ABSTRACT
Two modelling approaches are presented in this article for spatial and temporal analysis of water resources risk. Major sources of uncertainty in water resources management are spatial and temporal variability. Spatial variability occurs when values fluctuate with the location of an area and temporal variability occurs when values fluctuate with time. System dynamics (SD) simulation and hydrodynamic modelling are presented in this article as tools for modelling the dynamic characteristics of flood risk and its spatial variability. The first modelling framework presents SD simulation coupled with 3D fuzzy set theory. Whereas the second modelling framework presents hydrodynamic modelling coupled with 3D fuzzy set theory. The two integrated modelling frameworks are illustrated and compared using the Red River flood of 1997 (Manitoba, Canada) as a case study. For the 1997 Red River case study, SD simulation proved to be efficient modelling approach for capturing the feedback-based dynamic processes occurring in the watershed. However, the SD simulation has limited capacity for adequately representing spatial processes. The SD simulation coupled with 3D fuzzy set theory and geographic information system-based spatial analysis tool provides an integrated approach capable of modelling the spatial and temporal variability of flood risk. With respect to the topography of Red River basin, the hydrodynamic modelling coupled with 3D fuzzy set theory proved to be an accurate approach for predicting spatial and temporal variation of water surface elevation, velocity, flux, etc. The integrated approach demonstrates high accuracy in predicting spatial and temporal variability of flood risk.
Acknowledgements
Our sincerest thanks go to Duane E. Kelln, Alfred Warkentin, Sie Dan, Eugene F. Kozera, and Bob Harrison of Manitoba Water Stewardship for providing the necessary data to carry out this work.
Funding
Funding from National Sciences and Engineering Research Council (NSERC) of Canada to carry out this work is greatly appreciated.