Improvement to the Thornthwaite Method to Study the Runoff at a Basin Scale Using Temporal Remote Sensing Data

Abstract

Most of the popular hydrological models are intensive data driven hence, it has become a constraint in computing runoff of river basins where the meteorological data availability is scant. Studying environmental impact assessment on runoff has also become complex in many basins due to non-availability of sufficient historic meteorological data. Directly or indirectly, major components of hydrological cycle such as evapotranspiration and soil moisture are dependent on land use pattern at basin scale. Keeping in view of this, in this paper, an attempt was made to propose modification to simple monthly water balance model by integrating potential evapotranspiration with land use coefficients that were derived from the temporal satellite remote sensing data to compute runoff at basin scale. Godavari Basin, India was selected as study basin to demonstrate the approach. Monthly land use coefficients of all land use classes were computed during the calibration process of the model by matching the computed runoff with field runoff. Runoff during the last 18 years (1990–91 to 2007–08) was computed using the developed methodology. Four years datasets were used for model calibration and the rest of the data for model validation. Spatial annual groundwater flux, reservoir flux and domestic water consumption grids were computed using the field data and integrated with the model in computing runoff. From the Nash-Sutcliffe efficiency coefficient, it is found that computed runoff is very well matching the field runoff. The demonstrated approach is found to be more accurate and simple in computing runoff at basin scale in absence of high intensity meteorological data.