Forecasting of Rainfall and Identification of Its Scarcity in Indian States for the Upcoming Decade

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Vysoká škola báňská - Technická univerzita Ostrava

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This research delves into the analysis of rain- fall data for the past 50 years in India to identify criti- cal areas necessitating the implementation of rainwater harvesting systems. The impetus for this investigation arises from the rising demand for such systems, primar- ily driven by dwindling groundwater levels in certain Indian regions. These declining groundwater levels can be attributed to reduced rainfall, which, in turn, can be linked to the effects of global warming and the unpre- dictability of weather conditions. The study employs time series analysis techniques, particularly utilizing the neural prophet model, to forecast the rainfall in the upcoming decade for the different states in India. Based on the forecasting data, the most significant deficits in terms of annual rainfall are identified using the percent- age departure formula available on the IMD (Indian Meteorological Department) website. The result shows that the following states are the most deficient, i.e., Mathatwada region, and Haryana Chandigarh region, in terms of scarcity of rainfall. It has been observed from the analysis that the error is in the range of ±1%. The predicted rainfall in Haryana, Chandigarh is -683.53 mm, and Mathatwada is 5865 mm

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data science, microanalysis, neural prophet, rainwater harvesting, statistical analysis, time series analysis

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Advances in electrical and electronic engineering. 2025, vol. 23, no. 4, pp. 263 – 280 : ill.