Estimation of Rainfall from Climatology Data Using Artificial Neural Networks in Palembang City South Sumatera

Abstract

Estimation of climatological parameters, especially rainfall is a data requirement for all regions of Indonesia. The availability of rainfall data is used for early warning of flood or drought disasters. The study location is in Palembang City, South Sumatra Province, where floods and droughts often occur and lack of availability of rainfall data. This study aims to obtain the best model in estimating rainfall from climatological data. The analysis was carried out to estimate the rainfall from the climatological data using the Artificial Neural Networks method. The Artificial Neural Networks were applied and showed some results with the best calibration was at 16 years using TRAINLM with 1500 epochs that is the performances NSE = 0.54, RMSE = 99.37, and R = 0.74. Whereas the best validation was at 1 year that is the performances NSE = 0.41, RMSE = 87.32, and R = 0.65.