Developing a New Deconvolution Technique to Model Rainfall-Runoff in Arid Environments

摘要

Noisy rainfall-runoff records of short duration are encountered in arid environments where rainfall often occurs in short isolated bursts and the data are measured with a considerable margin of error. Known noise was superimposed on synthetic rainfall-runoff data to examine the ability of the Neuman-de Marsily deconvolution method to estimate the correct impulse response of the system when the data include only a single storm event. Approximately 50 Monte Carlo simulation runs were performed for each of three different noise models. The results clearly demonstrated that the deconvolution model leads to reliable estimates and can be used with confidence in the presence of realistic noise levels.