Table 5.30 shows the effects of the previously discussed sensitivity analysis on the model water balance. It is clear from the Table that the inflow and the outflow from the model boundaries have a greater influence on the model behaviour than changes in the recharge, boundary conditions, hydraulic conductivity or specific yield. For example, the effects of increased abstraction on the inflow and outflow from the model boundary are very noticeable, with the former decreasing by up to 14% and the latter increasing by 22%
when the abstraction was decreased by 20%. These compare with the 16% increase in inflow and 14% decrease outflow when the abstraction was decreased by 20%. The (-/+
20%) variations in the recharge rates produce (+7%) and (-7%) changes in the inflow from the model boundary while the same variation percentage in the recharge rates result in (-9%) and (10%) changes in the outflow from the model boundary respectively. These recorded changes or sensitivities are much larger than those obtained when the hydraulic characteristics were changed. For example, when the hydraulic conductivity was decreased by 20%, only a slight change in the inflow (-2%) from the model boundary was recorded; the corresponding change in the boundary outflow was -4% On the other hand, when the hydraulic conductivity was increased by 20%, the inflow from the model boundary changed by (+1%) and the outflow changed by (+4%). The variation by (-20%) in the specific yield produces (-10%) change inflow from the model storage and only (+1%) change in the inflow from the model boundary, while it results in (+2%) change outflow from the model storage and only (-3%) change in the outflow from the model
boundary. In contrast, the variation by (+20%) in the specific yield produces (+3%) change inflow from the model storage and only (-1%) change in the inflow from the model boundary, while it results in no change in outflow from the model storage and only (+2%) change in the outflow from the model boundary.
Finally, changing the boundary condition from being constant head boundary condition to be general head boundary condition resulted in a 5% increase in the inflow from the model boundary and +16% change in the outflow from the model. By nature, a general head boundary condition allows the flow to either to enter or leave the model domain depending on the direction of hydraulic gradient at the boundary, i.e. a higher head within the domain relative to outside it at boundary will allow water to move out of the domain whereas the opposite will happen if at the boundary, the head within the domain is lower than outside the domain. The fact that overall, in proportional terms, more water actually flowed out of the model domain than into it for the general head boundary condition is a reflection of the highly dynamic way in which hydraulic conditions can change during the simulation, which may not be captured with a constant head assumption at the boundary.
5.8 Summary
This Chapter described the simulation model of Ash Sharqiyah Sands Aquifer. The model of a uniform square grid of 500 m spacing, comprising 170 rows and 110 columns was developed for the unconfined layer 1 and semi-confined layer 2 of the aquifer. The MODFLOW model was run in the steady state mode via the commercial GMS-software.
Polygon zonation distributions were used successfully in implementing the automatic steady state calibration for the hydraulic parameters (K and Sy) of the heterogeneous layer 2 using 42 control points. Sixty one observation wells were selected to carry out the calibration process; 21 and 40 observation wells were used for layer 1 and layer 2
respectively. The comparison between the observed and simulated heads was reported to be maximum two metres. Four observation wells, covering different parts of the model domain and close to the two operational wellfields, were used to calibrate the transient model for the aeolianite (layer 1), as they have continuous water record during this period, while six observation wells were chosen to calibrate the transient model for the alluvium (layer 2). The model was also validated to ensure that it was able to predict heads data not used in its calibration. In all of these observation wells, the modelled heads validated reasonably well and matched the observed value with a maximum difference of approximately (+/-) 0.2m.
Once the calibration and verification of the model had been done successfully, the groundwater simulation model was then used to assess the long-term implications of continued abstractions at the two operational wellfields on groundwater conditions in the aquifers of Ash Sharqiyah Sands to meet the domestic water supply to Ash Sharqiyah Region up to 2030. It was found that the existing operational 29 wells of the two groundwater wellfields will not be capable by 1st September 2025 to meet the domestic water supply needs for the eight Wilayats of Ash Sharqiyah Region without creating extensive drawdown and causing negative impact on existing operational Aflaj and the environment. Therefore, it was essential to develop a practical and reliable optimization model in order to determine the optimum pumping scenarios from the existing production wells as well as from Sur Desalination Plant to meet the increasing domestic water supply needs for the eight Wilayats of Ash Sharqiyah Region without drying out the existing 29 operational wells and insuring a minimum flow in the existing Aflaj. This scenario will be investigated in detailed in the next optimization Chapter 6.
It was found that the simulation model was relatively not sensitive within -20% to 20% to the recharge rate, hydraulic conductivity and specific yield indicating that the values used
in the simulation model were determined very accurately. The model was also found to be relatively not sensitive to the boundary condition especially for layer 2 when its boundary condition was changed from being constant heads to be general head for both layers.
However, the simulation model is sensitive (-/+6.4%) to the +/-20% variation in abstraction. It was also found that the inflow and the outflow from model boundaries as influenced by the abstractions have a greater influence on the model behaviour than changes to the recharge, boundary conditions, hydraulic conductivity or specific yield.
Table 5.1: Al Kamil Production Wellfield
Table 5.2: Jaalan Production Wellfield
Well No. * Easting
Table 5.3: Recorded monthly wadi flow data for Wadi al Batha in 106m³ from 19983 to 1997 (MWR, 1997g)
Wadi Area Km
Record period
Mean monthly flow for period of record (106m³) Year 106m³
Table 5.4: Recorded main monthly Rainfalls data for Wadi al Batha in (mm) from 1976 to 1997 (MWR, 1997g)
Station Elevatio