@inproceedings{a1c98532e63a422ea235cf5c351e38b4,
title = "Empirical flow parameters: A tool for hydraulic model screening",
abstract = "Conditional distributions constructed from an extensive database are presented as an alternative to regression equations to estimate mean section velocity or other selected hydraulic parameters for storm flows or other conditional discharges at un-gauged locations. Illustrative examples are presented showing how to generate the distributions in the R programming environment and represent them as graphs, tables, or quantile functions. A particularly powerful feature of R as the tool to access the database is the ability to rapidly construct conditional distributions, where the distributional information is conditioned on some other criteria in the database. Conditioning addresses considerations such as the 95th percentile discharge from all observations being far less meaningful than the 95th percentile discharge for observations from drainage areas less than 40 square miles (Discharge conditioned on drainage area). Several other conditioning examples are presented. The use of the tool as a screening instrument for hydraulic modeling is discussed.",
author = "Cleveland, {Theodore G.} and Neale, {Caroline M.} and Tay, {Cristal C.} and Herrmann, {George R.}",
year = "2015",
doi = "10.1061/9780784479162.250",
language = "English",
series = "World Environmental and Water Resources Congress 2015: Floods, Droughts, and Ecosystems - Proceedings of the 2015 World Environmental and Water Resources Congress",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "2549--2557",
editor = "Webster, {Veronica L.} and Karen Karvazy",
booktitle = "World Environmental and Water Resources Congress 2015",
note = "null ; Conference date: 17-05-2015 Through 21-05-2015",
}