Verification of Rain Model for Year 2021 for Selected Areas of India Prone to Drought

Anand M Sharan*

Professor, Mechanical Engineering Department, Faculty of Engineering, Memorial University of Newfoundland, ST. John’s, Newfoundland, Canada

*Corresponding Author: Anand M Sharan, Professor, Mechanical Engineering Department, Faculty of Engineering, Memorial University of Newfoundland, ST. John’s, Newfoundland, Canada.

Received: January 27, 2022; Published: March , 2022

Abstract

In this work, the rain model for the areas of India which are prone to drought – is investigated based on four methods. These methods are: The Time Series method, The Root Mean Square (RMS) method, The Fast Fourier Transform (FFT) method, and the Artificial Neural Network (ANN) method. The predicted rain amount for each of the areas is taken as the average result obtained by each of these methods. One has to keep in mind that the rainfall in these areas are highly erratic. The predicted rainfall is compared with the actual rainfall in these areas. The accuracy of the model is based on the average of the percentage deviation from the actual rainfall. The rainfall is considered as normal by the Indian Meteorological Department (IMD) is within 19% of the actual rain amount.

Keywords: Areas of India; ANN; FFT; Prone to Drought

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Citation

Citation: Anand M Sharan. "Verification of Rain Model for Year 2021 for Selected Areas of India Prone to Drought". Acta Scientific Agriculture 6.4 (2022): 02-07.

Copyright

Copyright: © 2022 Anand M Sharan. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.