Adequate groundwater development for the rural population is essential because groundwater is an important source of drinking water and agricultural water. In this study, ensemble models of decision tree-based machine learning algorithms were used with geographic information system (GIS) to map and test groundwater yield potential in Yangpyeong-gun, South Korea. Groundwater control factors derived from remote sensing data were used for mapping, including nine topographic factors, two hydrological factors, forest type, soil material, land use, and two geological factors. A total of 53 well locations with both specific capacity (SPC) data and transmissivity (T) data were selected and randomly divided into two classes for model training (70%) and testing (30%). First, the frequency ratio (FR) was calculated for SPC and T, and then the boosted classification tree (BCT) method of the machine learning model was applied. In addition, an ensemble model, FR-BCT, was applied to generate and compare groundwater potential maps. Model performance was evaluated using the receiver operating characteristic (ROC) method. To test the model, the area under the ROC curve was calculated; the curve for the predicted dataset of SPC showed values of 80.48% and 87.75% for the BCT and FR-BCT models, respectively. The accuracy rates from T were 72.27% and 81.49% for the BCT and FR-BCT models, respectively. Both the BCT and FR-BCT models measured the contributions of individual groundwater control factors, which showed that soil was the most influential factor. The machine learning techniques used in this study showed effective modeling of groundwater potential in areas where data are relatively scarce. The results of this study may be used for sustainable development of groundwater resources by identifying areas of high groundwater potential.

Recently, data mining analysis techniques have been developed, as large spatial datasets have accumulated in various fields. Such a data-driven analysis is necessary in areas of high uncertainty and complexity, such as estimating groundwater potential. Therefore, in this study, data mining of various spatial datasets, including those based on remote sensing data, was applied to estimate groundwater potential. For the sustainable development of groundwater resources, a plan for the systematic management of groundwater resources should be established based on a quantitative understanding of the development potential. The purpose of this study was to map and analyze the groundwater potential of Goyang-si in Gyeonggi-do province, South Korea and to evaluate the sensitivity of each factor by applying data mining models for big data analysis. A total of 876 surveyed groundwater pumping capacity data were used, 50% of which were randomly classified into training and test datasets to analyze groundwater potential. A total of 13 factors extracted from satellite-based topographical, land cover, soil, forest, geological, hydrogeological, and survey-based precipitation data were used. The frequency ratio (FR) and boosted classification tree (BCT) models were used to analyze the relationships between the groundwater pumping capacity and related factors. Groundwater potential maps were constructed and validated with the receiver operating characteristic (ROC) curve, with accuracy rates of 68.31% and 69.39% for the FR and BCT models, respectively. A sensitivity analysis for both models was performed to assess the influence of each factor. The results of this study are expected to be useful for establishing an effective groundwater management plan in the future.

The UN disaster report highlights that 90% of disasters from 1995 to 2015 were a consequence of hydrometeorological changes. An analysis by the World Meteorological Organization revealed that water-related disasters, including droughts, heatwaves, typhoons, and floods, which are partly driven by climate change, caused extensive global property damage and loss of life. Despite concerted global efforts for net-zero carbon emissions, there is a noticeable lack of integration of water in decarbonization strategies.Traditionally, the water sector's response to the climate crisis has primarily centered on establishing policies and systems for water management to adapt to vulnerability, rather than actively participating in greenhouse gas reduction (mitigation). This strategic preference is largely attributed to the absence of a distinct organizational classification for the water sector in the national greenhouse gas inventory, leading to an unclear identification of the sector's own emissions profile.In light of these challenges, this study addresses the critical need for assessing greenhouse gas emissions within the water sector and advocates for the establishment and implementation of carbon-neutral policies tailored specifically to the sector's unique characteristics. By delving into these imperatives, the study seeks to bridge the gap between global climate efforts and the water sector, fostering a more comprehensive and sustainable approach to climate resilience and mitigation."Within the study's scope, the organizational boundary of the water sector was meticulously delineated. It encompasses water supply, wastewater, and livestock manure treatment services, as well as water resources facilities such as dams, reservoirs, and river spaces. Comprehensive assessments were conducted to calculate greenhouse gas emissions and absorption within these boundaries. This nuanced approach aims to provide a detailed understanding of the carbon emissions associated with key components of the water sector.Moreover, the study identifies and assesses potential trajectories for attaining carbon neutrality in the water sector through the development and examination of three distinct scenarios. The demand-led scenario prioritizes water efficiency, leakage management, adoption of a vegetarian diet, and achieving energy self-sufficiency. The technology-led scenario emphasizes innovative technologies and substantial financial investments, while the combined scenario integrates elements from both the demand-led and technology-led pathways, offering a nuanced and balanced approach.In conclusion, this case study illuminates a promising trajectory toward achieving carbon neutrality in the water sector by 2050, particularly when adopting a mixed scenario that combines elements from the three outlined scenarios. The comprehensive insights garnered from this study contribute to a more sustainable, resilient, and low-carbon future, highlighting the integral role of the water sector in global climate objectives.Additionally, the study concludes that efforts towards carbon neutrality in the water sector represent a policy direction that enhances the public benefits of adaptation and reduction strategies. By actively engaging in mitigation measures, the water sector not only contributes to climate goals but also enhances its adaptive capacity, creating a synergistic approach that maximizes positive outcomes for both the environment and society. This integrated strategy highlights the potential for carbon neutrality initiatives in the water sector to serve as a model for broader climate action policies, emphasizing the interconnected benefits of sustainable practices.

Groundwater level decline and quality deterioration is continuously observed nationwide in South Korea. Meanwhile, the demand for groundwater, which is relatively stable and clean in the face of climate crisis and future industry, is increasing in South Korea. In order to meet sustainable use for growing groundwater demand, it is essential to assess groundwater resources sustainability by taking into account the economic, social, and environmental factors in management and planning of groundwater resources. This study proposes groundwater sustainability management indicators to account for these factors based on DPSIR framework. A case study is performed to assess groundwater resources sustainability on 5 river basins(Han-river, Keum-river, Nakdong-river, Youngsan-river, Seomjin-river) by using indicators with available data in South Korea. The results show that groundwater depletion and contamination is susceptible to occur nationwide with spatial variation. Renewable groundwater resources per capita is evaluated to be approximately ranged from 1,000 to 10,000 m3/yr over the nation, while less than 1,000 m3/yr in the western and southeastern parts of South Korea, which is related to high population and urbanization. Much of Groundwater abstraction occurs with respect to groundwater recharge in the easter areas. Among 5 river basins, groundwater dependence of Geum-river basin area is highest. Overall, the wester parts of Korea including Keum-river, Youngsan-river, Seomjin-river basins, are susceptible to be more stressed. Total nitrogen load is high in subbasins of Han-river and Keum-river basins, but groundwater quality index for nitrate-nitrogen shows different spatial patterns. In South Korea, total e-coli, NO3-N, and Cl- are major contaminants observed in groundwater. The case study shows that proposed groundwater sustainability management indicators can good enough to provide a general view of groundwater resources status. Proposed indicators can also be utilized to evaluate current status of groundwater and policies for National Water Management Basic Plan as well as used as elemental indicators for developing a comprehensive index for necessity. Further data collection and analysis is required for comprehensive assessment of groundwater resources management sustainability.