Runoff Prediction Uncertainty for Ungauged Agricultural Watersheds

Abstract

A physically based stochastic watershed model is used to estimate runoff prediction uncertainty for small agricultural watersheds in Hastings, Nebraska. The stochastic nature of the model results from postulating a probabilistic model for parameter estimation and input errors. The key factors assumed to contribute to prediction uncertainty are errors in estimating infiltration parameters and moisture conditions prior to a rainfall event. The error distributions for parameter estimates are inferred from soil survey information, and the error distribution for moisture conditions from a regression between antecedent precipitation indices and measured soil moisture. Comparison of model predicted and observed errors demonstrates that the model is conservative in that it is biased towards overprediction of errors.