Previsão de Seca Meteorológica de Longo Prazo para a Região Noroeste de Bangladesh Usando Rede Neural Artificial Wavelet

Abstract

Meteorological drought is a temporary and recurring atmospheric event, originating from a lack of precipitation over a considerable period in a particular area. The north-western part of Bangladesh is facing precipitation anomalies that may turn into meteorological drought, and for this reason, it is required to investigate the confirmation of the emergence of meteorological drought in this area near the future. In this study, using Artificial Neural Network (ANN), this phenomenon has been investigated for a region of the north-western part of Bangladesh that is the Bogra district. Through the prediction study of meteorological drought index- the Standardized Precipitation Index (SPI-12 and SPI-24), it has been found that this region will face extreme meteorological drought within 2030. The data has been pre-processed through Discrete Wavelet Transformation (DWT) before prediction, which has improved accuracy. The major challenges for this study were forecasting drought for a longer lead time (almost 16 years). Non-linear autoregressive artificial neural network (NAR-NN) coupled with DWT has successfully predicted that with a reasonable accuracy of R-value > 0.8 and a mean square error (MSE) ≤ 0.05. The result shows that extremely dry and wet events will occur in that area very frequently, affecting stream-flow, reservoir storage, and groundwater recharge.

Keywords
meteorological drought; Standardized Precipitation Index; Wavelet Artificial Neural Network (WANN); North-western region of Bangladesh