Groundwater最新文献

A well-planned field data collection program should be designed to (1) collect a sufficient set of data of the right types at the right locations, and (2) collect a parsimonious set of data to avoid unnecessary costs. Combining PEST and a simple analytic element method (AEM) groundwater flow model for the site of interest provides a relatively simple, low-cost method of developing such a program. AEM models are well suited to this approach because they are quick to develop yet hydraulically accurate, reducing impacts on project budgets at early data collection planning stages; and quick to run, solving rapidly for the many iterations that PEST requires to generate good parameter estimates. This article shows two examples of this method: one for a steady state watershed model, and one for a transient pumping test project to demonstrate that PEST coupled with a simple AEM model that sketches out the key features of a site conceptual model can be an efficient tool in planning key parts of a hydrogeologic site investigation.

Structural landform evolution and hydrogeochemical analyses are crucial for understanding the characteristics of karst groundwater systems and the development of deep karst formed by complex aquifers in a tectonic collision zone. Detailed structural landform evolution analysis was carried out along the large-scale anticlinorium to investigate the temporal evolution of karst aquifer systems and karstification. Results showed that the tectonic activity included weak horizontal compression and slow vertical uplift during the Triassic to Middle Jurassic, forming a denuded clastic platform. This period was mainly preserved in the geological record as burial karst. From the Late Jurassic to the Early Cretaceous, the study area was strongly compressed by S–N-trending stress, and developed E–W-trending high-angle imbricate thrust structures, which controlled the formation of folded and fault-blocked mountains. Vertical multilayered strata underwent a strong horizontal extrusion, forming a large-scale anticlinorium with secondary folds and faults. With the exposure of carbonate rocks due to rapid crustal uplift, karst began to develop, forming a vertical multilayer karst aquifer system and controlling the distribution of karst groundwater. The Fangxian faulted basin was formed from the Late Cretaceous to the Paleogene, whereby landforms were dominated by intermountain basins. Slow crustal uplift caused the retreat of the denudation line to the east, leading to an increase in hydrodynamic conditions and karstification, and the initiation of early karst groundwater systems. Since the Neogene, intermittent and rapid crustal uplift has led to the deepening of rivers, resulting in the formation of peak clusters and canyons, the development of deep karst, and the complete formation of karst groundwater systems. Combined with hydrogeochemical and borehole data, local, intermediate, and regional karst groundwater systems were identified. It has vital significance to the geological route selection or construction of deep-buried tunnels and the utilization of karst groundwater.

Permeability is a required parameter for studying aquifer properties. However, for sandstone aquifers with low permeability, it is difficult to measure permeability directly through experiments. Based on fractal theory and the J function, a new method to calculate the permeability of a sandstone aquifer is derived. This work first solves the J function under each water saturation according to its definition. Combined with mercury pressure data, the J function and logarithmic curve equation of water saturation are then fitted by the drawing method, and the fractal dimension and tortuosity of the aquifer are further solved. Finally, the aquifer's permeability is calculated using the new permeability calculation method. To verify the accuracy of the proposed method, 15 rock samples from the Chang 7 Group, Ordos Basin, are taken as research objects. The permeability is calculated using the new method combined with mercury injection data and aquifer characteristic parameters, and the results are compared with the real permeability. The relative error of most samples is <20%, which shows the permeability calculated by this method is accurate and reliable. The effects of fractal dimension, tortuosity, and porosity on permeability are also analyzed.

Inspired by the analysis by Mishra et al. (2012) of variable pumping rate tests using piecewise-linear reconstructions of the pumping history, this article contains a derivation of the convolutional form of pumping tests in which the pumping history may take any possible form. The solution is very similar to the classical Theis (1935) equation but uses the Green's function for a pumped aquifer given by taking the time derivative of the well function $��W��\left(��u��\left(�t�\right)���\right)��$. This eliminates one integration inside another and renders the convolution including the pumping history about as computationally demanding as calculating the well function alone, so that the convolution can be completed using handy mathematical software. It also allows nonlinear well losses, and because an easily-computed deterministic model exists for all data points and pumping history, an objective function may include all data, so that errors are reduced in calculating any nonlinear-well losses. In addition, data from multiple observation wells may be used simultaneously in the inversion. We provide codes in MATLAB and Python to solve for drawdown resulting from an arbitrary pumping history and compute the optimal aquifer parameters to fit the data. We find that the subtleties in parameter dependencies and constructing an appropriate objective function have a substantial effect on the interpreted parameters. Furthermore, the optimization from step-drawdown tests is typically nonunique and strongly suggests that a Bayesian inversion should be used to fully estimate the joint probability density of the parameter vector.

Effective groundwater management is critical to future environmental, ecological, and social sustainability and requires accurate estimates of groundwater withdrawals. Unfortunately, these estimates are not readily available in most areas due to physical, regulatory, and social challenges. Here, we compare four different approaches for estimating groundwater withdrawals for agricultural irrigation. We apply these methods in a groundwater-irrigated region in the state of Kansas, USA, where high-quality groundwater withdrawal data are available for evaluation. The four methods represent a broad spectrum of approaches: (1) the hydrologically-based Water Table Fluctuation method (WTFM); (2) the demand-based SALUS crop model; (3) estimates based on satellite-derived evapotranspiration (ET) data from OpenET; and (4) a landscape hydrology model which integrates hydrologic- and demand-based approaches. The applicability of each approach varies based on data availability, spatial and temporal resolution, and accuracy of predictions. In general, our results indicate that all approaches reasonably estimate groundwater withdrawals in our region, however, the type and amount of data required for accurate estimates and the computational requirements vary among approaches. For example, WTFM requires accurate groundwater levels, specific yield, and recharge data, whereas the SALUS crop model requires adequate information about crop type, land use, and weather. This variability highlights the difficulty in identifying what data, and how much, are necessary for a reasonable groundwater withdrawal estimate, and suggests that data availability should drive the choice of approach. Overall, our findings will help practitioners evaluate the strengths and weaknesses of different approaches and select the appropriate approach for their application.

Solute migration is typically simulated to describe and estimate the fate and transport of contaminants in groundwater. The unit-concentration approach is investigated here as a method to enable solute transport simulations to expand the capabilities of groundwater flow modeling. The unit-concentration method uses a concentration value of one to identify sources of water to be assessed and a concentration of zero for all other water sources. The distribution of concentration thus obtained, unlike particle tracking methods, provides a more intuitive and direct quantification of the contribution of sources reaching various sinks. The unit-concentration approach can be applied readily with existing solute transport software for a range of analyses including source allocation, well capture analysis, and mixing/dilution calculations. This paper presents the theory, method, and example applications of the unit-concentration approach for source quantification.