Ground water最新文献

Transient hydraulic tomography (THT) is proven to be effective in representing hydraulic and storage properties in diverse hydrogeologic settings. Sequential inversion of THT is computationally efficient, however, its accuracy is constrained by the number and sequence of pumping datasets used in the inversion. While signal-to-noise ratio (SNR) is commonly used to regulate the order of pumping datasets, it often disregards the information content. We propose an alternate strategy to rank the pumping ports based on the information contained in the data for use with inversion. A non-parametric Gringorten plotting position was used to generate cumulative distribution functions (CDFs) of the transient datasets, with the CDF corresponding to the maximum drawdown port set as a reference. The Kullback-Leibler divergence (KLD) is employed to quantify variations in time-drawdown datasets by statistically measuring the divergence from the reference distribution. Pumping ports are then ranked in the decreasing order of KLD and further used in the inversion. The proposed methodology is tested under a controlled environment using a laboratory sandbox model. Discrete wavelet transform (DWT) was applied to denoise the raw pumping datasets, and PEST coupled with MODFLOW was used to perform the inversion. The performance of KLD-assisted inversion (RMSE_KLD = 0.278 ± 0.177 cm) is found to be superior to SNR-assisted inversion (RMSE_SNR = 1.075 ± 0.990 cm). Further, a reduction in THT data (by 68%) by specifying a threshold on KLD (>10) has drastically reduced the computational time (by 64%) with commensurable accuracy (RMSE_KLDF = 0.265 ± 0.121 cm). Our findings lead to the conclusion that sequential inversion of THT with information-driven datasets outperforms quality-driven datasets, even with reduced pump-test data.

Jeju volcanic island of South Korea is characterized by hydrogeological heterogeneity, which has resulted in complex environments in a coastal aquifer system. The shape of the fresh-saltwater transition zone (FSTZ) and depth-dependent tidal influences on fresh-saltwater interaction in the eastern part of Jeju Island were examined by assessing geological logs from drilling cores, vertical profiles of specific conductance (SC) and temperature from geophysical logging, and performing time series analysis of groundwater level and multi-depth SC (collected from multiple sensors installed at various borehole depths). A sharp interface and step-like FSTZ were developed in the hyaloclastite and lava layers, respectively. The tidal influences on groundwater levels were highly associated with the distance from the coastline; however, SC data revealed different responses to tidal changes according to depth. Based on these data, we propose a conceptual hydrogeological model that incorporates different volcanic structures, including hyaloclastite and lava layers. Conduit flow through the highly permeable hyaloclastite layers led to the development of a sharp interface of FSTZ and disturbed the tidal signals on SC by acting as a preferential pathway for fast and abundant fresh groundwater discharge. Conversely, in the lava layers characterized by the successive formation of high- and low-permeability layers, boundary flows in the geological boundaries created a step-like FSTZ and showed a relatively high association between the tide and SC. This study highlights the crucial role of hydrogeological heterogeneity in determining the complex behaviors of fresh-saltwater interactions in the coastal aquifers of volcanic regions.

An airborne electromagnetic (AEM) survey was conducted using the Resolve™ frequency-domain system over a buried bedrock valley near Elora, Ontario, Canada. A statistical bootstrapping approach was used to establish a relationship between the electrical resistivity from spatially interpolated one-dimensional AEM resistivity models and the lithostratigraphy of Quaternary sediments logged in continuously cored holes located within and adjacent to the buried bedrock valley. Three lithology types were classified using a bootstrapping approach: (i) clay, (ii) sandy to muddy diamicton with the presence of clasts, and (iii) sand/gravel. The statistically derived ranges in electrical resistivity from the model were used to generate a lithostratigraphic model of the Quaternary deposits along the valley axis. The resulting lithology model differentiated more electrically resistive coarse-grained sand and gravel from electrically conductive finer-grained clay-rich tills; but was not able to resolve interbedded layers associated with complex fluvial deposits. Modeled Quaternary deposit architecture and bedrock morphology along two transects orthogonal to the valley axis were consistent with co-located surface electrical resistivity tomography models and borehole natural gamma logs, indicating that the AEM method, when calibrated using high-quality continuous-core logs, can support quantitative conceptualizations of complex Quaternary architecture within and around a buried bedrock valley. Key limitations in this approach were the reduced vertical resolution of the AEM method and the inability to resolve thinly bedded layers (meter scale) identified in the core logs that may have a hydrogeologic influence. This study demonstrates the utility of combining airborne electrical methods with high-resolution geological logs through statistical analysis to constrain hydrostratigraphic architecture at scales relevant to municipal groundwater flow systems.

Missing data in hydrological records can limit resource assessment, process understanding, and predictive modeling. Here, we present ARCHI (Automated Regional Correlation Analysis for Hydrologic Record Imputation), a new, open-source software package in R designed to aggregate, impute, cluster, and visualize regionally correlated hydrologic records. ARCHI imputes missing data in "target" records by linear regression using more complete "reference" records as predictors. Automated imputation is implemented using a novel, iterative algorithm that allows each site to be considered a target or reference for regression, growing the pool of complete references with each imputed record until viable gap-filling ceases. Users can limit artifacts from spurious correlations by specifying model-acceptance criteria and applying geospatial, correlation, and group-based filters to control reference selection. ARCHI provides additional functions for visualizing results, clustering records with similar correlation structures, evaluating holdout data, and interactive parameterization with an accessible and intuitive graphical user interface (GUI). This methods brief provides an overview of the ARCHI package, modeling guidelines, and benchmarking on two regional groundwater-level datasets from the Central Valley, CA and Long Island, NY. We evaluate ARCHI alongside widely used multivariate imputation software to highlight and contextualize its computational efficiency, imputation accuracy, and model transparency when applied to large, groundwater-level datasets.

Heat transport in the subsurface is an important aspect of research related to the effects of a warming climate on ecological services (i.e., cold-water refugia); the development of geothermal resources for energy banking schemes (i.e., aquifer thermal energy storage [ATES]); and the effects of temperature on other aspects of groundwater quality, such as nutrient cycling. Historically, simulation of heat transport using the MODFLOW groundwater simulator and related codes was performed by scaling the input parameters of a solute-transport model to emulate heat transport. However, that approach required additional pre- and post-processing of input and output and could not account for the variation in effective thermal storage and transport properties during transient, unsaturated flow, for example. True heat-transport capabilities in the context of MODFLOW were first introduced in a variant called USG-Transport. More recently, a new groundwater energy-transport (GWE) model type has been added to MODFLOW 6, the core version of the MODFLOW hydrologic simulator. GWE supports the simulation of heat transport on structured or unstructured grids as well as within and between features of advanced packages that represent streams, lakes, multi-aquifer wells, and the unsaturated zone. GWE is integrated within MODFLOW 6 and is accessible through the FloPy Python package and the MODFLOW 6 application programming interface (API). An example simulation demonstrates conduction between grid cells through both the water and the solid aquifer material, including thermal bleeding from saturated overburden cells into a groundwater flow field.

This study examines the factors influencing the adoption of solar tube well technology for groundwater extraction in the agriculture sector, focusing on the Balochistan region of Pakistan. Water scarcity is a major challenge in this region due to declining groundwater level and unreliable power supplies. The study uses a binary logit regression model to analyze the factors that determine the adoption of solar tube wells by farmers. The study took into account variables such as age, education level of household head and access to credit, farmers' perception of groundwater depletion, number of hours of tube well operation, and cost of adopting solar technology. The results indicate that education level and experience positively influence farmers' ability to use solar tube wells. Education provides farmers with the knowledge to understand modern farming methods and the benefits of solar technology. In addition, the cost-effectiveness and increased operating hours of solar tube wells contribute significantly to their adoption. Farmers' concerns about greater groundwater depletion also influenced their decisions, with those seeing groundwater decline more likely to adopt solar technology. The results also suggest that policies that promote access to credit and reduce the initial cost of solar tube well adoption can further encourage farmer's adoption decision.

Wetlands, as crucial terrestrial carbon reservoirs, have recently suffered severe degradation due to intense human activities. Lacustrine sediments serve as vital indicators for understanding wetland environmental changes. In the current paper, porewater samples were extracted from lacustrine sediment in three boreholes with a depth of ~75 cm in the Huixian karst wetland, southwest China, to study the chemical and dissolved inorganic carbon (DIC) evolution under anthropogenic influence. Two boreholes are situated beneath the Mudong Lake, while the other one is in the degraded wetland area. The results show that porewater in the central region of Mudong Lake is natural HCO₃-Ca type water and recharged by karst groundwater as evidenced by depleted ²H -¹⁸O isotopes. Methanogenesis prevails in this area, suggested by positive δ¹³C values ranging from 4.29‰ to 7.05‰. However, shallow porewater at the western edge of Mudong Lake and porewater in the degraded wetland exhibit significantly higher concentrations of NO₃ ^- and SO₄ ^2-, resulting from the agricultural input and recharged groundwater influenced by oxidation of pyrite. These processes lead to a decrease in methane production and generate DIC through degradation of organic fertilizer and carbonate weathering by sulfuric acid, thereby significantly altering porewater δ¹³C values. Two types of DIC mixing processes were observed based on the increasing δ¹³C values with depth, which can be attributed to the unique karst groundwater subsystems. This work highlights the potential impact of human-induced porewater chemical variations on the fate of DIC, particularly in karst wetland environments.

In simulations of groundwater flow through dipping aquifers, layers of model cells are often "deformed" to follow the top and bottom elevations of the aquifers. When this approach is used in MODFLOW, adjacent cells within the same model layer are vertically offset from one another, and the standard conductance-based (two-point) formulation for flow between cells does not rigorously account for these offsets. The XT3D multi-point flow formulation in MODFLOW 6 is designed to account for geometric irregularities in the grid, including vertical offsets, and to provide accurate results for both isotropic and anisotropic groundwater flow. A recent study evaluated the performance of the standard formulation and XT3D using a simple, synthetic benchmark model of a steeply dipping aquifer. Although XT3D generally improved the accuracy of flow simulations relative to the standard formulation as expected, neither formulation produced accurate flows in cases that involved large vertical offsets. In this paper, we explain that the inability of XT3D to produce accurate flows in the steeply dipping aquifer benchmark was not due to an inherent limitation of the flow formulation, but rather to the limited cell connectivity inherent in the most commonly used discretization packages in MODFLOW 6. Furthermore, we demonstrate that XT3D is able to produce the expected accuracy when adequate cell connectivity is introduced using MODFLOW's unstructured grid type and the aquifer is discretized vertically using at least two model layers.

Quantifying lacustrine groundwater discharge (LGD) is important for understanding the dynamics of lake ecosystems and their expansion. This study focuses on Lake Qinghai, employing radium isotope models to evaluate the contributions of both shallow and deep groundwater. The data indicate that the activity of ²²³Ra and ²²⁴Ra demonstrates a pronounced gradient, decreasing from the shoreline to the center of Lake Qinghai. Additionally, vertical stratification characteristics were observed. The spatial distribution of radium isotope activity suggests that there is discharge of both shallow and deep groundwater into the lake. Deep groundwater migrates slowly and its apparent age reflects the time elapsed since the water became enriched in Ra and was isolated from the source, in the study system this age is estimated to be 10.1 d. In contrast, shallow groundwater displayed varied apparent ages in different regions: 7.9 d in the north, 13.1 d in the south, and 7.4 d in the southeastern area of the lake. The LGDs of shallow groundwater discharge in the north, south, and southeast areas of Lake Qinghai were estimated by ²²⁴Ra as 1.89 × 10⁶ to 2.69 × 10⁶ m³/d, 3.25 × 10⁶ to 3.99 × 10⁶ m³/d, and 4.51 × 10⁶ to 6.33 × 10⁶ m³/d, respectively. For deep groundwater, the LGD was 0.16 × 10⁶ to 0.29 × 10⁶ m³/d. Annually, the total LGD fluxes of shallow and deep groundwater are 27.86 × 10⁸ to 37.59 × 10⁸ m³/year and 0.58 × 10⁸ to 1.06 × 10⁸ m³/year, respectively. This study is the first to evaluate shallow and deep groundwater discharge around the lake. Understanding these discharge dynamics is essential for developing effective management strategies to preserve lake environments.