Assessing the influence of weather parameters on rainfall to forecast river discharge based on short-term

Abstract

Rain serves as one of the key components in water cycle and it comes in the form of water droplets that are condensed from atmosphere and then fall on earth surface as rainfall. It has much importance. However, excessive rainfall can cause environmental hazards. This work developed an adaptive neuro – fuzzy inference system (ANFIS) to relate certain weather parameters (temperature and relative humidity) with rainfall in order to forecast the amount of rainfall capable of causing River Yazaram in Mubi town to discharge. It is predicted that, Mubi will experience high rainfall on 7th, 27th and 30th August 2016 as 56 mm, 28.8 mm and 28.8 mm respectively. Furthermore, on 7th August 2016 River Yazaram is likely to discharge. The model developed is validated with mean square percentage error (MAPE) of 4.64% and correlation coefficient of 0.1277 and 0.075 of rainfall with temperature and relative humidity respectively. Keywords: Model, Weather parameters, Forecasting and rainfall