Usability of the Weather Forecast for Tackling Climatic Variability and Its Effect on Maize Crop Yield in Northeastern Hill Region of India

Author:

Chakraborty DebasishORCID,Saha Saurav,Sethy Bira Kishore,Singh Huidrom Dayananda,Singh Naseeb,Sharma Romen,Chanu Athokpam Nomita,Walling Imtisenla,Anal Pashel Rolling,Chowdhury Samik,Hazarika Samarendra,Mishra Vinay Kumar,Jha Prakash KumarORCID,Prasad P. V. VaraORCID

Abstract

Weather forecasts are important for the planning of agricultural operations, especially during times of heightened climatic variability. This study analyzed and verified the medium-range weather forecast issued by the India Meteorological Department (IMD) for different weather parameters over four locations in the northeastern hill (NEH) region of India considering five years of daily datasets. Results revealed good overall accuracy of the forecast over the NEH region. The accuracy of relative humidity (>80%), rainfall (>79%), and wind speed (>70%) were good, and the accuracy of temperature was average, with the usability values for maximum temperatures (44.7–62.7%) comparatively better than for minimum temperatures (38.5–58.6%). The correlation coefficient between the observed and forecasted values was positive (0.24–0.70) and statistically significant for most of the cases, indicating that the forecast could capture variations. Field experiments for maize crops showed that a near-real-time weather forecast-based agro-advisory could manage the uncertainties related to the in-season weather and thereby help in its day-to-day management, which is depicted by the statistically significant (p < 0.05) improvements in the yield of maize. The accuracy of the minimum temperature was poor during winter and post-monsoon seasons, when it plays a crucial role in the determination of optimal growing conditions. Usability of the maximum temperature needs improvement during the pre-monsoon season, as crop cultivation over the region starts from this season due to the high probability of assured rainfall. Therefore, the forecasts were found to be useful but in need of improvement for minimum temperature, which is very crucial for the region.

Funder

Indian Council of Agricultural Research

Publisher

MDPI AG

Subject

Agronomy and Crop Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Forecasting Crop Yield For Sustainable Agriculture;International Journal of Advanced Research in Science, Communication and Technology;2023-12-11

2. Crop Yield Prediction Using Machine Learning Models: Case of Irish Potato and Maize;Agriculture;2023-01-16

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