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Evaluation of Markov Chain Based Drought Forecasts in an Andean Regulated River Basin Using the Skill Scores RPS and GMSS

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  • Alex Avilés
  • Rolando Célleri
  • Javier Paredes
  • Abel Solera

Abstract

On behalf of the decision-makers of Andean regulated river basins a drought index was developed to predict the occurrence and extent of drought events. Two stochastic models, the Markov Chain First Order (MCFO) and the Markov Chain Second Order (MCSO) model, predicting the frequency of monthly droughts were applied and the performance checked using two skill scores, respectively the ranked probability score (RPS) and the Gandin-Murphy skill score (GMSS). Data of the Chulco River basin (3200–4300 m.a.s.l.), situated in the Ecuadorian southern Andes, were employed to test the performance of both models. Results indicate that events with greater drought severity were more accurately predicted. The study also revealed the importance of verifying the quality of the forecasts and to have an assessment of the likely performance of the forecasting models before adopting any model and accepting the resulting information for decision-making. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Alex Avilés & Rolando Célleri & Javier Paredes & Abel Solera, 2015. "Evaluation of Markov Chain Based Drought Forecasts in an Andean Regulated River Basin Using the Skill Scores RPS and GMSS," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 1949-1963, April.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:6:p:1949-1963
    DOI: 10.1007/s11269-015-0921-2
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    References listed on IDEAS

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    Cited by:

    1. Mahdi Soleimani Motlagh & Hoda Ghasemieh & Ali Talebi & Khodayar Abdollahi, 2017. "Identification and Analysis of Drought Propagation of Groundwater During Past and Future Periods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 109-125, January.
    2. Zhang, Yu & Hao, Zengchao & Feng, Sifang & Zhang, Xuan & Xu, Yang & Hao, Fanghua, 2021. "Agricultural drought prediction in China based on drought propagation and large-scale drivers," Agricultural Water Management, Elsevier, vol. 255(C).

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