Statistical Modelling 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 July 2024 | Viewed by 542

Special Issue Editor


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Guest Editor
Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland
Interests: hydrological extremes; floods; droughts; precipitation; statistical modelling; estimation; uncertainty
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Special Issue Information

Dear Colleagues,

In the face of observed climate change, we are increasingly dealing with extreme hydrological phenomena, such as droughts and floods. Their assessment, modelling and prediction represent a significant challenge for the scientific community. Due to their profound effects, hydrological extremes are also of special interest to the general public, policymakers and natural event risk managers. Hence, the most pressing challenge currently is the development of a new generation of more accurate and reliable models that can estimate the impact of environmental changes on the frequency and magnitude of extreme weather events.

In this Special Issue of Water, we are particularly interested in studies presenting innovative approaches to the statistical modelling and analysis of hydrological extremes, namely floods and droughts. We invite authors to present their research on the following topics, among other related subjects:

  • Univariate and multivariate extreme value analysis;
  • Flood frequency modelling;
  • Regional and global drought analysis;
  • Assessment of uncertainties in hydrological observations;
  • (Combined) use of various sources of data as in situ, satellite, climate model outputs, paleohistorical, etc.
  • Projections of extreme hydrological phenomena;
  • Compound events approach;
  • Socio-environmental consequences of hydrological extremes;
  • Vulnerability analysis of extreme events.

Dr. Iwona Kuptel-Markiewicz
Guest Editor

Manuscript Submission Information

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Keywords

  • hydrological extremes
  • floods
  • droughts
  • statistical and stochastic modelling
  • flood frequency analysis
  • drought risk and uncertainty analysis
  • climate change

Published Papers (1 paper)

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Research

23 pages, 2239 KiB  
Article
Developing Regional Hydrological Drought Risk Models through Ordinary and Principal Component Regression Using Low-Flow Indexes in Susurluk Basin, Turkey
by Çiğdem Gürler, Alper Serdar Anli and Havva Eylem Polat
Water 2024, 16(11), 1473; https://doi.org/10.3390/w16111473 - 22 May 2024
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Abstract
Susurluk Basin is among the basins that may be most affected by drought risk due to its agricultural, economic, and natural resources. In this study, regional hydrological drought risk models were developed for water supply systems in the Susurluk Basin, Turkey. Twenty-four flow [...] Read more.
Susurluk Basin is among the basins that may be most affected by drought risk due to its agricultural, economic, and natural resources. In this study, regional hydrological drought risk models were developed for water supply systems in the Susurluk Basin, Turkey. Twenty-four flow observation sites with 25 years or more of data showing natural flow characteristics as much as possible were converted into daily flow data with Q7, Q15, Q30, and Q60 low-flow indexes. Regionalization was carried out by two-stage multivariate cluster and principal component analysis using the basins’ physical and hydrological characteristics and low-flow statistics, and two homogeneous regions were obtained due to the discordancy, heterogeneity, and goodness of fit tests, which are L-moment approaches. Regional models were performed with ordinary and principal component regression techniques using the physical and hydrological characteristics of the watersheds and regional low-flow frequency analysis. The cross-validation procedure results for ungauged basins show that ordinary regression models are more effective in the lowland first region. In contrast, principal component regression models are more suitable for the mountainous second region. This study’s findings, which are a first for the Susurluk Basin, will have important results in terms of agricultural water management in the region and will help the water authority in water allocation. To investigate whether human impact and climate change impact the prediction of hydrological drought, we recommend seasonal non-stationary frequency analysis with the addition of useful empirical hydrological drought indexes. Full article
(This article belongs to the Special Issue Statistical Modelling of Hydrological Extremes: Floods and Droughts)
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