Special Issue "Management of Hydrological Extremes: Floods and Droughts"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: 20 October 2019.

Special Issue Editors

Guest Editor
Prof. Dr. João Filipe Santos Website E-Mail
Civil Engineering, Polytechnic Institute of Beja, 7800-309 Beja, Portugal
Phone: 00351-284 311 543
Interests: drought; floods; spatio-temporal analysis on hydroclimatic variables; climate change impact on water resources availability
Guest Editor
Prof. Dr. Maria Manuela Portela Website E-Mail
CERIS, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
Phone: +351 218 418 142
Interests: surface hydrology; extreme hydrological events; statistical models; trend detection; regionalization models; uncertainty and risks analysis and design of infra-structures
Guest Editor
Prof. Dr. Inmaculada Pulido-Calvo Website E-Mail
Dpto. de Ciencias Agroforestales, Escuela Técnica Superior de Ingeniería, Universidad de Huelva, 21007 Huelva, Spain
Phone: +34 667445436
Interests: hydraulic and water resources engineering; artificial neural networks; irrigation engineering; drought and pipe network analysis

Special Issue Information

Dear Colleagues

The management of extreme hydrological phenomena such as droughts and floods is assumed to be an important concern to all human civilization. Since they are global natural hazards that are being intensified by climate variability and constitute a threat to increasingly scarce freshwater, it is important to develop knowledge to support risk management and adaptation planning.

This Special Issue will focus on highlighting ongoing research investigations and new methodologies in the field to better anticipate and improve preparedness systems for future hydrological extreme events but also to facilitate the process of decision making and the promotion of societal resilience.

Within this framework, the Editor of this Special Issue would like to invite original research contributions that emphasize the following areas:

- Water governance and regulatory processes regarding the management of hydrological extremes;

- Preparedness systems and disaster warning. Methods and applications for (a) monitoring floods and droughts, (b) frequency analysis on flood and drought variables/indicators, spatio-temporal patterns, and variability, and (c) the prediction of hydrological extremes in near real-time and future forecasting;

- Risk assessment concepts for hydrological extremes that could innovate in respect to the limitations of current methods and assessment practices;

- An assessment of value of the information on hydrological impacts to relevant stakeholders and decision makers at regional scale using case studies;

- Risk management. New approaches on (a) the prevention and mitigation of hydrological extremes and (b) adaptation strategies for future climate scenarios;

- The vulnerability of water resources systems to extreme hydrological events using case studies.

Submissions of both general methodological contributions as well as case studies of hydrological extremes management in different regions covering a wide range of spatial scales are strongly encouraged.

Prof. Dr. João Filipe Santos
Prof. Dr. Maria Manuela Portela
Dr. Inmaculada Pulido-Calvo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • risk assessment
  • society resilience
  • floods
  • droughts
  • water resources vulnerability
  • preparedness and early warning systems

Published Papers (3 papers)

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Research

Open AccessFeature PaperArticle
A Continuous Drought Probability Monitoring System, CDPMS, Based on Copulas
Water 2019, 11(9), 1925; https://doi.org/10.3390/w11091925 (registering DOI) - 14 Sep 2019
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Management of Hydrological Extremes: Floods and Droughts)
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Open AccessArticle
Dependence Between Extreme Rainfall Events and the Seasonality and Bivariate Properties of Floods. A Continuous Distributed Physically-Based Approach
Water 2019, 11(9), 1896; https://doi.org/10.3390/w11091896 - 11 Sep 2019
Abstract
This paper focuses on proposing the minimum number of storms necessary to derive the extreme flood hydrographs accurately through event-based modelling. To do so, we analyzed the results obtained by coupling a continuous stochastic weather generator (the Advanced WEather GENerator) with a continuous [...] Read more.
This paper focuses on proposing the minimum number of storms necessary to derive the extreme flood hydrographs accurately through event-based modelling. To do so, we analyzed the results obtained by coupling a continuous stochastic weather generator (the Advanced WEather GENerator) with a continuous distributed physically-based hydrological model (the TIN-based real-time integrated basin simulator), and by simulating 5000 years of hourly flow at the basin outlet. We modelled the outflows in a basin named Peacheater Creek located in Oklahoma, USA. Afterwards, we separated the independent rainfall events within the 5000 years of hourly weather forcing, and obtained the flood event associated to each storm from the continuous hourly flow. We ranked all the rainfall events within each year according to three criteria: Total depth, maximum intensity, and total duration. Finally, we compared the flood events obtained from the continuous simulation to those considering the N highest storm events per year according to the three criteria and by focusing on four different aspects: Magnitude and recurrence of the maximum annual peak-flow and volume, seasonality of floods, dependence among maximum peak-flows and volumes, and bivariate return periods. The main results are: (a) Considering the five largest total depth storms per year generates the maximum annual peak-flow and volume, with a probability of 94% and 99%, respectively and, for return periods higher than 50 years, the probability increases to 99% in both cases; (b) considering the five largest total depth storms per year the seasonality of flood is reproduced with an error of less than 4% and (c) bivariate properties between the peak-flow and volume are preserved, with an error on the estimation of the copula fitted of less than 2%. Full article
(This article belongs to the Special Issue Management of Hydrological Extremes: Floods and Droughts)
Open AccessArticle
Deriving Design Flood Hydrographs Based on Copula Function: A Case Study in Pakistan
Water 2019, 11(8), 1531; https://doi.org/10.3390/w11081531 - 24 Jul 2019
Abstract
Flood events are characterized by flood peaks and volumes that can be mutually constructed using a copula function. The Indus basin system of Pakistan is periodically threatened by floods during monsoon seasons and thus causes huge losses to infrastructure as well as the [...] Read more.
Flood events are characterized by flood peaks and volumes that can be mutually constructed using a copula function. The Indus basin system of Pakistan is periodically threatened by floods during monsoon seasons and thus causes huge losses to infrastructure as well as the community and economy. The design flood hydrograph (DFH) of suitable magnitude and degree is imperative for sheltering dams against the flood risk. The hydrological pair of flood peak and volume is required to be defined using a multivariate analysis method. In this paper, the joint probability function of the hydrological pair is employed to derive the DFH in the Indus basin system of Pakistan. Firstly, we compared the fitting performance of different probability distributions (PDs) as a marginal distribution. Next, we compared the Archimedean family of copulas to construct the bivariate joint distribution of flood peak and volume. Later, the equal frequency combination (EFC) method and most likely combination (MLC) method using “OR” joint return period (JRPor), was involved to derive the design flood quantiles. Finally, we derived the DFH using the two combination methods based on Gumbel–Hougaard copula for different return periods. We presented the combination methods for updating the shape of the DFH in Pakistan. Our study will contribute towards the improvement of design standards of dams and environmental recovery in Pakistan. Full article
(This article belongs to the Special Issue Management of Hydrological Extremes: Floods and Droughts)
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