Precision of headwater stream permanence estimates from a monthly water balance model in the Pacific Northwest, USA
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Abstract
Stream permanence classifications (i.e., perennial, intermittent, ephemeral) are a primary consideration to determine stream regulatory status in the United States (U.S.) and are an important indicator of environmental conditions and biodiversity. However, at present, no models or products adequately describe surface water presence for regulatory determinations. We modified the Thornthwaite monthly water balance model (MWBM) with a flow threshold parameter to estimate flow permanence and evaluated the model’s accuracy and precision for more than 1.3 million headwater stream reaches in the U.S. Pacific Northwest (PNW). Stream reaches were assigned to one of eight calibration groups by unsupervised classification based on sensitivity to MWBM parameters. Suitable MWBM parameter sets were identified by comparing modeled stream permanence estimates to surface water presence observations (SWPO). Parameter sets with accuracies > 65% were considered suitable. The MWBM estimated stream permanence with high precision at 40% of reaches, with poor precision at 20% of reaches, and no suitable parameter sets were identified for 40% of reaches. Results highlight the need for increased SWPO collection to improve calibration and assessment of stream permanence models. Additionally, implementation of the MWBM to estimate surface water presence indicates potential for process-based models to predict stream permanence with future development.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Precision of headwater stream permanence estimates from a monthly water balance model in the Pacific Northwest, USA |
| Series title | Water |
| DOI | 10.3390/w14060895 |
| Volume | 14 |
| Issue | 6 |
| Year Published | 2022 |
| Language | English |
| Publisher | Multidisciplinary Digital Publishing Institute |
| Contributing office(s) | Idaho Water Science Center, National Geospatial Program, Northern Rocky Mountain Science Center, Advanced Research Computing (ARC) |
| Description | 895, 21 p. |
| Country | United States |
| State | California, Idaho, Montana, Nevada, Oregon, Utah, Washington, Wyoming |
| Other Geospatial | Pacific Northwest |
| Google Analytic Metrics | Metrics page |