Assessment of aquifer recharge and groundwater availability in a semiarid region of Brazil in the context of an interbasin water transfer scheme

There are several source codes available to model groundwater flow, such as FEFLOW (Diersch 2014), OpenGeoSys (Kolditz et al. 2012) or AquiMod (Mackay et al. 2014). For this study, the choice of MODFLOW-2005 was made because of its capability to simulate all considered subsurface flow processes, and to be consistent with existing studies in the area thus facilitating comparison with these studies. The Groundwater Modelling System (GMS) software package was used to set up MODFLOW.

The model domain was designed to represent the Medium Aquifer system. Its spatial discretization, a rectangular structured grid, which was required to apply the MODFLOW Control Finite Volume Differences formulation, was selected to simulate the regional groundwater flow. Thus, a fixed grid size of 500 × 500 m was set. The resulting three-dimensional (3D) grid (XYZ) had 208 cells in the X direction, 159 cells in the Y direction and 3 vertical layers, which was based on the main hydrogeological formations in the Medium Aquifer system (Fig. 2).

The area of 2,166 km², in which the Medium Aquifer is unconfined, was used to define the flow domain. The cells inside this polygon were active for the calculation of groundwater head, while the cells outside this area were inactivated. This resulted in 26,277 active cells in the grid. The aquifer depth was set to a mean value of 500 m, based on Mendonça (2001). Previous studies assumed homogeneous hydrogeological properties throughout the aquifer. However, in this study, the total depth was divided into three layers of 100, 100 and 300 m from surface to bottom to account for a possible decrease of hydraulic conductivity caused by sediment compaction (based on Medonça 2001). The digital elevation model (DEM) was obtained from Shuttle Radar Topography Mission (SRTM) data with a resolution of 30 m (Farr et al. 2007). Its reliability was confirmed by Governo do Estado do Ceará (2009), who performed a validation of the DEM topography using elevation points collected by a differential global positioning system (DGPS), which reported a good correspondence between satellite and field data.

The lateral boundaries of the Medium Aquifer were characterized by the Santana aquitard in the east, the Brejo Santo aquitard in the west and the crystalline basement at the northern and southern sides (see Fig. 1). Based on these properties, the lateral boundary conditions were set as no-flow boundaries; however, the Superior Aquifer interacts with the Medium Aquifer system by percolation through the Santana aquitard and infiltration of water emerging from springs at the plateau slope at the contact of the Arajara and Santana formations (see the schematic cross section in Fig. 3). This interaction was represented in the model by the MODFLOW Recharge (RCH) package.

The contribution of natural springs located at the cliff of the Araripe plateau to the recharge of the Medium Aquifer was estimated using a database from COGERH and the National Department of Mineral Production (DNPM). The database lists 320 natural springs with data of annual water production and annual authorized water withdrawal.

Information on pumping wells was retrieved from the database of the Brazilian Geological Survey (CPRM), called SIAGAS (CPRM 2020). Wells with no data concerning depth or pumping rate were excluded. In total, 532 wells were registered within the model domain (Fig. 4), which were implemented in the model by the MODFLOW Well (WEL) package, using elevation, depth and pumping rate (m³/day). Because screen depths were not available for these wells, either a default screen of 10 m was chosen or the wells were assigned automatically to the first layer only (first 100 m) without using screens.

The SIAGAS database also provided information about the type of groundwater use (public, domestic, irrigation, leisure or multiple uses), as well as the allowed hourly pumping rate. The daily pumping rate implemented in MODFLOW was based on Golder-Pivot (2005), Rede Cooperativa de Pesquisa (2007) and the World Bank (2011). For each well with a pumping rate less than or equal to 50 m³/h, a daily pumping regime of 8 h was assumed, corresponding to private wells for domestic water use. For wells with a pumping rate greater than 50 m³/h, a daily pumping regime of 20 h was assumed, corresponding to public and irrigation wells, likely to be pumping water more intensively. The sum of these 532 pumping rates was the artificial discharge of the Medium Aquifer. Assuming that the yearly water demand remained constant during the MODFLOW simulation period (2010–2016), the wells represented an abstraction capacity of 7.14 × 10⁷ m³/year of water.

Streams were added to the groundwater model using the MODFLOW Streamflow Routing (SFR2) package. The simplified Manning equation was adopted, which required values of the hydraulic conductivity of the streambed, width, sinuosity, roughness and value of incoming flow for each stream segment. The package automatically computes flow between the stream and the aquifer, including the channel transmission losses. Values for the hydraulic conductivity of the streambed and stream geometry for each segment were retrieved from field data (FUNCEME 2018). For stream reaches where no field data were available, the values were inferred from the closest measured stream. The reservoir water released as upstream input discharge was considered for some stream reaches.

The recharge to the Medium Aquifer comprises the infiltrated rainfall generated by the surface-water model WASA. Recharge was implemented in the groundwater model MODFLOW as a recharge rate, which was applied to the most upper active cell. The interaction with the Superior Aquifer was also represented using the RCH package at the western boundary of the model as aforementioned. The estimated contribution from the Superior Aquifer using RCH was added to the recharge calculated by WASA. Machado et al. (2007) estimated that 4% of mean annual rainfall infiltrates into the Superior Aquifer System in forested areas, and only one-fifth of this value in the case of deforested areas. They also estimated that about 20% of the total recharge percolates through the Santana aquitard and effectively contributes to the recharge of the Medium Aquifer.

WASA was integrated with MODFLOW, using recharge that was generated by WASA as an input variable for MODFLOW. For each subbasin, WASA yielded a monthly time series of the mean daily recharge to groundwater, which was obtained after streamflow calibration (for more details, see ESM). These values were implemented in MODFLOW using the RCH package, by defining polygons following the subbasins contours. Three additional polygons were created at the western boundary, where the estimated contribution from the Superior Aquifer was added to the WASA recharge rates, resulting in six recharge zones (Fig. 5).

Then, MODFLOW simulated the groundwater flow in the Medium Aquifer at a daily scale with a monthly varying recharge rate in each recharge polygon (sufficient to observe seasonal variations). However, the scarcity of field measurements of hydraulic conductivity and storage coefficients added uncertainty to these model parameters. Data for model calibration were the groundwater level time series measured at 26 monitoring wells (Fig. 4) from 2010 to 2016. Calibration using the algorithm PEST (Doherty et al. 1994) allowed the determination of the set of parameters that best simulated the observations at monitoring wells.

Once the integrated model was calibrated, CAC could be represented in the model as a new channel with the SFR2 package of MODFLOW, releasing water to the main streams in the area. This new input of water to the streams might generate recharge into the Medium Aquifer by channel transmission losses. By carrying out a scenario analysis, i.e. comparing simulations with and without CAC, the effects of this new water management system on the groundwater flow could be assessed. For the scenario analysis, a context of a prolonged drought period was considered, i.e., low groundwater recharge. A scenario analysis approach has been adopted to study the impact of human interventions on surface-water and groundwater resources in other drylands (e.g., Bauer et al. 2006; Izady et al. 2015).

The CAC route was retrieved from a COGERH shapefile and used to create a new SFR2 segment. The channel elevations were estimated from the SRTM raster. The channel width was uniformly set to 20 m, based on design documents. The channel is concreted to preserve the flow of water; thus, the hydraulic conductivity of the streambed was set to 0. The design inflow of 30 m³/s was set at the entrance of the segment. An evaporation value of 1.5 mm/day was also set to account for the evaporation at the water surface. No data regarding the potential amount of water released from the canal to the subbasin streams were available. Thus, an arbitrary value of 0.29 m³/s (5,000 m³/day) was set as inflow to each of the five streams crossed by CAC, in order to preserve the flow to the next canal segments. Since the CAC segment considered here is only a part of this water transfer project (145.3 out of 1,250 km), it was important to ensure that the water release simulation from CAC in the Salgado River watershed does not result in a reduction of flow to the next watersheds crossed by this project.

An uncertainty analysis was also carried out on (1) the simulated groundwater recharge, and (2) the estimation of total pumping volume when CAC was active, since it is not realistic to consider error-free simulated recharge and the pumping rate may be higher during prolonged droughts due to water demand increases, respectively. For the uncertainty analysis on groundwater recharge, it was assumed that the range of recharge uncertainty bounds is proportional to the standard deviation of the error of simulated streamflow, i.e., the observed error at the surface is similar to the error in groundwater recharge. Regarding total pumping volume, an increase of 25 and 50% of the estimated total pumping volume was considered.

Moreover, considering that there is no unique calibration solution for a real-world groundwater modelling application, a MODFLOW parameter sensitivity analysis was carried out to assess the effects of parameter uncertainties on head simulation. Hydraulic conductivity, specific yield and specific storage were selected for the sensitivity analysis, these being the most influential parameters. Then MODFLOW was run, changing individually the selected parameters by the following multiplication factors: 0.1, 0.25, 0.5, 0.75, 1.25, 1.5, 1.75, and 2.0. Finally, the different outputs were plotted and compared.

Calibration-free WASA simulation presented monthly river flow higher than the stream gauge observations. Gradual increase of soil-saturated hydraulic conductivity and porosity increased the amount of water infiltrating the soil profile, therefore decreasing runoff. The optimal fit was obtained after increasing the saturated hydraulic conductivity and porosity by 65%.

Figure 6 shows the interannual variability of the monthly discharge. One distinctive period from 2003 to 2009 was characterized by higher peak discharge during the wet season (January to May). On the other hand, a much drier period could be identified from 2010 until 2016, which was characterized by low peak discharge during the wet season. These two periods can be explained by the interannual variability of precipitation, with the presence of a prolonged meteorological drought in the latter period (not shown).

The simulated river discharge time series (Fig. 6) resulted from the calibration with the highest Nash-Sutcliffe efficiency (NSE). Because of the availability of the measured discharge time series, the chosen calibration period for subbasins 186 and 172 was 1995–2016, and for subbasin 170 this was 2000–2016. Non-calibrated simulations from Güntner (2002) resulted in a NSE of –0.54 for subbasin 186, which was improved to 0.73 after calibration, and a NSE of 0.34 for the subbasin 172, which was improved to 0.61.

However, the performance for subbasin 170 did not improve after calibration, with a NSE of 0.70 without calibration and 0.19 with calibration. This can be explained by the fact that most of this subbasin area (Fig. 4) is located in the crystalline domain, i.e., outside the Araripe sedimentary basin, which corresponds more closely to the parameterization in the non-calibrated version of WASA. As a result, the recharge to groundwater that is input to MODFLOW might be an overestimation in the case of subbasin 170. However, this subbasin forms only a small proportion of the total area, which still leads to a low value of groundwater recharge when compared to the recharge calculated from the other subbasins.

WASA provides a separate output file giving daily deep groundwater recharge for each subbasin in meters cubed. These values were converted to millimeters by dividing them by the subbasin area to match the input requirements of the MODFLOW RCH package. As expected from the precipitation and river flow time series, high interannual variability of groundwater recharge was observed, with a maximum annual recharge of 267 mm simulated for subbasin 186 in 2004 and a minimum annual recharge of less than 1 mm simulated in subbasin 172 in 1993, 2012, 2015 and 2016 (Fig. 7).

When comparing the values used in previous studies with the mean annual recharge of each subbasin for the whole calibration period, the recharge rates of 148.2 and 196 mm/year estimated in the Golder-Pivot (2005) and Rede Cooperativa de Pesquisa (2007) studies, respectively, are much higher than the results obtained by WASA (186: 86.8 mm/year; 172: 40.2 mm/year; and 170: 47.6 mm/year), probably because the former studies assumed a very high constant groundwater recharge rate from the infiltrated rainfall. The long-term recharge values from WASA are more similar to those calculated by the World Bank (2011): 60 mm/year in the western part of the aquifer and 16 m/year in the eastern part. Moreover, the latter study showed higher values of recharge in the western part of the Medium Aquifer, which corresponds to the subbasin 186.

In order to ensure the reliability of the WASA calibration results, it was assessed whether the contribution of each dominant process to the catchment water balance made hydrological sense in the context of the study area (e.g., semiarid climate, sandy soils and intense rainy seasons). To do so, the proportional values of the WASA outputs were summarized: actual evapotranspiration, surface runoff and recharge regarding rainfall in each subbasin for the whole period of simulation (Fig. 8).

Evapotranspiration was 75–85% of rainfall. The remaining part of rainfall was then distributed over the system mainly in surface runoff contributing to river discharge (5–18%) and in recharge to groundwater (5–10%). These values of actual evapotranspiration, surface runoff and recharge are typical for semiarid regions like northeast Brazil (Ponce 1995). Other processes involved in the surface-water balance were, e.g., subsurface runoff, storage contents of the soil layer and interception by plants, representing altogether less than 4% of the total contribution.

Although the overall water balance was similar for the three subbasins, some differences in the relative contribution of each process could be related to the input rainfall data combined with the characteristics of the study area. For instance, the higher proportion of surface runoff in subbasins 186 and 170 compared to that from 172 could be explained by higher precipitation in the former. Based on the mean annual precipitation in the three subbasins (subbasin 186: 975 mm; subbasin 172: 737 mm; and subbasin 170: 869 mm), differences in runoff responses are expected. This explained partly the lower contribution of surface runoff to the water balance in subbasin 172, although this subbasin is mainly located over a crystalline basement. This lower surface runoff was compensated by a higher actual evapotranspiration rate.

The order of magnitude of most of the inflows and outflows of the groundwater system could be quantified before MODFLOW application. Here the overall water balance of the Medium Aquifer was presented for the whole period of WASA simulation (1990–2016), based on WASA outputs, available regional data and previous studies (Table 1).

The amount of water percolating through the Santana aquitard to the Medium Aquifer was estimated using the average rainfall time series over the Araripe plateau. For the period 1990–2016, this resulted in a mean annual percolation of 6.5 mm in forested areas and 1.3 mm in deforested areas. When applied to an area of 600 km², corresponding to the overlying Santana Formation, the estimated inflow to the Medium Aquifer (2,166 km²) was 2.3 × 10⁶ m³/year or 1.1 mm/year. The potential amount of water available from the springs located at the cliff of the Araripe plateau was estimated by calculating the difference between water production and withdrawal. The contribution of these springs to recharge was only 6 × 10⁵ m³/year or 0.3 mm/year, considering a 7% infiltration rate, which was based on the recharge rates obtained with WASA. The sum of the contribution of the Santana aquitard percolation and the recharge from springs is equal to 1.4 mm/year, which is the total contribution of the Superior Aquifer percolation.

Therefore, the total contribution of the Superior Aquifer percolation could be considered negligible in comparison to the catchment rainfall infiltration. The catchment rainfall infiltration was the most relevant component of the Medium Aquifer recharge, being circa 47 times the Superior Aquifer percolation on average. The annual recharge was approximately twice the amount of water abstracted, which indicates an average increase in the water level between 1990 and 2016. This abstraction rate would indicate a sustainable use of groundwater. However, the results from WASA showed a high interannual variability of groundwater recharge. While periods with high rainfall resulted in recharge reaching 184.7 mm/year like in 2008, annual rainfall was much lower from 2012 to 2016, resulting in a mean annual recharge dropping to 13.9 mm. Therefore, when considering this drought period, groundwater abstraction becomes unsustainable, as abstraction is now circa twice the amount of recharge.

In fact, groundwater abstraction might be much higher and, consequently, significantly unsustainable. The study of Golder-Pivot (2005) estimated an annual increase in water demand of 1.77%, which would represent an increase of the abstraction capacity by 1.3 × 10⁶ m³/year. Moreover, it is expected that during a prolonged drought period, water demand increases, resulting in increased groundwater abstraction.

First simulations were run in steady state to reproduce the initial head distribution in the study area, i.e., a stationary situation with no storage change. The abstraction wells were not included to simulate groundwater flow in which inflow was equal to outflow over one hydrological year. The steady-state model using PEST was calibrated to reproduce the initial head distribution observed at monitoring wells on August 1, 2012. The calibration of hydraulic conductivity, recharge rate and hydraulic conductivity of the streambed resulted in the head distribution presented in Fig. 9.

The groundwater flow in the Medium Aquifer after the steady-state calibration showed a general flow direction from S–SW to N–NE. The flow direction was mainly driven by topography, following the downhill slope from the Araripe plateau and converging to the main river network, which are the natural outlets of the aquifer. Channel transmission losses occurred mainly in upstream areas.

The model’s capability to reproduce the head distribution observed could be analysed from the model residuals. The calibration resulted in a mean residual head of –0.62 m, a root mean squared (RMS) residual head of 9.48 m, and a scaled RMS error of 0.23, which is calculated as RMS divided by the range of observed head (i.e., maximum head – minimum head). The largest residual heads were observed in the central part of the model, with a maximum residual of almost 26 m. The lowest residual heads were mainly observed in the western part of the model, with a minimum residual of –18.2 m observed. The coefficient of correlation of 0.925 between observed and simulated head reflects a satisfactory representation of the groundwater flow at the beginning of the transient simulation (Fig. 10).

The values of the parameters obtained after the steady-state calibration (Table 2) were quite different from the initial values set for the Medium Aquifer from previous studies. For instance, the calibrated hydraulic conductivity for layers 2 and 3 (0.1 m/day) seemed to be very low to represent sandy sedimentary formations, which were estimated at about 5 m/day by Mendonça (2001) using pumping test data. In addition, the calibrated recharge was quite different between the recharge zones, whereas the results from WASA were more homogeneous between the subbasins. In fact, it seems unrealistic to observe such drastic spatial changes in recharge rates, which could be explained by a high contribution of groundwater flow to storage in the initial head distribution. Moreover, since recharge is temporally highly variable due to high precipitation variability, it was inappropriate to use the calibrated recharge from the steady-state model for the 4–5 years of transient simulation. Therefore, WASA recharge was used as direct recharge input in the transient model (see next section); however, besides the uncertainties involved, the low mean residual head obtained after steady-state calibration meant this simulation provided satisfactory initial head conditions for the transient calibration of the regional groundwater flow.

Simulation of the groundwater flow in transient mode requires imposing stresses on the system varying with time. Here, the recharge was applied as a monthly varying stress entering the system to account for the intra-annual variability caused by distinct seasonality and the interannual variability caused by the highly variable annual precipitation. Groundwater flow was then simulated using a monthly time step from September 2012 to September 2016. As stated earlier, the dataset resulting from the steady-state calibration in September 2011 was exported and used as the initial heads for the transient simulation of the groundwater flow in the Medium Aquifer system.

The main issue was compensating for the error introduced by the initial discrepancy in storage, which led to an enormous amount of water leaving the aquifer at the streams in the lowest elevation part of the model domain (NE part, downstream end of the main river network), where the groundwater level was simulated as being several meters above the streambed elevation. Ultimately, a transient calibration of the model was performed, adjusting the hydraulic conductivities of the three layers, the hydraulic conductivity of the streambed, and the specific yield. The model calibration showed satisfactory results with a mean residual head of –1.15 m and an RMS residual head of 10.27 m for the total simulation period, with optimal parameters presented in Table 3.

Figure 11 shows the changes of hydraulic head over the simulation period. No large change of regional flow direction or water level could be observed, in accordance with the low recharge computed for the period 2012–2016 (Fig. 7). The main change from Figs. 11a to 11b was a decrease in the groundwater dome presented in the central part of the model domain. This change may be attributed to the overestimation of the groundwater level in the initial head distribution. A steady decrease of the hydraulic head could be observed in the model over the period of simulation in the northwestern part of the model, which could be explained by the high density of pumping wells in this area (Fig. 4).

The capability of the calibrated model to reproduce the intra-annual and interannual variations of the hydraulic head at monitoring wells differed in the study area. The model accurately reproduced the interannual head variations in the northwest (corresponding to WASA subbasin 186) such as shown in Fig. 12a,b; this area comprises 25 boreholes (66% of the total). On the other hand, performance was much poorer in the central part (equivalent to subbasin 170) as shown in Fig. 12c,d, and in the southeast (subbasin 172) as shown in Fig. 12e,f. In these latter two areas, the poorer calibration represents much fewer boreholes; thus, local aquifer heterogeneities are more influential on the discrepancies between simulated and observed heads. This could be partly explained by the performance of WASA in estimating recharge in the three subbasins (see NSE of the calibrated WASA model). WASA performed better at reproducing discharge at the outlet of subbasin 186. The groundwater modelling uncertainties may also be related to the simplified representation of the geology—e.g., no variation of lithology and sediment thickness—and the groundwater abstraction data scarcity.

The comparison between the performance of the WASA-MODFLOW modelling and three previous models is summarized in Table 4, which shows that the model performance was an improvement in steady-state simulation compared to the studies of Golder-Pivot (2005) and the World Bank (2011). For transient simulations, the model of this study performed much better than that from Rede Cooperativa de Pesquisa (2007). Also, for transient simulations, the WASA-MODFLOW modelling performance was similar to the model performance in the study of the World Bank; however, this comparison of performances should be considered with caution since the aim of the study, size of modelled area, modelling approach and data used for calibration were quite different between the considered studies.

The Ceará Water Belt was added to the modelling as a new SFR2 segment. For small discharges, such as the CAC releases, it was also assumed that flows were concentrated in streambed paths that have much lower hydraulic conductivity than the total streambed area and river banks (Lange 2005; Souza and Costa 2014). Therefore, assuming the presence of clogging layers with hydraulic properties similar to silty clay soils, this study assessed the hydraulic conductivity of the streambed for the five streams receiving water from CAC equal to 2.21 m/day (calibrated value) and 0.01 m/day (new assumed value), which avoided having all the water released from infiltrating into the aquifer in the first stream cells.

The potential of the SFR water transfer-CAC implementation was investigated by running the calibrated MODFLOW in transient mode for 5 years beyond the end of the head time series, i.e., a scenario from August 2016 to January 2022. The scenario results were compared with and without CAC. The head distribution of the calibrated transient model for August 2016 was set as the initial condition. The recharge time series for the 2011–2016 simulation, which was a period of severe drought, was replicated for the 2016–2022 scenario, to assess the potential of the water transfer scheme in the context of a prolonged drought.

Considering a streambed hydraulic conductivity of 0.01 m/day, the implementation of CAC led to an increase of the hydraulic head by up to 3 m at the outlet of the Medium Aquifer system after 5 years (2016–2022 scenario; Fig. 13). Moreover, there was an average increase of the hydraulic heads over the study area of 0.5–1 m. The daily amount of groundwater recharge by channel transmission losses resulting from water release of CAC was estimated as 1.89 × 10⁴ m³, which represented an additional recharge of 6.89 × 10⁶ m³/year in the context of a prolonged drought. However, it is important to note that the CAC-driven recharge input did not compensate for the relevant decrease of the hydraulic heads in areas that do not surround the receiving streams (Fig. 13), resulting from the joint effect of low natural recharge (drought) and high groundwater pumping. Therefore, the water transfer scheme would represent an additional source of recharge to the Medium Aquifer, but it would not solve alone the issue of unsustainable management of groundwater resources, a result also confirmed even when a streambed hydraulic conductivity was 2.21 m/day. The difference from this scenario was only a concentration of higher heads (from 0.25 to 1.50 m) in the upstream parts of the Medium Aquifer (Fig. 14); however, it clearly indicated that water transportation downstream and beyond the Medium Aquifer system may be more difficult due to higher streambed hydraulic conductivity.

Assessing a variation of ±25% of the simulated groundwater recharge in the 2016–2022 scenario, which is proportional to the observed error of WASA-based simulated streamflows, it was found that an increase of 25% in the groundwater recharge presented a low influence on the hydraulic heads with most of the head differences close to zero (Fig. 15a). The head differences are defined as the differences between the changed simulated recharge and the original one. On the other hand, a decrease of 25% in the groundwater recharge was enough to reduce the head difference around –1.0 m (Fig. 15b), which practically balances the gains from the CAC-driven recharge input; therefore, severe droughts may impose even a greater challenge for managed aquifer recharge in the Salgado River watershed.

An increase of 25 and 50% of the estimated total pumping volume was assessed, since water demand increases may trigger higher pumping rates during prolonged droughts. It was found that an increase of 25 and 50% of the estimated total pumping volume has a relevant negative impact on the groundwater level in the northwest, which makes the gains from the CAC-driven recharge input negligible (Fig. 16a). On the other hand, this higher pumping rate scenario showed a low impact on the groundwater level in the southeast (Fig. 16b); therefore, this uncertainty analysis suggested a larger artificial recharge demand in the northwest, and that water transportation downstream and beyond the Medium Aquifer is preferable to using the streams in the southeast.

Finally, evaluating the influence of MODFLOW parameter uncertainties on head simulation (see the outputs of MODFLOW parameter sensitivity analysis in ESM), it was found that lower hydraulic conductivities and lower specific yields presented the largest impacts on head simulation, principally in the northwest and in the central part of the model domain with predominantly lower head (Figs. S1 and S2 in the ESM), while higher hydraulic conductivities and higher specific yields presented negligible influence on head simulation surrounding the receiving streams (Figs. S1 and S2 in the ESM). The changes in specific storage presented very low influence on head simulation in most parts of the modelling domain with a head difference less than 0.5 m. If the order of magnitude of hydraulic conductivities and specific yields were not matched, a larger artificial recharge demand would be necessary to balance the lower groundwater level in the northwest and in the central part of the Medium Aquifer system. On the other hand, this parameter sensitivity analysis confirmed that water transportation downstream and beyond the system is preferable using the streams in the southeast, because of low influence of parameter changes on the region surrounding them.

When interbasin water transfers are planned, many dimensions must be considered, including engineering, economics, climatology, ecology, law, and politics (Gupta and van der Zaag 2008). Problems and controversies consistently accompany such projects, especially the increasingly common water transfer ‘mega-projects’ (Shumilova et al. 2018). For example, the world’s largest such project, the South-to-North Water Diversion Project in China, has been plagued with controversies since conceptualisation in the 1950s over the involuntary resettlement of 100,000s of people, unequal economic development in donor and recipient basins, and potential downstream water quality impacts and salinisation of agricultural land (Shao et al. 2003; Rogers et al. 2020). While this study does not seek to respond to most of these seemingly inherent controversies, it can counter several reported criticisms of interbasin water transfer schemes and suggest how they can contribute to integrated water resources management (the examples here are from Brazil but are applicable elsewhere). Firstly, conflict has been reported between donor and recipient basins of the Paraíba do Sul River water transfer scheme when drought forced inadequate downstream flows (de Andrade et al. 2011). The findings of this study show that increased groundwater availability, at least in the vicinity of the streams, could buffer periods of drought. Secondly, riparian communities to the São Francisco Transbasin Project have spoken of concerns of water being prioritised for large economic centres (de Andrade et al. 2011). The modelling demonstrated that equivalent communities riparian to the CAC and its receiving streams should benefit from enhanced groundwater recharge augmenting their water resources. Thirdly, while not a criticism of interbasin water transfers per se, Brazil has been criticized for being behind in promoting managed aquifer recharge, a successful solution to water scarcity in other semiarid regions of the world (Shubo et al. 2020). This study demonstrates the viability of artificially recharging aquifers via interbasin transfers, where the hydrogeology allows.