Developing a five-day streamflow forecasting system for Upper Narmada River Basin

Accurate streamflow forecast with longer lead time is helpful for several hydrological applications such as scheduling irrigation, estimating inflow to reservoirs, sending alarms in case of extreme events etc. Major flooding events in the Indian subcontinent in recent years have highlighted the need for more precise streamflow forecasts and confirmed the potential advantage of high-resolution NWP models.In India, National Center for Medium Range Weather Forecast (NCMRWF) provides rainfall forecasts from its UK Met office Unified Model based deterministic model (NCUM), and ensemble prediction system (NEPS). However, the utility of different forecast products in streamflow forecasting is still being explored. In a recent study, Goswami et al. (2018 ) used NCUM rainfall forecast during two heavy rainfall events as an input to a Soil and Water Assessment Tool (SWAT) model for streamflow forecasting in Narmada river basin. The performance of streamflow forecasts were found to be directly related to skill in NCUM rainfall forecast causing different levels of overestimations in upper and lower parts of Narmada.

This study attempts to overcome the limitations shown in Goswami et al. by setting up a streamflow forecasting system using SWAT over the Manot Watershed which is a part of upper Narmada river basin in central India. The streamflow forecast is examined from 2016 to 2018 at multiple lead times i.e.1 to 5 days. Rainfall forecast(s)of 0.25 *0.25 degrees spatial resolution are taken from three global NWP models namely Japan Metrological agency (JMA), NCMRWF and European Center for Medium Range Forecast (ECMWF).In this study, we use rain-gauge based gridded (IMD) rainfall product as observation data for set up the SWAT model. The preliminary comparison of simulated streamflow with the observation shows that the patterns of stream flow generated by different forecast products is in good match with high peaks. Our results also indicate that the forecast accuracy of NCMRWF is closely comparable with other forecast products for all lead time.The detailed results of ongoing work will be presented at the conference.