## 3 Results and Discussion  
### GIS Application  
#### 3.1.1 Case Scenario 1: No Detection of Leakage Location(s)  
To prove that this integrated approach works, this method was applied to dates that are known not to have any leakages. The raw data provided by SEWA is shown below, and it illustrates the flow and pressure values for each day in one month at 10 locations in the city of Sharjah. Using ArcGIS Pro, the flow and pressure data for each location are evaluated to map the water quality parameters. As mentioned in the previous section, the assumption is made that any flow higher than the average or pressure value lower than the average from the data set (highlighted in green and red) is suspected to have a leak in that location. Another assumption for suspected leakage is customer complaints. Tables 1 and 2 show the daily flow data (in m\({}^{3}\)/day) at 10 different locations in a specific month, and Table 3 shows the average flow for that month. Any value less than the average is highlighted in green. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c} \hline \hline
**DMA** & **D1** & **D2** & **D3** & **D4** & **D5** & **D6** & **D7** & **D8** & **D9** & **D10** & **D11** & **D12** & **D13** & **D14** & **D15** & **D16** \\ \hline Al Rahmanya-1 & 740 & 760 & 660 & 680 & 710 & 770 & 710 & 670 & 600 & 790 & 580 & 740 & 500 & 600 & 0 & 650 \\ \hline Al Rahmanya-3 & 960 & 1100 & 1030 & 920 & 1200 & 1140 & 1210 & 1120 & 600 & 1160 & 990 & 1190 & 1140 & 670 & 1250 & 1210 \\ \hline Industrial Area-4 & 4500 & 5070 & 540 & 6930 & 5430 & 5450 & 5120 & 5110 & 4760 & 4730 & 4960 & 5180 & 5380 & 5150 & 5350 \\ \hline Industrial Area-4 & 30 & 20 & 10 & 0 & 40 & 30 & 40 & 40 & 20 & 10 & 0 & 10 & 20 & 40 & 10 & 30 \\ \hline Barashi & 410 & 570 & 160 & 630 & 670 & 930 & 1180 & 2260 & 2070 & 1800 & 1220 & 1420 & 640 & 780 & 1060 & 830 \\ \hline Maysaloon & 440 & 650 & 800 & 450 & 170 & 100 & 240 & 1310 & 1710 & 2540 & 2780 & 3120 & 2620 & 2670 & 2940 & 3110 \\ \hline Al Fayah & 980 & 980 & 1020 & 920 & 1030 & 1050 & 1070 & 1080 & 1010 & 1060 & 1080 & 1070 & 1060 & 960 & 1020 \\ \hline Al Ghuwair & 3340 & 4230 & 8190 & 3800 & 4650 & 5290 & 2870 & 3850 & 830 & 790 & 870 & 860 & 1200 & 890 & 950 & 1070 \\ \hline Bu Tina & 6500 & 690 & 6600 & 7280 & 7270 & 7120 & 7010 & 7040 & 6930 & 7410 & 7800 & 7420 & 7410 & 7150 & 7200 & 7150 \\ \hline Al Sabkha & 3740 & 3730 & 3660 & 3670 & 3770 & 3760 & 3680 & 3730 & 3700 & 3870 & 3810 & 3720 & 3840 & 3970 & 3780 & 3830 \\ \hline Al Sabkha & 890 & 880 & 900 & 830 & 800 & 860 & 740 & 880 & 850 & 820 & 800 & 730 & 640 & 690 & 700 & 630 \\ \hline Al Ghaphia & 1270 & 1140 & 750 & 220 & 580 & 1170 & 610 & 830 & 1060 & 740 & 350 & 690 & 830 & 730 & 850 & 760 \\ \hline Al GTables 4 and 5 show the daily pressure data (in bars) at 10 different locations in one month, and Table 6 shows the average flow for that month. Any value less than the average is highlighted in red. The model is initiated by adding the given pressure and flow values into the ArcGIS Pro software. This is followed by the addition of the flow query values, which exclude any flow values above the average value and identify the value with the lowest flow below average from each location. Furthermore, the pressure query values are found by taking the average of the average pressure values from each location. Once the query values have been obtained in the model, a buffer analysis is conducted within a radius of 2000 m around the suspected leakage areas. That is, the buffer analysis tool on ArcGIS Pro traverses the suspected regions and creates buffer polygon offsets. The blue polygons in Figure 7 show the intersections of the buffer offsets generated from the suspected areas within a 2000-meter radius.