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Natural Disasters and Extreme Hazards under Changing Climate

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A special issue of Climate (ISSN 2225-1154).

Deadline for manuscript submissions: closed (1 September 2023) | Viewed by 51112

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Dr. Lelys Bravo de Guenni

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Department of Statistics, University of Illinois at Urbana, Champaign, IL, USA
Interests: statistical analysis; statistics; climate; environmental modeling; rainfall probability theory; probabilistic risk analysis
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Dr. Huikyo Lee

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Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Interests: atmospheric sciences; stratospheric dynamics; neural network modeling for satellite remote sensing; atmospheric chemistry; air quality modeling
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Prof. Dr. Wen Cheng Liu

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Department of Civil and Disaster Prevention Engineering, National United University, Miaoli 36063, Taiwan
Interests: hydrology and hydraulics; environmental fluid mechanics; disaster prevention and ecological engineering; contaminant transport modeling; environmental monitoring; climate change
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Dr. Josh Tsun-Hua Yang

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Guest Editor

Department of Civil Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
Interests: hydrometeorological modeling; flood routing; the application of cyber-physical systems and internet of things for disaster mitigation
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Special Issue Information

Dear Colleagues,

Climate change is having a growing influence on weather-related natural hazards. Extreme weather has occurred more frequently in this century than ever before. Climate change, in addition to growing population vulnerability and exposure, is increasing the risk of extreme-weather-related disasters, including droughts, flooding, and heatwaves. Moreover, natural disasters continue to preoccupy society and policymakers, especially in vulnerable regions. These extreme pulses or hazards, when occurring with an intensity or duration above a sustainable threshold, can cause considerable disruptions to livelihoods and socio-economic activities, which might result in long-term structural changes in the capacity for societal recovery.

The impact of climate change on extreme natural hazards will be of interest to readers across various disciplines. This is an issue that threatens the whole society and the future of mankind. Lessons will be learned on managing the risks of extreme events and adapting to climate change.

Dr. Lelys Bravo de Guenni
Dr. Huikyo Lee
Prof. Dr. Wen Cheng Liu
Dr. Josh Tsun-Hua Yang
Guest Editors

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Keywords

climate change
extreme weather
natural disaster
resilience
mitigation

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Published Papers (11 papers)

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Research

Jump to: Review

25 pages, 14366 KiB

Open AccessArticle

Climate Risk and Vulnerability Assessment of Georgian Hydrology under Future Climate Change Scenarios

by Aashutosh Aryal, Rieks Bosch and Venkataraman Lakshmi

Climate 2023, 11(11), 222; https://doi.org/10.3390/cli11110222 - 2 Nov 2023

Cited by 2 | Viewed by 4455

Abstract

The Climate Risk and Vulnerability Assessment (CRVA) is a systematic process used to identify gaps in regional climate adaptation strategies. The CRVA method assesses regional vulnerability, adaptation capacity, exposure, and sensitivity to climate change to support improved adaptation policies. This CRVA study assesses Georgia’s climate exposure, geographic sensitivity, and socio-economic sensitivity by focusing on the impacts of climate change on regional hydrology. The projected change in climate extreme indices, defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), is assessed against the 1961–1990 baseline under future Representative Concentration Pathway (RCP) scenarios. These indices encompass various climate factors such as the maximum daily temperature, warmth duration, total precipitation, heavy and extreme precipitation, maximum 5-day precipitation, and consecutive drought duration. This evaluation helps us understand the potential climate exposure impacts on Georgia. The climate-induced geographic sensitivity is examined based on water stress, drought risk, and changes in soil productivity using the Normalized Difference Vegetation Index (NDVI). The climate-induced socio-economic sensitivity is determined using the Gross Domestic Product per capita (GDP), Human Development Index, Education Index, and population density. The highest vulnerability to climate change was found in the Kakheti and Kvemo Kartli regions, with the vulnerability index values ranging from 6 to 15, followed by Mtskheta-Mtianeti, Samtskhe–Javakheti, and Shida Kartli with vulnerability index values ranging from 2 to 8. The location of these regions upstream of the Alazani-Iori, Khrami-Debeda, and Mktvari river basins indicates that the country’s water resources are vulnerable to climate change impacts in the future under the RCP 4.5 and 8.5 scenarios. Full article

(This article belongs to the Special Issue Natural Disasters and Extreme Hazards under Changing Climate)

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25 pages, 13004 KiB

Open AccessArticle

Disaster Risk, Climate Change, and Urbanization as Research Topics in Western Asia—A Bibliometric Literature Analysis

by Alexander Fekete

Climate 2023, 11(6), 131; https://doi.org/10.3390/cli11060131 - 17 Jun 2023

Cited by 4 | Viewed by 3060

Abstract

Scientifically analyzing and documenting climate change and related disaster risks is demanded by international organizations such as the United Nations. However, global or national studies predominate, and cross-regional overviews are lacking, especially for Western Asia. In four countries in the region, Iran, Israel, Saudi Arabia, and Turkey, transport accidents, floods, fires, and earthquakes are the predominant accidents and disasters in the Emergency Events Database (EM-DAT). The result is different when analyzing the scientific publications via a bibliometric literature analysis using VOS viewer and the Web of Science, and earthquakes, climate change, COVID-19, and terrorism dominate here. Governance and management are also an important and recurring cluster topic. The conceptual components of vulnerability and resilience are discussed in most countries. The hazards are often associated with specific concepts and quantitative methods. GIS and remote sensing as specific methodologies also often appear in a cluster. Further clusters derived from the keyword search include floods and droughts, food security and agriculture, and posttraumatic stress and psychological aspects. The results help us to identify countries with a rich literature on certain hazards and gaps in relation to other types of disasters, which are more prevalent. The findings can help scientists and policymakers to support future studies based on either high or low research coverage. Full article

(This article belongs to the Special Issue Natural Disasters and Extreme Hazards under Changing Climate)

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15 pages, 3514 KiB

Open AccessArticle

Brief Overview of Greek Fir Radial Growth in Response to Climate and European Fir Budworm: Three Case Studies from Giona Mountain, Central Greece

by Panagiotis P. Koulelis and Panos V. Petrakis

Climate 2023, 11(4), 78; https://doi.org/10.3390/cli11040078 - 31 Mar 2023

Cited by 2 | Viewed by 2383

Abstract

Tree rings provide an invaluable insight into how trees adapt to changes in climate. This study presents aggregated results, from our research on tree rings, climatic response and the insect Choristoneura murinana infestations from three studies on Greek fir, located in stands across Central Greece and Giona Mountain on three different altitudes. In our studies, was found that extreme droughts and wet events had a negative or positive effect on fir growth, respectively. April’s precipitation had a positive correlation with growth for all the stands, which supports other authors’ findings. Moreover, the average maximum temperature of the growing season and the maximum temperature of April, July and August were also linked to growth. Evapotranspiration during the growing season was seen to be inversely proportional to the growth of fir. An apparent decline in tree ring growth more severe in stand 3 (Average Tree Ring Width Index, ARWI < 0.6) has been observed, particularly in recent years. The data suggests that temperature is having a detrimental effect on fir growth in the area, with a significant decreasing tendency in growth from 1993 for the high altitude stands and from 1998 for the lower altitude stand. To ensure successful and sustainable forest management in the future, more research into tree rings and their relationship with climate must be carried out. Full article

(This article belongs to the Special Issue Natural Disasters and Extreme Hazards under Changing Climate)

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13 pages, 261 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

by Norma F. Kanarek, Qi Wang, Tak Igusa, Tara Kirk Sell, Zachary Anthony Cox, James M. Kendra and Jonathan Links

Climate 2022, 10(11), 159; https://doi.org/10.3390/cli10110159 - 23 Oct 2022

Cited by 1 | Viewed by 1984

Abstract

Objective: Understanding long-term disaster effects is key to building theories of recovery and informing policymaking. Findings regarding long-term recovery are inconsistent, with some scholars finding that disasters have little long-term impact, and others asserting otherwise. To assist in resolving this discord, we apply a conceptual framework and computational model of community resilience (“COPEWELL”) that places community functioning (CF) at the center of evaluating the effects of disaster over time. Using flooding as a disaster type, we hypothesize a change in baseline CF trend when a flood-related federally declared disaster event occurs. Methods: We used county-level flood-related federally declared disaster events (2010–2014) and selected population demographics to study their effects on annual CF trends among United States counties (N = 3141). Results: In multivariate analysis of baseline CF, we found a significant negative relationship of prior five-year flood status, federal regions relative to the Northeast (Region I), lower total earnings, and greater population size. Annual CF trend was 0.09% (95%CI: 0.01%–0.16%). In multivariate analysis, significant predictors included baseline CF (β = −0.0178, −0.0047–−0.0309), any concurrent flood-related federally declared disaster events (−0.0024, −0.0040–−0.0008), ten-year prior flood events (−0.0017, −0.0034–−0.0000) and concurrent population change (−0.0186, −0.0338–−0.0035). Conclusions: Recent floods depress baseline CF, while concurrent and ten-year-ago floods depress trend in CF. Resilience may potentially be modified by raising baseline CF and maintaining population over time. Full article

(This article belongs to the Special Issue Natural Disasters and Extreme Hazards under Changing Climate)

29 pages, 12055 KiB

Open AccessArticle

Contribution to the Study of Forest Fires in Semi-Arid Regions with the Use of Canadian Fire Weather Index Application in Greece

by Nikolaos Ntinopoulos, Marios Spiliotopoulos, Lampros Vasiliades and Nikitas Mylopoulos

Climate 2022, 10(10), 143; https://doi.org/10.3390/cli10100143 - 30 Sep 2022

Cited by 8 | Viewed by 3408

Abstract

Forest fires are of critical importance in the Mediterranean region. Fire weather indices are meteorological indices that produce information about the impact as well as the characteristics of a fire event in an ecosystem and have been developed for that reason. This study explores the spatiotemporal patterns of the FWI system within a study area defined by the boundaries of the Greek state. The FWI has been calculated and studied for current and future periods using data from the CFSR reanalysis model from the National Centers for Environmental Protection (NCEP) as well as data from NASA satellite programs and the European Commission for Medium-Range Weather Forecasts (ECWMF) in the form of netCDF files. The calculation and processing of the results were conducted in the Python programming language, and additional drought- and fire-related indices were calculated, such as the standardized precipitation index (SPI), number of consecutive 50-day dry periods (Dry50), the Fosberg fire weather index (FFWI), the days where the FWI exceeds values of 40 and 50 days (FWI > 40) and (days FWI > 50). Similar patterns can easily be noted for all indices that seem to have their higher values concentrated in the southeast of the country owing to the higher temperatures and more frequent drought events that affect the indices’ behavior in both the current and future periods. Full article

(This article belongs to the Special Issue Natural Disasters and Extreme Hazards under Changing Climate)

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20 pages, 3124 KiB

Open AccessArticle

Intensity, Duration and Spatial Coverage of Aridity during Meteorological Drought Years over Northeast Thailand

by Tenanile Dlamini, Veeranun Songsom, Werapong Koedsin and Raymond J. Ritchie

Climate 2022, 10(10), 137; https://doi.org/10.3390/cli10100137 - 23 Sep 2022

Cited by 6 | Viewed by 3031

Abstract

Gaps in drought monitoring result in insufficient preparation measures for vulnerable areas. This paper employed the standardized precipitation index (SPI) to identify meteorological drought years and the Thornthwaite aridity index (TAI) to evaluate aridity in three provinces of northeast Thailand growing cassava and sugarcane at massive scales. Precipitation and temperature data were sourced from Global Land Data Assimilation System-2 (GLDAS-2) Noah Model products at 0.25 degree resolution and used for calculating the drought indices. This study was conducted for the period of 2004 to 2015. The SPI was computed for 1, 3 and 6 months scales to measure short- to medium-term moisture. The results indicated major meteorological drought years as 2004, 2005, 2010, 2012, 2014 and 2015. A range of 1 to 3 months of extreme rainfall shortage was experienced during each of these years, including the growing season of 2004, 2012 and 2015. TAI-based results indicated that the area experiences an average of 7 to 8 months of aridity during drought periods, compared to the historical overall average of 6 months. The spatial TAI for the major drought years indicated delayed onset, intermittency or early cut-off of the rainy season. The year 2004 was the most intense in terms of aridity. The longest duration of aridness for some areas was between 9 and 10 months in 2012 and 2014, respectively. In terms of spatial coverage, all meteorological drought years had out-of-season aridity. Based on the region’s historical records, this highlighted an increase in the frequency of droughts and duration of aridity. A disturbance in the growing season has the potential to affect crop yields, hence, the need to improve and strengthen existing adaptive measures for agriculture as the main source of food and income in the northeast. Full article

(This article belongs to the Special Issue Natural Disasters and Extreme Hazards under Changing Climate)

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16 pages, 3738 KiB

Open AccessEditor’s ChoiceArticle

Compound Extremes of Air Temperature and Precipitation in Eastern Europe

by Elena Vyshkvarkova and Olga Sukhonos

Climate 2022, 10(9), 133; https://doi.org/10.3390/cli10090133 - 5 Sep 2022

Cited by 14 | Viewed by 3279

Abstract

The spatial distribution of compound extremes of air temperature and precipitation was studied over the territory of Eastern Europe for the period 1950–2018. Using daily data on air temperature and precipitation, we calculated the frequency and trends of the four indices—cold/dry (CD), cold/wet (CW), warm/dry (WD) and warm/wet (WW). The connection between these indices and large-scale patterns in the ocean–atmosphere system, such as the North Atlantic Oscillation (NAO), the East Atlantic (EA) and Scandinavia (SCAND) patterns, was also studied. The positive and statistically significant trends in the region were observed for the warm extremes (especially the WW index) in all seasons, with maximum values in the winter season, while negative trends were obtained for the cold extremes. The NAO index has a strong positive and statistically significant correlation with the warm compound indices (WD and WW) in the northern part of Eastern Europe in winter like the EA pattern, but with smaller values. The spatial distribution of the correlation coefficients between compound extremes and the SCAND index in the winter season is opposite to the correlation coefficients with the NAO index. Full article

(This article belongs to the Special Issue Natural Disasters and Extreme Hazards under Changing Climate)

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12 pages, 2390 KiB

Open AccessArticle

Climate-Induced Fire Hazard in Forests in the Volga Federal District of European Russia during 1992–2020

by Yuri Perevedentsev, Boris Sherstyukov, Artyom Gusarov, Timur Aukhadeev and Nadezhda Mirsaeva

Climate 2022, 10(7), 110; https://doi.org/10.3390/cli10070110 - 18 Jul 2022

Cited by 3 | Viewed by 2330

Abstract

This paper shows the relevance of the problem of fire hazard in the forests of the Volga Federal District (VFD) of European Russia. The Nesterov index and the Selyaninov hydrothermal coefficient (HTC) are considered as indicators of fire hazard. The changes in climatic conditions in the VFD during 1955–2018 are shown; a trend towards warming and an increase in aridity in the study region were revealed. The repeatability of various fire hazard classes from May to September was calculated using the Nesterov method. It is shown that in July, the most dangerous situation was in the south of the VFD, where the repeatability of class IV fire hazard reached 27%. Using the HTC index, the degree of aridity of the district in the summer period was estimated. The frequency of the most arid conditions (HTC < 0.5) increases from the north to the south of the district, from 6% (Kirov Region) to 47% (Orenburg Region). Using the TT index, the potential thunderstorm danger in the VFD was assessed. With the help of the constructed maps, the hotspots of the most probable occurrence of thunderstorms were detected. The use of Rosstat data on the number of forest fires from 1992 to 2020 made it possible to consider the spatiotemporal distribution of forest fires in 14 administrative regions of the VFD. The distribution of the number of fires by the regions is shown depending on their forest cover and season. The peak of the number of fires was revealed in 2010, when the entire territory of the study region was covered by a severe drought, as a result of which the area of forests covered by fire increased many times over. In recent years (since 2017), there has been an increase in the area of burned forest due to the active phase of climate warming. Full article

(This article belongs to the Special Issue Natural Disasters and Extreme Hazards under Changing Climate)

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Review

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17 pages, 2992 KiB

Open AccessReview

Comprehensive Review: Advancements in Rainfall-Runoff Modelling for Flood Mitigation

by Muhammad Jehanzaib, Muhammad Ajmal, Mohammed Achite and Tae-Woong Kim

Climate 2022, 10(10), 147; https://doi.org/10.3390/cli10100147 - 10 Oct 2022

Cited by 39 | Viewed by 11592

Abstract

Runoff plays an essential part in the hydrological cycle, as it regulates the quantity of water which flows into streams and returns surplus water into the oceans. Runoff modelling may assist in understanding, controlling, and monitoring the quality and amount of water resources. The aim of this article is to discuss various categories of rainfall–runoff models, recent developments, and challenges of rainfall–runoff models in flood prediction in the modern era. Rainfall–runoff models are classified into conceptual, empirical, and physical process-based models depending upon the framework and spatial processing of their algorithms. Well-known runoff models which belong to these categories include the Soil Conservation Service Curve Number (SCS-CN) model, Storm Water Management model (SWMM), Hydrologiska Byråns Vattenbalansavdelning (HBV) model, Soil and Water Assessment Tool (SWAT) model, and the Variable Infiltration Capacity (VIC) model, etc. In addition, the data-driven models such as Adaptive Neuro Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN), Deep Neural Network (DNN), and Support Vector Machine (SVM) have proven to be better performance solutions in runoff modelling and flood prediction in recent decades. The data-driven models detect the best relationship based on the input data series and the output in order to model the runoff process. Finally, the strengths and downsides of the outlined models in terms of understanding variation in runoff modelling and flood prediction were discussed. The findings of this comprehensive study suggested that hybrid models for runoff modeling and flood prediction should be developed by combining the strengths of traditional models and machine learning methods. This article suggests future research initiatives that could help with filling existing gaps in rainfall–runoff research and will also assist hydrological scientists in selecting appropriate rainfall–runoff models for flood prediction and mitigation based on their benefits and drawbacks. Full article

(This article belongs to the Special Issue Natural Disasters and Extreme Hazards under Changing Climate)

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21 pages, 1018 KiB

Open AccessReview

Effectiveness of Drought Indices in the Assessment of Different Types of Droughts, Managing and Mitigating Their Effects

by Jean Marie Ndayiragije and Fan Li

Climate 2022, 10(9), 125; https://doi.org/10.3390/cli10090125 - 25 Aug 2022

Cited by 21 | Viewed by 8640

Abstract

Droughts are the most destructive catastrophes in the world. The persistence of drought is considered to cause many challenges for both humans and animals and ruins the ecosystem. These challenges have encouraged scientists to search for innovative methods and models that are effective for assessing and predicting drought events. The use of drought indices has been extensively employed in many regions across the globe and their effectiveness demonstrated. This review illustrates the effectiveness of drought indices in the assessment of droughts, with a focus on drought management and mitigation measures. Additionally, several ways of managing drought risk and proactive strategies that need to be implemented to mitigate droughts have been illustrated. In conclusion, this article suggests that drought mitigation should be done more naturally, in ways that strongly protect the environment rather than involve engineering projects which might cause the degradation of rivers and land, and damage the ecosystem. Full article

(This article belongs to the Special Issue Natural Disasters and Extreme Hazards under Changing Climate)

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15 pages, 692 KiB

Open AccessReview

Risks to the Health of Russian Population from Floods and Droughts in 2010–2020: A Scoping Review

by Elena A. Grigorieva and Alexandra S. Livenets

Climate 2022, 10(3), 37; https://doi.org/10.3390/cli10030037 - 6 Mar 2022

Cited by 20 | Viewed by 5347

Abstract

Climate change and natural disasters caused by hydrological, meteorological, and climatic causes have a significant and increasing direct and indirect impact on human health, leading to increased mortality and morbidity. Russia is a country that suffers from frequent climatic and weather disasters. This is mainly due to its vast territory, complex geographical and ecological environment, and widely varying climatic conditions. This review provides information on climatological and hydrological extremes in Russia in 2010–2020, floods and droughts, and their impact on the health and well-being of the country’s population. A literature search was conducted using electronic databases Web of Science, Pubmed, Science Direct, Scopus, and e-Library, focusing on peer-reviewed journal articles published in English and in Russian from 2010 to 2021. Four conceptual categories were used: “floods”, “droughts”, “human health”, and “Russia”. It is concluded that while most hazardous weather events cannot be completely avoided, many health impacts can potentially be prevented. The recommended measures include early warning systems and public health preparedness and response measures, building climate resilient health systems and other management structures. Full article

(This article belongs to the Special Issue Natural Disasters and Extreme Hazards under Changing Climate)

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