Application of Remote Sensing and GIS to Model Mountainous Rivers

Abstract

The purpose of this study is to develop a semidistributed, physically based hydrologic model ~SDPB - HM! for mountainous watersheds areas. Most of the model's required parameters were acquired using remote sensing and digital terrain elevation data. A three-stage computer classifier model was built based on the error back-propagation artificial neural network approach~EBPANN! and refined to classify the land cover types of the study area. In addition, the reflection properties of the land cover types were used to improve the technique of estimating the net radiation in Morton's evapotranspiration model. A procedure was proposed for discretizing the watershed areas, aimed to increase the homogeneity and minimize the calculation time. The SDPB - HM was applied to the Albert River Basin in the Rocky Mountains in British Columbia, Canada. The Albert River meteorological data from October 1986 to September 1987 was used to calibrate the model parameters. In addition, the SDPB - HM was validated using the meteorological data of a case study from October 1987 to September 1988 and from October 1988 to September 1989. Comparison between the simulated and the observed flow at the outlet of river showed a good agreement during these periods.