Application of artificial intelligence and statistical recurrent models in predicting rainfall: A case study of Ludhiana, Punjab

Authors

  • SUBHRAJYOTI BHATTACHARJEE Department of Soil and Water Conservation Engineering, College of Agricultural Engineering and Technology
  • NILESH BIWALKAR Department of Soil and Water Conservation Engineering, College of Agricultural Engineering and Technology
  • KOYEL SUR Punjab Remote Sensing Centre, Ludhiana
  • SAMANPREET KAUR Department of Soil and Water Conservation Engineering, College of Agricultural Engineering and Technology
  • SOM PAL SINGH Department of Climate Change & Agriculture Meteorology, PAU, Ludhiana

DOI:

https://doi.org/10.54386/jam.v27i3.3038

Keywords:

SARIMA, NAR, Rainfall prediction

References

Amshi, A. H., and Prasad, R. (2023). Time series analysis and forecasting of cholera disease using discrete wavelet transform and seasonal autoregressive integrated moving average model. Sci. African, 20: e01652.

Baig, F., Ali, L., Faiz, M. A., Chen, H., and Sherif, M. (2024). How accurate are the machine learning models in improving monthly rainfall prediction in hyper arid environment? J. Hydrol., 633: 131040.

Kothiyal, S., Goel, S., Singh, R. K., Chilwal, A., and Ranjan, R. (2025). SARIMA-based time series analysis of rainfall and temperature for the Tarai region of Uttarakhand. J. Agrometeorol., 27(1): 73-76. https://doi.org/10.54386/jam.v27i1.2838

Priyan, K. (2021). Issues and challenges of groundwater and surface water management in semi-arid regions. Groundwater resources development and planning in the semi-arid region, 1-17.

Sarkar, P., Basak, P., Panda, C. S., Gupta, D. S., Ray, M., and Mitra, S. (2023). Prediction of major pest incidence in Jute crop based on weather variables using statistical and machine learning models: A case study from West Bengal. J. Agrometeorol., 25(2): 305-311. https://doi.org/10.54386/jam.v25i2.1915

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Published

01-09-2025

How to Cite

BHATTACHARJEE, S., BIWALKAR, N., KOYEL SUR, KAUR, S., & SINGH, S. P. (2025). Application of artificial intelligence and statistical recurrent models in predicting rainfall: A case study of Ludhiana, Punjab. Journal of Agrometeorology, 27(3), 395–398. https://doi.org/10.54386/jam.v27i3.3038

Issue

Vol. 27 No. 3 (2025): September

Section

Short Communication

Categories

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Copyright (c) 2025 SUBHRAJYOTI BHATTACHARJEE, NILESH BIWALKAR, KOYEL SUR, SAMANPREET KAUR, SOM PAL SINGH

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