Groundwater Modeling in Agricultural Arid Area under Different Scenarios, East Nile Delta, Egypt

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Abdulaziz, Osman Abdelghany, Alaa Ahmed This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4749523/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The East Nile Delta represents the natural extension of the Nile Delta that recently showed significant changes in groundwater system related to both agricultural and urbanization land development. The current study presents a GIS-based 3D groundwater flow model to outline a safe framework for pumping stress management to the upper 100 m of Quaternary aquifer located North of Ismaelia Canal. Model construction comprised 93 borehole data to model a 19-layer grid of the fluvial Quaternary deposits. The finite difference MODFLOW 2000 accomplished simulation to predict groundwater head distribution across the aquifer system in both steady and transient states. Steady state model is calibrated to the 1991-groundwater hydrogeological map of Egypt, and subsequently provided the initial conditions for the 1991–2005 transient simulation. The transient model is considered calibrated as the calculated head matches the field observations of 2004–2005. Using severe aquifer stress strategy, three scenarios are proposed to manage the reported local rise in groundwater head and evaluate the potential aquifer production during drought. This involved using several infiltration rates from irrigation return and pumping stress to model predictions extending to the year 2030. Results showed pumping controls to the rising groundwater head especially towards the North where confinement conditions prevail with two subregions, northern and southern, requiring different schemes of management. Optimum pumping and infiltration rate are determined for these subregions and for the unconfined parts of the Quaternary aquifer. During drought, a maximum of 500 million m 3 /yr are producible from the unconfined aquifer with standard discharge of 5000 m 3 /d that may induce drawdown less than 0.5 m. The water budget of modeled aquifer indicated that pumping stress is predominantly balanced by seepage from Ismaelia canal and Damietta branch with slight contributions from irrigation canals and drains. Details of water budget and changes in groundwater head to pumping stresses across the modeled area are presented and discussed in detail. The model results provide a scientific platform to delineate efficient and sustainable management to the East Nile Delta Quaternary aquifer associating active dynamic land development. Earth and environmental sciences/Environmental sciences/Environmental chemistry Earth and environmental sciences/Environmental sciences/Environmental impact Earth and environmental sciences/Hydrology Water resources management Groundwater flow modelling Arid regions Quaternary aquifer East Nile Delta Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction During recent decades, the demand for water has been increasing due to urbanization and industrialization around the world. In arid regions, the prolonged droughts, climate change variabilities and overexploitation of aquifer systems intensifies the depletion and deterioration of water quality and impacts the ecosystem [ 1 – 3 ]. Consequently, a wise balance/equilibrium between aquifer in-flow (losing rivers/canals, rainfall, and excess irrigation) and aquifer out-flow (withdrawals for development purposes, baseflow, and seepage) is urgently needed [ 4 ]. An in-depth understanding of aquifer characteristics becomes vital for the conservation and efficient management of groundwater resources. However, the subsurface environment is not easily accessible and restricted by several factors that can contribute to the complexity of the groundwater movement, including heterogeneity and multiphase flow. In general, geological heterogeneity represents an influential constraint to any hydrogeological aspects including recharge that in consequence controls aquifer productivity [ 5 ]. In such cases, models provide a novel way to understand, simulate, and forecast the behavior of groundwater systems. Understanding aquifer performance, defining sustainable water resource management, forecasting and anticipating solute transport can all benefit significantly using numerical and/or analytical models [ 6 , 7 ]. But also, it is worth mentioning that there are lots of complexities associated with groundwater flow modeling, and it is always suggested to start with a conceptual model. After successful conceptualization of the simple model, complexity in the model can be added [ 8 ]. Various authors have proposed different techniques for creating conceptual models, which are essential for transport modeling. [ 9 ] explored the benefits, purposes, and definitions of conceptual models within the domain of experts. [ 10 ] suggest that a single-layer model is sufficient for assessing water balance, while three-layer and five-layer models are recommended for representing aquitards in practical applications. [ 11 ] have conducted commendable work by comparing multiple alternative models in various scenarios and addressing associated challenges. A conceptual model serves as a simplified representation of the area being studied, encompassing the model domain, boundary conditions, sources, sinks, and material zones. The main objective of constructing a conceptual model is to simplify the field problem and organize the associated data so that the system can be analyzed more readily. The need for simplifying assumptions arises due to the impracticality of completely reconstructing the field system and the scarcity of data required for a comprehensive description of the system. It is crucial to maintain simplicity in the conceptual model while ensuring that it has the capacity to effectively represent the physical aspects of hydrological behavior. However, the model should not be overly constrained in a manner that artificially limits the range of predicted outcomes. Challenges in approximating reality become more pronounced during transport modeling as solute transport processes are simplified to a few dominant mechanisms, in addition to simplifying flow [ 12 ]. The current investigation introduces a methodology that utilizes spatially varied data for water table variations, hydro-geological zones, and various geospatial and modelling tools to evaluate the aquifer production under different scenarios. This approach deviates from the conventional practice of using a lump sum value of average recharge for the study area. Instead, the methodology employs these spatially distributed values to develop a conceptual groundwater flow model. Materials and Methods Materials and Methods 2.1 Study area The East Nile Delta falls in-between latitudes 30º 00' and 31º 30' and longitudes 31º 00' and 32º 30' and is characterized into two basic physiographic units (Fig. 1): river terraces of fluvial/deltaic origin and fluvio-marine flats [ 13 ]. Major rivers flood plains, e.g., Nile Delta, are known for having an aquifer system made of a succession fine grained layers, typically mud size, and highly permeable sand and gravel zones that associated complex confinement conditions [ 14 ]. These changes confinement conditions restraint groundwater flow, especially for shallow aquifers where active land development and substantial water volume is abstracted or supplemented. For the East Nile Delta, [ 15 ] estimated a water deficit of 789.81 MCM/year was at Ismailia, Al-Salhiya, El Qantara West, Port Said and Fayed, while [ 16 ] evaluated the risks of heavy metal accumulation in Qalubiya drain and related high concentrations to contributions from municipal, industrial, and agricultural wastes. Thus, numerous management actions are taken to mitigate such effects on the agricultural and industrial development plans. This comprised the abstraction of additional 4 billion m3 from the Nile Delta Quaternary aquifer, exceeding the reused water to 2.3 billion m3, and improving irrigation practices and domestic water use to save freshwater loss of approximately 2.5 billion m 3 [ 17 ]. Thus, the sustainable groundwater development plans became vital to maintain water use under potential aquifer stress during droughts. 2.2 Building geological model. To evaluate the aquifer system performance to severe pumping stress, a 3D groundwater flow model is constructed to simulate water resources management. In this model, a 3D finite difference model was developed to simulate groundwater flow in the Quaternary aquifer of East Nile Delta region between 2004 and 2030. To numerically solve the governing flow equation based on water balance with a fully implicit finite different approximation, MODFLOW 2000 [ 18 ] with the governing logic presented in Eq. 1 was implemented. $$\:\frac{\partial\:}{\partial\:x}\left({K}_{xx\:}h\frac{\partial\:h}{\partial\:x}\right)+\frac{\partial\:}{\partial\:y}\left({K}_{yy}\:h\frac{\partial\:h}{\partial\:y}\right)+\frac{\partial\:}{\partial\:z}\left({K}_{zz}\:h\frac{\partial\:h}{\partial\:y}\right)-\omega\:={S}_{s}\frac{\partial\:h}{\partial\:t}$$ 1 Where: K xx , K yy , K zz are K values (m 3 /d) along x, y, and z axis, h is the hydraulic head, ω is a source and sink term (volumetric flux m 3 /d), S s is the specific storage (dimensionless), and t is time (day). A well calibrated groundwater flow model that simulates the flow through the complex stratigraphy of the Nile Delta flood plain, was constructed using the following basic steps. Typically, MODFLOW uses a structured grid of consistently continuous layers across the model domain. Therefore, 93 borehole data selected in the study area was first checked to confirm relative spatial continuation of the layers in the model domain. Five hydrostratigraphic units were identified to model the complex fluvial features of the Quaternary aquifer including clay, sandy clay, fine sand, coarse sand, and sand and gravel. These units were mapped to 19 horizons within a model georeferenced to UTM system and NAD 1984- zone 36N projection. These horizons are modeled to solids using a distance weighted interpolation algorithm that extend to a total of 100m depth. Before converting solids to MODFLOW, a grid layers of 125 column, 175 rows, and 19 layers was constructed and rotated 30˚, so that the MODFLOW grid is parallel to the dominant direction of groundwater flow (Fig. 2). Within solids each horizon was mapped into a single layer within MODFLOW grid. MODFLOW solves the groundwater flow equation on a cell-by-cell basis within the 3D grid. 2.3 Conceptual model Conceptual model approach is used to build the MODFLOW model with model parameters designed as sources and sinks, boundary conditions, and observation points in the map module using GIS tools. In this model, confinement conditions were set as convertible with a contrast of two orders magnitude (or more) of in hydraulic conductivity of successive hydrostratigraphic units as a basis for automatic assignment [ 19 ]. The developed conceptual model consists of three coverages including sources and sinks, recharge zones, and observation points (Fig. 2, a). After visual examination of the flow lines and inspection of the inflow – outflow locations, four physical boundaries including Demietta Branch, Ismaelia Canal, Suez Canal, and Mediterranean Sea were mapped as specified head boundaries to the modeled area (Table .1). [ 19 ] indicated that conventional finite difference equations do not recognize that a well penetrating more than one stratigraphic unit forms pathway for water movement between layers. Therefore, the calculated head in multilayer aquifer system represents the composite average of the heads in all the penetrated layers. Table 1 Hydraulic parameters for steady model and specific yield and specific storage for transient model Steady State Model Hydraulic Conductivity (Kh: m/d) Clay 0.0015 Sandy Clay 0.85 Fine Sand 1.1 Coarse Sand 85 Sand & Gravel 375 Recharge Rate (m/d) Traditional Agriculture 0.00000582: 0.00005 Reclamation Land 0.000059: 0.0029456 Conductance (m/d) Irrigation Canals 0.001: 0.03 Drains 0.01 :0.12 Transient Model Material Specific yield (unitless) Specific Storage (1/m) Shale 0.05 .0.08 Sandy Shale 0.06 0.001 Fine Sand 0.25 0.005 Coarse Sand 0.3 0.0004 Sand & Gravel 0.35 0.00004 In this study, 170 sites are selected to represent more than 6000 production wells that pump a total volume of approximately 2.1 million m 3 /d from the modeled area. In all wells, screen intervals were assigned based on the pumping rate and well depth, while high intensity fluxes were assigned to the lower sand and gravel unit to avoid dry cells effect. For each river arc, the head and conductance of the river bottom was assigned based on data in Table (1) or estimated relative to the nearest known head. In addition, the main drains were simulated using the drain package with head and conductance assigned as described in rivers (Table 1 ). For simplicity, El Manzala Lake was simulated as a general head polygon with a general head of 0.25 m amsl. In the present model, at least 12 recharge zones were identified in the agriculture land with recharge rates ranging between 5.82 e-6 m/d in the traditional agricultural land to 0.00029 m/d in the reclaimed land. Model calibration is essential to maintain trustworthy prediction that lacks wet and dry cells in addition to the erroneous head distribution. It typically includes observation points where calculated and observed head should considerably match through adjusting some input parameters. For model verification, forty observation points, mostly belonging to Research Institute for Ground Water’s observation network, are used to calibrate the unstressed steady state model. Alternatively, observation heads of 46 wells were imported for model calibration during transient simulation. 3.4 Model execution Before execution, the 3D-model was checked for errors and warnings to ensure conversion and accurate solution. Storativity and Transmissivity of modeled hydrogeologic units are assigned while the specific yield values fall in the possible ranges published by [ 20 ]. Alternatively, the storage parameters of hydrostratigraphic units for the transient model are listed in Table 1 . Hydraulic conductivity, conductance, and recharge rate appear influential parameters for systematic adjustment while model calibration. These parameters are sequentially adjusted followed by repeated run/rerun using error estimation and calibration statistics as constraint. The model is considered calibrated for steady state as the mean error approached − 0.066 with RMSE of 0.505 m, which is practically very small compared to the total head (14.5 m). Table 1 shows the final input parameters that were used in the calibrated unstressed steady state model. Converting steady model into transient usually involves large datasets including recharge and well data together with observation data. In addition, model validity is sensitive to the selection of appropriate time steps that associate minimal impacts on numerical results. Transient simulations of the present study fall within two types: interpretive and predictive. The 1990–2004 transient simulation is interpretive to the system response to land use changes described by [ 21 ] using field observations in 2004 for model calibration. A total of 46 head data, with 95% confidence and 10% observed head interval, collected in summer of 2004 are utilized in transient model calibration. The calibrated transient model is consequently used for predictions of aquifer responses for different stress scenarios. Results and Discussion Groundwater flow models are developed as a well-established tool applied over local or regional scale for evaluating the potential of groundwater resources [ 22 ]. In the present study, changes in pumping data for transient model were insignificant over the interpretive transient simulation, as agricultural land development was mainly based on surface water between 1990 and 2003 (Abdel Salam et al, 2004). Figure 2b presents the head distribution for the calibrated unstressed steady state model. A plot to the calculated versus observed head at 40 observation points utilized in model calibration indicates a good match (Fig. 3a). Transient simulation is classically used to investigate time-dependent problems and typically requires starting with a calibrated model for steady state. For transient simulation, most input parameters of calibrated unstressed steady model are slightly changed but the geometry of recharge zones is adjusted to fit the progressive changes in land use between 1990–2004 [ 21 ]. Once the transient model is considered calibrated (Fig. 3c), the 1984–2004 head inventory showed a progressive rise in groundwater head indicating a remarkable increase in aquifer storage, i.e. gaining aquifer. Thus, recharge represents the only stress parameter prevailed transient simulation between 1990 and 2004, with other parameters of source and sink remain unchanged. The recharge rate is systematically adjusted for each independent recharge zone followed by transient model execution. Aquifer stress considered 8-stress periods of 2-years each with 2-time steps for each stress period through the entire simulation period. The computed water budget involves the Inflow and Out-Flow budgets. Figure 3b and 3d present the groundwater budgets for the 1990–2004 calibrated interpretive transient simulation. Constant head, irrigation canals, and recharge are the major contributions to In-Flow budget, while storage and general head constitute secondary components (Fig. 3b). In addition, recharge showed a significant progressive increase to groundwater system In-Flow over the simulated period, while constant head reported a gradual decrease. On the contrary, pumping wells and discharge to drains presented the major contributions to the 1990–2004 Out-Flow water budget, with minimal annual changes for all contributions through the simulated period Fig. 3d). 3.1 The transient model predictions The 1990–2004 interpretive transient simulation offers a valuable technique to evaluate the annual rate of aquifer gain that defined a form of biannual periodic increase in recharge rate. Statistically, recharge rates ranged between 2.39 10 − 5 m/d and 2.04 10 − 7 m/d with an average value of 4.61 10 − 6 m/d. Assuming limited changes to aquifer conditions with minimal changes in land use, 2024-head distribution within the modeled East Nile Delta region is predicted (Fig. 4a). Such a prediction in head change distributions provides valuable information for efficient planning and sustainable development to groundwater system including rate and dispersal of withdrawal stress. The 2024-model prediction (Fig. 4b) indicates a significant head rise to the northern part of the reclamation area which acts as a drain to the entire developed area and coincides with the direction of the overall northward groundwater flow. The other zone is encountered near Qalub area (Fig. 1) where mass population and active agricultural activities near unconfined aquifer are reported. Similar observations are encountered in various localities at the desert fringes of the Nile Valley and/or Nile Delta that approach serious problems including water logging [ 23 ]. Due to the nature of fluvial and fluviomarine depositional environment of the Quaternary aquifer, local vertical heterogeneity in facies induce markable local variations in groundwater head. Because of the aquifer heterogeneity in vertical and spatial domains, it is expected that the rate at which groundwater head rise would locally vary across the aquifer. Therefore, 17 representative sites are selected for monitoring groundwater head across the model (Fig. 4a and b) which indicated marked head change variations (2.0 m at R4/R6 and < 0.2 m at R1). As shown in Fig. 4b, the rise in groundwater head of the reclamation land varied increasingly between 2.0 m (R4 and R6) and less than 0.2 m at R1 site with gradual decrease north- and eastward. In the traditional agricultural lands, the maximum reported rise reported 1.6 m at T9, but most T-stations fall between .3 and .75 m. The inventory of model budget indicated constant head and recharge as the main In-Flow budget components and the recharge volume increased to 1.433.850 m 3 /d with slight decrease to infiltration from irrigation canals and constant head (Fig. 5a). In addition, negligible changes to aquifer storage and general head contributions to the In-Flow budget may reflect prevalent unconfined conditions of the aquifer. Alternatively, Out-Flow budget (Fig. 5b) reported production wells and drains as primary constituents with limited contributions from the discharge to general head and constant head components. Despite the obvious negligence to storage as a primary Out-Flow component, it is almost duplicated (121.000 m3/d versus 239.000 m3/d) because of the rising groundwater head (Fig. 4b). 3.2 The predicted aquifer stress In theory, an unlimited number of strategies of aquifer stress can be tested using the calibrated transient model, however applicable strategies remain dependent on the actual field practices [ 24 ]. Due to hydrochemical and hydrogeological constrains related to water salinity and water quality, potential aquifer development is viable to the area located south of + 4m potentiometric surface with a buffer zone of 3–5 km width to the West of Suez Canal to keep fresh-salt water interface undisturbed [ 25 ]. In this study, high pumping stress strategy (utilizing three different pumping scenarios, Fig. 6) is considered to continue to the year 2030 using additional 100 sites for groundwater withdrawal distributed over the predefined aquifer development area, particularly at Agri-reclamation projects and main populated areas within traditional Delta fringe. Seasonal pumping is adopted using various pumping rates over the year with a maximum duration of 8 years to achieve a safe yield in the Quaternary aquifer. Intensive pumping (60–70% of annual abstraction) was reserved for summer period (April-October) that requires greater water volumes for both municipal and agricultural consumption. Most of this groundwater abstraction is pumped at the reclamation land with restricted pumping (3–6 million m 3 /yr) assigned to the area located north of Mit Ghamr city (Fig. 1). Simulations of the high stress scenarios showed slight drawdown (~ 0.3 m) in T4, T5, T10 and R1 (Fig. 7a, c, and e), while the maximum drawdown is always seen at T4 and T5 (Fig. 4a). On the contrary, an increase in head (0.05–0.35 m) at R3, R6, and T8 is reported, with higher head seen in R6 and T8 (Fig. 4). Drawdown patterns are related to the distribution of pumping stress, both magnitude and time, except for R1 with gentle linear head decrease associating the strategy systematic decrease in recharge. Water budget calculations (Fig. 7b, d, and f) presented infiltration from the specified head and In-storage as important contributions to In-Flow budget while the obvious increase, as expected, is reserved to additional pumping stresses. The calculated constant head has increased to 1.804.400, 293.969, and 149.058 m 3 /d for strategy I, II, and III respectively, demonstrating excessive influx with the periodic pumping stress of strategy I. Alternatively, Out-Flow budget indicated substantial storage decrease (112.119 m 3 /d) for all scenarios and was inversely related-to pumping stress representing constant head compensation, reported as In-Flow, for additional pumping rather than storage (Fig. 7b, d, and f). Except for the slight increase in infiltration from general head and irrigation canals and a slight decrease in quantities trapped by the general head, other water budget components of this strategy presented negligible changes (~ 10.000 m 3 /d) over the simulation time (Fig. 7b, d, and f). 3.3 Aquifer response to pumping stress. Approximately all model runs for the study area confirmed that the constant head, particularly Ismaelia Canal, and infiltration of excess irrigation water present the principal contributors to aquifer replenishment while well abstractions are the main discharge element. Field works and previous literatures reported the quaternary aquifer of less than 150m thick and comprises fresh groundwater overlying brackish water that change northward to salt water at Mit Ghamr that progressively increase southward to ~ 200 m at Zifta (Fig. 1). Zift-Mit Ghamr strip appears sensitive to saltwater encroachment due to aquifer disturbances by groundwater abstraction with a maximum permissible drawdown not more than 0.5 m. The calculated drawdown associating the additional pumping (3–6 million m 3 /yr) over the 3 scenarios of high stress strategy around Mit Ghamr fall between 0.20 and 0.45m delineating the framework to the maximum available abstraction (1000 m 3 /d) at the northern confined aquifer to maintain stabilized fresh-salt water interface. The northern confined aquifer showed a water budget with local recharge primarily from returned irrigation water and small quantity related seepage of irrigation canals. In addition, the change in storage indicated a total change of 70.000 m3/d that mainly explains a drawdown of moderate effect at this area. For the Nile River-Demietta branch, the flow budget presented outflow exceeding Inflow by approximately 5.000 m3/d and such a value indicates the sensitivity of the aquifer at this area for any further pumping stress. Thus, the northern confined aquifer possesses a limited potential as water supply and local assessment to the subregion should be carefully considered before additional groundwater abstraction is proposed. Both the confined and unconfined parts of the modeled aquifer present a good potential to the area extending south of Mit Ghamr, with the maximum anticipated yields located between Banha and Qalub (Fig. 1). This is confirmed by the monitoring points in the southern confined aquifer (T8 and T10, Figs. 6 and 4a) with drawdown less than 0.4 m in all scenarios of the extreme aquifer stress, significantly less than the maximum permissible drawdown (1.0 m) at this area. However, the southern confined aquifer stress near the proximity of Mit Ghamr should avoid northward propagating resonance of over pumping, especially for long time. The presence of irrigation canals, especially the main canals in the unconfined part of the aquifer, e.g., Ismaelia Canal, plays an important role in aquifer response to pumping stress. For example, T10 located far away from main streams follows the rhythm of pumping scenarios while T8 response appears unaffected due to the replenishment by infiltration from Ismaelia Canal (Fig. 4a and 6). In addition, continuous pumping of moderate to high stresses (scenario II) induces a drawdown greater than the periodic pumping even if it involves stages of higher pumping (Scenarios I and III) than those of continuous pumping (Fig. 6). Notably, the groundwater heads at R3, R6, and T8 show continuous rise over the simulation period as if these areas are not affected by pumping. This is true for R3 because it is located at the buffer zone of Lake Manzala, but the subregions around R6 and T8 are affected by pumping stress stabilized by excessive infiltration from the main irrigation canals (Ismaelia canal-its branch El Salheya El Gadida canal for R6 and Ismaelia Canal-Bahr Muis for T8). The drawdown is commonly recovered over a 3–4-year period following the peak stress and recovery typically follows a gradual pattern. Generally, analysis of water budget and head response nominated the southern confined aquifer as a potential site for groundwater storage and development with continuous pumping capacity of approximately 300–450 million m3/yr over several years of drought within the permissible frame of drawdown. Yet, the maximum point discharge rate should be within 2000–3000 m3/d that may approach 4000 m3/d between Banha and Qalub (Fig. 1). 3.4 Implication for management and sustainability Seasonal pumping of various intensities appears promising to manage providing enough water supply together with maintaining suitable control to the rising groundwater level, especially in the northern and southern confined aquifers. The unconfined part of the Quaternary aquifer, however, showed a continuous rise as reported at R3 and R6 that was also confirmed by field observations at several localities where the groundwater head rose over 4.0 m (Fig. 4a and 6). Such observations dictate using modern irrigation techniques to reduce infiltration rates associating flooding irrigation and, in some cases, imposing a relatively high stress pumping schemes at localities distributed over the entire unconfined part of the aquifer that maintain stabilized groundwater table. The groundwater head and water budget simulation results indicated significant effects of excess irrigation water on aquifer system and therefore the high stress strategy appears applicable and suitable for the unconfined part of the aquifer. Such a strategy could be upgraded locally to the dominant conditions of the land-use and groundwater system that could be economically more efficient. This is typically true if conjugated use of groundwater and surface water is envisaged. Despite the tested aquifer stress reported negligible drawdown, the total yield per production well should not exceed 4500–5000 m3/d to avoid upwelling effects of salt water from the underlying Miocene aquifer. The Quaternary aquifer of the East Nile Delta is characterized with good hydraulic properties especially where clay layers and/or disseminations are not present, as in most of reclamation land where high stress pumping stimulated excessive infiltration of returned irrigation water that counteracted drawdown effect together with infiltration from Ismaelia canal. This is geochemically confirmed by high nitrogen content associated with irrigation return and low TDS of the water samples collected from reclamation area (Ismail 2007). Generally, it is extremely difficult to adopt the aquifer management to a specific pumping scenario but, it would be convenient to adjust this g scenario to fit the hydrostratigraphic setting of the aquifer and the overall aquifer system at the locality of interest. This typically achieves better groundwater resources management and efficient control of the groundwater head. Conclusions In this work a nineteen-layer groundwater model is constructed to delineate an effective groundwater resources management in the East Nile Delta Quaternary aquifer. Flow simulations through this model has executed using MODFLOW and showed that pumping stress can manage the rising water head particularly at the confined part of aquifer whereas excess return irrigation water appears a key parameter that control the unconfined part of the aquifer. Using a high stress pumping strategy with the three suggested scenarios, results characterized the study area into three subregions: northern confined, southern confined and unconfined aquifers. Located to the North of Mit Ghamr, the northern confined aquifer showed limited development potential due to the effect of the salt water encroachments with maximum total abstraction of 3–6 million m3/yr using maximum well yield of 1000 m3/d. The southern confined aquifer extends south Mit Ghamr as the upper clay cap extend and showed good development potential with a total groundwater abstraction of 450 million m3/yr. and well yield up to 3000–4000 m3/d at standard production wells. Going south and eastward, the unconfined aquifer may provide a maximum discharge of more than 500 million m3/yr. with a total well yield of ~ 5000 m3/d. Water budget of the simulation runs indicated important contributions pumping wells as the only important to Out-Flow budget but constant head and recharge from irrigation canals/drains as the important contributors to In-Flow budget. Recovery of groundwater after aquifer stress usually is accomplished over three years in the confined aquifer starting with steep recovery through the first few months followed by gradual recovery. Seasonal pumping proved efficient for safe aquifer development in East Nile Delta with 60% of abstraction assigned to summer months. The results of this study provide an efficient foundation to a sustainable groundwater resources management to the Quaternary aquifer in the East Nile Delta region and the final transient calibrated model presents a platform for evaluating various multi-disciplinary policies in the near future or on the long run. Declarations Declaration of competing interest The authors state that they have no known competing financial interests or personal relationships that might influence the work reported herein. Author Contribution A.M.A.: Conceptualization, Formal analysis and investigation, Data acquisition, Validation, Writing – original draft, Writing – review & editing. O.A.: Conceptualization, Methodology, Formal analysis and investigation, Software, Data curation, Validation, Supervision, Writing – original draft, Writing – review & editing. A.A.: Conceptualization, Methodology, Data curation, Writing – review & editing. A.A.: Formal analysis and investigation, Data curation, Supervision, Writing – review & editing. A.M.A and A.A.: Conceptualization, Methodology, Formal analysis and investigation, Data acquisition, Validation, Writing – original draft, Writing – review & editing.All authors contributed to the article and approved the submitted version. 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Woessner, and R.J. Hunt, Applied groundwater modeling: simulation of flow and advective transport . 2015: Academic press. Morris, D.A. and A.I. Johnson, Summary of hydrologic and physical properties of rock and soil materials, as analyzed by the hydrologic laboratory of the US Geological Survey, 1948-60 . 1966, US Geological Survey. Abdulaziz, A.M., J. Hurtado, José M, and R.J.I.J.o.R.S. Al-Douri, Application of multitemporal Landsat data to monitor land cover changes in the Eastern Nile Delta region , Egypt. 2009. 30(11): p. 2977–2996. Han, P.-F., et al., Three-dimensional inter-basin groundwater flow toward a groundwater-fed stream: Identification, partition, and quantification. 2024. 629: p. 130524. Khalil, M.M., et al., Poor drainage-induced waterlogging in Saharan groundwater-irrigated lands: Integration of geospatial, geophysical, and hydrogeological techniques. 2021. 207: p. 105615. Abdulaziz, A.M. and A.M.J.A.J.o.G. Faid, Evaluation of the groundwater resources potential of Siwa Oasis using three-dimensional multilayer groundwater flow model , Mersa Matruh Governorate, Egypt. 2015. 8: p. 659–675. Ismael, A.M.A.A., Applications of remote sensing, GIS, and groundwater flow modeling in evaluating groundwater resources: two case studies; east Nile Delta, Egypt and Gold Valley, California, USA . 2007: The University of Texas at El Paso. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4749523","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":338655958,"identity":"2dd541aa-06f8-49ed-ad3b-8fcf22854ddb","order_by":0,"name":"Abdulaziz M. Abdulaziz","email":"","orcid":"","institution":"United Arab Emirates University","correspondingAuthor":false,"prefix":"","firstName":"Abdulaziz","middleName":"M.","lastName":"Abdulaziz","suffix":""},{"id":338655959,"identity":"3a9ab275-87dc-4b34-9ffc-dc57babe909f","order_by":1,"name":"Osman Abdelghany","email":"","orcid":"","institution":"United Arab Emirates University","correspondingAuthor":false,"prefix":"","firstName":"Osman","middleName":"","lastName":"Abdelghany","suffix":""},{"id":338655960,"identity":"48463b29-9e20-41d0-b505-03720ba8aeec","order_by":2,"name":"Alaa Ahmed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYFACHiBms7HjJ1VLWrJkA4laDjNuOECsBv72s0c3fChLYza+kfzwMQ+DnTwD+2H8uiXO5KXdnHHOhs/sRpqxMQ9DsmEDT1oCfmsO5Jjd5m1LYza7kWAmzcPADFSeY4BXh/z5N2a3/7YdZtw8I/37bx6G+gQG/vcf8GoxuAG0hRGoZYNEjhkzD8PhBAaJHPzuMrzxxuxmz7m0ZIkzb4ol5xgcN2yTeIbfYXLnc8xu/CgDRmV7+sYPbyqq5fn5kx/gtwbNncA4IkX9KBgFo2AUjALsAAAV3kRODQ4akwAAAABJRU5ErkJggg==","orcid":"","institution":"United Arab Emirates University","correspondingAuthor":true,"prefix":"","firstName":"Alaa","middleName":"","lastName":"Ahmed","suffix":""}],"badges":[],"createdAt":"2024-07-16 11:59:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4749523/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4749523/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62367718,"identity":"c388949e-de76-49d7-bee5-a33b23f169b3","added_by":"auto","created_at":"2024-08-13 11:27:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":183977,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the study area\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4749523/v1/f39393d6b9e5744a5b6593d3.png"},{"id":62368241,"identity":"be7c37ec-34d6-4edb-827d-a3919f306eac","added_by":"auto","created_at":"2024-08-13 11:35:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":510585,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Conceptual model, (b) 1990 steady state head distribution in the study area.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4749523/v1/5f9ee353bd3a25d277045ff5.png"},{"id":62368237,"identity":"1e777e3d-910c-475e-9b04-ee6410b92d2c","added_by":"auto","created_at":"2024-08-13 11:35:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":93126,"visible":true,"origin":"","legend":"\u003cp\u003eCross plot of the observed versus computed head for 1990 model (a) and 1990-2004 transient model(c); In-flow (b) and outflow budget (d) for -1990-2004 transient model\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4749523/v1/c1d2dd6c359c88de57c860b7.png"},{"id":62367716,"identity":"7603812d-5bd0-4494-bcf3-d7d7e58d0e69","added_by":"auto","created_at":"2024-08-13 11:27:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":126712,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Groundwater head distribution as predicted by the transient model. (b) Cumulative head change calculated by the 2024 unstressed transient model.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4749523/v1/918c2160ae15f6c7453baad4.png"},{"id":62367712,"identity":"0155ce87-1f00-42ca-b074-73195ad3efcf","added_by":"auto","created_at":"2024-08-13 11:27:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":52259,"visible":true,"origin":"","legend":"\u003cp\u003e(a and b) Water budget of the 2024 unstressed transient model\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4749523/v1/01e613739fa3b6437337fe3b.png"},{"id":62368239,"identity":"f97f5029-afec-4ae8-973c-9230b47f52fb","added_by":"auto","created_at":"2024-08-13 11:35:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":29869,"visible":true,"origin":"","legend":"\u003cp\u003ePumping stress Scenarios for 2030 predictions\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4749523/v1/78a110eff56051e759465a3e.png"},{"id":62368769,"identity":"bb65eafa-5f59-438c-a50a-458833be13a3","added_by":"auto","created_at":"2024-08-13 11:43:44","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":184913,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003ea, b and c) Groundwater head prediction \u0026nbsp;\u0026nbsp;statistics, (d, e and f) Water budget of the 2030 stressed transient model \u0026nbsp;\u0026nbsp;flow budget for the different scenarios.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4749523/v1/2feb4e4ad748fdd7deaedc90.png"},{"id":66174055,"identity":"b799b627-c279-42ee-bb3b-9bea59fc3992","added_by":"auto","created_at":"2024-10-08 11:09:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1443716,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4749523/v1/d2490f8e-cdb1-4e83-90ca-71d9e8caf710.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Groundwater Modeling in Agricultural Arid Area under Different Scenarios, East Nile Delta, Egypt","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDuring recent decades, the demand for water has been increasing due to urbanization and industrialization around the world. In arid regions, the prolonged droughts, climate change variabilities and overexploitation of aquifer systems intensifies the depletion and deterioration of water quality and impacts the ecosystem [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Consequently, a wise balance/equilibrium between aquifer in-flow (losing rivers/canals, rainfall, and excess irrigation) and aquifer out-flow (withdrawals for development purposes, baseflow, and seepage) is urgently needed [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn in-depth understanding of aquifer characteristics becomes vital for the conservation and efficient management of groundwater resources. However, the subsurface environment is not easily accessible and restricted by several factors that can contribute to the complexity of the groundwater movement, including heterogeneity and multiphase flow. In general, geological heterogeneity represents an influential constraint to any hydrogeological aspects including recharge that in consequence controls aquifer productivity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In such cases, models provide a novel way to understand, simulate, and forecast the behavior of groundwater systems. Understanding aquifer performance, defining sustainable water resource management, forecasting and anticipating solute transport can all benefit significantly using numerical and/or analytical models [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. But also, it is worth mentioning that there are lots of complexities associated with groundwater flow modeling, and it is always suggested to start with a conceptual model. After successful conceptualization of the simple model, complexity in the model can be added [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVarious authors have proposed different techniques for creating conceptual models, which are essential for transport modeling. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] explored the benefits, purposes, and definitions of conceptual models within the domain of experts. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] suggest that a single-layer model is sufficient for assessing water balance, while three-layer and five-layer models are recommended for representing aquitards in practical applications. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] have conducted commendable work by comparing multiple alternative models in various scenarios and addressing associated challenges. A conceptual model serves as a simplified representation of the area being studied, encompassing the model domain, boundary conditions, sources, sinks, and material zones. The main objective of constructing a conceptual model is to simplify the field problem and organize the associated data so that the system can be analyzed more readily. The need for simplifying assumptions arises due to the impracticality of completely reconstructing the field system and the scarcity of data required for a comprehensive description of the system. It is crucial to maintain simplicity in the conceptual model while ensuring that it has the capacity to effectively represent the physical aspects of hydrological behavior. However, the model should not be overly constrained in a manner that artificially limits the range of predicted outcomes. Challenges in approximating reality become more pronounced during transport modeling as solute transport processes are simplified to a few dominant mechanisms, in addition to simplifying flow [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The current investigation introduces a methodology that utilizes spatially varied data for water table variations, hydro-geological zones, and various geospatial and modelling tools to evaluate the aquifer production under different scenarios. This approach deviates from the conventional practice of using a lump sum value of average recharge for the study area. Instead, the methodology employs these spatially distributed values to develop a conceptual groundwater flow model.\u003c/p\u003e "},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eMaterials and Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\n\u003ch2\u003e2.1 Study area\u003c/h2\u003e\n\u003cp\u003eThe East Nile Delta falls in-between latitudes 30\u0026ordm; 00' and 31\u0026ordm; 30' and longitudes 31\u0026ordm; 00' and 32\u0026ordm; 30' and is characterized into two basic physiographic units (Fig.\u0026nbsp;1): river terraces of fluvial/deltaic origin and fluvio-marine flats [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e]. Major rivers flood plains, e.g., Nile Delta, are known for having an aquifer system made of a succession fine grained layers, typically mud size, and highly permeable sand and gravel zones that associated complex confinement conditions [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e]. These changes confinement conditions restraint groundwater flow, especially for shallow aquifers where active land development and substantial water volume is abstracted or supplemented.\u003c/p\u003e\n\u003cp\u003eFor the East Nile Delta, [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e] estimated a water deficit of 789.81 MCM/year was at Ismailia, Al-Salhiya, El Qantara West, Port Said and Fayed, while [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e] evaluated the risks of heavy metal accumulation in Qalubiya drain and related high concentrations to contributions from municipal, industrial, and agricultural wastes. Thus, numerous management actions are taken to mitigate such effects on the agricultural and industrial development plans. This comprised the abstraction of additional 4\u0026nbsp;billion m3 from the Nile Delta Quaternary aquifer, exceeding the reused water to 2.3\u0026nbsp;billion m3, and improving irrigation practices and domestic water use to save freshwater loss of approximately 2.5\u0026nbsp;billion m\u003csup\u003e3\u003c/sup\u003e [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]. Thus, the sustainable groundwater development plans became vital to maintain water use under potential aquifer stress during droughts.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003e2.2 Building geological model.\u003c/h2\u003e\n\u003cp\u003eTo evaluate the aquifer system performance to severe pumping stress, a 3D groundwater flow model is constructed to simulate water resources management. In this model, a 3D finite difference model was developed to simulate groundwater flow in the Quaternary aquifer of East Nile Delta region between 2004 and 2030. To numerically solve the governing flow equation based on water balance with a fully implicit finite different approximation, MODFLOW 2000 [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e] with the governing logic presented in Eq.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e was implemented.\u003c/p\u003e\n\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equ1\" class=\"mathdisplay\"\u003e$$\\:\\frac{\\partial\\:}{\\partial\\:x}\\left({K}_{xx\\:}h\\frac{\\partial\\:h}{\\partial\\:x}\\right)+\\frac{\\partial\\:}{\\partial\\:y}\\left({K}_{yy}\\:h\\frac{\\partial\\:h}{\\partial\\:y}\\right)+\\frac{\\partial\\:}{\\partial\\:z}\\left({K}_{zz}\\:h\\frac{\\partial\\:h}{\\partial\\:y}\\right)-\\omega\\:={S}_{s}\\frac{\\partial\\:h}{\\partial\\:t}$$\u003c/div\u003e\n\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eWhere:\u003c/p\u003e\n\u003cp\u003eK\u003csub\u003exx\u003c/sub\u003e, K\u003csub\u003eyy\u003c/sub\u003e, K\u003csub\u003ezz\u003c/sub\u003e are K values (m\u003csup\u003e3\u003c/sup\u003e/d) along x, y, and z axis, h is the hydraulic head, \u0026omega; is a source and sink term (volumetric flux m\u003csup\u003e3\u003c/sup\u003e/d), S\u003csub\u003es\u003c/sub\u003e is the specific storage (dimensionless), and t is time (day).\u003c/p\u003e\n\u003cp\u003eA well calibrated groundwater flow model that simulates the flow through the complex stratigraphy of the Nile Delta flood plain, was constructed using the following basic steps. Typically, MODFLOW uses a structured grid of consistently continuous layers across the model domain. Therefore, 93 borehole data selected in the study area was first checked to confirm relative spatial continuation of the layers in the model domain. Five hydrostratigraphic units were identified to model the complex fluvial features of the Quaternary aquifer including clay, sandy clay, fine sand, coarse sand, and sand and gravel. These units were mapped to 19 horizons within a model georeferenced to UTM system and NAD 1984- zone 36N projection. These horizons are modeled to solids using a distance weighted interpolation algorithm that extend to a total of 100m depth. Before converting solids to MODFLOW, a grid layers of 125 column, 175 rows, and 19 layers was constructed and rotated 30˚, so that the MODFLOW grid is parallel to the dominant direction of groundwater flow (Fig.\u0026nbsp;2). Within solids each horizon was mapped into a single layer within MODFLOW grid. MODFLOW solves the groundwater flow equation on a cell-by-cell basis within the 3D grid.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003e2.3 Conceptual model\u003c/h2\u003e\n\u003cp\u003eConceptual model approach is used to build the MODFLOW model with model parameters designed as sources and sinks, boundary conditions, and observation points in the map module using GIS tools. In this model, confinement conditions were set as convertible with a contrast of two orders magnitude (or more) of in hydraulic conductivity of successive hydrostratigraphic units as a basis for automatic assignment [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e]. The developed conceptual model consists of three coverages including sources and sinks, recharge zones, and observation points (Fig.\u0026nbsp;2, a). After visual examination of the flow lines and inspection of the inflow \u0026ndash; outflow locations, four physical boundaries including Demietta Branch, Ismaelia Canal, Suez Canal, and Mediterranean Sea were mapped as specified head boundaries to the modeled area (Table .1). [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e] indicated that conventional finite difference equations do not recognize that a well penetrating more than one stratigraphic unit forms pathway for water movement between layers. Therefore, the calculated head in multilayer aquifer system represents the composite average of the heads in all the penetrated layers.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eHydraulic parameters for steady model and specific yield and specific storage for transient model\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"9\" align=\"left\"\u003e\n\u003cp\u003eSteady State Model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eHydraulic Conductivity (Kh: m/d)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eClay\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0015\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSandy Clay\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.85\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFine Sand\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoarse Sand\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e85\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSand \u0026amp; Gravel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e375\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eRecharge Rate (m/d)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTraditional Agriculture\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00000582: 0.00005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReclamation Land\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000059: 0.0029456\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eConductance (m/d)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIrrigation Canals\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001: 0.03\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDrains\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.01 :0.12\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"6\" align=\"left\"\u003e\n\u003cp\u003eTransient Model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaterial\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSpecific yield (unitless)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSpecific Storage (1/m)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eShale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.0.08\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSandy Shale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFine Sand\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoarse Sand\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0004\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSand \u0026amp; Gravel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00004\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eIn this study, 170 sites are selected to represent more than 6000 production wells that pump a total volume of approximately 2.1\u0026nbsp;million m\u003csup\u003e3\u003c/sup\u003e/d from the modeled area. In all wells, screen intervals were assigned based on the pumping rate and well depth, while high intensity fluxes were assigned to the lower sand and gravel unit to avoid dry cells effect. For each river arc, the head and conductance of the river bottom was assigned based on data in Table\u0026nbsp;(1) or estimated relative to the nearest known head. In addition, the main drains were simulated using the drain package with head and conductance assigned as described in rivers (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). For simplicity, El Manzala Lake was simulated as a general head polygon with a general head of 0.25 m amsl. In the present model, at least 12 recharge zones were identified in the agriculture land with recharge rates ranging between 5.82 e-6 m/d in the traditional agricultural land to 0.00029 m/d in the reclaimed land.\u003c/p\u003e\n\u003cp\u003eModel calibration is essential to maintain trustworthy prediction that lacks wet and dry cells in addition to the erroneous head distribution. It typically includes observation points where calculated and observed head should considerably match through adjusting some input parameters. For model verification, forty observation points, mostly belonging to Research Institute for Ground Water\u0026rsquo;s observation network, are used to calibrate the unstressed steady state model. Alternatively, observation heads of 46 wells were imported for model calibration during transient simulation.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003e3.4 Model execution\u003c/h2\u003e\n\u003cp\u003eBefore execution, the 3D-model was checked for errors and warnings to ensure conversion and accurate solution. Storativity and Transmissivity of modeled hydrogeologic units are assigned while the specific yield values fall in the possible ranges published by [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]. Alternatively, the storage parameters of hydrostratigraphic units for the transient model are listed in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Hydraulic conductivity, conductance, and recharge rate appear influential parameters for systematic adjustment while model calibration. These parameters are sequentially adjusted followed by repeated run/rerun using error estimation and calibration statistics as constraint. The model is considered calibrated for steady state as the mean error approached \u0026minus;\u0026thinsp;0.066 with RMSE of 0.505 m, which is practically very small compared to the total head (14.5 m). Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the final input parameters that were used in the calibrated unstressed steady state model. Converting steady model into transient usually involves large datasets including recharge and well data together with observation data. In addition, model validity is sensitive to the selection of appropriate time steps that associate minimal impacts on numerical results. Transient simulations of the present study fall within two types: interpretive and predictive. The 1990\u0026ndash;2004 transient simulation is interpretive to the system response to land use changes described by [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e] using field observations in 2004 for model calibration. A total of 46 head data, with 95% confidence and 10% observed head interval, collected in summer of 2004 are utilized in transient model calibration. The calibrated transient model is consequently used for predictions of aquifer responses for different stress scenarios.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003eGroundwater flow models are developed as a well-established tool applied over local or regional scale for evaluating the potential of groundwater resources [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e]. In the present study, changes in pumping data for transient model were insignificant over the interpretive transient simulation, as agricultural land development was mainly based on surface water between 1990 and 2003 (Abdel Salam et al, 2004). Figure\u0026nbsp;2b presents the head distribution for the calibrated unstressed steady state model. A plot to the calculated versus observed head at 40 observation points utilized in model calibration indicates a good match (Fig.\u0026nbsp;3a). Transient simulation is classically used to investigate time-dependent problems and typically requires starting with a calibrated model for steady state. For transient simulation, most input parameters of calibrated unstressed steady model are slightly changed but the geometry of recharge zones is adjusted to fit the progressive changes in land use between 1990\u0026ndash;2004 [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e]. Once the transient model is considered calibrated (Fig.\u0026nbsp;3c), the 1984\u0026ndash;2004 head inventory showed a progressive rise in groundwater head indicating a remarkable increase in aquifer storage, i.e. gaining aquifer. Thus, recharge represents the only stress parameter prevailed transient simulation between 1990 and 2004, with other parameters of source and sink remain unchanged. The recharge rate is systematically adjusted for each independent recharge zone followed by transient model execution.\u003c/p\u003e\n\u003cp\u003eAquifer stress considered 8-stress periods of 2-years each with 2-time steps for each stress period through the entire simulation period. The computed water budget involves the Inflow and Out-Flow budgets. Figure\u0026nbsp;3b and 3d present the groundwater budgets for the 1990\u0026ndash;2004 calibrated interpretive transient simulation. Constant head, irrigation canals, and recharge are the major contributions to In-Flow budget, while storage and general head constitute secondary components (Fig.\u0026nbsp;3b). In addition, recharge showed a significant progressive increase to groundwater system In-Flow over the simulated period, while constant head reported a gradual decrease. On the contrary, pumping wells and discharge to drains presented the major contributions to the 1990\u0026ndash;2004 Out-Flow water budget, with minimal annual changes for all contributions through the simulated period Fig.\u0026nbsp;3d).\u003c/p\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1 The transient model predictions\u003c/h2\u003e\n\u003cp\u003eThe 1990\u0026ndash;2004 interpretive transient simulation offers a valuable technique to evaluate the annual rate of aquifer gain that defined a form of biannual periodic increase in recharge rate. Statistically, recharge rates ranged between 2.39 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e m/d and 2.04 10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e m/d with an average value of 4.61 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e m/d. Assuming limited changes to aquifer conditions with minimal changes in land use, 2024-head distribution within the modeled East Nile Delta region is predicted (Fig.\u0026nbsp;4a). Such a prediction in head change distributions provides valuable information for efficient planning and sustainable development to groundwater system including rate and dispersal of withdrawal stress. The 2024-model prediction (Fig.\u0026nbsp;4b) indicates a significant head rise to the northern part of the reclamation area which acts as a drain to the entire developed area and coincides with the direction of the overall northward groundwater flow. The other zone is encountered near Qalub area (Fig.\u0026nbsp;1) where mass population and active agricultural activities near unconfined aquifer are reported. Similar observations are encountered in various localities at the desert fringes of the Nile Valley and/or Nile Delta that approach serious problems including water logging [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eDue to the nature of fluvial and fluviomarine depositional environment of the Quaternary aquifer, local vertical heterogeneity in facies induce markable local variations in groundwater head. Because of the aquifer heterogeneity in vertical and spatial domains, it is expected that the rate at which groundwater head rise would locally vary across the aquifer. Therefore, 17 representative sites are selected for monitoring groundwater head across the model (Fig.\u0026nbsp;4a and b) which indicated marked head change variations (2.0 m at R4/R6 and \u0026lt;\u0026thinsp;0.2 m at R1). As shown in Fig.\u0026nbsp;4b, the rise in groundwater head of the reclamation land varied increasingly between 2.0 m (R4 and R6) and less than 0.2 m at R1 site with gradual decrease north- and eastward. In the traditional agricultural lands, the maximum reported rise reported 1.6 m at T9, but most T-stations fall between .3 and .75 m. The inventory of model budget indicated constant head and recharge as the main In-Flow budget components and the recharge volume increased to 1.433.850 m\u003csup\u003e3\u003c/sup\u003e/d with slight decrease to infiltration from irrigation canals and constant head (Fig.\u0026nbsp;5a). In addition, negligible changes to aquifer storage and general head contributions to the In-Flow budget may reflect prevalent unconfined conditions of the aquifer. Alternatively, Out-Flow budget (Fig.\u0026nbsp;5b) reported production wells and drains as primary constituents with limited contributions from the discharge to general head and constant head components. Despite the obvious negligence to storage as a primary Out-Flow component, it is almost duplicated (121.000 m3/d versus 239.000 m3/d) because of the rising groundwater head (Fig.\u0026nbsp;4b).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2 The predicted aquifer stress\u003c/h2\u003e\n\u003cp\u003eIn theory, an unlimited number of strategies of aquifer stress can be tested using the calibrated transient model, however applicable strategies remain dependent on the actual field practices [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. Due to hydrochemical and hydrogeological constrains related to water salinity and water quality, potential aquifer development is viable to the area located south of +\u0026thinsp;4m potentiometric surface with a buffer zone of 3\u0026ndash;5 km width to the West of Suez Canal to keep fresh-salt water interface undisturbed [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. In this study, high pumping stress strategy (utilizing three different pumping scenarios, Fig.\u0026nbsp;6) is considered to continue to the year 2030 using additional 100 sites for groundwater withdrawal distributed over the predefined aquifer development area, particularly at Agri-reclamation projects and main populated areas within traditional Delta fringe. Seasonal pumping is adopted using various pumping rates over the year with a maximum duration of 8 years to achieve a safe yield in the Quaternary aquifer. Intensive pumping (60\u0026ndash;70% of annual abstraction) was reserved for summer period (April-October) that requires greater water volumes for both municipal and agricultural consumption. Most of this groundwater abstraction is pumped at the reclamation land with restricted pumping (3\u0026ndash;6\u0026nbsp;million m\u003csup\u003e3\u003c/sup\u003e/yr) assigned to the area located north of Mit Ghamr city (Fig.\u0026nbsp;1). Simulations of the high stress scenarios showed slight drawdown (~\u0026thinsp;0.3 m) in T4, T5, T10 and R1 (Fig.\u0026nbsp;7a, c, and e), while the maximum drawdown is always seen at T4 and T5 (Fig.\u0026nbsp;4a). On the contrary, an increase in head (0.05\u0026ndash;0.35 m) at R3, R6, and T8 is reported, with higher head seen in R6 and T8 (Fig.\u0026nbsp;4). Drawdown patterns are related to the distribution of pumping stress, both magnitude and time, except for R1 with gentle linear head decrease associating the strategy systematic decrease in recharge. Water budget calculations (Fig.\u0026nbsp;7b, d, and f) presented infiltration from the specified head and In-storage as important contributions to In-Flow budget while the obvious increase, as expected, is reserved to additional pumping stresses. The calculated constant head has increased to 1.804.400, 293.969, and 149.058 m\u003csup\u003e3\u003c/sup\u003e/d for strategy I, II, and III respectively, demonstrating excessive influx with the periodic pumping stress of strategy I. Alternatively, Out-Flow budget indicated substantial storage decrease (112.119 m\u003csup\u003e3\u003c/sup\u003e/d) for all scenarios and was inversely related-to pumping stress representing constant head compensation, reported as In-Flow, for additional pumping rather than storage (Fig.\u0026nbsp;7b, d, and f). Except for the slight increase in infiltration from general head and irrigation canals and a slight decrease in quantities trapped by the general head, other water budget components of this strategy presented negligible changes (~\u0026thinsp;10.000 m\u003csup\u003e3\u003c/sup\u003e/d) over the simulation time (Fig.\u0026nbsp;7b, d, and f).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e3.3 Aquifer response to pumping stress.\u003c/h2\u003e\n\u003cp\u003eApproximately all model runs for the study area confirmed that the constant head, particularly Ismaelia Canal, and infiltration of excess irrigation water present the principal contributors to aquifer replenishment while well abstractions are the main discharge element. Field works and previous literatures reported the quaternary aquifer of less than 150m thick and comprises fresh groundwater overlying brackish water that change northward to salt water at Mit Ghamr that progressively increase southward to ~\u0026thinsp;200 m at Zifta (Fig.\u0026nbsp;1). Zift-Mit Ghamr strip appears sensitive to saltwater encroachment due to aquifer disturbances by groundwater abstraction with a maximum permissible drawdown not more than 0.5 m. The calculated drawdown associating the additional pumping (3\u0026ndash;6\u0026nbsp;million m\u003csup\u003e3\u003c/sup\u003e/yr) over the 3 scenarios of high stress strategy around Mit Ghamr fall between 0.20 and 0.45m delineating the framework to the maximum available abstraction (1000 m\u003csup\u003e3\u003c/sup\u003e/d) at the northern confined aquifer to maintain stabilized fresh-salt water interface. The northern confined aquifer showed a water budget with local recharge primarily from returned irrigation water and small quantity related seepage of irrigation canals. In addition, the change in storage indicated a total change of 70.000 m3/d that mainly explains a drawdown of moderate effect at this area. For the Nile River-Demietta branch, the flow budget presented outflow exceeding Inflow by approximately 5.000 m3/d and such a value indicates the sensitivity of the aquifer at this area for any further pumping stress. Thus, the northern confined aquifer possesses a limited potential as water supply and local assessment to the subregion should be carefully considered before additional groundwater abstraction is proposed. Both the confined and unconfined parts of the modeled aquifer present a good potential to the area extending south of Mit Ghamr, with the maximum anticipated yields located between Banha and Qalub (Fig.\u0026nbsp;1). This is confirmed by the monitoring points in the southern confined aquifer (T8 and T10, Figs.\u0026nbsp;6 and 4a) with drawdown less than 0.4 m in all scenarios of the extreme aquifer stress, significantly less than the maximum permissible drawdown (1.0 m) at this area. However, the southern confined aquifer stress near the proximity of Mit Ghamr should avoid northward propagating resonance of over pumping, especially for long time. The presence of irrigation canals, especially the main canals in the unconfined part of the aquifer, e.g., Ismaelia Canal, plays an important role in aquifer response to pumping stress. For example, T10 located far away from main streams follows the rhythm of pumping scenarios while T8 response appears unaffected due to the replenishment by infiltration from Ismaelia Canal (Fig.\u0026nbsp;4a and 6). In addition, continuous pumping of moderate to high stresses (scenario II) induces a drawdown greater than the periodic pumping even if it involves stages of higher pumping (Scenarios I and III) than those of continuous pumping (Fig.\u0026nbsp;6). Notably, the groundwater heads at R3, R6, and T8 show continuous rise over the simulation period as if these areas are not affected by pumping. This is true for R3 because it is located at the buffer zone of Lake Manzala, but the subregions around R6 and T8 are affected by pumping stress stabilized by excessive infiltration from the main irrigation canals (Ismaelia canal-its branch El Salheya El Gadida canal for R6 and Ismaelia Canal-Bahr Muis for T8). The drawdown is commonly recovered over a 3\u0026ndash;4-year period following the peak stress and recovery typically follows a gradual pattern. Generally, analysis of water budget and head response nominated the southern confined aquifer as a potential site for groundwater storage and development with continuous pumping capacity of approximately 300\u0026ndash;450\u0026nbsp;million m3/yr over several years of drought within the permissible frame of drawdown. Yet, the maximum point discharge rate should be within 2000\u0026ndash;3000 m3/d that may approach 4000 m3/d between Banha and Qalub (Fig.\u0026nbsp;1).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e3.4 Implication for management and sustainability\u003c/h2\u003e\n\u003cp\u003eSeasonal pumping of various intensities appears promising to manage providing enough water supply together with maintaining suitable control to the rising groundwater level, especially in the northern and southern confined aquifers. The unconfined part of the Quaternary aquifer, however, showed a continuous rise as reported at R3 and R6 that was also confirmed by field observations at several localities where the groundwater head rose over 4.0 m (Fig.\u0026nbsp;4a and 6). Such observations dictate using modern irrigation techniques to reduce infiltration rates associating flooding irrigation and, in some cases, imposing a relatively high stress pumping schemes at localities distributed over the entire unconfined part of the aquifer that maintain stabilized groundwater table. The groundwater head and water budget simulation results indicated significant effects of excess irrigation water on aquifer system and therefore the high stress strategy appears applicable and suitable for the unconfined part of the aquifer. Such a strategy could be upgraded locally to the dominant conditions of the land-use and groundwater system that could be economically more efficient. This is typically true if conjugated use of groundwater and surface water is envisaged. Despite the tested aquifer stress reported negligible drawdown, the total yield per production well should not exceed 4500\u0026ndash;5000 m3/d to avoid upwelling effects of salt water from the underlying Miocene aquifer. The Quaternary aquifer of the East Nile Delta is characterized with good hydraulic properties especially where clay layers and/or disseminations are not present, as in most of reclamation land where high stress pumping stimulated excessive infiltration of returned irrigation water that counteracted drawdown effect together with infiltration from Ismaelia canal. This is geochemically confirmed by high nitrogen content associated with irrigation return and low TDS of the water samples collected from reclamation area (Ismail 2007). Generally, it is extremely difficult to adopt the aquifer management to a specific pumping scenario but, it would be convenient to adjust this g scenario to fit the hydrostratigraphic setting of the aquifer and the overall aquifer system at the locality of interest. This typically achieves better groundwater resources management and efficient control of the groundwater head.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this work a nineteen-layer groundwater model is constructed to delineate an effective groundwater resources management in the East Nile Delta Quaternary aquifer. Flow simulations through this model has executed using MODFLOW and showed that pumping stress can manage the rising water head particularly at the confined part of aquifer whereas excess return irrigation water appears a key parameter that control the unconfined part of the aquifer. Using a high stress pumping strategy with the three suggested scenarios, results characterized the study area into three subregions: northern confined, southern confined and unconfined aquifers. Located to the North of Mit Ghamr, the northern confined aquifer showed limited development potential due to the effect of the salt water encroachments with maximum total abstraction of 3\u0026ndash;6\u0026nbsp;million m3/yr using maximum well yield of 1000 m3/d. The southern confined aquifer extends south Mit Ghamr as the upper clay cap extend and showed good development potential with a total groundwater abstraction of 450\u0026nbsp;million m3/yr. and well yield up to 3000\u0026ndash;4000 m3/d at standard production wells. Going south and eastward, the unconfined aquifer may provide a maximum discharge of more than 500\u0026nbsp;million m3/yr. with a total well yield of ~\u0026thinsp;5000 m3/d. Water budget of the simulation runs indicated important contributions pumping wells as the only important to Out-Flow budget but constant head and recharge from irrigation canals/drains as the important contributors to In-Flow budget. Recovery of groundwater after aquifer stress usually is accomplished over three years in the confined aquifer starting with steep recovery through the first few months followed by gradual recovery. Seasonal pumping proved efficient for safe aquifer development in East Nile Delta with 60% of abstraction assigned to summer months. The results of this study provide an efficient foundation to a sustainable groundwater resources management to the Quaternary aquifer in the East Nile Delta region and the final transient calibrated model presents a platform for evaluating various multi-disciplinary policies in the near future or on the long run.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e \u003cp\u003eThe authors state that they have no known competing financial interests or personal relationships that might influence the work reported herein.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.M.A.: Conceptualization, Formal analysis and investigation, Data acquisition, Validation, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing. O.A.: Conceptualization, Methodology, Formal analysis and investigation, Software, Data curation, Validation, Supervision, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing. A.A.: Conceptualization, Methodology, Data curation, Writing \u0026ndash; review \u0026amp; editing. A.A.: Formal analysis and investigation, Data curation, Supervision, Writing \u0026ndash; review \u0026amp; editing. A.M.A and A.A.: Conceptualization, Methodology, Formal analysis and investigation, Data acquisition, Validation, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing.All authors contributed to the article and approved the submitted version.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThis study was supported by the United Arab Emirates University through the funds no. 12S139 and 12S158.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKonikow, L.F. and E.J.H.j. Kendy, \u003cem\u003eGroundwater depletion: A global problem.\u003c/em\u003e 2005. 13: p. 317\u0026ndash;320.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAli, S.R., J.N.J.C.J.o.A.S. 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Faid, \u003cem\u003eEvaluation of the groundwater resources potential of Siwa Oasis using three-dimensional multilayer groundwater flow model\u003c/em\u003e, Mersa Matruh Governorate, Egypt. 2015. 8: p. 659\u0026ndash;675.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIsmael, A.M.A.A., \u003cem\u003eApplications of remote sensing, GIS, and groundwater flow modeling in evaluating groundwater resources: two case studies; east Nile Delta, Egypt and Gold Valley, California, USA\u003c/em\u003e. 2007: The University of Texas at El Paso.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Water resources management, Groundwater flow modelling, Arid regions, Quaternary aquifer, East Nile Delta","lastPublishedDoi":"10.21203/rs.3.rs-4749523/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4749523/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe East Nile Delta represents the natural extension of the Nile Delta that recently showed significant changes in groundwater system related to both agricultural and urbanization land development. The current study presents a GIS-based 3D groundwater flow model to outline a safe framework for pumping stress management to the upper 100 m of Quaternary aquifer located North of Ismaelia Canal. Model construction comprised 93 borehole data to model a 19-layer grid of the fluvial Quaternary deposits. The finite difference MODFLOW 2000 accomplished simulation to predict groundwater head distribution across the aquifer system in both steady and transient states. Steady state model is calibrated to the 1991-groundwater hydrogeological map of Egypt, and subsequently provided the initial conditions for the 1991\u0026ndash;2005 transient simulation. The transient model is considered calibrated as the calculated head matches the field observations of 2004\u0026ndash;2005. Using severe aquifer stress strategy, three scenarios are proposed to manage the reported local rise in groundwater head and evaluate the potential aquifer production during drought. This involved using several infiltration rates from irrigation return and pumping stress to model predictions extending to the year 2030.\u003c/p\u003e \u003cp\u003eResults showed pumping controls to the rising groundwater head especially towards the North where confinement conditions prevail with two subregions, northern and southern, requiring different schemes of management. Optimum pumping and infiltration rate are determined for these subregions and for the unconfined parts of the Quaternary aquifer. During drought, a maximum of 500\u0026nbsp;million m\u003csup\u003e3\u003c/sup\u003e/yr are producible from the unconfined aquifer with standard discharge of 5000 m\u003csup\u003e3\u003c/sup\u003e/d that may induce drawdown less than 0.5 m. The water budget of modeled aquifer indicated that pumping stress is predominantly balanced by seepage from Ismaelia canal and Damietta branch with slight contributions from irrigation canals and drains. Details of water budget and changes in groundwater head to pumping stresses across the modeled area are presented and discussed in detail. The model results provide a scientific platform to delineate efficient and sustainable management to the East Nile Delta Quaternary aquifer associating active dynamic land development.\u003c/p\u003e","manuscriptTitle":"Groundwater Modeling in Agricultural Arid Area under Different Scenarios, East Nile Delta, Egypt","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-13 11:27:39","doi":"10.21203/rs.3.rs-4749523/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eea8e071-2038-4552-9ea9-aa32aad91df8","owner":[],"postedDate":"August 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":35875156,"name":"Earth and environmental sciences/Environmental sciences/Environmental chemistry"},{"id":35875157,"name":"Earth and environmental sciences/Environmental sciences/Environmental impact"},{"id":35875158,"name":"Earth and environmental sciences/Hydrology"}],"tags":[],"updatedAt":"2024-10-08T11:08:34+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-13 11:27:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4749523","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4749523","identity":"rs-4749523","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}