Water, Geohazards, and Artificial Intelligence

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

Deadline for manuscript submissions: closed (20 December 2023) | Viewed by 16559

Special Issue Editor


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Guest Editor
Department of Earth Sciences, Utrecht University, Utrecht, Netherlands
Interests: environmental hydrogeology; artificial intelligence; geohazards; morphotectonics; geology; Earth sciences
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The increasing global impact of geohazards, which is connected to ongoing climate change, weathering, hydrological changes, subsidence, a lack of vegetation, and human activities, emphasizes the role of water from different viewpoints and at different scales; these range from microscopic porous media to regional studies, and from modeling based on observed data to laboratory experiments, which appear to be the most promising approaches to water-related geohazards.

On this basis, we are running a Special Issue on recent advances in water-related geohazards using artificial intelligence and integrated methods.

We would like to invite scientists in this field to contribute to this Special Issue, which will focus broadly on the review, analysis, mapping, prediction, experimentation, susceptibility analysis, monitoring, and modeling of water-related geohazards such as landslides and slope instabilities, as well as the analysis of early-warning definitions based on artificial intelligence findings.

We welcome contributions on newly developed monitoring instruments, methods, techniques, and approaches, as well as relevant case studies on water, geohazards, and AI. Topics of interest include: landslides, qanats, slope stabilities, floods, geotechnical hazard mapping, porous media, and their cascading combinations.

Dr. Reza Derakhshani
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

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

  • landslides
  • slope stability
  • artificial intelligence
  • experiments and models
  • natural hazards
  • porous media
  • geotechnical hazards
  • geomorphology and climate change
  • remote sensing and GIS analysis
  • morphotectonics
  • water basins
  • watershed morphometric indices
  • debris flow
  • water table
  • groundwater seepage
  • failure mechanism
  • hydrogeology

Published Papers (12 papers)

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Research

Jump to: Review

16 pages, 5579 KiB  
Article
Changes in the Hydrological Characteristics of the Attabad Landslide-Dammed Lake on the Karakoram Highway
by Yousan Li, Hongkui Yang, Youhui Qi, Wenqian Ye, Guangchao Cao and Yanhe Wang
Water 2024, 16(5), 714; https://doi.org/10.3390/w16050714 - 28 Feb 2024
Viewed by 610
Abstract
Understanding the evolving hydrological characteristics of landslide-induced barrier lakes is crucial for flood control, forecasting, early warning, and safety measures in reservoir areas. This study examines the changes in the hydrological characteristics of the Attabad landslide-dammed lake over the past decade after the [...] Read more.
Understanding the evolving hydrological characteristics of landslide-induced barrier lakes is crucial for flood control, forecasting, early warning, and safety measures in reservoir areas. This study examines the changes in the hydrological characteristics of the Attabad landslide-dammed lake over the past decade after the occurrence of the landslide, focusing on lake area dynamics and sediment concentration. High-resolution satellite images from QuickBird, Pleiades, and WorldView2 over seven periods were analyzed. The findings indicate that the lake area has gradually decreased, with the center of mass shifting towards the lake dam, indicating a trend towards stability. The suspended sediment in the barrier lake is distributed in a strip running from north to south, then northeast to southwest, with the sediment concentration decreasing from the lake entrance to the dam and from the lake bank to the center. Over time, the average sediment concentration has decreased from 2010 to 2020, with higher concentrations in summer than in winter. Notably, during the 2017–2020 period, the lower-middle parts of the lake experienced a higher sediment concentration, while the dam area witnessed lower concentrations, thereby reducing the sediment impact on the dam. Furthermore, the sediment content in the middle of the dammed lake is relatively high, which may lead to the formation of a new dammed dam in the middle and the division of the original dammed lake into two smaller lakes, which will affect the stability of the dammed lake. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence)
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14 pages, 5463 KiB  
Article
Risk Colored Snake (RCS): An Innovative Method for Evaluating Flooding Risk of Linear Hydraulic Infrastructures
by José-Luis Molina, Santiago Zazo, Fernando Espejo, Carmen Patino-Alonso, Irene Blanco-Gutiérrez and Domingo Zarzo
Water 2024, 16(3), 506; https://doi.org/10.3390/w16030506 - 05 Feb 2024
Viewed by 894
Abstract
Floods are probably the most hazardous global natural event as well as the main cause of human losses and economic damage. They are often hard to predict, but their consequences may be reduced by taking the right precautions. In this sense, hydraulic infrastructures, [...] Read more.
Floods are probably the most hazardous global natural event as well as the main cause of human losses and economic damage. They are often hard to predict, but their consequences may be reduced by taking the right precautions. In this sense, hydraulic infrastructures, such as dams, are generally the most widely used management elements to significantly mitigate this natural risk. However, others, such as linear ones, mainly ditches and canals, can both in themselves be potentially active risk-generating factors and vectors of flooding risk propagation. The aim of this research is to develop an accurate and detailed technique for assessing the intrinsic risk of these infrastructures due to flood events. This is performed based on two key factors: the proximity to urban areas and the water level reached in the infrastructures. Consequently, this research is developed through a double geomatic and hydraulic component organized into four steps: topological processing, parameter computation, risk calculation, and development of the Risk Colored Snake (RCS) technique. This was successfully applied to the network of irrigation ditches of Almoradí in Alicante (Spain), which is characterized by a high exposure level to flood hazards. RCS is a valuable tool to easily assess the potential risk of each section of the linear hydraulic infrastructures. By means of color-coding RCS, it is simpler for the end user to quickly detect potentially problematic locations in an accurate and detailed manner. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence)
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23 pages, 9033 KiB  
Article
Optimized Wavelet and Wavelet Packet Transform Techniques for Assessing Crack Behavior in Curved Segments of Arched Beam Bridges Spanning Rivers
by Liang Chen, Xingrong Lu, Daping Deng, Mehdi Kouhdarag and Yimin Mao
Water 2023, 15(22), 3977; https://doi.org/10.3390/w15223977 - 16 Nov 2023
Viewed by 775
Abstract
Our study focuses on the dynamic transient analysis of arched beam bridges over rivers, which face unique geohazards and challenges, including vibrations and dynamic loads that can affect structural integrity. The finite element software ANSYS v. 19.3 was employed to assess acceleration time [...] Read more.
Our study focuses on the dynamic transient analysis of arched beam bridges over rivers, which face unique geohazards and challenges, including vibrations and dynamic loads that can affect structural integrity. The finite element software ANSYS v. 19.3 was employed to assess acceleration time histories at various bridge positions. Using MATLAB, we conducted wavelet packet decomposition to extract insights from the data, specifically isolating river-induced influences. In this article, the introduction of the wavelet packet rate index (WPERI) is presented as a novel metric for the detection of cracks in the curved bridge segments over rivers. The WPERI proves reliable in accounting for the river environment’s impact on structural integrity. Our findings highlight the sensitivity and precision of the WPERI in accurately detecting cracks and vulnerabilities in these riverine bridges. By combining WPT, finite element analysis, and signal decomposition, our research offers insights into tailored crack detection methods for riverine bridges. This study underscores the potential of WPT as a tool for identifying and characterizing cracks in curved bridge elements over rivers. The innovative WPERI provides a holistic approach to addressing structural issues, thus enhancing bridge durability amid changing environmental conditions. It contributes significantly to structural engineering and paves the way for the further exploration of river-specific crack detection techniques. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence)
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14 pages, 10184 KiB  
Article
Source Discrimination of Mine Water by Applying the Multilayer Perceptron Neural Network (MLP) Method—A Case Study in the Pingdingshan Coalfield
by Man Wang, Jianguo Zhang, Xinyi Wang, Bo Zhang and Zhenwei Yang
Water 2023, 15(19), 3398; https://doi.org/10.3390/w15193398 - 28 Sep 2023
Viewed by 807
Abstract
In a complex multiaquifer mine, discriminant approaches that have previously been presented cannot successfully locate water sources. With multiple processing layers, computing models may learn representations of data at various levels of abstraction. Modern technology in many domains has significantly enhanced these models. [...] Read more.
In a complex multiaquifer mine, discriminant approaches that have previously been presented cannot successfully locate water sources. With multiple processing layers, computing models may learn representations of data at various levels of abstraction. Modern technology in many domains has significantly enhanced these models. The problem of distinguishing the source of mine water in mines and tunnels has been addressed by studying the hydrochemical components of the Pingdingshan coalfield and applying the multilayer perceptron neural network (MLP) method to discriminate the source of the mine water. There were five types of mine water in the Pingdingshan coalfield. Each type of water was encoded with the numbers 0 to 4. The one-hot code method was used to encode the numbers, which is the output set. On the basis of hydrochemical data processing, the MLP model was developed using a characteristic ion contrast on aquifers with distinctive chemical properties. The research results show that two hidden layers (with 10 neurons in each hidden layer) for the model were fit for completing the prediction process with a better performance. This approach enabled us to discriminate water sources for the Pingdingshan coalfield and could be tried for other coalfields with similar hydrogeological conditions. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence)
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16 pages, 6454 KiB  
Article
In2O3/NIO/MOS2 Composite as a Novel Photocatalytic towards Imatinib and 5-Fluorouracil Degradation
by Nasirodin Khashi and Mohammad Hossein Sayadi
Water 2023, 15(18), 3263; https://doi.org/10.3390/w15183263 - 14 Sep 2023
Viewed by 719
Abstract
Photocatalysts with high efficiency in water and wastewater treatment have gained increasing attention in recent years. This study synthesized an In2O3/NiO/MoS2 composite using the hydrothermal method and characterized its crystal structure, particle size, morphology, elemental purity, and optical [...] Read more.
Photocatalysts with high efficiency in water and wastewater treatment have gained increasing attention in recent years. This study synthesized an In2O3/NiO/MoS2 composite using the hydrothermal method and characterized its crystal structure, particle size, morphology, elemental purity, and optical properties. This nanocomposite exhibits high photocatalytic activity under visible light radiation. It achieved efficiencies of 91.57% and 88.23% in decomposing Imatinib and 5-fluorouracil, respectively. The formation of heterogeneity between MoS2 and NiO enhances the photocatalytic activity, which facilitates the separation and transfer efficiency of photo-generated electron-hole pairs, increases the catalytic active sites, and inhibits the rate of electron-hole recombination. The photocatalytic mechanism shows that both O2− and H+ are reactive species for the degradation of the studied pollutant. The stability and reusability tests deposited that the In2O3/NiO/MoS2 composite photocatalyst has superior stability during four reuse cycles. The results of the study show that a unique photocatalyst system can provide a new perspective and create new opportunities for the design of efficient composite photocatalysts. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence)
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16 pages, 30611 KiB  
Article
Investigating Earthquake-Induced Changes in the Persian Gulf Marginal Strip, Using Sentinel-1A Images and Radar Interferometry
by Mohammad Mohammadhasani, Fateme Kamali, Ahmad Rashidi, Mobin Bahrampour, Shahram Shafieibafti, Razieh Abbaspour and Reza Derakhshani
Water 2023, 15(17), 3108; https://doi.org/10.3390/w15173108 - 30 Aug 2023
Viewed by 781
Abstract
Geohazards, such as earthquakes, pose significant threats to human life and infrastructure in various regions across the globe. Iran, in particular, is highly vulnerable to earthquakes due to its unique structural and tectonic characteristics. Therefore, it is crucial to monitor geohazards in order [...] Read more.
Geohazards, such as earthquakes, pose significant threats to human life and infrastructure in various regions across the globe. Iran, in particular, is highly vulnerable to earthquakes due to its unique structural and tectonic characteristics. Therefore, it is crucial to monitor geohazards in order to mitigate their impacts. Several techniques, including the global positioning system, geodesy, tacheometry, and mapping cameras, have been developed for this purpose. Among these methods, radar interferometry has emerged as a particularly accurate and cost-effective approach. It is capable of operating under all weather conditions, 24 h a day, and can cover large areas with high spatial and temporal resolution. In this research, we employed Sentinel 1A images and radar interferometry to investigate the changes in the Earth’s surface following earthquakes in the marginal strip of the Persian Gulf. Specifically, our focus was on earthquakes in Bandar Khamir, and we analyzed the Earth’s surface changes three days and fifteen days after the events. The findings of our study revealed that the most significant uplift occurred around Bandar Khamir, with an uplift rate of 14 cm. Conversely, the highest subsidence was observed near Bandar Charak, with a subsidence of 12 cm. Furthermore, we observed a rise of 32 cm around the eastern and northern regions of Bandar Khamir 11 days after the initial period, accompanied by a subsidence of 31 cm around Bandar Lange and Bandar Charak. These results underscore the importance of continuous monitoring of earthquakes and their impact on the Earth’s surface, particularly in coastal areas where the effects on the water table and coastal infrastructure can be severe. In conclusion, this study highlights the significance of employing radar interferometry as a powerful tool for monitoring and assessing the impacts of earthquakes. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence)
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24 pages, 4470 KiB  
Article
Enhancing Urban Surface Runoff Conveying System Dimensions through Optimization Using the Non-Dominated Sorting Differential Evolution (NSDE) Metaheuristic Algorithm
by Ahmed Cemiloglu, Licai Zhu, Biyun Chen, Li Lu and Yaser A. Nanehkaran
Water 2023, 15(16), 2927; https://doi.org/10.3390/w15162927 - 14 Aug 2023
Cited by 1 | Viewed by 772
Abstract
Rapid urban development and increase in construction have significantly altered the surface coverage of cities, resulting in a rise in impervious surfaces such as roofs, streets, and pavements. These changes act as barriers against rainwater infiltration into the soil, leading to a substantial [...] Read more.
Rapid urban development and increase in construction have significantly altered the surface coverage of cities, resulting in a rise in impervious surfaces such as roofs, streets, and pavements. These changes act as barriers against rainwater infiltration into the soil, leading to a substantial increase in surface runoff. Managing surface runoff has become a critical task in civil engineering and urban planning, as it can mitigate damage and provide opportunities for utilizing excess water. However, traditional flood control and guidance systems tend to be extensive and expensive, prompting researchers to explore cost-effective alternatives that consider all design parameters and variables. In this research, we propose an innovative approach that combines the NSDE (non-dominated sorting differential evolution) metaheuristic algorithm as an optimizer with the SWMM (storm water management model) as a simulator. The objective is to design efficient surface runoff collection networks by thoroughly investigating their hydraulic behaviors. This study focuses on the Chitgar watershed in Tehran, Iran, utilizing the SWMM model and NSDE multi-objective metaheuristic algorithm to determine the optimal dimensions of the channel and its intersecting structures. The aim is to minimize costs and reduce water leakage from the network. A comparison is made between the optimized design results and the existing network plan (without any design modifications). The analysis reveals substantial reductions in water leakage for all three design scenarios: a 7.66% reduction when considering only bridges, a 7.35% reduction with only the canal, and an impressive 95.26% reduction when both the canal and bridges are incorporated. These findings demonstrate the superiority of the optimized designs in terms of cost-effectiveness and the efficient management of surface runoff. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence)
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20 pages, 4855 KiB  
Article
Optimal Exploitation of Urban Water Supply Networks Based on Pressure Management with the Nondominated Sorting Differential Evolution (NSDE) Algorithm
by Ahmed Cemiloglu, Zhu Licai, Abbas Ugurenver and Yaser A. Nanehkaran
Water 2023, 15(14), 2583; https://doi.org/10.3390/w15142583 - 14 Jul 2023
Cited by 1 | Viewed by 1275
Abstract
Urban water distribution networks are crucial infrastructures for providing essential services to society, but their exorbitant costs and limited water resources make their optimization a critical research area. Optimal management and design of these networks can help to reduce costs and enhance their [...] Read more.
Urban water distribution networks are crucial infrastructures for providing essential services to society, but their exorbitant costs and limited water resources make their optimization a critical research area. Optimal management and design of these networks can help to reduce costs and enhance their efficiency while meeting technical, economic, and quality standards. In particular, the management of network pressure is critical for reducing leakage in water distribution systems. Thus, this study aimed to investigate two objective functions for optimizing the water distribution network: (i) minimizing costs while considering the number of pressure-relief valves, and (ii) minimizing network pressure by observing the optimal pressure range. To achieve this, the Nondominated Sorting Differential Evolution (NSDE) multi-objective metaheuristic algorithm was employed as the optimization tool, and a computer program was written in MATLAB software for solving the optimization models. EPANET software was also used for hydraulic simulation of the water distribution network. The efficiency and capabilities of these models were tested on the case study of the third district of Mashhad in Iran. The results indicated that the installation and adjustment of pressure-relief valves in accordance with the positions and optimal settings of the output of the proposed models significantly improved the desired goals, particularly the average pressure of the network. As an example of optimization, the study achieved a 56.12% reduction in pressure compared to the case without a plan, considering five pressure-relief valves. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence)
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20 pages, 20211 KiB  
Article
Effects of Spatial Data Acquisition on Determination of a Gravel-Bed River Geomorphology
by Mohammadreza Maddahi and Majid Rahimpour
Water 2023, 15(9), 1719; https://doi.org/10.3390/w15091719 - 28 Apr 2023
Cited by 1 | Viewed by 1210
Abstract
Bed irregularities of water bodies play a significant role in many hydraulic and river engineering experiments and models. Accurate measurement of river geomorphology requires great fieldwork effort. Optimizing the dataset size of measured points will reduce the time and costs involved. In this [...] Read more.
Bed irregularities of water bodies play a significant role in many hydraulic and river engineering experiments and models. Accurate measurement of river geomorphology requires great fieldwork effort. Optimizing the dataset size of measured points will reduce the time and costs involved. In this study, the geomorphology of a gravel bed river reach was measured using different spatial acquisition methods. Digital elevation models were created for each measurement method and the volumes of under/overestimation were calculated. The results show that the sampling methods had more effect on the accuracy of the interpolated geomorphology than the density of the measured points. By choosing an optimized sampling method, the measurement efforts decreased to less than 50%, with negligible errors of around 15 m3 and 10 m3 over and underestimation, respectively, in a water body area of around 2200 m2. These findings help to provide more accurate geomorphological data with less effort as inputs for experimental and numerical models to derive better results. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence)
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13 pages, 5708 KiB  
Article
Investigation of the Leachate Effect on Permeability and Geotechnical Characteristics of Fine-Grained Soil Modified Using Nanoclay–Nanofiber Composites
by Mehdi Nikbakht, Fariba Behrooz Sarand, Rouzbeh Dabiri and Masoud Hajialilue Bonab
Water 2023, 15(2), 294; https://doi.org/10.3390/w15020294 - 11 Jan 2023
Cited by 3 | Viewed by 1713
Abstract
Using low permeability soils in landfill liners is a guaranteed leachate control and prevents leakage which causes environmental pollution. In this matter, the application of new technologies such as nano provides more capable filters that are used for reducing leachate pollutants and modifying [...] Read more.
Using low permeability soils in landfill liners is a guaranteed leachate control and prevents leakage which causes environmental pollution. In this matter, the application of new technologies such as nano provides more capable filters that are used for reducing leachate pollutants and modifying the geotechnical properties of liners. The presented study attempted to conduct experimental research on nanoclay–nanofiber composite usage to control landfill liner permeability and observe its impact on the geotechnical characteristics of liners which provide a strong barrel for leachate leakage prevention and increase the liner durability for crack generations. In this regard, a total of 120 different geotechnical experiments were performed on mixed improved fine-grained soil samples which were categorized into four groups including nanoclay additives, nanofiber additives, nanocomposite additives, and control samples (without additives). According to the experimental results, permeability decreased, and geotechnical properties (e.g., Atterberg limits, unconfined compressive strength, cohesion, and friction) were increased with increasing nanocomposite content in the soil. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence)
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13 pages, 2059 KiB  
Article
Armourstone Quality Analysis for Coastal Construction in Chabahar, Southeast Iran
by Mohyeddin Ahrari-Roudi and Mojtaba Zaresefat
Water 2023, 15(1), 151; https://doi.org/10.3390/w15010151 - 30 Dec 2022
Viewed by 1469
Abstract
Natural stones (armourstones) of varying sizes and qualities are frequently used to construct breakwaters to protect coastal engineering structures from wave actions for economic reasons. Time-related armourstone deterioration in the form of abrasion and disintegration may result in structural damage. Therefore, it is [...] Read more.
Natural stones (armourstones) of varying sizes and qualities are frequently used to construct breakwaters to protect coastal engineering structures from wave actions for economic reasons. Time-related armourstone deterioration in the form of abrasion and disintegration may result in structural damage. Therefore, it is necessary to investigate the performance and quality of the armourstones, which should be robust and long-lasting. The study aimed to examine the quality of two distinct types of rocks from three breakwaters used as armourstones in the Chabahar region and compare the results to the observed field performance. This study aimed to illustrate why it is crucial to characterise rocks thoroughly before deciding which ones to use in a particular project and to evaluate how well current classification techniques account for the observed field performance of stones that may have complex geological compositions. The physical and mechanical properties of the rock were evaluated through both on-site observation and laboratory testing. The results indicated that the class of rocks used in the breakwater had a wide range of suitability ratings. It was discovered that sedimentary rocks have the best water absorption and porosity properties. In addition, age is a positive factor, as the rate of destruction decreases with age. Component and particle size can also play a role in lithology, which is a significant factor in the rock’s durability. Also, the findings demonstrated that the marine organisms in the rock component play an important role in the stability of these structures, even though rock mass breakwaters are less qualified for breakwater construction as per international coastal engineering standards. According to the findings, a breakwater made of lumachel rock boulders, or alternatively sandstone boulders, will last the longest. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence)
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Review

Jump to: Research

23 pages, 1988 KiB  
Review
Revolutionizing Groundwater Management with Hybrid AI Models: A Practical Review
by Mojtaba Zaresefat and Reza Derakhshani
Water 2023, 15(9), 1750; https://doi.org/10.3390/w15091750 - 02 May 2023
Cited by 8 | Viewed by 4051
Abstract
Developing precise soft computing methods for groundwater management, which includes quality and quantity, is crucial for improving water resources planning and management. In the past 20 years, significant progress has been made in groundwater management using hybrid machine learning (ML) models as artificial [...] Read more.
Developing precise soft computing methods for groundwater management, which includes quality and quantity, is crucial for improving water resources planning and management. In the past 20 years, significant progress has been made in groundwater management using hybrid machine learning (ML) models as artificial intelligence (AI). Although various review articles have reported advances in this field, existing literature must cover groundwater management using hybrid ML. This review article aims to understand the current state-of-the-art hybrid ML models used for groundwater management and the achievements made in this domain. It includes the most cited hybrid ML models employed for groundwater management from 2009 to 2022. It summarises the reviewed papers, highlighting their strengths and weaknesses, the performance criteria employed, and the most highly cited models identified. It is worth noting that the accuracy was significantly enhanced, resulting in a substantial improvement and demonstrating a robust outcome. Additionally, this article outlines recommendations for future research directions to enhance the accuracy of groundwater management, including prediction models and enhance related knowledge. Full article
(This article belongs to the Special Issue Water, Geohazards, and Artificial Intelligence)
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