Risk Analysis in Landslides and Groundwater-Related Hazards
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrogeology".
Deadline for manuscript submissions: closed (20 March 2024) | Viewed by 22563
Special Issue Editors
Interests: hydrogeology; environmental impact assessment; natural hazard susceptibility; spatial modeling; machine learning; geology; civil engineering
Special Issues, Collections and Topics in MDPI journals
Interests: natural hazards; water resources; engineering geology; GIS; machine learning; soft computing; remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: natural hazards; environmental geology; engineering geology; GIS; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: hydrogeology; environmental impact assessment; natural hazard susceptibility; spatial modeling; machine learning; geology; civil engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Many disasters related to global climate change and water, such as landslides, groundwater, and floods, occur all over the world each year. In most cases, natural disasters of this kind have caused serious financial and human losses worldwide. It is mainly caused by the gradual or extreme action of factors related to the climate, structure, geological morphology process, and human activities that have a negative impact on the geological environment. Although the scientific community tries to simulate these phenomena with high accuracy to obtain the risk of landslide- and groundwater-related hazards, some characteristics leading to their evolution and occurrence are still unclear. Natural disasters seem to be complex in nature, as are the changes in frequency, speed, duration, and affected areas. All these characteristics make it a rather difficult task to fully understand the mechanism behind its evolution and occurrence.
Accurate and timely prediction of these disasters and identification of their risks can not only protect people from injury and death but also reduce property losses and economic losses caused by these disasters. Advances in science and technology have greatly improved our disaster management capabilities. However, it is still necessary to apply advanced prediction tools to various landslide- and groundwater-related disasters to analyze their risks.
This Special Issue aims to provide an outlet for peer-reviewed publications that implement state-of-the-art methods and techniques incorporating spatial analysis, AI, and ML methods to map, monitor, evaluate, and assess landslide and groundwater disasters, emphasize our understanding of disaster mechanisms, and build a safer future. This Special Issue focuses on the risks related to landslide and groundwater hazards and invites contributions using the most advanced research as well as case studies and lessons learned from failure, including but not limited to:
- Sequential landslide monitoring, earthquake landslide, landslide caused by rainfall, geotechnical engineering problems related to landslide, landslide risk prediction and assessment, landslide triggering and failure mechanism, numerical modeling and GIS application zoning of hazards, the development of new monitoring techniques and forecasting models for early warning systems, etc.
- Mechanism of groundwater related disasters, numerical analysis method of rock soil fluid solid coupling, groundwater evolution law, spatial isotope data and model, groundwater seismic effect model, groundwater risk assessment and dynamic control, water resources assessment and management, groundwater dating and paleohydrology, new trends and challenges of isotope hydrology, etc.
Prof. Dr. Wei Chen
Dr. Paraskevas Tsangaratos
Dr. Ioanna Ilia
Dr. Xia Zhao
Guest Editors
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Keywords
- landslide susceptibility
- landslide hazard analysis
- risk analysis
- risk evaluation
- risk management
- rainfall
- groundwater
- modelling
- monitoring
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