Groundwater最新文献

Coastal groundwater-dependent ecosystems (GDEs), such as wetlands, estuaries and nearshore marine habitats, are biodiversity hotspots that provide valuable ecosystem services to society. However, coastal groundwater and associated ecosystems are under threat from groundwater exploitation and depletion, as well as climate change impacts from sea-level rise and extreme flood and drought events. Despite many well-intentioned policies focused on sustainable groundwater use and species protection, coastal GDEs are falling through gaps generated by siloed policies and as a result, are declining in extent and ecological function. This study summarized then examined policies related to the management of coastal groundwater and connected ecosystems in two key case study areas: Queensland (Australia) and California (USA). Despite both areas being regarded as having progressive groundwater policy, our analysis revealed three universal policy gaps, including (1) a lack of recognition of the underlying groundwater system, (2) fragmented policies and complex governance structures that limit coordination, and (3) inadequate guidance for coastal GDE management. Overall, our analysis revealed that coastal GDE conservation relied heavily on inclusion within protected areas or was motivated by species recovery, meaning supporting groundwater systems remained underprotected and outside the remit of conservation efforts. To close these gaps, we consider the adoption of ecosystem-based management principles to foster integrated governance between disparate agencies and consider management tools that bridge traditional conservation realms. Our findings advocate for comprehensive policy frameworks that holistically address the complexities of coastal GDEs across the land-sea continuum to foster their long-term sustainability and conservation.

MODFLOW 6 is the latest in a line of six “core” versions of MODFLOW released by the U.S. Geological Survey. The MODFLOW 6 architecture supports incorporation of additional hydrologic processes, in addition to groundwater flow, and allows interaction between processes. The architecture supports multiple model instances and multiple types of models within a single simulation, a flexible approach to formulating and solving the equations that represent hydrologic processes, and recent advances in interoperability, which allow MODFLOW to be accessed and controlled by external programs. The present version of MODFLOW 6 consolidates popular capabilities available in MODFLOW variants, such as the unstructured grid support in MODFLOW-USG, the Newton-Raphson formulation in MODFLOW-NWT, and the support for partitioned stress boundaries in MODFLOW-CDSS. The flexible multi-model capability allows users to configure MODFLOW 6 simulations to represent the local-grid refinement (LGR) capabilities available in MODFLOW-LGR, the multi-species transport capabilities in MT3DMS, and the coupled variable-density capabilities available in SEAWAT. This paper provides a new, holistic and integrated overview of simulation capabilities made possible by the MODFLOW 6 architecture, and describes how ongoing and future development can take advantage of the program architecture to integrate new capabilities in a way that is minimally invasive and automatically compatible with the existing MODFLOW 6 code.

The slug test has been commonly used to estimate aquifer parameters. Previous studies on the slug test mainly focused on a single-layer aquifer. However, understanding the interaction between layers is particularly important when assessing aquifer parameters under certain circumstances. In this study, a new semi-analytical model on transient flow in a three-layered aquifer system with a partially penetrating well was developed for the slug test. The proposed model was solved using the Laplace transform method and the Goldstein-Weber transform method, where the semi-analytical solution for the model was obtained. The drawdowns of the proposed model were analyzed to understand the impacts of the different parameters on the drawdowns in a three-layered aquifer system. The results indicated that groundwater interactions between the layers have a significant impact on the slug test. In addition, a shorter and deeper well screen as well as a greater permeability ratio between the layers creates a greater interface flow between them, leading to a higher drawdown in the slug test. Finally, a slug test in a three-layered aquifer system was conducted in our laboratory to validate the new model, which indicated that the proposed model performed better in the interpretation of the experimental data than a previous model proposed by Hyder et al. (1994). We also proposed an empirical relationship to qualitatively identify the errors in the application of single-layer model for the analysis of response data in a three-layered aquifer system.

Assimilating recent observations improves model outcomes for real-time assessments of groundwater processes. This is demonstrated in estimating time-varying recharge to a shallow fractured-rock aquifer in response to precipitation. Results from estimating the time-varying water-table altitude (h) and recharge, and their error covariances, are compared for forecasting, filtering, and fixed-lag smoothing (FLS), which are implemented using the Kalman Filter as applied to a data-driven, mechanistic model of recharge. Forecasting uses past observations to predict future states and is the current paradigm in most groundwater modeling investigations; filtering assimilates observations up to the current time to estimate current states; and FLS estimates states following a time lag over which additional observations are collected. Results for forecasting yield a large error covariance relative to the magnitude of the expected recharge. With assimilating recent observations of h, filtering and FLS produce estimates of recharge that better represent time-varying observations of h and reduce uncertainty in comparison to forecasting. Although model outcomes from applying data assimilation through filtering or FLS reduce model uncertainty, they are not necessarily mass conservative, whereas forecasting outcomes are mass conservative. Mass conservative outcomes from forecasting are not necessarily more accurate, because process errors are inherent in any model. Improvements in estimating real-time groundwater conditions that better represent observations need to be weighed for the model application against outcomes with inherent process deficiencies. Results from data assimilation strategies discussed in this investigation are anticipated to be relevant to other groundwater processes models where system states are sensitive to system inputs.

Sub-surface characterization in fractured aquifers is challenging due to the co-existence of contrasting materials namely matrix and fractures. Transient hydraulic tomography (THT) is proved to be an efficient and robust technique to estimate hydraulic (K_m, K_f) and storage (S_m, S_f) properties in such complex hydrogeologic settings. However, performance of THT is governed by data quality and optimization technique used in inversion. We assessed the performance of gradient and gradient-free optimizers with THT inversion. Laboratory experiments were performed on a two-dimensional, granite rock (80 cm × 45 cm × 5 cm) with known fracture pattern. Cross-hole pumping experiments were conducted at 10 ports (located on fractures), and time-drawdown responses were monitored at 25 ports (located on matrix and fractures). Pumping ports were ranked based on weighted signal-to-noise ratio (SNR) computed at each observation port. Noise-free, good quality (SNR > 100) datasets were inverted using Levenberg–Marquardt: LM (gradient) and Nelder–Mead: NM (gradient-free) methods. All simulations were performed using a coupled simulation-optimization model. Performance of the two optimizers is evaluated by comparing model predictions with observations made at two validation ports that were not used in simulation. Both LM and NM algorithms have broadly captured the preferential flow paths (fracture network) via K and S tomograms, however LM has outperformed NM during validation ($��R_{\mathrm{LM}}^2�=�0.76�,�{\text{RMSE}}_{\mathrm{LM}}�=�1.75��\mathrm{cm}�,�R_{\mathrm{NM}}^2�=�0.73�,�{\text{RMSE}}_{\mathrm{NM}}�=�1.77��\mathrm{cm}�$). Our results conclude that, while method of optimization has a trivial effect on model predictions, exclusion of low quality (SNR ≤ 100) datasets can significantly improve the model performance.

Significant efforts have been expended for improved characterization of hydraulic conductivity (K) and specific storage (S_s) to better understand groundwater flow and contaminant transport processes. Conventional methods including grain size analyses (GSA), permeameter, slug, and pumping tests have been utilized extensively, while Direct Push-based Hydraulic Profiling Tool (HPT) surveys have been developed to obtain high-resolution K estimates. Moreover, inverse modeling approaches based on geology-based zonations, and highly parameterized Hydraulic Tomography (HT) have also been advanced to map spatial variations of K and S_s between and beyond boreholes. While different methods are available, it is unclear which one yields K estimates that are most useful for high resolution predictions of groundwater flow. Therefore, the main objective of this study is to evaluate various K estimates at a highly heterogeneous field site obtained with three categories of characterization techniques including: (1) conventional methods (GSA, permeameter, and slug tests); (2) HPT surveys; and (3) inverse modeling based on geology-based zonations and highly parameterized approaches. The performance of each approach is first qualitatively analyzed by comparing K estimates to site geology. Then, steady-state and transient groundwater flow models are employed to quantitatively assess various K estimates by simulating pumping tests not used for parameter estimation. Results reveal that inverse modeling approaches yield the best drawdown predictions under both steady and transient conditions. In contrast, conventional methods and HPT surveys yield biased predictions. Based on our research, it appears that inverse modeling and data fusion are necessary steps in predicting accurate groundwater flow behavior.

In this paper we present a new reactive transport code for the efficient simulation of groundwater quality problems. The new code couples the two previously existing tools OpenFoam and PhreeqcRM. The major objective of the development was to transfer and expand the capabilities of the MODFLOW/MT3DMS-family of codes, especially their outstanding ability to suppress numerical dispersion, to a versatile and computationally efficient code for unstructured grids. Owing to the numerous, previously existing transport solvers contained in OpenFoam, the newly developed code achieves this objective and provides a solid basis for future expansions of the code capabilities. The flexibility of the OpenFoam framework is illustrated by the addition of diffusional processes for gaseous compounds in the unsaturated zone and the advection of gases (multiphase transport). The code capabilities and accuracy are illustrated through several examples: (1) a simple 2D case for conservative solute transport under saturated conditions, (2) a gas diffusion case with reactions in the unsaturated zone, (3) a hydrogeologically complex 3D reactive transport problem, and finally (4) the injection of CO₂ into a deep aquifer with acidification being buffered by carbonate minerals.

Hydraulic fracturing (HF) events consume high volumes of water over a short time. When groundwater is the source, the additional pumping by rig/frack supply wells (RFSWs) may impose costs on owners of other sector wells (OSWs) by lowering the hydraulic head. The Carrizo–Wilcox aquifer in south Texas is the main source of water for HF of the Eagle Ford Shale (EFS) Play. The objectives are to assess the impacts of groundwater pumping for HF supply on: (1) hydraulic heads in OSWs located nearby an RFSW and (2) volumetric fluxes between layers of the regional aquifer system compared to a baseline model without the effect of RFSW pumping. The study area spans the footprint of the EFS Play in Texas and extends from 2011 to 2020. The pumping schedules of 2500 RFSWs were estimated from reported pumped water volumes to supply 22,500 HF events. Median annual drawdowns in OSWs ranged from 0.2 to 6.6 m, whereas 95th percentile annual drawdowns exceeded 20 m. The magnitudes of drawdown increased from 2011 to 2020. Of the four layers that comprise the Carrizo–Wilcox aquifer, the upper Wilcox was the most intensively pumped for HF supply. During the peak HF year of 2014, the net flux to the upper Wilcox was 292 Mm³ compared to the baseline net flux for the same year of 278 Mm³—a relative gain of 14 Mm³. Pumping for HF supply has the potential to negatively impact nearby OSWs by capturing water from adjacent aquifer layers.

Chemical and isotopic processes occur in every segment of the hydrological cycle. Hydrogeochemistry—the subdiscipline that studies these processes—has seen a transformation from “witch's brew” to credible science since 2000. Going forward, hydrogeochemical research and applications are critical to meeting urgent societal needs of climate change mitigation and clean energy, such as (1) removing CO₂ from the atmosphere and storing gigatons of CO₂ in soils and aquifers to achieve net-zero emissions, (2) securing critical minerals in support of the transition from fossil fuels to renewable energies, and (3) protecting water resources by adapting to a warming climate. In the last two decades, we have seen extensive activity and progress in four research areas of hydrogeochemistry related to water-rock interactions: arsenic contamination of groundwater; the use of isotopic and chemical tracers to quantify groundwater recharge and submarine groundwater discharge; the kinetics of chemical reactions and the mineral-water interface's control of contaminant fate and transport; and the transformation of geochemical modeling from an expert-only exercise to a widely accessible tool. In the future, embracing technological advances in machine learning, cyberinfrastructure, and isotope analytical tools will allow breakthrough research and expand the role of hydrogeochemistry in meeting society's needs for climate change mitigation and the transition from fossil fuels to renewable energies.