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Unlocking Flow: An Investigation of topographical controls on Canadian river runoff

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Abstract:
Digital Elevation Models (DEMs) are a crucial tool for watershed analysis, offering valuable insights into landscape-scale hydrology. Traditional watershed delineations are derived by filling a DEM to force flow paths through topographic depressions, thus creating a continuous drainage network throughout the domain. However, this approach is challenged in landscapes characterized by abundant real-world depression storage, internally drained lake basins, and intermittently blocked stream channels such as the Canadian Shield (CS). The CS landscape is influenced by “fill-and-spill” surface water hydrology, with runoff flow paths controlled by bedrock sills and rocky cascades that are overtopped when water levels are high but cease flowing when water levels are low. To better represent this intermittently connected drainage pattern, we apply an alternative, less aggressive DEM filling model (Fill-Spill-Merge or FSM) to a continental-scale DEM (MERIT) for all of Canada. To ensure adequate filling of DEM errors while also preserving real-world topographic depressions, we propose a climatic method to initialize a key FSM parameter (“runoff depth”) that optimizes observed discharges from 1690 Environment and Climate Change Canada (ECCC) active gauging stations with climate model data. Our application of FSM to all 1690 gaugues identifies 255 topographical control points that can influence the actively flowing area of the watershed. Extending the approach to ungauged areas of the CS identifies 583 control points. This research demonstrates how CS watersheds are affected by fill-and-spill hydrology, emphasizing the critical role of accurrate terrain modeling for delineating surface water flow paths in depressional landscapes.
Notes:
Thesis (Sc. M.)--Brown University, 2023

Citation

Wagle, Nimisha, "Unlocking Flow: An Investigation of topographical controls on Canadian river runoff" (2023). Earth, Environmental and Planetary Sciences Theses and Dissertations. Brown Digital Repository. Brown University Library. https://repository.library.brown.edu/studio/item/bdr:7gtvpbpu/

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