A Web-Based Tool to Estimate Pollutant Loading Using LOADEST

Water

Youn Shik Park²  Bernie A. Engel¹  Jane Frankenberger¹  Hasun Hwang³ 

[1] Department of Agricultural and Biological Engineering, Purdue University, 225 South University Street, West Lafayette, IN 47907-2093, USA; E-Mails:;Department of Rural Construction Engineering, Kongju National University, 54 Daehak-ro, Yesan-gun, Chungcheongnam-do 32439, Korea;National Institute of Environmental Research, 42 Hwankyoung-ro Seo-gu Incheon 404-708, Korea; E-Mail:

关键词: LOADEST;    pollutant load;    regression model;    web-based tool;   

DOI  :  10.3390/w7094858

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.