Abstract

The standardized precipitation index (SPI), is one of the most used drought indices. However, it is difficult to use to monitor the ongoing drought characteristics because it cannot be expeditiously related to precipitation deficits. It also does not provide information regarding the drought probability nor the temporal evolution of the droughts. By assigning the SPI to drought-triggering precipitation thresholds, a copula-based continuous drought probability monitoring system (CDPMS), was developed aiming to monitor the probability of having a drought as the rainy season advances. In fact, in climates with very pronounced rainy seasonality, the absence of precipitation during the rainy season is the fundamental cause of droughts. After presenting the CDPMS, we describe its application to Mainland Portugal and demonstrate that the system has an increased capability of anticipating drought probability by the end of the rainy season as new precipitation records are collected. The good performance of the system results from the ability of the copula to model complex dependence structures as those existing between precipitations at different time intervals. CDPMS is an innovative and user-friendly tool to monitor precipitation and, consequently, the drought probability, allowing the user to anticipate mitigation and adaptation measures, or even to issue alerts.

Highlights

  • Drought is a natural phenomenon without a clear onset which makes it difficult to recognize

  • It was assumed that the precipitation was progressively recorded and provided to the model until February 2018 aiming at estimating the drought probability by the end of the rainy season

  • Thisthe study developed such a tool, based on moderate copulas applied to the continuous model was not able to distinguish the intensity of the event, once severe and extreme droughts are monitoring of the drought probability, using only precipitation data, the continuous drought probability monitoring system (CDPMS)

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Summary

A Continuous Drought Probability Monitoring

João Dehon Pontes Filho 1 , Maria Manuela Portela 2, * , Ticiana Marinho de Carvalho Studart 1 and Francisco de Assis Souza Filho 1. Civil Engineering Research and Innovation for Sustainability (CERIS), Instituto Superior Tecnico (IST), University of Lisbon, 1649-004 Lisboa, Portugal. Received: 29 July 2019; Accepted: 11 September 2019; Published: 14 September 2019

Introduction
Mainland
Methods
CDPMS Definition
Copula Fitting Extreme Drought
Conditional Probability
CDPMS Performance Assessment
Precipitation Data
Precipitation Thresholds for Drought Recognition
Copula Fitting
Drought Risk Monitoring
Example
CDRMS Applied to a Single Site
CDRMS Development for Santa Marta da Montanha
CDRMS Application—Drought Risk Monitoring
Discussion
Findings

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