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Robust decadal hydroclimate predictions for northern Italy based on a twofold statistical approach

  • Sara Rubinetti
  • , Carla Taricco
  • , Silvia Alessio
  • , Angelo Rubino
  • , Ilaria Bizzarri
  • , Davide Zanchettin

Research output: Contribution to journalArticlepeer-review

Abstract

The Mediterranean area belongs to the regions most exposed to hydroclimatic changes, with a likely increase in frequency and duration of droughts in the last decades. However, many climate records like, e.g., North Italian precipitation and river discharge records, indicate that significant decadal variability is often superposed or even dominates long-term hydrological trends. The capability to accurately predict such decadal changes is, therefore, of utmost environmental and social importance. Here, we present a twofold decadal forecast of Po River (Northern Italy) discharge obtained with a statistical approach consisting of the separate application and cross-validation of autoregressive models and neural networks. Both methods are applied to each significant variability component extracted from the raw discharge time series using Singular Spectrum Analysis, and the final forecast is obtained by merging the predictions of the individual components. The obtained 25-year forecasts robustly indicate a prominent dry period in the late 2020s/early 2030s. Our prediction provides information of great value for hydrological management, and a target for current and future near-term numerical hydrological predictions.

Original languageEnglish
Article number671
JournalAtmosphere
Volume11
Issue number6
DOIs
Publication statusPublished - 1 Jun 2020
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Decadal climate predictions
  • Drought
  • Neural networks
  • Po river discharges
  • Runoff
  • Statistical methods

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