Advances in Hydrogeological Research

The release of pollutants from lead-zinc mining areas poses a significant threat to the environment, making pollution tracing crucial for environmental protection. However, the complexity of carbonate mining areas makes tracing these pollutants challenging. This study used δ³⁴S_SO4 and δ¹⁸O_SO4 isotopes combined with the Stable Isotope Mixing Models in R (SIMMR) to assess anthropogenic sulfate sources in the Daliangzi mining area. The river water types were mainly Ca²⁺-Mg²⁺-HCO₃⁻, and SO₄²⁻, which are significantly influenced by dolomite dissolution. The δ³⁴S_SO4 values ranged from 6.47‰ to 17.96‰ and the δ¹⁸O_SO4 values ranged from −5.66‰ to 13.98‰. The SIMMR results showed that evaporite dissolution in tributaries, driven by gypsum, contributed 31% of sulfate, while sulfide oxidation, sewage, and atmospheric deposition contributed 19%, 18%, and 24%, respectively. The tailings pond near Xincha Creek has a higher sulfate release potential than the processing plant near Cha Creek. In the mainstream, sulfide oxidation contributed 25%, primarily from mine drainage. Anthropogenic sources, including sulfide oxidation, fertilizers, and sewage, made up about 50% of the total sulfate, with sulfide oxidation accounting for half of this input. The strong correlation between the Zn and SO₄²⁻ concentrations (R² = 0.82) and between the Zn and the contribution from the sulfide oxidation (R² = 0.67) indicates their co-release during sulfide oxidation, making SO₄²⁻ a proxy for tracing Zn sources. This study highlights the utility of δ³⁴S_SO4 and δ¹⁸O_SO4 with SIMMR in tracing anthropogenic inputs and underscores the significant impact of mining on river systems and the sulfur cycle. Full article

Groundwater is a significant source of water supply, especially with depleted and quality-deteriorated surface water. The number of drilled boreholes for groundwater has been increased, but erroneous results often occur while selecting sites for digging boreholes. This makes it necessary to follow a science-based method indicating potential zones for groundwater storage. The LithoSFR Model is a systematic approach we built to create an indicative map with various categories for potential groundwater sites. It is based mainly on retrieved geospatial data from satellite images and from available thematic maps, plus borehole data. The geospatial data were systematically manipulated in a GIS with multi-criteria applications. The novelty of this model includes the empirical calculation of the level each controlling factor (i.e., weights and rates), as well as the LithoSFR Model, adopting new factors in its design. This study was applied on a representative Mediterranean region, i.e., Lebanon. Results showed that 44% of the studied region is characterized by a very high to high potentiality for groundwater storage, mainly in areas with fractured and karstified carbonate rocks. The obtained results from the produced map were compared with datasets which were surveyed from representative boreholes to identify the discharge in the dug boreholes, and then to compare them with the potential zones in the produced map The reliability of the produced map exceeded 87%, making it a significant tool to identify potential zones for groundwater investment. Full article

Climate change and human activities affect regional sediment transport and ecological environment construction. Investigating sediment transport and its influencing factors in the Yihe River Basin (YHRB) will provide guidance for regional soil and water conservation and sustainable development. We analyzed the chronological changes, cycles, spatial distribution and influencing factors using Mann–Kendall (M-K) trend analysis, wavelet analysis, and the Pettitt mutation point (PMP) test, then quantified the role of precipitation and human activities in sediment transport changes. The results showed that annual precipitation decreased marginally, whereas sediment load has noticeably declined. Four precipitation cycles were observed: 4–8a, 9–14a, 16–19a, and 20–28a, where 9–14a was dominant; sediment transport cycles were tracked: 3–5a, 9–15a, and 30a, where 30a was dominant with a decreasing trend. The sediment load was higher in the central, northern, and southwestern sub-basins of the YHRB, while it was lower in the southeast. The contribution of human activities and precipitation changes to sediment transport was 73.14% and 26.86% in transitional phase I (1965–1980) and 71.97% and 28.03% in transitional phase II (1981–2020), respectively. Hydraulic engineering construction, water resource development, land-use changes, and soil and water conservation measures intercepted precipitation and sediment, making them the primary factor affecting sediment transport changes in the YHRB. Full article

Aquifers are complex systems that present significant challenges in terms of characterization due to the lack or absence of watershed-scale hydrogeological information. An alternative to address the need to characterize watershed-scale aquifer behavior is recession flow analysis. Recession flows are flows sustained by groundwater release from the aquifer. Aquifer behavior can be characterized using recession flow records available from gauging stations, and therefore an indirect measure of aquifer behavior is obtained through watershed-scale recession flow records and analysis. This study seeks to identify the minimum time period necessary to characterize the behavior of groundwater storage systems in watersheds with different geological, morphological, and hydrological characteristics. To this end, various watersheds in south-central Chile underwent recession flow analysis, with eight time periods considered (2, 3, 4, 5, 10, 15, 20, and 25 years). The results indicate that 25 years of records are sufficient for the characterization of watershed-scale aquifer behavior, along with the representation of the groundwater storage-release (S-Q) process in watersheds with different geological, morphological, and hydrological characteristics. Additionally, the results show that an initial characterization of the groundwater system behavior in watersheds with different geological characteristics can be carried out with two years of records. This information could be important for practical engineering and the study of groundwater systems in watersheds with limited hydrological and hydrogeological information. Full article

The rural population in the Dry Zone of Sri Lanka is largely affected by Chronic Kidney Disease of Unknown etiology (CKDu). According to the multidisciplinary research carried out so far, quality of groundwater is considered one of the possible causative factors for CKDu. Therefore, assessment of the quality of groundwater being used for drinking and its evolution mechanism is the key to identifying the linkage between CKDu and drinking water. This study aimed to perform a detailed investigation on groundwater sources using isotopic, chemical, and hydrogeological methods in the CKDu-endemic (site A) and the control area (sedimentary formation—site B) in the Malwathu Oya basin and the control areas in the Malala Oya basin (site C) selected for a systematic comparison. Our investigation shows that elevated levels of TDS, magnesium, and fluoride in the shallow groundwater affected by climatic, geochemical, and hydrogeological processes may contribute to the CKDu in the Dry Zone of Sri Lanka. All the groundwater samples analysed have exceeded the hardness threshold. Prominent Mg hardness proportion together with excess F⁻ in the CKDu endemic area may produce nephrotoxic MgF₂ complexes that may trigger renal damage. In contrast, NaF complexes in the CKDu control area leads to reduction of F⁻ toxicity in the human body. Elevated F⁻ and Mg²⁺ are found in site A, low F⁻ and high Mg²⁺ in site B, and either combinations of low F⁻ and low Mg²⁺, high F⁻ and low Mg²⁺, or low F⁻ with high Mg²⁺ in site C. TDS, hardness, Mg²⁺, Na⁺, and F⁻ are formed with different mechanisms in the three selected areas. The primary process that regulates the evolution of groundwater types and contents in sites A and C is the weathering of silicates. Similarly, in site A, carbonate dissolution and reverse ion exchange are quite strong. Cation exchange and evaporite dissolution are more pronounced in site C. Shallow groundwaters are evapo-concentrated, hence their quality deteriorates more significantly than the deep groundwater in the CKDu endemic area. Dilution decreases the ion content in site A while evaporite dissolution increases it in site C after the rainy season. Evaporation and seawater mixing affect the quality of groundwater in site B. It is also found that a statistically significant difference exists in the F⁻/Na⁺, F⁻/Mg²⁺, and F⁻/Ca²⁺ between the endemic and control areas. Intensive rock weathering combined with desorption has added excess F⁻ to the groundwater in site A, while cation exchange and fluorite dissolution are contributing factors in site C. Full article

The controlling hydrogeochemical processes of an intermontane aquifer in central Mexico were identified through multivariate statistical analysis. Hierarchical cluster (HCA) and k-means clustering analyses were applied to Na⁺, K⁺, Ca²⁺, Mg²⁺, F⁻, Cl⁻, SO₄²⁻, NO₃⁻, HCO₃⁻, As, pH and electrical conductivity in 40 groundwater samples collected from shallow and deep wells, where As and F⁻ are contaminants of concern. The effectiveness of each hierarchical and k-means clustering method in explaining solute concentrations within the aquifer and the co-occurrence of arsenic and fluoride was tested by comparing two datasets containing samples from 40 and 36 wells, the former including ionic balance outliers (>10%). When tested without outliers, cluster quality improved by about 5.4% for k-means and 7.3% for HCA, suggesting that HCA is more sensitive to ionic balance outliers. Both algorithms yielded similar clustering solutions in the outlier-free dataset, aligning with the k-means solution for all 40 samples, indicating that k-means was the more robust of the two methods. k-means clustering resolved fluoride and arsenic concentrations into four clusters (K1 to K4) based on variations in Na⁺, Ca²⁺, As, and F⁻. Cluster K2 was a Na-HCO₃ water type with high concentrations of As and F. Clusters K1, K3, and K4 exhibited a Ca-HCO₃, Na-Ca-HCO₃, and Ca-Na-HCO₃ water types, respectively, with decreasing As and F concentrations following the order K2 > K3 > K1 > K4. The weathering of evaporites and silicates and Na-Ca ion exchange with clays were the main processes controlling groundwater geochemistry. The dissolution of felsic rocks present in the aquifer fill is a likely source of As and F⁻, with evaporation acting as an important concentration factor. Full article

Soil moisture is among the most essential variables in hydrology and earth science. Many satellite missions, such as AMSR-E/2, have been launched to observe it in broader spatial coverage to overcome the shortage of in situ observations. However, the satellite soil moisture products have been reported to comprise errors caused by the so-called “temperature effects” widely observed in dielectrically measured in situ volumetric soil water content (SWC). In this work, we confirmed the existence of these errors in AMSR2 soil moisture products. A new algorithm was developed to remove these errors using satellite data at ascending and descending overpasses. The application of this algorithm to both satellite and in situ data of SWC and soil temperature at the Mongolia site shows that the difference between SWC values at ascending and descending overpasses caused by temperature effects is effectively removed. We assess the impact of this removal method on satellite data by comparing it with in situ data, utilizing metrics such as the correlation coefficient and other widely adopted evaluation methods. It is shown that the difference between the original and corrected in situ SWC is much smaller than that between AMSR2 and in situ SWC, either corrected or not. The results indicate that the metric values between the corrected AMSR2 and in situ SWC, after removing apparent differences caused by temperature effects, slightly improved compared to those between the original AMSR2 and in situ SWC. Though these findings imply that the removed errors may not be the most dominant, considering the current significant difference between AMSR2 and in situ SWC, the removal makes the ascending and descending data have close characteristics. It may allow using data at both ascending and descending overpasses and double the temporal resolution of AMSR2 SWC data. Full article

Large rivers without hydrological data from remote sensing observations have recently become a hot research topic. The Irrawaddy River is among the major tropical rivers worldwide; however, published hydrological data on this river have rarely been obtained in recent years. In this paper, based on the existing measured the total suspended matter flux (F_TSM) and discharge data for the Irrawaddy River, an inversion model of the total suspended matter concentration (C_TSM) is constructed for the Irrawaddy River, and the C_TSM and F_TSM from 1990 to 2020 are estimated using the L1 products of Landsat-8 OLI/TIRS and Landsat-5 TM. The results show that over the last 30 years, the F_TSM of the Irrawaddy River decreased at a rate of 3.9 Mt/yr, which is significant at the 99% confidence interval. An increase in the vegetation density of the Irrawaddy Delta has increased the land conservation capacity of the region and reduced the inflow of land-based total suspended matter (TSM). The F_TSM of the Irrawaddy River was estimated by fusing satellite data and data measured at hydrological stations. The research method employed in this paper provides a new supplement to the existing hydrological data for large rivers. Full article

River water-level prediction is crucial for mitigating flood damage caused by torrential rainfall. In this paper, we attempt to predict river water levels using a deep learning model based on radar rainfall data instead of data from upstream hydrological stations. A prediction model incorporating a two-dimensional convolutional neural network (2D-CNN) and long short-term memory (LSTM) is constructed to exploit geographical and temporal features of radar rainfall data, and a transfer learning method using a newly defined flow–distance matrix is presented. The results of our evaluation of the Oyodo River basin in Japan show that the presented transfer learning model using radar rainfall instead of upstream measurements has a good prediction accuracy in the case of torrential rain, with a Nash–Sutcliffe efficiency (NSE) value of 0.86 and a Kling–Gupta efficiency (KGE) of 0.83 for 6-h-ahead forecast for the top-four peak water-level height cases, which is comparable to the conventional model using upstream measurements (NSE = 0.84 and KGE = 0.83). It is also confirmed that the transfer learning model maintains its performance even when the amount of training data for the prediction site is reduced; values of NSE = 0.82 and KGE = 0.82 were achieved when reducing the training torrential-rain-period data from 12 to 3 periods (with 105 periods of data from other rivers for transfer learning). The results demonstrate that radar rainfall data and a few torrential rain measurements at the prediction location potentially enable us to predict river water levels even if hydrological stations have not been installed at the prediction location. Full article

The Grombalia aquifer constitutes a complex aquifer system formed by shallow, unconfined, semi-deep, and deep aquifers at different exploitation levels. In this study, we focused on the upper aquifer, the Wadi El Bey coastal aquifer. To assess natural aquifer recharge, we used a novel physiography-based method that uses soil texture-dependent potential infiltration coefficients and monthly rainfall data. The developed transient flow model was then applied to compute the temporal variation in the groundwater level in 34 observation wells from 1973 to 2020, taking into account the time series of spatially variable groundwater recharge, artificial groundwater recharge from 5 surface infiltration basins, pumping rates on 740 wells, and internal prescribed head cells to mimic water exchange between the wadis and aquifer. The quantified deviations in the computed hydraulic heads from measured water levels are acceptable because the database used to construct a scientifically sound and reliable groundwater model was limited. Further work is required to collect field data to quantitatively assess the local inflow and outflow rates between surface water and groundwater. The simulation of 12 climate scenarios highlighted a bi-structured north—south behaviour in the hydraulic heads: an increase in the north and a depletion in the south. A further increase in the pumping rate would, thus, be severe for the southern part of the Wadi El Bey aquifer. Full article