New Insights in Climate Change Effects on Hydrological Cycle and Water Resources Management

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

Deadline for manuscript submissions: closed (3 June 2024) | Viewed by 8112

Special Issue Editors


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Guest Editor
School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China
Interests: GRACE; terrestrial water storage; groundwater; evapotranspiration; reconstruction of TWSA
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of geography and Information Engineering, China University of Geosciences, Wuhan 430078, China
Interests: water resources management; hydrological forecasting; drought evolution; remote sensing hydrology
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Atmospheric Science, School of Environmental Studies, China University of Geosciences, Wuhan 430078, China
Interests: evapotranspiration; heatwave; drought; flood forecasting
School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China
Interests: drought; terrestrial water storage; flood; water resources management; risk assessment

Special Issue Information

Dear Colleagues,

Climate change, driven primarily by global warming, is having a profound impact on the Earth's hydrological cycle and the management of water resources. The hydrological cycle, which encompasses processes such as precipitation, evapotranspiration, water storage changes, and runoff, plays a critical role in maintaining the availability and quality of freshwater resources. However, altering climate patterns are disrupting this delicate balance, leading to a range of challenges for water resources management worldwide.

Under the influence of changing climate, population growth, urbanization, land use changes, and poor water management practices, water scarcity has become a pressing issue, particularly in arid, semi-arid, and subtropical regions. The consequences of water scarcity are far-reaching, affecting various sectors, including agriculture, industry, and domestic water supply. Moreover, projections indicate that, by 2025, approximately one in four individuals on Earth may experience water scarcity, highlighting the urgency of addressing this issue.

In this Special Issue, we are looking for original scientific contributions on the hydrological cycle and water resources management, with topics including but not limited to contributions of climate change to the hydrological cycle, changes of hydrological variables (precipitation, evapotranspiration, runoff, etc.), GRACE application in hydrology, impact of hydrological drought and flood, vegetation phenology  and ecohydrological effects, meteorological and hydrological drought evolution, advances in hydrological forecasting, monitoring of groundwater storage, remote sensing of climate extremes, and new perspective from SWOT satellite.

In addition, we dedicate this Special Issue to Prof. Jianyu Liu, who died of cancer in June 2023. He was an expert in climate change and hydrology. He had organized a Special Issue titled "The Water Cycle and Climate Change" with us in this journal, https://www.mdpi.com/journal/atmosphere/special_issues/Water_Cycle_Climate

Dr. Yulong Zhong
Prof. Dr. Shuang Zhu
Dr. Dongdong Kong
Dr. Peng Yang
Guest Editors

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Keywords

  • climate change
  • water resources management
  • precipitation
  • streamflow
  • evapotranspiration
  • terrestrial water storage
  • climate variability

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Published Papers (6 papers)

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Research

18 pages, 5885 KiB  
Article
Long-Term Trends and Variability of Hydroclimate Variables and Their Linkages with Climate Indices in the Songhua River
by Chongya Ma, Wenhan Pei, Jiping Liu and Guobin Fu
Atmosphere 2024, 15(2), 174; https://doi.org/10.3390/atmos15020174 - 30 Jan 2024
Cited by 1 | Viewed by 974
Abstract
The long-term trends and variability of hydroclimate variables are critical for water resource management, as well as adaptation to climate change. Three popular methods were used in this study to explore the trends and variability of hydroclimate variables during last 122 years in [...] Read more.
The long-term trends and variability of hydroclimate variables are critical for water resource management, as well as adaptation to climate change. Three popular methods were used in this study to explore the trends and variability of hydroclimate variables during last 122 years in the Songhua River (SHR), one of most important river systems in China. Results show the followings: (1) There was an obvious pattern of decadal oscillations, with three positive and three negative precipitation and streamflow anomalies. The lengths of these phases vary from 11 to 36 years. (2) Annual temperature demonstrated a statistically significant increasing trend in the last 122 years, and the trend magnitude was 0.30 °C/10 years in the last 50–60 years, being larger than that of the global surface temperature. It has increased much faster since 1970. (3) Monthly precipitation in the winter season in recent years was almost the same as that in earlier periods, but a significantly increasing monthly streamflow was observed due to snowmelt under a warming climate. (4) A statistically significant correlation between hydroclimate variables and climate indices can be determined. These results could be used to make better water resource management decisions in the SHR, especially under future climate change scenarios. Full article
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25 pages, 16447 KiB  
Article
Attribution of Runoff Variation in Reservoir Construction Area: Based on a Merged Deep Learning Model and the Budyko Framework
by Lilan Zhang, Xiaohong Chen, Bensheng Huang, Liangxiong Chen and Jie Liu
Atmosphere 2024, 15(2), 164; https://doi.org/10.3390/atmos15020164 - 27 Jan 2024
Viewed by 1056
Abstract
This study presents a framework to attribute river runoff variations to the combined effects of reservoir operations, land surface changes, and climate variability. We delineated the data into natural and impacted periods. For the natural period, an integrated Long Short-Term Memory and Random [...] Read more.
This study presents a framework to attribute river runoff variations to the combined effects of reservoir operations, land surface changes, and climate variability. We delineated the data into natural and impacted periods. For the natural period, an integrated Long Short-Term Memory and Random Forest model was developed to accurately simulate both mean and extreme runoff values, outperforming existing models. This model was then used to estimate runoff unaffected by human activities in the impacted period. Our findings indicate stable annual and wet season mean runoff, with a decrease in wet season maximums and an increase in dry season means, while extreme values remained largely unchanged. A Budyko framework incorporating reconstructed runoff revealed that rainfall and land surface changes are the predominant factors influencing runoff variations in wet and dry seasons, respectively, and land surface impacts become more pronounced during the impacted period for both seasons. Human activities dominate dry season runoff variation (93.9%), with climate change at 6.1%, while in the wet season, the split is 64.5% to 35.5%. Climate change and human activities have spontaneously led to reduced runoff during the wet season and increased runoff during the dry season. Only reservoir regulation is found to be linked to human-induced runoff changes, while the effects of land surface changes remain ambiguous. These insights underscore the growing influence of anthropogenic factors on hydrological extremes and quantify the role of reservoirs within the impacts of human activities on runoff. Full article
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16 pages, 5126 KiB  
Article
Unravelling the Drought Variance Using Machine Learning Methods in Six Capital Cities of Australia
by Wenjing Yang, Shahab Doulabian, Amirhossein Shadmehri Toosi and Sina Alaghmand
Atmosphere 2024, 15(1), 43; https://doi.org/10.3390/atmos15010043 - 29 Dec 2023
Cited by 2 | Viewed by 1309
Abstract
Understanding and projecting drought, especially in the face of climate change, is crucial for assessing its impending risks. However, the causes of drought are multifaceted. As the environmental research paradigm pivots towards machine learning (ML) for predictions, our investigation contrasted multiple ML techniques [...] Read more.
Understanding and projecting drought, especially in the face of climate change, is crucial for assessing its impending risks. However, the causes of drought are multifaceted. As the environmental research paradigm pivots towards machine learning (ML) for predictions, our investigation contrasted multiple ML techniques to simulate the Standardized Precipitation Evapotranspiration Index (SPEI) from 2009 to 2022, utilizing various potential evapotranspiration (PET) methods. Our primary focus was Australia, the world’s driest inhabited continent. Given the challenges with ML model interpretation, SHAP (SHapley Additive exPlanations) values were employed to decipher SPEI variations and to gauge the relative importance of precipitation (Prec) and PET in six key Australian cities. Our findings revealed that while different PET methods resulted in distinct mean values, their trends remained consistent. Post the Millennium Drought, Australia experienced several drought events. SPEI discrepancies based on PET methods were minimal in humid regions like Brisbane and Darwin. However, for arid cities, the Priestley–Taylor equation-driven SPEI differed notably from other methods. Ridge regression was the most adept at mirroring SPEI changes among the assessed ML models. Furthermore, the SHAP explainer discerned that PET-related climate variables had a greater impact on SPEI in drier cities, whereas in humid cities, Prec was more influential. Notably, the research emphasised CO2′s role in influencing drought dynamics in humid cities. These insights are invaluable for enhancing drought mitigation strategies and refining predictive models. Such revelations are crucial for stakeholders aiming to improve drought prediction and management, especially in drought-prone regions like Australia. Full article
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20 pages, 12201 KiB  
Article
Evaluation of Freeze–Thaw Erosion Intensity in the Ecological Function Reserve of the Greater Hinggan Mountains Based on Geographic Information Systems and a Geographic Detector
by Yanru Liu, Yuefeng Lu, Miao Lu, Ying Sun, Jing Li and Kaizhong Yao
Atmosphere 2024, 15(1), 36; https://doi.org/10.3390/atmos15010036 - 27 Dec 2023
Viewed by 1214
Abstract
Freeze–thaw erosion is one of the three major soil erosions in China, including wind erosion and hydraulic erosion, which leads to the destruction of the natural environment, the imbalance of economic development, a threat to personal safety, and irreversible disaster to the country [...] Read more.
Freeze–thaw erosion is one of the three major soil erosions in China, including wind erosion and hydraulic erosion, which leads to the destruction of the natural environment, the imbalance of economic development, a threat to personal safety, and irreversible disaster to the country and people. China’s permafrost area accounts for about one-fifth of the country’s land area, and the seasonal permafrost area accounts for half of China’s land area, mainly concentrated in the Qinghai–Tibet Plateau, Xinjiang Province, Heilongjiang Province, Gansu Province, and other regions. In order to establish an evaluation system for the ecological function reserve of the Greater Hinggan Mountains, nine evaluation indicators were selected from the perspectives of topography, climate, soil, and vegetation conditions. GIS technology, a multiple collinearity test, and principal component analysis were used to comprehensively evaluate the freeze–thaw erosion in the ecological function reserve of the Greater Hinggan Mountains. This study categorized the evaluation results into five intensity levels, from micro to severe. Finally, the degree of influence of different influencing factors on freeze–thaw erosion and the interactions between the factors were analyzed using a geographic detector. The results showed the following: (1) The intensity of freeze–thaw erosion in the study area gradually increased from west to east, and the comprehensive evaluation results were −0.2552 to 0.7581. Overall, moderate, severe, and mild erosion accounted for 29.83%, 25.9%, and 21.54% of the total area of the freeze–thaw zone, respectively. (2) Soil moisture content and the annual range in temperature were the main factors contributing to freeze–thaw erosion. The degree of influence of the two effects on freeze–thaw erosion (q = 0.5997) was better than that of the single-factor effect. Full article
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18 pages, 7108 KiB  
Article
Twenty-Year Spatiotemporal Variations of TWS over Mainland China Observed by GRACE and GRACE Follow-On Satellites
by Wei Chen, Yuhao Xiong, Min Zhong, Zihan Yang, C. K. Shum, Wenhao Li, Lei Liang and Quanguo Li
Atmosphere 2023, 14(12), 1717; https://doi.org/10.3390/atmos14121717 - 22 Nov 2023
Cited by 1 | Viewed by 1366
Abstract
Terrestrial water storage (TWS) is a pivotal component of the global water cycle, profoundly impacting water resource management, hazard monitoring, and agriculture production. The Gravity Recovery and Climate Experiment (GRACE) and its successor, the GRACE Follow-On (GFO), have furnished comprehensive monthly TWS data [...] Read more.
Terrestrial water storage (TWS) is a pivotal component of the global water cycle, profoundly impacting water resource management, hazard monitoring, and agriculture production. The Gravity Recovery and Climate Experiment (GRACE) and its successor, the GRACE Follow-On (GFO), have furnished comprehensive monthly TWS data since April 2002. However, there are 35 months of missing data over the entire GRACE/GFO observational period. To address this gap, we developed an operational approach utilizing singular spectrum analysis and principal component analysis (SSA-PCA) to fill these missing data over mainland China. The algorithm was demonstrated with good performance in the Southwestern River Basin (SWB, correlation coefficient, CC: 0.71, RMSE: 6.27 cm), Yangtze River Basin (YTB, CC: 0.67, RMSE: 3.52 cm), and Songhua River Basin (SRB, CC: 0.66, RMSE: 7.63 cm). Leveraging two decades of continuous time-variable gravity data, we investigated the spatiotemporal variations in TWS across ten major Chinese basins. According to the results of GRACE/GFO, mainland China experienced an average annual TWS decline of 0.32 ± 0.06 cm, with the groundwater storage (GWS) decreasing by 0.54 ± 0.10 cm/yr. The most significant GWS depletion occurred in the Haihe River Basin (HRB) at −2.07 ± 0.10 cm/yr, significantly substantial (~1 cm/yr) depletions occurred in the Yellow River Basin (YRB), SRB, Huaihe River Basin (HHB), Liao-Luan River Basin (LRB), and Southwest River Basin (SWB), and moderate losses were recorded in the Northwest Basin (NWB, −0.34 ± 0.03 cm/yr) and Southeast River Basin (SEB, −0.24 ± 0.10 cm/yr). Furthermore, we identified that interannual TWS variations in ten basins of China were primarily driven by soil moisture water storage (SMS) anomalies, exhibiting consistently and relatively high correlations (CC > 0.60) and low root-mean-square errors (RMSE < 5 cm). Lastly, through the integration of GRACE/GFO and Global Land Data Assimilation System (GLDAS) data, we unraveled the contrasting water storage patterns between northern and southern China. Southern China experienced drought conditions, while northern China faced flooding during the 2020–2023 La Niña event, with the inverse pattern observed during the 2014–2016 El Niño event. This study fills in the missing data and quantifies water storage variations within mainland China, contributing to a deeper insight into climate change and its consequences on water resource management. Full article
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29 pages, 12919 KiB  
Article
Investigating the Seasonal Effect of Climatic Factors on Evapotranspiration in the Monsoon Climate Zone: A Case Study of the Yangtze River Basin
by Mengmeng Wang, Miao Li, Qing An, Zhengjia Zhang and Jing Lu
Atmosphere 2023, 14(8), 1282; https://doi.org/10.3390/atmos14081282 - 13 Aug 2023
Viewed by 1108
Abstract
Evapotranspiration (ET) plays an essential role in water balance and ecological environment changes. The Yangtze River Basin (YRB) is a typical monsoon climate zone. Most existing studies on the impact of climatic factors on annual ET have overlooked the seasonal effect. This study [...] Read more.
Evapotranspiration (ET) plays an essential role in water balance and ecological environment changes. The Yangtze River Basin (YRB) is a typical monsoon climate zone. Most existing studies on the impact of climatic factors on annual ET have overlooked the seasonal effect. This study quantitatively analyzed the spatiotemporal variation characteristics of ET and its relationship with climatic factors at the annual and monthly scales in the YRB using high−spatial−resolution PML_V2 ET data from 2001 to 2020. Results showed that: (1) the spatiotemporal distribution of the regions with significant correlation between ET and individual climatic factors (i.e., air temperature, solar radiation and precipitation) in the YRB showed obvious cyclical changes in month, and the spatial change pattern is strongly related to the elevation; (2) the area proportion of the dominant climatic factors affecting annual ET in the study area was characterized by solar radiation > specific humidity > precipitation > air temperature > wind speed. However, monthly ET in most areas of the YRB was driven by solar radiation and air temperature, especially in summer and autumn, while ET in spring and winter was mainly driven by solar radiation, air temperature, and specific humidity. Full article
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