Streamflow prediction at ungauged remote sites

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The main goal of this research project is to evaluate and improve the accuracy, functionality, reliability, and suitability of Ontario Flow Assessment Tools (OFAT) III for micro-hydropower (MHP) generation projects in ungauged basins; this projects aims to identify the main sources of uncertainty and quantify the magnitude of the inherent error associated with stream flow assessment in ungauged basins. OFAT III is a new online spatial application currently under development that will automate a series of labour intensive hydrology tasks using data packages, known as Ontario Integrated Hydrology Data, to provide a collection of related elevation and mapped water features for hydrology applications, such as stream flow assessment. Although these hydro-electric power generators have been receiving a great deal of attention from both private and public sectors, there are inadequate records of hydrological data for optimum design of such projects in ungauged, headwater streams, in Ontario. This study develops novel methods for estimation of stream flow at ungauged remote sites using an integrated approach that employs OFAT III datasets and Water Survey of Canada historic stream flow statistics at over 100 stations to prepare input data for the training of an artificial neural network model (ANN). Further it employs the hydrological regionalization methods and seasonal hydrologic analysis to minimize the error and generate a more accurate estimation of streamflow. This project will develop design tools for implementation of micro-hydropower generation stations to advance Canada's green renewable energy generation goals and advance sustainable development in rural communities. This research will contribute to advancement of Canadian manufacturers of emerging micro-hydropower technologies with development of engineering design tools to make them more cost-competitive.