EGU22-10782
https://doi.org/10.5194/egusphere-egu22-10782
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Clustering fine-scale river network topologies for use in Earth system models

Laura Torres-Rojas1, Noemi Vergopolan2,3, Daniel Guyumus1, and Nathaniel W. Chaney1
Laura Torres-Rojas et al.
  • 1Duke University, Civil and Environmental Engineering, Durham, NC, United States of America (laura.torres@duke.edu)
  • 2Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States of America
  • 3NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States of America

Representing the physical heterogeneity of the land surface in Earth System Models (ESM) remains a persistent challenge due to its relevance to represent weather and climate dynamics and the hydrological cycle accurately. To address this challenge, the HydroBlocks Land Surface Model (LSM) [1] uses a hierarchical tiling scheme that defines its Hydrologic Response Units (HRUs) by clustering high-resolution global environmental data (e.g., 30-m land cover, topography, soil properties). The recently implemented reach-based routing scheme in HydroBlocks enables a two-way coupling between the high-resolution river network and the land HRUs. However, preliminary results show that the implementation is only computationally manageable for a limited number of river reaches (~5,000) per macroscale grid cell (1x1 arc degree). This hinders the scheme generalization and scalability over continental scales. As such, further simplification of the river network structure in routing schemes is required to ensure the feasibility of the approach in ESMs.

This presentation will explore simplification alternatives for river network topologies using clustering analysis. Initially, given that a significant fraction of the total river reaches on any domain are first-order, we propose an approach that clusters these streams based on average basins’ physical and environmental features (e.g., slope, upslope contributing area, aspect, average precipitation, and land cover), and channels’ geometry. The river network topology is simplified by depicting all the clusters’ members as single equivalent channels. The clustering is performed using K-means, and the number of clusters depends on a maximum target number of reaches required to provide computational tractability. Although useful, this approach will not be enough to sufficiently reduce the computational burden, for which solving the second- and even third-order reaches remain a substantial load. Therefore, the second approach relies on clustering the river channel structure over sets of interconnected reaches (i.e., topologies including first-, second-, and third-order streams). The performance of the proposed approach will be compared to the original HydroBlocks implementation for the temporal evolution of the streamflow, inundation height and the resulting computation times.

 

[1]      N. W. Chaney, L. Torres-Rojas, N. Vergopolan, and C. K. Fisher, “HydroBlocks v0.2: enabling a field-scale two-way coupling between the land surface and river networks in Earth system models,” Geosci. Model Dev., vol. 14, no. 11, pp. 6813–6832, Nov. 2021, doi: 10.5194/gmd-14-6813-2021.

How to cite: Torres-Rojas, L., Vergopolan, N., Guyumus, D., and Chaney, N. W.: Clustering fine-scale river network topologies for use in Earth system models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10782, https://doi.org/10.5194/egusphere-egu22-10782, 2022.

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