EFFECTS OF RADAR-ESTIMATED PRECIPITATION UNCERTAINTY ON RAINFALL-RUNOFF MODELING

Abstract

Runoff generation has been shown to be very sensitive to precipitation input. With the use of precipitation estimates from weather radar, errors are introduced from both the transformation from reflectivity to precipitation rate and the spatial and temporal aggregation of the radar product. Currently, a significant degree of uncertainty exists in the accuracy of radar-based precipitation estimates. When uncalibrated or poorly calibrated radar products were used as input to a rainfall-runoff model, the resulting predicted runoff varied severely from the runoff generated using well-calibrated radar products. Another source of uncertainty, errors in the precipitation system structure due to aggregation in time and space, has also been shown to affect runoff generation. This study focuses on separating the primary runoff-generating mechanisms -- infiltration excess and saturation excess -- to assess their responses to variable precipitation inputs individually. For the case of saturation excess runoff, there was minimal sensitivity due to temporal aggregation of the precipitation; however, there was considerable sensitivity to spatial aggregation. For the case of infiltration excess runoff, temporal and spatial aggregation of the precipitation significantly reduced the amount of runoff produced. The magnitudes of these runoff reductions varied between storms and showed a high degree of dependence on storm characteristics, particularly the maximum precipitation intensity.