Water Level Modelling and Prediction of Floods, Evacuation Plan and Reservoir Inflow, Based on Deduru Oya Basin, Sri Lanka

In water resources reservoir plays an important role as it functions for different purposes in different times such as providing effective water storage, water for hydropower generation, water for irrigation activities, mitigating the impacts of disastrous environmental effects, as well as meeting the water demand for the people in drought conditions. In order to minimize the impacts which are faced by the people in downstream areas and also for the safety and maintenance of the reservoir it requires fast and accurate prediction of decisions. These impacts are mainly caused due to the uncertain weather and climate conditions, other geographical characteristics and also due to the reservoir operations. So that implementing a system which consists of accurate modelling and prediction of water levels, floods existence and flood evacuation plan, and optimization of reservoir operations based on inflow prediction in order to minimize these impacts have been taken into consideration throughout the study. Since Artificial Neural Network (ANN) shows a significant improvement in the area of hydrological modelling in last decade, multilayer perceptron (MLP) method is applied to develop the flood model. Long Short-Term Memory (LSTM) models are developed for the modelling and prediction of water levels of downstream locations and also for the reservoir inflow prediction from the upstream basin based on the nonlinear time series analysis of hydrological data around the area.