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Estimated quantiles for the pour points of 9,203 level-12 hydrologic unit codes in the southeastern United States, 1950--2009

Metadata Updated: October 28, 2023

This page contains 15 estimated quantiles for 9,203 level-12 Hydrologic Unit Code in the Southeastern United States for the decades 1950-1959, 1960-1969, 1970-1979, 1980-1989, 1990-1999, and 2000-2009. A multi-output neural network was used to generate the estimated quantiles (Worland and others, 2019). The R scripts that generated the predictions are also included along with a README file. The 15 quantiles are associated with the following 15 non-exceedance probabilities (NEPs): 0.0003, 0.0050, 0.0500, 0.1000, 0.2000, 0.3000, 0.4000, 0.5000, 0.6000, 0.7000, 0.8000, 0.9000, 0.9500, 0.9950, and 0.9997. The quantiles were calculated using the Weibull plotting position (more details can be found in the accompanying manuscript). In addition to the median estimate of the quantiles, 68th, 95th, and 99.7th percentile intervals are also included in .csv file. The percentile intervals were estimated using Monte-Carlo dropout for 500 forward passes of the neural network. The intervals are represented in the .csv file as p0.0015, p0.0250, p0.1600, p0.5000, p0.8400, p0.975, and p0.9985 which indicates the 68th, 95th, and 99.7th percentile intervals. The median (p0.5000) and the mean estimate should be used if only a single realization of the estimated quantiles is needed. The neural network was trained using streamflow data at sites with records that contained only non-zero streamflow values. However, the model was used to make predictions for every HUC12 pour point. Some of these predictions are likely for sites that have streamflow values equal to zero. Worland, S. C., Steinschneider, S., Asquith, W., Knight, R. and Wieczorek, M., 2019, Prediction and inference of flow-duration curves using multi-output neural networks, Water Resources Research , submitted.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Created Date June 1, 2023
Metadata Updated Date October 28, 2023

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date June 1, 2023
Metadata Updated Date October 28, 2023
Publisher U.S. Geological Survey
Maintainer
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Identifier USGS:5c98bb40e4b0b8a7f6288b6f
Data Last Modified 20200821
Category geospatial
Public Access Level public
Bureau Code 010:12
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Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 66e922df-671e-4833-ac68-c1bef35ff05a
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -100.4667,26.7065,-81.5563,37.0458
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash 0eea5df1fee7a3afb6be6167f9f4e8437ad0a5871574e9a2d5870e80695f711a
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