Abstract:
The Indus River, a transboundary and one of the biggest rivers in the world originates in west
ern Tibet, flows northwest through Ladakh, Gilgit-Baltistan, and then south and southeast across
Pakistan and empties into the Arabian Sea. Tarbela Reservoir is one of the biggest being con
structed on the Indus River and plays a pivotal role for agriculture, water storage, hydropower,
and ecosystem stabilization. This study attempts to model and forecast the monthly extreme
precipitation events in the Upper Indus Basin (UIB) using time series and machine learning
approaches. The observed data about precipitation has been collected from the Pakistan Me
teorological Department (PMD) for the duration of 1960-2013 and then the monthly extreme
precipitation was calculated by using Excel. Two classes of time series models, i.e., Autoregres
sive Integrated Moving Average (ARIMA) whereas LSTM form of Recurrent Neural Network
(RNN) form machine learning approach have been used. The performance of these models
has been assessed by using various error statistics (e.g., RMSE, MBE, AIC, and BIC) as well as
graphically. The findings of this study may help policymakers in water availability, hydropower,
infrastructure loss, flooding, and agriculture.
