Investigating the Accuracies in Short-Term Weather Forecasts and Its Impact on Irrigation Practices

Kambhammettu, B. V. N. P. and Regonda, Satish Kumar (2023) Investigating the Accuracies in Short-Term Weather Forecasts and Its Impact on Irrigation Practices. Journal of Water Resources Planning and Management, 149 (2). 04022079. ISSN 0733-9496

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Abstract

The effectiveness of irrigation schedules and crop growth models is largely dependent on the accuracies associated with the most uncertain input parameter, viz. weather forecasts. This research is focused on quantifying the inaccuracies associated with the India Meteorological Department (IMD) issuing short-term weather forecasts (with 1-5 days lead time), and their propagation into irrigation models, with an objective to select the optimal parameters for use with simulation. While precipitation (P) forecasts were directly used, remaining meteorological forecasts were converted to reference evapotranspiration (ET0) forecasts. The effectiveness of the 'P' and 'ET0' forecasts was found to be low at all lead times. We applied two popular bias correction methods: linear scaling (LS) and empirical quantile mapping (EQM), and observed a marginal improvement in forecast skill. Bias-corrected, forecast-driven irrigation scenarios, along with conventional irrigation (that ignores weather forecast), and a hypothetical perfect 5-day forecast-based irrigation (as reference) system were tested on a water-intensive paddy crop for two growing seasons (S1: monsoon and S2: winter). Conventional irrigation resulted in the highest use of irrigation water (820 mm in S1, 880 mm in S2) and percolation loss (1,140 mm in S1, 680 mm in S2), while achieving a low relative yield (0.88 in S1, 0.87 in S2). LS-corrected forecasts outperformed other scenarios with 20.24%±4.21% and 1.25%±1.51% savings in irrigation costs for S1 and S2, respectively. While IMD forecasts greatly improved irrigation schedules in the monsoon season, their usage for winter crops was found to be trivial. Our findings conclude that LS-corrected IMD forecasts were moderately reliable over multiple lead times and can serve as a valuable addition to irrigation scheduling, provided the contribution of 'P' to the total water balance is significant.

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IITH Creators:
IITH CreatorsORCiD
Kambhammettu, B. V. N. P.UNSPECIFIED
Regonda, Satish Kumarhttp://www.orcid.org/0000-0003-3188-9415
Item Type: Article
Uncontrolled Keywords: Bias correction; Crop simulation; India Meteorological Department (IMD); Irrigation schedule; Rice; Weather forecast; Atmospheric thermodynamics; Crops; Solvents; Uncertainty analysis; Water conservation; Water management; Water supply; Weather forecasting; Bias correction; Crop simulations; India meteorological department; Irrigation crops; Irrigation practices; Irrigation schedule; Leadtime; Linear-scaling; Rice; Weather forecast; accuracy assessment; computer simulation; correction; irrigation system; quantitative analysis; rice; weather forecasting; Irrigation; India
Subjects: Civil Engineering
Civil Engineering > Water resources engineering
Divisions: Department of Chemical Engineering
Depositing User: Mr Nigam Prasad Bisoyi
Date Deposited: 22 Aug 2023 05:27
Last Modified: 22 Aug 2023 05:27
URI: http://raiithold.iith.ac.in/id/eprint/11580
Publisher URL: https://doi.org/10.1061/JWRMD5.WRENG-5644
OA policy: https://v2.sherpa.ac.uk/id/publication/11583
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