Data and scripts supporting Elkouk et al. (2024) "towards understanding parametric controls on runoff sensitivity to climate in the community land model: A Case study over the Colorado River Headwaters"
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| Owners: | Yadu Pokhrel |
| Type: | Resource |
| Storage: | The size of this resource is 103.6 MB |
| Created: | Feb 25, 2025 at 10:06 p.m. |
| Last updated: | Feb 25, 2025 at 10:47 p.m. |
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| Content types: | Multidimensional Content Multidimensional Content Multidimensional Content Multidimensional Content Multidimensional Content |
| Sharing Status: | Public |
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Abstract
Crucial to the assessment of future water security is how the land model component of Earth System Models partition precipitation into evapotranspiration and runoff, and the sensitivity of this partitioning to climate. This sensitivity is not explicitly constrained in land models nor the model parameters important for this sensitivity identified. Here, we seek to understand parametric controls on runoff sensitivity to precipitation and temperature in a state-of-the-science land model, the Community Land Model version 5 (CLM5). Process-parameter interactions underlying these two climate sensitivities are investigated using the sophisticated variance-based sensitivity analysis. This analysis focuses on three snow-dominated basins in the Colorado River headwaters region, a prominent exemplar where land models display a wide disparity in runoff sensitivities. Runoff sensitivities are dominated by indirect or interaction effects between a few parameters of subsurface, snow, and plant processes. A focus on only one kind of parameters would therefore limit the ability to constrain the others. Surface runoff exhibits strong sensitivity to parameters of snow and subsurface processes. Constraining snow simulations would require explicit representation of the spatial variability across large elevation gradients. Subsurface runoff and soil evaporation exhibit very similar sensitivities. Model calibration against the subsurface runoff flux would therefore constrain soil evaporation. The push toward a mechanistic treatment of processes in CLM5 have dampened the sensitivity of parameters compared to earlier model versions. A focus on the sensitive parameters and processes identified here can help characterize and reduce uncertainty in water resource sensitivity to climate change. (https://doi.org/10.1029/2024WR037718)
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| Start Date: | 10/01/1934 |
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| End Date: | 09/30/2010 |
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This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| U.S. National Science Foundation | Anthropogenic water management, Climate Change, and Environmental Sustainability in the Southwestern US (ACCESS) | 2103030 and 2103119 |
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This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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