2000 Volume 44 Pages 127-132
The present paper shows the relevance of a new approach of using back propagation neural network (BPNN) in storm runoff estimation by using near surface soil moisture. Intensive field observation and field experiment conducted to observe the behavior of a forested catchment in Tono area is presented. The results obtained by numerical experiment using BPNN were tested by the field experiment and catchment observations. Both the experiment and field observations supported the results of the previous studies. The field experiment showed that the importance of litter layer in the direct contribution to runoff was not so significant. It was observed that the highly conductive soil layer underlying the litter layer and overlying the less macroporous soil zone with low hydraulic conductivity was the chief contributor to the total runoff in the study area. The field observation showed that the main contribution to the total storm runoff was from the channel system that received the runoff from such layers as in the field experiment.
