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Geohazards Monitoring Assessment: Earth-Observation Techniques
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Geohazards Monitoring Assessment: Earth-Observation Techniques

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

Deadline for manuscript submissions: closed (10 April 2024) | Viewed by 15085

Special Issue Editors

Prof. Dr. Shibiao Bai

E-Mail Website
Guest Editor
College of Marine Science and Engineering, Nanjing Normal University, Nanjing, China
Interests: landslide, multi-hazard; spatial analysis; remote sensing application; hazard and risk assessment
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jinghui Fan

E-Mail Website
Guest Editor
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources (AGRS), China Geological Survey, Beijing, China
Interests: synthetic aperture radar (SAR) interferometry; remote sensing application; ground deformation; GIS application
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the increase in extreme weather and the expansion and intensity of human activities, the impact of geological disasters on human beings has become more and more remarkable. Frequently and widely distributed geohazards and hazard chains are a major threat to the sustainable development of human production and life. Earth-observation technology has unique advantages in long-time series regional data accumulation, multi-parameter high-frequency monitoring, multi-factor comprehensive analysis, and emergency relief support. There have been many contributions to geohazard detection and characterization. However, considering the geohazard conditioning factors of geological, geomorphological, and hydrological predictors, and also the geohazard-triggering factors of the short-term cumulative rainfall, antecedent rainfall, rain infiltration, and soil hydrological conditions, the time evolution monitoring and permanent real-time early warning system of geohazards still need strengthening. With the introduction of new technologies and methods such as 3S technology and intelligent algorithms, monitoring and assessment studies are necessary to adapt to the rapid development of Earth observation technology. The aim of this research topic is to explore the application of Earth observation systems in geohazard monitoring and risk assessment. We welcome research topics on time evolution monitoring, early warning systems, and hazard assessment of different types of single geohazards or multiple geohazards. We also welcome a wider range of geohazard-related research to join our Special Issue.

Prof. Dr. Shibiao Bai
Prof. Dr. Jinghui Fan
Guest Editors

Manuscript Submission Information

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Keywords

  • geohazard
  • monitoring and assessment
  • Earth-observation
  • ground motion
  • GIS
  • case study

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Published Papers (4 papers)

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Research

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14 pages, 9031 KiB  
Article
Dam Surface Deformation Monitoring and Analysis Based on PS-InSAR Technology: A Case Study of Xiaolangdi Reservoir Dam in China
by Qun Wang, Yufei Gao, Tingting Gong, Tiejun Liu, Zhengwei Sui, Jinghui Fan and Zhenyu Wang
Water 2023, 15(18), 3298; https://doi.org/10.3390/w15183298 - 19 Sep 2023
Cited by 4 | Viewed by 2289
Abstract
The Xiaolangdi Dam is a key project for the control and development of the Yellow River. It bears the functions of flood control, controlling water and sediment in the lower reaches, ice prevention, industrial and agricultural water supply, power generation, and so on. [...] Read more.
The Xiaolangdi Dam is a key project for the control and development of the Yellow River. It bears the functions of flood control, controlling water and sediment in the lower reaches, ice prevention, industrial and agricultural water supply, power generation, and so on. Its safety is related to people’s life and property safety and local economic and social development. It is of great significance to carry out comprehensive and regular deformation monitoring for dams since the deformation is an important evaluation index for dam safety. Interferometric Synthetic Aperture Radar (InSAR) technology has been a rapidly evolving technology in the field of space geodesy in recent years. It offers advantages such as high monitoring precision, extensive coverage, and high monitoring point density, making it a powerful tool for monitoring deformations in hydraulic engineering projects. Based on Sentinel-1 data covering the Xiaolangdi Dam from September 2020 to November 2022, the PS-InSAR technique was used to obtain the surface deformation of the Xiaolangdi Dam, and reservoir water level data on image acquisition dates were obtained for joint analysis. The results show that there is a large deformation in the center of the dam crest of the Xiaolangdi Dam, while both sides of the slope and downstream dam foot are relatively stable. The time series deformation of the dam body is closely related to the reservoir water level change. When the water level increases, the dam body tends to deform downstream; when the water level decreases, the dam body tends to deform upstream. The deformation and water level of the Xiaolangdi Dam exhibit a clear negative correlation. There is no significant cumulative deformation on the dam slopes or at the base of the dam. However, cumulative deformation occurs over time in the central area of the dam’s crest. The deformation process at the central area of the dam’s crest follows a continuous and non-disruptive pattern, which is consistent with the typical deformation behavior of the Xiaolangdi earth–rock dam structure. Therefore, it is judged that the current deformation of the Xiaolangdi Dam does not impact the safe operation of the dam. InSAR technology enables the rapid acquisition of high-precision, high-density deformation information on the surfaces of reservoir dams. With an increasing number of radar satellites in various frequency bands, such as Sentinel-1 and TerraSAR-X, there is now an ample supply of available data sources for InSAR applications. Consequently, InSAR technology can be extended to routine monitoring applications for reservoir dam deformations, especially for small and medium-sized reservoirs that may not be equipped with ground measurement tools like GNSS. This holds significant importance and potential for enhancing the safety monitoring of such reservoirs. Full article
(This article belongs to the Special Issue Geohazards Monitoring Assessment: Earth-Observation Techniques)
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19 pages, 4386 KiB  
Article
A Hybrid Coupled Model for Groundwater-Level Simulation and Prediction: A Case Study of Yancheng City in Eastern China
by Manqing Hou, Suozhong Chen, Xinru Chen, Liang He and Zhichao He
Water 2023, 15(6), 1085; https://doi.org/10.3390/w15061085 - 12 Mar 2023
Cited by 2 | Viewed by 1710
Abstract
The over-exploitation of groundwater has led to a significant drop in groundwater levels, which may lead to a series of geological disasters and ecological environmental problems such as ground subsidence and ground cracks. Therefore, through studying the dynamic change characteristics of groundwater, we [...] Read more.
The over-exploitation of groundwater has led to a significant drop in groundwater levels, which may lead to a series of geological disasters and ecological environmental problems such as ground subsidence and ground cracks. Therefore, through studying the dynamic change characteristics of groundwater, we can grasp the dynamic changes in groundwater level over time and invert the hydrogeological parameters, which provides an important basis for the management of groundwater resources. In this study, the confined aquifer III groundwater between 2005 and 2014 in Yancheng City was selected as the research object, and the Back Propagation (BP) neural network, Spatial-temporal Auto Regressive and Moving Average (STARMA) model, and BP-STARMA model were used to predict the spatial and temporal evolution trends of groundwater. In order to compare the prediction effectiveness of the BP-STARMA model, the fitting and prediction accuracies of the three models were measured from the perspectives of time and space. The results of the Relative Squared Error (RSE), Normal Mean Squared Error (NMSE), Root-Mean-Squared Error (RMSE), and Mean Absolute Error (MAE) were used to assess the robustness of the BP-STARMA model. The results showed that the fitting of the RMSE of BP-STARMA model was reduced by 39.92%, 38.35%, 30.25%, 31.55%, and 13.57% compared with the STARMA model, and by 22.2%, 8.7%, 15.9%, 28.5%, and 4.42% compared with the BP neural network model, respectively. Collectively, this shows that the BP-STARMA model has a better spatiotemporal prediction of groundwater level than the STARMA and BP neural network models, is more applicable to spatially continuous time-discrete spatiotemporal sequences, and is more applicable to spatiotemporal sequences that respond to natural geographic phenomena. Full article
(This article belongs to the Special Issue Geohazards Monitoring Assessment: Earth-Observation Techniques)
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18 pages, 66017 KiB  
Article
InSAR Displacement with High-Resolution Optical Remote Sensing for the Early Detection and Deformation Analysis of Active Landslides in the Upper Yellow River
by Kuan Tu, Shirong Ye, Jingui Zou, Chen Hua and Jiming Guo
Water 2023, 15(4), 769; https://doi.org/10.3390/w15040769 - 15 Feb 2023
Cited by 3 | Viewed by 2189
Abstract
Frequent landslides and other geological disasters pose a serious threat to human life and infrastructure in the Upper Yellow River. Detecting active landslides and ascertaining their impact necessitate the determination of deformation characteristics. In this study, we developed an integrated method combining interferometric [...] Read more.
Frequent landslides and other geological disasters pose a serious threat to human life and infrastructure in the Upper Yellow River. Detecting active landslides and ascertaining their impact necessitate the determination of deformation characteristics. In this study, we developed an integrated method combining interferometric synthetic aperture radar and high-resolution optical satellite remote sensing to detect active landslides in the Upper Yellow River region from Longyang Gorge to Lijia Gorge. Sentinel-1 satellite data from January 2019 to April 2021 with ascending and descending orbits were adopted to obtain deformation using the STACKING and interferometric point target analysis techniques. A 97.08% overlap rate in the detected results from the two InSAR technologies confirmed the suitability of both approaches. The missing detection rates (6.79% & 8.73%) from single line-of-sight (LOS) InSAR results indicate the necessity of different orbit direction data. Slight deformation rate changes (<4 mm/month) before and after rainy seasons of the Lijia Gorge landslide group indicate that precipitation exerted little impact on slope activity. This study supports the feasibility of integrated methods for the detection and analysis of active landslides in the Upper Yellow River and other regions. Full article
(This article belongs to the Special Issue Geohazards Monitoring Assessment: Earth-Observation Techniques)
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Review

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32 pages, 16478 KiB  
Review
A Review of Spatial Variations of Multiple Natural Hazards and Risk Management Strategies in Pakistan
by Muhammad Awais Hussain, Zhang Shuai, Muhammad Aamir Moawwez, Tariq Umar, Muhammad Rashid Iqbal, Muhammad Kamran and Muhammad Muneer
Water 2023, 15(3), 407; https://doi.org/10.3390/w15030407 - 18 Jan 2023
Cited by 10 | Viewed by 7848
Abstract
Natural hazards are dynamic and unpredictable events that are a continuous threat to global socio-economic development. Humans’ reactions to these catastrophes are influenced by their proximity to the hazards and their ability to anticipate, resist, cope with, and recover from their consequences. Due [...] Read more.
Natural hazards are dynamic and unpredictable events that are a continuous threat to global socio-economic development. Humans’ reactions to these catastrophes are influenced by their proximity to the hazards and their ability to anticipate, resist, cope with, and recover from their consequences. Due to climatic changes, the risk of multiple natural hazards is expected to increase in several regions of Pakistan. There is a pressing need to understand the spatial discrepancies of natural hazards due to climate change and identifying the regions that require special measures to increase resilience, achieve adaptation, and sustainable development goals. This paper synthesizes the related literature to understand spatial variations of natural hazards due to climate changes across Pakistan. The Emergency Events Database (EM-DAT), National Aeronautics and Space Administration Global Landslide Catalog (NASA-GLC), National Disaster Management Authority (NDMA), and Pakistan Meteorological Department (PMD) are utilized to analyze spatial discrepancies and vulnerabilities to natural hazards. This study unveils that Pakistan’s current risk analysis and management strategies seem to be obsolete compared to global trends. Because of spatial variations of hazards, most research work on hazard risk assessments and risk management focuses on a single hazard, neglecting the co-occurrence impact of different natural hazards. Very limited studies are included in comprehensive multi-hazard risk strategies. Therefore, in Pakistan, risk management would require integrated multi-hazard risk assessment approaches to detect, analyze, measure, and evaluate various natural hazards, their effects, and interconnections. Moreover, the Pakistan governmental institutes dealing with natural hazards should focus on pre-disaster mitigation and resilience techniques instead of investing only in post-disaster relief activities. Full article
(This article belongs to the Special Issue Geohazards Monitoring Assessment: Earth-Observation Techniques)
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