Inflow Prediction of Lower Paunglaung Dam for Water Resource Management

Reservoir dams play a vital role in the national economy and social development of any country, such as flood control, power generation, irrigation and water supply. The Lower Paunglaung Dam, the largest multipurpose dam in Myanmar, is facing difficulties in managing its water resources. Lower Paunglaung Dam and its weir were mainly constructed to irrigate agricultural land as well as to generate hydropower. Predicting the inflow rate precisely is therefore essential for managing water resources since it aids in planning for floods, droughts, and the production of electricity in the Nay Pyi Taw region. Moreover, climate change impacts are more significantly affecting the safety of dams. In order to prevent flood damage and maintain a steady supply of water from water resources, accurate dam inflow estimates are becoming more and more important in the face of climate change. In order to estimate dam inflow, this study used historical data from the previous 20 years. A deep learning model, Long Short-Term Memory (LSTM) is used in this system to predict the inflow of Lower Paunglaung Dam in the Paunglaung River watershed in Myanmar. Root Mean Square Error (RMSE), accuracy, number of epochs are taken into account for assessing the effectiveness and performance of the suggested inflow prediction model.