Fast Comprehensive Flood Risk Assessment Based on Game Theory and Cloud Model Under Parallel Computation (P-GT-CM)

Qiang Zou (), Li Liao and Hui Qin
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Qiang Zou: Changjiang Institute of Survey, Planning, Design and Research
Li Liao: Hubei University of Technology
Hui Qin: Huazhong University of Science and Technology

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2020, vol. 34, issue 5, No 5, 1625-1648

Abstract: Abstract Flood risk assessment is the fundamental work of flood risk management and important decision-making basis for essential flood mitigation, and it is an attractive and difficult problem with more requirements on convenience, effectiveness and timeliness. Specifically, the uncertainty and nonlinear relation between assessment indices and evaluation levels are always difficult to be revealed, and it is not easy to calculate the weight of assessment indices by subjective judgment and objective properties. Moreover, reducing the total computational time for rapid flood risk map application is rarely studied. On the basis of cloud model (CM), game theory (GT) and parallel computation technology (PC), a new model named P-CM-GT for fast comprehensive flood risk assessment was presented, which has three advantages, i.e. firstly, it could describe the fuzziness randomness of membership degree via CM; secondly, the combination weight integrating with different weights is employed via GC; thirdly, the computation process of CM and GT is combined with PC to reduce the running time. Finally, taking a case study on fast comprehensive flood risk assessment of Hubei Province in China, the flood risk grades were achieved with less time, and the results were appropriately consistent with the actual situation, and the future flood control focus is to set up a wholesome and effective emergency plan. Moreover, the proposed model is feasible, effective, fast and applicable, thus give out a novel thinking for fast flood risk management.

Keywords: Flood risk assessment; Cloud model; Game theory; Combination weight; Parallel computation (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11269-020-02495-7

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