Advances in continental domain hydrology: Improving simulations of cold region hydrological processes over North America

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Modelling the terrestrial component of the water cycle remains a critical scientific challenge. While global hydrological models have certainly improved over the past several decades, such large-domain models still struggle with representing complex cold region hydrological processes in data sparse environments. It is especially difficult to simulate the dynamics of glaciers, seasonal snow, permafrost, lakes and wetlands, and rivers, along with their biogeochemical cycles, when there is limited data available to prescribe landscape characteristics (topography, vegetation, soils, geology), and there is limited data available to evaluate the fidelity of process algorithms. These challenges have some urgency in Canada where warming is much larger than the global average and the changes in cold region hydrological processes are palpable. The long-term goal of this research is to substantially advance capabilities to simulate hydrological processes over continental domains. I will accomplish this long-term research strategy by implementing systematic approaches to model analysis and improvement that take advantage of both multiple hypothesis modeling tools as well as diagnostic model evaluation methods. I have three short-term objectives: Objective 1: Improve mechanistic model simulations of dominant hydrological processes in cold regions. To achieve this objective, I will improve algorithmic descriptions of cold region hydrological processes in the mechanistic multi-hypothesis SUMMA model (the Structure for Unifying Multiple Modeling Alternatives). Objective 2: Advance capabilities for process-based model evaluation and diagnostics. To achieve this objective, I will develop a multi-pronged model evaluation and benchmarking system, including (a) functional unit tests for land models, e.g., analytical solutions for idealized test cases, to ensure that the model equations are implemented correctly; (b) diagnostic tools for multiscale and multivariate model evaluation, extending capabilities in the international Land Model Benchmarking project (iLAMB); and (c) formal benchmarking methods to evaluate the information content in the model evaluation data. Objective 3: Evaluate the value of alternative parameterizations of hydrological processes of varying complexity. Building on the first two tasks, I will complete a set of structured model experiments to evaluate the value of alternative parameterizations of hydrological processes. I will systematically explore the complexity in process representation (process complexity) and the complexity in spatial discretization (spatial complexity), and evaluate how well alternative parameterizations represent dominant hydrologic processes across a myriad of spatial scales. This research will provide benefits for a range of societally-relevant applications, namely water security assessments and hydrological predictions, which can help increase societal resilience to climate variability and change.