Setting Simulation/Optimization Model

The Gaza Strip Simulation/Optimization model is setup starting from 2010 simulated conditions both for groundwater heads and salt concentration fields. The management scheme is optimized for the period 2011-2040, and results at the end of 2040 are compared within the not-optimized situation previously assessed, with reference to the best pumping scenario. The only-simulation model (S-0) to which compare S/O results are those coming from the ECH-RMO climate variables fed model.

The Simulation/optimization model is setup as described in Chapter 3, some proposed parameters of which are adapted to this Gaza Strip aquifer case study; in particular, they have been optimized only municipal wells’ pumping rates (as clustered for the simulation model, accounting 139 locations), the total amount of which, as above cited, has been setup to be the same of the best pumping scenario (paragraph 6.6), i.e. around 50 Mm3/y. Minimum allowed values for pumping are setup equal to zero for each well, while maximum allowed value is based on the current mean operational rate of each well.

148 The relative weights in equation (3.4), Chapter 3, are determined by means of a parametric trade-off calculation, as described in the above mentioned Chapter; starting from some partial results, the w2 values range is 1-100; yet, the Simulation/Optimization

model accounts for 1,000 runs (i.e. 5 possible solutions multiplied for 200 generations) of CODESA-3D simulation model. Final GA parameters are summarized in Table 6.25. After model setup and initialization, the transient management scenario (with the different 7 values of salinity weight w2) is simulated for a 30-years time interval. A single

S/O run spent an average CPU time of 72 hours on a dual CPU quad core 2.8 GHz system. Number of wells Pumping weight w1 Salinity weight w2 Individual length Population size Max generations number Crossover probability Mutation probability 139 10 1-100 2085 5 200 0.5 0.02

Table 6.25 – GA parameters for the Gaza Strip site

In this case, the optimal value of salinity weighting parameter w is 75, as shown in 2

Figure 6.33, ensuring in this way maximum total pumping (which corresponds to high percentages of the possible total pumping amount) while a total salt mass extracted (which depends on values of salt concentrations) within the reasonable limits of the feasibility region. The best fitness values tends at reaching a slightly increasing trend in the last part of the S/O process, as shown in Figure 6.34, stating that it is not changed by further increasing the number of generations.

Table 6.26 shows the comparison between the optimal pumping strategy (SO-0) with the non-optimized condition (T-0) for the wells of the study area. The analysis is conducted in terms of design and state variables, namely: total discharge (Q, m3/y), averaged hydraulic head (h, m), total salt normalized concentration (c, /) and total salt mass extracted (S, kg/year of chlorides) at the 139 clustered wells.

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Figure 6.33 – Trade-off curve with indication of limits of feasibility region (red dot lines); total extracted salts are in terms of chlorides.

Figure 6.34 – Best fitness function value during the S/O process

T-0 SO-0 T-0 SO-0 T-0 SO-0 T-0 SO-0

Q Q h h c c S S

m3/y m3/y m m / / kg/y kg/y 49,992,045 50,619,140 -0.68 -0.41 30.45 22.97 266,008,731 84,580,101

Table 6.26 – Comparison of non-optimized (T-0) and optimized (SO-0) pumping strategies: discharge (Q), head (h), normalized concentration (c) and extracted salt mass (S) at the 139 clustered wells.

The optimum pumping strategy ensures a decrease of about -68% in the total extracted salt mass and a recovery of +0.28 m in the hydraulic heads, while allowing to withdrawal

150 the +1.3% of projected abstraction rates, thus keeping quite equal the total pumping rate with reference to the best pumping scenario, and the total area affected by SWI (intended as the area in which the groundwater salts concentration are equal to 25,000 mg/l of chlorides, i.e. normalized concentration equal to 1) shows a reduction of about -11% (Table 6.27). Spatial distribution of heads and salt concentrations for the two scenarios are also shown in Figure 6.35 and Figure 6.36. A graphical representation of pumping magnitudes for the 139 clustered municipal wells, both for the T-0 and SO-0 situation is illustrated in Figure 6.37.

T-0 SO-0 ∆ %

Total abstraction (m3/y) 49,992,045 50,619,140 +627,095 +1.3 Average head (m) -0.68 -0.41 +0.28

Total salt mass (kg/y) 266,008,731 84,580,101 -181,428,630 -68.2 Total area affected by SWI (m2) 17,149,000 15,195,900 1,953,100 -11.3

Table 6.27 – Overall performance of non-optimized (T-0) and optimized (SO-0) pumping strategies and relative benefits

Figure 6.35 - Spatial distribution of groundwater heads (h, in m a.m.s.l.) for the T-0 (left) and SO-0 (right) situation at the end of 2040.

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Figure 6.36 - Spatial distribution of normalized salt concentration for the T-0 (left) and SO-0 (right) situation at the end of 2040.

Figure 6.37 - Representation of pumping magnitudes for the 139 clustered municipal wells, both for the T-0 (left) and SO-0 (right) situation at the end of 2040.

As it is shown in the above figures, it is evident how the Simulation/Optimization method is able to identify an optimal solution for the management of the aquifer: while keeping total pumpings quite constant (with reference to the not-optimized situation), SWI

152 process is slightly blocked, extracted salt water is significantly slower that the previous pumping configuration, and also groundwater levels have significantly increased.

6.6 Summary and conclusions

The 3D hydrogeological model of Gaza Strip coastal aquifer is developed and then implemented using the CODESA-3D code (Gambolati et al,. 1999, Lecca, 2000) allowing to simulate coupled problems of variably saturated flow and contaminant transport in groundwater, in the presence of a fluid phase of variable density.

The hydrogeological model of the Gaza Strip is calibrated in steady-state conditions with 1935 water levels, considering average climate conditions and natural conditions (‘no- pumping’ scenario), by coupling simulation (CODESA-3D) and optimization (PEST) modules; then, the same calibrated model has been used as basis for the validation procedure, which has been performed for 1935-2000 and 2001-2010 periods. Although there are still some uncertainties in the southern part of the area, where the model seems to reveal some incongruence in the uphill part simulated groundwater table, the overall model is considered to properly represent the Gaza Strip aquifer system.

The simulated fields of water tables and groundwater salt concentration in 2010 are used as basis to simulate the response of the hydrological basin to future scenarios of climate change in the periods 2011-2040 and 2041-2070. In the study are considered a combination of 20 scenarios for each period, resulting from 4 GCM-RCM models and one more ‘artificial’ RCM (CC-0) within the same trend depicted for the historical period (1981-2010), and a combination of different pumping management and SLR setup. The analysis of outputs coming from all the simulations shows that the increasing or decreasing in water levels, and higher and lower values of groundwater heads, corresponding in general to the NetP trends as reported in Chapter 5, Table 5.13; however, different climate scenarios variables, in this case, lead to differences in the groundwater system that can be hardly be appreciated if compared with pumping effects; it is evident, in fact, that pumping scenarios have extremely high impacts on the Gaza aquifer system.

Although some mitigation options are being evaluated for the GCA, in this study is only proposed a single strategy, which consists in assessing a new management scheme of

153 groundwater by the means of a simulation/optimization procedure aiming at maximizing the projected pumping rates, while constraining salt concentrations; the adopted procedure is illustrated in Chapter 3. Results coming from the application of this methodology to the Gaza Strip aquifer show that SWI process is slightly blocked, extracted salted water is significantly lowered, and groundwater levels have significantly increased; so that, the Simulation/Optimization method is able to identify a possible optimal solution for the management of the Gaza coastal aquifer.

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