Estimating Groundwater Recharge Research Articles

Effects of Xerophytic Vegetation-Salix on Soil Water Redistribution in Semiarid Region

Xerophytic vegetation re-regulates and allocates water resources through canopy interception, root water uptake and transpiration, and changes the water budget among precipitation, runoff, interception and infiltration, thus having a significant impact on the processes of the hydrological cycle. In this study, we investigated the effect of xerophytic shrub-Salix on soil water redistribution and water budget through an in situ monitoring experiment combined with two-dimensional vegetation water consumption modeling. The results showed that, due to the interception effect of root water uptake, it was difficult for precipitation infiltration to recharge deep soil water and groundwater. The measured data of soil moisture content, hydraulic head and precipitation were used to verify and calibrate the performance of the soil water flow model in the vadose zone by HYDRUS-2D. The effect of roots system on soil water was simulated, and the appropriate spacing of Salix replanting was estimated. Combined with the relationship between the transverse roots system and the crown width obtained by the investigation, it was determined that the spacing between the Salix should be greater than five times the crown width, so that the balance between the water consumption of Salix and the water supply of deep soil by precipitation could be considered. The results of this study are important for estimating groundwater recharge in arid areas and provide practical vegetation replanting options for similar regions.

Improving the water table fluctuation method to estimate groundwater recharge below thick vadose zones

ABSTRACT The water table fluctuation (WTF) method is popular for groundwater recharge (GR) estimation, but its accuracy is challenged when applied in areas with thick vadose zones because of the signal lag and attenuation with depth and uncertainties from barometric pressure effect and lateral flow. Improvement of the WTF method used the linear regression method and Darcy’s law, and has been assessed to give satisfactory results. In particular, the improved method presented lower GR (20–34%) relative to the conventional method. GR decreased from the centre to the edge of the tableland. The regional average GR was 63–81 mm year−1, equivalent to 11–14% of annual average rainfall. Lag times between recharge and rainfall ranged from 1 to 9 months. Rainfall and vegetation dominated the spatiotemporal variability of GR. Our study provides reference and technical support for GR estimation with the WTF method in regions with a thick vadose zone.

Impacts of Wildfires on Groundwater Recharge: A Comprehensive Analysis of Processes, Methodological Challenges, and Research Opportunities

Increasing wildfire activity has led to complex ecosystem consequences, with direct effects on the subsystems that affect the presence and movement of water. Although studies have investigated the cascading effects of wildfires on the water balance, our understanding of broad-scale groundwater modifications post fire remains unclear. This review aims to elucidate fire-induced shifts in the water balance, their causal factors, and their potential effects on groundwater recharge. By scrutinizing prior research examples that modeled post-fire recharge scenarios, the review highlights persistent knowledge gaps. The challenge of quantifying and integrating fire-induced alterations in precipitation, wind, and land temperature patterns into recharge projection models is specifically addressed. Despite these gaps, post-fire values of hydrologically meaningful parameters such as leaf area index (LAI), curve number (CN), and near-surface saturated hydraulic conductivity (KST) have been identified. Simulating post-fire recharge via the extrapolation of these values requires the consideration of site-specific conditions, vegetation recovery, and ash removal. It frequently results in a reduced interception and increased surface runoff, while evapotranspiration remains dependent on site-specific factors and often dictates groundwater recharge estimates. Although post-fire recharge simulations are inherently complex and imprecise, their growing application can guide land-use alterations and support policy implementation that considers fire-induced water availability changes.

Comparison of methods to calculate groundwater recharge for karst aquifers under a Mediterranean climate

Karst aquifers can be particularly vulnerable to human activities and climate change due to their relatively high degree of connection with the surface. This study utilized an ensemble of event-based recharge calculation methods to address the problem of structural uncertainty for the example of the Western Mountain Aquifer (WMA), a Mediterranean karst aquifer located in Israel and the West Bank. Spatially distributed recharge estimates derived from the Soil and Water Assessment Tool (SWAT) and the process-based infiltration model (PIM) were compared to site-specific, empirical regression models. The SWAT and PIM mean annual recharge estimates ranged from 32–34.6% of precipitation, almost equating to the results of empirical regression models (32–36%). Future recharge predictions under the influence of climate change were quantified by parameterizing the SWAT and PIM methods with a downscaled regional climate model of Israel. SWAT predicts a 23% decrease in recharge by 2051–2070 relative to 1981–2001. In contrast, PIM shows a 9% decrease, possibly due to the representation of infiltration through preferential flow pathways and exclusion of surface runoff processes. These divergent projections underline key methodological differences in the representation of hydrological processes. Nevertheless, both methods effectively provided good estimates of groundwater recharge. The recharge rates estimated from the various methods were integrated into MODFLOW to assess their relative impacts on groundwater storage dynamics. The ensemble of MODFLOW projected groundwater storage outputs can provide guidance for sustainable groundwater management in the region.

Estimation of Groundwater Recharge in a Volcanic Aquifer System Using Soil Moisture Balance and Baseflow Separation Methods: The Case of Gilgel Gibe Catchment, Ethiopia

Understanding the recharge–discharge system of a catchment is key to the efficient use and effective management of groundwater resources. The present study focused on the estimation of groundwater recharge using Soil Moisture Balance (SMB) and Baseflow Separation (BFS) methods in the Gilgel Gibe catchment where water demand for irrigation, domestic, and industrial purposes is dramatically increasing. The demand for groundwater and the existing ambitious plans to respond to this demand will put a strain on the groundwater resource in the catchment unless prompt intervention is undertaken to ensure its sustainability. Ground-based hydrometeorological 36-years data (1985 to 2020) from 17 stations and satellite products from CHIRPS and NASA/POWER were used for the SMB method. Six BFS methods were applied through the Web-based Hydrograph Analysis Tool (WHAT), SepHydro, BFLOW, and Automated Computer Programming (PART) to sub-catchments and the main catchment to estimate the groundwater recharge. The streamflow data (discharge) obtained from the Ministry of Water and Energy were the main input data for the BFS methods. The average annual recharge of groundwater was estimated to be 313 mm using SMB for the years 1985 to 2020 and 314 mm using BFS for the years 1986 to 2003. The results from the SMB method revealed geographical heterogeneity in annual groundwater recharge, varying from 209 to 442 mm. Significant spatial variation is also observed in the estimated annual groundwater recharge using the BFS methods, which varies from 181 to 411 mm for sub-catchments. Hydrogeological conditions of the catchment were observed, and the yielding capacity of existing wells was assessed to evaluate the validity of the results. The recharge values estimated using SMB and BFS methods are comparable and hydrologically reasonable. The findings remarkably provide insightful information for decision-makers to develop effective groundwater management strategies and to prioritize the sub-catchments for immediate intervention to ensure the sustainability of groundwater.

Groundwater modeling and estimation of the safe pumping rate for the sustainable use of groundwater resources in Kombolcha town, upper Borkena watershed, Ethiopia

ABSTRACT The rate of groundwater extraction is increasing due to population growth. Balancing pumping rates with natural recharge is necessary for sustainable use. The safe groundwater pumping rate was determined using the groundwater model ModelMuse. To determine the safe pumping rate, 39 borehole data points were gathered and adjusted for 4, 8, and 12 h of pumping scenarios for 50 years in a steady-state pumping condition. The recharge rates in the study area were calculated using four empirical approaches in addition to the water balance method. Of the four empirical methods, the water balance technique provided the most accurate estimates of groundwater recharge, with an estimated average recharge rate of 176.75 mm per year. The ModelMuse model water balance report demonstrated that there was positive storage for all boreholes to be pumped simultaneously under 4- and 8-h pumping rate scenarios, but that there would be a significant drawdown under 12-h pumping from the stress period of 2039–2065, and the summation of inflow and outflow would become negative, indicating that the withdrawal rate is greater than the recharge rate. Thus, the safe pumping rate for Borkena groundwater was calculated to be 975 L/s in 8-h pumping rate scenarios.

Groundwater recharge estimation in the Ziway Lake Watershed, Ethiopian Rift: an approach using SWAT and CMB techniques

Groundwater recharge estimation in the Ziway Lake Watershed, Ethiopian Rift: an approach using SWAT and CMB techniques

Groundwater recharge estimation in Mediterranean mountain environments by isotope profiles – Partitioning of macropore and matrix flow

Developing and continuously improving effective and feasible methods to estimate groundwater recharge is essential to ensure sustainable resource assessment. Mountain environments represent key areas for the regional water balance. In this study, the isotope profile method was used to investigate water fluxes through the vadose zone and subsequent groundwater recharge in a Mediterranean mountain environment. Six high-resolution soil water isotope profiles were taken at two different locations in the Troodos Massif (Cyprus) in the eastern Mediterranean, focusing on estimating recharge in the soil of hillslopes. Analysis of the isotope profiles yielded recharge rates ranging from 30–70 mm/year, leading to a re-evaluation of previous studies on groundwater recharge. The comparison of results obtained by the peak-shift method and mathematical modeling was used to partition matrix and macropore flow, reaching up to 39 %. Potential methodological limits of the environmental isotope profile method in skeleton-rich soils were found.

Groundwater recharge estimation using WetSpass-M and MTBS leveraging from HydroOffice and WHAT tools for baseflow in Weyib watershed, Ethiopia.

WetSpass-M model and multi-technique baseflow separation (MTBS) were applied to estimate spatio-temporal groundwater recharge (GWR) to be used to comprehend and enhance sustainable water resource development in the data-scarce region. Identification of unit Hydrographs And Component flows from Rainfall, Evaporation, and Streamflow (IHACRES) techniques outperform the existing 13 MTBS techniques to separate baseflow depending on the correlation matrix; mean baseflow was 5.128 m3/s. The WetSpass-M model performance evaluated by Nash-Sutcliff Efficiency (NSE) was 0.95 and 0.89; R2 was 0.90 and 0.85 in comparison to observed and simulated mean monthly baseflow and runoff (m3/s), respectively. The estimated mean annual water balance was 608.2 mm for actual evapotranspiration, 221.42 mm for the surface runoff, 87.42 mm for interception rate, and 177.66 mm for GWR, with an error of - 3.29 mm/year. The highest annual actual evapotranspiration was depicted in areas covered by vegetation, whereas lower in the settlement. The peak annual interception rates have been noticed in areas covered with forests and shrublands, whereas the lowest in settlement and bare land. The maximum annual runoff was depicted in settlement and bare land, while the lowest was in forest-covered areas. The annual recharge rates were low in bare land due to high runoff and maximum in forest-covered areas due to low surface runoff. The watershed's downstream areas receive scanty annual rainfall, which causes low recharge and drought. The findings point the way ahead in terms of selecting the best approach across multi-technique baseflow separations.

Groundwater Recharge Assessment in Central Benin: The Case of the Collines Region (West Africa)

The objective of this study was to assess groundwater recharge in the hard-rock central region of Benin so as to compare it with the water needs of the local population. To reach this objective, we applied the Water Table Fluctuation (WTF) method, which requires long-term monitoring of groundwater level fluctuations. Groundwater level time series were used in combination with other data (including time series of surface water discharge and rainfall) to estimate groundwater recharge but also to shed further light on the relationship between surface water and groundwater. The results demonstrated that the minimum inter-annual groundwater recharge amount is about 1.09 × 109 m3, which is enough to cover the basic water needs of the local population. It should be highlighted that in sub-regions where the density of the population is high, water shortage can still occur with the above estimated groundwater recharge amount. This study has also illustrated that when applying the WTF method, sites with a highly uncertain specific yield can be detected.

Discrepancy and estimates of groundwater recharge under different land use types on the Loess Plateau

Study regionThe Dongzhi tableland on the loess plateau, China. Study focusThis study investigates how various land use types on the Loess Plateau affect groundwater recharge using the chloride mass balance method (CMB). By integrating data from Cl–, NO3/Cl–, and stable isotopes (δ18O and δ2H), the research develops a new approach to estimate the average ion concentration rates in soil profiles. This methodology provides a nuanced understanding of how precipitation infiltration recharges groundwater under different land use scenarios and the impact of land use changes on these processes. New hydrological insights for the regionThe research findings highlight significant variations in groundwater recharge rates among different land uses. Grasslands show the highest recharge rate at 26 mm/yr, followed by forests at 23 mm/yr, while shrublands have the lowest at 5 mm/yr. Agricultural lands have moderate recharge rates ranging from 14 to 16 mm/yr. Transitioning from agricultural land to other land uses like shrublands and forests results in dramatic changes in recharge rates, with decreases and increases in recharge of 72% and 61%, respectively. These insights are crucial for developing strategic land-use planning to optimize groundwater recharge and enhance water security on the Loess Plateau. The study emphasizes the need for policies that balance hydrological science and land management to sustain both human livelihoods and ecological continuity.

Assessing groundwater drought vulnerability through baseflow separation and index-based analysis under climate change projections

Groundwater is an essential resource, providing drinking water to millions of people globally and supporting agriculture, industry, and ecosystems. It acts as a drought buffer and provides a stable source of water during dry periods. However, groundwater is often underestimated and overexploited, leading to aquifer depletion and other negative impacts. Groundwater is invisible and difficult to measure, which makes it challenging for sustainable management. This study employed the Soil & Water Assessment Tool (SWAT) hydrological model to simulate streamflow in an eastern Afghan watershed using satellite-based and reanalysis data. Variables from five Coupled model intercomparison project phase 6 (CMIP6) general circulation models (GCMs), including minimum and maximum temperature and precipitation, were bias-corrected (downscaled) using Quantile Mapping (QM). The results from these five GCMs were then compared based on statistical criteria to determine the most reliable model, and the selected model was used to derive future data (i.e., 2021 to 2050) under different climate scenarios after applying QM. Using the future climate data and the developed SWAT model, streamflow values were projected for future periods. Considering that there are various methods to estimate groundwater recharge and the most commonly used technique involves baseflow separation procedures, this study used seven baseflow separation methods to estimate groundwater recharge values based on streamflow time series from the baseline period and different climate scenarios. To evaluate the groundwater drought characteristics, a recently proposed index called the Groundwater Recharge Drought Index (GRDI) and the run theory method were used. Results indicated that the SWAT model performed well in simulating and predicting streamflow. The sixth version of the Model for Interdisciplinary Research on Climate (MIROC6) provided the highest accuracy compared to other climate models. Moreover, it was observed that the baseflow separation methods significantly affected the estimation of groundwater recharge, thus the obtained results from all developed methods were considered. The log-normal function was found to provide the best correlation for estimating GRDI. The findings revealed a gradual decrease in drought duration in the coming years. However, the magnitude and severity of droughts are projected to increase, especially under pessimistic climate scenarios.

A high-resolution map of diffuse groundwater recharge rates for Australia

Abstract. Estimating groundwater recharge rates is important to understand and manage groundwater. Numerous studies have used collated recharge datasets to understand and project regional- or global-scale groundwater recharge rates. However, recharge estimation methods all have distinct assumptions, quantify different recharge components and operate over different temporal scales. We use over 200 000 groundwater chloride measurements to estimate groundwater recharge rates using an improved chloride mass balance (CMB) method across Australia. Groundwater recharge rates were produced stochastically using gridded chloride deposition, runoff and precipitation datasets. After filtering out groundwater recharge rates where the assumptions of the method may have been compromised, 98 568 estimates of recharge were produced. The resulting groundwater recharge rates and 17 spatial datasets were integrated into a random forest regression algorithm, generating a high-resolution (0.05°) model of groundwater recharge rates across Australia. The regression reveals that climate-related variables, including precipitation, rainfall seasonality and potential evapotranspiration, exert the most significant influence on groundwater recharge rates, with vegetation (the normalised difference vegetation index or NDVI) also contributing significantly. Importantly, the mean values of both the recharge point dataset (43.5 mm yr−1) and the spatial recharge model (22.7 mm yr−1) are notably lower than those reported in previous studies, underscoring the prolonged timescale of the CMB method, the potential disparities arising from distinct recharge estimation methodologies and limited averaging across climate zones. This study presents a robust and automated approach to estimate recharge using the CMB method, offering a unified model based on a single estimation method. The resulting datasets, the Python script for recharge rate calculation and the spatial recharge models collectively provide valuable insights for water resource management across the Australian continent, and similar approaches can be applied globally.

Can eXplainable AI Offer a New Perspective for Groundwater Recharge Estimation?—Global‐Scale Modeling Using Neural Network

AbstractDue to the difficulties in estimating groundwater recharge and cross‐boundary nature of many aquifers, estimating groundwater recharge at large scale has been called upon. Process‐based models as well as data‐driven models have been established to meet this need. Meanwhile, with the advent of explainable artificial intelligence (XAI) methods, data‐driven machine learning models can take advantage of enhanced explainability while keeping the strength of high flexibility. In this study, an ensemble neural network model was built to check the suitability of the model to predict groundwater recharge and the possibility to gain new insights from large data set. Recent large inputs of groundwater recharge data and additional input for the Arabian Peninsula collated in this study were fed to the model with multiple predictors related to climatology considering seasonality, soil and plant characteristics, topography, and hydrogeology. The model showed higher performance (adjusted R2: 0.702, RMSE: 193.35 mm yr−1) than a recent global process‐based model in predicting groundwater recharge. Using XAI methods as individual conditional expectations and Shapley Additive Explanation interaction values, the model behavior was analyzed and possible linear and non‐linear relationships between the predictors and the groundwater recharge rate were found. Long‐term averaged precipitation and enhanced vegetation index showed non‐linear relationships with groundwater recharge rate, while slope, compound topographic index, and water table depth showed low importance to the model results. Most model behaviors followed the domain knowledge, while multi‐correlation between predictors and data skewness hindered the model from learning.

Uncertainties in physical and tracer methods in actual groundwater recharge estimation in the thick loess deposits of China

Groundwater recharge (GR) can be estimated with physical, tracer techniques and numerical modelling; however, the uncertainties in these methods have not been fully interpreted. This study selected six methods for actual GR estimation in the saturated zones with different data requirements and method assumptions, including two physical methods (i.e., water table fluctuation WTF and Darcy's law DL) and four tracer techniques (i.e., chloride mass balance CMB, tritium renewal rate TRR, chlorofluorocarbons CFC and 14C dating method CBD). Taking the loess tablelands of China as an example study area, we first analyzed the uncertainties in these methods and then recommended the appropriate methods for GR estimation in regions with thick vadose zones. Overall, the recharge rates from WTF, CMB and CFC (88 ± 24, 98 ± 33 and 53 ± 9 mm/year) were much greater than those from DL, TRR and CBD (10 ± 3, 14 ± 3 and 7 ± 5 mm/year). The differences in estimated GR are closely related to the method parameters, assumptions and temporal scales. Specifically, the model parameters (e.g., specific yield, hydraulic conductivity) exhibit large ranges due to spatiotemporal heterogeneity, and the physical methods are more sensitive to hydrogeological parameters compared with the tracer techniques. The uncertainties related to model assumptions originate from the simplified water/solute movement processes. The lag effect of the thick vadose zone largely limits WTF and TRR, but contributes to CMB. Ignoring the mixing and dispersion effect may overestimate recharge by 36–48 % for CFC, and the heterogeneity of the aquifer reduces the potential of CBD for recharge estimation. Overall, CMB is considered as the most optimal method for estimating GR in the thick loess deposits. This study deepens the understanding of the uncertainties in GR assessment methods in regions with thick vadose zones.

Quantitative and qualitative assessment of groundwater resources for drinking water supply in the peri-urban area of Dhaka, Bangladesh

Groundwater is the primary source of freshwater for drinking, industrial, and agricultural water in many nations worldwide. This vital resource is deteriorating due to rapidly growing urbanization, pollution, overexploitation, and climate change. However, it is unclear how much this specific resource deteriorates over time. Therefore, this study aimed to investigate groundwater resources qualitatively and quantitatively in the peri-urban area of Dhaka, Bangladesh. The study used the modified Mann-Kendall trend test, hotspot analysis, groundwater recharge estimation, multivariate statistical analysis, and the water quality index (WQI) mapping. The trend analysis of groundwater levels indicates that in the most recent year, groundwater levels close to industrial areas have declined at a maximum rate of 1.18 m/year. The estimated groundwater recharge reveals that it is highest (480 mm/year) on rural agricultural land and lowest (220 mm/year) in urban areas. With a 99% confidence level, the groundwater water trend cluster analysis indicates the hotspots of groundwater level depletion near the industrial area. The results showed that Mn, Fe, and As exceeded the World Health Organization's (WHO) recommended limit for drinking water by 76.92%, 61.53%, and 23.07%, respectively. The principal component analysis and hierarchical clustering results indicate that groundwater quality is influenced by rock-water interaction and human interventions. The WQI results suggest that 47.05% of the samples were excellent, 7.69% were good, 9.96% were poor, 17.65% were very poor, and the remaining 17.65% were unfit for drinking purposes. The depletion of groundwater hotspots was identified in northeast region of the study area. Overall, an integrated framework was proposed that offers a holistic approach to sustainable groundwater resource management amid urbanization and industrialization. These findings will provide an essential guideline for groundwater resource management in the peri-urban area of Dhaka city.

Estimation of groundwater recharge from groundwater level fluctuations and baseflow rates around Mount Meru, Tanzania

Estimating groundwater recharge, direct runoff and baseflow is essential for understanding groundwater resource availability and managing groundwater systems. This study estimates groundwater recharge, direct runoff and baseflow on two slopes of Mount Meru: the northern and southern slopes using the water-table fluctuation (WTF) method and baseflow separation technique. High-frequency groundwater level measurements in five shallow wells over three hydrological years from 2018 to 2021 were analysed, while streamflow data in four gauging stations over nine hydrological years from 2010 to 2019 were used. The results of the WTF method show that the aquifer undergoes an average recharge of 544 mm/year and 90 mm/year on the south-western and north-eastern slopes, respectively. On average, this recharge is about 53% and 13% of the annual rainfall on each slope. The baseflow results show that the aquifer on the south-eastern and north-western slopes recharges an average of 88 mm/year and 54 mm/year, respectively, which is on average about 12% and 7% of annual rainfall, respectively. In general, the high recharge on the south-western slope is attributed to the high rainfall, and the high hydraulic conductivity and high hydraulic diffusivity of the pyroclastic deposits compared to the debris avalanche deposits on the north-eastern slope. In addition, debris avalanche deposits show homogeneous recharge conditions, while pyroclastic deposits show heterogeneous recharge conditions. The WTF method can be useful to identify areas of preferential recharge so that preferential groundwater flow paths can be mapped for focused recharge of surface runoff during the rainy season.

Evaluating groundwater resources trends through multiple conceptual models and GRACE satellite data.

In this research, three numerical groundwater flow models, developed and calibrated from three equally plausible conceptual models over the Nasia Basin, have been used to assess groundwater resources variations over a transient period. The use of multiple numerical models reduces the effect of uncertainties in conceptual model formulation. All the three calibrated numerical models indicate an increasing trend of groundwater recharge and storage over the period of the groundwater level monitoring. This suggests that the prevailing erratic climatic conditions in the area are conducive for increasing groundwater recharge and storage in the terrain. The high-intensity, short duration rainfall patterns, attending climate change in the basin, enhance high levels of infiltration and percolation, leading to steadily increasing groundwater recharge. Groundwater recharge estimates from each of the models over the transient period appear to reflect the pattern of seasonal variations in rainfall in the region. Data from the models indicates a significant role of baseflow in sustaining perennial streamflow in the area. This presents a significant development in terms of groundwater-based adaptation projects, especially in agriculture. The trend of groundwater recharge in the Nasia Basin is in sync with regional groundwater storage variations estimated from the Gravity Recovery and Climate Experiment (GRACE) satellite data collected and processed over the Volta Basin. At the Volta Basin level, groundwater storage variations indicate a strong positive trend of increasing groundwater recharge from 2002 (beginning of the GRACE mission) to 2022 (end point of the data used for this research). Analysis of the GRACE data suggests that there is a cumulative increase in groundwater storage by 30cm, representing approximately 120 km3 of groundwater over the period in the basin. This translates into approximately 15mm/year of groundwater storage increase. Thus, at both the regional and local levels, groundwater appears to be responding positively to the impacts of erratic rainfall patterns observed in the area recently. The high-intensity, short duration rainfall patterns appear to favor significant groundwater recharge, resulting in a strong positive groundwater storage signal. The high positive groundwater storage signal suggests increasing groundwater resources potential in the area, indicating promising opportunities for groundwater-based climate change adaptation interventions.

Testing the reproducibility of active-distributed temperature sensing for measuring groundwater specific discharge beneath a braided river

Braided rivers are a major contributor of groundwater recharge, yet little is known about how recharge rates vary in time. Existing methods for estimating groundwater recharge from rivers (i.e., river loss) are inadequate for studying highly heterogeneous braided river systems at a sufficient spatiotemporal resolution. To do so, active-distributed temperature sensing (A-DTS) is employed, which combines fibre optic temperature measurements with an active heat source, enabling high-resolution quantification of water fluxes. In this study, twelve successive A-DTS surveys were conducted during a 24-hour experiment on a 100 m horizontal subsurface hybrid fibre optic cable installed at 5 m depth beneath a braided river. The experiment was carried out under conditions where the river stage and flow were relatively stable to demonstrate the reproducibility and effectiveness of the A-DTS method for measuring groundwater specific discharge. This foundational work will provide a high level of confidence in the method for future studies aimed at evaluating temporal variations in groundwater recharge. The median groundwater specific discharge values calculated over the 24-hour period had a very narrow range from 3.5 to 4.0 m d−1 across the wetted footprint of the river, which is within the measurement error of the installation (6 %), indicating relatively stable groundwater recharge during the experiment. This provides confidence in the repeatability of the A-DTS method as an effective technology for quantifying river loss over longer time periods, to understand seasonal variability of groundwater recharge in braided river systems.

Estimating groundwater recharge rates in the Upper Awash Basin, Ethiopia under different combinations of model complexity and objective functions

Abstract This study addresses the critical need for reliable groundwater recharge quantification by investigating the uncertainty associated with recharge estimation based on various combinations of model complexity and objective functions. Focusing on the Hombele catchment in the upper Awash Basin, Ethiopia, the research aims to analyze parameter sensitivity under different model complexities and objectives while estimating groundwater recharge for the period 1986–2013. Employing a Monte-Carlo-based calibration scheme, the study fine-tunes model parameters using objective functions like KGE, NSE, LogNSE, R2, and VE across 10 combinations of model complexity and objective functions. Results identify FC, LP, and BETA as highly sensitive parameters, while UZL, K0, and MAXBAS show limited influence in all model complexity and objective function scenarios. The semi-distributed HBV-light model achieves calibration, validation, and overall period KGE (NSE) values of 0.89 (0.80), 0.80 (0.73), and 0.87 (0.77), respectively. Sensitivity analyses reveal significant impacts on model parameters and recharge estimation based on the chosen objective function and model complexity levels. Average annual recharge rates range from 185.9–280.5 mm when the HBV-light model is semi-distributed, contrasting with 185.3–321.7 mm under lumped model conditions, emphasizing the importance of considering these factors in groundwater resource assessments.