Inductive transfer applied to stream discharge modeling

Artificial neural networks and inductive transfer are used to develop models that predict the discharge (flow rate) of fresh water streams in Nova Scotia from weather data. The objective is to show that transfer can be used to reduce the time and cost associated with collecting large amounts of the data for environmental modeling. The models use two days of weather data to predict the discharge for the following day. The models can be applied to land use, water management and flood predictions for sections of streams where continuous monitoring is not feasible. Models developed using only 180 days of training data with transfer from related streams perform as well on independent test data as models constructed using five years of training data and no transfer.