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Drought Evaluation Under Climate Change Condition

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

Deadline for manuscript submissions: 25 August 2025 | Viewed by 647

Special Issue Editor


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Guest Editor
Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
Interests: spatiotemporal pattern

Special Issue Information

Dear Colleagues,

Focus: This Special Issue will concentrate on the comprehensive evaluation of drought under the backdrop of climate change. It will explore the multifaceted impacts of changing climatic patterns on drought occurrence, severity, and duration. Researchers will explore how alterations in temperature, precipitation, wind patterns, and other climatic variables interact to exacerbate or mitigate drought conditions.

Scope: The scope encompasses a wide range of geographical regions, from arid and semi-arid zones traditionally more prone to drought to regions newly experiencing water stress due to climate change. It will cover various drought-affected sectors, including agriculture, water resources management, ecosystems, and human health. Methodologically, it will incorporate field studies, remote sensing analyses, modeling techniques, and socio-economic surveys to provide a holistic view.

Purpose: The primary purpose is to synthesize the latest knowledge and advancements in drought evaluation. By combining diverse research, we aim to equip policymakers, practitioners, and researchers with the tools and understanding to develop effective adaptation and mitigation strategies. We also seek to raise awareness about addressing drought in a changing climate.

Relation to the Existing Literature: The existing literature on drought and climate change is extensive but fragmented. This Special Issue will usefully supplement it in several ways. Firstly, it will provide updated and region-specific case studies that reflect the most recent climate trends. Many previous works have relied on historical data, while this issue will focus on the current and projected changes. Secondly, integrating multiple disciplinary approaches will bridge the gaps between hydrological, ecological, agricultural, and social science research. For example, it will explore the physical aspects of drought, socio-economic consequences, and feedback loops between them. Lastly, it will offer a platform for comparing and contrasting different methodological frameworks used in drought evaluation, facilitating the identification of best practices.

Contribution to Sustainability: Drought is a major threat to sustainability. In the context of water resources, sustainable management requires accurate drought evaluation. By understanding the patterns and impacts of drought, we can develop more efficient water allocation strategies, such as implementing water-saving technologies in agriculture and optimizing reservoir operations. It helps preserve biodiversity by identifying vulnerable habitats and implementing conservation measures during drought periods. From a socio-economic perspective, it enables the formulation of policies that support affected communities, like providing financial aid and alternative livelihood options. Overall, this Special Issue provides the knowledge base for making informed decisions that enhance long-term sustainability.

Dr. Yanfeng Wu
Guest Editor

Manuscript Submission Information

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Keywords

  • climate change
  • drought evaluation
  • water resources management
  • agricultural impacts
  • ecosystem resilience
  • socio-economic consequences
  • remote sensing for drought
  • modeling drought
  • adaptation strategies
  • sustainable development

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Published Papers (1 paper)

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Research

20 pages, 26018 KiB  
Article
An Accuracy Assessment of the ESTARFM Data-Fusion Model in Monitoring Lake Dynamics
by Can Peng, Yuanyuan Liu, Liwen Chen, Yanfeng Wu, Jingxuan Sun, Yingna Sun, Guangxin Zhang, Yuxuan Zhang, Yangguang Wang, Min Du and Peng Qi
Water 2025, 17(14), 2057; https://doi.org/10.3390/w17142057 - 9 Jul 2025
Viewed by 351
Abstract
High-spatiotemporal-resolution remote sensing data are of great significance for surface monitoring. However, existing remote sensing data cannot simultaneously meet the demands for high temporal and spatial resolution. Spatiotemporal fusion algorithms are effective solutions to this problem. Among these, the ESTARFM (Enhanced Spatiotemporal Adaptive [...] Read more.
High-spatiotemporal-resolution remote sensing data are of great significance for surface monitoring. However, existing remote sensing data cannot simultaneously meet the demands for high temporal and spatial resolution. Spatiotemporal fusion algorithms are effective solutions to this problem. Among these, the ESTARFM (Enhanced Spatiotemporal Adaptive Reflection Fusion Model) algorithm has been widely used for the fusion of multi-source remote sensing data to generate high spatiotemporal resolution remote sensing data, owing to its robustness. However, most existing studies have been limited to applying ESTARFM for the fusion of single-surface-element data and have paid less attention to the effects of multi-band remote sensing data fusion and its accuracy analysis. For this reason, this study selects Chagan Lake as the study area and conducts a detailed evaluation of the performance of the ESTARFM in fusing six bands—visible, near-infrared, infrared, and far-infrared—using metrics such as the correlation coefficient and Root Mean Square Error (RMSE). The results show that (1) the ESTARFM fusion image is highly consistent with the clear-sky Landsat image, with the coefficients of determination (R2) for all six bands exceeding 0.8; (2) the Normalized Difference Vegetation Index (NDVI) (R2 = 0.87, RMSE = 0.023) and the Normalized Difference Water Index (NDWI) (R2 = 0.93, RMSE = 0.022), derived from the ESTARFM fusion data, are closely aligned with the real values; (3) the evaluation and analysis of different bands for various land-use types reveal that R2 generally exhibits a favorable trend. This study extends the application of the ESTARFM to inland water monitoring and can be applied to scenarios similar to Chagan Lake, facilitating the acquisition of high-frequency water-quality information. Full article
(This article belongs to the Special Issue Drought Evaluation Under Climate Change Condition)
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