Tag Results: Flow State DynamicsBack
A current challenge in ecohydrology is the incorporation of beaver dams into hydrological models. Select works have attempted to solve this problem using routing approaches, Manning coefficient variations, pond dynamics, or fully-distributed hydraulic models; however, all these approaches assume that all beaver dams are homogeneous structures and react in the same way to rainfall events. Recent findings highlight the importance of including the functional heterogeneity of beaver dams, especially the water path past the dam (dam flow state). To overcome the challenge of accounting for different dam flow states interrupting downstream water transmission in different ways, we developed BEAVERPY, a flow state-based Python package that can be coupled with the platform Cold Regions Hydrological Model (CRHM) to represent both streamflow modulation by ponds and dams, while also simulating infiltration and evapotranspiration. We used the broad-crested weir equation for the overflow dams, the Darcy equation for the seep flow dams, and the v-notch weir equation for the gapflow dams, verifying each case with synthetic experiments. To calibrate and validate the model, we instrumented the ponds and streams in a peatland fen in the Canadian Rocky Mountains in Alberta with level sensors and ‘DamCams’ (trail cameras) to capture flow type. Then, we used LIDAR DEM data and high-resolution imagery to delineate the hydrological response units. Each pond is represented as an HRU, which can interact with soil and routing modules. Finally, we conducted a scenario-testing experiment to understand the sensitivity of different beaver dam flow states for several storms. The results indicate the importance of including flow state dynamics for the beaver dam representations, and highlight the importance of integrating animal-ecological aspects into the streamflow modelling. This research has implications for understanding the use of beaver as a nature-based solution for flood mitigation and river restoration.