Dam Management Through Various Machine Learning And Deep Learning Models: A Review

Dams or reservoirs play a significant role in managing drought, flood, hydro power generation, irrigation for agriculture activities, drinking purposes etc. Data from meteorological department like daily prediction and weekly prediction of rainfalls in catchment areas, monsoon effects and water levels in dams, inflow level, outflow rate of water from dams, temperature etc. are major criteria for deciding dam openings. Correct and timely data helps to take correct decisions for managing dams. In this review, several machine learning and deep learning algorithms like ANFIS, CANFIS, decision tree, artificial neural network (ANN), random forest, Particle swarm optimization, gradient boosting, XG Boost, multilayer perceptron, Genetic algorithm, CNN, RNN, SMLA, Artificial Bee colony Optimization are presented for effective dam or reservoir management.