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