Using Sporadic Streamflow Measurements to Improve and Evaluate a Streamflow Model in Ungauged Basins in Wisconsin
Publication: Journal of Hydrologic Engineering
Volume 27, Issue 4
Abstract
Streamflows derived from hydrological models are widely used in decision-making processes in a broad array of natural resources applications. There remain substantial challenges in quantifying error and uncertainty in hydrological models, but understanding the sources and magnitudes of error and uncertainty are essential to support robust decision making. In this study, the accuracy of a mixed-effects model for streamflow (flow-duration curves) across the state of Wisconsin, the Natural Community Model (NCM), was evaluated. The NCM is used as the basis for scientific studies and management decisions in Wisconsin, but uncertainty in the NCM has not yet been quantified, and performance has not been assessed formally except at continuously monitored streamflow stations. Although there are a couple hundred long-term monitoring stations, there are thousands of short-term and sporadic monitoring stations in Wisconsin. To take advantage of the vast number of sparsely monitored and short-term stations, an index gauge approach was used to estimate long-term streamflow percentiles and flow-duration curves (with uncertainty). These flow-duration targets formed the basis for an assessment of NCM accuracy in ungauged streams. A random forest model for NCM error was developed that provides a qualitative understanding of sources of error in the NCM as well as a quantitative way to correct the NCM using information from the sporadic/short-term streamflow stations that could not be included in the original NCM training set. By combining the original NCM and the random forest model, an updated NCM was produced with reduced error (75th percentile of errors dropped from 0.23 to ), and uncertainty estimates were defined for use with the updated NCM in decision making and research applications.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available in a repository online in accordance with funder data retention policies. Code and data used to generate the results in this study can be found at https://doi.org/10.4211/hs.1d78d40efa2844cb9db2c19b67be464d (Lapides 2021). Some data are private and available upon request from the Wisconsin Department of Natural Resources ([email protected]). See https://dnr.wisconsin.gov/topic/WaterUse/data.htmlforadditionaldetails.
Acknowledgments
I want to thank Adam Freihoefer, Alex Latzka, Aaron Pruitt, Rachel Greve, Aaron Fisch, and Bryan M. Maitland for useful discussions and assistance with data access and standardization and the Water Use Section at the Wisconsin Department of Natural Resources and Anneliese Sytsma for feedback on early drafts. This work was funded by the Wisconsin Department of Natural Resources and administered by the University of Wisconsin Water Resources Institute.
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Journal of Hydrologic Engineering
Volume 27 • Issue 4 • April 2022
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© 2022 American Society of Civil Engineers.
History
Received: Jul 13, 2021
Accepted: Dec 2, 2021
Published online: Feb 15, 2022
Published in print: Apr 1, 2022
Discussion open until: Jul 15, 2022
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