The sensitivity of simulated streamflow to individual hydrologic processes across North America. Mai, J., Craig, J. R., Tolson, B. A., & Arsenault, R. Nature Communications, 13(1):455, January, 2022. Number: 1 Publisher: Nature Publishing Group![The sensitivity of simulated streamflow to individual hydrologic processes across North America [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Streamflow sensitivity to different hydrologic processes varies in both space and time. This sensitivity is traditionally evaluated for the parameters specific to a given hydrologic model simulating streamflow. In this study, we apply a novel analysis over more than 3000 basins across North America considering a blended hydrologic model structure, which includes not only parametric, but also structural uncertainties. This enables seamless quantification of model process sensitivities and parameter sensitivities across a continuous set of models. It also leads to high-level conclusions about the importance of water cycle components on streamflow predictions, such as quickflow being the most sensitive process for streamflow simulations across the North American continent. The results of the 3000 basins are used to derive an approximation of sensitivities based on physiographic and climatologic data without the need to perform expensive sensitivity analyses. Detailed spatio-temporal inputs and results are shared through an interactive website.
@article{mai_sensitivity_2022,
title = {The sensitivity of simulated streamflow to individual hydrologic processes across {North} {America}},
volume = {13},
copyright = {2022 The Author(s)},
issn = {2041-1723},
url = {https://www.nature.com/articles/s41467-022-28010-7},
doi = {10.1038/s41467-022-28010-7},
abstract = {Streamflow sensitivity to different hydrologic processes varies in both space and time. This sensitivity is traditionally evaluated for the parameters specific to a given hydrologic model simulating streamflow. In this study, we apply a novel analysis over more than 3000 basins across North America considering a blended hydrologic model structure, which includes not only parametric, but also structural uncertainties. This enables seamless quantification of model process sensitivities and parameter sensitivities across a continuous set of models. It also leads to high-level conclusions about the importance of water cycle components on streamflow predictions, such as quickflow being the most sensitive process for streamflow simulations across the North American continent. The results of the 3000 basins are used to derive an approximation of sensitivities based on physiographic and climatologic data without the need to perform expensive sensitivity analyses. Detailed spatio-temporal inputs and results are shared through an interactive website.},
language = {en},
number = {1},
urldate = {2023-06-14},
journal = {Nature Communications},
author = {Mai, Juliane and Craig, James R. and Tolson, Bryan A. and Arsenault, Richard},
month = jan,
year = {2022},
note = {Number: 1
Publisher: Nature Publishing Group},
keywords = {NALCMS},
pages = {455},
}
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