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Natural Hazards

, Volume 93, Issue 1, pp 339–347 | Cite as

Two precautions of entropy-weighting model in drought-risk assessment

  • Fanghui Yi
  • Chen Li
  • Yan Feng
Original Paper
  • 81 Downloads

Abstract

Two disadvantages of the entropy-weighting model (EWM) in drought-risk assessment are presented through two typical examples in this paper. (1) For distortion in the normalization process, entropy defined by EWM cannot represent the indicator’s dipartite degree correctly when too many zero values exist in the observation data. (2) Given that EWM neglects the indicator’s practical significance in drought-risk assessment, the indicator’s dipartite degree cannot correctly represent its importance when observation data are concentrated in the worst category. These two problems lead to unjustified drought-risk assessment results. Therefore, the features of observation data should be checked before weighting. If the indicator’s observation values are concentrated in the worst domain or numerous zero values exist, then EWM should be applied cautiously.

Keywords

Entropy-weighting method Drought-risk assessment Observation data checking 

Notes

Acknowledgements

This work is supported by the Natural Science Foundation of Water Resource Department of Hunan Government (No. 201524507).

Supplementary material

11069_2018_3303_MOESM1_ESM.doc (41 kb)
Supplementary material 1 (DOC 41 kb)

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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Water Resources and Hydropower EngineeringWuhan UniversityWuhanChina
  2. 2.School of Civil Engineering and ArchitectureNanchang UniversityNanchangChina
  3. 3.Key Laboratory of Poyang Lake Environment and Resource Utilization (Nanchang University)Ministry of EducationNanchangChina

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