Application of hierarchical Bayesian methods to a spatially explicit model of long-term mean annual streamflow for the conterminous United States
Description
The data release documents the application of hierarchical Bayesian
methods to a previously developed hybrid (statistical-mechanistic)
SPARROW (SPAtially Referenced Regression On Watershed attributes)
model of long-term mean annual streamflow for streams and rivers of
conterminous United States. The performance and interpretability of
three models were evaluated. The models included a non-hierarchical
baseline model with spatially constant coefficients and model error
variance, and two hierarchical models with regionally varying coefficients
and model error variances, as described in the journal article
(see Table 2; https://doi.org/10.1029/2019WR025037). An R script is provided
that allows users to execute the three models.
Resources
| Name |
Format |
Description |
Link |
|
55 |
Landing page for access to the data |
https://doi.org/10.5066/P9JSVCZX |
|
55 |
The metadata original format |
https://data.usgs.gov/datacatalog/metadata/USGS.19b9b62c-5655-4fd5-9050-78fbb020dc8a.xml |
Tags
- environment
- groundwater-and-surface-water-interaction
- surfacewater-model
- surfacewater
- usgs-19b9b62c-5655-4fd5-9050-78fbb020dc8a
- geoscientificinformation
- inlandwaters
- usgssurfacewatermodel
- sparrow