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Temporal and Spatial Evolution Characteristics of Drought Under Climate Change

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water and Climate Change".

Deadline for manuscript submissions: 25 December 2026 | Viewed by 690

Editors


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Guest Editor
School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
Interests: drought assessment; drought monitoring; drought propagation; remote sensing; extreme precipitation
Special Issues, Collections and Topics in MDPI journals
School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
Interests: drought monitoring; drought prediction; drought propagation; hydrological model; carbon cycling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Drought exhibits significant temporal and spatial evolution characteristics across global land surfaces under climate change. Temporally, drought frequency, duration, and severity have increased, and there has been a rising trend in flash droughts driven by intensified evapotranspiration and precipitation deficits, with significant interannual and interdecadal variability. Spatially, drought expansion and intensification are most pronounced in mid-latitude semi-arid and arid regions, the Mediterranean, East Asia, and parts of Africa and Australia, while humid zones also experience elevated drought risks, which leads to strong spatial heterogeneity in drought propagation and transition patterns. Overall, climate warming heightens the water cycle imbalance and thus reshapes the spatiotemporal distribution of drought, increasing the likelihood of concurrent droughts across multiple regions.

We are therefore pleased to announce the launch of a Special Issue titled “Temporal and Spatial Evolution Characteristics of Drought Under Climate Change”, which aims to systematically gather cutting-edge research results on the occurrence, development, spatiotemporal dynamics, evolution laws, and driving mechanisms of drought events under global climate change. This Special Issue hopes to  promote academic exchanges and share achievements in the fields of drought monitoring and early warning, evolution simulation, disaster assessment, and response strategies, and to provide theoretical support and a scientific basis for drought disaster prevention and control, water resource security, and regional sustainable development under climate change.

Topics of interest include, but are not limited to, the following:

  1. Temporal and spatial evolution patterns and long‑term trends of drought under climate change;
  2. Driving mechanisms of drought evolution, including climate warming, precipitation variability, circulation patterns, and human activities;
  3. Drought monitoring indices, identification approaches, multi‑source data application, and assessment methods;
  4. Drought propagation processes, drought–flood abrupt alternation, and regional teleconnection characteristics;
  5. Impacts of drought on the hydrological cycle, water resources, agricultural production, and ecosystem stability;
  6. Drought risk assessment, early warning systems, adaptation strategies, and disaster prevention countermeasures.

Dr. Fei Wang
Dr. Kai Feng
Guest Editors

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Keywords

  • droughts indicators
  • drought propagation
  • spatiotemporal evolution
  • remote sensing
  • drought mitigation strategies

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Published Papers (2 papers)

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Research

20 pages, 11296 KB  
Article
Exploring Drivers of Hydrological Drought Dynamics Across the Upper Yellow River Basin, China: Insights from the Sub-Basins Contribution, Large Reservoir Regulation, and Teleconnection
by Zhongwei Ren, Xin Li and Te Zhang
Water 2026, 18(17), 2071; https://doi.org/10.3390/w18172071 - 23 Aug 2026
Abstract
Improving the understanding of hydrological drought mechanisms is paramount for drought resistance and early warning in a changing environment. The Upper Yellow River Basin (UYRB), the primary water-producing region of the Yellow River Basin, experiences hydrological droughts that are jointly influenced by climate [...] Read more.
Improving the understanding of hydrological drought mechanisms is paramount for drought resistance and early warning in a changing environment. The Upper Yellow River Basin (UYRB), the primary water-producing region of the Yellow River Basin, experiences hydrological droughts that are jointly influenced by climate variability and human activities. This study systematically investigated the spatiotemporal evolution of hydrological droughts in the UYRB and elucidated their underlying mechanisms from the perspectives of sub-basin contributions, reservoir regulation, and large-scale climate drivers. We found an increasing trend in yearly drought severity from 1956 to 2010 under the natural scenario, but large reservoirs significantly reduced the severity. The headwater region, Tao River Basin, and interval region 2 were identified as the key areas in drought formation of the whole UYRB. Reservoirs generally increased monthly drought intensity in summer and autumn but decreased drought intensity in spring and winter. For drought events lasting for a longer time, reservoirs interrupted their continuity, which reduced the average severity and duration but exaggerated peak intensity, especially for extreme events. The impacts of different reservoirs on drought variations showed distinct differences due to different operation regulations. Cascade reservoir regulation weakened and altered the relationships between hydrological drought and climate indices, including PDO, AMO, NAO, and ENSO, at the 8–16 and 32–64 month timescales. This finding indicates that the effects of large-reservoir regulation should be removed using naturalized streamflow when identifying teleconnection drivers of hydrological drought and conducting drought early warning. These findings provide new insights into the mechanisms governing hydrological drought under the combined influences of climate change and reservoir regulation and offer a scientific basis for drought early warning, reservoir operation, and integrated water resources management. Full article
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27 pages, 33399 KB  
Article
Spatiotemporal Evolution and Driving Mechanisms of Soil Drought in the Haihe River Basin (2000–2022) Based on the Standardized Soil Moisture Index
by Jinpeng Wang, Qian Xu, Fei Wang, Qingqing Tian and Yu Tian
Water 2026, 18(15), 1877; https://doi.org/10.3390/w18151877 - 2 Aug 2026
Viewed by 440
Abstract
Accurately depicting the spatiotemporal evolution patterns and driving mechanisms of soil drought is of great significance for regional agricultural drought warning and adaptive management of water resources. There are still shortcomings in the existing research in terms of indicator applicability, mutation detection and [...] Read more.
Accurately depicting the spatiotemporal evolution patterns and driving mechanisms of soil drought is of great significance for regional agricultural drought warning and adaptive management of water resources. There are still shortcomings in the existing research in terms of indicator applicability, mutation detection and trend persistence collaborative diagnosis, as well as the quantification of multi-scale meteorological driving factors. In response to the above issues, this study constructs the Standardized Soil Moisture Index (SSMI) based on the principle of soil moisture supply and demand balance, and comprehensively uses BFAST structure mutation detection, autocorrelation correction Mann–Kendall (MMK) trend test, Hurst persistence analysis, and cross-wavelet transform methods to systematically analyze soil drought in the Haihe River Basin (HRB) from 2000 to 2022. Using the FLDAS reanalysis dataset and multi-source meteorological observation data, this study revealed the stage changes, seasonal evolution characteristics, and dominant meteorological driving factors of soil drought in the watershed. Key findings include: (1) the most significant structural breakpoint occurred in May 2005 (confidence interval: March–November 2005); (2) spring exhibited the strongest drying trend (mean Zs = −0.51), while autumn showed the strongest anti-persistence (mean Hurst = 0.41), making it the most vulnerable season for future soil moisture state shifts; (3) evapotranspiration was the dominant meteorological driver, with the highest significant coherence area percentage (SCAP), followed by air humidity, soil moisture, soil temperature, air temperature, and precipitation in descending order of influence. Full article
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