Overcoming the challenges of flow forecasting in a data poor region

Abstract In Ontario, the Ministry of Natural Resources and Forestry (MNRF) is responsible for the provincial flood forecasting and warning (PFFW) program. The goal of Ontario’s PFFW program is to reduce the risk of loss of life, injury, and property damage due to flooding. The Surface Water Monitoring Centre (SWMC) fulfills MNRF’s provincial mandate for public safety by providing daily provincial scale Hazard Identification and Risk Assessment (HIRA) for flooding for the province at a provincial scale. The SWMC uses a variety of tools to complete the HIRA, however, there are currently no operational flood forecasting capabilities available within the suite of monitoring tools used by the province. Ontario’s Special Advisor on Flooding Report and the Ontario Flooding Strategy highlights flood forecasting as a part of overall flood management. As a follow up, a pilot study using WATFLOOD® was undertaken in the Severn River in Northern Ontario to explore the use and implications of operational forecasting capabilities in a data poor region. There are currently no year-round meteorological stations in this watershed. WATFLOOD is well suited for application in remote and data poor regions as the hydrological parameters are not watershed based and can be calibrated with data from watersheds in a similar physiographic/climatic domain – e.g. the Hudson Bay Lowlands. This paper will show: that hydrological and routing parameters from a more densely instrumented region can be applied to a data poor region; that WATFLOOD can be used to provide an acceptable flow forecast and calibration in a data-poor region; and Numerical weather model data, rather than conventional gauge data can be used to successfully calibrate a hydrological model in a data poor region.