Hydrological Modeling and Assessment of Meteorological and Geological Hazards

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

Deadline for manuscript submissions: 20 June 2025 | Viewed by 2497

Special Issue Editors


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Guest Editor
1. Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region, Ministry of Education, Chang’an University, Xi’an, China
2. School of Water and Environment, Chang’an University, Xi’an, China
Interests: soil environmental quality; soil erosion; hydrology ecology; geological disaster
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Water and Environment, Chang’an University, Xi’an 710054, China
Interests: hydraulic engineering; hydrology and water resources; environmental engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, rapid population growth has led to enormous amounts of pressure being put on resources and the environment. Continuous human activities and climate change have caused the deterioration of ecological environments, resulting in a series of meteorological, geological, and other natural disasters. Disaster prevention and reduction is a common goal pursued by all countries in the world. In natural disaster risk monitoring and assessment, hydrological ecological models and risk assessment indicators can give full consideration to the advantages of numerical simulation, correlation analysis, and generalized reasoning methods and have been widely used in the past 20 years. Understanding the impact of human activities and climate change in key regions is conducive to regional natural disaster risk management, the establishment of a natural disaster risk assessment system, and the provision of scientific support for disaster prevention and reduction. However, controlling disaster risk completely seems impractical, especially since quantifying human activities is often difficult. In these cases, reliable methods such as hydrological models and numerical simulations seem to be the most promising way to reduce natural disasters and increase social resilience.

Given this scientific framework, we would like to invite scientists involved in this research field to contribute to this Special Issue, which will broadly focus on the analysis, evaluation, and simulation of natural disasters caused by climate change, human activities, or other drivers, including the risk management and assessment of meteorological disasters and geological disasters. Therefore, manuscripts dealing with case studies of climate change simulation, the impacts of human activities, large-scale or regional drought disasters, the assessment of geological environment trends, and risk analysis of natural disasters at different scales will also be welcomed.

Prof. Dr. Aidi Huo
Prof. Dr. Pingping Luo
Dr. Chunli Zheng
Guest Editors

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Keywords

  • climate change
  • meteorological and geological disaster
  • risk assessment
  • hydrological simulation

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Published Papers (2 papers)

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Research

18 pages, 4808 KiB  
Article
Spatiotemporal Variation of Soil Erosion in the Northern Foothills of the Qinling Mountains Using the RUSLE Model
by Yuxiang Cheng, Aidi Huo, Feng Liu, Adnan Ahmed, Mohamed EL-Sayed Abuarab, Ahmed Elbeltagi and Dmitri Evgenievich Kucher
Water 2024, 16(15), 2187; https://doi.org/10.3390/w16152187 - 1 Aug 2024
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Abstract
The Qinling region in central China, known as the ‘Dragon Vein of China’, is a vital ecological barrier facing significant soil erosion challenges. This study aims to enhance soil erosion management and analyse the spatiotemporal changes of soil erosion in the northern foothills [...] Read more.
The Qinling region in central China, known as the ‘Dragon Vein of China’, is a vital ecological barrier facing significant soil erosion challenges. This study aims to enhance soil erosion management and analyse the spatiotemporal changes of soil erosion in the northern foothills of the Qinling Mountains. We collected data on precipitation, terrain, land use types, and soil in the designated region. Using GIS technology and the Revised Universal Soil Loss Equation (RUSLE) model, we created a detailed soil erosion map and analysed its evolution from 2018 to 2022. Results show a significant reduction in soil erosion in 2020–2021 despite a general upward trend in other years. Innovation includes integrating remote sensing with RUSLE for high-precision mapping and introducing a hierarchical approach for erosion risk assessment. The study found erosion peaks in summer and autumn, with higher levels in the southern parts compared to the northern parts. Influential factors include climate variables, human activities, soil, and vegetation types. The average soil erosion modulus in 2023 is 233.515 t/(km2·a), with total soil erosion of 85,233.046 t/a, mainly concentrated in the valley and mountain basin areas. This research provides a theoretical basis for improving the natural environment and implementing comprehensive soil and water conservation measures in the Qinling region, offering a model for similar ecological regions globally. Full article
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12 pages, 4680 KiB  
Article
Spatial Differentiation and Influencing Factors Analysis of Drought Characteristics Based on the Standardized Precipitation Index: A Case Study of the Yellow River Basin
by Qi Liu, Aidi Huo, Zhixin Zhao, Xuantao Zhao, Nazih Yacer Rebouh and Chenxu Luo
Water 2024, 16(10), 1337; https://doi.org/10.3390/w16101337 - 8 May 2024
Cited by 3 | Viewed by 1103
Abstract
It is crucial to identify drought characteristics and determine drought severity in response to climate change. Aiming at the increasingly serious drought situation in the Yellow River Basin, this study firstly selected the standardized precipitation index (SPI) and streamflow drought index (SDI) to [...] Read more.
It is crucial to identify drought characteristics and determine drought severity in response to climate change. Aiming at the increasingly serious drought situation in the Yellow River Basin, this study firstly selected the standardized precipitation index (SPI) and streamflow drought index (SDI) to analyze the characteristics of drought seasons, then identified the frequency, duration, and intensity of drought based on the run theory, and finally recognized the abrupt changing and driving factors of major drought events in specific years by the Mann–Kendall trend test. The conclusions showed the following: (1) The drought in the downstream of the Yellow River Basin was more severe than that in the upstream. The drought characteristics showed significant regional differentiation and deterioration. (2) The drought intensity and duration had an obvious spatial correlation. Compared with the other seasons, the drought duration and severity in spring and autumn were the most serious, and in winter, they showed an aggravating trend. (3) According to a time series analysis of drought conditions in the Yellow River Basin, the worst drought occurred in 1997–2001 with the least rainfall on record and a sudden rise in temperatures. This study could provide a scientific reference for agricultural drought disaster prevention and mitigation. Full article
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