Ulaanbaatar (UB), the capital of Mongolia, is one of the fastest-growing cities in the developing world. Due to increasing demand driven by rapid population and industrial growth, sustainable water resource management is required. Therefore, we investigated sustainability in UB from the perspective of water quality. During five sampling campaigns, we collected 135 water samples (58 from bedrock wells, 44 from shallow wells tapped into the alluvial aquifer, 24 from rivers, and 9 from springs). The hydrochemistry of the water samples was controlled by two major processes: NO₃ contamination, and silicate and carbonate mineral weathering. The groundwater samples could be classified into three groups based on their NO₃ levels and spatial distribution. Group 1 had natural background NO₃ levels (median: 1.7 mg/L) and silicate weathering–dominant water–rock interactions and was distributed in the alluvial aquifer along the floodplain. Group 2 was dominated by carbonate weathering processes, had a maximum NO₃ concentration of 47.4 mg/L, and was distributed between the riverbank and upslope area; overall, it reflected ongoing contamination. Group 3 was distributed in the upslope Ger districts and showed significant NO₃ contamination (range: 64.0–305.4 mg/L) due to dense and poor living conditions. The stable isotope signatures indicated that the city’s major water supply from riverbank filtration (i.e., Group 1 wells) mixed dynamically with the river; therefore, it showed no sign of NO₃ contamination. However, the isotope values and bedrock groundwater quality of wells in Groups 2 and 3 implied that they were closely connected, with the same water source, and showed a strong potential for expanding NO₃ contamination toward Group 1 wells. To support sustainable development in UB, the implementation of appropriate institutional measures to protect and preserve water resources, with systematic spatio-temporal monitoring and a focus on Ger districts, is crucial.

When groundwater drought occurs, baseflow discharges to surface-water bodies will be reduced and then domestic and agricultural water usage becomes at risk of insufficient supply. Thus, in this study, several methods for groundwater drought assessment were tested with long-term monitoring water-level data in the study area to preserve groundwater sustainability from drought, principally caused by reduced precipitation and propagated through agricultural drought and groundwater drought. Because of the Monsoon climate on the Korean Peninsula, the groundwater storage (or water-level) is secured until the end of summer, then falls by natural discharge during the dry seasons of autumn, winter and the following spring. Thus, the rainfall in the wet season seems to mainly influence groundwater storage until the spring of the following year. As the groundwater level (GWL) declines due to natural drainage and the use of agricultural water increases by the end of the dry season (October–May), the GWL will become lowered below the critical level. Below this level, sufficient water supply is not secured. Using the Standardized Precipitation Index (SPI), threshold method and 95% probability occurrence method, drought detection and the frequency of drought are compared. Groundwater drought using the threshold method results in more frequent occurrence than using the SPI method. The 95% occurrence method responds to severe drought but it also has weakness in missing the man-induced GWL decline in every spring season. For groundwater drought assessment, an appropriate drought index should be utilized according to climatic conditions and catchment characteristics. In the study area, variations of the both natural and anthropogenic effects are mixed and the threshold method is more suitable as a measure for preventing water resources shortage.

The sustainability of rural areas depends on the availability of water resources. The Mangyeong River Basin (MRB) in Korea faces a water supply shortage for agriculture and industry. Based on 11-year (2005–2015) precipitation and groundwater monitoring data, groundwater sustainability was evaluated in terms of natural and man-made factors and their spatio-temporal variations. A precipitation time-series revealed a declining trend, but there were different seasonal trends between wet and dry periods, with declining and rising trends, respectively. Groundwater hydrographs from five national groundwater monitoring wells showed temporal variations. Groundwater wells located in downstream areas showed both recharge from upgradient areas and local man-made impacts (e.g. from pumping), resulting in an ambiguous relationship between precipitation and water levels. However, other monitoring wells in the upstream areas displayed water level responses to precipitation events, with a declining trend. Using the standardized precipitation index at a time scale of 12 months (SPI-12) and the standardized groundwater level anomaly, meteorological and groundwater drought conditions were compared to infer the relationship between precipitation deficit and groundwater shortage in the aquifer. The SPI results indicated severely dry to extremely dry conditions during 2008–2009 and 2015. However, the standardized groundwater level anomaly showed various drought conditions for groundwater, which were dependent on the site-specific hydrogeological characteristics. Finally, groundwater sustainability was assessed using water budget modelling and water quality data. Presently, if groundwater is used above 39.2% of the recharge value in the MRB, groundwater drought conditions occur throughout the basin. Considering water quality issues, with nitrate being elevated above the natural background, this critical abstraction value becomes 28.4%. Consequently, in the MRB, sustainable groundwater management should embrace both natural and human-induced factors to regulate over-exploitation and prevent contamination.

This study focused on characterising aquifer systems based on water-level changes observed systematically at 159 paired groundwater monitoring wells throughout Korea. Using spectral analysis, principal component analysis (PCA), and cross-correlation analysis with linear regression, aquifer conditions were identified from the comparison of water-level changes in shallow alluvial and deep bedrock monitoring wells. The spectral analysis could identify the aquifer conditions (i.e., unconfined, semi-confined and confined) of 58.5% of bedrock wells and 42.8% of alluvial wells: 93 and 68 wells out of 159 wells, respectively. Even among the bedrock wells, 50 wells (53.7%) exhibited characteristics of the unconfined condition, implying significant vulnerability of the aquifer to contaminants from the land surface and shallow depths. It appears to be better approach for deep bedrock aquifers than shallow alluvial aquifers. However, significant portions of the water-level changes remained unclear for categorising aquifer conditions due to disturbances in data continuity. For different aquifer conditions, PCA could show typical pattern and factor scores of principal components. Principal component 1 due to wet-and-dry seasonal changes and water-level response time was dominant covering about 55% of total variances of each aquifer conditions, implying the usefulness of supplementary method of aquifer characterisation. Cross-correlation and time-lag analysis in the water-level responses to precipitations clearly show how the water levels in shallow and deep wells correspond in time scale. No significant differences in time-lags was found between shallow and deep wells. However, clear time-lags were found to be increasing from unconfined to confined conditions: from 1.47 to 2.75 days and from 1.78 to 2.75 days for both shallow alluvial and deep bedrock wells, respectively. In combination of various statistical methods, three types of water-level fluctuation patterns were identified from the water-level pairs: Type I of identical aquifer systems (77.8%), Type II of the different aquifer systems with different recharge flow paths (9.5%), and Type III of unmatched aquifer system pairs and correlations (12.7%). Type I and II could be used as verification of aquifer condition in the paired monitoring system. However, Type III shows the complexity of water-level fluctuation in different aquifer conditions. This study showed that confined or not-confined conditions are not directly related to the depth of wells in the aquifer. Therefore, the utilisation of groundwater as a water-supply source should be carefully designed, tested for its hydrogeologic conditions, and managed to ensure sustainable quantity and quality.

This paper describes the impacts of the M5.8(5.1) Gyeongju earthquakes on groundwater levels using data obtained from a unique coastal monitoring well. The monitoring strategy integrates conventional water level monitoring with periodic, continuous measurements of temperature and electrical conductivity (EC) within the water column of the well. Another important component of the monitoring system is a new instrument, the InterfacEGG, which is capable of dynamically tracking the freshwater‐saltwater interface. Although the system was set up to monitor seawater intrusion related to over‐pumping, as well as rainfall and tidal effects, it recorded impacts associated with a large earthquake and aftershocks approximately 241 km away. Seismic energies associated with the M5.8(5.1) Gyeongju earthquakes induced groundwater flows to the monitoring well through fractures and joints in the crystalline basement rocks. Temperature and EC logging data showed that the EC vertical profile declined from an average of approximately 5300 to 4800 μS/cm following the earthquakes. The temperature profile showed a trend toward lower temperatures as the depth increased, a feature not commonly observed in previous studies. Data from the InterfacEGG suggested that the rise in EC was not due to the saltwater intrusion, but from the tendency for brackish water entering the borehole to induce convective mixing at deeper depths as the seismic waves travel through the well‐aquifer system. The increase in groundwater levels was caused by pulse of colder, less brackish water flowing into the well because of the earthquake. This behavior reflects an enhancement in rock permeability by removing precipitates and colloidal particles from clogged fractures, which improve the hydraulic connection with a nearby unit with a higher hydraulic head. This study suggests there is value added with a more aggressive monitoring strategy.

Significant variation in the precipitation events caused by global climate change has made it difficult to manage water resources due to the increased frequency of unexpected droughts and floods. Under these conditions, groundwater is needed to ensure a sustainable water supply; thus, estimates of precipitation recharge are essential. In this study, we derived an apparent recharge coefficient (ARC) from a modified water table fluctuation equation to predict groundwater storage changes due to precipitation events. The ARC is calculated as the ratio of the recharge rate over the specific yield (R/S_y); therefore, it implicitly expresses variation in S_y. The ARC varies spatially and temporally, corresponding to the precipitation events and hydrogeological characteristics of unsaturated materials. ARCs for five monitoring wells from two basins in Korea in different seasons were calculated using a 10-year groundwater level and weather dataset for 2005–2014. Then, the reliability of the ARCs was tested by the comparison of the predicted groundwater level changes for 2015 and 2016 with observed data. The root mean square error ranged from 0.03 to 0.09 m, indicating that the predictions were acceptable, except for one well, which had thick clay layers atop the soil layer; the low permeability of the clay slowed the precipitation recharge, interfering with groundwater level responses. We performed a back-calculation of R from the S_y values of the study areas; the results were similar to those obtained via other methods, confirming the practical applicability of the ARC. In conclusion, the ARC is a viable method for predicting groundwater storage changes for regions where long-term monitoring data are available, and subsequently will facilitate advanced decision making for allocating and developing water resources for residents, industry, and groundwater-dependent ecosystems.