flow.py calculate trend and corresponding p value trend_[start_year]_[end_year] the output of flow.py [station] [trend] [p value] diff.cal-Bru.perc the difference between our calculated trend and p-value and those reported in Brutsaert's paper (for 1988-2007) [station] [trend diff (cal-Bru)] [trend diff percentage] [p-value diff] [p-value diff perc] big.diff.stations stations which has a calculated trend for 1988-2007 different than Bru's trend for >5% [station] [trend diff percentage (cal-Bru)] [p-value diff percentage (cal-Bru)] compare.yL7 comparing calculated yL7 with yL7 calculated by Bru each row is a year, 20 rows altother (1988-2007) the first 41 colums are Bru's data; the second 41 columns are our calculated data in the order of station.order diff.yL7 difference between Bru's yL7 and our calculated yL7 (Bru's - ours) each row is a year, 20 rows altother (1988-2007) each column is a basin, in the order of station.order plot.yL7.diff.py python script to plot yL7 difference well_data.py process USGS well data USGS_well_data USGS well data ########################### # input ########################### station.order list of station ID in the order of listed in Bru's paper (same order as Bru's raw yL7 data)) station.basin matching stations with 11 basins [station] [number of basin] [basin name] basin.list a list of the names of 11 larger basins (ordered) bas_map list of 11 basins (same order as listed in Bru's paper) directly from Liz not read by scripts basin.values.ori the original values in the GIS map for the 11 basins (in the order of listed bas_map) ########################### # output ########################### trend_[start year]_[end year]_[K*] trend at each station (for specified K value) [station] [trend(mm/yr)] [p-value] yL7_[start year]_[end year] 7-day annual low flow each row: a year each column: a station (in the order of station.list) yL7_occur_month_[start year]_[end year] the occurrence month of the 7-day low flow same format as yL7_[start year]_[end year] trend_[start year]_[end year]_map the areal mean storage trend for 11 basins each row: a bain (in the order of basin.list) first column: the values in the original GIS raster file (gwtrends2.asc) second column: trend values (to substitute the values in the first column) this file can be directly read by rewrite.scr trend_resid_[start year]_[end year]_map the areal mean standard deviation for residual of storage trend for 11 basins each row: a bain (in the order of basin.list) first column: the values in the original GIS raster file (gwtrends2.asc) second column: SD values (to substitute the values in the first column) this file can be directly read by rewrite.scr trend_flow_larger_basin_[start year]_[end year] regression coefficients for flow trend of 11 larger basins each row: a basin (in the order of basin.list) the regression is: y = m * x + c, where x is year; y is areal mean annual low flow first column: m [mm/(d*yr)]; second column: c [mm/d] ########################### In Brutsaert_data directory ########################### Low flows east of Rockies (1).xlsx raw Excel data from Liz low_flow_from_Bru.xlsx revise the format of 'residual' sheet in the above Excel yL7_Bru_1988_2007 formatted Bru's yL7 data each row is yL7 for a year (1988-2007) each column is a basin, in the order of station.order unit: mm/d trend_Bru_1988_2007 the trend and p value reported in Brutsaert 2009 paper (for 1988-2007)