This theme aims to advance our knowledge on flood forecasting systems and enhance flood forecasting capacity in Canada, which is a key target of FloodNet. An enhanced flood forecasting system that can deliver accurate and reliable forecasts with an appropriate lead time is seriously needed for better flood mitigation in flood prone regions of Canada. In addition to its five projects, this theme will benefit from the outcomes of Themes 1 and 2 in the development of the Canadian adaptive flood forecasting and early warning system (CAFFEWS). CAFFEWS will also help in the analysis of flood impacts on water resources systems and the environment (Projects 4-1, 4-2, 4-3 of Theme 4).
THEME LEADER:
Professor Paulin Coulibaly (McMaster University)
Department of Civil Engineering and School of Geography and Earth Sciences
Email: couliba@mcmaster.ca
CO-LEADER:
Professor Weihua Zhuang (University of Waterloo)
Department of Electrical and Computer Engineering
Email: wzhuang@uwaterloo.ca
Dr. Peter Rasmussen - In Memoriam (University of Manitoba)
Email: -
Dr. Tricia Stadnyk
Email: tricia.stadnyk@ucalgary.ca
Dr. Thian Gan
Email: tgan@ualberta.ca
Dr. Paulin Coulibaly
Email: couliba@mcmaster.ca
Objective: Review flood forecasting systems currently implemented by Canadian provinces and evaluate their performance in meeting their intended purpose.
Significance of research: In order to propose better methods for flood forecasting in Canada, it is imperative to start with a thorough evaluation and comparison of existing methods. In this project, we will evaluate adopted and alternative methods through a number of selected case studies.
Outcomes: The proposed research will result in recommendations for the type of tools and data that are most suitable for flood forecasting under particular circumstances. This information will provide input to other projects and guide some of the research efforts in FloodNet, specifically Project 3-4.
Dr. Aaron Berg
Email: aberg@uoguelph.ca
Dr. Paulin Coulibaly
Email: couliba@mcmaster.ca
Dr. Thian Gan
Email: tgan@ualberta.ca
Objective 1: Assess whether the monitoring network and available data can meet enhanced flood forecasting requirements and use other sources of information (e.g., remote sensing, radar, gridded/reanalysis datasets) along with regionalization techniques to address data limitations.
Objective 2: Use available satellite derived soil moisture products to derive and assess near real time, spatially distributed, estimates of the status of soil water and snow water equivalence. Investigate bias correction techniques for estimating rainfall from the next generation of radar (NEXRAD) data.
Significance: This subproject will address the critical issue of the paucity of monitoring data. The limitation of Canadian hydrometric networks is well established. A general framework is needed to consistently address data limitation. In recent years satellite derived hydrological products have emerged that are of interest for the improvement of initial state estimation for hydrologic models used in flood forecasting. Similarly, merging radar rainfall with rain gauge data allows the generation of distributed rainfall fields needed for improved flood forecasting.
Outcomes: A robust tool for data estimation will be developed to address the common problem of data limitation due to inadequate monitoring networks.This subproject will generate practical tools for deriving distributed products (rainfall, soil moisture, snow water equivalent) from radar and satellite data for inclusion in flood forecasting systems. In addition, these products can have various applications including climate model initialization, reservoir operation planning, and crop yield prediction.
Dr. Weihua Zhuang (University of Waterloo)
Email: wzhuang@uwaterloo.ca
Dr. Wei Song (University of New Brunswick)
Email: wsong@unb.ca
Dr. Paulin Coulibaly (McMaster University)
Email: couliba@mcmaster.ca
Objective: Investigate and develop effective and efficient wireless networking strategies to reliably transmit FloodNet sensing data to the information processing center and disseminate flood warning messages to the general public in a timely manner.
Significance: Due to potentially devastating damages from floods to lives and properties, enhanced information collection and communication is essential to assist the FloodNet framework in preventing costly impacts on the economy and casualties caused by disasters.
Outcomes: We will develop new integrated systematic approaches for reliable transmission of spatially distributed data collected from various sources to an information processing center. We will also develop effective and efficient information dissemination strategies (algorithms and protocols) to deliver timely alerts of the flood forecasting system to the general public. The outcomes from Project 3-3 will feed directly into CAFFEWS.
Dr. Paulin Coulibaly (McMaster University)
Email: couliba@mcmaster.ca
Dr. Amin Elshorbagy (University of Saskatchewan)
Email: amin.elshorbagy@usask.ca
Dr. Aaron Berg (University of Guelph)
Email: aberg@uoguelph.ca
Dr. Bryan Tolson (University of Guelph)
Email: btolson@uwaterloo.ca
Dr. François Anctil (Université Laval)
Email: francois.anctil@gci.ulaval.ca
Dr. Peter Rasmussen - In Memoriam (University of Manitoba)
Email: -
Objective: Develop a forward-looking flood forecasting tool (i.e., CAFFEWS) that includes adaptive structures for assimilating new technology and new data/information as they become available, and which can be adapted to different regions of Canada for enhanced flood forecasting.
Significance: Accurate and reliable flood forecasts are fundamental to enhanced flood mitigation and can be obtained by developing an advanced flood forecasting system. The development of CAFFEWS will contribute significantly to enhancing the national capacity for flood forecasting, which is one of the key targets of FloodNet.
Outcomes: To deliver an adaptive flood forecasting and early warning system for Canada.
Dr. Donald Burn (University of Waterloo)
Email: dhburn@uwaterloo.ca
Dr. Amin Elshorbagy (University of Saskatchewan)
Email: amin.elshorbagy@usask.ca
Dr. Paulin Coulibaly (McMaster University)
Email: couliba@mcmaster.ca
Objective: To provide an impartial and thorough evaluation of CAFFEWS in a variety of forecast settings for conditions typical of Canadian forecast situations.
Significance: The efficacy of CAFFEWS for forecasting in a Canadian environment needs to be evaluated to determine under which conditions the new system can provide improved forecasts and to quantify the range of expected improvements in forecasting capability. This work will lead to implementation recommendations that our partners can use to revise their current flood forecasting approaches.
Outcomes: The outcomes from this project will include: i) a rigorous evaluation of CAFFEWS for a variety of differing data availability conditions and forecasting environments; ii) a summary of the conditions for which CAFFEWS is anticipated to result in improved forecasts; and iii) an estimate of the expected magnitude of improvement in the various forecast performance metrics.