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Droughts Prediction: a Methodology Based on Climate Seasonal Forecasts

Author

Listed:
  • E. Arnone

    (Università degli Studi di Udine
    Amigo s.r.l.)

  • Marco Cucchi

    (University of Reading
    University of Reading)

  • Sara Dal Gesso

    (Amigo s.r.l.)

  • Marcello Petitta

    (ENEA, SSPT-MET-CLIM
    Institute for Earth Observation)

  • Sandro Calmanti

    (ENEA, SSPT-MET-CLIM)

Abstract

This study proposes a methodology for the drought assessment based on the seasonal forecasts. These are climate predictions of atmospheric variables, such as precipitation, temperature, wind speed, for upcoming season, up to 7 months. In regions particularly vulnerable to droughts and to changes in climate, such as the Mediterranean areas, predictions of precipitation with months in advance are crucial for understanding the possible shifts, for example, in water resource availability. Over Europe, practical applications of seasonal forecasts are still rare, because of the uncertainties of their skills; however, the predictability varies depending on the season and area of application. In this study, we describe a methodology which integrates, through a statistical approach, seasonal forecast and reanalysis data to assess the climate state, i.e. drought or not, of a region for predefined periods in the next future, at monthly scale. Additionally, the skill of the forecasts and the reliability of the released climate state assessment are estimated in terms of the false rate, i.e. the probability of missing alerts or false alarms. The methodology has been first built for a case study in Zakynthos (Greece) and then validated for a case study in Sicily (Italy). The selected locations represent two areas of the Mediterranean region often suffering from drought and water shortage situations. Results showed promising findings, with satisfying matching between predictions and observations, and false rates ranging from 1 to 50%, depending on the selected forecast period.

Suggested Citation

  • E. Arnone & Marco Cucchi & Sara Dal Gesso & Marcello Petitta & Sandro Calmanti, 2020. "Droughts Prediction: a Methodology Based on Climate Seasonal Forecasts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(14), pages 4313-4328, November.
  • Handle: RePEc:spr:waterr:v:34:y:2020:i:14:d:10.1007_s11269-020-02623-3
    DOI: 10.1007/s11269-020-02623-3
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    References listed on IDEAS

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    1. Donald Wilhite & Mark Svoboda & Michael Hayes, 2007. "Understanding the complex impacts of drought: A key to enhancing drought mitigation and preparedness," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 763-774, May.
    2. De Felice, Matteo & Alessandri, Andrea & Catalano, Franco, 2015. "Seasonal climate forecasts for medium-term electricity demand forecasting," Applied Energy, Elsevier, vol. 137(C), pages 435-444.
    3. A. Cancelliere & G. Mauro & B. Bonaccorso & G. Rossi, 2007. "Drought forecasting using the Standardized Precipitation Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 801-819, May.
    4. Alexander Danilenko & Eric Dickson & Michael Jacobsen, 2010. "Climate Change and Urban Water Utilities : Challenges and Opportunities," World Bank Publications - Reports 11696, The World Bank Group.
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    Cited by:

    1. Luis Garrote & Alvaro Sordo-Ward, 2020. "Preface to the Special Issue: Managing Water Resources for a Sustainable Future," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(14), pages 4307-4311, November.
    2. Pietro Monforte & Maria Alessandra Ragusa, 2022. "Temperature Trend Analysis and Investigation on a Case of Variability Climate," Mathematics, MDPI, vol. 10(13), pages 1-13, June.
    3. Abdol Rassoul Zarei & Mohammad Reza Mahmoudi, 2020. "Ability Assessment of the Stationary and Cyclostationary Time Series Models to Predict Drought Indices," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(15), pages 5009-5029, December.

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