Spatiotemporal Evolution Patterns and Propagation Mechanisms in Drought

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

Deadline for manuscript submissions: 20 February 2025 | Viewed by 764

Special Issue 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

E-Mail Website
Guest Editor
School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
Interests: water resources; drought disaster; agricultural drought; drought assessment

E-Mail Website
Guest Editor
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 Issue Information

Dear Colleagues,

Climate change is intensifying the occurrence of extreme weather events, with particularly profound impacts on drought. Drought stands as the most common natural disaster globally, characterized by its high frequency, long duration, extensive coverage, and substantial losses. With climate change and human activities affecting water resources, the frequency, severity, and unpredictability of droughts and other extreme events are set to increase significantly.

Therefore, we are pleased to announce the launch of a Special Issue titled “Spatiotemporal Evolution Patterns and Propagation Mechanisms in Drought”, in which we aim to integrate the latest research methods, technologies, applications, and advancements into the monitoring, forecasting, and mitigation of drought events. This Special Issue seeks to enhance our societal and ecosystem-related understanding of, and responses to, the challenges posed by drought events.

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

  1. Improving existing drought indices and developing novel composite drought indices;
  2. Exploring pathways and mechanisms for multi-type drought propagation;
  3. Identifying the driving factors behind drought events;
  4. Characterizing and predicting the impacts of climate change and human activities on various aspects of drought events;
  5. Revealing spatiotemporal evolution patterns in multi-type drought on various spatial and temporal scales;
  6. Developing scientifically sound drought management plans to effectively control drought at its source or interrupt its propagation.

We look forward to receiving your submissions.

Dr. Fei Wang
Prof. Dr. Yanbin Li
Dr. Kai Feng
Guest Editors

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Keywords

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

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Published Papers (1 paper)

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Research

22 pages, 17451 KiB  
Article
Identification of the Runoff Evolutions and Driving Forces during the Dry Season in the Xijiang River Basin
by Fei Wang, Ruyi Men, Shaofeng Yan, Zipeng Wang, Hexin Lai, Kai Feng, Shikai Gao, Yanbin Li, Wenxian Guo and Qingqing Tian
Water 2024, 16(16), 2317; https://doi.org/10.3390/w16162317 - 17 Aug 2024
Viewed by 592
Abstract
During the dry season, river flow gradually diminishes, and surface water flow dries up. Therefore, the investigation of runoff during the dry season is of great practical significance for rational water allocation and water resource management. Based on hydrological station data from the [...] Read more.
During the dry season, river flow gradually diminishes, and surface water flow dries up. Therefore, the investigation of runoff during the dry season is of great practical significance for rational water allocation and water resource management. Based on hydrological station data from the Xijiang River Basin (XRB) from 1961 to 2020, this study examines the trend and periodic characteristics of dry-season runoff, identifies fluctuation and variability in dry-season runoff, and investigates the main circulation factor combinations influencing dynamic changes in dry-season runoff. The results indicate the following: (1) the characteristics of dry-season runoff variations are basically consistent across sub-basins in the XRB during the study period, with the minimum (21.96 × 108 m3) and maximum (54.67 × 108 m3) average monthly runoff occurring in February and October, respectively; (2) interannual-scale dry-season runoff exhibits periodicity of 3.53 years and 7.5 years; (3) using the Bayesian estimator of abrupt seasonal and trend change algorithm (BEAST), a seasonal abrupt point with a probability of 20.5% occurs in 1983, and the confidence interval for this abrupt point is from 1980 to 1986; (4) based on the cross wavelet approach, solar sunspots are identified as the primary circulation factor contributing to dry-season runoff in the XRB, exhibiting a significant 8–14 years resonance cycle of negative correlation with runoff during the high-energy phase from 1972 to 2006. These findings offer a new perspective on understanding the evolution of dry-season runoff and circulation factor variations, which are crucial for accurate prediction, early warning, and rational allocation of water resources during the dry season. Full article
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