The potential use of remotely sensed soil moisture estimates in hydrological modelling

Abstract

This study aims to investigate the potential use of remotely sensed soil moisture (RSSM) estimates in calibrating a hydrological model in the Upper Peradeniya Catchment area in the Mahaweli Basin, a significant contributor to Sri Lanka's economy. Hydrological observations in various kinds are essential for constraining a reliable set of parameters for hydrological simulations. Soil moisture, which is listed among the fifty essential climate variables by the Global Climate Observing System, plays a crucial role in this process. Due to practical issues, when estimating the spatial and temporal distribution of soil moisture in basin-scale hydrological modelling, RSSM products are a viable solution over in-situ measurements. In this study, the ABCD hydrological model was used to simulate soil moisture in different seasons of the watershed. Finally, the RSSM data from Soil Moisture Active Passive (SMAP L4) satellite were integrated with the soil moisture estimations from the hydrological model to recalibrate the parameters. The findings of this study suggest that the integration of SMAP L4 to the ABCD model has no significant impact in enhancing the accuracy. However, the study highlights the importance of using multiple inputs in hydrological model calibration to enhance the reliability in final output.