Drought Monitoring, Prediction and Impacts (2nd Edition)

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

Deadline for manuscript submissions: 31 August 2025 | Viewed by 558

Special Issue Editor


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Guest Editor
1. School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China
2. Department of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Republic of Korea
Interests: climatology; climate extremes; climate change; drought; hydrology; water resources
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Special Issue Information

Dear Colleagues,

This Special Issue is a follow-up to the first edition of the Special Issue entitled “Drought Monitoring, Prediction and Impacts” (https://www.mdpi.com/journal/atmosphere/special_issues/HBYJEKG0MC), published in Atmosphere in 2024.

Nowadays, climate change is the most debated issue worldwide, affecting not only our lives but also posing a serious threat to future generations. Anthropogenic activities are consistently modifying the climate system, which has resulted in altered precipitation patterns, elevated atmospheric carbon dioxide, the melting of snow covers, and most importantly an increase in global temperature. Recently, droughts in various regions of the world have highlighted the dangers of a lack of domestic animal feed, forcing farmers to import grain for their animals. This Special Issue aims to showcase the latest advancements in the monitoring and prediction of droughts to enhance our understanding of their complex dynamics and mitigate their adverse impacts.

The purpose of this Special Issue is to assemble cutting-edge research contributions from the global scientific community, fostering collaboration and knowledge exchange in the field of drought monitoring, simulation, and prediction. By disseminating innovative approaches and methodologies, this Special Issue aims to enhance the accuracy of drought prediction, support sustainable water resource management, and contribute to the development of effective strategies to mitigate the adverse impacts of droughts on society and the environment. We encourage researchers to submit original research articles, reviews, and case studies to this Special Issue. Contributions that incorporate multidisciplinary approaches and data-driven methodologies are especially welcome. Together, let us address the challenges of droughts and strive to build a more resilient and sustainable future.

This Special Issue seeks high-quality research papers that cover a broad spectrum of topics related to drought monitoring, simulation, and prediction. Potential areas of interest include remote sensing and monitoring, climate models and simulation, data assimilation and fusion, drought prediction and early warning systems, hydrological and agricultural impacts, adaptation and mitigation strategies, uncertainty, and risk assessment.

Prof. Dr. Muhammad Abrar Faiz
Guest Editor

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Keywords

  • droughts monitoring
  • simulation and prediction
  • impacts
  • remote sensing
  • climate models
  • evapotranspiration
  • drought indices
  • data assimilation
  • early warning systems
  • hydrological impacts
  • agricultural impacts
  • adaptation strategies
  • water resources
  • sustainable development

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Published Papers (2 papers)

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Research

23 pages, 8237 KiB  
Article
Evaluation of Time Delay and Cumulative Effects of Meteorological Drought on Net Primary Productivity of Vegetation in the Upper Reaches of the Yellow River, China
by Huazhu Xue, Zhi Li, Guotao Dong and Hao Wang
Atmosphere 2025, 16(5), 602; https://doi.org/10.3390/atmos16050602 - 16 May 2025
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Abstract
As a critical region for ecological construction in China, the upper Yellow River is still relatively short of research on the time-lag and cumulative effects of regional-scale drought on vegetation growth. Therefore, based on net primary productivity (NPP) estimated by the improved CASA [...] Read more.
As a critical region for ecological construction in China, the upper Yellow River is still relatively short of research on the time-lag and cumulative effects of regional-scale drought on vegetation growth. Therefore, based on net primary productivity (NPP) estimated by the improved CASA (Carnegie–Ames–Stanford approach) model and multi-time scale SPEI, trend analysis, significance test and partial correlation analysis were employed to explore the spatial and temporal patterns of NPP and quantitatively evaluate its response to drought. The results showed that (1) From 2001 to 2022, NPP was higher in the south and lower in the north, decreasing from southwest to northeast, and annual NPP was increasing in 87.9% of the regions. NPP in spring, summer and autumn has been significantly improved. (2) In terms of interannual and spatial distribution, except for spring and winter, annual, summer and autumn all showed an insignificant trend of humidification. (3) The lag and cumulative effects of drought on vegetation in most areas are positively correlated. About 82.58% of NPP in the growing season has a time-lag effect with drought, which mainly focuses on 1–2 months. The average lag time was 3.6 months, indicating that NPP had the strongest correlation with the meteorological drought index of the previous 3.6 months. For cumulative effect, about 66.14% of NPP had a cumulative effect on drought, and the cumulative time scales were mainly March, April, November and December. With the worsening of drought conditions, the effect of drought on NPP is enhanced. These findings enhance the understanding of the long-term consequences of drought on terrestrial ecosystems and provide a basis for the development of mitigation and adaptation strategies aimed at alleviating the adverse effects of drought on agriculture and ecosystems. Full article
(This article belongs to the Special Issue Drought Monitoring, Prediction and Impacts (2nd Edition))
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24 pages, 8538 KiB  
Article
Drought Trend Analysis Using Standardized Precipitation Evapotranspiration Index in Cold-Climate Regions
by Yaser Sabzevari, Saeid Eslamian, Abhiram Siva Prasad Pamula and Mohammad Hadi Bazrkar
Atmosphere 2025, 16(4), 482; https://doi.org/10.3390/atmos16040482 - 21 Apr 2025
Viewed by 385
Abstract
This study aimed to conduct a drought trend analysis using the standardized precipitation evapotranspiration index (SPEI) in two mountainous and cold-climate regions in Iran and the United States (US). The Mann–Kendall test was employed to assess the trend in the Upper Colorado River [...] Read more.
This study aimed to conduct a drought trend analysis using the standardized precipitation evapotranspiration index (SPEI) in two mountainous and cold-climate regions in Iran and the United States (US). The Mann–Kendall test was employed to assess the trend in the Upper Colorado River Basin (UCRB) in the US and Lorestan province. The results reveal a predominantly decreasing trend in drought occurrences across Lorestan, especially in southern and southwestern areas with lower elevations. In contrast, the UCRB showed a positive trend, indicating a wet period. The western parts of the UCRB were predominantly affected by droughts. Among the stations, the Khorram Abad station exhibited the most statistically significant trend at the 99% confidence level (Z > 2.57). A temporal trend analysis of droughts revealed more positive and negative abrupt changes in the UCRB than in Lorestan. This indicates a higher degree of small-scale variability in the UCRB compared to Lorestan. This study indicates that factors such as elevation, land use changes, and proximity to water sources may contribute to the observed variations in drought trends. Additionally, the findings highlight that rising temperatures have a significantly greater impact on drought severity than reductions in precipitation. This study provides a temperature-responsive method for drought assessments, supporting the development of adaptive strategies that address snowmelt variability, seasonal water availability, and shifting drought patterns in cold regions. Full article
(This article belongs to the Special Issue Drought Monitoring, Prediction and Impacts (2nd Edition))
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