| Abstract: | ABSTRACT A method of stream baseflow prediction using a parallel drain theory and convolution techniques was developed. The infiltrating portions of several rain events were superimposed on the ground-water reserves and allowed to drain to the stream as individual baseflow responses. The convolution technique was used in summing the contributions from each rain event to the stream to give the total baseflow at any point in time. A single lumped parameter was adapted from a parallel drain analogy to represent the physical characteristics of a watershed. This parameter determines the time delay between a rainfall event and the resulting baseflow response. The procedure was applied to data from five watersheds. One year of records was used to find the best-fitting runoff delay coefficient, thus calibrating the response function which was subsequently applied to two test years to predict a dry weather low flow sequence. The agreement between predicted and observed flows was reasonably good, but marred by frequent minor rainfalls during the chosen dry periods. The application of the method should be much more successful in the western states where prolonged dry periods are common. |
