1. Mohammed Alzaaq MS GIS Program University of Redlands

2. Introduction Database Design Implementation Results Conclusion

3. Introduction - Database Design - Implementation - Results - Conclusions Salton Sea Background: Location: - Southern of California History: - 1905 a dam on Colorado River - rainstorm hit the area. General information: - Lowest surface elevation 277 feet below.. - Largest lake 370 sq. miles. Salton Sea Problems: salinity and drought. Salinity: - The Salton Sea’s salinity is about 54 g/L - The Pacific Ocean’s salinity is around 35 g/L - salt increases 1% every year.

4. Introduction - Database Design - Implementation - Results - Conclusions Professor Timothy Krantz - The Salton Sea Database Program (SSDP) http://www.spatial.redlands.edu/salton/ssdp.aspx Salton Sea Authorty

5. Introduction - Database Design - Implementation - Results - Conclusions

6. The Project Problem: - Where should the pipelines be located? - Where should the solar sites be located around the pipelines? - Factors should be considered.

7. Introduction - Database Design - Implementation - Results - Conclusions First Goal: - determining the optimal location for pipelines Second Goal: - identifying suitable sites for solar energy.

8. Introduction - Database Design - Implementation - Results - Conclusions Least-Cost Path Analysis: - connecting two points with a route. - has a source point, destination point, and cost surface. -. Weighted Overlay Analysis: - determining factors. - defining their weighted values. - identifying suitable sites for solar energy

9. Introduction - Database Design - Implementation - Results - Conclusions System Design: Input Layers: Land cover Protected Land Roads Rivers Cities DEM Input Layers: Land cover Protected Land Roads Rivers Cities DEM Geoprocessing Output Layer: Pipeline Routes Suitable Solar Sites Output Layer: Pipeline Routes Suitable Solar Sites Least-Cost Path Pipelines Tool Weighted overly Solar Sites Tool Least-Cost Path Pipelines Tool Weighted overly Solar Sites Tool

10. Introduction - Database Design - Implementation - Results - Conclusions

12. Boundaries. Human Factors. Natural Factors.

13. Introduction - Database Design - Implementation - Results - Conclusions

14. Digital Elevation Model (DEM)

15. Introduction - Database Design - Implementation - Results - Conclusions Land Cover Dataset

16. Introduction - Database Design - Implementation - Results - Conclusions Road Network Dataset

17. Introduction - Database Design - Implementation - Results - Conclusions Slope Cities Protected Land RiversRoads Land Cover

18. Introduction - Database Design - Implementation - Results - Conclusions Roads: - divided to: Paved Roads with value from 0 – 200 Unpaved Roads with value 0 – 100

19. Introduction - Database Design - Implementation - Results - Conclusions Roads:

20. Introduction - Database Design - Implementation - Results - Conclusions Roads:

21. Introduction - Database Design - Implementation - Results - Conclusions Slope

22. Introduction - Database Design - Implementation - Results - Conclusions Cities - high values for cities. - the equation was Con(IsNull("%Feature_Cities_Raster%"),0,300)

23. Introduction - Database Design - Implementation - Results - Conclusions Rivers - high values for rivers. - the equation was Con(IsNull("%Feature_Rivers_Raster%"),0,300).

24. Introduction - Database Design - Implementation - Results - Conclusions Protected Land - high values for protected land. - the equation was Con(IsNull("%Protected_Land_Raster%"),0,300)

25. Introduction - Database Design - Implementation - Results - Conclusions Land Cover - assigned based on the cover types. - the equation was Con("%Feature_Land_Raster%" == 2,300, Con("%Feature_Land_Raster%" == 5,300, Con("%Feature_Land_Raster%" == 7,300, Con("%Feature_Land_Raster%" == 8,200, Con("%Feature_Land_Raster%" == 4,200,1)))))

26. Introduction - Database Design - Implementation - Results - Conclusions Land Cover

27. Introduction - Database Design - Implementation - Results - Conclusions Least-Cost Path - source point. - destination point. - cost surface.

28. Introduction - Database Design - Implementation - Results - Conclusions Least-Cost Path

29. Introduction - Database Design - Implementation - Result - Conclusions Least-Cost Path Analysis: - 275 km. - 68 sea level at Salton Sea. - 60 meter elevation.

30. Introduction - Database Design - Implementation - Results - Conclusions At High Elevation Area. Elevation Profile: - 60 Meters. - 20 Meters (Vertical = elevation in meter, Horizontal = distance in meter)

31. Introduction - Database Design - Implementation - Results - Conclusions Slope, Solar Radiation, and Distance from the Pipelines. Slope Factor: - from DEM. - the range values form 0 to 40 degrees. - 4 degrees for each class. - was weighted 25%.

32. Introduction - Database Design - Implementation - Results - Conclusions Solar Radiation Factor: - sun light. - elevation. - orientation. - shadows. The Value Range: - between 401993 – ­­­­­­­­­­­­­658507 kwh/m²/Day. - suitable area for solar sites. - was weighted 50%.

33. Introduction - Database Design - Implementation - Results - Conclusions Distance from Pipelines: - 500 meter maximum distance. - each class has 50 meters distance. - was weighted 25%

34. Introduction - Database Design - Implementation - Results - Conclusions Weighted Overlay

35. Introduction - Database Design - Implementation - Result - Conclusions 60 Meter Elevation Area:

36. Introduction - Database Design - Implementation - Result - Conclusions 20 Meter Elevation Area:

37. Introduction - Database Design - Implementation - Result - Conclusions Pipeline Routes Solar Sites Suitability Surface

38. Introduction - Database Design - Implementation - Result - Conclusion Pipeline Routes was determined by using least-cost path. Solar Sites was discovered by using weighted overlay. A paper map was submitted to the client.