Numerous studies have been conducted to minimize the adversity yet continuous monitoring is required for the Northwest region of Bangladesh. The study introduces a method for forecasting meteorological droughts in the Northwest region of Bangladesh using daily precipitation, and temperature data from 1952 to 2020. The Standard Precipitation Index (SPI) and Standard Precipitation-Evapotranspiration Index (SPEI) parameters were created, and an Artificial Neural Network (ANN) model was used to predict droughts over 3-, 6-, 9-, and 12-month lead time. The findings of the study showed that short lead time prediction was better compared to long lead time predictions. The study also found that SPEI-based predictions were better than SPI for the six stations of the study area. Using the ANN model to predict drought using more parameters, the community of that location can be more resilient.
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METEOROLOGICAL DROUGHT PREDICTION FOR THE NORTHWEST REGION OF BANGLADESH USING ARTIFICIAL NEURAL NETWORK (ANN)
Published:
17 April 2024
by MDPI
in OHOW 2023 – The 2nd International Symposium on One Health, One World
session Climate change and green recovery
Abstract:
Keywords: SPI, SPEI, Multi-layer perceptron, ANN, Levenberg-Marquardt Algorithm
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