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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 21, issue 2
Hydrol. Earth Syst. Sci., 21, 707-720, 2017
https://doi.org/10.5194/hess-21-707-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Sub-seasonal to seasonal hydrological forecasting

Hydrol. Earth Syst. Sci., 21, 707-720, 2017
https://doi.org/10.5194/hess-21-707-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 02 Feb 2017

Research article | 02 Feb 2017

Short to sub-seasonal hydrologic forecast to manage water and agricultural resources in India

Reepal Shah1, Atul Kumar Sahai2, and Vimal Mishra1 Reepal Shah et al.
  • 1Civil Engineering, Indian Institute of Technology (IIT) Gandhinagar and ITRA Project: Measurement to Management (M2M): Improved Water Use Efficiency and Agricultural Productivity through Experimental Sensor Network, Gandhinagar, India
  • 2Indian Institute of Tropical Meteorology (IITM), Pune, India

Abstract. Water resources and agriculture are often affected by the weather anomalies in India resulting in disproportionate damage. While short to sub-seasonal prediction systems and forecast products are available, a skilful hydrologic forecast of runoff and root-zone soil moisture that can provide timely information has been lacking in India. Using precipitation and air temperature forecasts from the Climate Forecast System v2 (CFSv2), the Global Ensemble Forecast System (GEFSv2) and four products from the Indian Institute of Tropical Meteorology (IITM), here we show that the IITM ensemble mean (mean of all four products from the IITM) can be used operationally to provide a hydrologic forecast in India at a 7–45-day accumulation period. The IITM ensemble mean forecast was further improved using bias correction for precipitation and air temperature. Bias corrected precipitation forecast showed an improvement of 2.1mm (on the all-India median mean absolute error – MAE), while all-India median bias corrected temperature forecast was improved by 2.1°C for a 45-day accumulation period. Moreover, the Variable Infiltration Capacity (VIC) model simulated forecast of runoff and soil moisture successfully captured the observed anomalies during the severe drought years. The findings reported herein have strong implications for providing timely information that can help farmers and water managers in decision making in India.

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