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ANALYSIS OF ESTIMATED RAINFALL DATA USING SPATIAL INTERPOLATION. Preethi Raj GEOG 5650 (Environmental Applications of GIS)

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Presentation on theme: "ANALYSIS OF ESTIMATED RAINFALL DATA USING SPATIAL INTERPOLATION. Preethi Raj GEOG 5650 (Environmental Applications of GIS)"— Presentation transcript:

1 ANALYSIS OF ESTIMATED RAINFALL DATA USING SPATIAL INTERPOLATION. Preethi Raj GEOG 5650 (Environmental Applications of GIS)

2 Environmental Application of GIS Spring 06 2 INTRODUCTION Current research in Hydrology emphasizes on ability to forecast hydrologic parameters. Precipitation Infiltration Evapo-transipiration Stream flow Hydrologic Cycle

3 Environmental Application of GIS Spring 06 3 PROBLEMS Precipitation plays an important role in Hydrologic cycle. Need for precipitation data to have a better understanding of Hydrologic cycle. Due to practical difficulties not possible to have rain gauges all over the world. Need for an alternative to estimate precipitation data.

4 Environmental Application of GIS Spring 06 4 STUDY AREA - USA Total number of stations = 6322

5 Environmental Application of GIS Spring 06 5 STUDY AREA - USA Number of stations selected = 1904

6 Environmental Application of GIS Spring 06 6 PROCESSES SPATIAL INTERPOLATION Kriging Interpolation Inverse Distance Weighted interpolation

7 Environmental Application of GIS Spring 06 7 KRIGING

8 Environmental Application of GIS Spring 06 8 KRIGING PREDICTION STANDARD ERROR MAP

9 Environmental Application of GIS Spring 06 9 INVERSE DISTANCE WEIGHTED IDW POWER- 2 IDW POWER - 3 IDW POWER - 4IDW POWER - 5

10 Environmental Application of GIS Spring 06 10 ANALYSIS TENNESSEE ALABAMA SELECTED STATIONS = 62 UNSELECTED STATIONS = 148 = SELECTED STATION = UNSELECTED STATION

11 Environmental Application of GIS Spring 06 11 RESULTS

12 Environmental Application of GIS Spring 06 12 RESULTS Interpolation Method Root-Mean-Square Kriging0.3734 IDW- Power 20.3652 Optimize power value(2.5595) 0.3602 IDW- Power 30.3619 IDW- Power 40.3704 IDW- Power 50.3784

13 Environmental Application of GIS Spring 06 13 CONCLUSIONS Values obtained using Kriging, IDW- Power 2 & 3 gives similar values and closer to actual precipitation value. Difference in values obtained using IDW – Power 5 is high.

14 Environmental Application of GIS Spring 06 14 THANK YOU ANY QUESTIONS ?

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