by- tarun gill.ppt

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1、,by: tarun gill,Interpolation and evaluation of probable Maximum Precipitation (PMP) patterns using different methods,objectives,To convert vector based PMP to raster based PMP using different interpolation methods.Finding the accuracy of all the methods used.Determining the best method for interpol

2、ation.,Interpolation,Predicting values of a certain variable at unsampled location based on the measurement values at sampled locations.,Different interpolation methods,Deterministic methods Use mathematical functions based on the degree of similarity or degree of smoothing,Geostatistical methods Us

3、e Both mathematical and statistical functions based on spatial autocorrelation,Data used,Probable maximum precipitation maps,Theoretically the greatest depth of precipitation for a given duration that is physically possible over a drainage area at a certain time of year.,Hmr-52 -Standard pmp estimat

4、es for united states east of the 105 meridian,Areas -10,200,1000,5000,10000 sq.miles Duration-6,12,24,48,72hours,Interpolate Using geostatistical wizard Optimize parameters Final raster grid,methodology,Original PMP shape files (vector data),Vectorize and compare with original shapefile,methodology,

5、INVERSE DISTANCE WEIGHTED,The further away the point the lesser its weight in defining the value at the unsampled location.,Uses values of nearby points and their distances,Weight of each point is inversely proportional to its distance from that point.,Inverse distance weighted,Inverse distance weig

6、hted,Inverse distance weighted,Raster created after interpolation,Conversion of raster into contours,comparison,spline,Fits a mathematical function to a specified number of nearest points.,Unknown points are estimated by plotting their position on the spline,minimizes overall surface curvature,Redun

7、dant values are often ignored,Regularised tension,spline,spline,spline,Raster created after interpolation,Conversion of raster into contours,comparison,Ordinary kriging,Z(s) = (s) + (s),Trend analysis,(si, sj) = sill - C(si, sj),semiVariogram (si,sj) = var(Z(si) - Z(sj),Covariance C(si, sj) = cov(Z(si), Z(sj),Ordinary kriging,Ordinary kriging,Ordinary kriging,Raster created after interpolation,Conversion of raster into contours,comparison,IDW,spline,kriging,comparison,Conclusion,