This project aims to help the Red Cross predict flooding occurrences in Togo due to overflow in the Nangbeto Dam. Flooding is a result of both high flow rate and the water level in the dam at any point in time. This project focuses specifically on predicting the flow rate in the dam using precipitation data from eight locations around the country. A Lasso model and cross validation were employed to evaluate the significance of the predictors and capture the variance of flow rate.
Jessica Wert, Angelica Estrada, Oumayma Koulouh (Smith College)