Advancements in Water and Soil Related Disaster Prevention: Exploring Emerging Topics and Innovations

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

Deadline for manuscript submissions: 20 June 2024 | Viewed by 4571

Special Issue Editors


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Guest Editor
Department of Civil Engineering, Dong-A University, Busan 49315, Republic of Korea
Interests: climate change; rainfall-runoff analysis; water resources management; remote sensing; big data; floods; droughts

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Guest Editor
Department of Civil and Environmental Engineering, Chung-Ang University, Seoul 06974, Republic of Korea
Interests: hydrology; climate change; sustainability; machine learning; artificial intelligence; big data; sensor networks; IoT (Internet of Things); early warning systems; hydrological modeling, disaster and risk management
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Fire and Disaster Prevention, Konkuk University, 268 Chungwon-daero, Chungju 27478, Republic of Korea
Interests: geotechnical property; geophysical survey; elastic wave; electromagnetic wave; landslide; geotechnical disaster prevention

Special Issue Information

Dear Colleagues,

Water-related and soil-related hazards are known as natural disasters with high risk, individually or collectively, in that they can cause serious impacts on both civilizations and ecosystems. Water-related hazards like floods and droughts are becoming more severe and frequent under the impact of climate change. The soil-related hazards, like landslides and slope failures, usually occur without any previous notice, often causing property damage and casualties.

To secure our resilience from the abruptly changing world, it is necessary to understand the most recent data or techniques in order to prevent these types of disasters in advance. Recently, there have been attempts to advance the conventional hydrological methods based on big data analysis, machine learning, novel statistical methods, etc. In the geotechnical field, innovative sensors have been recently developed to measure the spatiotemporal responses of geomaterials.

The Special Issue titled “Advancements in Water and Soil Related Disaster Prevention: Exploring Emerging Topics and Innovations” aims to provide the latest advances in understanding extreme hydrological processes and characterizing geomaterials with innovative sensors and their applications, focusing on exploring the complex interplay between water and soil divisions through interdisciplinary research. Through these interdisciplinary investigations, the Special Issue seeks to contribute to a more comprehensive understanding of the interplay between water and soil divisions and to identify pathways towards a more sustainable and equitable resource management. The topics covered by this special issue include, but are not limited to, novel approaches to rainfall-runoff processes; climate change impact assessment using big data; machine learning or artificial intelligence for floods and droughts; landslide forecasting; innovative sensor technologies; and advances in the characterization of geomaterials.

Dr. Wooyoung Na
Dr. Changhyun Jun
Dr. Sang Yeob Kim
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • rainfall-runoff processes
  • climate change impact
  • floods and droughts
  • landslide
  • geotechnical property
  • geophysical survey
  • innovative sensors
  • big data analysis
  • machine learning

Published Papers (5 papers)

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Research

20 pages, 6695 KiB  
Article
Morphometric Analysis Using Geographical Information System and the Relationship with Precipitation Quantiles of Major Dam Basins in South Korea
by Sejeong Oh, Jinwook Lee, Jongjin Baik, Changhyun Jun and Eui Hoon Lee
Water 2024, 16(7), 1053; https://doi.org/10.3390/w16071053 - 06 Apr 2024
Viewed by 478
Abstract
Geographic information system (GIS) and remote sensing (RS) technologies are potent tools for evaluating various aspects of basin hydrology. This study conducted a morphological analysis using GIS tools on seven major dam basins in Korea. Additionally, long-term RS-based precipitation data were obtained, the [...] Read more.
Geographic information system (GIS) and remote sensing (RS) technologies are potent tools for evaluating various aspects of basin hydrology. This study conducted a morphological analysis using GIS tools on seven major dam basins in Korea. Additionally, long-term RS-based precipitation data were obtained, the probability of precipitation was estimated, and their relationship was examined. The findings are summarized as follows. It was observed that most major dam basins in Korea, which were the focus of this study, had a broad radial shape, and due to the mountainous topography, there was a notable presence of numerous river branches. Through the estimation of probability precipitation and its comparison with morphological indices, it was noted that wider basins tend to have higher rainfall amounts and a relatively uniform spatial distribution. Furthermore, it was found that the more uniform the spatial distribution, the simpler the river network. This trend becomes more pronounced in relation to basin size for longer durations, and in spatial dispersion for shorter durations. However, it is crucial to acknowledge that the complexity of these relationships is also affected by other factors such as climate, altitude, and local geographical conditions. Full article
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13 pages, 4221 KiB  
Article
Study on Calculating Appropriate Impact Assessment for LID Facility Using A-I-R Curve
by Youngseok Song, Yoonkyung Park, Moojong Park and Jingul Joo
Water 2023, 15(23), 4198; https://doi.org/10.3390/w15234198 - 04 Dec 2023
Viewed by 806
Abstract
Low impact development (LID) facilities are designed to maintain water circulation functions on the surface and subsurface. LID facilities can be applied to various areas and are expected to have both short-term and long-term effects, making them widely installed in urban areas. In [...] Read more.
Low impact development (LID) facilities are designed to maintain water circulation functions on the surface and subsurface. LID facilities can be applied to various areas and are expected to have both short-term and long-term effects, making them widely installed in urban areas. In this study, our objective is to calculate the A-I-R (Area ratio-rainfall Intensity-Runoff reduction rate) curve by applying design standards to tree filter boxes, garden plant pots, infiltration ditches, and rain barrels among various LID facilities. The analysis was conducted by constructing a SWMM-LID model and analyzing 209 items, considering the area ratio (A) and rainfall intensity (I) of the LID facilities. The runoff reduction rate (R) varies by LID facility according to the A-I-R curve. It reaches up to 100.0% for rain barrels, up to 30.0% for infiltration ditches, up to 20.0% for garden plant pot, and up to 12.0% for tree filter boxes. If the A-I-R curve of the LID facility is applied to the design standards, it is expected to facilitate the design of the facility’s size and inlet according to the target reduction rate. Full article
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22 pages, 11726 KiB  
Article
Evaluation of Methods for Estimating Long-Term Flow Fluctuations Using Frequency Characteristics from Wavelet Analysis
by Jinwook Lee, Geonsoo Moon, Jiho Lee, Changhyun Jun and Jaeyong Choi
Water 2023, 15(16), 2968; https://doi.org/10.3390/w15162968 - 17 Aug 2023
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Abstract
This study was aimed at exploring different indices to quantify flow fluctuations and calculate long-term flow indicators (L-FFI). Three approaches were considered to calculate the indicators: Method (1)—calculate the annual index and then average it; Method (2)—average the annual flow characteristics and then [...] Read more.
This study was aimed at exploring different indices to quantify flow fluctuations and calculate long-term flow indicators (L-FFI). Three approaches were considered to calculate the indicators: Method (1)—calculate the annual index and then average it; Method (2)—average the annual flow characteristics and then calculate the index; and Method (3)—calculate the index considering all available data. Wavelet analysis was performed to evaluate the derived L-FFI. The evaluation index was based on the period corresponding to the highest spectral power from the wavelet transformation of seasonally differenced data. Strong and negative positive correlations were observed between the L-FFI and the high- and low-flow variations, respectively. The correlation coefficient (R) between L-FFIs and the frequency with maximum global wavelet power showed that Method (2) consistently yielded the most reliable results across various facets, having a determination coefficient of 0.73 (R2) on average. In the regionalization analysis using the Ward method, it was consistently observed that the two largest dams (the Chungju Dam and the Uiam Dam) were significantly differentiated from the other dams. Furthermore, Method (2) showed the most similar characteristics to the clustering of the wavelet features. The outcomes are expected to facilitate long-term water resource management. Full article
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21 pages, 5245 KiB  
Article
Shrinkage Characteristics and Microstructure Evolution of Yili Loess under Different Wetting and Drying Cycles
by Aynur Abduhell, Zizhao Zhang, Wenyu Cheng and Yanyang Zhang
Water 2023, 15(16), 2932; https://doi.org/10.3390/w15162932 - 14 Aug 2023
Viewed by 749
Abstract
The loess in Yili Valley is prone to landslides in the rainy season. We studied the influence law of shrinkage and the microstructure of the loess in Yili Valley under different wetting and drying cycles. Considering the climatic conditions and sampling depth of [...] Read more.
The loess in Yili Valley is prone to landslides in the rainy season. We studied the influence law of shrinkage and the microstructure of the loess in Yili Valley under different wetting and drying cycles. Considering the climatic conditions and sampling depth of the study area, shrinkage tests were carried out under six kinds of dry and wet cycling paths. The fracture changes and shrinkage characteristics of the loess under different dry–wet cycling times were analyzed, and the deformation characteristics of the loess during the process of water-loss shrinkage under the dry–wet cycling conditions were discussed. The results show that (1) there is an exponential relationship between the number of dry and wet cycles and the final shrinkage rate. The influence of dry and wet cycles on the final shrinkage rate is significant in the early stage. (2) With the increase in the number of dry and wet cycles, the decline in the final shrinkage rate decreases, and the final shrinkage rate and shrinkage coefficient of soil also show a decreasing trend, while the soil sample area first increases and then gradually decreases, and the surface shrinkage cracking is gradually stable. The surface porosity tends to increase. (3) Under the action of repeated wet expansion and dry contraction, irregular cracks are produced inside the soil body, which leads to the increase in soil permeability, reduces the strength of the soil body, reflects the phenomenon of strength deterioration, and thus indicates the stability of loess slopes. The research results of this paper can provide an important parameter basis for the prevention and control of loess landslide geological disasters in Yili Valley. Full article
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18 pages, 2046 KiB  
Article
Influence of Rainfall Pattern on Wetness Index for Infinite Slope Stability Analysis
by Wooyoung Na, Changhyun Jun and Sang Yeob Kim
Water 2023, 15(14), 2535; https://doi.org/10.3390/w15142535 - 11 Jul 2023
Viewed by 1199
Abstract
Landslides are one of the riskiest disasters combining excessive rainfall and unstable slope that a wetness index can quantify. The wetness index generated by water infiltration considering the rainfall pattern such as cumulated rainfall, rainfall duration and rainfall intensity should be estimated for [...] Read more.
Landslides are one of the riskiest disasters combining excessive rainfall and unstable slope that a wetness index can quantify. The wetness index generated by water infiltration considering the rainfall pattern such as cumulated rainfall, rainfall duration and rainfall intensity should be estimated for the slope stability analysis. Even though the infiltration capacity of soils has been largely focused to evaluate the slope stability, the temporal patterns of rainfall have commonly been ignored or assumed as a steady state for the prediction of the slope failure in the previous studies. Thus, this study focuses more on evaluating the influence of various rainfall patterns on the slope stability, and compares it with an actual landslide incident that occurred in 2011, in Korea. The factor of safety (FS) considering the time-dependent wetness index variation is used to determine the slope stability. For the various rainfall designs, the uniform rainfall distribution, Yen and Chow, Mononobe, alternating block and second quartile Huff models are adopted. Thereafter, the FS variations from five models are compared with an actual landslide incident in Seoul, Korea. Among the rainfall designs, the models that consider the abrupt rainfall intensity capture the landslide time with an FS < 1. Therefore, the appropriate adoption of a rainfall distribution model should be highlighted for landslide prediction. Full article
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