Advances in Quantifying Streamflow Variability Across Continental Scales: 2. Improved Model Regionalization and Prediction Uncertainties Using Hierarchical Bayesian Methods-Reference-Cited by-同舟云学术

Advances in Quantifying Streamflow Variability Across Continental Scales: 2. Improved Model Regionalization and Prediction Uncertainties Using Hierarchical Bayesian Methods

Published:2019-12 Issue:12 Volume:55 Page:11061-11087
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resour. Res.

Author:

Alexander Richard B.¹^ORCID,Schwarz Gregory E.¹^ORCID,Boyer Elizabeth W.²^ORCID

Affiliation:

1. U.S. Geological Survey Reston VA USA

2. Department of Ecosystem Science and Management Pennsylvania State University PA USA

Funder

U.S. Geological Survey

Pennsylvania State University

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2019WR025037

Reference74 articles.

1. An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction

2. Alexander R. B. &Schwarz G.E.(2019).Application of hierarchical Bayesian methods to a spatially explicit model of long‐term mean annual streamflow for the conterminous United States [Software release]. U.S. Geological Survey.https://doi.org/10.5066/P9JSVCZX

3. Advances in quantifying streamflow variability across continental scales: 1. Identifying natural and anthropogenic controlling factors in the USA using a spatially explicit modeling method;Alexander R. B.;Water Resources Research,2019

4. Effect of stream channel size on the delivery of nitrogen to the Gulf of Mexico

5. Differences in Phosphorus and Nitrogen Delivery to The Gulf of Mexico from the Mississippi River Basin

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