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Importance of monsoon rainfall cannot be ignored as it affects round the yearactivities ranging from agriculture to industrial. Accurate rainfall estimationand prediction is very helpful in decision making in the sectors of waterresource management and agriculture. Due to dynamic nature of monsoon rainfall,it's accurate prediction becomes very challenging task. In this paper, weanalyze and evaluate various deep learning approaches such as one dimensionalConvolutional Neutral Network, Multi-layer Perceptron and Wide Deep NeuralNetworks for the prediction of summer monsoon rainfall in Indian state ofRajasthan.For our analysis purpose we have used two different types of datasetsfor our experiments. From IMD grided dataset, rainfall data of 484 coordinatesare selected which lies within the geographical boundaries of Rajasthan. Wehave also collected rainfall data of 158 rain gauge station from waterresources department. The comparison of various algorithms on both these datasets is presented in this paper and it is found that Deep Wide Neural Networkbased model outperforms the other two approaches.

A Deep and Wide Neural Network-based Model for Rajasthan Summer Monsoon Rainfall (RSMR) Prediction