A gene-wavelet model for long lead time drought forecasting

Ali Danandeh Mehr*, Ercan Kahya, Mehmet Özger

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

88 Citations (Scopus)

Abstract

Drought forecasting is an essential ingredient for drought risk and sustainable water resources management. Due to increasing water demand and looming climate change, precise drought forecasting models have recently been receiving much attention. Beginning with a brief discussion of different drought forecasting models, this study presents a new hybrid gene-wavelet model, namely wavelet-linear genetic programing (WLGP), for long lead-time drought forecasting. The idea of WLGP is to detect and optimize the number of significant spectral bands of predictors in order to forecast the original predictand (drought index) directly. Using the observed El Nin&tild;o-Southern Oscillation indicator (NINO 3.4 index) and Palmer's modified drought index (PMDI) as predictors and future PMDI as predictand, we proposed the WLGP model to forecast drought conditions in the State of Texas with 3, 6, and 12-month lead times. We compared the efficiency of the model with those of a classic linear genetic programing model developed in this study, a neuro-wavelet (WANN), and a fuzzy-wavelet (WFL) drought forecasting models formerly presented in the relevant literature. Our results demonstrated that the classic linear genetic programing model is unable to learn the non-linearity of drought phenomenon in the lead times longer than 3. months; however, the WLGP can be effectively used to forecast drought conditions having 3, 6, and 12-month lead times. Genetic-based sensitivity analysis among the input spectral bands showed that NINO 3.4 index has strong potential effect in drought forecasting of the study area with 6-12-month lead times.

Original languageEnglish
Pages (from-to)691-699
Number of pages9
JournalJournal of Hydrology
Volume517
DOIs
Publication statusPublished - 9 Sept 2014

Bibliographical note

Publisher Copyright:
© 2014 Elsevier B.V.

Keywords

  • Drought forecasting
  • El Nin&tild;o-Southern Oscillation
  • Hydrologic models
  • Linear genetic programing
  • Palmer's modified drought index
  • Wavelet transform

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