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Participants  Daniel Veasey  Aditya Banerjee  Danial Ho  Trond Vlot  Sean Moylan  Kirk Langridge  Scott Sam Perth Modern School.

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Presentation on theme: "Participants  Daniel Veasey  Aditya Banerjee  Danial Ho  Trond Vlot  Sean Moylan  Kirk Langridge  Scott Sam Perth Modern School."— Presentation transcript:

1 Participants  Daniel Veasey  Aditya Banerjee  Danial Ho  Trond Vlot  Sean Moylan  Kirk Langridge  Scott Sam Perth Modern School

2 Aim Our aim is to look for any direct correlations between socio-economic status and water consumption rates. Our hypothesis is that water consumption rates will be higher in suburbs with higher socio-economic status. We hope to do this by using data from water corporation and the Perth Social Atlas We will then put the data into ArcMap, and hopefully find a conclusion.

3 Why we chose the problem Water shortage (drought) is common in today’s news. This inspired us to see if there were any direct correlations between socio- economic status and water consumption. Hopefully our results will aid in the conservation of water in these troubling times.

4 How the task was approached We started by contacting the water corporation to access their figures of water consumption. We then went to a class to learn how to use the mapping software ArcGIS. Tom Gardner came to our school, specially to help use to use GIS. We then used data from the Perth Social Atlas, to determine socio-economic status of all suburbs. We then combined the data, and put them in ArcMap. We used graduated colours to determine whether a correlation existed.

5 Software used We mainly used the software called ArcGIS. We found that ArcGIS was a very useful software that fulfilled our needs. With the help of Tom Gardner, we were able to colour code the various socio-economic statuses of different suburbs. This made it clearer to see whether a correlation existed between socio-economic status and water consumption levels. We mainly used the software called ArcGIS. We found that ArcGIS was a very useful software that fulfilled our needs. With the help of Tom Gardner, we were able to colour code the various socio-economic statuses of different suburbs. This made it clearer to see whether a correlation existed between socio-economic status and water consumption levels.

6 Data Used The data we used consisted of a map which clearly showed the water consumption rates in each suburb, thanks to the water corporation, unfortunately we ran into problems loading each suburbs’ socio-economic status and as such we used Perth’s Social Atlas instead to give us a rough idea of each suburbs’ socio- economic status.

7 Method To get our results we contacted the water corporation for statistics on the average water consumption of various suburbs. We then found the socio- economic status of each suburb, then we tried to combined the results in ArcGIS, which helped us to prove there was no correlation.

8 Data From Perth Social Atlas Low Income AreasHigh Income Areas

9 Water Consumption Data

10 Explanation of data After inserting the data into ArcMap we used graduated colours to highlight the water consumption rates for each area. In our graduated colours system the lighter green colours represent the lower average KL consumption, the dark reds represent the higher end of the scale.

11 Arcmap Data overlayed on WA Map

12 Problems Faced It took a while to get the datasets that we needed and once we got the data we couldn’t open it as it was in pdf format. We solved this problem by accessing computers with adobe, then we were then able to complete our work. Also when we originally looked for Data on the ABS we found that their data wasn’t by suburb, so we had to use the perth Social Atlas instead.

13 What we achieved After comparing the results we proved that there was no correlation between the socio- economic status of a suburb and the water consumption. We infer that water consumption may be linked to factors such as population size of the suburb and industrial areas.

14 Future Research Potential Although we are disappointed that our research proved no correlation between the two datasets, we still believe that more research could be done to discover what factors are resulting in higher water consumption, e.g. Population size.

15 We would like to give a special thanks to: Mr Lowry Tom Gardner Michael Canci from the water corporation Daniel Veasey

16 References We got our water consumption data from Michael Canci at the Water Corporation We got our income statistics from the Perth Social Atlas 2006


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