GIS modeling for predicting river runoff volume in ungauged drainages in the Greater Toronto Area, Canada

Abstract

This paper introduces two parsimonious models for predicting runoff for ungauged basins from the observed river flow data in gauged basins and precipitation data from rain gauging stations in the same area. The models assume the runoff is related to the precipitation subject to variance of drainage basins. The runoff can be modeled as a function of precipitation and parameters determined by basin descriptive properties. The parameter values of the models can be calibrated statistically on the basis of observed historical runoff data and precipitation data. Further the parameters can be regressed to associate with the areas of different landcover types occupying the drainage basins. This regression model can be used for estimating parameter values for ungauged basins in the same study area which can be further used together with precipitation data to predict the runoff in the ungauged basins. An example of adopted Soil Conservation Service (SCS) method with application to the Oak Ridges Moraine area was introduced to demonstrate the implementation of the models introduced. The information used for the modeling and prediction includes: surficial geology, DEM, Landsat TM images, historical river flow data, and precipitation and temperature data from weather stations.