Preprints
https://doi.org/10.5194/hess-2022-218
https://doi.org/10.5194/hess-2022-218
 
23 Jun 2022
23 Jun 2022
Status: a revised version of this preprint is currently under review for the journal HESS.

Ensemble streamflow prediction considering the influence of reservoirs in India

Urmin Vegad1 and Vimal Mishra1,2 Urmin Vegad and Vimal Mishra
  • 1Civil Engineering, Indian Institute of Technology (IIT) Gandhinagar
  • 2Earth Sciences, Indian Institute of Technology (IIT) Gandhinagar

Abstract. Developing an ensemble hydrologic prediction system is essential for reservoir operations and flood early warning. However, efforts to build hydrologic ensemble prediction systems considering the influence of reservoirs have been lacking in India. We examine the potential of the Extended Range Forecast System (ERFS, 16 ensemble members) and Global Ensemble Forecast System (GEFS, 21 ensemble members) forecast for streamflow prediction in India using the Narmada River basin as a testbed. We use the Variable Infiltration Capacity (VIC) with reservoir operations (VIC-Res) scheme to simulate the daily river flow at four locations in the Narmada basin. We examined the streamflow forecast skills of the ERFS forecast for the period 2003–2018 at 1–32 day lead. We compared the streamflow forecast skills of raw meteorological forecasts from ERFS and GEFS at a 1–10 day lead for the summer monsoon (June–September) 2019–2020. The ERFS forecast underestimated extreme precipitation against the observations compared to the GEFS during the summer monsoon of 2019–2020. However, both the forecast products showed better skills for minimum and maximum temperatures than precipitation. Ensemble streamflow forecast from the GEFS performed better than the ERFS during 2019–2020. The performance of the GEFS based ensemble streamflow forecast declines after five days lead. Overall, the GEFS ensemble streamflow forecast can provide reliable skills at a 1–5 day lead. Our findings provide directions for developing a flood early warning system based on ensemble streamflow prediction considering the influence of reservoirs in India.

Urmin Vegad and Vimal Mishra

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2022-218', Anonymous Referee #1, 31 Jul 2022
    • AC1: 'Reply on RC1', Vimal Mishra, 15 Sep 2022
  • RC2: 'Comment on hess-2022-218', Anonymous Referee #2, 11 Aug 2022
    • AC2: 'Reply on RC2', Vimal Mishra, 15 Sep 2022

Urmin Vegad and Vimal Mishra

Urmin Vegad and Vimal Mishra

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Short summary
Floods cause enormous damage to infrastructure and agriculture in India. However, the utility of ensemble meteorological forecast for hydrologic prediction has not been examined. Moreover, Indian river basins have a considerable influence of reservoirs that alter the natural flow variability. We develop a hydrologic modelling based streamflow prediction considering the influence of reservoirs in India.