Coastal aquifers are complex systems governed by fresh-saline water interactions and ocean tidal effects. The vertical electrical conductivity (EC) and temperature (T) are general indicators for detecting the fresh-saline water interface (FSI) and seawater intrusion in groundwater wells located in coastal aquifers. In this method brief, we developed a cost-effective Arduino-based automatic-vertical profile monitoring system (A-VPMS) to continuously record vertical EC and T in groundwater wells, with the aim of testing its effectiveness in spatiotemporal monitoring of the FSI in a coastal aquifer located in eastern Korea. By analyzing the high-density EC and T data obtained by the A-VPMS, we evaluated the characteristics of the FSI, such as depth and spatial distribution. Our established EC and T data collection method using the A-VPMS proved to be efficient and reliable, providing an excellent tool for fine-scale temporal and spatial understanding of seawater intrusion. The results of this study demonstrate the potential of the A-VPMS for continuous monitoring of the FSI in coastal aquifers, which is crucial for sustainable management of groundwater resources. This article is protected by copyright. All rights reserved.

The Jiangcang Basin is an important mining area of the former Qilian Mountain large coal base in Qinghai Province, and understanding the groundwater circulation mechanism is the basis for studying the hydrological effects of permafrost degradation in alpine regions. In this study, hydrogeochemical and multiple isotope tracer analysis methods are used to understand the chemical evolution and circulation mechanisms of the groundwater in the typical alpine region of the Jiangcang Basin. The diversity of the groundwater hydrochemistry in the study area reflects the complexity of the hydrogeochemical environment in which it is located. The suprapermafrost water and intrapermafrost water are recharged by modern meteoric water. The groundwater is closely hydraulically connected to the surface water with weak evaporation overall. The high δ34 S value of deep groundwater is due to SO4 reduction, and SO4 2- -rich snow recharge with lixiviated sulfate minerals are the main controlling factor for the high SO4 2- concentration in groundwater. According to the multivariate water conversion relationships, it reveals that the river receives more groundwater recharge, suprapermafrost water is recharged by the proportion of meteoric water, which is closely related to the mountainous area at the edge of the basin, while intrapermafrost water is mainly recharged by the shallow groundwater. This study provides a data-driven approach to understanding groundwater recharge and evolution in alpine regions, in addition to having significant implications for water resource management and ecological environmental protection in coal bases of the Tibetan Plateau.

Groundwater monitoring to measure a variety of indicator parameters including dissolved gas concentrations, total dissolved gas pressure (TDGP), and redox indicators is commonly used to evaluate the impacts of gas migration (GM) from energy development in shallow aquifer systems. However, these parameters can be challenging to interpret due to complex free-phase gas source architecture, multicomponent partitioning, and biogeochemical reactions. A series of numerical simulations using a gas flow model and a reactive transport model were conducted to delineate the anticipated evolution of indicator parameters following GM in an aquifer under a variety of physical and biogeochemical conditions. The simulations illustrate how multicomponent mass transfer processes and biogeochemical reactions create unexpected spatial and temporal variations in several analytes. The results indicate that care must be taken when interpreting measured indicator parameters including dissolved hydrocarbon concentrations and TDGP, as the presence of dissolved gases in background groundwater and biogeochemical processes can cause potentially misleading conclusions about the impact of GM. Based on the consideration of multicomponent gas partitioning in this study, it is suggested that dissolved background gases such as N2 and Ar can provide valuable insights on the presence, longevity and fate of free-phase natural gas in aquifer systems. Overall, these results contribute to developing a better understanding of indicators for GM in groundwater, which will aid the planning of future monitoring networks and subsequent data interpretation.

The Maocun underground karst river system in the peak cluster depression is an important source of groundwater in southwest China. Multitracers and high resolution water-level-monitoring technology were used to assess and evaluate the hydrogeological structure and flow dynamics. The results showed that the spatial geological structures of the sites had high heterogeneity. Scatter plots of environmental tracers divided the sampling points into groups under different water flow patterns. The karstification was found to increase from sites XLB and LLS to sites BY, SGY and BDP to sites CY and DYQ, where the main water flow patterns at these site groups were diffuse water, both diffuse water and conduit water, and conduit water, respectively. The response times of the subsystems were found to be influenced by the spatial structure, the degree of karstification, and the volume of precipitation and frequency. The average response times of SGY, BDP, ZK, and Outlet in the selected precipitation scenarios were 5.17, 4.08, 16.42, and 5.83 h, respectively. In addition, the EC, δ13 CDIC , 222 Rn, and δ18 O exhibited both linear or exponential relationships. Overall, three hydrogeological conceptual models were constructed showing: (1) high precipitation driving the deep water, resulting in a concentrated flow regime and regional groundwater flow field; (2) both concentrated and diffuse water flows existing under moderate precipitation, resulting in mixed water flow field; (3) the water cycle in the shallow karst aquifer system under low precipitation causing the local groundwater flow field to be dominated by diffuse water flow.

Conceptual change is the process of developing a new understanding of an idea or related set of ideas and has been researched and theorized extensively in the last few decades. Although there is ongoing debate about how and why conceptual change occurs, all agree that individuals' prior knowledge plays a role, everyone engages differently in the process, and the context of the learning environment is influential. In this paper we build upon the work explored by Jimenez-Martinez (this issue) on conceptual change in hydrogeology, and explore how the conceptual change theory of Vosniadou may facilitate understanding the learning process in hydrogeology. Vosniadou's theory is particularly applicable because it addresses the learning of ideas that combine abstract (GW flow) and visible (water flow) concepts. A pathway for exploring hydrogeology students' mental models (from naïve framework theory, to synthetic models, to scientific mental models) and identifying misconceptions specifically within hydrogeology using methods established by Vosniadou and colleagues is proposed as a means to address some of the challenges identified by Jimenez-Martinez. This article is protected by copyright. All rights reserved.

Water table depth (WTD) has a substantial impact on the connection between groundwater dynamics and land surface processes. Due to the scarcity of WTD observations, physically-based groundwater models are growing in their ability to map WTD at large scales, however, they are still challenged to represent simulated WTD compared to well observations. In this study, we develop a purely data-driven approach to estimating WTD at continental scale. We apply a random forest (RF) model to estimate WTD over most of the contiguous US (CONUS) based on available WTD observations. The estimated WTD are in good agreement with well observations, with a Pearson correlation coefficient (r) of 0.96 (0.81 during testing), a Nash-Sutcliffe efficiency (NSE) of 0.93 (0.65 during testing), and a root mean square error (RMSE) of 6.87 m (15.31m during testing). The location of each grid cell is rated as the most important feature in estimating WTD over most of the CONUS, which might be a surrogate for spatial information. In addition, the uncertainty of the RF model is quantified using quantile regression forests. High uncertainties are generally associated with locations having a shallow WTD. Our study demonstrates that the RF model can produce reasonable WTD estimates over most of the CONUS, providing an alternative to physics-based modeling for modeling large-scale freshwater resources. Since the CONUS covers many different hydrologic regimes, the RF model trained for the CONUS may be transferrable to other regions with a similar hydrologic regime and limited observations. This article is protected by copyright. All rights reserved.

In 1989, the Southern Nevada Water Authority (SNWA) launched the Southern Nevada Groundwater Development Project-a bold plan to construct a series of deep wells in east-central Nevada to pump groundwater and send it to the Las Vegas region through 300 miles of pipeline. Before starting work on the project, SNWA conducted an environmental impact study and secured water rights in the valleys. Applications for additional new water rights were filed with Nevada State Engineer on the basis of uncaptured evapotranspiration. The SNWA spent decades and millions of dollars studying the hydrogeology of the region and developing computer models to demonstrate that the project would not have an unduly negative impact on the ecology or water users in the region. The project was opposed by environmental groups, native American tribes, and existing water rights holders. One of the protestants was the Cleveland Ranch in Spring Valley. Using the SNWA's own groundwater model, the ranch argued that the project would result in substantial harm to the ranch's water rights which included springs, wells, and a stream, and that the project would result in perpetual groundwater mining, which is forbidden by Nevada state policy. The Nevada State Engineer approved the project, but the decision was eventually reversed by Seventh District Court, which sided with the ranch and ruled that the project would never be sustainable and is therefore not compatible with Nevada policy. The project was formally abandoned in 2020.

This note describes the development and testing of a novel, programmable reversing flow 1D (R1D) experimental column apparatus designed to investigate reaction, sorption, and transport of solutes in aquifers within dynamic reversing flow zones where waters with different chemistries mix. The motivation for constructing this apparatus was to understand the roles of mixing and reaction on arsenic discharging through a tidally fluctuating riverbank. The apparatus can simulate complex transient flux schedules similar to natural flow regimes The apparatus uses an Arduino microcontroller to control flux magnitude through two peristaltic pumps. Solenoid valves control flow direction from two separate reservoirs. In-line probes continually measure effluent electrical conductance, pH, oxidation-reduction potential, and temperature. To understand how sensitive physical solute transport is to deviations from the real hydrograph of the tidally fluctuating river, two experiments were performed using: 1) a simpler constant magnitude, reversing flux direction schedule (RCF); and 2) a more environmentally relevant variable magnitude, reversing flux direction schedule (RVF). Wherein, flux magnitude was ramped up and down according to a sine wave. Modeled breakthrough curves of chloride yielded nearly identical dispersivities under both flow regimes. For the RVF experiment, Peclet numbers captured the transition between diffusion and dispersion dominated transport in the intertidal interval. Therefore, the apparatus accurately simulated conservative, environmentally relevant mixing under transient, variable flux flow regimes. Accurately generating variable flux reversing flow regimes is important to simulate the interaction between flow velocity and chemical reactions where Brownian diffusion of solutes to solid-phase reactions sites is kinetically limited. This article is protected by copyright. All rights reserved.

Field-based learning in hydrogeology enables students to develop their understanding and application of practical methodologies, and to enhance many of the generic skills (e.g., teamwork, problem-solving). However, teaching and learning hydrogeology in general, and especially in the field, presents cognitive difficulties, such as the diversity in student education and experience, the hidden nature of water movement and transport of chemicals, and the preexisting students' mental models of the subsurface, in particular. At any given experimental or teaching site there is only one reality for which lecturers can have an approximate conceptual model, including aquifer(s) geometry and functioning (e.g., flow direction). However, students' preconceptions (i.e., mental model), in some cases misconceptions, influence not only their outcome from the learning strategy designed, but also the conceptual model expression (i.e., flow chart, block diagram, or similar) for the study area or site. In practice, two general "teaching challenges" are identified to enable students' transition from the mental to the conceptual model: (1) identify and dispel any prior misconceptions and (2) show how to go from the partial information to the integration of new information for the development of the conceptual model. The inclusion of specific prior-to-field lessons in the classroom is recommended and in general, done. However, introducing a prior-to-field survey to learn about students' backgrounds, and methodologies for the development and expression of hydrogeological conceptual models and for testing multiple plausible conceptual models will help students transition from the mental to the conceptual model.

This study synthesizes two different methods for estimating hydraulic conductivity (K) at large scales. We derive analytical approaches that estimate K and apply them to the contiguous United States. We then compare these analytical approaches to three-dimensional, national gridded K data products and three transmissivity (T) data products developed from publicly available sources. We evaluate these data products using multiple approaches: comparing their statistics qualitatively and quantitatively and with hydrologic model simulations. Some of these datasets were used as inputs for an integrated hydrologic model of the Upper Colorado River Basin and the comparison of the results with observations was used to further evaluate the K data products. Simulated average daily streamflow was compared to daily flow data from 10 USGS stream gages in the domain, and annually averaged simulated groundwater depths are compared to observations from nearly 2000 monitoring wells. We find streamflow predictions from analytically informed simulations to be similar in relative bias and Spearman's rho to the geologically informed simulations. R-squared values for groundwater depth predictions are close between the best performing analytically and geologically informed simulations at 0.68 and 0.70 respectively, with RMSE values under 10 m. We also show that the analytical approach derived by this study produces estimates of K that are similar in spatial distribution, standard deviation, mean value, and modeling performance to geologically-informed estimates. The results of this work are used to inform a follow-on study that tests additional data-driven approaches in multiple basins within the contiguous United States.