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CRDEMO: Combined regionalization and dual entropy‐multiobjective optimization for hydrometric network design
Author(s) -
Samuel Jos,
Coulibaly Paulin,
Kollat Joshua
Publication year - 2013
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2013wr014058
Subject(s) - dual (grammatical number) , multi objective optimization , entropy (arrow of time) , mathematical optimization , computer science , mathematics , physics , thermodynamics , art , literature
Establishing an adequate hydrometric network to provide accurate and reliable continuous flow information for various users remains a major challenge. This includes the design of new networks or the evaluation of existing networks. This study proposes a combined regionalization and dual entropy‐multiobjective optimization (CRDEMO) method for determining minimum network that meets the World Meteorology Organization (WMO) standards, which is considered herein an optimal minimum network. A regionalization approach is used to estimate flows in potential locations for new additional stations, and a dual entropy‐multiobjective optimization approach is used to identify optimal trade‐offs between the maximum possible information content and the minimum shared information among the stations. The method was examined in two Canadian River basins, namely, the St. John River and St. Lawrence River basins. The St. John River basin has a higher network density compared to the St. Lawrence River basin. Results of the analysis indicate that the St. Lawrence River basin requires a high number of new additional stations to meet the WMO minimum network density. It was also determined that existing stations do not have a significant influence in determining the locations of new stations in the St. Lawrence River basin. Conversely, however, in the St. John River basin, existing stations have significant influence on the determination of locations of new stations due to the higher number of existing stations. Overall, the CRDEMO technique is shown to be robust for designing optimal minimum hydrometric networks and can be a useful tool for evaluating current and proposed networks.