Recharge Estimates Research Articles

Ground truthing global-scale model estimates of groundwater recharge across Africa

Groundwater is an essential resource for natural and human systems throughout the world and the rates at which aquifers are recharged constrain sustainable levels of consumption. However, recharge estimates from global-scale models regularly disagree with each other and are rarely compared to ground-based estimates. We compare long-term mean annual recharge and recharge ratio (annual recharge/annual precipitation) estimates from eight global models with over 100 ground-based estimates in Africa. We find model estimates of annual recharge and recharge ratio disagree significantly across most of Africa. Furthermore, similarity to ground-based estimates between models also varies considerably and inconsistently throughout the different landscapes of Africa. Models typically showed both positive and negative biases in most landscapes, which made it challenging to pinpoint how recharge prediction by global-scale models can be improved. However, global-scale models which reflected stronger climatic controls on their recharge estimates compared more favourably to ground-based estimates. Given this significant uncertainty in recharge estimates from current global-scale models, we stress that groundwater recharge prediction across Africa, for both research investigations and operational management, should not rely upon estimates from a single model but instead consider the distribution of estimates from different models. Our work will be of particular interest to decision makers and researchers who consider using such recharge outputs to make groundwater governance decisions or investigate groundwater security especially under the potential impact of climate change.

Impact of climate change on groundwater recharge and salinity distribution in the Vientiane basin, Lao PDR

Abstract Groundwater is widely used for domestic, agricultural, and industrial purposes in the Vientiane basin. The trend of groundwater use is increasing but the usage of the mentioned groundwater is without proper study and monitoring. Six climatic scenarios from three General Circulation Models (GCMs) under Representative Concentration Pathways (RCPs) 4.5 and 8.5 were used to project rainfall and temperature in the future (2021–2050) periods. The numerical models HELP3, MODFLOW, and MT3D were used for groundwater recharge estimation, groundwater potential, and salinity distribution, respectively. The study found that during the following 30 years (2050), rainfall is expected to rise by 16, 17.52, and 49.93% for the MPI-ESM-MR, MIROC5, and CNRM-CM5 (under RCPs 4.5 and 8.5), respectively. Groundwater recharge is estimated to rise from baseline throughout all future climate conditions. Climate change's impact on salinity distribution in depth aquifers, the area with the water with the TDS between 500 and 1,500 mg/l will tend to decrease, whereas the freshwater (TDS <500 mg/l) area will tend to increase. Annual groundwater replenishment is expected to increase from current levels in all future climate scenarios in the range of 334–401 MCM/year or approximately 22.7–47.5%.

Influence of Shallow Groundwater Evapotranspiration on Recharge Estimation Using the Water Table Fluctuation Method

AbstractGroundwater recharge moves downward from the land surface and reaches the groundwater to replenish aquifers. Despite its importance, methods to directly measure recharge remain cost and time‐intensive. Recharge is usually estimated using indirect methods, such as the widely used water‐table fluctuation (WTF) method, which is based on the premise that rises in groundwater levels are due to recharge. In the WTF method, recharge is calculated as the difference between the observed groundwater hydrograph and the hydrograph obtained in the absence of water input. The hydrograph in the absence of rise‐producing input is estimated based on a characteristic master recession curve (MRC), which describes an average behavior for a declining water‐table. Previous studies derive MRC using recession data from all seasons. We hypothesize that for sites where groundwater table is shallow, using recession data from periods with high groundwater‐influenced evapotranspiration (ET) rates versus all periods will yield significantly different MRC, and consequently different estimates of recharge. We test this hypothesis and show that groundwater recession rates are significantly greater in warm months when the groundwater‐influenced ET rates are higher. Since obtaining seasonal recession rates is challenging for locations with a limited amount of data and is prohibitive if it is to be obtained for any given season of a particular year, we propose two novel parsimonious methods to obtain recession time constants for distinct seasons. The proposed methods show the potential to significantly improve the estimates of seasonal recession time constants and provide a better understanding of seasonal variations in recharge estimates.

Using Geospatial Techniques and Analytic Hierarchy Process to Map Groundwater Potential Zones.

This study is conducted in Luvuvhu River Catchment (LRC) of South Africa, which has numerous major agricultural farms that are located in the upper catchment, especially in Levubu Valley. The significant irrigation developments in upper catchment have resulted in a decrease in the yield of surface water resources to such an extent that these resources struggle to meet domestic and industrial demand. The aim of this study is to delineate groundwater potential zones (GWPZ) as a way of establishing alternative water resources to relieve the overly stressed surface water resources. Various datasets are processed to extract groundwater controlling factors. Map layers of controlling factors are assigned weights according to their relative importance to groundwater occurrence using analytic hierarchy process and then integrated based on weighted sum analysis to generate GWPZ map. Rainfall infiltration breakthrough (RIB) and area under curve (AUC) are used to validate the GWPZ map. GWPZ map shows that lower catchment has very high groundwater potential covering about 409 km2 . Nonetheless, about 50% of LRC spatially falls within high groundwater potential zone. Groundwater recharge, based on RIB for three boreholes, that is, A9N0007, A9N0008, and A9N0018 around Levubu Valley is estimated at 8.3, 15.4, and 16.2%, respectively. Boreholes A9N0018 and A9N0018 correspond to moderate to high groundwater potential zone, whereas A9N007 coincides with low to moderate zone. Considering the groundwater recharge estimates and associated potential zones, RIB results correspond well with GWPZ map. Also, an AUC, based on 26 boreholes, of 70.9% is achieved; thus, indicating a reliable model.

Investigating the feasibility of using precipitation measurements from weather RaDAR to estimate potential recharge in regional aquifers: the Majella massif case study in Central Italy

Rain gauge spatial sparsity and temporal discontinuity of data represent one of the major issues for reliable recharge estimations. In the past decades, the use of ground-based microwave weather RaDAR has dramatically improved quantitative rainfall estimation by providing spatially continuous estimates of rainfall over an area of more than 400 km2 every 10 minutes. Furthermore, weather RaDAR data have also proved relatively reliable in mountainous areas. These paramount features of RaDAR-derived precipitation data could improve the estimation of potential recharge of aquifers, which rely on geospatializations (e.g., Thiessen polygons) of rainfall data collected by a sparse rain gauge network which often shows lacking at high altitude (i.e., recharge areas), introducing additional uncertainty in the inflow volumes. Weather RaDAR rainfall estimation is also affected by various sources of error, which can be reduced by proper post-processing; however, uncertainties remain, especially for surface rain rate estimations. Despite the currently necessary complex numerical processing, the purpose of the study is to evaluate the use of the weather RaDAR data as an alternative or in addition to meteorological data. Based on the above considerations, the feasibility of using RaDAR-based precipitation data to estimate aquifer potential recharge and calculate a detailed water budget in the areas characterized by high elevations, such as the Majella massif in the central Apennines, has been evaluated. To address this objective, the water budget has been calculated in the 2017-2018 period using both RaDAR-based precipitation data and rain gauge data, as well as adopting different methods (i.e., Turc and Thornthwaite). Although intrinsically uncertain, the RaDAR-based precipitation data provided solid results, pointed out by comparing it with water budget obtained by rain gauge data, and especially with experimental literature data. This interdisciplinary work may pave the way for continuous monitoring of aquifer potential recharge at extremely high temporal and spatial resolution.

Characterizing groundwater flow in a former uranium mine (Bertholène, France): Present status and future considerations

Study regionBertholène is a former uranium mine in Aveyron, where tailings and waste rocks are stored in a natural valley. This results in acid mine drainage (AMD) at the outlet of the tailings storage facility (TSF), where there is a dedicated water treatment plant. Study focusA detailed data analysis was conducted using data from 13 piezometers and from long-term monitoring of the local climate. A 3D model was developed using MODFLOW to understand groundwater flows at the catchment scale and identify flow paths from the contamination sources within the TSF. Previous geochemical modeling of TSFs had indicated that AMD was expected to occur for 50–100 years, therefore the site must be managed with a long-term view. As climate change may affect not only the recharge but also the frequency and intensity of extreme events, its impact on water balance and water levels at the site has to be studied for the next 100 years. New Hydrological Insights for the RegionData analysis provides information about the unsaturated conditions within the tailings. Then water balance calculations at the TSF outlet validate the contribution of two different water zones. Modeling using the recharge estimation supports the current functioning of the catchment. The impact study of extreme events shows that the water table should not permanently reach the tailings over the next century.

Understanding process controls on groundwater recharge variability across Africa through recharge landscapes

• Classifications can help consolidate our understanding of recharge controls. • Wetter Recharge Landscapes generate more recharge than dry Recharge Landscapes. • Mean annual recharge rates increase with increasing recharge ratios. • Global datasets limit our ability to explain the spatial variability of recharge. Groundwater is critical in supporting current and future reliable water supply throughout Africa. Although continental maps of groundwater storage and recharge have been developed, we currently lack a clear understanding on how the controls on groundwater recharge vary across the entire continent. Reviewing the existing literature, we synthesize information on reported groundwater recharge controls in Africa. We find that 15 out of 22 of these controls can be characterised using global datasets. We develop 11 descriptors of climatic, topographic, vegetation, soil and geologic properties using global datasets, to characterise groundwater recharge controls in Africa. These descriptors cluster Africa into 15 Recharge Landscape Units for which we expect recharge controls to be similar. Over 80% of the continents land area is organized by just nine of these units. We also find that aggregating the Units by similarity into four broader Recharge Landscapes (Desert, Dryland, Wet tropical and Wet tropical forest) provides a suitable level of landscape organisation to explain differences in ground-based long-term mean annual recharge and recharge ratio (annual recharge / annual precipitation) estimates. Furthermore, wetter Recharge Landscapes are more efficient in converting rainfall to recharge than drier Recharge Landscapes as well as having higher annual recharge rates. In Dryland Recharge Landscapes, we found that annual recharge rates largely varied according to mean annual precipitation, whereas recharge ratio estimates increase with increasing monthly variability in P-PET. However, we were unable to explain why ground-based estimates of recharge signatures vary across other Recharge Landscapes, in which there are fewer ground-based recharge estimates, using global datasets alone. Even in dryland regions, there is still considerable unexplained variability in the estimates of annual recharge and recharge ratio, stressing the limitations of global datasets for investigating ground-based information.

Groundwater recharge estimation using water table fluctuation and empirical methods

Abstract The reliable estimation of groundwater recharge is fundamental to the appropriate use of groundwater resources. Shallow groundwater resource quantification for irrigation in highland regions remains challenging. Specifically, in the humid Ethiopian highlands, only limited research has been done on groundwater recharge estimation. Despite the various techniques used to determine recharge, the objective of this study was to better understand natural groundwater recharge using water table fluctuation (WTF) and empirical methods in the sub-humid Ethiopian highlands. The Ene-Chilala watershed was selected for this study. Precipitation, infiltration rate, and piezometric water levels were measured. Precipitation was measured over a 4-year period (2013–2016), whereas infiltration and the groundwater table were measured over a 1-year period (2014). Recharge rates using WTF were determined from the three slope positions and the median of all piezometers for the whole watershed. Infiltration rates on the upslope were greater compared to the mid- and downslopes. The rainfall intensity exceeded the infiltration rate in all slope positions, so the excess rainfall recharged the perched upslope aquifer and eventually drained as interflow to recharge the mid- and downslopes. The estimated groundwater recharge from WTF was less compared to the average of empirical estimations. Surprisingly, from the nine selected empirical equations, the modified Chaturvedi formula had a similar estimation to the WTF method. In conclusion, it is challenging to find long-term seasonal and spatial groundwater-level data. Long-term groundwater data should, therefore, be available in order to arrive at a reliable recharge estimate and for effective groundwater management practices.

Estimating soil water flux from single-depth soil moisture data

• We introduce a new analytical relationship between soil moisture and water flux. • Flux can be calculated from single-depth moisture data along the unsaturated zone. • The new solution is based on Richards equation with arbitrary hydraulic functions. • This solution allows shallow or deep groundwater table at the bottom boundary. Finding a relationship between soil moisture and soil water flux at a single soil depth has been of particular interest in recent years. Such a relationship, however, is challenging to derive due to a high degree of nonlinearity of the soil water flow governing equation, known as Richards equation. This paper presents a new algebraic soil moisture-flux relationship based on an approximate analytical solution of Richards equation with arbitrary soil hydraulic functions. This solution accounts for the groundwater contributions to soil moisture variations along the unsaturated zone. The new solution was evaluated using numerical solutions of Richards equation via the HYDRUS-1D model. Despite its simplicity, the new solution could reproduce HYDRUS-1D simulations for a homogeneous soil profile with coefficient of determination (R 2 ) higher than 0.9 in most cases. The new solution offers a potential approach to modeling groundwater recharge in existing groundwater models. In particular, this model can potentially provide a more realistic recharge estimate compared to the kinematic-wave approximation of Richards equation, that neglects upward flows through the vadose zone. Future research is needed to account for soil layering and root water uptake in the soil moisture-flux relationship.

Spatial and temporal simulation of groundwater recharge and cross-validation with point estimations in volcanic aquifers with variable topography

Study regionThis study is performed for the volcanic aquifers of semi-humid Lake Tana basin in northwest Ethiopia, the source region of Blue Nile basin. Study focusestimating groundwater recharge at required spatial and temporal scale is a challenge in groundwater management, sustainability and pollution studies. In this study, the physically-based WetSpass model is applied. The recharge by WetSpass is validated with estimations by water table fluctuation (WTF) and chloride mass balance (CMB) methods. Evaluating the groundwater recharge estimation mechanism for the volcanic aquifers lying at different topographical setting, that represents wide part of the world groundwater aquifers, and suggesting more appropriate methods will benefit different similar studies. New hydrological insights for the regionthe mean annual rainfall, recharge, surface runoff, and evapotranspiration are estimated at 1431 mm, 315 mm, 416 mm, and 770 mm, respectively. The recharge varies from 0% to 57% of the rainfall. A high variation is also noted using WTF and CMB methods showing the strong heterogeneous nature of the hydro(meteoro)logical characteristics of the area. WetSpass is effective in aquifers where diffuse recharging mechanism is the predominant type and recharge is controlled by rainfall. Hence, it is found less effective in the storage-controlled flat floodplain, alluvial and fractured rock aquifer areas. In these areas, the point estimates by the WTF and CMB are effective and can be considered as reliable values.

Inverse unsaturated-zone flow modeling for groundwater recharge estimation: a regional spatial nonstationary approach

Inverse unsaturated-zone flow modeling for groundwater recharge estimation: a regional spatial nonstationary approach

Estimation of natural groundwater recharge in Chennai River basin using multiple approaches

ABSTRACT Groundwater is vital in Chennai Metropolitan Area, and thus its sustainable management is essential. This study aims to estimate groundwater recharge in the Chennai River basin (CRB) using an empirical method, a rainfall infiltration factor (RIF) method, a geographical information system (GIS)-distributed model, and the water table fluctuation (WTF) method. The average recharge estimates were 196 mm/year (empirical), 127 mm/year (WTF), and 122 mm/year (RIF). These results agree with the estimate of the GIS-distribution model, where 59% of the area has high recharge (>100 mm/year). The effective recharge from rainfall was around 10% with the RIF and WTF methods and 16% using the empirical method. All the estimates were statistically significant with confidence levels of over 98%, using a 95% confidence interval. The WTF method (with a 99.9% confidence level) was the most reliable of the four approaches. However, we suggest using multiple methods to cross-check the results and that measuring rainfall and water level is necessary for accurate recharge estimates in the future.

Incorporating Snowmelt into Daily Estimates of Recharge Using a State-Space Model of Infiltration.

A state-space model (SSM) of infiltration estimates daily groundwater recharge using time-series of groundwater-level altitude and meteorological inputs (liquid precipitation, snowmelt, and evapotranspiration). The model includes diffuse and preferential flow through the unsaturated zone, where preferential flow is a function of liquid precipitation and snowmelt rates and a threshold rate, above which there is direct recharge to the water table. Model parameters are estimated over seasonal periods and the SSM is coupled with the Kalman Filter (KF) to assimilate recent observations (hydraulic head) and meteorological inputs into recharge estimates. The approach can take advantage of real-time hydrologic and meteorological data to deliver real-time recharge estimates. The model is demonstrated on daily observations from two bedrock wells in carbonate aquifers of northwestern New York (USA) between 2013 and 2018. Meteorological inputs for liquid precipitation and snowmelt are compiled from SNODAS (2021). Results for recharge during winter and spring seasons show preferential flow events to the water table from liquid precipitation, snowmelt, or a combination of the two. Recharge estimates summed annually are consistent with previous estimates of recharge reported from groundwater flow and surface-process models. Results from the SSM and KF point to errors in meteorological inputs, such as the snowmelt rate, that are not compatible with hydraulic head observations. Whereas liquid and solid precipitation are measured at discrete stations and extrapolated to 1-km2 grid cells, snowmelt is a meteorological modeled outcome that may not represent conditions in the vicinity of monitoring well locations.

Three-Dimensional Hierarchical Hydrogeological Static Modeling for Groundwater Resource Assessment: A Case Study in the Eastern Henan Plain, China

Groundwater is closely related to hydrogeological structure and hydro-lithology, which mainly refers to the spatial distributions and properties of the environment where groundwater occurs. To analyze the constraints of hydrogeological structure and hydro-lithology on regional groundwater resources in the Eastern Henan Plain, China, we reconstructed the three-dimensional (3D) hierarchical models at two scales, hydrogeological structural models and hydro-lithological models, using hydrogeological cross-sections. First, the hydrogeological structural models of four aquifer groups, corresponding to four formations of the Quaternary in the study area, were reconstructed. Second, the hierarchical hydro-lithological model was built using SIS and IK estimation under the constraint of each aquifer group model space, respectively. Compared to global model, the variograms of hierarchical model captured more spatial characteristics of lithology in each aquifer group. The IK hierarchical model presents more continuities, clear boundaries, and realistic geometric shapes of the three lithologies, excluding the banding characteristics of the IK global model. The hierarchical SIS models reproduced the lithology distribution of each aquifer group and captured small changes in the lithology, with the smallest absolute percentage errors (APEs). Third, coupling the SIS hierarchical models and the groundwater levels, the groundwater resource in the study area was estimated to have a total volume of 1.2339 × 104 m3. The shallow groundwater in the study area is mainly concentrated in Hebi City and the Puyang basin of the Yellow River, and deep groundwater is mainly concentrated in the northern Anyang City and Hebi City. Finally, the possible quantities of shallow and deep groundwater recharges were estimated for future groundwater management decision in the study area. The hierarchical hydrogeological model, groundwater resource assessment, and possible groundwater recharge estimation can also provide a basis for groundwater vulnerability, groundwater extraction, and land subsidence assessment.

Estimation of evapotranspiration from measured meteorological parameters

Five empirical equations, namely, FAO-56 Penman–Monteith, Hargreaves–Samani, Makkink, Turc, and Priestley–Taylor are utilized in the estimation of evapotranspiration for the month of May in 2018 for Trombay site in Maharashtra. Evapotranspiration from a given surface is a function of incoming solar radiation, net radiation, ground heat flux, air temperature, relative humidity, and wind speed. Daily average measurements of these parameters are utilized in the empirical equations for the estimation of evapotranspiration. These estimated values are compared with the measured data from pan evaporimeter installed at Trombay. The measured data from the pan evaporimeter are corrected using the pan coefficient Kp which in turn is also estimated using empirical equations. The average value of the pan coefficient Kp is 0.8 for the site. The average measured value of evapotranspiration is 4.7 mm/d for May 2018, whereas the values estimated using the five empirical equations range from 3.3 mm/d to 12.7 mm/d. Among the five equations, the Turc equation was found to be in the best agreement with the measured values of evapotranspiration. Such studies are useful in the estimation of groundwater recharge, latent heat flux, and agriculture meteorology.

Estimating groundwater recharge in the assiniboine delta aquifer using HYDRUS-1D

Unconfined aquifers are often directly impacted by high irrigation demands. Therefore, accurate recharge estimates are crucial for sustainable groundwater management. It is important over time to re-examine the existing hydrologic understanding of aquifers, taking into account developments in knowledge and changing climate conditions. The last in depth study into the Assiniboine Delta Aquifer located in Manitoba, Canada, that gave a recharge estimate was conducted in the 1980s (Render, 1988). This work re-examined the Assiniboine Delta Aquifer, employing new methods and data to estimate recharge rates. Twelve one-dimensional models were created in the software HYDRUS-1D to model the soil water fluxes in the unsaturated zone to analyze the historic recharge from 1996 to 2019. Remote weather station data, measured hydraulic conductivity, soil texture distribution, soil moisture content, and soil temperature data were used to initialize and run the models. Inverse calibration used the measured moisture contents to calibrate the models, which resulted in Root Mean Square Error in the calibration and validation periods averaging 0.034 and 0.051 m3/m3, respectively, above the 0.025 m3/m3 sensor measurement error. Rough estimates of soil texture distribution across the aquifer was determined to assist in the final recharge estimate. The historical regional recharge average was estimated to be 68 mm/year, double the previous estimate for the aquifer (Render, 1988). Modelled periods were limited to less than a year due to limitations in the general HYDRUS-1D software model code under frozen soil conditions, which the Assiniboine Delta Aquifer experiences during the winter months. Assumptions on initial soil moisture contents, snowpack heights, and model start dates were best estimated for historical years. Results show these estimates can have significant impacts on the resulting recharge. Suggested future work includes implementing the HYDRUS-1D freeze-thaw code to allow for model spin-up and multi-year simulations to enhance the reliability of model results.

Estimation of replenishable groundwater resources and their utilization status in hard rock terrain

For an efficient management and development of groundwater resources, it is imperative to have a reliable database on groundwater resources. In this regard, present study was conducted during 2015–18 in Mahatma Gandhi Chitrakoot Vishwavidyalaya, Chitrakoot, Satna, Madhya Pradesh, India. Dynamic groundwater resources of study area have been estimated by using the guidelines of the groundwater resources estimation committee (GEC-1997), Ministry of Water Resources, Government of India. In this study, rainwater infiltration factor (RIF) techniques and different conventional norms were used for groundwater recharge estimation. The assessments of groundwater units were categorized based on stage of groundwater development for the year 2016. The annual groundwater draft for all uses such as domestic and irrigation was 5931.54 ha m. The annual groundwater recharge in the study area was 8666.81 ha m and net annual groundwater availability was 8318.85 ha m. The groundwater utilization and stage of groundwater development had also been determined and the overall stage of groundwater development of Babina block was found to be 71.30%. There was no significant rise or fall of water levels during both the pre-monsoon and post-monsoon intervals in the study area. Considering the stage of groundwater development, it has been categorized that Babina block of Jhansi district, a part of Bundelkhand region falls under ‘SAFE’ category of groundwater development with excellent potential for the future groundwater development.

Radon and Salinity Mass Balance Constraints on Groundwater Recharge on a Semi-Arid Island (Catalina, California)

Quantifying the freshwater component of submarine groundwater discharge (SGD) is critical in the analysis of terrestrial influences on marine ecosystems and in assessing the water budget and groundwater recharge of coastal aquifers. In semi-arid to arid settings, this quantification is difficult because low SGD rates translate into low concentrations of groundwater solutes in coastal waters. In this study, fresh SGD (FSGD) was quantified for Toyon Bay on Catalina Island, California, for wet and dry seasons using a combination of radon and salinity mass balance models, and the results were compared to watershed-specific groundwater recharge rates obtained from soil water balance (SWB) modeling. Calculated FSGD rates vary only slightly with season and are remarkably similar to the recharge estimates from the SWB model. While sensitivity analyses revealed FSGD estimates to be significantly influenced by uncertainties in geochemical variability of the groundwater end-member and fluctuations of water depth, the results of this study support the SWB-model-based recharge rates. The findings of this study highlight the utility of the radon-and-salinity-mass-balance-based FSGD estimates as groundwater recharge calibration targets, which may aid in establishing more refined sustainable groundwater yields.

Groundwater recharge estimation and potential recharge mapping in the Afram Plains of Ghana using SWAT and remote sensing techniques

The Afram Plains watershed is one of the major watersheds located at the lower part of the Volta Basin in Ghana with high groundwater usage. Dependency on groundwater is a fast-growing concern in the plains due to the unreliable supply of surface water. This has put the groundwater resources under intense pressure and has necessitated the need for sustainable management of the groundwater resources. This study aimed to estimate the recharge, spatial distribution, and potential recharge zones of groundwater at different scales in the Afram Plains area using the Soil and Water Assessment Tool (SWAT) model and Geography Information System (GIS) approach. The SWAT model was set up (1983–2016), calibrated (1983–1990) and validated (1991–1997) using digital elevation model, soil, land use, climate datasets, and discharge data. The GIS approach was used to produce thematic maps for eight contributing factors; rainfall, elevation, land cover land use, lineaments, drainage, geology, soil and slope for mapping the recharge zones. The results showed that about 1.65% (19.3 mm) of the SWAT simulated mean annual rainfall (1176.9 mm) is converted into groundwater recharge in the watershed. The potential recharge zones categorized as very poor, poor, moderate and high zones have area coverages of 0.58% (20.8 km2), 22.4% (798 km2), 60.9% (2169 km2), and 16.2% (576 km2), respectively. The potential recharge zones after validation over boreholes and wells data indicated that the Afram Plains area is dominated by the moderate potential zone.

How Fluvial Deposits Distort Aquifer Recharge Estimated From Groundwater Age: Insights From a Landscape Evolution Model

AbstractSustainable management of groundwater relies on robust estimates of aquifer fluxes. As such, recharge can be estimated from groundwater age using analytical models assuming a homogeneous aquifer. We propose to assess how this assumption affects recharge estimates in fluvial deposits. First, we use CHILD, a landscape evolution model, to generate plausible deposits after tens of thousands of years of river evolution. Then, we use the fractional packing model to compute porosity and permeability of unconsolidated sediments assuming a mixture of a coarse and a fine fraction. Finally, we use PFLOTRAN to simulate groundwater flow and mean age over two thousand years of spatially uniform recharge. This reproduces the boundary conditions underlying Vogel's analytical model to estimate recharge rates. Our results are based on 20,000 realizations from varying inputs: grain sizes, aggradation rate of the river, porosity, recharge, etc. For most models, the mean estimate of the recharge rate remains below an absolute error of 25%. But fluvial heterogeneities can lead to local errors ranging from close to zero to several thousand percent, which means that estimates may vary drastically depending on sampling locations. A sensitivity analysis using the δ‐importance measure and CUSUNORO curves exposes how fluvial processes influence the range and distribution of the error. For instance, a high bank erodibility and small coarse grain size under low aggradation rates favor the reworking of deposits, which increases heterogeneity and leads to high errors. This work paves the way for a more reliable estimation of recharge by considering the sedimentary context.