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The Water Cycle and Climate Change (3rd Edition)
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The Water Cycle and Climate Change (3rd Edition)

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: 15 July 2025 | Viewed by 8164

Special Issue Editor

Dr. Yuqing Zhang

E-Mail Website
Guest Editor
School of Geography and Planning, Huaiyin Normal University, Huai’an 223300, China
Interests: climate change; compound meteohydrological extremes; heat waves; droughts; model simulations
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is the third volume in a series of publications dedicated to “The Water Cycle and Climate Change” (https://www.mdpi.com/journal/atmosphere/special_issues/Water_Cycle_Climate), and “The Water Cycle and Climate Change (2nd Edition)” (https://www.mdpi.com/journal/atmosphere/special_issues/J168Z34NR4)

A warmer climate will intensify the global and regional water cycle, leading to significant changes in precipitation, evapotranspiration, streamflow, and water storage. For example, global warming can cause the redistribution of global and regional water resources on spatial and temporal scales. This redistribution may further increase precipitation variability (precipitation whiplash events), and can thus exacerbate extreme conditions (e.g., more droughts or floods). Assessing water cycle characteristics in the context of climate change has important implications for global and regional water resource management and food security. However, the assessments and mechanisms of climate warming on hydro-climatic extreme events certainly need to be deepened and expanded, especially for compound weather and climate extremes, which represent combinations of multiple drivers and/or hazards, amplifying disproportionate impacts on natural environments and the social economy compared to individual extremes. Therefore, it is important and necessary to quantify the impacts of climate change, as well as other anthropogenic factors, on the water cycle, such as streamflow, evapotranspiration, floods, and droughts.

This Special Issue provides a platform for studying the water cycle and its response to climate change, especially hydrometeorological extremes (e.g., individual, concurrent, and compound hydro-climatic extreme events). We sincerely invite researchers to contribute the latest research on the water cycle and climate change. We encourage the submission of research manuscripts which focus on, but are not limited to, the discussion of the following topics:

(1) Contributions of climate change to the water cycle.
(2) Impacts of climate change on hydroclimatic extremes.
(3) Identification and mechanisms of compound extreme hydroclimatic events.
(4) Model simulations of hydro-climatic extreme events.
(5) Historical assessments and future projections of hydrometeorological extremes.
(6) Socio-economic impacts of extreme hydrometeorological events under water cycle anomalies.

Dr. Yuqing Zhang
Guest Editor

Manuscript Submission Information

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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. Atmosphere 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 2400 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

  • climate change
  • hydrometeorological extremes
  • compound weather and climate extremes
  • model simulations
  • drought and flood
  • spatio-temporal patterns

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Published Papers (9 papers)

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Research

12 pages, 2013 KiB  
Article
A New Approach to Estimating the Sensible Heat Flux in Bare Soils
by Francesc Castellví and Nurit Agam
Atmosphere 2025, 16(4), 458; https://doi.org/10.3390/atmos16040458 - 16 Apr 2025
Viewed by 192
Abstract
The estimation of sensible heat flux (H) in drylands is important because it constitutes a significant portion of the net available surface energy. A model to estimate H half-hourly measurements for bare soils was derived by combining the surface renewal (SR) theory and [...] Read more.
The estimation of sensible heat flux (H) in drylands is important because it constitutes a significant portion of the net available surface energy. A model to estimate H half-hourly measurements for bare soils was derived by combining the surface renewal (SR) theory and the Monin–Obukhov similarity theory (MOST), involving the land surface temperature (LST), wind speed, and the air temperature in a period of half an hour, HSR-LST. The surface roughness lengths for momentum (zom) and for heat (z0h) were estimated at neutral conditions. The dataset included dry climates and different measurement heights (1.5 m up to 20 m). Root mean square error (RMSE) over the mean actual sensible heat flux estimate (HEC), E =RMSEHEC¯100%, was considered excellent, good, and moderate for E values of up to 25%, 35%, and 40%, respectively. In stable conditions, HSR-LST and HMOST values were comparable and both were unacceptable (E > 40%). However, the RMSE using HSR-LST ranged between 8 Wm2 and 12 Wm2 and performed slightly better than HMOST. In unstable conditions, HSR-LST was in excellent, good, and moderate agreement in 3, 6, and 5 cases, respectively; HMOST was good in 3 cases; and the remaining 11 cases were intolerable because they required site-specific calibration. Full article
(This article belongs to the Special Issue The Water Cycle and Climate Change (3rd Edition))
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17 pages, 5745 KiB  
Article
The Impact of Climate Change on the Functioning of Drainage Systems in Industrial Areas—A Case Study
by Katarzyna Wartalska, Szymon Szymczewski, Weronika Domalewska, Marcin Wdowikowski, Kornelia Przestrzelska, Andrzej Kotowski and Bartosz Kaźmierczak
Atmosphere 2025, 16(3), 347; https://doi.org/10.3390/atmos16030347 - 20 Mar 2025
Viewed by 359
Abstract
Stormwater drainage from urbanised areas has gained importance due to progressing land surface sealing and climate change. More frequent extreme rainfall events lead to overloaded drainage systems and flash floods, particularly in industrial zones experiencing rapid development. The study analysed the sewage system [...] Read more.
Stormwater drainage from urbanised areas has gained importance due to progressing land surface sealing and climate change. More frequent extreme rainfall events lead to overloaded drainage systems and flash floods, particularly in industrial zones experiencing rapid development. The study analysed the sewage system operation in the Special Economic Zone (SEZ) in Lower Silesia, Poland to assess the impact of climate-induced rainfall changes. Three rainfall scenarios were used: model rainfall using historic rainfall intensities, model rainfall using actual intensities, and real precipitation recorded in June 2022. Findings indicate that climate change has negatively affected the stormwater drainage system, resulting in increased overloads and flooding. Particularly, the II scenario showed a significant rise in rainwater inflow to retention reservoirs by 53.1% for ZR-1 and 44.5% for ZR-2 (compared to the I scenario). To address these issues, adaptations are needed for increased rainwater flows, including additional retention facilities, blue–green infrastructure, or rainwater harvesting for the SEZ needs. Full article
(This article belongs to the Special Issue The Water Cycle and Climate Change (3rd Edition))
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18 pages, 10834 KiB  
Article
Spatio-Temporal Analysis of Changes in the Iranian Summer Subtropical High-Pressure System from a Climate Change Perspective
by Mokhtar Fatahian, Zahra Hejazizadeh, Ali Reza Karbalaee, Hamed Shahidinia and Junye Wang
Atmosphere 2025, 16(3), 273; https://doi.org/10.3390/atmos16030273 - 26 Feb 2025
Viewed by 578
Abstract
Climate change plays a significant role in altering the behavior of large-scale atmospheric systems, particularly the subtropical high-pressure systems relevant to the climate of Iran. This study investigates the impact of climate change on the subtropical high-pressure system over Iran by utilizing ERA5 [...] Read more.
Climate change plays a significant role in altering the behavior of large-scale atmospheric systems, particularly the subtropical high-pressure systems relevant to the climate of Iran. This study investigates the impact of climate change on the subtropical high-pressure system over Iran by utilizing ERA5 reanalysis data and CORDEX projections. Focusing on future projections (2022–2063) under RCP4.5 and RCP8.5 scenarios, the analysis reveals substantial shifts in the position and intensity of the subtropical high when comparing the high-pressure center between currently observed data and the projected scenarios. The center of the high-pressure system exhibits a northward migration, particularly pronounced in August; a consistent upward trend in geopotential height, analyzed using the Kendall trend method, is observed, indicating a strengthening of the high-pressure system. This intensification leads to a westward and northward expansion of the summer high-pressure cell. Consequently, this study anticipates the emergence of more pronounced cyclonic circulations at higher latitudes (>38° N) in the future. These findings suggest that climate change will substantially alter the behavior of the subtropical high over Iran, impacting regional weather patterns and potentially leading to climate anomalies. Full article
(This article belongs to the Special Issue The Water Cycle and Climate Change (3rd Edition))
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18 pages, 2906 KiB  
Article
Integration of Deep Learning Neural Networks and Feature-Extracted Approach for Estimating Future Regional Precipitation
by Shiu-Shin Lin, Kai-Yang Zhu and He-Yang Huang
Atmosphere 2025, 16(2), 165; https://doi.org/10.3390/atmos16020165 - 31 Jan 2025
Viewed by 593
Abstract
This study proposes a deep neural network (DNN) as a downscaling framework with nonlinear features extracted by kernel principal component analysis (KPCA). KPCA utilizes kernel functions to extract nonlinear features from the source climatic data, reducing dimensionality and denoising. DNN is used to [...] Read more.
This study proposes a deep neural network (DNN) as a downscaling framework with nonlinear features extracted by kernel principal component analysis (KPCA). KPCA utilizes kernel functions to extract nonlinear features from the source climatic data, reducing dimensionality and denoising. DNN is used to learn the nonlinear and complex relationships among the features extracted by KPCA to predict future regional rainfall patterns and trends in complex island terrain in Taiwan. This study takes Taichung and Hualien, on both the eastern and western sides of Taiwan’s Central Mountain Range, as examples to investigate the future rainfall trends and corresponding uncertainties, providing a reference for water resource management and usage. Since the Water Resources Agency (WRA) of the Ministry of Economic Affairs of Taiwan currently recommends the CMIP5 (AR5) GCM models for Taiwan regional climate assessments, the different emission scenarios (RCP 4.5, RCP 8.5) data simulated by two AR5 GCMs, ACCESS and CSMK3, of the IPCC, and monthly rainfall data of case regions from January 1950 to December 2005 in the Central Weather Administration (CWA) in Taiwan are employed. DNN model parameters are optimized based on historical scenarios to estimate the trends and uncertainties of future monthly rainfall in the case regions. The simulated results show that the probability of rainfall increase will improve in the dry season and will reduce in the wet season in the mid-term to long-term. The future wet season rainfall in Hualien has the highest variability. It ranges from 201 mm to 300 mm, with representative concentration pathways RCP 4.5 much higher than RCP 8.5. The median percentage increase and decrease in RCP 8.5 are higher than in RCP 4.5. This indicates that RCP 8.5 has a greater impact on future monthly rainfall. Full article
(This article belongs to the Special Issue The Water Cycle and Climate Change (3rd Edition))
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32 pages, 13260 KiB  
Article
Flood Susceptibility Mapping in Punjab, Pakistan: A Hybrid Approach Integrating Remote Sensing and Analytical Hierarchy Process
by Rana Muhammad Amir Latif and Jinliao He
Atmosphere 2025, 16(1), 22; https://doi.org/10.3390/atmos16010022 - 28 Dec 2024
Viewed by 1455
Abstract
Flood events pose significant risks to infrastructure and populations worldwide, particularly in Punjab, Pakistan, where critical infrastructure must remain operational during adverse conditions. This study aims to predict flood-prone areas in Punjab and assess the vulnerability of critical infrastructures within these zones. We [...] Read more.
Flood events pose significant risks to infrastructure and populations worldwide, particularly in Punjab, Pakistan, where critical infrastructure must remain operational during adverse conditions. This study aims to predict flood-prone areas in Punjab and assess the vulnerability of critical infrastructures within these zones. We developed a robust Flood Susceptibility Model (FSM) utilizing the Maximum Likelihood Classification (MLC) model and Analytical Hierarchy Process (AHP) incorporating 11 flood-influencing factors, including “Topographic Wetness Index (TWI), elevation, slope, precipitation (rain, snow, hail, sleet), rainfall, distance to rivers and roads, soil type, drainage density, Land Use/Land Cover (LULC), and the Normalized Difference Vegetation Index (NDVI)”. The model, trained on a dataset of 850 training points, 70% for training and 30% for validation, achieved a high accuracy (AUC = 90%), highlighting the effectiveness of the chosen approach. The Flood Susceptibility Map (FSM) classified high- and very high-risk zones collectively covering approximately 61.77% of the study area, underscoring significant flood vulnerability across Punjab. The Sentinel-1A data with Vertical-Horizontal (VH) polarization was employed to delineate flood extents in the heavily impacted cities of Dera Ghazi Khan and Rajanpur. This study underscores the value of integrating Multi-Criteria Decision Analysis (MCDA), remote sensing, and Geographic Information Systems (GIS) for generating detailed flood susceptibility maps that are potentially applicable to other global flood-prone regions. Full article
(This article belongs to the Special Issue The Water Cycle and Climate Change (3rd Edition))
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16 pages, 5839 KiB  
Article
Analysis of Hydrological Memory Characteristics in Taiwan’s Catchments
by Ting-Jui Fang, Hsin-Yu Chen and Hsin-Fu Yeh
Atmosphere 2025, 16(1), 19; https://doi.org/10.3390/atmos16010019 - 27 Dec 2024
Viewed by 764
Abstract
Climate change often affects streamflow, which can be categorized into immediate and lag responses. Historically, the phenomenon of lag responses, known as hydrological memory, has often been overlooked. This study aims to determine whether hydrological memory characteristics exist in Taiwan’s catchments and to [...] Read more.
Climate change often affects streamflow, which can be categorized into immediate and lag responses. Historically, the phenomenon of lag responses, known as hydrological memory, has often been overlooked. This study aims to determine whether hydrological memory characteristics exist in Taiwan’s catchments and to identify the lag time in streamflow response. Using data from 67 catchments across Taiwan with a length of over 30 years, the study examines the response of streamflow to precipitation and potential evapotranspiration across different time scales. Streamflow elasticity was employed to quantify the sensitivity of catchment streamflow. Sensitivity analysis results indicate that the month scale better explains the sensitivity of streamflow to climatic factors compared to the year scale. Therefore, memory characteristics are discussed using the month scale. Only 19.4% of the studied catchments exhibit significant hydrological memory, making it a rare phenomenon in Taiwan. The conceptual model of hydrological memory shows that extreme precipitation and other hydrological climate anomalies primarily impact river streamflow generation 33 days (1.11 months) later, with the influence of precipitation on streamflow recharge lag up to 50 days (1.67 months). Catchments with hydrological memory characteristics are predominantly located in southwestern Taiwan, mainly in catchments smaller than 500 km2, with generally lower baseflow indices and a higher proportion of streamflow contributions. These characteristics are less common in high-elevation areas. The results of this study highlight that streamflow response to climatic factors exhibits a lag time, illustrating the memory characteristics of Taiwan’s catchments. This understanding will aid in the prediction of hydrological phenomena and provide valuable references for hydrological modeling and the development and management of water resources. Full article
(This article belongs to the Special Issue The Water Cycle and Climate Change (3rd Edition))
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19 pages, 44786 KiB  
Article
Historical and Future Changes in Meteorological–Hydrological Compound Drought in China
by Zhuoyuan Li, Er Lu, Juqing Tu and Dian Yuan
Atmosphere 2024, 15(12), 1459; https://doi.org/10.3390/atmos15121459 - 6 Dec 2024
Viewed by 757
Abstract
Drought is typically divided into meteorological, agricultural, hydrological, and socioeconomic categories. Generally, the transition from meteorological drought to other types of droughts is known as drought propagation. When drought propagation occurs, different types of droughts may still exist simultaneously or successively. In this [...] Read more.
Drought is typically divided into meteorological, agricultural, hydrological, and socioeconomic categories. Generally, the transition from meteorological drought to other types of droughts is known as drought propagation. When drought propagation occurs, different types of droughts may still exist simultaneously or successively. In this study, compound droughts are divided into three categories: hydrological meteorological compound drought (HMD), meteorological hydrological compound drought (MHD), and simultaneous compound drought (SD). ERA5 and CMIP6 data are used for analysis under historical and future scenarios. Different types of compound droughts have emerged in extreme centers in different basins. Our analysis indicates a significant upward trend in the duration of these three compound droughts from 1979 to 2022. Additionally, our projections under SSP5-8.5 and SSP2-4.5 suggest a substantial increase in the occurrence of various compound droughts. HMD, MHD and SD all show a consistent upward trend under the future scenario above the moderate-drought level. MHDs are projected to experience the most significant increase compared to the historical period in the far-future period (2066–2099) under SSP5-8.5. Full article
(This article belongs to the Special Issue The Water Cycle and Climate Change (3rd Edition))
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21 pages, 6453 KiB  
Article
Game Theory-Based Comparison of Disaster Risk Assessment for Two Landfall Typhoons: A Case Study of Jilin Province’s Impact
by Zhennan Dong, Dan Zhu, Yichen Zhang, Jiquan Zhang, Xiufeng Yang and Fanfan Huang
Atmosphere 2024, 15(12), 1434; https://doi.org/10.3390/atmos15121434 - 29 Nov 2024
Viewed by 810
Abstract
Utilizing the best typhoon track data, district and county scale disaster data in Jilin Province, meteorological data, and geographical data, the combined weighting method of AHP-EWM (Analytic Hierarchy Process–Entropy Weight Method) and game theory is employed to conduct a comprehensive risk analysis and [...] Read more.
Utilizing the best typhoon track data, district and county scale disaster data in Jilin Province, meteorological data, and geographical data, the combined weighting method of AHP-EWM (Analytic Hierarchy Process–Entropy Weight Method) and game theory is employed to conduct a comprehensive risk analysis and comparison of the disaster risk caused by two typhoons, Maysak and Haishen, in Jilin Province. Game theory enhances precision in evaluation beyond conventional approaches, effectively addressing the shortcomings of both subjective and objective weighting methods. Typhoon Maysak and Typhoon Haishen exhibit analogous tracks. They have successively exerted an impact on Jilin Province, and the phenomenon of overlapping rain areas is a crucial factor in triggering disasters. Typhoon Maysak features stronger wind force and greater hourly rainfall intensity, while Typhoon Haishen has a longer duration of rainfall. Additionally, Typhoon Maysak causes more severe disasters in Jilin Province. With regard to the four dimensions of disaster risk, the analysis of hazards reveals that the areas categorized as high risk and above in relation to the two typhoons are mainly located in the central-southern and eastern regions of Jilin Province. Typhoon Maysak has a slightly higher hazard level. During the exposure assessment, it was determined that the high-risk areas occupied 16% of the gross area of Jilin Province. It is mainly concentrated in three economically developed cities, as well as some large agricultural counties. In the context of vulnerability analysis, regions classified as high risk and above constitute 54% of the overall area. The areas classified as having high vulnerability are predominantly located in Yushu, Nong’an, and Songyuan. From the analysis of emergency response and recovery ability, Changchun has strong typhoon disaster prevention and reduction ability. This is proportional to the local level of economic development. The mountainous areas in the east and the regions to the west are comparatively weak. Finally, the comprehensive typhoon disaster risk zoning indicates that the zoning of the two typhoons is relatively comparable. When it comes to high-risk and above areas, Typhoon Maysak accounts for 38% of the total area, while Typhoon Haishen occupies 47%. The regions with low risk are predominantly found in Changchun, across the majority of Baicheng, and at the intersection of Baishan and Jilin. Upon comparing the disasters induced by two typhoons in Jilin Province, it was observed that the disasters caused by Typhoon Maysak were considerably more severe than those caused by Typhoon Haishen. This finding aligns with the intense wind and heavy rainfall brought by Typhoon Maysak. Full article
(This article belongs to the Special Issue The Water Cycle and Climate Change (3rd Edition))
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24 pages, 6188 KiB  
Article
Characteristics of Vegetation Photosynthesis under Flash Droughts in the Major Agricultural Areas of Southern China
by Yuqing Zhang, Fengwu Liu, Taizheng Liu, Changchun Chen and Zhonghui Lu
Atmosphere 2024, 15(8), 886; https://doi.org/10.3390/atmos15080886 - 25 Jul 2024
Cited by 1 | Viewed by 1358
Abstract
Flash droughts adversely affect agriculture and ecosystems due to their rapid depletion of soil moisture (SM). However, few studies assessed the impacts of flash droughts on crops, especially in the agricultural regions of southern China. In this study, we investigated flash droughts using [...] Read more.
Flash droughts adversely affect agriculture and ecosystems due to their rapid depletion of soil moisture (SM). However, few studies assessed the impacts of flash droughts on crops, especially in the agricultural regions of southern China. In this study, we investigated flash droughts using crop root zone SM in the main agricultural region of southern China. Additionally, solar-induced chlorophyll fluorescence (SIF) served as a vegetation index to explore the crop response to flash droughts. The results reveal that the SIF exhibited an upward trend from 2001 to 2020 in the study area, indicating the enhanced photosynthetic capacity of crops and subsequent yield improvement. Hotspots of flash drought frequency occurred in the eastern areas of both the upper and lower Yangtze River regions, specifically in areas where the most rapid types of flash droughts were particularly prevalent. The average duration of flash droughts in the southern agricultural region was 6–12 pentads, a sufficiently long duration to significantly hinder crop photosynthesis, resulting in negative SIF standardized anomalies. The area affected by flash droughts in the southern agricultural region presented a downward trend during 2001–2020, with flash droughts of the longest duration in the recent decade, specifically in 2019, 2010, and 2013. The response frequency and time of SIF to flash droughts were >80% and <2 pentads, respectively, indicating that crops in the study area have a high sensitivity to flash droughts. In the northern part of the middle Yangtze River region and the southwestern and southeastern parts of the South China region, the mean values of the standardized anomalies of the SIF were lower than −0.5 during flash droughts, suggesting that crops in these areas were severely affected by flash droughts. During the late summer of 2019, the study area experienced a precipitation shortage coupled with high evapotranspiration capacity. This unfavorable combination of meteorological conditions can quickly lead to a substantial depletion of SM, ultimately triggering flash droughts that can be devastating for crops. Our findings can enhance the understanding of the impacts of flash droughts on crops in agricultural regions, as well as provide early warning signals of flash droughts for farmers to make appropriate mitigation strategies. Full article
(This article belongs to the Special Issue The Water Cycle and Climate Change (3rd Edition))
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