Abstract
Recreational fishing is a popular activity in many urbanized watersheds. When river water is incidentally ingested during fishing sessions, substantial waterborne fecal contamination can cause adverse health effects. This study aims to spatially map health risks for recreational fishers caused by waterborne Escherichia coli (E. coli) in the highly urbanized Tamsui River watershed. First, indicator kriging was used to probabilistically estimate the distributions of waterborne E. coli and determine the conditional cumulative distribution function (CCDF). Subsequently, to propagate the parameter variability, Monte Carlo simulation was adopted to characterize the ingestion rate and exposure duration for recreational fishers and E. coli realizations were generated using random fields on the basis of the estimated CCDF. Finally, after the three parameters were combined, the approximate beta-Poisson dose–response function was employed to quantitatively determine potential risks to recreational fishers in the Tamsui River and its tributaries. The analysis results revealed that the risks of recreational fishing exceed an acceptable level of 8 infections per 1000 fishers per day at several urban river courses. Therefore, recreational fishing activities in urban riverbanks pose a substantial health threat. Recreational fishing in urban riverbanks should be limited before the construction of complete sanitary sewer systems. The river mouth and certain upstream river sections are suitable for the development of recreational fishing.
Similar content being viewed by others
References
Aminu M, Matori A, Yusof KW, Malakahmad A, Zainol RB (2015) A GIS-based water quality model for sustainable tourism planning of Bertam River in Cameron Highlands, Malaysia. Environ Earth Sci 73(10):6525–6537
Benke KK, Hamilton AJ (2008) Quantitative microbial risk assessment: uncertainty and measures of central tendency for skewed distributions. Stoch Environ Res Risk Assess 22(4):533–539
Brown TC, Taylor JG, Shelby B (1991) Assessing the direct effects of streamflow on recreation: a literature review. Water Resour Bull 27(6):979–989
Cambardella CA, Moorman TB, Parkin TB, Karlen DL, Novak JM, Turco RF, Konopka AE (1994) Field-scale variability of soil properties in central Iowa soils. Soil Sci Soc Am J 58:1501–1511
Chen YC, Yeh HC, Wei C (2012) Estimation of river pollution index in a tidal stream using kriging analysis. Int J Environ Res Public Health 9(9):3085–3100
Chen SK, Jang CS, Peng YH (2013) Developing a probability-based model of aquifer vulnerability in an agricultural region. J Hydrol 486:494–504
Cheng BY, Liu TC, Shyu GS, Chang TK, Fang WT (2011) Analysis of trends in water quality: constructed wetlands in metropolitan Taipei. Water Sci Technol 64(11):2143–2150
Chica-Olmo M, Luque-Espinar JA, Rodriguez-Galiano V, Pardo-Igúzquiza E, Chica-Rivas L (2014) Categorical indicator kriging for assessing the risk of groundwater nitrate pollution: the case of Vega de Granada aquifer (SE Spain). Sci Total Environ 470–471:229–239
Chigor VN, Sibanda T, Okoh AI (2014) Assessment of the risks for human health of adenoviruses, hepatitis A virus, rotaviruses and enteroviruses in the Buffalo River and three source water dams in the Eastern Cape. Food Environ Virol 6:87–98
Cressie N, Frey J, Harch B, Smith M (2006) Spatial prediction on a river network. J Agric Biol Environ Stat 11(2):127–150
Deutsch CV, Journel AG (1998) GSLIB: geostatistical software library and user’s guide, 2nd edn. Oxford University Press, New York
Donovan E, Unice K, Roberts JD, Harris M, Finley B (2008) Risk of gastrointestinal disease associated with exposure to pathogens in the water of the Lower Passaic River. Appl Environ Microbiol 74(4):994–1003
El-Ayouti A, Abou-Ali H (2013) Spatial heterogeneity of the Nile water quality in Egypt. J Environ Stat 4(8):1–12
Gerba CP, Rose JB, Haas CN, Crabtree KD (1996) Waterborne rotavirus: a risk assessment. Water Res 30(12):2929–2940
Goovaerts P (1997) Geostatistics for natural resources evaluation. Oxford University Press, New York, pp 259–368
Goovaerts P, Semrau J, Lontoh S (2001) Monte Carlo analysis of uncertainty attached to microbial pollutant degradation rates. Environ Sci Technol 35:3924–3930
Goovaerts P, AvRuskin G, Meliker J, Slotnick M, Jacquez G, Nriagu J (2005) Geostatistical modeling of the spatial variability of arsenic in groundwater of southeast Michigan. Water Resour Res. doi:10.1029/2004WR003705
Haas CN (2015) Microbial dose response modeling: past, present, and future. Environ Sci Technol 49(3):1245–1259
Haas CN, Thayyar-Madabusi A, Rose JB, Gerba CP (2000) Development of a dose-response relationship for Escherichia coli O157:H7. Int J Food Microbiol 1748:153–159
Haas CN, Rose JB, Gerba CP (2014) Quantitative microbial risk assessment, 2nd edn. Wiley, New York, pp 72–73
Health Canada (2012) Guidelines for Canadian recreational water quality, 3rd edn. Water, Air and Climate Change Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, p 26
Hoef JM, Peterson EE, Theobold D (2006) Spatial statistical models that use flow and stream distance. Environ Ecol Stat 13:449–464
Holtcamp W (2012) In the same boat? Health risks of water recreation are not limited to full-contact activities. Environ Health Perspect 120(2):a77
Jang CS (2016) Using probability-based spatial estimation of the river pollution index to assess urban water recreational quality in the Tamsui River watershed. Environ Monit Assess 188(36):1–17
Jang CS, Liu CW, Lin KH, Huang FM, Wang SW (2006) Spatial analysis of potential carcinogenic risks associated with ingesting arsenic in aquacultural tilapia (Oreochromis mossambicus) in blackfoot disease hyperendemic areas. Environ Sci Technol 40:1707–1713
Jang CS, Liang CP, Wang SW (2013) Integrating the spatial variability of water quality and quantity to probabilistically assess groundwater sustainability for use in aquaculture. Stoch Environ Res Risk Assess 27:1281–1291
Juang KW, Lee DY (1998) Simple indicator Kriging for estimating the probability of incorrectly delineating hazardous areas in a contaminated site. Environ Sci Technol 32:2487–2493
Lee JJ, Jang CS, Wang SW, Liu CW (2007) Evaluation of potential health risk of arsenic-affected groundwater using indicator kriging and dose-response model. Sci Total Environ 384:151–162
Liao YL, Ma HW, Tsai MX, Shi XJ, Yang WL, Lou YQ, Lin SR, Yu JJ, Huang IL, Yeh YB (2011) Project of risk assessment of water recreational activities in the Tamsui River watershed. Environmental Protection Bureau, New Taipei City Government, Taiwan, Appendix pp A-4
Money ES, Carter GP, Serre ML (2008) Improving the assessment of E. coli exposure levels along un-monitored stream reaches. Epidemiology 19(6):S162–S163
Money ES, Carter GP, Serre ML (2009) Modern space/time geostatistics using river distances: data integration of turbidity and E. coli measurements to assess fecal contamination along the Raritan River in New Jersey. Environ Sci Technol 43:3736–3742
Omran EE (2012) A proposed model to assess and map irrigation water well suitability using geospatial analysis. Water 4(3):545–567
Palisade Corporation (2015) @Risk: risk analysis using Monte Carlo simulation. Palisade Corporation, New York. http://www.palisade.com/risk/
Peterson EE, Urquhart NS (2006) Predicting water quality impaired stream segments using landscape-scale data and a regional geostatistical model: a case study in Maryland. Environ Monit Assess 121:613–636
Peterson EE, Merton AA, Theobald DM, Urquhart NS (2006) Patterns in spatial autocorrelation in stream water chemistry. Environ Monit Assess 121:569–594
Rijal G, Tolson JK, Petropoulou C, Granato TC, Glymph A, Gerba C, Deflaun MF, O’Connor C, Kollias L, Lanyon R (2011) Microbial risk assessment for recreational use of the Chicago Area Waterway System. J Water Health 9(1):169–186
Soller JA, Schoen ME, Bartrand T, Ravenscroft JE, Ashbolt NJ (2010) Estimated human health risks from exposure to recreational waters impacted by human and non-human sources of faecal contamination. Water Res 44(16):4674–4691
Steyn M, Jagals P, Genthe B (2004) Assessment of microbial infection risks posed by ingestion of water during domestic water use and full-contact recreation in a mid-southern African region. Water Sci Technol 50(1):301–308
Sunger N, Haas CN (2015) Quantitative microbial risk assessment for recreational exposure to water bodies in Philadelphia. Water Environ Res 87(3):211–222
Taiwan Central Weather Bureau (2015) Internet application of climate data. Central Weather Bureau, Ministry of Transportation and Communications, Executive Yuan, Taiwan. http://e-service.cwb.gov.tw/wdps/index_net.jsp
Taiwan Environmental Protection Administration (Taiwan EPA) (2015) Environmental water quality information. Environmental Protection Administration, Executive Yuan, Taiwan. http://wq.epa.gov.tw/WQEPA/Code/?Languages=en
Taiwan Water Resources Agency (2015) Application network of hydrological data. Water Resources Agency, Ministry of Economic Affairs, Executive Yuan, Taiwan. http://gweb.wra.gov.tw/HydroApplication/index.aspx
Till D, McBride G, Ball A, Taylor K, Pyle E (2008) Large-scale freshwater microbiological study: rationale, results and risks. J Water Health 6(4):443–460
Tseng LY, Jiang SC (2012) Comparison of recreational health risks associated with surfing and swimming in dry weather and post-storm conditions at Southern California beaches using quantitative microbial risk assessment (QMRA). Mar Pollut Bull 64(5):912–918
U.S. Environmental Protection Agency (U.S. EPA) (1986) Ambient water quality criteria for bacteria—1986. EPA 440-5-84-002. U.S. Environmental Protection Agency, Washington, DC, pp 15
U.S. Environmental Protection Agency (U.S. EPA) (2001) Risk assessment guidance for superfund (RAGS) volume III—part A: process for conducting probabilistic risk assessment. Office of Emergency and Remedial Response, U.S. Environmental Protection Agency Washington, DC, pp 3-1–3-27
U.S. Environmental Protection Agency (U.S. EPA) (2002) Implementation guidance for ambient water quality criteria for bacteria. Office of Water, U.S. Environmental Protection Agency, Washington, DC, (EPA-823-B-02-003) pp 7–9
U.S. Environmental Protection Agency (U.S. EPA) (2007) Report of the experts scientific workshop on critical research needs for the development of new or revised recreational water quality criteria. Office of Water, Office of Research and Development, U.S. Environmental Protection Agency, Washington, DC, (EPA 823-R-07-006) pp 13–20
U.S. Environmental Protection Agency (U.S. EPA) (2012) Recreational water quality criteria. Office of Water, United States Environmental Protection Agency, Washington, DC, (EPA-820-F-12-058), pp 14
U.S. Environmental Protection Agency (U.S. EPA) (2014) Microbiological risk assessment (MRA) tools, methods, and approaches for water media. Office of Science and Technology Office of Water U.S. Environmental Protection Agency Washington, DC, (EPA-820-R-14-009) pp 90–94 and pp 104–110
Wang YB, Liu CW, Liao PY, Lee JJ (2014) Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters. Environ Monit Assess 186(3):1781–1792
World Health Organization (WHO) (2003) Guidelines for safe recreational water environments. Coastal and fresh waters, vol 1. World Health Organization, Geneva, pp 82–87
Acknowledgements
The authors would like to thank the Taiwan Environmental Protection Administration and the New Taipei City Government generously supporting the data on E. coli and the exposure duration for recreational fishers, respectively, in the Tamsui River watershed, and the Taiwan Ministry of Science and Technology for financially supporting this research under Contract Nos. MOST 104-2410-H-424-014 and MOST 105-2410-H-424-015.
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Jang, CS., Chen, SK. Establishing a spatial map of health risk assessment for recreational fishing in a highly urbanized watershed. Stoch Environ Res Risk Assess 32, 685–699 (2018). https://doi.org/10.1007/s00477-017-1380-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00477-017-1380-5