Estimation of Surface-Subsurface Water Balance in Lower Tapi River Basin Using Gridded Data and Station-Based Observed Data

Abstract

ABSTRACT Water is an essential resource. An understanding of catchment water balance is crucial to ensure water availability in the region. Hydrological models are credible tools for water balance assessment of a region. These models are data intensive. The traditional hydrological modeling approach relies on station-based observed data. The availability of sufficient long-term consistent observed data is often limited. On the other hand, climate reanalysis data for a long timeperiod is available from multiple data sources. This study estimates runoff characteristics for Lower Tapi River Basin in western India, with the help of a Soil Conservation Service Curve Number method. The catchment water balance in terms of runoff, baseflow, and recharge at sub-basin scale is worked out with the help of station-based and climate reanalysis datasets. The model output are calibrated against observed river gauging data. A reasonable fit between model-simulated and observed runoff is obtained in terms of duration and magnitude of runoff peak. Tested model is applied to future climate scenarios. The simulations show an increase in surface runoff, recharge, baseflow and total runoff for future time period. Results reveal that climate changes have significant impact on hydrology of the basin.