## 4 Discussion  
The model on ArcGIS 3.0 Pro was successfully tested on a section of the Sharjah WDN. The results obtained from the analysed data showed a gradual increase in the suspected leakage area from October to July. This can be attributed to the extreme temperature fluctuations between the tested seasons as well as the time factor. This indicates that there is  
Figure 9: Analysis maps for June.  
more pipe breakage/leakage in summer and winter compared to the rest of the seasons [45]. SEWA also confirmed the vulnerability of pipe leakage in that area [46].  
Typically, there is less rainfall during the summer, causing the ground to be very loose. This allows the pipes to shift and/or expand, which can lead to pipe bursts and leakage as a result. Additionally, hot and dry weather calls for more showers, the frequent recreational use of water in general, the frequent watering of lawns and plants, and more drinking water for our consumption. All of these create a higher-than-normal water demand, which poses a high demand for the water pipes as well. If the pipes are not in good condition, are aging, or are rusting, an increase in water demand can lead to a leak somewhere in the line, or worse, they may burst. Moreover, if a pipe is clogged, the pipeline pressure can increase to an extent that pushes the pipe to crack and leak. Temperature changes in winter can cause the pipes to contract upon cooling, causing cracks and leaks as a result. Furthermore, there is typically a water consumption reduction during this season, causing a rise in the water pipe pressure which might lead to leaks. In transition months like October, the water consumption and weather conditions are typically less extreme and hence do not pose a threat to the distribution pipes. Additionally, any change in soil characteristics due to weather fluctuations would cause changes in pipeline infrastructure, which would cause an imbalance between pipeline sections and fittings, and cause pipe wall rupture, water leakage, and pipe bursts [47].  
Another perspective to consider is the time factor between the trials. Pipes that had been damaged during October (due to aging, temperature change, and construction anomalies) could continue to deteriorate over the year if no measures are taken to fix/replace those [48].  
Considering that the model results agreed with the typically expected weather, soil, and temporal impacts on the water network and consistency with the literature in potential leakage location, this proves the model's accuracy and efficiency in water leak detection [49]. Additionally, the real-time analysis creates an added benefit of increasing the time to respond or take action, minimizing future risk, understanding the network's behaviour as leaks occur, and identifying the common areas of leaks/bursts, while simultaneously saving unnecessary costs [49]. Finally, the model results can be displayed in the GIS in combination with other layers, including the topographic layer of the city, the road layer, and the water treatment plants in the vicinity, which can provide an understanding of the network behaviour and critical zone identification for optimal management and operation of the pipe system. Furthermore, the method utilizes existing pipe sensors which can eliminate the costs associated with other means of leakage detection. The method also proved its applicability in a large-scale network.