Appendix B. GIS Workflow

          The first layer brought in was a simple vector layer displaying the name, location and agency responsible for each weather station. This was done by creating a table containing all the relevant information and converting it to a shapefile. Then tables were created containing each station name, latitude, longitude, and total evapotranspiration for each 8-day period analyzed. A separate file was created containing the table for each 8-day period. Each table was converted to a shapefile. The MODIS raster grid for each corresponding 8-day period was also brought in. The model below was then run for each period.

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          First, each weather station 8-day evapotranspiration shapefile was converted to a raster surface using the Inverse-Distance Weighted method, using the ET field as the Z value.

          Next, erroneous values in the MODIS raster grid were nullified using raster calculator. In MODIS ET data, fill values of 32761 through 32767 are assigned to erroneous or missing cells, so cells with values of 32761 and above were assigned NoData. The following expression was used in Raster Calculator: SetNull(“Input_raster” >= 32761, “Input_raster”), where “Input_raster” is replaced by the raster layer name. Raster Calculator was used again to fill cells with nullified values. A cell with NoData was assigned the average of the four surrounding cells, using the following expression: Con(IsNull("calculation"), FocalStatistics("calculation", NbrRectangle(4,4, "CELL"), "MEAN"), "calculation"), where “calculation” is the name of the raster layer with nullified erroneous values.

          Finally, the values between the surface raster created using the weather station data and the “clean” MODIS raster were compared by calculating the percent difference between the two. The following expression was used: (Abs(“Modis” – “met_station_idw”) / “met_station_idw”) * 100, where “Modis” is the clean MODIS raster, and “met_station_idw” is newly generated surface raster.

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