Aquifer Response Research Articles

Remote Sensing Estimation of Shallow and Deep Aquifer Response to Precipitation‐Based Recharge Through Downscaling

AbstractThe Gnangara groundwater system is a highly productive water resource in southwestern Australia. However, it is considered one of the most vulnerable groundwater systems to climate change, due to consistent declines in precipitation and recharge, and regional climate models project further declines into the future. This study introduces a new framework underpinned by machine learning techniques to provide reliable estimates of precipitation‐based recharge over the whole Perth Basin (including the Gnangara system). By combining estimates of baseflow, groundwater evaporation, and extraction, groundwater recharge was estimated over the Perth (testing site) and Gnangara (calibration site) systems using downscaled Groundwater Storage Anomalies (GWSA) from the Gravity Recovery and Climate Experiment (GRACE) mission. The random forest regression (RFR) model was used to downscale the spatial resolution of GRACE to 0.05° (approx. 5 km), providing estimable signals over the relatively small calibration site (∼2,200 km2) in order to discern any meaningful signals from the original GRACE resolution. Our study reveals that downscaled signals from GRACE can be used to provide precipitation‐based recharge estimates for groundwater systems accurately. However, the growing impacts of climate change, which has led to sporadic precipitation patterns over Western Australia, can limit the efficiency of satellite remote sensing methods in estimating recharge, especially in deep and complex aquifers.

Simulation of Seawater Intrusion and Upconing Processes in Mediterranean Aquifer in Response to Climate Change (Plana de Castellón, Spain)

In coastal regions, groundwater is often the only freshwater resource available for human consumption, agriculture, and other productive activities. From a management point of view, it is essential to understand the processes that occur in a coastal aquifer affected by seawater intrusion and upconing processes and evaluate their potential response to climate change as these scenarios usually indicate a decrease in aquifer recharge. Therefore, the dynamics of seawater intrusion and the upconing process in the Plana de Castellón aquifer on the Mediterranean coast were analysed by building and calibrating a new numerical model of flow and transport using the MODFLOW and SEAWAT codes. The model was used to examine two Shared Socioeconomic Pathway (SSP) climate change scenarios (SSP1–2.6 and SSP5–8.5) when considering field data with constant extraction conditions. The results suggest that by 2050, groundwater levels could rise by 0.18 m (on average) in the SSP1–2.6 scenario and by 0.12 m for the SSP5–8.5 scenario. In these cases, aquifer recharge and groundwater discharge to the sea could increase compared to the historical period, as precipitation is not expected to decrease significantly during this timeframe, even in the most unfavourable scenario (SSP5–8.5). The result would be the attenuation of seawater intrusion and a decrease in the volume of the aquifer that is affected by the upconing process, resulting in total dissolved solids values below 2000 mg/L. The innovation of this research lies in the fact that the numerical model allowed the dynamics of seawater intrusion and the upconing process to be adequately represented, especially in the latter process, as it was not possible to model it with real data in another study. These results can improve and facilitate decision-making for the management of the aquifer and contribute to plans for future exploitation strategies.

Groundwater level predictions in the Thames Basin, London over extended horizons using Transformers and advanced machine learning models

This study breaks new ground by using the Temporal Fusion Transformer (TFT) method for groundwater level prediction, addressing the complex dynamics of the Thames Basin aquifer in England. Our research combines extensive hydrological data collected from the Thames Basin with advanced machine learning, where a complex network of rivers and streams substantially affects groundwater dynamics. Unlike previous studies, this research focuses on long-term forecasting with deep learning, offering, for the first time, a 60-day prediction horizon based on daily data. To rigorously examine the model performance and robustness on new, unseen data, we applied the walk-forward validation method and other matrices such as RMSE and R2 coupled with the Holdout technique. The models used were Long Short-Term Memory (LSTM), Attention-based LSTM, LSTM with Bayesian optimisation, Attention-based LSTM with Bayesian optimisation and TFT. They were used on the basin's Chalk, Jurassic Limestone, and Lower greensand aquifers. Whilst both LSTM models were optimised using the Bayesian technique, TFT was applied for its inherent capability in complex time series. Our methodology processed historical groundwater and rainfall data from 2001 to 2023, accounting for the potential lag in aquifer response to the proximity of the river system. The dataset served as training, validation, and holdout for each model, focusing on capturing the dynamic temporal fluctuation. The results clearly showed the superiority of the TFT model in all aquifer types compared to other models across all horizons. The Limestone had the greatest result in the 7-day projections, with an RMSE of 0.02 and R2 of 0.98; Whilst the Chalk and Lower greensand, had RMSEs of 0.03 with R2 values of 0.75 and 0.95, respectively. The Limestone aquifer performed best for the 30-day horizon again (RMSE = 0.06, R2 = 0.85), with the Chalk and Lower greensand aquifer yielding RMSE of 0.04 and 0.12 and R2 values of 0.64 and 0.74, respectively. In the 60 days predictions, the best results were observed in the limestone aquifer with RMSE of 0.09 and R2 of 0.65 in holdout validation. However, in chalk and lower greensand aquifers, the TFT showed RMSEs of 0.05 and 0.15 and R2s of 0.45 and 0.58, respectively. Traditional LSTM models demonstrated limited predictive power compared to the main model TFT, while the attention mechanism slightly improved the accuracy. This study not only sets a new benchmark in hydrological modelling accuracy but also highlights the potential of advanced machine learning in managing complex aquifers and predicting the water table.

Modeling Groundwater Levels in California's Central Valley by Hierarchical Gaussian Process and Neural Network Regression

AbstractModeling groundwater levels continuously across California's Central Valley (CV) hydrological system is challenging due to low‐quality well data which is sparsely and noisily sampled across time and space. The lack of consistent well data makes it difficult to evaluate the impact of 2017 and 2019 wet years on CV groundwater following a severe drought during 2012–2015. A novel machine learning method is formulated for modeling groundwater levels by learning from a 3D lithological texture model of the CV aquifer. The proposed formulation performs multivariate regression by combining Gaussian processes (GP) and deep neural networks (DNN). The hierarchical modeling approach constitutes training the DNN to learn a lithologically informed latent space where non‐parametric regression with GP is performed. We demonstrate the efficacy of GP‐DNN regression for modeling non‐stationary features in the well data with fast and reliable uncertainty quantification, as validated to be statistically consistent with the empirical data distribution from 90 blind wells across CV. We show how the model predictions may be used to supplement hydrological understanding of aquifer responses in basins with irregular well data. Our results indicate that on average the 2017 and 2019 wet years in California were largely ineffective in replenishing the groundwater loss caused during previous drought years.

Flooding and flood water storage in karst systems of the Mediterranean region

Flooding is a recurring natural phenomenon that can have both life-giving and destructive aspects. In natural environments, floods are often an important element of the seasonal hydrologic cycle that provides water and nutrients to soil, supporting unique, rich and diverse ecosystems. However, flood events can also represent a destructive force that can endanger lives and cause significant damage in urban areas. Karst areas, in particular, are unique because of their special hydraulic characteristics in terms of flood occurrence, the dependence of ecosystems on such events, and attempts to actively store and manage floods. In this article, the hydraulic response of karst aquifers to heavy precipitation events, flood generation, and engineering interventions for flood control are discussed using several examples from karst areas in the Mediterranean region. Flooding mechanisms and regulatory structures in karst poljes are considered using several typical examples from the Dinaric mountain range. In addition, different variants of groundwater abstraction for increasing storage capacity and flood control are presented using examples from France and Montenegro. Managed aquifer recharge in karst areas and adjacent aquifers is demonstrated with examples from Jordan and Algeria. Finally, failed attempts at flood storage in karst reservoirs are presented with examples from Spain and Montenegro. These examples of flood retention in karst areas show the wide range of planning and technical measures and remind us of possible risks and failures in implementation as well as some positive and negative impacts on the environment and especially on ecosystems.

Theoretical evaluation of high-permeability wellbore skin effect on aquifer response under pumping

Skin zones with distinct hydraulic properties often form around wellbores during drilling operations. Conventional skin-factor models, developed for low-permeability (positive) skin, assume discontinuous hydraulic heads between the wellbore and aquifer. However, these models may be inadequate for high-permeability (negative) skin scenarios resulting from intensive well development. This study derives a new skin-factor approach for negative skin approaches based on the two-zone model approach. We derive a new skin-factor approach that maintains continuous heads between the wellbore and aquifer while allowing for discontinuous fluxes. Using Laplace and finite cos-Fourier transformations, we develop a groundwater flow model for aquifer pumping under a partially penetrating well, incorporating this new approach. An asymptotic expansion method is employed to obtain a large-time solution. The proposed model is also compared to the existing two-zone model. Sensitivity analysis reveals that high-permeability skin significantly affects drawdown, particularly when there is a sudden increase in porosity within the skin zone. This revised approach provides a more accurate framework for modeling various skin effects, offering valuable insights for groundwater management and well hydraulic modeling in both hydrogeology and petroleum engineering applications.

Controlling Arsenic Cross-contamination in Multi-aquifer System of Gangetic Flood Plain Through Optimal Well Spacing Based on Aquifer Response Modelling—A Case Study from Buxar District and Neighbouring Areas, Bihar, India

Controlling Arsenic Cross-contamination in Multi-aquifer System of Gangetic Flood Plain Through Optimal Well Spacing Based on Aquifer Response Modelling—A Case Study from Buxar District and Neighbouring Areas, Bihar, India

Multi-Facet analysis of analytical and numerical models to resolve sustainable artificial recharge rates in unconfined aquifers

Managed aquifer recharge (MAR) has emerged as a potential solution to resolve water insecurity, globally. However, integrated studies quantifying the surplus source water, suitable recharge sites and safe recharge capacity is limited. In this study, a novel methodology is presented to quantify transient injection rates in unconfined aquifers and generate MAR suitability maps based on estimated surplus water and permissible aquifer recharge capacity (PARC). Subbasin scale monthly surplus surface runoff was estimated at 75% dependability using a SWAT model. A linear regression model based on numerical solution was used to capture the aquifer response to injection and to calculate PARC values at subbasin level. The available surplus runoff and PARC values was then used to determine the suitable site and recharge rate during MAR operation. The developed methodology was applied in the semi-arid region of Lower Betwa River Basin (LBRB), India. The estimated surplus runoff was generally confined to the monsoon months of June to September and exhibited spatial heterogeneity with an average runoff rate of 5000 m3/d in 85% of the LBRB. Analysis of the PARC results revealed that thick alluvial aquifers had large permissible storage capacity and about 50% of the LBRB was capable of storing over 3500 m3/d of water. This study revealed that sufficient surplus runoff was generated in the LBRB, but it lacked the adequate safe aquifer storage capacity to conserve it. A total 65 subbasins was identified as the best suited sites for MAR which had enough surplus water and storage capacity to suffice 20% of the total water demand in the LBRB. The developed methodology was computationally efficient, could augment the field problem of determining scheduled recharge rates and could be used as a decision-making tool in artificial recharge projects.

The contraction of freshwater lenses in barrier island: A combined geophysical and numerical analysis

Coastal aquifers, vital for supplying freshwater to over one billion people worldwide, often face saltwater intrusion, with barrier island aquifers playing a crucial role in this coastal system. Despite the proliferation of studies exploring the impacts of sea-level rise, storm surges, and over-pumping, the effect of droughts on barrier island aquifers salinization remains largely under-investigated. This lack of attention is particularly concerning given the heightened vulnerability of barrier island aquifers; most ultimately rely solely on aerial recharge compared to continental coastal aquifers. An in-depth understanding of recharge and salinization processes is important for sustainably managing these islands' marginal freshwater resources, especially considering climate change impacts. This study presents an evaluation approach for the response of a freshwater lens (FWL) to drought conditions, incorporating in-situ observations, geophysical measurements, and numerical modeling. The study examines the response of a shallow unconfined aquifer on an Atlantic coast barrier island to the 2020 Northeast extreme hydrological drought. It encompasses a density-driven flow model informed by time-lapse electrical resistivity imaging and in-situ measurements, including groundwater head and salinity collected from monitoring wells. Results from our approach indicate that FWL volume is reduced by 11% during the drought, but it returns to its previous volume over the following spring season, indicating that the net volume of the FWL remains unchanged on an annual scale. The mean groundwater residence time on the island is approximately a year, indicating that the barrier island aquifer is a hydrodynamically active coastal zone. These findings highlight the vulnerability and resilience of shallow unconfined barrier island aquifers to droughts and climate change.

EOR simulation of polymer flooding

Enhanced oil recovery (EOR) techniques, such as polymer flooding, have gained significant attention as a means to maximise hydrocarbon extraction from reservoirs. The success of polymer flooding is intricately tied to the complex interplay between fluid properties, reservoir heterogeneity, and injection strategies. It is admitted in classical modelling methodologies, to account for the mobility ratio in polymer flooding by scaling it with the help of the shear rate in situ. The accuracy of shear assessment therefore rules the mobility of oil and the global process efficiency. It is assumed to depend not solely on pore radius, rate, and porosity, but also on a dimensional parameter known as the shape factor, which varies according to the specifications of several authors. When lab measurement is available, it is possible to adjust this value to match the shear rate recorded from a rheometer at feeding stage, ahead of the core. In the present paper the consequence of not performing this stage in the case of a core flood, then in the simulation of a polymer flood pilot is investigated. An alteration of the recovery factor is then expected. The amplitude shall result from the coupling between pore-scale effects and reservoir-scale response, induced by geological constraints such as reservoir layers productivity, aquifer response, and multiphase dynamics. Relative effect and influence on reservoir parameters will be quantified, commented, and discussed.

Comparison of groundwater storage changes over losing and gaining aquifers of China using GRACE satellites, modeling and in-situ observations

Groundwater depletion in intensively exploited aquifers of China has been widely recognized, whereas an overall examination of groundwater storage (GWS) changes over major aquifers remains challenging due to limited data and notable uncertainties. Here, we present a study to explore GWS changes over eighteen major aquifers covering an area of 1,680,000 km2 in China using data obtained from the Gravity Recovery and Climate Experiments (GRACE), global models, and in-situ groundwater level observations. The analysis aims to reveal the discrepancy in annual trends, amplitudes, and phases associated with GWS changes among different aquifers. It is found that GWS changes in the studied aquifers represent a spatial pattern of ‘Wet-gets-more, Dry-gets-less’. An overall decreasing trend of −4.65 ± 0.34 km3/yr is observed by GRACE from 2005 to 2016, consisting of a significant (p < 0.05) increase of 47.28 ± 3.48 km3 in 7 aquifers and decrease of 103.56 ± 2.4 km3 (∼2.6 times the full storage capacity of the Three Gorges Reservoir) in 10 aquifers summed over the 12 years. The annual GWS normally reaches a peak in late July with an area-weighted average annual amplitude of 19 mm, showing notable discrepancy in phases and amplitudes between the losing aquifers (12 mm in middle August) in northern China and gaining aquifers (28 mm in early July) mostly in southern China. GRACE estimates are generally comparable, but can be notably different, with the results obtained from model simulations and in-situ observations at aquifer scale, with the area-weighted average correlation coefficients of 0.6 and 0.5, respectively. This study highlights different GWS changes of losing and gaining aquifers in response to coupled impacts of hydrogeology, climate and human interventions, and calls for divergent adaptions in regional groundwater management.

Groundwater vulnerability zonation using Aplis and Foster method in The Ponorogo-Ngawi groundwater basin

In 2021, Ngawi district became the largest rice producer in East Java. Groundwater is the main water source used for irrigation purposes. Lack of management for developing necessary irrigation wells has resulted in uncontrolled groundwater use, potentially reducing groundwater quantity and quality. This study aims to analyze groundwater vulnerability zones. An assessment was conducted using the Aplis and Foster methods, and their parameter classes can be customized to match the conditions of the research area. The Aplis method considers five parameters: altitude (A), slope (P), lithology (L), infiltration (I), and soil (S). The Foster method considers four parameters: aquifer response characteristics (RA), aquifer storage characteristics (DS), aquifer thickness (s), and groundwater depth (h). The vulnerability values obtained using the Aplis method ranged from 30 to 131 and were divided into four classes: low, moderate, high, and very high. The Vulnerability values obtained using the Foster method ranged from 10 to 15 for the low and moderate classes. A non-technical approach through the strict application of permits and restrictions on groundwater usage is a basis for formulating policies related to groundwater management in the research area.

Quantifying water loss in leaky micro-dam reservoir through water balance analysis and high-resolution water level data modeling

Abstract This study aimed to assess the runoff, recharge, and response of a shallow aquifer to leakage from the Arato micro-dam reservoir (MDR). The assessment was conducted using the Soil Conservation Service Curve Number (SCS-CN), soil moisture balance (SMB), and diver (automatic data logger) measurements in both the MDR and a shallow hand-dug well. Recharge was estimated using the chloride mass balance (CMB) and water table fluctuation (WTF) methods. The results revealed that the annual runoff from the catchment was 48.8 mm, which accounted for approximately 0.71 million m3. The yearly groundwater recharge was estimated to be 104, 92.8, and 100 mm using the SMB, CMB, and WTF methods, respectively. Furthermore, the water balance model of the Arato MDR indicated a leakage rate of 13.2 mm/day. It is noteworthy that the estimated leakage exceeded the seepage initially anticipated during the project's design phase (9,965 m3/year). This research project highlights the significance of utilizing local climatic and physical data from the specific watershed under investigation when planning reservoirs and other water resources. It also underscores the importance of conducting thorough site investigations to accurately quantify hydraulic conductivity for leakage estimation purposes.

ERORUN‐STAFOR: A collaborative observatory for the multidisciplinary study of the critical zone processes in a tropical volcanic watershed including a Tropical Montane Cloud Forest

AbstractTropical volcanic islands are biodiversity hotspots where the Critical Zone (CZ) still remains poorly studied. In such steep topographic environments associated with extreme climatic events (cyclones), deployment and maintenance of monitoring equipment is highly challenging. While a few Critical Zone Observatories (CZOS) are located in tropical volcanic regions, none of them includes a Tropical Montane Cloud Forest (TMCF) at the watershed scale. We present here the dataset of the first observatory from the French network of critical zone observatories (OZCAR) located in an insular tropical and volcanic context, integrating a ‘Tropical Montane Cloud Forest’: The ERORUN‐STAFOR observatory. This collaborative observatory is located in the northern part of La Réunion island (Indian Ocean) within the 45.0 km2 watershed of Rivière des Pluies (i.e., Rainfall river) which hosts the TMCF of Plaines des Fougères, one of the best preserved natural habitats in La Réunion Island. Since 2014, the ERORUN‐STAFOR monitoring in collaboration with local partners collected a multidisciplinary dataset with a constant improvement of the instrumentation over time. At the watershed scale and in its vicinity, the ERORUN‐STAFOR observatory includes 10 measurement stations covering the upstream, midstream and downstream part of the watershed. The stations record a total of 48 different variables through continuous (sensors) or periodic (sampling) monitoring. The dataset consists of continuous time series variables related to (i) meteorology, including precipitation, air temperature, relative humidity, wind speed and direction, net radiation, atmospheric pressure, cloud water flux, irradiance, leaf wetness and soil temperature, (ii) hydrology, including water level and temperature, discharge and electrical conductivity (EC) of stream, (iii) hydrogeology, including (ground)water level, water temperature and EC in two piezometers and one horizontally drilled groundwater gallery completed by soil moisture measurements under the canopy. The dataset is completed by periodic time series variables related to (iv) hydrogeochemistry, including field parameters and water analysis results. The periodic sampling survey provides chemical and isotopic compositions of rainfall, groundwater, and stream water at different locations of this watershed. The ERORUN‐STAFOR monitoring dataset extends from 2014 to 2022 with an acquisition frequency from 10 min to hourly for the sensor variables and from weekly to monthly frequency for the sampling. Despite the frequent maintenance of the monitoring sites, several data gaps exist due to the remote location of some sites and instrument destruction by cyclones. Preliminary results show that the Rivière des Pluies watershed is characterized by high annual precipitation (&gt;3000 mm y−1) and a fast hydrologic response to precipitation (≈2 h basin lag time). The long‐term evolution of the deep groundwater recharge is mainly driven by the occurrence of cyclone events with a seasonal groundwater response. The water chemical results support existing hydrogeological conceptual models suggesting a deep infiltration of the upstream infiltrated rainfall. The TMCF of Plaine des Fougères shows a high water storage capacity (&gt;2000% for the Bryophytes) that makes this one a significant input of water to groundwater recharge which still needs to be quantified. This observatory is a unique research site in an insular volcanic tropical environment offering three windows of observation for the study of critical zone processes through upstream‐midstream‐downstream measurements sites. This high‐resolution dataset is valuable to assess the response of volcanic tropical watersheds and aquifers at both event and long‐term scales (i.e., global change). It will also provide insights in the hydrogeological conceptual model of volcanic islands, including the significant role of the TMCFs in the recharge processes as well as the watershed hydrosedimentary responses to extreme climatic events and their respective evolution under changing climatic conditions. All data sets are available at https://doi.org/10.5281/zenodo.7983138.

Saltwater Intrusion Into a Confined Island Aquifer Driven by Erosion, Changing Recharge, Sea‐Level Rise, and Coastal Flooding

AbstractAquifers on small islands are at risk of salinization due to low elevations and limited adaptive capacity, and present risks will be exacerbated by climate change. Most studies addressing small‐island saltwater intrusion (SWI) have focused on homogeneous sandy islands and one or two hydraulic disturbances. We herein investigate SWI dynamics in a layered, confined island aquifer in response to multiple environmental perturbations related to climate change, with two considered in tandem. Our field and modeling work is based on an island aquifer that provides the drinking water supply for an Indigenous community in Atlantic Canada. Observation well data and electrical resistivity profiles were used to calibrate a numerical model (HydroGeoSphere) of coupled groundwater flow and salt transport. The calibrated model was used to simulate the impacts of climate change including sea‐level rise (SLR), storm surge overtopping, changing aquifer recharge, and erosion. Simulated aquifer conditions were resilient to surges because the confining layer prevented deeper saltwater leaching. However, reduced recharge and erosion resulted in saltwater wedge migration of 170 and 110 m, respectively when considered individually, and up to 295 m (i.e., into the wellfield) when considered together. Despite the confining conditions, SLR resulted in wedge migration up to 55 m as the confining pressures were not sufficient to resist wedge movement. This is the first study to harness an integrated, surface‐subsurface hydrologic model to assess effects of coastal erosion and other hydroclimatic stressors on island aquifers, highlighting that climate change can drive extensive salinization of critical groundwater resources.

Assessing the impact of precipitation on hardrock aquifer system using standard precipitation index and groundwater resilience index: a case study of Purulia, West Bengal, India.

Groundwater stored in the aquifers provides water security during natural hazards, e.g. clean water access during floods and droughts. Groundwater drought, a phenomenon closely linked with rainfall (climate) variability, is less researched, especially in India. This study aims to detect precipitation and groundwater droughts and comprehend the groundwater response to long-term precipitation trends (25years). As a case study, the drought-affected and groundwater-depleted Purulia district in West Bengal, India, which is a part of the Chotanagpur plateau, was selected. Precipitation and groundwater droughts (in aquifer types of shallow, moderate and deep) are detected using the Standard Precipitation Index (SPI) and Groundwater Resilience Index (GRI). During the 25 yearstudy period (1996-2020),Purulia had 13 (52%) rainfall deficiency years, with an annualaverage rainfall of 1382 mm. SPI detected four severe droughts and the most severe occurring in 2010-2011 (1.50). GRI found that aquifermedium had a 71% [Formula: see text] conditions and are the most resilient and aquiferdeep experienced maximum extreme drought events and is the most stressed. The cross-correlationcoefficients (CCCs) between rainfall and groundwater is moderate in deep, shallow, and medium aquifers, with CCCs - 0.43, - 0.59, and - 0.49, respectively. Positive CCCs are found for seasonal lags of - 3, - 4, and - 7. The study found that during the monsoon, average depth to groundwater level is 1 - 4m and it drops to 8-10m during the lean period, more than 85% of wells are vulnerable to extreme droughts (SPI > 1.5), aquifer's response to rainfall is aquifershallow > aquifermoderate > aquiferdeep, and aquifer's may be arranged as aquifermoderate > aquifershallow > aquiferdeep depending on their drought resistance. This study, with the use of statistical tools and long term data, will aid in the management of groundwater at varying depthsby creating basis forunderstanding the groundwater response to rainfall events.

Estimating Groundwater Flow Velocity in Shallow Volcanic Aquifers of the Ethiopian Highlands Using a Geospatial Technique

The shallow volcanic aquifer is the major rural water supply source in the Ethiopian highlands. A significant number of hand pump wells in these aquifers experience a rapid decline in yield and poor performance within a short period of time after construction. Hence, reliable estimation of groundwater flow velocity is important to understand groundwater flow dynamics, aquifer responses to stresses and to optimize the sustainable management of groundwater resources. Here, we propose the geospatial technique using four essential input raster maps (groundwater elevation head, transmissivity, effective porosity and saturated thickness) to investigate groundwater flow velocity magnitude and direction in the shallow volcanic aquifers of the Ethiopian highlands. The results indicated that the high groundwater flow velocity in the Mecha site, ranging up to 47 m/day, was observed in the fractured scoraceous basalts. The Ejere site showed groundwater flow velocity not exceeding 7 m/day in the fractured basaltic aquifer and alluvial deposits. In the Sodo site, the groundwater flow velocity was observed to exceed 22 m/day in the fractured basaltic and rhyolitic aquifers affected by geological structures. The Abeshege site has a higher groundwater flow velocity of up to 195 m/day in the highly weathered and fractured basaltic aquifer. In all study sites, aquifers with less fractured basalt, trachyte, rhyolite, welded pyroclastic, and lacustrine deposits exhibited lower groundwater flow velocity values. The groundwater flow velocity directions in all study sites are similar to the groundwater elevation head, which signifies the local and regional groundwater flow directions. This work can be helpful in shallow groundwater resource development and management for rural water supply.

Well performance in relation to design, construction and wellfield operation: a case study from the fossil Ram Sandstone aquifer in southern Jordan

The Dubaydib wellfield in southern Jordan comprises 55 wells that are up to 600 m in depth, and exploits the fossil Ram Sandstone aquifer. It has an average output of 100 million cubic metres per year (Mm 3 a −1 ) and well yields of 51–80 l s −1 . Drilling fluid has affected well performance with lowest specific capacities of 1.56 l s −1 m −1 in bentonite-drilled wells, highest (5.46 l s −1 m −1 ) in water-drilled open hole constructions and in the middle range (3.07 l s −1 m −1 ) in polymer drilled wells. Well loss coefficients and skin effect values confirm these results. The productivity of wells drilled using bentonite-based drilling fluids has not improved during production, indicating that the damage has been irreversible. Well efficiency evaluations have been found to be sensitive to the method of calculation and not to provide a reliable measure of productivity. During the course of wellfield operation (2013–21) specific capacities declined from an all-well average of 3.78 l s −1 m −1 down to 3.13 l s −1 m −1 (or c. 17% reduction). The decline reflects the deepening of groundwater levels as a result of aquifer response rather than well deterioration. As groundwater extraction is from storage, specific capacities will continue to fall, with tentative estimates suggesting values down to 2.56 l s −1 m −1 after 25 years and 2.16 l s −1 m −1 after 50 years.

Analytical study of dual‐porosity coastal aquifer with generalized nonlinear water transfer term

AbstractThis study proposes a new mathematical model for the hydraulic head distribution induced by the tidal wave in fractured coastal aquifers. The flow in the fractured aquifer is described by adopting the well‐known dual‐porosity (DP) concept. It simply describes the interaction of the flow between the fractures and matrix blocks. The past studies commonly used the lumped‐distributed approach, a first‐order mass transfer approximation, to reflect such a flow interaction. Herein, we incorporate a new generalized transfer term (GTT) into the DP model. The weighting factor in the GTT is capable of reflecting the geometrical properties of the matrix flow. The GTT can reduce to the first‐ and second‐order terms by setting the weight to zero and one, respectively. Moreover, the sensitivity analysis is used to delve into the impacts of the aquifer parameters on the flow response in the coast aquifer, and the effects of the model parameters on the head amplitude and phase shift are explored in this study. The sensitivity analysis is performed to assess the hydraulic properties of the coast aquifer in response to the hydraulic head. Overall, we believe that the present model facilitates in developing sound plans of water resources management in coastal regions.

Benefits and Cautions in Data Assimilation Strategies: An Example of Modeling Groundwater Recharge.

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.