MODIS Imagery of Turbid Plumes in San Diego Coastal Waters During Rainstorm Events

Remote Sensing of Environment 114 (2010) 332–344

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Remote Sensing of Environment

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MODIS imagery of turbid plumes in San Diego coastal waters during rainstorm events

Florence Lahet, Dariusz Stramski ⁎

Marine Physical Laboratory, Scripps Institution of Oceanography, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0238, USA article info abstract

Article history: Data of normalized water-leaving radiance, nLw, obtained from the Moderate Resolution Imaging Spectro- Received 6 November 2008 radiometer (MODIS) on the Aqua satellite at spatial resolution of 250 m (band 1 centered at 645 nm) and 500 m Received in revised form 13 August 2009 (band 4 at 555 nm) are used to study turbid plumes in coastal waters of southern California during rainstorm Accepted 20 September 2009 events in winter of 2004–2005. Our study area includes San Diego coastal waters, which extend approximately 25 km offshore between Point Loma and 10 km south of the US–Mexican border. These waters are inﬂuenced by Keywords: terrigenous input of particulate and dissolved materials from San Diego and Tijuana watersheds and non-point Ocean color MODIS sources along the shore. Optimum threshold values of satellite-derived normalized water-leaving radiances at Coastal ocean both wavebands were established for distinguishing the plume from ambient ocean waters. These threshold Turbid plumes values were determined by searching for a maximum correlation between the estimates of satellite-derived Rainstorm events plume area calculated using a broad range of nLw values and the environmental variables characterizing rainfall, Southern California river discharge, wind, and tides. A correlation analysis involving the amount of precipitated water accumulated during a storm event over the San Diego and Tijuana watersheds was selected as the basis for ﬁnal determinations

of the optimum threshold nLwthr and subsequent calculations of the plume area. By applying this method to a sequence of MODIS imagery, we demonstrate the spatial extent and evolution of the plume during rainstorm events under various conditions of precipitation, river discharge, wind forcing, and coastal currents. © 2009 Elsevier Inc. All rights reserved.

1. Introduction radiances, nLw, above the threshold value of 1.3 mW cm−2 μm−1 sr−1 at 555 nm allowed discrimination of the runoff plume from ambient Ocean color remote sensing offers an attractive approach to ocean waters. Nezlin et al. (2005) compared the relationships between distinguish turbid plumes produced by stormwater discharge in the plume size derived from SeaWiFS and rainstorm data in different coastal coastal ocean from ambient marine waters. Optical sensors deployed on areas of southern California. They showed that the primary factors aircrafts or satellites provide a means to detect plumes over extended controlling the relationships include watershed land-use characteristics, spatial and temporal scales that cannot be adequately addressed with watershed size, and land topography. traditional analysis of discrete water samples. Plumes are influenced by The objective of this study is to analyze the satellite-derived plume various factors such as the nature and magnitude of runoff discharged area in relation to environmental parameters during rainstorm events in from rivers and other sources, wind, currents, tides, and the buoyancy of the San Diego region of southern California. We use ocean color imagery water (Stumpf et al., 1993; Garvine, 1995; Chao, 1998; Warrick et al., from the Moderate Resolution Imaging Spectroradiometer (MODIS) 2004b; Ahn et al., 2005). Several studies of stormwater plumes in the flown aboard the Aqua spacecraft. Two high spatial resolution bands, Southern California Bight showed the potential usefulness of ocean color 1 and 4, within the visible spectral region are used. The MODIS band 1 satellite data for water quality assessment and coastal management with a spatial resolution of 250 m has a spectral range of 620–670 nm (e.g., Ahn et al., 2005; Warrick et al., 2007; Nezlin et al., 2008). with a center wavelength of 645 nm. The band 4 with a resolution of Using satellite observations from the Sea-viewing Wide Field-of- 500 m has a spectral range of 545–565 nm centered at 555 nm. Recent view Sensor (SeaWiFS), Nezlin and DiGiacomo (2005) analyzed the studies demonstrated the potential of these bands to monitor water relationship between the amount of precipitated rainwater and plume quality in estuarine and coastal waters (Hu et al., 2004; Chen et al., 2007; characteristics over the San Pedro Shelf, which is adjacent to the coastal Shutler et al., 2007). watershed within the Los Angeles metropolitan area. By assessing We examine the time period from December 28, 2004 through maximum correlation between the plume size and precipitated March 7, 2005, which represents the third heaviest rainfall season rainwater, they found that satellite-derived normalized water-leaving in southern California since records began in 1850 (NOAA National Weather Service, 2007). During that period, repeated and at times long periods of intense rain and runoff had a significant effect on coastal water quality in the San Diego region. We defined several storm events ⁎ Corresponding author. Marine Physical Laboratory, Scripps Institution of Oceanography, University of California San Diego, La Jolla, 9500 Gilman Dr, CA 92093-0238, USA. using rainfall data and analyzed eighteen MODIS images. We discuss the E-mail address: [email protected] (D. Stramski). determinations of threshold values for satellite-derived water-leaving

0034-4257/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.rse.2009.09.017 F. Lahet, D. Stramski / Remote Sensing of Environment 114 (2010) 332–344 333 radiances, nLw(645) at 645 nm and nLw(555) at 555 nm, which are the San Diego coast at least as far as Point Loma, or south along the used to define a plume. These threshold determinations are based on Mexican coast of northern Baja California. The storm drain system also examining the correlation between the plume area and environmental contributes to pollution of coastal waters. Consequently, turbid plumes parameters (rainfall, Tijuana River discharge, wind, tides). Using a in coastal waters, especially during storms, represent an environmental sequence of MODIS images, we illustrate the spatial extent and hazard due to associated pollutants. The beaches of Imperial Beach north evolution of the plume during selected rainstorm events. of the Tijuana River mouth were closed during 83 days in 2005. Our study region is characterized by an arid warm Mediterranean 2. Characterization of the study area climate with 85% of precipitation occurring during a rainy season from November through March. The average annual precipitation is less than The study area extends along the San Diego coastline from approx- 300 mm. Rainfall is highly variable from year to year and from month to imately Point Loma in the north to 10 km south of the US–Mexican month. Droughts are typical. Floods occur at times, although they are border, and is defined by latitudes of about 32°26′N and 32°41′N generally short lasting. Climate in the region can vary considerably over and longitudes 117°04′W and 117°22′W(Fig. 1). This area includes the short geographical distances. For example, the western slope of the coastal ocean waters extending about 25 km offshore. The enclosed Peninsular Range (the prominent topographic feature of the region) waters of San Diego Bay are not considered for plume determinations, as receives about 1 m and the foothills west of the Peninsular Range about our interest is focused just on coastal ocean waters adjacent directly to 400–500 mm of annual rainfall (Isla & Lee, 2006). the open ocean. The San Diego Bay is connected with the ocean near There are eleven hydrologic units in the San Diego region, which are Point Loma. associated with river/stream systems that discharge into the Pacific The environmental problems in the study area occur due to the large Ocean (Fig. 2). We have considered the following hydrologic units (from population of the San Diego-Tijuana metropolitan area and the con- south to north): Tijuana (TIJ), Otay (OT), Sweetwater (SW), Pueblo San centrated commercial, naval, and recreational activities (Schiff et al., Diego (PUE), San Diego (SD), Penasquitos (PEN), and San Dieguito (SDo) 2000). There are multiple sources of particles, organic substances, nutri- (see also Nezlin & Stein, 2005). Whereas the southernmost units (TIJ and ents, and contaminants that discharge into the coastal ocean in this OT) are adjacent to the coastal waters of direct interest to our study, the region (Tran et al., 1997; Zeng & Vista, 1997; Zeng et al., 1997). Signif- remaining units may also affect the area through the outflow from San icant degradation of coastal water quality is caused by stormwater run- Diego Bay or predominant southward transport of coastal waters from off during episodic rainstorm events, mainly in the winter season (e.g., the north. The rivers of the region are small but have generally high Characklis & Wiesner, 1997; Davis et al., 2001). In particular, the Tijuana sediment yields. For example, Tijuana, Sweetwater, and San Diego rivers River discharges into the ocean just north of the US–Mexican border. are characterized by a mean annual flow of 28.9×106, 7.42×106,and After heavy rains, the Tijuana River carries runoff from the city of Tijuana 13.7×106 m3 yr−1 and a mean annual suspended sediment flux of and from sewage that overflows from the International Wastewater 0.206×106, 0.0043×106, and 0.010×106 ton yr−1,respectively(Inman Treatment Plant in Tijuana. Plumes from the river can travel north along & Jenkins, 1999).

Fig. 1. Map of southern California coastal waters showing the study area (black box). The map speciﬁes the location of Mission Bay (MB), San Diego River mouth (SDR), Point Loma (PL), Coronado (C), San Diego Bay (SDBa), Tijuana River (TR), the US–Mexican border (B), Los Buenos Creek mouth and Punta Los Buenos (LBC and PLB). The bathymetry is shown. The four sections, S1, S2, S3, and S4, for which the offshore extent of plume was calculated (Table 3 and relevant text in Section 4.3) are also shown as dashed lines. 334 F. Lahet, D. Stramski / Remote Sensing of Environment 114 (2010) 332–344

Fig. 2. Thirty-seven stations (solid circles) located within the US part of the Tijuana watershed and the San Diego watershed (Otay, Sweetwater, Pueblo San Diego, San Diego, Penasquitos, and San Dieguito hydrologic units), which provided data for calculating the rainfall parameters. The map was obtained from the website of the San Diego watershed network (http://map.sdsu.edu/group2001/group3/index.htm). Stations within the Mexican part of the Tijuana hydrologic unit are not shown.

Winds in the San Diego region are generally weak. Wind speeds in 3. Data and methods excess of 8 ms−1 are infrequent (Lentz & Winant, 1986). A sea breeze, which is common from the late morning through the evening, produces 3.1. Satellite data awesterlyflow at an average speed of about 4–5ms−1. At times, mainly in the fall and winter, dry and windy weather conditions known as Santa MODIS-Aqua Level 1A data were obtained from NASA Goddard AnaforminsouthernCalifornia(e.g.,Raphael, 2003). Space Flight Center and processed to Level 2 format using the NASA's Ocean currents in the study area are related to different forcing SeaWiFS Data Analysis System (SeaDAS version 5.1.6) software. The including barotropic tides, internal waves, winds, as well as larger-scale normalized water-leaving radiances nLw(645) (i.e., band 1 at 645 nm, flows such as the southward flowing California Current system (Bray 250 m spatial resolution) and nLw(555) (i.e., band 4 at 555 nm, 500 m et al., 1999; Chadwick & Largier, 1999). In addition, current patterns are spatial resolution) were calculated. The atmospheric correction was related to regional bathymetry and coastline shape (Kim et al., 2007;Jan based on an aerosol model utilizing the shortest infrared wavelength Svejkovsky, personal communication). The prominent bathymetric at 1240 nm and the longest infrared wavelength at 2130 nm (Wang & features include the relatively steep drop-off paralleling the outside Shi, 2005; Wang, 2007). Eighteen MODIS images for the period from edge of the Point Loma kelp bed, the shoreward reaching deep-water 12/30/2004 through 3/7/2005 were processed for the study area and basin outside Coronado Shores, the alluvial fan of the Tijuana River, and projected using a Lambert azimuthal equal area projection. During the gradually sloping bottom along a relatively straight coastline from that time period several significant rainstorm events occurred. Coronado to Punta Los Buenos in Mexico (Fig. 1). The most frequent flow regime (occurring 60–70% of the time) is dominated by moderate 3.2. Precipitation data southward currents. The flow immediately south of Point Loma tends to round the headland toward the east. Near the beach, most of this water Daily rainfall data from 44 meteorological stations located in seven again veers southward until deflected offshore by the shallows of the hydrologic units (Fig. 2) were obtained from NOAA National Climatic Tijuana River alluvial fan. This alluvial fan tends to sometimes create a Data Center Climate Data Online, the San Diego County rainfall moni- cyclonic eddy offshore from the Tijuana Estuary in the US and Playas de toring network, and the Mexican “Comisión Nacional del Agua”. A mean ̄ Tijuana in Mexico. Northward flow regime is relatively uncommon (20% daily precipitation, Ph,wasfirst calculated for each hydrologic unit, h. ̄ of the time) and generally lasts 1 to 2 days. The most significant feature We then calculated an area-weighted mean daily precipitation, PWS,for during northward flow is related to the influence of the Tijuana River composite watersheds, WS, from: alluvial fan. As the near-shore waters reach the shallows from the south, fl — n — n they become de ected to the northwest (i.e., offshore). ∑ ∑ ð Þ PWS = Ah Ph= Ah 1 The tidal range in San Diego Bay is ∼1.7 m from mean lower-low to h =1 h =1 mean higher-high water, with extreme range up to 3 m (Chadwick &

Largier, 1999). Cross-shelf and alongshore tidal currents on the where Ah is the area of the h-th hydrologic unit and n is the number Southern California shelf are poorly correlated with the tidal elevation of hydrologic units included in the composite watershed (Nezlin & (Winant & Bratkovich, 1981). Stein, 2005). Seven composite watersheds were considered with an F. Lahet, D. Stramski / Remote Sensing of Environment 114 (2010) 332–344 335

̄ increasing spatial extent from south to north. The first composite Using these criteria, we analyzed daily precipitation data of PWS watershed, WS1, represents just the Tijuana hydrologic unit, the during the time period December 28, 2004–March 7, 2005 and we second composite watershed, WS2, includes Tijuana and Otay units, identified three storm events (Fig. 3aandTable 1). The first event the third WS3 includes Tijuana, Otay, and Sweetwater units, etc. The between December 28, 2004 and January 12, 2005 was characterized by ̄ final composite watershed, WS7, includes seven hydrologic units 3days of heavy rains with PWS >20 mm, including one day with ̄ extending from the Tijuana unit in the south to the San Dieguito unit PWS =45 mm. The second event between January 25 and January 29, in the north (see Fig. 2). The Tijuana unit is the largest unit with most 2005, is a rainy episode lasting 5 days with daily precipitation in the of its area in Mexico. The large part of the Mexican area has, however, range from about 0.3 to 7 mm. The third event lasted from February 6 relatively few rainfall stations. Therefore, in our calculations of rainfall through March 6, 2005 and consisted of a series of heavy rain events parameters, we tested two versions of the Tijuana unit, with and separated by a few days of weak or no precipitation. The dates indicating without the Mexican part. the beginning and the end of each event as well as the dates when For defining the beginning date and the end date of an individual MODIS imagery is available for the analysis of plumes during these rainstorm event, we followed the criteria proposed by Nezlin and events are given in Table 1. DiGiacomo (2005). According to these criteria, the rainstorm begins on a We also calculated the accumulated amount of precipitated water, day when the accumulated precipitation during the 7-day period Vt, for the day t of the plume analysis with MODIS imagery. The value preceding that day exceeds 2.5 mm. Under this threshold value, no of Vt represents the precipitated water accumulated during the period significant rainfall effect on water quality in near-shore waters was of a given storm and was calculated from: observed in the Los Angeles region (Ackerman & Weisberg, 2003). The — — — — — 2 3 4 … values of area-weighted mean daily precipitation were considered Vt = PWS;t−1 + k PWS;t−2 + k PWS;t−3 + k PWS;t−4 + k PWS;t−5 + significant when greater than 0.25 mm. The lower values were ignored. ð2Þ ̄ The end of a storm was defined by a day with PWS<0.25mm and an accumulated precipitation during the 5-day period following that day where k is the coefficient characterizing the persistence of the less than 2.5 mm. precipitated water within the plume, and t−1, t−2, t−3, etc. are the

Fig. 3. Variations of selected environmental factors during the time period from December 28, 2004 through March 7, 2005. This time period is indicated at the top axis. (a) An area- weighted mean daily precipitation (solid line) and accumulated amount of precipitated water, Vt (dashed line is for k=0.5 and dashed–dotted line is for k=0.7). (b) Mean daily discharge of Tijuana River, Q. (c) Mean daily wind vectors (W is wind speed). (d) Tidal phase, TP. The consecutive numbers from 1 through 18 at the bottom horizontal axis correspond to MODIS image number (see Table 1). The arrows at the top axis designate the dates of the 6 MODIS images shown in Figs. 8 and 9. 336 F. Lahet, D. Stramski / Remote Sensing of Environment 114 (2010) 332–344

Table 1 3.4. Plume area calculation Occurrence of rainstorm events determined from the analysis of an area-weighted mean daily precipitation, P̄ . WS The calculation of plume area, PA, includes two main components. Event Beginning and MODIS imagery First, a threshold value for the satellite-derived normalized water- end date leaving radiance, nLwthr, is determined to identify the boundary of the 1 12/28/2004 12/30/2004 (1); 1/1/2005 (2); 1/12/2005 (3); 1/19/2005 (4) plume, and second, the area of satellite pixels within the plume is 1/12/2005 calculated. These determinations were made with the MODIS imagery of 2 1/25/2005 1/29/2005 (5); 1/31/2005 (6); 2/2/2005 (7); 2/3/2005 (8) nLw(645) and nLw(555). The plume area obtained from nLw(645) is 1/29/2005 3 2/6/2005 2/9/2005 (9); 2/13/2005 (10); 2/16/2005 (11); denoted by PA645 and that obtained from nLw(555) by PA555.Inthese 2/18/2005 (12); 2/23/2005 (13); 2/24/2005 (14); determinations, nLwthr was varied between 0.01 and 0.05 with a step of − − − 2/25/2005 (15) 0.01 mW cm 2 μm 1 sr 1 for both MODIS bands and then between 3/6/2005 2/27/2005 (16); 3/2/2005 (17); 3/7/2005 (18) 0.05 and 2 (band 1) and between 0.05 and 3 (band 4) with a step of − 2 − 1 − 1 Shown are the beginning and end dates of the events as well as the dates of MODIS-Aqua 0.05 mW cm μm sr . We estimated the optimum threshold images available for the analysis of plumes associated with the events during the time period values of nLwthr at 645 nm and 555 nm for distinguishing the plume – December 28, 2004 March 7, 2005. The MODIS image numbers are shown in parenthesis. from ambient ocean waters by searching for the maximum correlation

between the plume area and the accumulated rainfall, Vt.These indices for consecutive days during the period preceding the day t optimum levels of nLwthr are assumed to yield the best estimates of (Nezlin & DiGiacomo, 2005). The highest order term in the sum of plume area. Although Vt is the primary environmental factor providing a Eq. (2) corresponds to the day before the beginning of a given storm basis for determining the optimum levels of nLwthr,wealsopresent event. Vt was calculated for k varying between 0.05 and 0.95 with a similar calculations based on other environmental factors (Section 4.2 step of 0.05. below). The area of the plume within boundaries determined by nLwthr was calculated using a method based on the multiplication of the matrix of

3.3. Other environmental data pixel areas by a mask, masknLw.ThemasknLw value for a given pixel equals to 1 when nLw≥nLwthr, and 0 when nLw

Fig. 4. The coefficient of determination, r2, of the linear relationship between the plume area, PA, and the accumulated amount of precipitated water, Vt, as a function of the Fig. 5. The plume area, PA, as a function of the accumulated amount of precipitated threshold value of satellite-derived normalized water-leaving radiance, nLwthr. The correlation curves are plotted for various values of parameter k. Panel (a) is for the water, Vt, calculated using the optimum threshold values of normalized water-leaving MODIS band 1 centered at 645 nm and panel (b) for the band 4 at 555 nm. radiance nLwthr and parameter k given in Table 2. Panel (a) shows the relationship for the MODIS band 1 centered at 645 nm, and panel (b) for the band 4 at 555 nm. The data encircled were collected during large Tijuana river discharge exceeding 10 m3 s− 1. differences. For example, Nezlin et al. (2005) examined a larger coastal region during a longer period of time (October 6, 1997–June 26, 2003) compared with our study. The relatively short period of time covered in watersheds. The water levels in the reservoirs were very low prior to our study represents a season with very heavy rainfall. This is expected the rainstorms of 2004–2005 and held back major volumes of to result in more rapid saturation of soils with water and discharge of precipitated water during the rainstorms. During these rainstorms, stormwater to coastal ocean, which can reduce k. In addition, highly there was also significant resuspension through wave action, which turbid plumes during heavy rainfall produce enhanced water-leaving cannot be distinguished from older runoff in MODIS data. Consequently, radiance. This may explain the higher value of optimum nLwthr(555) in the plumes may sometimes appear larger than their true runoff our study. Nezlin et al. (2005) also showed that land-use characteristics, components. size, and elevation of the drainage area are important factors affecting The consideration of rainfall data representing the composite coastal plumes. Based on effective land use, impervious cover of the watershed WS7 (including the hydrological units from Tijuana to San watersheds of Orange County and San Diego region is <10%, so the Dieguito) appears to be a reasonable approach for our analysis. The amount of water infiltrating soils is expected to be relatively high and highest values of the coefficient of determination, r2 =0.75–0.77, be- the runoff to the ocean relatively slow. Such conditions are expected to tween the plume area and Vt are obtained for this composite watershed. favor relatively high values of k. During rainstorm events the plume is generally affected by multiple

Fig. 5 shows the actual data of plume areas, PA645 and PA555, plotted terrestrial sources of freshwater discharge into the ocean, which versus Vt for our study area. The plume areas were calculated using the can extend over significant distances along the coastline. Thus, the optimum values of nLwthr and k, as determined from Fig. 4. For both hydrologic units located north of our study area may have influence on MODIS bands, the data points are spread over the observed range of the plume within the study area, especially as the transport of surface 2 variability. PA645 varies between nearly zero and about 80 km and waters in this region is predominantly southward. The consideration of 2 2 2 PA555 between a few km and 90 km . The intercept of the relationships the Tijuana unit alone yields the lowest values of r . Nevertheless, these is positive but small, suggesting that rainfall was a primary source of the values are relatively high (0.65–0.68), which reflects a major impact of plumes. Some images were not obtained under perfectly clear skies, the Tijuana unit on the study area. The addition of data from the Mexican which contribute to the scatter in the data points. Some outliers may part of the Tijuana unit does not improve the correlation significantly also originate from the presence of surface water impoundments in the compared with the consideration of the US part only. 338 F. Lahet, D. Stramski / Remote Sensing of Environment 114 (2010) 332–344

2 4.2. Relationships between the plume area and various environmental examined. The maximum r corresponds to nLwthr(555) that increases parameters from 1.55 mW cm−2 μm−1 sr−1 (k=0.7) for the relationship involving −2 −1 −1 Vt (Fig. 4b) to 2.15 mW cm μm sr (k=0.5) for the relationship 2 Table 2 provides a summary of relationships between the plume involving Wt (Fig. 6d). The differences in the patterns of variation in r area, PA, and various environmental parameters for both MODIS for the two MODIS bands seen in Figs. 4 and 6 are not easily amenable to ̄ bands. In addition to the rainfall data, PWS and Vt, the parameters detailed explanation. Likely, these differences arise mostly from strong characterizing the Tijuana River flow, wind conditions, and tides are spectral variation in water-leaving radiance in response to variation in considered in this analysis. A multivariate analysis of more than two spectrally-dependent inherent optical properties (IOPs) of water. The variables at a time was not conducted because the number of available water-leaving radiance at different wavelengths is also dependent to a data is too small. The highest values of r2 (>0.75) are found for the different extent on the vertical structure of IOPs. linear relationships between PA and the accumulated rainfall, Vt, the The estimates of plume area calculated from each MODIS image in accumulated wind speed, Wt, and the accumulated zonal wind stress, both bands using the optimum values of nLwthr based on the correlation τEW,t. Weak correlation is observed between PA and the tidal phase analysis involving the parameters Vt, Q,andWt are compared in Fig. 7. and no significant correlation for the meridional wind stress. Among For the 645 nm band there is just one sets of data points illustrating PA645 ̄ the daily values of environmental parameters, only the rainfall, PWS, because the optimum nLwthr(645) is the same for all three environ- and Tijuana River flow, Q, show significant correlation with PA mental parameters considered (see Table 2). For the 555 nm band the 2 (r =0.53–0.63). The Tijuana River flow is the only parameter for three sets of data points representing different estimates of PA555 which the accumulated values Qt do not correlate better with PA than correspond to different optimum values of nLwthr(555) associated with the mean daily values Q. In addition, our data set shows no correlation the three parameters (see Table 2). Although the compared estimates of (r2 is only 0.0039) between the mean daily rainfall within the Tijuana PA differ to some extent, similar patterns of variability in the several hydrologic unit and the mean daily discharge of Tijuana River. A estimates of PA shown in Fig. 7 are not surprising as the environmental possible explanation is the diversion, prior to reaching the Tijuana variables covary to a large extent during rainstorm events (Fig. 3). Estuary, of up to 45,500 m3 per day of the Tijuana River flow into the Fig. 7 also shows that the plume areas calculated from the MODIS International Wastewater Treatment Plant. This flow is then treated imagery at 645 nm are generally smaller than those calculated from and released through an offshore outfall, so there is no Tijuana River imagery at 555 nm. In particular, PA645 is consistently smaller (by 8– 3 outflow into the ocean until the flow volume exceeds about 45,500 m 100%) than the PA555 estimates based on Vt and Q for all MODIS per day. Generally, this corresponds to more than about 2.5 mm of images examined. Only a small number of PA555 estimates based on rainfall (Jan Svejkovsky, personal communication). Wt are somewhat smaller than the PA645 estimates (see the data for 2 The variation of r as a function of nLwthr for the relationships MODIS images 13–16 in Fig. 7). The differences between the bands are between PA and Q and between PA and Wt are presented in Fig. 6. difficult to interpret in detail but not unexpected. The MODIS bands 1 2 Similarly to the results in Fig. 4, r shows large variation with nLwthr,and (645 nm) and 4 (555 nm) have different spatial resolution of 250 m also with k for the accumulated wind speed Wt. For the 645 nm band, and 500 m at nadir, respectively. The higher resolution has naturally 2 the maximum r is reached at the same value of nLwthr(645)= better potential for adequately resolving plume features, so the use of −2 −1 −1 0.55 mW cm μm sr for the three relationships: PA645 vs. Vt 250 m band is advantageous from that standpoint. In addition, the (Fig. 4a), PA645 vs. Q (Fig. 6a), and PA645 vs. Wt (Fig. 6b). The k values for different wavelengths imply differences in the depth of the upper Vt and Wt, which yield the maximum correlation, are also about the ocean layer “seen” by MODIS in these bands. Because of significantly same (0.5 and 0.55). This is not the case when the 555 nm band is higher water absorption in the red compared with green wavelengths,

Table 2 2 ̄ Results from the linear regression analysis between the plume area (PA645 and PA555 in km ) and the rainfall (PWS and Vt), the Tijuana River discharge (Q and Qt), the wind speed

(W and Wt), the zonal and meridional wind stress (τEW, τEW,t, τNS, and τNS,t), and the tidal phase (TP).

2 Parameter r nLwthr Linear equation

nLwthr and k ̄ Band 1 (645 nm) Rainfall (mm) 0.63 1.00 PA645 =1.631⁎PWS +2.354

0.77 (0.55; 0.5) PA645 =1.226⁎Vt +2.066 3 −1 River ﬂow (m s ) 0.56 0.55 PA645 =0.6318⁎Q+11.39

0.11 (0.30; 0.5) PA645 =0.3437⁎Qt +38.92 −1 Wind speed (m s ) 0.10 0.45 PA645 =−7.497⁎W+48.89

0.83 (0.55; 0.55) PA645 =8.371⁎Wt −40.51 −1 −2 Zonal wind stress (kg m s ) 0.08 0.30 PA645 =−917.9⁎τEW +51.64

0.89 (2.00; 0.15) PA645 =80.43⁎τEW,t −0.4666 −1 −2 Meridional wind stress (kg m s ) 0.07 1.85 PA645 =−112.4⁎τNS +1.744

0.19 (0.40; 0.55) PA645 =747.4⁎τNS,t +20.33

Tidal phase (min) 0.45 0.30 PA645 =−0.08651⁎TP+72.27 ̄ Band 4 (555 nm) Rainfall (mm) 0.62 3.00 PA555 =1.455⁎PWS +0.9309

0.75 (1.55; 0.70) PA555 =1.236⁎Vt +10.22 3 −1 River ﬂow (m s ) 0.53 1.85 PA555 =0.6297⁎Q+17.53

0.36 (1.35; 0.05) PA555 =0.9154⁎Qt +42.53 −1 Wind speed (m s ) 0.09 1.85 PA555 =−6.792⁎W+47.14

0.79 (2.15; 0.5) PA555 =8.029⁎Wt −34.00 −1 −2 Zonal wind stress (kg m s ) 0.12 1.55 PA555 =−1123 ⁎τEW +48.53

0.84 (2.95; 0.05) PA555 =645.7⁎τEW,t −1.513 −1 −2 Meridional wind stress (kg m s ) 0.06 0.60 PA555 =2196 ⁎τNS +114.4

0.21 (1.60; 0.55) PA555 =797.3⁎τNS,t +25.96

Tidal phase (min) 0.43 1.60 PA555 =−0.08449⁎TP+65.24

The rainfall data represent average quantities obtained from measurements within the composite watershed WS7, which includes seven hydrologic units from the US part of Tijuana unit in the south to the San Dieguito unit in the north. For each environmental parameter (except for TP), the analysis was made for both the daily average value and the accumulated value (the latter denoted by subscript t). Results are presented for two MODIS bands and include: the coefﬁcient of determination, r2, the optimum threshold value of normalized − 2 − 1 − 1 water-leaving radiance, nLwthr (in mW cm μm sr ), the parameter k, and the best ﬁt linear equation. F. Lahet, D. Stramski / Remote Sensing of Environment 114 (2010) 332–344 339

Fig. 6. The coefﬁcient of determination, r2, of the linear relationship between the plume area, PA, and environmental factors as a function of the threshold value of satellite-derived normalized water-leaving radiance, nLwthr. Panels (a) and (c) are for the relationship between PA and the mean daily discharge of Tijuana River, Q. Panels (b) and (d) are for the relationship between PA and the accumulated value of wind speed, Wt. In this case, the correlation curves are plotted for various values of parameter k. The left-hand panels are for the MODIS band 1 centered at 645 nm and the right-hand panels are for the band 4 at 555 nm.

Fig. 7. The plume area, PA, calculated for each of the eighteen MODIS images considered in this study. The calculations were based on the optimum threshold values of normalized water- −2 −1 −1 leaving radiance, nLwthr, given in Table 2. Speciﬁcally, the values of PA calculated from two MODIS bands are shown: for nLwthr(645)=0.55 mW cm μm sr based on correlation −2 analysis with accumulated precipitated water Vt (circles), mean daily discharge of Tijuana River Q (circles), and accumulated wind speed Wt (circles), and for nLwthr(555)=1.55 mW cm −1 −1 −2 −1 −1 −2 −1 −1 μm sr based on Vt (crosses), for nLwthr(555)=1.85 mW cm μm sr based on Q (triangles), and for nLwthr(555)=2.15 mW cm μm sr based on Wt (solid circles). The consecutive MODIS image numbers from 1 through 18 at the bottom horizontal axis correspond to dates of image acquisition (see Table 1). The time period of our study from December 28, 2004 through March 7, 2005 is indicated at the top axis. 340 F. Lahet, D. Stramski / Remote Sensing of Environment 114 (2010) 332–344

Fig. 8. MODIS images illustrating the spatial extent of turbid plumes observed during rainstorm events in the San Diego region. The images were acquired at the MODIS band 1 centered at 645 nm on the dates indicated in the upper right corner of the graphs. The study area is contained within the white box. Plume pixels are shown in white. Black pixels correspond to the lack of valid ocean color data. Land is shown in grey. The upper map on the left-hand side also shows the location of several geographic features and components within the region: Mission Bay (MB), San Diego River mouth (SDR), Point Loma (PL), San Diego Bay (SDBa), Tijuana River (TR), the US–Mexican border (B), and Los Buenos Creek mouth (LBC). the surface layer seen within the 645 nm band is expected to be We selected six MODIS images to demonstrate characteristic plume shallower than within the 555 nm band. Remote sensing at different features during two rainstorm events in the study area. Southerly winds wavebands is also differentially sensitive to variations in water optical force northward near-shore currents resulting in northward plume properties associated with particulate and dissolved materials. Aerial propagation; northerly winds result in plumes extended southward. multispectral imagery shows spectral reflectance differences between The image of December 30, 2004 (Figs. 8a and 9a) illustrates the plumes that are freshly discharged and older parts of the plumes. advection of the plume toward the north/northwest and the image of Fresh plumes reflect more light at longer wavelengths than older January 12, 2005 (Figs. 8b and 9b) towards the south. Both images were plumes (Jan Svejkovsky, personal communication). This observation acquired during the same intense rainstorm event that lasted more than can likely be attributed to sinking of suspended sediments. This two weeks. The four remaining images (01/29/2005, 01/31/2005, 02/ process is more intensive in the thin upper layer and, as such, might 02/2005, and 02/03/2005, Figs. 8c–fand9c–f) illustrate the progression be easily resolved by remote sensing at longer wavelengths. from plume formation during a less intense storm event to advection towards the south and dispersion after the event. Fig. 8 shows the 4.3. Characterization of plumes during selected rainstorm events images at the 250 m spatial resolution obtained within the 645 nm waveband. Fig. 9 shows the 500 m resolution data within the 555 nm In southern California, rainstorms are usually short episodic events waveband. The plume is represented by white pixels with the occurring in winter. The turbid plumes associated with inputs of ter- normalized water-leaving radiance greater than the optimum threshold rigenous and anthropogenic materials into the coastal ocean can persist values determined from the relationships PA vs. Vt (see Table 2). The for several days, and occasionally perhaps weeks (Nezlin et al., 2005; maps of surface currents for the days of image analysis are shown in Warrick et al., 2007). Freshwater from rivers and streams quickly Fig. 10. stratifies into a buoyant plume when it reaches the ocean, where the dispersal transport depends primarily on river plume inertia, wind, and 4.3.1. MODIS images of December 30, 2004 and January 12, 2005 current forcing (Washburn et al, 2003; Warrick et al., 2004a, Nezlin & December 30, 2004 was the third day of the first intense rainstorm DiGiacomo 2005; Warrick et al., 2007). event that occurred during the investigated period (Table 1). From the F. Lahet, D. Stramski / Remote Sensing of Environment 114 (2010) 332–344 341

Fig. 9. As in Fig. 8 but for the MODIS band 4 centered at 555 nm. beginning of this event on December 28, 2004 until its end on January Shelf (Los Angeles area) showed that bottom sediments are effectively 12, 2005, it rained almost every day in the San Diego and Tijuana resuspendedbywavesandcurrentsatbottomdepthslessthanabout ̄ watersheds. On December 30, PWS was about 3.3 mm and Vt about 15 m (Washburn et al., 1992). In our study area such shallow bathymetry 55 mm. On December 28 and December 29, heavy rains with daily occurs generally within a narrow zone along the shore. Somewhat larger precipitation of 19 mm and 45 mm respectively, and wind speeds offshore extent of shallow depths occurs off the entrance to San Diego Bay >6 ms−1 were observed (Fig. 3). The winds were blowing from the and off the Tijuana River mouth (see Fig. 1). southeast on December 28 and then from the southwest on December January 12, 2005 was the last day of the rainstorm event that 29 and 30. The average wind speed decreased to ∼1.8 ms−1 on started over two weeks earlier. Before the acquisition of the MODIS 3 −1 ̄ December 30. Q was very low before the storm (<0.4 m s since image on January 12, PWS ranged from 9 to 16 mm from January 7 December 15), increased markedly on December 29 (4.1 m3 s−1), and through January 10, and reached 30 mm on January 11 (Fig. 3). This 3 −1 reached a maximum of about 100 m s on December 30 (Fig. 3). The explains high values of Vt of about 50 mm on January 12. There was a ̄ 3 −1 latter value is the highest observed during the investigated time period. light rain on January 12 with PWS of 4.12 mm. Q was less than 8 m s Current data within the study area on December 30 indicates that the during the preceding week but reached 49 m3 s−1 on January 12. Winds direction was generally northwest and magnitude was ∼25 cm s−1 between 3.5 and 6.7 ms−1 were blowing from the southeast from (Fig. 10a). January 7 through January 10. The average wind speed increased on MODIS images acquired on December 30 suggest that the plume was January 11 (∼7.3 ms−1) and the direction changed to southwest. On advected north to northwest (Figs. 8a and 9a). The plume area is 60– January 12 the wind direction changed to northwest and the speed 76 km2 and the offshore extent exceeds 12 km at the S1 section located decreased to ∼2.5 ms−1. At the northern end of the study area, currents near Point Loma entrance to the San Diego Bay (Table 3, Fig. 1). The spatial of about 30 cm s−1 were flowing southwest (Fig. 10b). In the southern structure of the plume appears to reflect sources of turbid water discharge part, the direction of currents varied generally with the distance from from Tijuana River (TR), San Diego Bay (SDBa), and San Diego River (SDR) coastline from southward to southeastward, and to southwestward. The north of the study area (see Fig. 8a). This structure is most likely magnitude of currents generally decreased towards the south. dominated by the combination of inertia-related effects and northward Consistent with the general pattern of currents and winds are the current forcing. Resuspension processes in areas with relatively shallow MODIS images of January 12, which show an advection of the plume bathymetry may have also contributed to plume turbidity given that the towards the south (Figs. 8b and 9b). Compared to December 30, the winds exceeded 6 ms−1 on preceding days. The study on the San Pedro plume on January 12 extends significantly further south, well beyond the 342 F. Lahet, D. Stramski / Remote Sensing of Environment 114 (2010) 332–344

Fig. 10. Mean daily surface currents obtained from measurements with HF radars located in four different locations within the region (see text for details, the figures provided by the San Diego Coastal Ocean Observing System). The current fields are shown for the same dates as those in Figs. 8 and 9. study area. The plume is large with an area comparable to that observed 4.3.2. Sequence of MODIS images from January 29, 2005 through two weeks before (Table 3). The offshore extent of the plume is similar February 3, 2005 (∼7–8 km) throughout much of the study area. The second rainy episode during the investigated time period occurred at the end of January 2005 and lasted 5 days (see Table 3). Table 3 Compared to the previous rainstorm, this event was less intense with Area (PA) and offshore extent (S1, S2, S3, and S4) of the plume calculated from MODIS fl images at bands 1 and 4 within the study area. daily precipitation in the range from 0.3 to 6.7 mm, river ow from about zero to 0.74 m3 s−1, and winds up to about 4 ms−1 with variable 2 PA (km ) S1 (km) S2 (km) S3 (km) S4 (km) direction alternating between northwest and southwest (Fig. 3). On Band 1 (645 nm) 12/30/04 60.2 12.75 5.75 3.50 1.50 January 29, the last day of the event, PWS̄ was about 4 mm, Vt was in the 01/12/05 57.0 8.75 5.50 8.50 6.75 range 8–9 mm, and the wind was blowing from the northwest. The 01/29/05 20.4 0 3.50 4.00 ND −1 01/31/05 16.7 2.50 ND 3.00 1.50 currents of about 13 cm s were oriented southeast (Fig. 10c). There 02/02/05 3.29 0 0 1.75 ND was still a very weak rain on January 31 (PWS̄ =0.28mm)butnorainon 02/03/05 0.56 ND ND ND ND the following days. Vt showed a significant decrease after January 29. Band 4 (555 nm) 12/30/04 76.0 12.50 6.50 3.50 1.50 Weak northwest winds (∼2ms−1) were observed from January 30 01/12/05 89.6 7.50 7.50 8.00 7.00 through February 1. On February 2 and 3, the winds increased to ∼4– 01/29/05 56.3 6.50 5.00 5.00 3.50 −1 01/31/05 37.2 6.50 4.50 3.50 3.50 5ms and changed direction to northeast. The current data show 02/02/05 20.8 5.00 1.50 2.50 2.00 predominantly southward flow during that period (Fig. 10d–f). 02/03/05 2.96 ND ND ND ND The sequence of four MODIS images for the period of January 29

The plume area was calculated from the optimum threshold values of nLwthr and through February 3 illustrates how the plume was advected towards the parameter k corresponding to the relationships PA vs. Vt (see Table 2). The offshore extent south after its formation during a moderate rain event, and eventually of the plume was estimated across four sections (see also Fig. 1): S1 located at Point Loma dispersed to the point below the defining threshold on February 3 latitude (32°40′N, 117°10′W), S2 between Point Loma and Tijuana River mouth (32°37′N, (Figs. 8c–fand9c–f). Under very low or no precipitation and low 117°08′W), S3 at Tijuana River mouth (32°33′N, 117°08′W), and S4 between Tijuana River mouth and the southern end of the study area (32°29′N, 117°07′W). ND indicates no valid discharge from Tijuana River, the evolution of the plume was linked satellite data. primarily to the direction and strength of the wind and alongshore F. Lahet, D. Stramski / Remote Sensing of Environment 114 (2010) 332–344 343 currents. The images from January 29 through February 2 clearly show from MODIS band 1 at 645 nm. These differences can be attributed that the plume elongates along the north–south direction and is being largely to differences in the inherent optical properties of seawater in transported towards the south (Figs. 8c–eand10c–e). On February 3 the green and red wavebands, which result in differences in the depth of only a small number of plume pixels were identified. This result can be the upper ocean layer “seen” in these bands. The differences in the attributed to the main mechanisms of plume disappearance, which spatial resolution (250 m for band 1, 500 m for band 4) also play a role. include dispersion and dilution with ambient waters, and settling of The use of both bands offers advantages. Whereas the 645 nm band suspended particulate matter. provides information with higher spatial resolution and appears to For the images showing a sizeable plume, the plume area is better reveal the location of distinctive sources of runoff along the significantly smaller in the 645 nm band compared with the 555 nm coastline, the remotely-sensed information at the 555 nm band origi- band, which is consistent with the data from the previous rainstorm nates within a thicker layer of surface water compared with 645 nm (Table 3). The image in the 645 nm band appears to better reveal the band. discharge sources of turbid waters than the 555 nm band. On January 29 the plume seen in the 645 nm band is broken up into three parts, Acknowledgements which are not as readily observed in the 555 nm band. The three parts seen in the 645 nm band appear to be associated with the San Diego This study was supported by the National Aeronautics and Space Bay (small plume near Point Loma), Tijuana River (large plume in the Administration (Earth Observing System Interdisciplinary Science central part of the image), and Los Buenos Creek and the city of Program, NASA EOS/IDS Grant NNG04GK50G awarded to Dariusz Rosarito (plume features south of the study area where the image is Stramski). We would like to thank the NASA Goddard Space Flight partly obscured by significant cloud cover). This latter plume is Center for the production of MODIS images. We thank Eric Terrill and actually well seen in the next image of January 31. Mark Otero from the San Diego Coastal Ocean Observing System at Scripps Institution of Oceanography for river discharge and surface 5. Conclusions current data. Precipitation data were provided by Rand Allan from the County of San Diego, Department of Public Works, Raúl Larios, High correlation between the area of turbid plumes estimated from Alejandro González, Javier Espinosa from the Comisión Nacional del MODIS satellite imagery in the San Diego coastal region and several Agua in Mexico, the National Oceanic and Atmospheric Administra- environmental factors, such as rainfall, river flow, and wind speed, tion National Climatic Data Center Climate Data Online (NCDC/NNDC supports earlier studies showing that optical remote sensing can serve CDO), and the United States Geological Survey (USGS). We also thank as a means for monitoring a discharge of terrigenous and anthropogenic Nikolay Nezlin from Southern California Coastal Water Research particulate and dissolved materials and subsequent evolution of turbid Project, Jan Svejkovsky from Ocean Imaging Corp., Rick Reynolds from plumes in the coastal ocean during rainstorm events. 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