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Water 2015, 7(9), 4858-4868; doi:10.3390/w7094858

A Web-Based Tool to Estimate Pollutant Loading Using LOADEST

1
Department of Rural Construction Engineering, Kongju National University, 54 Daehak-ro, Yesan-gun, Chungcheongnam-do 32439, Korea
2
Department of Agricultural and Biological Engineering, Purdue University, 225 South University Street, West Lafayette, IN 47907-2093, USA
3
National Institute of Environmental Research, 42 Hwankyoung-ro Seo-gu Incheon 404-708, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Miklas Scholz
Received: 22 July 2015 / Revised: 26 August 2015 / Accepted: 2 September 2015 / Published: 8 September 2015
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Abstract

Collecting and analyzing water quality samples is costly and typically requires significant effort compared to streamflow data, thus water quality data are typically collected at a low frequency. Regression models, identifying a relationship between streamflow and water quality data, are often used to estimate pollutant loads. A web-based tool using LOAD ESTimator (LOADEST) as a core engine with four modules was developed to provide user-friendly interfaces and input data collection via web access. The first module requests and receives streamflow and water quality data from the U.S. Geological Survey. The second module retrieves watershed area for computation of pollutant loads per unit area. The third module examines potential error of input datasets for LOADEST runs, and the last module computes estimated and allowable annual average pollutant loads and provides tabular and graphical LOADEST outputs. The web-based tool was applied to two watersheds in this study, one agriculturally-dominated and one urban-dominated. It was found that annual sediment load at the urban-dominant watershed exceeded the target load; therefore, the web-based tool identified correctly the watershed requiring best management practices to reduce pollutant loads. View Full-Text
Keywords: LOADEST; pollutant load; regression model; web-based tool LOADEST; pollutant load; regression model; web-based tool
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Park, Y.S.; Engel, B.A.; Frankenberger, J.; Hwang, H. A Web-Based Tool to Estimate Pollutant Loading Using LOADEST. Water 2015, 7, 4858-4868.

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