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Assessment of Extreme Meteorological and Hydrological Events

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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 (25 January 2024) | Viewed by 10304

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Special Issue Editors

Dr. Qing Cao

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Guest Editor

School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: hydrometeorology; climate change; ENSO; rainfall; runoff

Prof. Dr. Tiexi Chen

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Guest Editor

School of Geography and Science, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: hydrology; water resources; remote sensing; climate change
Special Issues, Collections and Topics in MDPI journals

Dr. Shuci Liu

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Guest Editor

Department of Environment and Science, Queensland Government, Brisbane 4102, Australia
Interests: hydrology; water resources; water quality; climate change

Special Issue Information

Dear Colleagues,

This Special Issue, entitled “Assessment of Extreme Meteorological and Hydrological Events”, aims to provide an in-depth examination of extreme weather events and their impact on the Earth's atmosphere, climate, and hydrological systems. This Special Issue will focus on the assessment and analysis of extreme meteorological phenomena, such as hurricanes, heatwaves, heavy rainfall, droughts, floods, and other extreme weather patterns, along with their associated hydrological consequences.

This Special Issue will build upon and contribute to the existing body of literature related to extreme meteorological and hydrological events. While numerous studies have been published on individual aspects of extreme events, this collection aims to create a comprehensive synthesis of recent advancements in the field.

Overall, we aim to provide researchers, policymakers, and practitioners with a valuable resource for understanding and addressing the challenges posed by extreme meteorological and hydrological events in the context of a changing world. Through this comprehensive examination, this Special Issue will contribute to the advancement of knowledge and inform evidence-based decision making for effective disaster risk reduction and climate change adaptation measures.

Dr. Qing Cao
Prof. Dr. Tiexi Chen
Dr. Shuci Liu
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 submissions that pass pre-check are 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 semimonthly 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 2600 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

extreme events
meteorological events
risk assessment
climate change adaptation
extreme weather patterns
water resources

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Published Papers (5 papers)

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Research

16 pages, 4882 KiB

Open AccessArticle

Response of Land Surface Temperature to Heatwave-Induced Bio-Geophysical Changes in Tropical Forests on Hainan Island from 2010 to 2022

by Yunshuai Li, Xinyuan Shao, Zhixiang Wu, Zhongyi Sun, Mingzhe Li, Lingxiu Jiang, Yuanhong Xian and Peng Wang

Water 2024, 16(5), 752; https://doi.org/10.3390/w16050752 - 1 Mar 2024

Viewed by 1276

Abstract

Land surface temperature plays an important role in the water cycle and surface energy balance. Using data collected by a vorticity covariance tower from 2010 to 2022, the relative threshold method and TRM method were employed to study the land–atmosphere exchange of water and the heat flux of rubber forest ecosystems under heatwave and non-heatwave conditions. The results show that the latent heat flux, sensible heat flux, and incoming and outgoing radiation increase from non-heatwave to heatwave conditions. In addition, the multi-year average LST was 6.7 °C higher under HW conditions than under non-HW conditions at the 99% confidence level. Further attribution analysis demonstrates that heatwave-induced land surface temperature change is mainly governed by atmospheric factors rather than by land surface factors. Specifically, radiative forcing shows the largest positive contribution, which is partly offset by the negative contributions of air temperature and relative humidity. In particular, the contributions of radiative forcing, air temperature, relative humidity, and atmospheric pressure to LST were 14.70 K, −4.76 K, −5.86 K, and −0.04 K, respectively. Moreover, surface resistance contributed to LST by 2.42 K, aerodynamic resistance by −0.23 K, and soil heat flux by −0.91 K. Full article

(This article belongs to the Special Issue Assessment of Extreme Meteorological and Hydrological Events)

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24 pages, 60353 KiB

Open AccessArticle

Evaluation of Extreme Climate Indices over the Three Northeastern Provinces of China Based on CMIP6 Models Outputs

by Heng Xiao, Yue Zhuo, Kaiwen Pang, Hong Sun, Zhijia An and Xiuyu Zhang

Water 2023, 15(22), 3895; https://doi.org/10.3390/w15223895 - 8 Nov 2023

Cited by 1 | Viewed by 1337

Abstract

This study evaluates the performance of Global Climate Models (GCMs) in simulating extreme climate in three northeastern provinces of China (TNPC). A total of 23 GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) were selected and compared with observations from 1961 to 2010, using the 12 extreme climate indices defined by the Expert Team on Climate Change Detection and Indicators. The Interannual Variability Skill Score (IVS), Taylor diagrams and Taylor Skill Scores (S) were used as evaluation tools to compare the outputs of these 23 GCMs with the observations. The results show that the monthly minimum of daily minimum temperature (TNn) is overestimated in 55.7% of the regional grids, while the percentage of time when the daily minimum temperature is below the 10th percentile (TN10p) and the monthly mean difference between the daily maximum and minimum temperatures (DTR) are underestimated in more than 95% of the regional grids. The monthly maximum value of the daily maximum temperature (TXx) and the annual count when there are at least six consecutive days of the minimum temperature below the 10th percentile (CSDI) have relatively low regional spatial biases of 1.17 °C and 1.91 d, respectively. However, the regional spatial bias of annual count when the daily minimum temperature is below 0 °C (FD) is relatively high at 9 d. The GCMs can efficiently capture temporal variations in CSDI and TN10p (IVS < 0.5), as well as the spatial patterns of TNn and FD (S > 0.8). For the extreme precipitation indices, GCMs overestimate the annual total precipitation from days greater than the 95th percentile (R95p) and the annual count when precipitation is greater than or equal to 10 mm (R10 mm) in more than 90% of the regional grids. The maximum number of consecutive days when precipitation is below 1 mm (CDD) and the ratio of annual total precipitation to the number of wet days (greater than or equal to 1 mm) (SDII) are underestimated in more than 80% and 54% of the regional grids, respectively. The regional spatial bias of the monthly maximum consecutive 5-day precipitation (RX5day) is relatively small at 10.66%. GCMs are able to better capture temporal variations in the monthly maximum 1-day precipitation (RX1day) and SDII (IVS < 0.6), as well as spatial patterns in R95p and R10mm (S > 0.7). The findings of this study can provide a reference that can inform climate hazard risk management and mitigation strategies for the TNPC. Full article

(This article belongs to the Special Issue Assessment of Extreme Meteorological and Hydrological Events)

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21 pages, 9400 KiB

Open AccessArticle

Mapping the Social, Economic, and Ecological Impact of Floods in Brisbane

by Yuewei Hou, Yongping Wei, Shuanglei Wu and Jinghan Li

Water 2023, 15(21), 3842; https://doi.org/10.3390/w15213842 - 3 Nov 2023

Cited by 1 | Viewed by 4238

Abstract

Flooding has become one of the most dangerous and expensive disasters due to urbanization and climate change. Tools for assessing flood impact are required to support the shift of flood mitigation management from post-disaster recovery and reconstruction to community-driven pre-disaster warning and preparation. This study aims to develop an integrated approach to spatially assess the economic and social losses and ecological gain and identify the geographical factors of locations with high impacts of floods in Brisbane using the datasets collected from both the 2011 and 2022 flood events. Water depth, inundated area, land cover, ecosystem service value, mortality, and morbidity were considered to assess flood impacts. It is found that downstream (above 23,500 m from the upper stream) riverside communities (within 800 m of the river) with low altitudes (below 15 m) are more likely to experience significant flood damage. Flood impacts have bell-shaped developments with elevation and direct distance to the upstream river source and an exponential decline with distances to the river. These findings have implications for formulating future urban land use and community-tailored mitigation strategies, particularly for flood warning and preparation. Full article

(This article belongs to the Special Issue Assessment of Extreme Meteorological and Hydrological Events)

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21 pages, 7713 KiB

Open AccessArticle

Quantitative Analysis of the Uncertainty of Drought Process Simulation Based on Atmospheric–Hydrological Coupling in Different Climate Zones

by Huating Xu, Zhiyong Wu, Hai He, Ruifang Chen and Xiaotao Wu

Water 2023, 15(18), 3286; https://doi.org/10.3390/w15183286 - 18 Sep 2023

Cited by 1 | Viewed by 1219

Abstract

Droughts can lead to drought disasters, which have become one of the main natural disasters affecting the development of social economies and ecological environments around the world. Timely and effective drought process simulation and prediction based on atmospheric–hydrological coupling is crucial for drought prevention and resistance. The initial condition (IC) is one source causing uncertainty in drought process simulation and prediction, and the impacts are different with drought duration, basin size and region. Therefore, a quantitative method that measures the uncertainty caused by ICs on the drought process simulation in different climate zones is proposed in this study. In this study, the VIC (Variable Infiltration Capacity) model at a resolution of 0.05°, which is proven as an ideal model to reflect drought processes, was used as the hydrological model to obtain soil moisture. By analyzing the Soil Moisture Anomaly Percentage Index (SMAPI) error characteristics that were simulated based on different ICs, an uncertainty index for drought process simulation was constructed in different climate zones. It was found that with the development of a drought process, the uncertainty converges, and it decreases to within 10% after a drought occurs for 5 to 6 months, while it is less than 5% in the particular basin in a humid region. In climate transition zones, both the uncertainty and its decrease rate are greater than those in humid regions. Climate characteristics, as well as soil types and vegetation types, are fundamental factors that cause differences in drought process simulation and uncertainty changes. The precipitation and temperature distribution more obviously vary spatially and temporally, a greater uncertainty is caused by ICs. This quantitative method reveals the impact of ICs on drought process simulation in different climate regions and provides a basis for the further improvement of drought simulation and prediction based on atmospheric–hydrological coupling. Full article

(This article belongs to the Special Issue Assessment of Extreme Meteorological and Hydrological Events)

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19 pages, 6569 KiB

Open AccessArticle

Influence of Teleconnection Factors on Extreme Precipitation in Henan Province under Urbanization

by Yuxiang Zhao, Jie Tao, He Li, Qiting Zuo, Yinxing He and Weibing Du

Water 2023, 15(18), 3264; https://doi.org/10.3390/w15183264 - 14 Sep 2023

Cited by 1 | Viewed by 1296

Abstract

Urban extreme precipitation is a typical destructive hydrological event. However, the disaster-causing factors of urban extreme precipitation in Henan Province have rarely been discussed. In this study, daily precipitation data of 11 stations covering a disaster-affected area in “21.7” rainstorm event from 1951 to 2021 and hundreds of climatic indexes set were selected. First, the Granger causality test was adopted to identify the dominant teleconnection factors of extreme precipitation. Then, the effects of teleconnection factors on extreme precipitation in four design frequencies of 10%, 1%, 0.1%, and 0.001% in typical cities of Henan Province were analyzed by using regression and frequency analysis. Finally, the future variation was predicted based on CMIP6. The results show that: (1) The West Pacific 850 mb Trade Wind Index, Antarctic oscillation index, and other factors exert common influence on disaster-affected cities. (2) Teleconnection factors are the dominant force of urban extreme precipitation in most cities (50.3–99.8%), and area of built-up districts, length of roads, area of roads, and botanical garden areas are the key urbanization indicators affecting extreme precipitation. (3) In the future scenarios, the duration and intensity characteristics of urban extreme precipitation will increase, and the growth rate will increase monotonically with the recurrence period. Full article

(This article belongs to the Special Issue Assessment of Extreme Meteorological and Hydrological Events)

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