| Summary: | Low-gradient landscapes found in parts of the Taiga Plains and the North American Prairies can be dominated by many depressional wetlands with variable storage capacity. Runoff from these regions is influenced by the local storage capacity of individual wetlands and water exchange between the wetlands. Fill-and-spill conceptual models have been proposed to consider the connectivity-controlled process in wetland dominated catchments. Although fill-and-spill phenomenon has been locally observed, few studies examine the response of a landscape to thousands of cascading wetlands, as is seen in a number of Canadian landscapes. Being able to characterize, understand, and parameterize this response in hydrological models may enable successful simulation of the contribution area and runoff response in wetland-dominated regions. Current probabilistic fill-and-spill models consider individual features rather than the cumulative connections between adjacent wetlands in a cascade. The lack of understanding of the regional effects of wetland distributional characteristics on landscape hydrology, combined with insufficiently resolved elevation data, particularly in flat terrains, are two concerns that signify the need for an improved probabilistic runoff model. We propose an upscaled wetland fill-and-spill (UWFS) algorithm to investigate the response of large-scale wetland systems in low gradient areas to rainfall or snowmelt events. The research addressed in this thesis consists of the following: 1. An explicit probabilistic-analytic model is developed and tested for cascades of wetlands, providing an upscaling approach to understand and characterize system responses. To do this, first, a probabilistic analytic model is developed based on the fill-and-spill conceptualization, which considers each wetland in the basin as a member of an ensemble. The mathematical solution requires information about the initial deficit distribution and distribution of wetland local contributing areas which may be estimated via a combination of ...
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