Covariation of coastal water temperature and microbial pollution at interannual to tidal periods



[1] Water temperature and fecal indicator bacteria levels covary along the shoreline of Huntington and Newport Beach, California at interannual to tidal periods. During summer, cooler than average waters caused by interannual variability in sea surface temperature (SST), synoptic upwelling, and tidal-period cooling are coincident with elevated levels of microbial pollution in the surf zone. This relationship can be explained by the effects of weakening in stratification on the fate of a waste water plume and the prolonged persistence of fecal indicator bacteria in colder waters. During winter, warmer than average water caused by basin scale oscillations and atmospheric and oceanographic processes that contribute to the Multivariate El Nino Southern Oscillation Index are indicative of elevated total coliform levels in the surf zone. The elevated coliform levels can be ascribed to increased rainfall, and the resultant storm water inflow to the surf zone.

1. Introduction

[2] Fecal indicator bacteria (FIB), including total coliform (TC), fecal coliform (FC), and enterococci (ENT), are used throughout the world as metrics of water quality and health risks associated with marine water contact [Barthram and Rees, 2000]. In the U.S., the number of recreational beach closures and advisories due to elevated levels of FIB more than doubled between 1999 and 2001 (from 6,200 to 13,410) (Natural Resources Defense Council, Testing the waters, available at The National Shellfish Registry ( reports that in 1995 31% of the 21,349,000 acres of shellfish harvesting waters in the U.S. were harvest-limited due to FIB impairment.

[3] In light of the economic impacts beach closures can have on a coastal community [Rabinovici et al., 2004], the potential health threats polluted beaches impose [Turbow et al., 2003], and the elusive nature of FIB sources [Boehm et al., 2002a], a method of accurately predicting microbial pollution at a beach would benefit coastal managers and the beach-going community. In this study, we explore the relationship between water temperature and fecal pollution in the surf zone at Huntington and Newport Beach (HNB). We are specifically interested in examining how (1) inter-annual temperature anomalies, (2) synoptic-scale upwelling, and (3) tidal-band changes in surf zone temperature correlate to water quality along the shoreline.

2. Materials and Methods

[4] The field site is a 23 km length of sandy coastline in northern Orange County, CA (Figure 1) that includes HNB. Rainfall occurs between November and March and averages 30.02 cm/yr (Santa Ana Watershed Project Authority, The Orange County Sanitation District (OCSD) discharges 106 m3/d FIB-rich treated municipal sewage near the southeastern terminus of the San Pedro Shelf, just offshore of HNB (Figure 1b).

Figure 1.

Map of the study site. Background map in panel A is from the USGS seamless data base.

[5] Between 1958 and 2001, OCSD monitored FIB at 17 sites in HNB at least three times per week (black circles in Figure 1a). Between 1958 and 1998, waters were assayed for TC alone following standard method 9221B [Greenberg et al., 1992]. In June 1998, assays for FC and ENT were added to the monitoring program using standard method 9220 [Greenberg et al., 1992] and EPA method 1600 [Messer and Dufour, 1998].

[6] Monthly sea surface temperature (SST) anomalies for 1958 to 2001 were obtained for a 2° × 2° area defined by San Diego to the south and Santa Barbara to the north [Lluch-Cota et al., 2001]. Anomalies for 2002 were extracted from the PFEG NOAA Global Real-time Surface Observations, monthly 1° × 1° degree data set (

[7] Daily surf zone temperatures (1990–2001) were obtained from Huntington (33°39.294 N, 118°00.223 W) and Balboa (33°36′N 117°54′W) piers (SIO, Surface water temperature, salinity and densities at shore stations, U.S. West Coast 1916–1997 data report, available at

[8] From June 1999 to June 2000, hourly measurements of temperatures and currents were recorded at four locations (solid black squares in Figure 1b). Station P was equipped with doppler current meters with temperature sensors (Aanderaa Instruments, Nesttun, Norway) at 1 m and 45 m below the surface. Nearshore stations S, R, and Q were equipped with current meters at 5 m (Interocean Systems, Inc, San Diego, CA) and 10 m depths (Falmouth Scientific, Cataumet, MA). Currents were rotated 60° counterclockwise from true north (TN) to define an alongshore direction.

[9] Hourly regional winds were obtained from the National Data Buoy Center (NDBC) buoy #46025 (33.75°N 119.08°W) ( Hourly local winds were obtained from Santa Ana Airport (10.5 km from the shoreline at 33.68°N 117.87°W). Winds were rotated 60° counterclockwise from TN to define a local alongshore direction.

[10] Remote winds for nine coastal locations from 22.5°N (Cabo San Lucas, Mexico) to 42.5°N (Gold Beach, Oregon, USA) at a resolution of 2.5° were obtained from the National Center for Environmental Predictions and the National Center for Atmospheric Research (NCAR/NCEP) Reanalysis Wind Data Set [Kalnay et al., 1996]. Following Pringle and Riser [2003] winds were rotated 19.93° counterclockwise from TN to define a general alongshore direction representative of the entire California-Baja shoreline.

[11] Rain data from 1958 to 2001 was obtained from Laguna Beach just south of NHB through the NCEP website.

[12] Lagged correlation analyses of currents, temperatures, and wind were completed as follows. Low frequency variations were removed from daily averages using a 30-day window Hamming filter. The original data was residualized using the filtered data and regression coefficients from original and filtered data. In determining the significance of cross correlations, we accounted for the artificial amplification by adjusting degrees of freedom [Chelton, 1984].

3. Results and Discussion

3.1. Interannual Variations in SST

[13] Figure 2 shows the log-mean TC in the study area, average SST anomaly, and total annual rainfall (JFM only) for JFM and JJA (panels A and B, respectively) from 1958 to 2001. In JFM, a positive correlation exists between SST anomaly and log-mean TC (r = 0.27, p < 0.08), while during JJA, a negative correlation exists between SST anomaly and log-mean TC (r = −0.33, p < 0.05). These results suggest microbial pollution and SST covary along the shoreline of our study area, with TC levels higher during warmer than average winters and colder than average summers.

Figure 2.

Panel A. Total Rainfall, mean TC, and average SST anomaly during JFM. Panel B. Mean TC and average SST anomaly during JJA. Panel C. Average TC at each station during a cool (squares) or warm-average (circles) event. p-values are shown at top. Panel D. Geometric mean of ENT at station 9N (solid line) and 95% C.I. (dotted lines) (top) and temperature deviation and standard error in the surf zone as a function of day since the full moon during JJA. Open and solid circles represent full and new moons, respectively.

[14] During JFM, SST in the Southern California Bight is controlled primarily by basin scale oscillations, and oceanographic and atmospheric processes which contribute to the Multivariate ENSO Index (MEI) [Lluch-Cota et al., 2003] (r = 0.71, p < 0.05 between SST and MEI). Consequently, TC and MEI are also correlated (r = 0.40, p < 0.05) illustrating the important role global-scale processes have on local-scale pollution. The exact mechanism whereby the local surf zone becomes polluted actually involves rainfall, a side effect of warm waters and ENSO (r = 0.48, p < 0.05, and r = 0.42, p < 0.05 for rainfall and SST and MEI, respectively), which causes increased quantities of FIB laden storm water runoff to enter the surf zone [Barthram and Rees, 2000].

[15] There two possible explanations of the relationship between SST and TC during JJA. When summertime temperatures are colder than usual, stratification is weaker offshore compared to when temperatures are average or above average [County Sanitation Districts of Orange County, 2000]. Weakly stratified conditions affect the fate of the wastewater plume released offshore of the beach, and the possibility that the plume surfaces and is transported onshore increases [Fischer et al., 1979]. Alternatively, the inverse relationship between TC die-off rates and temperature observed by various researchers [Wait and Sobsey, 2001; Burkhardt et al., 2000] supports the notion that TC from local sources may persist longer in cold water compared to warm.

3.2. Upwelling

[16] During months when the water column is stratified (May through November), surf zone temperature can episodically drop 2 to 6°C for several days. The spatial scale of these cooling events is large in comparison to our 23 km study site according to temperatures recorded at Huntington and Balboa piers. To examine the impact of these cooling events on water quality along the shoreline, TC data from each shoreline station were separated into a “cool” bin or “average-warm” bin based on the day's temperature deviation from its 11-year average at Huntington pier. Cool events were defined by temperature deviations of −2.8°C or greater. Choosing any negative temperature deviation greater than −2°C produced similar results; we chose −2.8°C to increase the sample size in the cool data bin while avoiding the inclusion of data from cooling events that were not at the scale or duration of the upwelling events we were targeting.

[17] Averages of each bin are shown in Figure 2c. At 0, 3N, and 6N water quality is worse during cool events, at 6S and 9S water quality is improved during cool events, and at all other stations, there is no statistical difference between TC during the two events. To interpret the results presented in Figure 2c (specifically the spatial pattern) we investigated the origin of the cool water mass(es) responsible for episodic cooling using current and temperature data collected between June 1999 and June 2000 offshore of Huntington Beach. Figure 3 shows the temperature data at 1 m and 45 m at station P and 5 m and 10 m at station Q (top panel), as well as alongshore currents (middle panel) at P (1 m and 45 m) and Q (5 m and 10 m), and cross shore currents (bottom panel) at P (1 m and 45 m) and Q (5 m). Station Q is chosen as a representative nearshore station (data at Q, R, and S are similar). Episodic cooling events in July and September 1999, and May 2000 are highlighted by blue shading; red shading highlights the return to average temperature conditions. During cooling events, surface and nearshore waters drop in temperature in unison as alongshore currents align themselves in the southeast (hereafter referred to as downcoast) direction throughout the water column. The temperature drops are evident in all surface temperature measurements including those taken in the surf zone. Contemporaneously, deep waters at station P are direction onshore, while surface waters both in the nearshore and offshore are directed away from the coast.

Figure 3.

Temperature and current data from stations P and Q. Episodic cooling events in July and September 1999, and May 2000 are highlighted by blue; red highlights the return to average temperature conditions.

[18] Lagged correlation analyses corroborate the scenario described above. At all stations and depths examined, alongshore currents and water temperature are positively correlated with temperatures lagging currents by 1 to 5 days (0.288 ≤ r ≤ 0.459, p < 0.01). Cross shore current and temperature correlations at P are consistent with upwelling, with cooling of waters at 45 m significantly, negatively correlated with currents (onshore flow occurs when temperatures are dropping) (r = −0.320, p < 0.01, lag 2 d), and cooling of waters at the surface (1 m) coincident with offshore flow (r = 0.148, p < 0.05, lag 1 d). In the nearshore, station S shows significant positive correlations between temperature and cross shore currents at 5 m (r = 0.340, p < 0.01, lag 4 d) and R at 10 m (r = 0.185, p < 0.01, lag 3 d) suggesting cooling coincident with offshore flow. Stations Q and R lack significance in their cross shore current- temperature correlations with the exception of data at 5 m at R where a slight correlation is found (r = 0.187, p < 0.05, lag 5 d). Although significant, these correlations are small, thus there may be other processes influence synoptic temperature changes.

[19] Local, regional, and remote alongshore winds were investigated as possible forcing mechanisms for the cooling events and the changes in water quality that accompany them. For simplicity, we limit our discussion to temperature at 1 m at station P. Local and regional alongshore winds and temperature at 1 m are lag correlated with small but significant coefficients, respectively (r = 0.164, lag 4 d and r = 0.203, lag 1 d, both p < 0.01). The only significant relationship between local temperature and remote winds is in Baja, Mexico at 27.5°N where winds are slightly positively correlated with temperature at station P (r = 0.203, p < 0.05) with winds leading temperature by 1 day. The influence of remote winds at this particular site in Baja on temperatures at Point Loma, CA is discussed by Pringle and Riser [2003] who found they exert an influence on cooling. Pringle and Riser [2003] postulate that coastal trapped waves are generated by the remote winds and propagate pole-ward causing upwelling along the coast.

[20] Based on our analyses, local and remote winds together account for at most 8% of the total variance of synoptic-scale cooling. Cooling might be forced primarily by other pressure gradients imposed by large scale changes in wind stress. Nevertheless, close examination of currents during representative cooling events in 1999–2000 illustrate cold subthermocline waters offshore of the beach are directed onshore during cooling. Assuming these are representative of similar magnitude and duration cooling events throughout 1990 to 2001, one possible interpretation of differences in TC during cool and average-warm events in Figure 2c is shoreline water quality during cool events is representative of typical offshore water quality, while during warm-average events it is representative of typical shoreline water quality as influenced by terrestrial land-based sources. It is interesting to note that while currents are directed towards the southeast during cooling events, elevated FIB appear at the northwest end of the study site. A possible source of TC in subthermocline offshore waters is the wastewater outfall. The phenomena of treated wastewater impacting nearby shorelines during upwelling events has been described for Los Angeles, CA [Siegel et al., 1988], and has been cautioned by Fischer et al. [1979]. Noble et al. [2003] did not find a link between the plume and nearshore water quality in 2002 at HNB. Further research is warranted to fully understand the fate of the wastewater plume and its influence on nearshore water quality.

3.3. Tidal-Band Temperature Variations

[21] Boehm et al. [2002a] showed that TC, FC, and ENT at stations 3N, 6N, and 9N exhibit lunar variability during JJA. The lunar pattern for ENT at 9N is shown in Figure 2d (top) where the geometric mean of ENT and 95% confidence intervals are shown as a function of day since the full moon using data from 1998 to 2001. Because FIB are measured at the same time everyday (8:00), the lunar pattern could owe its existence to fortnightly variability in tide range or the semi-diurnal/diurnal variability in tide level due to aliasing (see auxiliary material). The latter possibility is not supported by studies thus far [Noble et al., 2003; Grant et al., 2001; A. B. Boehm et al., Groundwater discharge: A potential association with fecal indicator bacteria in the surf zone, submitted to Environmental Science and Technology, 2004, hereinafter referred to as Boehm et al., submitted manuscript, 2004]. Boehm et al. (submitted manuscript, 2004) did not find significant covariation between FIB at 6N and tide level alone, and variation of FIB during spring and neap tides has been documented during a range of tide levels [Noble et al., 2003; Boehm et al., submitted manuscript, 2004].

[22] The average temperature deviation from the day-of-year average was determined as a function of day since the full moon at Huntington pier [Pineda, 1995]. Because the FIB lunar pattern is unique to summer time conditions, we limited our temperature analysis to JJA, but included all the available data years (1990–2001) (Figure 2d, bottom). Water temperature exhibits fortnightly variation, with temperatures coldest on day 4 and 15 since the full moon. This result is consistent with that of Pineda [1995] who identified predictable patterns of upwelling in the lunar month at surf zone stations along the California coast. Pineda attributes lunar upwelling to breaking internal tidal bores. Given documentation of internal tides at the study area [Boehm et al., 2002b; Noble et al., 2003], it is possible that the intermittent “lunar” upwelling is caused by breaking internal tidal bores.

[23] If internal tidal bores are responsible for the lunar FIB pattern, they may be advecting FIB-laden treated wastewater (discharged into subthermocline waters) into the surf zone, because this represents an offshore source of FIB. The lunar upwelling events are out-of-phase with the lunar FIB events, with cold temperatures lagging the high bacteria events by 2 to 4 days. The exact mechanism of internal bore-driven cross shelf transport must be further investigated to explain this phase-lag. Noble et al. [2003] documented this transport mechanism during their field study of 2002, but did not show a connection between the plume and nearshore water quality. We cannot rule out that the spring-neap tidal-period variation in water temperature and FIB is caused by phenomena such as tidally influenced groundwater flux [Moore et al., 2002].