Modeling seasonal variability of fecal coliform in natural surface waters using the modified SWAT

JOURNAL OF HYDROLOGY

卷:535

Article

Cho, Kyung Hwa¹  Pachepsky, Yakov A.²  Kim, Minjeong¹  Pyo, JongCheol¹  Park, Mi-Hyun³  Kim, Young Mo⁴  Kim, Jung-Woo⁵  Kim, Joon Ha⁴ 

[1] Ulsan Natl Inst Sci & Technol, Sch Urban & Environm Engn, Ulsan 689798, South Korea

[2] USDA ARS, Environm Microbial & Food Safety Lab, 10300 Baltimore Ave,Bldg 173,BARC East, Beltsville, MD 20705 USA

[3] Univ Massachusetts, Dept Civil & Environm Engn, 130 Nat Resources Rd, Amherst, MA 01003 USA

[4] Gwangju Inst Sci & Technol, Sch Environm Sci & Engn, 261 Cheomdan Gwagiro, Gwangju 500712, South Korea

[5] Korea Atom Energy Res Inst, Radioact Waste Technol Dev Div, 1045 Daedeok Daero, Daejeon 305353, South Korea

关键词: Soil and water assessment tool;    Fecal contamination;    Surface water;    Bacterial water quality;   

DOI  :  10.1016/j.jhydrol.2016.01.084

来源: Elsevier

【 摘 要 】

Fecal coliforms are indicators of pathogens and thereby, understanding of their fate and transport in surface waters is important to protect drinking water sources and public health. We compiled fecal coliform observations from four different sites in the USA and Korea and found a seasonal variability with a significant connection to temperature levels. In all observations, fecal coliform concentrations were relatively higher in summer and lower during the winter season. This could be explained by the seasonal dominance of growth or die-off of bacteria in soil and in-stream. Existing hydrologic models, however, have limitations in simulating the seasonal variability of fecal coliform. Soil and in-stream bacterial modules of the Soil and Water Assessment Tool (SWAT) model are oversimplified in that they exclude simulations of alternating bacterial growth. This study develops a new bacteria subroutine for the SWAT in an attempt to improve its prediction accuracy. We introduced critical temperatures as a parameter to simulate the onset of bacterial growth/die-off and to reproduce the seasonal variability of bacteria. The module developed in this study will improve modeling for environmental management schemes. (C) 2016 Elsevier B.V. All rights reserved.

【 授权许可】

Free