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Abstract: The coastal zone is the significant environmental setting where ocean interfaces land. In addition, it is economically important because of its high residential, commercial and recreational values. Meanwhile, in the United States, public coastal areas are increasingly off-limits due to elevated levels of fecal pollution and other contaminants. This study investigates the effects of rainfall, discharge, wave, and alongshore transport on coastal FIB (fecal indicator bacteria) concentrations at adjacent beaches in Orange County, California, over three years’ period from October 2001 to September 2004. In order to identify the dominant tempora land spatial patterns of fecal pollutions along the coastal beaches, Empirical Orthogonal Function analysis was utilized for the three-year measurements (n = 39,525) of FIB concentration data from 17 sampling stations. Through the data analysis and the empirical orthogonal function analysis, it was found that the dominant factor effecting coastal FIB concentration is precipitation event and consequent water discharge from Santa Ana River in the area. The Empirical Orthogonal Function analysis revealed the potential non-point FIB sources around northern part of Orange County beaches. In addition, this study confirmed the existing alongshore transport by wave-driven surf zone current and offshore tidal currents.
Key words: Fecal pollution, coastal water, rainfall, discharge, alongshore transport.
1. Introduction
The coastal zone is the interface between ocean and land, and an important ecological, economic, and recreational resource. Urbanization of the ocean’s coastline has increased significantly the flow of toxic contaminants and pathogenic microorganisms into the coastal zone. Coastal waters have many beneficial uses and they are a transport medium and a final repository for all manner of human waste [1]. The latter inexorably diminishes the former, as evidenced by a wide spectrum of coastal ills, which threatens human health in manifold ways. In the United States, public coastal beaches are increasingly off-limits due to elevated levels of fecal pollution and other contaminants. Mitigating this pollution and identifying pollutant sources in coastal system is complicated by the high degree of complexity of coastal systems [2]. Much of this complexity is associated with the spatial and temporal variability of the relevant physicochemical, biological, and oceanographic processes.
The near shore concentration of indicator bacteria is controlled by complex and non-linear interactions between human activities and natural processes. Their sources are primarily human in nature: discharge of treated sewage through offshore outfalls and rivers, breaks in sewage collection lines, and runoff from urban and agricultural watersheds [3-5]. The near
Multi-dimensional spatial-temporal data of FIB for 17 sampling stations were analyzed using a multivariate statistical technique called EOF(empirical orthogonal function) analysis. EOF analysis of the water quality data involves the following steps [14-18]:
(1) Organization of the data into a data matrix, Xij , with i and j corresponding to sampling sites and sampling times. Entries in the data matrix represent the log-transformed concentrations of FIB;
(2) Preparation of a de-meaned data matrix,
i represents the mean of all concentration measurements at the ith station, and ri(??i) is the standard deviation of all concentration measurements at the ith station;
(3) Decomposition of the de-meaned data matrix into a series of EOF modes and associated loadings. The modes are ordered such that the first mode captures the most variance in the de-meaned data set, the second captures the next most data variance, and
frequency marks). During this period, FIB concentrations along the beaches frequently exceeded one or more California State standards.
The goal of the EOF approach is to identify the dominant temporal patterns (referred to here as“modes”) in time series data, and then to quantitatively determine how these modes are distributed spatially, by examining the spatial distribution of “loadings” associated with each mode. EOF analysis was carried out in the three FIB species concentrations for the 17 sampling stations along the
sampling sites. This result implies that the spatial variability captured by the first EOF mode is relatively homogeneous across all sampling sites; i.e., if the concentrations are rising in one part of the sampling grid, they are rising in the rest of the grid as well. The second EOF loading plots show that sampling stations 3N, 6N, and 9N have consistently higher values than the rest of the stations and suggest
In this study, land-based monitored coastal water quality data and related environmental data were combined to identify dominant seasonal and annual pattern of microbiological pollutions along the Orange County coast. This study sheds light on the spatial and temporal patterns of FIB concentrations along the coast of Orange County, Southern California; and on the sources and transport pathways that give rise to these patterns. Water sample concentrations of FIB
Growth: A State of the Coast Report, NOAA’s State of the coast report, National Oceanic and Atmospheric Administration, Silver Spring, Md., 1996.
[2] J.H. Kim, S.B. Grant, Public mis-notification of coastal water quality: A probabilistic evaluation of posting errors at Huntington Beach, California, Environmental Science and Technology 38 (2004) 2497-2504.
[3] K. Schiff, M. Stevenson, San Diego regional storm water monitoring program: Contamination inputs to coastal wetlands and lagoons, Bulletin Southern California Academy of Sciences 95 (1996) 7-16.
[4] H.M. Solo-Gabriele, M.A. Wolfert, T.R. Desmarais, C.J. Palmer, Sources of E. coli from coastal subtropical environment, Applied and Environmental Microbiology 66 (2000) 230-237.
[5] R.S. Fujioka, Monitoring coastal marine waters for spore forming bacteia of faecal and soil origin to determine point from non-point source pollution, Water Science and Technology 44 (2001) 181-188.
[6] M.A. Mallin, K.E. Williams, E.C. Esham, R.P. Lowe, Effect of human development on bacteriological water quality in coastal watersheds, Ecological Applications 10(2000) 1047-1056.
[7] A.B. Boehm, S.B. Grant, J.H. Kim, S.L. Mowbray, C.D. McGee, C.D. Clark, et al., Decadal and shorter period variability of surf zone water quality at Huntington Beach, California, Environmental Science and Technology 36(2002) 3885-3892.
[8] C.E. Chamberlain, R.A. Mitchell, A decay model for enteric bacteria in natural waters, Water Pollution Microbiology 2 (1978) 325-348.
[9] N. Mezrioui, B. Baleux, M. Troussellier, A microcosm study of the survival of E. coli and Salmonella typhimurium in brackish water, Water Research 29 (1995) 459-465.
[10] J.H. Kim, S.B. Grant, Public mis-notification of coastal water quality: A probabilistic analysis of posting errors at Huntington Beach, California, Environmental Science and Technology 38 (2004) 2497-2504.
[11] J. Bartram, G. Reese, Monitoring bathing water: A practical guide to the design and implementation of assessments and monitoring programmes, World Health Organization, 2000.
[12] A.B. Boehm, S.B. Weisberg, Tidal forcing of enterococci at marine recreational beaches at fortnightly and semidiurnal frequencies, Environmental Science and Technology 39 (2005) 5575-5583.
[13] J.H. Kim, S.B. Grant, C.D. McGee, B.F. Sanders, J.L. Largier, Locating sources of surf zone pollution: A mass budget analysis of fecal indicator bacteria at Huntington Beach, California, Environmental Science and Technology 38 (2004) 2626-2636.
Forecasting tropical cyclone motion using empirical orthogonal function representations of environmental wind fields, Monthly Weather Review 114 (1986) 2466-2477.
[19] S.B. Grant, J.H. Kim, B.H. Jones, S.A. Jenkins, J. Wasyl, C. Cudaback, Surf zone entrainment, along-shore transport, and human health implications of pollution from tidal outlets, Journal of Geophysical Research 110 (2005) C10025.
[20] S.B. Grant, B.F. Sanders, A.B. Boehm, J.A. Redman, J.H. Kim, R.D. Mrse, et al., Generation of enterococci bacteria in a coastal saltwater marsh and its impact on surf zone water quality, Environmental Science and Technology 35(2001) 2407-2415.
Key words: Fecal pollution, coastal water, rainfall, discharge, alongshore transport.
1. Introduction
The coastal zone is the interface between ocean and land, and an important ecological, economic, and recreational resource. Urbanization of the ocean’s coastline has increased significantly the flow of toxic contaminants and pathogenic microorganisms into the coastal zone. Coastal waters have many beneficial uses and they are a transport medium and a final repository for all manner of human waste [1]. The latter inexorably diminishes the former, as evidenced by a wide spectrum of coastal ills, which threatens human health in manifold ways. In the United States, public coastal beaches are increasingly off-limits due to elevated levels of fecal pollution and other contaminants. Mitigating this pollution and identifying pollutant sources in coastal system is complicated by the high degree of complexity of coastal systems [2]. Much of this complexity is associated with the spatial and temporal variability of the relevant physicochemical, biological, and oceanographic processes.
The near shore concentration of indicator bacteria is controlled by complex and non-linear interactions between human activities and natural processes. Their sources are primarily human in nature: discharge of treated sewage through offshore outfalls and rivers, breaks in sewage collection lines, and runoff from urban and agricultural watersheds [3-5]. The near
Multi-dimensional spatial-temporal data of FIB for 17 sampling stations were analyzed using a multivariate statistical technique called EOF(empirical orthogonal function) analysis. EOF analysis of the water quality data involves the following steps [14-18]:
(1) Organization of the data into a data matrix, Xij , with i and j corresponding to sampling sites and sampling times. Entries in the data matrix represent the log-transformed concentrations of FIB;
(2) Preparation of a de-meaned data matrix,
i represents the mean of all concentration measurements at the ith station, and ri(??i) is the standard deviation of all concentration measurements at the ith station;
(3) Decomposition of the de-meaned data matrix into a series of EOF modes and associated loadings. The modes are ordered such that the first mode captures the most variance in the de-meaned data set, the second captures the next most data variance, and
frequency marks). During this period, FIB concentrations along the beaches frequently exceeded one or more California State standards.
The goal of the EOF approach is to identify the dominant temporal patterns (referred to here as“modes”) in time series data, and then to quantitatively determine how these modes are distributed spatially, by examining the spatial distribution of “loadings” associated with each mode. EOF analysis was carried out in the three FIB species concentrations for the 17 sampling stations along the
sampling sites. This result implies that the spatial variability captured by the first EOF mode is relatively homogeneous across all sampling sites; i.e., if the concentrations are rising in one part of the sampling grid, they are rising in the rest of the grid as well. The second EOF loading plots show that sampling stations 3N, 6N, and 9N have consistently higher values than the rest of the stations and suggest
In this study, land-based monitored coastal water quality data and related environmental data were combined to identify dominant seasonal and annual pattern of microbiological pollutions along the Orange County coast. This study sheds light on the spatial and temporal patterns of FIB concentrations along the coast of Orange County, Southern California; and on the sources and transport pathways that give rise to these patterns. Water sample concentrations of FIB
Growth: A State of the Coast Report, NOAA’s State of the coast report, National Oceanic and Atmospheric Administration, Silver Spring, Md., 1996.
[2] J.H. Kim, S.B. Grant, Public mis-notification of coastal water quality: A probabilistic evaluation of posting errors at Huntington Beach, California, Environmental Science and Technology 38 (2004) 2497-2504.
[3] K. Schiff, M. Stevenson, San Diego regional storm water monitoring program: Contamination inputs to coastal wetlands and lagoons, Bulletin Southern California Academy of Sciences 95 (1996) 7-16.
[4] H.M. Solo-Gabriele, M.A. Wolfert, T.R. Desmarais, C.J. Palmer, Sources of E. coli from coastal subtropical environment, Applied and Environmental Microbiology 66 (2000) 230-237.
[5] R.S. Fujioka, Monitoring coastal marine waters for spore forming bacteia of faecal and soil origin to determine point from non-point source pollution, Water Science and Technology 44 (2001) 181-188.
[6] M.A. Mallin, K.E. Williams, E.C. Esham, R.P. Lowe, Effect of human development on bacteriological water quality in coastal watersheds, Ecological Applications 10(2000) 1047-1056.
[7] A.B. Boehm, S.B. Grant, J.H. Kim, S.L. Mowbray, C.D. McGee, C.D. Clark, et al., Decadal and shorter period variability of surf zone water quality at Huntington Beach, California, Environmental Science and Technology 36(2002) 3885-3892.
[8] C.E. Chamberlain, R.A. Mitchell, A decay model for enteric bacteria in natural waters, Water Pollution Microbiology 2 (1978) 325-348.
[9] N. Mezrioui, B. Baleux, M. Troussellier, A microcosm study of the survival of E. coli and Salmonella typhimurium in brackish water, Water Research 29 (1995) 459-465.
[10] J.H. Kim, S.B. Grant, Public mis-notification of coastal water quality: A probabilistic analysis of posting errors at Huntington Beach, California, Environmental Science and Technology 38 (2004) 2497-2504.
[11] J. Bartram, G. Reese, Monitoring bathing water: A practical guide to the design and implementation of assessments and monitoring programmes, World Health Organization, 2000.
[12] A.B. Boehm, S.B. Weisberg, Tidal forcing of enterococci at marine recreational beaches at fortnightly and semidiurnal frequencies, Environmental Science and Technology 39 (2005) 5575-5583.
[13] J.H. Kim, S.B. Grant, C.D. McGee, B.F. Sanders, J.L. Largier, Locating sources of surf zone pollution: A mass budget analysis of fecal indicator bacteria at Huntington Beach, California, Environmental Science and Technology 38 (2004) 2626-2636.
Forecasting tropical cyclone motion using empirical orthogonal function representations of environmental wind fields, Monthly Weather Review 114 (1986) 2466-2477.
[19] S.B. Grant, J.H. Kim, B.H. Jones, S.A. Jenkins, J. Wasyl, C. Cudaback, Surf zone entrainment, along-shore transport, and human health implications of pollution from tidal outlets, Journal of Geophysical Research 110 (2005) C10025.
[20] S.B. Grant, B.F. Sanders, A.B. Boehm, J.A. Redman, J.H. Kim, R.D. Mrse, et al., Generation of enterococci bacteria in a coastal saltwater marsh and its impact on surf zone water quality, Environmental Science and Technology 35(2001) 2407-2415.