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Climate Extremes: Human-Environment Consequences and Adaptation Measures：Volume II
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Climate Extremes: Human-Environment Consequences and Adaptation Measures：Volume II

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

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 15455

Special Issue Editor

Dr. Alban Kuriqi

E-Mail Website
Guest Editor
CERIS—Civil Engineering Research and Innovation for Sustainability, Instituto Superior Tecnico, University of Lisbon. Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal
Interests: renewable energy; hydropower impacts; water management; ecohydrology; ecohydraulic; river restoration; climate change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Climate change due to global warming is no longer a modeling assumption but something that is happening and affecting our lives in different aspects. Climate change affects the temporal and spatial variability of meteorological components, such as precipitation and temperature, and alters the hydrologic cycle, i.e., evapotranspiration, runoff, flow discharge in rivers, and groundwater budget, at different levels. These meteorohydrological alterations result in extreme events such as floods and droughts, which in turn lead to numerous devastating consequences for the environment and humans. Flushing away entire settlements, wildfires, agriculture droughts, and hydrologic droughts impairing society and the ecosystem at different trophic levels are some of the most common consequences. Both flood and drought event frequency has been continuously increasing in recent decades. Therefore, it is imperative to improve our knowledge of management and adaptation measure policies. This Special Issue aims in particular to stimulate interdisciplinary research among different fields such as economics, hydrology, integrated water resource management and transboundary water cooperation, integrated flood and drought risk management, geology, geotechnics, natural hazard policies and legislation, sociology, geography, and their interactions in different regions of the world. Moreover, this Special Issue aims to generate cutting-edge knowledge, methods, and procedures for extreme event management. Innovative measures to mitigate and adapt to the effects of extreme events are essential, in particular, in sensitive areas. A better understanding of extreme event mechanisms is essential to obtain strategically relevant information that supports correct decision-making and implementation of appropriate environmental adaptation and/or protection measures. In a broad view, interesting topics include but are not limited to floods, landslides, meteorological droughts, hydrological droughts, agriculture droughts, wildfires, several other climate-related hazards like typhoons/cyclones/hurricanes, heatwaves, and most importantly adaptation measures related to respective extremes. Thus, it is the right moment to focus on new research areas that link sustainable development, climate change, and disaster risks.

Dr. Alban Kuriqi
Guest Editor

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. Climate 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 1800 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

  • floods
  • droughts
  • landslides
  • debris flows
  • wildfires
  • ecology
  • water resource
  • urban flooding
  • urban stormwater
  • urban hydrological modeling
  • climate change drivers
  • climate change adaptation
  • the resilience of agricultural production
  • adaptation measures
  • mitigation measures
  • hydrology

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Published Papers (5 papers)

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Research

22 pages, 7640 KiB  
Article
Wetland Water Level Prediction Using Artificial Neural Networks—A Case Study in the Colombo Flood Detention Area, Sri Lanka
by Tharaka Jayathilake, Ranjan Sarukkalige, Yukinobu Hoshino and Upaka Rathnayake
Climate 2023, 11(1), 1; https://doi.org/10.3390/cli11010001 - 21 Dec 2022
Cited by 6 | Viewed by 2803
Abstract
Historically, wetlands have not been given much attention in terms of their value due to the general public being unaware. Nevertheless, wetlands are still threatened by many anthropogenic activities, in addition to ongoing climate change. With these recent developments, water level prediction of [...] Read more.
Historically, wetlands have not been given much attention in terms of their value due to the general public being unaware. Nevertheless, wetlands are still threatened by many anthropogenic activities, in addition to ongoing climate change. With these recent developments, water level prediction of wetlands has become an important task in order to identify potential environmental damage and for the sustainable management of wetlands. Therefore, this study identified a reliable neural network model by which to predict wetland water levels over the Colombo flood detention area, Sri Lanka. This is the first study conducted using machine learning techniques in wetland water level predictions in Sri Lanka. The model was developed with independent meteorological variables, including rainfall, evaporation, temperature, relative humidity, and wind speed. The water levels measurements of previous years were used as dependent variables, and the analysis was based on a seasonal timescale. Two neural network training algorithms, the Levenberg Marquardt algorithm (LM) and the Scaled Conjugate algorithm (SG), were used to model the nonlinear relationship, while the Mean Squared Error (MSE) and Coefficient of Correlation (CC) were used as the performance indices by which to understand the robustness of the model. In addition, uncertainty analysis was carried out using d-factor simulations. The performance indicators showed that the LM algorithm produced better results by which to model the wetland water level ahead of the SC algorithm, with a mean squared error of 0.0002 and a coefficient of correlation of 0.99. In addition, the computational efficiencies were excellent in the LM algorithm compared to the SC algorithm in terms of the prediction of water levels. LM showcased 3–5 epochs, whereas SC showcased 34–50 epochs of computational efficiencies for all four seasonal predictions. However, the d-factor showcased that the results were not within the cluster of uncertainty. Therefore, the overall results suggest that the Artificial Neural Network can be successfully used to predict the wetland water levels, which is immensely important in the management and conservation of the wetlands. Full article
(This article belongs to the Special Issue Climate Extremes: Human-Environment Consequences and Adaptation Measures：Volume II)
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21 pages, 9808 KiB  
Article
Contemporary Climate Change and Its Hydrological Consequence in the Volga Federal District, European Russia
by Yuri Perevedentsev, Artyom Gusarov, Nadezhda Mirsaeva, Boris Sherstyukov, Konstantin Shantalinsky, Vladimir Guryanov and Timur Aukhadeev
Climate 2022, 10(12), 198; https://doi.org/10.3390/cli10120198 - 12 Dec 2022
Cited by 1 | Viewed by 1984
Abstract
An analysis of spatiotemporal variability of air temperature and precipitation in the Volga Federal District (European Russia) between 1966 and 2021 was carried out. Based on data from 20 meteorological stations, relatively evenly located on the territory under consideration, the spatial distribution of [...] Read more.
An analysis of spatiotemporal variability of air temperature and precipitation in the Volga Federal District (European Russia) between 1966 and 2021 was carried out. Based on data from 20 meteorological stations, relatively evenly located on the territory under consideration, the spatial distribution of average monthly and average annual air temperatures and monthly and annual precipitation was assessed; some indicators of the temporal variability of these variables in the period under consideration were calculated and analyzed. It was revealed that throughout the Volga Federal District, there was a tendency of climate warming in all months, and a slight increase in annual precipitation, except for the southeast of the district, where the precipitation trend was negative. It is noted that in the period 1955–1998, the number of negative air temperature anomalies was approximately equal to the number of positive ones; however, in the later period 1999–2021, the number of positive anomalies significantly exceeded the number of negative ones. Based on reanalysis data, climatic maps of vaporization and runoff in the Volga Federal District during 1966–2021 were created. The dependence of air temperature fluctuations on the nature of atmospheric circulation was revealed using the NAO, AO, and SCAND indices. On the example of the central part of the district (Republic of Tatarstan), some increase in summer aridity of the climate was revealed by using Budyko’s dryness index, Selyaninov’s hydrothermal coefficient, and Sapozhnikov’s humidification coefficient. The indicators of runoff and evaporation were also calculated using the methods of Schreiber and Ivanov. Against the background of the positive trend in vaporization rates, favorable conditions for a decrease in runoff were noted. Full article
(This article belongs to the Special Issue Climate Extremes: Human-Environment Consequences and Adaptation Measures：Volume II)
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25 pages, 2977 KiB  
Article
A Proposed Approach towards Quantifying the Resilience of Water Systems to the Potential Climate Change in the Lali Region, Southwest Iran
by Nejat Zeydalinejad, Hamid Reza Nassery, Farshad Alijani, Alireza Shakiba and Babak Ghazi
Climate 2022, 10(11), 182; https://doi.org/10.3390/cli10110182 - 19 Nov 2022
Cited by 7 | Viewed by 2174
Abstract
Computing the resilience of water resources, especially groundwater, has hitherto presented difficulties. This study highlights the calculation of the resilience of water resources in the small-scale Lali region, southwest Iran, to potential climate change in the base (1961–1990) and future (2021–2050) time periods [...] Read more.
Computing the resilience of water resources, especially groundwater, has hitherto presented difficulties. This study highlights the calculation of the resilience of water resources in the small-scale Lali region, southwest Iran, to potential climate change in the base (1961–1990) and future (2021–2050) time periods under two Representative Concentration Pathways, i.e., RCP4.5 and RCP8.5. The Lali region is eminently suitable for comparing the resilience of alluvial groundwater (Pali aquifer), karst groundwater (Bibitarkhoun spring and the observation wells W1, W2 and W3) and surface water (Taraz-Harkesh stream). The log-normal distribution of the mean annual groundwater level and discharge rate of the water resources was initially calculated. Subsequently, different conditions from extremely dry to extremely wet were assigned to the different years for every water system. Finally, the resilience values of the water systems were quantified as a number between zero and one, such that they can be explicitly compared. The Pali alluvial aquifer demonstrated the maximum resilience, i.e., 1, to the future climate change. The Taraz-Harkesh stream, which is fed by the alluvial aquifer and the Bibitarkhoun karst spring, which is the largest spring of the Lali region, depicted average resilience of 0.79 and 0.59, respectively. Regarding the karstic observation wells, W1 being located in the recharge zone had the lowest resilience (i.e., 0.52), W3 being located in the discharge zone had the most resilience (i.e., 1) and W2 being located between W1 and W3 had an intermediate resilience (i.e., 0.60) to future climate change. Full article
(This article belongs to the Special Issue Climate Extremes: Human-Environment Consequences and Adaptation Measures：Volume II)
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16 pages, 4673 KiB  
Article
Assessing the Adaptive Capacity of Slum Households to Flooding in the Coastline of Portee and Rokupa, Freetown, Sierra Leone
by Bashiru Turay
Climate 2022, 10(11), 181; https://doi.org/10.3390/cli10110181 - 19 Nov 2022
Cited by 2 | Viewed by 3007
Abstract
Frequent flooding has been a significant problem in Freetown, causing loss of lives and properties. The situation is worse for coastal residents, who are more vulnerable and exposed to the impacts. The government has made commitments to strengthen resilience and adaptive capacity by [...] Read more.
Frequent flooding has been a significant problem in Freetown, causing loss of lives and properties. The situation is worse for coastal residents, who are more vulnerable and exposed to the impacts. The government has made commitments to strengthen resilience and adaptive capacity by 2030. However, there is currently insufficient information to comprehend the coastal residents of Portee and Rokupa’s capacity to adapt to the yearly flooding to which they are subjected. This study aims to assess the adaptive capacity of 204 slum households selected by purposive sampling and using the local adaptive capacity framework. The results show that the widespread adaptive concerns are unflood-proofed housing; low membership in community-based organizations; and the lack of innovative, flexible and forward-looking flood management initiatives. This study argues that the inhabitants have reached their adaptation limit and are now fated to more loss and damage. The author recommends future studies to forecast the assets in the study location that will potentially be affected by different flood intensities when subjected to future climate change scenarios. Full article
(This article belongs to the Special Issue Climate Extremes: Human-Environment Consequences and Adaptation Measures：Volume II)
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15 pages, 9278 KiB  
Article
Climate Change and the Caribbean: Challenges and Vulnerabilities in Building Resilience to Tropical Cyclones
by Clint T. Lewis
Climate 2022, 10(11), 178; https://doi.org/10.3390/cli10110178 - 18 Nov 2022
Cited by 4 | Viewed by 4587
Abstract
Caribbean Small Island Developing States (SIDS) is one of the most vulnerable regions in the world to the impacts of climate change. The region has prioritized adaptation to climate change and has implemented many adaptation actions over the past 20 years. However, the [...] Read more.
Caribbean Small Island Developing States (SIDS) is one of the most vulnerable regions in the world to the impacts of climate change. The region has prioritized adaptation to climate change and has implemented many adaptation actions over the past 20 years. However, the region is becoming increasingly vulnerable to the impacts of tropical cyclones (TC). This paper analyses the impacts of TC on the region between 1980 to 2019. It aims to examine the economic loss and damage sustained by the region, identify the sectors most impacted, and ascertain the perspectives of key stakeholders on the factors that hinder building resilience. Statistical analysis techniques and semi-structured interviews were to unpack and understand the dataset. The paper finds that economic loss and damage has gradually increasing between 1980 to 2009 with a drastic increase between 2010 to 2019. The paper highlights the agriculture, housing, transport, and utility sectors as the most impacted. The findings also call to attention the need for increased access to adaptation financing for SIDS, the disadvantages of the income status that hinders building resilience, and the need for increased Early Warning Systems. The paper recommends revising the per capita national income as an eligibility criterion for accessing concessional development finance assistance, a comprehensive EWS for the countries in the region, and consideration of debt relief for countries affected by TC. Full article
(This article belongs to the Special Issue Climate Extremes: Human-Environment Consequences and Adaptation Measures：Volume II)
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