Literature DB >> 34327039

Modeling the Effects of Future Hydroclimatic Conditions on Microbial Water Quality and Management Practices in Two Agricultural Watersheds.

R Coffey1, J Butcher2, B Benham3, T Johnson4.   

Abstract

Anticipated future hydroclimatic changes are expected to alter the transport and survival of fecally-sourced waterborne pathogens, presenting an increased risk of recreational water quality impairments. Managing future risk requires an understanding of interactions between fecal sources, hydroclimatic conditions and best management practices (BMPs) at spatial scales relevant to decision makers. In this study we used the Hydrologic Simulation Program FORTRAN to quantify potential fecal coliform (FC - an indicator of the potential presence of pathogens) responses to a range of mid-century climate scenarios and assess different BMP scenarios (based on reduction factors) for reducing the risk of water quality impairment in two, small agricultural watersheds - the Chippewa watershed in Minnesota, and the Tye watershed in Virginia. In each watershed, simulations show a wide range of FC responses, driven largely by variability in projected future precipitation. Wetter future conditions, which drive more transport from non-point sources (e.g. manure application, livestock grazing), show increases in FC loads. Loads typically decrease under drier futures; however, higher mean FC concentrations and more recreational water quality criteria exceedances occur, likely caused by reduced flow during low-flow periods. Median changes across the ensemble generally show increases in FC load. BMPs that focus on key fecal sources (e.g., runoff from pasture, livestock defecation in streams) within a watershed can mitigate the effects of hydroclimatic change on FC loads. However, more extensive BMP implementation or improved BMP efficiency (i.e., higher FC reductions) may be needed to fully offset increases in FC load and meet water quality goals, such as total maximum daily loads and recreational water quality standards. Strategies for managing climate risk should be flexible and to the extent possible include resilient BMPs that function as designed under a range of future conditions.

Entities:  

Keywords:  Climate; Management responses; Microbial water quality; Modeling; Watersheds

Year:  2020        PMID: 34327039      PMCID: PMC8318128          DOI: 10.13031/trans.13630

Source DB:  PubMed          Journal:  Trans ASABE        ISSN: 2151-0032            Impact factor:   1.188


  34 in total

1.  Meteorological effects on the levels of fecal indicator bacteria in an urban stream: a modeling approach.

Authors:  Kyung Hwa Cho; Sung Min Cha; Joo-Hyon Kang; Seung Won Lee; Yongeun Park; Jung-Woo Kim; Joon Ha Kim
Journal:  Water Res       Date:  2010-01-11       Impact factor: 11.236

2.  Linking watershed modeling and bacterial source tracking to better assess E. coli sources.

Authors:  Jaehak Jeong; Kevin Wagner; Jaime J Flores; Tim Cawthon; Younggu Her; Javier Osorio; Haw Yen
Journal:  Sci Total Environ       Date:  2018-08-07       Impact factor: 7.963

3.  Patterns of Host-Associated Fecal Indicators Driven by Hydrology, Precipitation, and Land Use Attributes in Great Lakes Watersheds.

Authors:  Deborah K Dila; Steven R Corsi; Peter L Lenaker; Austin K Baldwin; Melinda J Bootsma; Sandra L McLellan
Journal:  Environ Sci Technol       Date:  2018-09-27       Impact factor: 9.028

Review 4.  A review on effectiveness of best management practices in improving hydrology and water quality: Needs and opportunities.

Authors:  Yaoze Liu; Bernard A Engel; Dennis C Flanagan; Margaret W Gitau; Sara K McMillan; Indrajeet Chaubey
Journal:  Sci Total Environ       Date:  2017-05-31       Impact factor: 7.963

5.  Coupling a continuous watershed-scale microbial fate and transport model with a stochastic dose-response model to estimate risk of illness in an urban watershed.

Authors:  Hehuan Liao; Leigh-Anne H Krometis; Karen Kline
Journal:  Sci Total Environ       Date:  2016-02-19       Impact factor: 7.963

6.  The impact of socio-economic development and climate change on E. coli loads and concentrations in Kabul River, Pakistan.

Authors:  Muhammad Shahid Iqbal; M M Majedul Islam; Nynke Hofstra
Journal:  Sci Total Environ       Date:  2018-09-28       Impact factor: 7.963

7.  Modelling faecal indicator concentrations in large rural catchments using land use and topographic data.

Authors:  J Crowther; M D Wyer; M Bradford; D Kay; C A Francis
Journal:  J Appl Microbiol       Date:  2003       Impact factor: 3.772

8.  Faecal indicator organism inputs to watercourses from streamside pastures grazed by cattle: Before and after implementation of streambank fencing.

Authors:  David Kay; John Crowther; Carl M Stapleton; Mark D Wyer
Journal:  Water Res       Date:  2018-06-20       Impact factor: 11.236

9.  Explaining and modeling the concentration and loading of Escherichia coli in a stream-A case study.

Authors:  Chaozi Wang; Rebecca L Schneider; Jean-Yves Parlange; Helen E Dahlke; M Todd Walter
Journal:  Sci Total Environ       Date:  2018-04-25       Impact factor: 7.963

10.  Modeling Biphasic Environmental Decay of Pathogens and Implications for Risk Analysis.

Authors:  Andrew F Brouwer; Marisa C Eisenberg; Justin V Remais; Philip A Collender; Rafael Meza; Joseph N S Eisenberg
Journal:  Environ Sci Technol       Date:  2017-02-08       Impact factor: 9.028

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.