The effect of gauge sampling density on the accuracy of streamflow prediction for rural catchments

Abstract A streamflow model of a 4800 km 2 rural catchment using distributed rain inputs and infiltration was set up in a computer. Rain inputs were provided in the form of half-hour accumulation maps of real storm events collected by radar over southern Quebec. Point sampling of the accumulation pattern simulated gauge returns. Interpolation of the ‘gauge’ data to complete coverage was accomplished using Thiessen polygons. Hydrographs were computed for the interpolated and radar accumulation fields as a simple function of distance from the catchment outflow point. Ten sampling densities were used, and for each density hydrographs were computed for a large number of repetitions with gauges redistributed randomly for each realization. Comparisons of estimates of total rainfall, total runoff, peak runoff and time to peak between the hydrographs resulting from the random sampling and interpolation, and that computed from the full resolution radar accumulation field were made. As with estimates of areal rainfall we find that gauge density has a very strong effect on the estimation accuracy of hydrograph parameters with the standard error generally falling off as a power law with increasing gauge density.