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Impacts of Climate Change on Extreme Hydro-Climatic Events: Droughts and Floods

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

Deadline for manuscript submissions: closed (31 December 2024) | Viewed by 9469

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Dr. María Jesús Esteban Parra

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Departamento de Física Aplicada, Facultad de Ciencias, Universidad de Granada, Granada, Spain
Interests: climate variability; climate change; dynamical downscaling; statistical downscaling; streamflow variability; drought; extreme events; teleconnections; seasonal forecasting
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Dr. Matilde García-Valdecasas Ojeda

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Applied Physics Department, University of Granada, 18071 Granada, Spain
Interests: climate change; regional climate models; climate projections; convection-permitting models; climate variability; hydrological models; flood hazards; drought; land–atmosphere feedback; aridity
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Dr. Sonia Raquel Gámiz-Fortis

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Guest Editor

Applied Physics Department, University of Granada, 18071 Granada, Spain
Interests: climate variability; climate change; seasonal prediction; decadal prediction; climate change projections; downscaling techniques; regional climate models; convection-permitting models; streamflow variability; drought
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Climate change is having a profound impact on extreme hydro-climatic events. On the one hand, droughts are becoming more frequent and severe, leading to reduced agricultural yields, water scarcity, and ecosystem stress. These dry spells also pose health and economic impacts in many parts of the world.

On the other hand, floods and extreme precipitation events are increasing in intensity and frequency, particularly in coastal regions. Rising sea levels, storm surges, and altered precipitation patterns contribute to more severe flooding and devasting effects. This results, among other negative impacts, in damage to critical infrastructure, land displacement, and water quality issues.

Implementing strategies for sustainable water management, resilient infrastructure, and early warning systems is essential to address these evolving hydro-climatic challenges and reduce their impacts on communities and ecosystems. To address these challenges, accurate climate projections as well as forecasting at different time scales (from seasonal to decadal) are crucial as climate services tools. This information can help communities and governments make appropriate decisions about water resource management, infrastructure planning, and disaster preparedness.

This Special Issue offers an opportunity to publish papers related to the impacts of climate change on extreme hydro-climatic events, specifically droughts and floods, but also those related to other extreme precipitation compound extreme events. Papers focused on observed and projected changes during the near and far future in the 21st century from different spatial scales and methodological approaches (statistical, physical, GCMs, downscaling, hydrological modeling, etc.) are welcome for submission. Papers dealing with climate change implications in topics such as water management are also of interest.

Dr. María Jesús Esteban Parra
Dr. Matilde García-Valdecasas Ojeda
Dr. Sonia Raquel Gámiz-Fortis
Guest Editors

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Keywords

climate change
drought
flood
extreme events
climate models
downscaling
water management
extreme precipitation compound events

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Published Papers (7 papers)

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Research

24 pages, 7022 KiB

Open AccessArticle

Evaluation of the Sensitivity of the Weather Research and Forecasting Model to Changes in Physical Parameterizations During a Torrential Precipitation Event of the El Niño Costero 2017 in Peru

by Alejandro Sánchez Oliva, Matilde García-Valdecasas Ojeda and Raúl Arasa Agudo

Water 2025, 17(2), 209; https://doi.org/10.3390/w17020209 - 14 Jan 2025

Abstract

This study evaluates the sensitivity of the Weather Research and Forecasting (WRF-ARW) model in its version 4.3.3 during different experiments on a torrential precipitation event associated with the 2017 El Niño Costero in Peru. The results are compared with two reference datasets: precipitation estimations from CHIRPS satellite data and SENAMHI meteorological station values. The event, which had significant economic and social impacts, is simulated using two nested domains with resolutions of 9 km (d01) and 3 km (d02). A total of 22 experiments are conducted, resulting from the combination of two planetary boundary layer (PBL) schemes: Yonsei University (YSU) and Mellor–Yamada–Janjic (MYJ), with five cumulus parameterization schemes: Betts–Miller–Janjic (BMJ), Grell–Devenyi (GD), Grell–Freitas (GF), Kain–Fritsch (KF), and New Tiedtke (NT). Additionally, the effect of turning off cumulus parameterization in the inner domain (d02) or in both (d01 and d02) is explored. The results show that the YSU scheme generally provides better results than the MYJ scheme in detecting the precipitation patterns observed during the event. Furthermore, it is concluded that turning off cumulus parameterization in both domains produces satisfactory results for certain regions when it is combined with the YSU PBL scheme. However, the KF cumulus parameterization is considered the most effective for intense precipitation events in this region, although it tends to overestimate precipitation in high mountain areas. In contrast, for lighter rains, combinations of the YSU PBL scheme with the GD or NT parameterization show a superior performance. It is worth nothing that for all experiments here used, there is a clear underestimation in terms of precipitation, except in high mountain regions, where the model tends to overestimate rainfall. Full article

(This article belongs to the Special Issue Impacts of Climate Change on Extreme Hydro-Climatic Events: Droughts and Floods)

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23 pages, 6616 KiB

Open AccessArticle

Adapting to Climate Change with Machine Learning: The Robustness of Downscaled Precipitation in Local Impact Analysis

by Santiago Mendoza Paz, Mauricio F. Villazón Gómez and Patrick Willems

Water 2024, 16(21), 3070; https://doi.org/10.3390/w16213070 - 26 Oct 2024

Viewed by 1920

Abstract

The skill, assumptions, and uncertainty of machine learning techniques (MLTs) for downscaling global climate model’s precipitation to the local level in Bolivia were assessed. For that, an ensemble of 20 global climate models (GCMs) from CMIP6, with random forest (RF) and support vector machine (SVM) techniques, was used on four zones (highlands, Andean slopes, Amazon lowlands, and Chaco lowlands). The downscaled series’ skill was evaluated in terms of relative errors. The uncertainty was analyzed through variance decomposition. In most cases, MLTs’ skill was adequate, with relative errors less than 50%. Moreover, RF tended to outperform SVM. Robust (weak) stationary (perfect prognosis) assumptions were found in the highlands and Andean slopes. The weakness was attributed to topographical complexity. The downscaling methods were shown to be the dominant source of uncertainties. This analysis allowed the derivation of robust future projections, showing higher annual rainfall, shorter dry spell duration, and more frequent but less intense high rainfall events in the highlands. Apart from the dry spell’s duration, a similar pattern was found for the Andean slopes. A decrease in annual rainfall was projected in the Amazon lowlands and an increase in the Chaco lowlands. Full article

(This article belongs to the Special Issue Impacts of Climate Change on Extreme Hydro-Climatic Events: Droughts and Floods)

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15 pages, 4673 KiB

Open AccessArticle

Variability of Dry Days and Sequences of Dry Days in the Polish Carpathians in the Period 1986–2020

by Marta Cebulska and Robert Twardosz

Water 2024, 16(20), 2982; https://doi.org/10.3390/w16202982 - 19 Oct 2024

Viewed by 608

Abstract

This study provides a climatological analysis of annual and long-term variability of dry days and sequences of dry days in the Polish Carpathians between 1986 and 2020. The input data for the research was compiled from the daily precipitation totals from 17 meteorological stations and the T. Niedźwiedź catalogue of circulation types over southern Poland. The frequency of sequences of dry days of different duration has been presented. The incidence of long-term periods has been related to the atmospheric circulation. The number of dry days and the averages of both the number and of the duration of sequences of dry days were analysed for the study period. This yielded an average annual number of dry days ranging from 142 to 195 (39–53% of days in a year), depending on the altitude above sea level and longitude. A general pattern emerged in which the number of dry days increased from west to east. At most stations, there were no statistically significant trends with respect to the dry day characteristics analysed. This is an obvious result of high year-to-year variability, which means that only large changes can achieve statistical significance. Dry days have been evidenced to relate to circulation types. The vast majority of dry days are related to anticyclonic systems, particularly the anticyclonic wedge (Ka) and western anticyclonic (Wa) situations. On the other hand, no clear-cut relationship was established between an increase in air temperature and the occurrence of dry days. Full article

(This article belongs to the Special Issue Impacts of Climate Change on Extreme Hydro-Climatic Events: Droughts and Floods)

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20 pages, 9614 KiB

Open AccessArticle

Spatial and Temporal Variations’ Characteristics of Extreme Precipitation and Temperature in Jialing River Basin—Implications of Atmospheric Large-Scale Circulation Patterns

by Lin Liao, Saeed Rad, Junfeng Dai, Asfandyar Shahab, Jianying Mo and Shanshan Qi

Water 2024, 16(17), 2504; https://doi.org/10.3390/w16172504 - 3 Sep 2024

Viewed by 841

Abstract

In recent years, extreme climate events have shown to be occurring more frequently. As a highly populated area in central China, the Jialing River Basin (JRB) should be more deeply explored for its patterns and associations with climatic factors. In this study, based on the daily precipitation and atmospheric temperature datasets from 29 meteorological stations in JRB and its vicinity from 1960 to 2020, 10 extreme indices (6 extreme precipitation indices and 4 extreme temperature indices) were calculated. The spatial and temporal variations of extreme precipitation and atmospheric temperature were analyzed using Mann–Kendall analysis, to explore the correlation between the atmospheric circulation patterns and extreme indices from linear and nonlinear perspectives via Pearson correlation analysis and wavelet coherence analysis (WTC), respectively. Results revealed that among the six selected extreme precipitation indices, the Continuous Dry Days (CDD) and Continuous Wetness Days (CWD) showed a decreasing trend, and the extreme precipitation tended to be shorter in calendar time, while the other four extreme precipitation indices showed an increasing trend, and the intensity of precipitation and rainfall in the JRB were frequent. As for the four extreme temperature indices, except for TN10p, which showed a significant decreasing trend, the other three indices showed a significant increasing trend, and the number of low-temperature days in JRB decreased significantly, the duration of high temperature increased, and the basin was warming continuously. Spatially, the spatial variation of extreme precipitation indices is more obvious, with decreasing stations mostly located in the western and northern regions, and increasing stations mostly located in the southern and northeastern regions, which makes the precipitation more regionalized. Linearly, most of the stations in the extreme atmospheric temperature index, except TN10p, show an increasing trend and the significance is more obvious. Except for the Southern Oscillation Index (SOI), other atmospheric circulation patterns have linear correlations with the extreme indices, and the Arctic Oscillation (AO) has the strongest significance with the CDD. Nonlinearly, NINO3.4, Pacific Decadal Oscillation (PDO), and SOI are not the main circulation patterns dominating the changes of TN90p, and average daily precipitation intensity (SDII), maximum daily precipitation amount (RX1day), and maximum precipitation in 5 days (Rx5day) were most clearly associated with atmospheric circulation patterns. This also confirms that atmospheric circulation patterns and climate tend not to have a single linear relationship, but are governed by more complex response mechanisms. This study aims to help the relevant decision-making authorities to cope with the more frequent extreme climate events in JRB, and also provides a reference for predicting flood, drought and waterlogging risks. Full article

(This article belongs to the Special Issue Impacts of Climate Change on Extreme Hydro-Climatic Events: Droughts and Floods)

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16 pages, 11839 KiB

Open AccessArticle

Assessment of Long-Term Streamflow Response to Flash Drought in the São Francisco River Basin over the Last Three Decades (1991–2020)

by Humberto Alves Barbosa and Catarina de Oliveira Buriti

Water 2024, 16(16), 2271; https://doi.org/10.3390/w16162271 - 12 Aug 2024

Viewed by 1335

Abstract

Flash droughts, characterized by a rapid onset and severe intensity, pose a serious threat to water resource management. Extensive research has indicated that drought has lagged impacts on streamflow. Nevertheless, the hydrometeorological conditions by which streamflow dynamics respond to drought within the São Francisco River Basin (SFRB) remain ambiguous. To bridge this gap, we conducted a study on long-term streamflow responses to flash drought in the SFRB from 1991 to 2020, combining the Standardized Antecedent Precipitation Evapotranspiration Index (SAPEI) and quantile streamflow with a trend analysis. This study employed the SAPEI, a daily drought index, to identify flash droughts and assess the response of streamflow to the identified events across the SFRB. Our findings reveal insights into the direct response of streamflow to flash drought conditions, stimulated by the application of the SAPEI for analysis of flash drought events. The interannual flash droughts fluctuated over the years, with the middle part of the SFRB experiencing frequent, longer flash droughts, while the south part encountered shorter but less frequent events. About 55% of the study area is trended towards drying conditions. A comparative analysis of the SAPEI and streamflow identified a synchronized response to the onset of flash drought events, but the recovery timescale for the SAPEI and streamflow varied among the events. This study enhances understanding of the flash-drought–streamflow relationship in the SFRB and provides theoretical support for addressing drought risks under climate change. Full article

(This article belongs to the Special Issue Impacts of Climate Change on Extreme Hydro-Climatic Events: Droughts and Floods)

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28 pages, 14381 KiB

Open AccessArticle

The Impact of Climate Change on Hydro-Meteorological Droughts in the Chao Phraya River Basin, Thailand

by Bounhome Kimmany, Supattra Visessri, Ponleu Pech and Chaiwat Ekkawatpanit

Water 2024, 16(7), 1023; https://doi.org/10.3390/w16071023 - 1 Apr 2024

Cited by 4 | Viewed by 2227

Abstract

This study evaluated the impacts of climate change on hydro-meteorological droughts in the Chao Phraya River Basin (CPRB), Thailand under two Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP8.5). We used three Reginal Climate Models (RCMs) of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment—Southeast Asia (SEACLID/CORDEX-SEA), which are bias corrected. The Soil and Water Assessment Tool (SWAT) was used to simulate streamflow for future periods. The Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were estimated and used for drought characterization at three time scales (3, 6, and 12 months). The lag time between meteorological and hydrological droughts is approximately 1–3 months. The results suggest that the CPRB is likely to experience less frequent hydro-meteorological drought events in the future. The meteorological drought is projected to be longer, more severe, and intense. The severity of hydrological drought tends to decrease, but the intensity could increase. Climate change has been discovered to alter drought behaviors in the CPRB, posing a threat to drought monitoring and warning because droughts will be less predictable in future climate scenarios. The characterization of historical and future droughts over the CPRB is therefore valuable in developing an improved understanding of the risks of drought. Full article

(This article belongs to the Special Issue Impacts of Climate Change on Extreme Hydro-Climatic Events: Droughts and Floods)

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22 pages, 15310 KiB

Open AccessArticle

The Applicability of the Drought Index and Analysis of Spatiotemporal Evolution Mechanisms of Drought in the Poyang Lake Basin

by Zihan Gui, Heshuai Qi, Faliang Gui, Baoxian Zheng, Shiwu Wang and Hua Bai

Water 2024, 16(5), 766; https://doi.org/10.3390/w16050766 - 4 Mar 2024

Cited by 1 | Viewed by 1506

Abstract

Poyang Lake, the largest freshwater lake in China, is an important regional water resource and a landmark ecosystem. In recent years, it has experienced a period of prolonged drought. Using appropriate drought indices to describe the drought characteristics of the Poyang Lake Basin (PLB) is of great practical significance in the face of severe drought situations. This article explores the applicability of four drought indices (including the precipitation anomaly index (PJP), standardized precipitation index (SPI), China Z-index (CPZI), and standardized precipitation evapotranspiration index (SPEI)) based on historical facts. A systematic study was conducted on the spatiotemporal evolution patterns of meteorological drought in the PLB based on the optimal drought index. The results show that SPI is more suitable for the description of drought characteristics in the PLB. Meteorological droughts occur frequently in the summer and autumn in the PLB, with the frequency of mild drought being 17.29% and 16.88%, respectively. The impact range of severe drought or worse reached 22.19% and 28.33% of the entire basin, respectively. The probability of drought occurrence in the PLB shows an increasing trend in spring, while in most areas, it shows a decreasing trend in other seasons, with only a slight increase in the upper reaches of the Ganjiang River (UGR). One of the important factors influencing drought in the PLB is atmospheric circulation. The abnormal variation of the Western Pacific Subtropical High was one of the key factors contributing to the severe drought in the PLB in 2022. This study is based on a long-term series of meteorological data and selects the drought index for the PLB. It describes the spatiotemporal distribution characteristics and evolution patterns of drought and investigates the developmental path and influencing factors of drought in typical years. This study provides a reliable scientific basis for similar watershed water resource management. Full article

(This article belongs to the Special Issue Impacts of Climate Change on Extreme Hydro-Climatic Events: Droughts and Floods)

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