Evaluating the Trend and Extreme Values of Faecal Indicator Organisms in a Raw Water Source: A Potential Approach for Watershed Management and Optimizing Water Treatment Practice
Tóm tắt
This study demonstrates the use of microbial load time series, through trend and extreme event analysis, to evaluate the effectiveness of watershed management strategies and to understand the probabilistic behaviour of extreme events. Heterotrophic plate count (HPC), Clostridium perfringens, intestinal enterococci, Escherichia coli, and coliform bacteria, were monitored from 1999 to 2012 at Nedre Romerike Vannverk (NRV) drinking water treatment plant, which takes its source water from Glomma River, Norway. Mann-Kendall test, Seasonal Mann-Kendall test, and Sen’s Slope Estimator were used for trend analysis over years and also seasonal trends were examined through linear regression. Mann-Kendall test results show a decreasing trend for all indicator microorganisms except Escherichia coli. Seasonal trend analysis results also indicate that Clostridium perfringens during autumn and intestinal enterococci during spring have a significantly decreasing trend. An increasing trend was observed for all pathogens during the summer season. Trend analysis results offer insights and crucial perspective for policy makers and planners to evaluate the existing watershed management strategies. Moreover, extreme microbial load events in the raw water was analysed using the POT method to estimate return levels of extreme indicator microbial load corresponding to selected return periods. It is of importance to calculate the return period of extreme microbial load events for the purpose of designing optimal pathogen barriers and performing risk analysis.
Tài liệu tham khảo
Abaurrea J, Asin J, Cebrian AC, Garcia-Vera MA (2011) Trend analysis of water quality series based on regression models with correlated errors. J Hydrol 400(3-4):341–352. doi:10.1016/j.jhydrol.2011.01.049
Antonopoulos VZ, Papamichail DM, Mitsiou KA (2001) Statistical and trend analysis of water quality and quantity data for the Strymon River in Greece. Hydrol Earth Syst Sci 5(4):679–691
Castillo E, Hadi AS (1997) Fitting the generalized Pareto distribution to data. J Am Stat Assoc 92(440):1609–1620
Deoliveira JT (1988) Stochastic-processes of extremes - definitions and statistics. Adv Appl Probab 20(1):7
El-Aroui M-A, Diebolt J (2002) On the use of the peaks over thresholds method for estimating out-of-sample quantiles. Comput Stat Data An 39(4):453–475. doi:10.1016/S0167-9473(01)00087-1
Embrechts P, Klüppelberg C, Mikosch T (1997) Modelling extremal events: for insurance and finance. Springer, Berlin, pp 283–358
Ercelebi SG, Toros H (2009) Extreme value analysis of Istanbul air pollution data. Clean-Soil Air Water 37(2):122–131
Falk M, Guillou A (2008) Peaks-over-threshold stability of multivariate generalized Pareto distributions. J Multivar Anal 99(4):715–734
Freudenthal AM (1976) Extreme value risk analysis in structural design of reactor components. Nucl Eng Des 37(1):179–181
Gilbert RO (1987) Statistical Methods for Environmental Pollution Monitoring. Wiley, New York, pp 204–252
Grizzetti B. BF, Bianchi M., Barkved L., Berge D., Campbell D., Dan Kim N., Gooch G., Lana Renoult N., Nesheim I., Machado M., Manasi S., Rieu-Clarke A., Stålnacke, P. and Tjomsland T. (2007) Managing data in Integrated Water Resources Management projects: the STRIVER case. European Commission Joint Research Center. Institute for Environment and Sustainability. Rural, Water and Ecosystem Resources Unit (JRC-EC). doi:http://kvina.niva.no/striver/Portals/0/documents/STRIVER_D21.pdf
Hadas O, Corradini MG, Peleg M (2004) Statistical analysis of the fluctuating counts of fecal bacteria in the water of Lake Kinneret. Water Res 38(1):79–88. doi:10.1016/j.watres.2003.09.004
Hait JR, Schektman Y (1980) Characterization of principal directions and components in principal components analysis (PCA) - similar components analysis. Biometrics 36(2):368–368
Heffernan JE (2012) An Introduction to Statistical Modeling of Extreme Values. Package ‘ismev’. http://cran.r-project.org/web/packages/ismev/ismev.pdf.
Helsel DR, Hirsch RM (2002) Statistical Methods in Water Resources. In: Techniques of Water Resources Investigations, vol Book 4. vol chapter A3. U.S. Geological Survey, p 522
Hirsch RM, Slack JR, Smith RA (1982) Techniques of trend analysis for monthly water-quality data. Water Resour Res 18(1):107–121. doi:10.1029/Wr018i001p00107
Hosking JRM, Wallis JR (1987) Parameter and quantile estimation for the generalized Pareto distribution. Technometrics 29(3):339–349. doi:10.2307/1269343
Huang YL, Batterman S (2003) An extreme value analysis of pollutant concentrations in surface soils due to atmospheric deposition. Hum Ecol Risk Assess 9(7):1729–1746
Iii JP (1975) Statistical inference using extreme order statistics. Ann Stat 3(1):119–131. doi:10.2307/2958083
Jiang YY, Zhuang QL (2011) Extreme value analysis of wildfires in Canadian boreal forest ecosystems. Can J Forest Res 41(9):1836–1851
Kasperski M, Hoxey R (2008) Extreme-value analysis for observed peak pressures on the Silsoe cube. J Wind Eng Ind Aerod 96(6–7):994–1002
Katz RW, Parlange MB, Naveau P (2002) Statistics of extremes in hydrology. Adv Water Resour 25(8–12):1287–1304
Klugman S (1997) Practical analysis of extreme values. Insur Math Econ 21(1):91–92. doi:10.1016/S0167-6687(97)00022-X
Konecny F, Nachtnebel HP (1985) Extreme value processes and the evaluation of risk in flood analysis. Appl Math Model 9(1):11–15
Kuchenhoff H, Thamerus M (1996) Extreme value analysis of Munich air pollution data. Environ Ecol Stat 3(2):127–141
Lang M, Ouarda TBMJ, Bobee B (1999) Towards operational guidelines for over-threshold modeling. J Hydrol 225(3–4):103–117
Leadbetter MR, Rootzen H (1988) Extremal theory for stochastic processes. Ann Probab 16(2):431–478
Li YH, Gao H, Li LY, Wang X (2010) Analysis of the surface water quality status and developing trend of the Yellow River Basin in the early 21st century. Proceedings of the 4th International Yellow River Forum on Ecological Civilization and River Ethics, Vol Ii:113-122
Luo PP, He B, Takara K, Razafindrabe BHN, Nover D, Yamashiki Y (2011) Spatiotemporal trend analysis of recent river water quality conditions in Japan. J Environ Monit 13(10):2819–2829. doi:10.1039/C1em10339c
Mazas F, Hamm L (2010a) The peaks-over-threshold statistical theory for the estimation of extreme sea-states. Part 1: a review of available methods. Houille Blanche 4:96–102
Mazas F, Hamm L (2010b) The peaks-over-threshold statistical theory for the estimation of extreme sea-states. Part 2: case studies. Houille Blanche 4:103–110
Naess A (1998) Statistical extrapolation of extreme value data based on the peaks over threshold method. J Offshore Mech Arct 120(2):91–96
Persson J, La KM (2012) On selection of threshold values in alarm-systems for drinking water monitoring. VATTEN – J Water Manag Res 1(68):43–51
Reay WG (2009) Water quality within the York river estuary. J Coastal Res: Spec Issue 57:23–39
Ross WH (1987) A peaks-over-threshold analysis of extreme wind speeds. Can J Stat 15(4):328–335
Sen PK (1968) Estimates of the regression coefficient based on Kendall’s Tau. J Am Stat Assoc 63(324):1379–1389. doi:10.1080/01621459.1968.10480934
Simiu E, Heckert NA (1996) Extreme wind distribution tails: A “peaks over threshold” approach. J Struct Eng ASCE 122(5):539–547
Thas O, Vanrolleghem P, Kops B, VanVooren L, Ottoy JP (1997) Extreme value statistics: potential benefits in water quality management. Water Sci Technol 36(5):133–140. doi:10.1016/S0273-1223(97)00498-8
Wong TST, Li WK (2010) A threshold approach for peaks-over-threshold modeling using maximum product of spacings. Stat Sini 20(3):1257–1272
XLSTAT (2012) Running a partial least squares (PLS) discriminant analysis with XLSTAT-PLS. http://www.xlstat.com/en/learning-center/tutorials/running-a-partial-least-square-pls-discriminant-analysis-with-xlstat-pls.htm. Accessed May, 27 2014
Yenilmez F, Keskin F, Aksoy A (2011) Water quality trend analysis in Eymir Lake, Ankara. Phys Chem Earth 36(5-6):135–140. doi:10.1016/j.pce.2010.05.005
Yin X, Hu GH (2009) Trend analysis of surface water quality in Hunan Province. 2009 Proceedings of International Conference on Environmental Science and Information Application Technology, Vol 3,:154–157. doi: Doi 10.1109/Esiat.2009.158
Yu Y-S, Zou S, Whittemore D (1993) Non-parametric trend analysis of water quality data of rivers in Kansas. J Hydrol 150(1):61–80. doi:http://dx.doi.org/10.1016/0022-1694(93)90156-4