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Salinity vs. Population Density For Spatial Technology In Schools (STIS) 2011 By The Geography class of Semester 2, 2011, Perth Modern School.

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Presentation on theme: "Salinity vs. Population Density For Spatial Technology In Schools (STIS) 2011 By The Geography class of Semester 2, 2011, Perth Modern School."— Presentation transcript:

1 Salinity vs. Population Density For Spatial Technology In Schools (STIS) 2011 By The Geography class of Semester 2, 2011, Perth Modern School

2 The Hypothesis That as population density increases so will soil salinity. This, if true may be as a result of removal of vegetation which serves to hold the water table containing dissolved salts deeper underground.

3 Why this problem was selected It took a class vote to decide as to what subject we were to investigate. Each member of the class came up with an idea of what could be done (within the limits and required to use GIS skills). These original ideas are displayed below. Then as a class we narrowed down our options, eventually ending with the ‘Salinity vs. Population Density’ task. We eliminated other possibilities due to their already available information and maps as well as the difficulty of the task.

4 Why this problem was selected Possible project ideas we created:  Salinity vs Population Density  Energy wastage in school  Is there a pattern to power outages?  ISD location exchanges  Heat islands or oceans  Radiation and High Tension lines  River Pollution chemical waste  Geocaching as an educational tool  Soil pollution  Food Miles  Where do WA’s products go?  Flight path noise  Effect of lack of backyards  North Perth heritage Project  Boat Ramps – location service area condition location of new ones  Water consumption in public spaces  Local brothels to bogan ratios (using GIS of course)

5 The Process-Topographical layer creation One of the set tasks was to create a topographical layer to put on the GIS system we were using to see if there was a correlation between terrain and salinity that could make the salinity versus population data invalid. Many programs were tried. We tried using the online WA Atlas but the contours were far too general to be used to create a topographical survey. We attempted to use Google Earth to draw up boundaries for coastal areas but we were unable to find significant landmarks that we could use as boundaries. Our teacher finally found some good maps for us to use that were supposed to be compatible with ArcGIS but we were unable load them onto ArcGIS. In the end the topographical layer was abandoned.

6 The Process-Locating the Salinity meters To start our project one of the early tasks was to find meters to measure the salinity of the soil. Once we established this was done by using conductivity meters, we began searching the appropriate departments.  West Australian Education Department: This was unsuccessful as their search engine was ineffective and after 20 or so searches did not wield any rentable equipment.  Water Department: This was also unsuccessful as the equipment was not available for student use.

7 The Process-Locating the Salinity meters For the above departments these are examples of the search terms we used:  Salinity testing  Salinity testing kits  Salinity testing equipment  Soil Salinity  Science equipment  Science consultant We then inquired within the school to the science department and found they had access to several salinity testing kits (conductivity meters, model EUTECH multi- parameter TESTR 35 Series). We used these to measure the salinity in all our soil samples.

8 The Process-Using the Conductivity meters  The salinity meters that we used were the EUTECH ‘Multi-Parameter TESTR 35 Series.’  They were very easy to operate.  To calibrate them, you only had to test a control sample with a known conductivity to ensure that the reading was correct.

9  Testing the salinity of the soil was also very simple. A suspension of the soil was made, with a 5:1 ratio of water to soil, and then the conductivity meter was put into the correct mode (micro Siemens). The electrodes were completely submerged in the suspension and that gave us our readings.  Once the reading had stabilised, the value was recorded, and placed into a table of results. The Process-Using the Conductivity meters

10 The Process-Project Management Software Ace project is web based project management software with the ability to create GANTT charts, assign tasks and deadlines, timesheet management and project cost tracking. Ace project is a collaboration oriented project system with a free package available meaning that if one were so inclined they would be able to have an account for an infinite amount of time. Ace project has a customer feedback section for improvements of the program; an example of this is the change from computer exclusive to smartphone and tablet device compatible. The program is also able to set statuses for jobs; (e.g. Waiting, in progress and completed); and the priority of jobs (e.g. low, normal and urgent. For more than 5 people to have an account on a project, payment is required, however multiple people can use an account and multiple projects can be opened for pseudo unlimited potential. A discount of 20% of the total price for payment packages is awarded if the purpose of the software is not profitable.

11 The Process-Project Management Software The application of this software was not implemented chiefly because the project did not need such a closely monitored approach. However, we considered the evaluation of the software to be beneficial to future generations whose school projects would be project based and the research done by this group could be useful to the future community.

12 The Process-Problems Methods for measuring soil conductivity were narrowed down to five possibilities early on in the project, these being  Boiling  fractional crystallization  silver nitrate precipitation  pH and conductivity testing.

13 The Process-Problems Boiling and fractional crystallization were eliminated first because of the fact that they were deemed time consuming and dangerous (they involved dissolving salts into a solution and boiling them until only solids remained). Testing for pH was eliminated because it would only detect acidic and basic salts, while all neutral salts would remain undetected that could influence salinity. Silver nitrate was also eliminated because it would only detect halide salts (Chloride and bromide mainly) however there would still be sulphates, oxides, hydroxides, acids and many others remaining undetected.

14 The Process-Problems By process of elimination we were left with the conductivity testing method. This involved saturating the soil samples and waiting for solids to settle in the bottom of a beaker then inserting the conductivity meter probes in. This would give a conductivity reading in deci-siemens per metre (ds/m).

15 Results

16 Discussion-Factors Affecting Validity  The people who got samples for our testing may have not followed the instructions properly (the soil sample needed to be taken from 30cm below the surface)  Where the samples were taken, only the postcode was used not the exact coordinates or address  The salt water from the sea could affect the sandy loams near it, which may affect the result

17 Discussion-Factors Affecting Validity  Things that may have been put on top of the soil i.e. Fertiliser…  The rain fall content may have affected the results when being tested  The accuracy of the testing of the soil samples with the conductivity metres  If someone just makes up numbers as the result  If someone is not aware of where they actually live and just puts down a random postcode

18 Discussion-Factors Affecting Validity  If the population of a suburb changes greatly from when the sample was taken and the results were handed in.  If there is some type of religious ceremony or celebration of any sort where they might through salt onto the soil in there are, and a sample was taken from that area.  If the conductivity metre has salt stuck to it before testing  If someone lives at the beach and takes their soil from there the salt water could affect the results.

19 Conclusion A correlation co-efficient of 0.52 indicates that there is very little correlation between population density and soil salinity. In some instances you have high salinity and high population, and in other cases the reverse is true. Therefore it is likely there are other contributing factors to the level of salinity in the metropolitan area. We suspect that topography is a major factor and we did initially intend to correlate that information, but we unable to upload it into the GIS. Some of the results indicate that high residential populations result in relatively intense watering which would flush the soil and reduce salinity. Also the sample size would need to be expanded significantly in order to get a more accurate result. This could be a project for the future. So far our results indicate that most households should not have concerns about the salinity.

20 Future Research Potential While the project has encountered numerous problems, the information we have gathered (though not complete) is potentially useful for future research on salinity in urban areas. The information that has been collected is the only piece of information available: minimal research has been done in the past on this subject. For the project to work however, modifications must be made to the method it is collected and recorded. Throughout the course of the processing of data, it has been discovered that salinity varies greatly within suburbs not only within the entire Perth metropolitan area. Because of the inaccuracy due these variations of results in each suburb another alternative has to be made. A different (perhaps more accurate) method that could be considered is to record not just by postcode/suburb but by the suburb/postcode and the terrain type. As there are many diverse terrains with varying salinity levels, simply measuring the salinity of the entire suburb would be too broad meaning them accuracy is limited. As stated before, there is very limited information on the matter and only we have the information however imprecise the measurements may be. With the information, we could possibly come to a solution to the rising salinity levels in the water table and other places.

21  Alastair Watling-Project management  Jay O’Dea-Hypothesiser  Cameron Harris-Topographical layering  Joe Dowson-GPS units for geo-tagging results  Dougal Hanson-GPS units for geo-tagging results  Lauren Anderson-ArcGIS licencing  Gavin Jackson-Mentor from Main Roads WA  Lucas Tan-General Help  Ashfaq Asif-Presentation  Ryan Cooper-Presentation  Cameron Duncan-Reporting on Conductivity meters  Xanthe Buddle-Planning  Lucy Axton-Planning  James Pretty-Acquiring equipment  Dylan Smith-Acquiring equipment  Nathan Fang-Project management software  Jackie Lin-Factors affecting validity of data  Crystal Dietrechsen-Factors affecting validity of data  Jason Yang-Future research potential  Ant Meczes -Soil testing kits  Geoffrey Chew-Proofing  William Sadler-Acknowledgments Acknowledgements

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