A novel method for characterizing harmful algal blooms in the Persian Gulf using MODIS measurements

Accepted Manuscript A novel method for characterizing harmful algal blooms in the Persian Gulf using MODIS measurements Mohsen Ghanea, Masoud Moradi, Keivan Kabiri PII: DOI: Reference:

S0273-1177(16)30284-8 http://dx.doi.org/10.1016/j.asr.2016.06.005 JASR 12780

To appear in:

Advances in Space Research

Received Date: Revised Date: Accepted Date:

23 January 2016 31 May 2016 6 June 2016

Please cite this article as: Ghanea, M., Moradi, M., Kabiri, K., A novel method for characterizing harmful algal blooms in the Persian Gulf using MODIS measurements, Advances in Space Research (2016), doi: http://dx.doi.org/ 10.1016/j.asr.2016.06.005

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A novel method for characterizing harmful algal blooms in the Persian Gulf using MODIS measurements Mohsen Ghanea a, Masoud Moradi a, Keivan Kabiri a a

Department of Marine Remote Sensing, Iranian National Institute for Oceanography and Atmospheric Science, Tehran, Iran. The Corresponding Author: Mohsen Ghanea Email Address: [email protected] or [email protected] Email Address of other authors: [email protected] and [email protected] Phone Number: +989132037975

KEY WORDS: Harmful algal bloom, Cochlodinium polykrikoids, MODIS, Ocean color remote sensing, Spectral signature, Persian Gulf.

ABSTRACT: Biophysical properties of water undergo meaningful variations under red tide (RT) outbreak. A massive Cochlodinium polykrikoids RT began in the eastern Persian Gulf (PG) in October 2008 and extended to the northern PG in December 2008. It killed large fish and hampered marine industries and water desalination appliances. Yet monthly averages of satellite-derived Chl-a (Chlorophyll-a), nFLH (normalized Fluorescence Line Height), and Kd490 (diffuse attenuation 1

coefficient at 490 nm) have not been compared in the PG. MODIS (MODerate Resolution Imaging Spectroradiometer) sensor provides global coverage, with short revisit time, and accessible, well validated ocean color products. This study compares the behavior of MODIS Chl-a, nFLH, and Kd490 in both normal and RT conditions. In doing so, their color maps are shown during normal and RT periods. Then, monthly variations of these products are shown as time-series between 2002 and 2008. HOCI (Hybrid Ocean Color Index) is defined by integrating these products to detect RT affected areas. The results gained from 100 locations in the PG show that HOCI >0.18 mW cm-2 µm-1 sr-1 mg m-4 and nFLH >0.04 mW cm-2 µm-1 sr-1 discriminates non-bloom waters from algal blooms. Rrs(443)/Rrs(412) > 1 is a proper statement to separate T. erythtraeum from N. millaris, N. scintillans, and diatoms. Rrs(667)/Rrs(443) >1 can differentiate C. polykrikoids from T. erythtraeum, N. millaris, N. scintillans, and diatoms as well. So, the combination of HOCI and Rrs(667)/Rrs(443) ratio is useful for detection and quantization of C. polykrikoids.

1.

INTRODUCTION

Algal bloom is a rapid increase in the number of phytoplankton species in estuarine, marine and fresh waters (Al-Muhairi et al. 2010), without concern over bloom impacts (Smayda, 1997). Harmful algal bloom or red tide (RT) is a bloom including toxic phytoplankton species with deleterious impacts (Smayda, 1997; Dierssen et al., 2006). It can affect marine life and human health by fish mortality and irritating the eyes. Furthermore, it can damage desalination plants and respiratory systems (Richlen et al., 2010; Al-Shehhi et al., 2011 and 2013). Sun light and nutrient loading are triggering factors for phytoplankton growth. Phytoplankton concentrations are

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influenced by marine currents, dust, and monsoonal winds (Brink et al., 1998; Wiggert et al., 2010; Al-Azri et al., 2010 and 2014; Al-Shehhi et al., 2011; Zhao and Ghedira, 2014). Mortality of marine organisms due to RT occurrence is common in the PG (Thangaraja, 1998; ROPME, 2003). Earlier studies have reported 38 taxa, including 18 for the species level and the others for the genus level in the PG (Al-Hasan et al., 1990; Rezai, 1995; Thangaraja et al., 1998). According to historical research, Trichodesmium, dinofelagellate (Cochlodinium polykrikoides and Noctiluca miliaris), and diatoms are the main species in the PG (Gomes et al., 2008). In October 2008, a widespread harmful algal bloom happened in the PG. It started from the Masqat coastlines in the Oman Sea and expanded to the most parts of the PG in several months (Richlen et al., 2010; Moradi and Kabiri, 2012; Zhao et al., 2015). The toxic C. polykrikoides bloom was the dominant species in the PG during the RT period (Richlen et al., 2010). It killed thousands of fish and marine mammals (Berktay, 2011) and damaged coral reefs, marine filtration and desalination plants (WDR, 2008). Upwelling circulation and dust deposition were significant sources of nutrient supply during the RT period (Zhao and Ghedira, 2014). Yet it is unknown to explain triggering factors of C. polykrikoides bloom in the PG (Moradi and Kabiri, 2012; Zhao and Ghedira, 2014). Monitoring RT is significant for environmental, ecological, and biological management of water regions. Satellite data is low-cost and efficient to generate daily ocean color products in synoptic coverage. MODIS (MODerate Resolution Imaging Spectroradiometer) sensor has been mounted on Terra (since 1999) and Aqua (since 2002). It monitors oceanographic phenomena by Chla (Chlorophyll-a), nFLH (normalized Fluorescence Line Height), and Kd490 (diffuse attenuation coefficient at 490 nm). These products are derived from MODIS Rrs (remote sensing reflectance) in 3

different bands. Earlier research estimated algal biomass by MODIS OC3 algorithm (O’Reilly et al., 1998, Carder et al., 1999, 2004). Al-Kaabi et al. (2013) estimated Secchi disk depth by MODIS Kd490. Secchi disk depth is a criterion to estimate water turbidity. Daily overpass times (at 10:30 local time by Terra and at 13:30 local time by Aqua) help researchers to investigate diurnal changes of ocean phenomena (Salomonson et al., 2001). Most of earlier studies in the PG utilized in situ data (Thangaraja, 1998; ROPME, 2003; Richlen et al., 2010; Al-Azri et al., 2010, 2013). In recent years, an increasing number of studies applied satellite data to monitor RT in the PG (Moradi and Kabiri, 2012; Al-Shehhi et al., 2013; Zhao and Ghedira, 2014; Zhao et al., 2015; Ghanea et al., 2015). Moradi and Kabiri (2012) compared MODIS FLH and Chl-a with in situ Chl-a in the eastern PG during the 2008 RT. They showed a high correlation between FLH and in situ Chl-a during the RT outbreak. There was a lower correlation between MODIS and in situ Chl-a due to effects of CDOM (Color Dissolved Organic Material) and shallow bottom. Therefore, FLH better detects RT affected areas in CDOM-rich waters. They characterized RT affected areas by nFLH >0.18 mW cm-2 µm-1 sr-1 and Chl-a anomaly >1 mg m-3. Chl-a anomaly is the difference between the current Chl-a and a two-month average value for two weeks ago (Stumpf et al., 2003). Zhao et al. (2015) developed a ratio index called as MFLH (Modified Fluorescence Line Height) through MERIS Rrs at 665, 681, and 754 nm. Due to lower wavelength baseline of MFLH, correlation between MFLH and in situ Chl-a was higher (= 0.53) than MCI (Maximum Chlorophyll Index) (= 0.038) and FLH (= 0.21). Similar to FLH, MFLH was effective to alert RT in CDOM-rich waters and could not distinguish RT affected areas in suspended sediment (SS) rich waters (Zhao et al., 2013). So, Zhao et al. (2015) used ERGB (Enhanced Red-Green-Blue) image and bbp (560) (particulate backscattering at 560 nm) to mask SS-rich waters. These waters 4

were observed as bright colors in ERGB image and had high bbp (560). In addition, they integrated ERGB, MFLH, true color composite, and bbp (560)/MFLH ratio to differentiate Cochlodinium from diatoms, Noctiluca, and Trichodesmium. Cochlodinium bloom was characterized by MFLH >0.04 mW cm-2 µm-1 sr-1, bbp (560)/ MFLH ratio <0.2 mW-1 cm2 µm m-1 sr, reddish brown color in true color, and dark color in ERGB. This study monitors MODIS Chl-a, nFLH, and Kd490 for both normal and RT conditions from the eastern to northern PG. In doing so, we investigate monthly averages of these products during 2002 to 2008. Then, their trends are compared in both normal and RT situations. According to the regression lines among these products in the RT conditions, HOCI (Hybrid Ocean Color Index) is defined. HOCI is compared with MODIS products for 30 locations in different parts of the PG. Besides, MODIS spectral signature from 412 to 678 nm is studied for these locations. It determines a spectral attribute to distinguish toxic C. polykrikoids blooms from other blooms such as T. erythtraeum, N. millaris, N. scintillans, and diatoms. A statistical analysis is carried out to assess mentioned products and indices for 100 locations in the PG.

2.

DATA AND METHODS

2.1. Study Area Fig. 1 shows the study area from east (the Strait of Hormuz) to north (Bandar-e Kangan offshore) of the PG. According to earlier reports of Iranian Fisheries Science Research Institute and Iranian National Institute for Oceanography and Atmospheric Science, no RT (or harmful algal blooms) happened in this study area between August 2002 and September 2008. The C. polykrikoids blooms (as a RT outbreak) started from the Strait of Hormuz in October 2008 and extended to the 5

northern PG in December 2008. The RT covered an area of ~86462 Km2 in late December 2008 (Zhao et al., 2015). The abundance of C. polykrikoids in the RT conditions exceeded 105 cells l-1 (Moradi and Kabiri, 2012). So, we considered three sub-regions in the eastern (Bandar-e Abbas offshore), middle (Lavan Island offshore), and northern (Bandar-e Kangan offshore) PG to investigate the effects of RT on MODIS products in different parts of study area. RT period for each sub-region is the time period when that sub-region is influenced by the 2008 RT. Normal period for each sub-region is the time period while that sub-region is not affected by RT activities between August 2002 and December 2008. Fig. 1. 2.2. Satellite Data Processing We got daytime MODIS Aqua and Terra level 2 (L2) data at 1 km spatial resolution from NASA data archive (http://ladsweb.nascom.nasa.gov/data) between 2002 and 2008. NASA OBPG (Ocean Biology Processing Group) processed these data using multi-sensor L1 to L2 conversion, updated atmospheric correction and geolocation algorithms, and instrument calibration (O’Reilly et al., 2000). Land, cloud masks, and L2 flag algorithm were applied to exclude pixels with bad quality. Chl-a, Kd490, and nFLH were estimated through the OC3 band ratio (O’Reilly et al., 2000), Morel et al. (2007), and the baseline subtraction (Behrenfeld et al., 2009) algorithms, respectively. 2.3. Methods Due to heavy cloudiness, aerosol, and water vapor conditions, Aqua and Terra satellites do not cover many areas of the PG in some days during summer. The values of water vapor and aerosol in the PG during summer are more than those values in fall (Ghanea et al., 2016). MODIS bio-optical products with the time shift over 4 hours (between satellite overpass and in situ measurements) 6

cannot properly retrieve bio-optical properties in turbid waters to detect red tide. For turbid waters, Darecki and Stramski (2004) showed that MODIS Chl-a with the time shift of 4-8 hours was often >2 mg m-3 than in situ Chl-a. So, we developed a proposed program in MatlabTM software to filter out data with high cloud coverage (>50%) over each sub-region. The number of days including qualified data for August and September is less than that number for October, November, and December (Fig. 2). No qualified data was available for August in some years. Monthly average of Chl-a, nFLH, and Kd490 were then calculated for each sub-region from August 2002 to December 2008. Scatter plots of Chl-a, nFLH, and Kd490 versus each other are plotted to analyze their behavior in the normal and RT conditions. HOCI is defined by integrating these products (Eq. 1). As previous products, the same processing was done to calculate monthly average of HOCI.

HOCI = Chl - a × K d490 × nFLH (1)

Afterward, L2 products were projected in the WGS84 coordinate reference system for the dates before and during the 2008 RT period. We then extracted a subset of data covering the PG and generated color maps of all products, HOCI and ERGB image using NASA-SeaDAS 7.0 software. ERGB image was generated by Rrs at 547 (R), 488 (G), and 443 (B) nm which have been stretched to the same scale. HOCI are compared with all products for 30 locations in different parts of the PG. We also display MODIS spectral signature from 412 to 678 nm and Rrs(667)/Rrs(443) ratio in these stations. Finally, we assess all mentioned products and indices in 100 locations of the PG during early and peak days of RT period. Fig. 2. 7

3.

RESULTS AND DISCUSSION

Fig. 3 shows color maps of MODIS L2 products spanning the period from October 2008 to December 2008. In middle October 2008, bloom patches entered the Strait of Hormuz at the eastern PG. On October 27, 2008, C. polykrikoids blooms covered the most areas of the Strait of Hormuz. Then, they extended towards the middle PG in November 2008. On December 23, 2008, the RT reached the northern PG. Algal bloom waters in Fig. 3 are characterized by high values of Chl-a (>5 mg m-3), nFLH (>0.04 mW cm-2 µm-1 sr-1), Kd490 (>0.4 m-1), HOCI (>0.18 mW cm-2 µm-1 sr-1 mg m-4), and dark colors in ERGB images. We have a discuss about these thresholds in subsequent sub-sections. Fig. 3.

3.1. Detection of algal bloom waters Fig. 4 represents monthly averages of three MODIS products in all sub-regions from August 2002 to December 2008. Monthly average of Chl-a was <5 mg m-3 during normal period except for sub-region 1 in October 2004 (= 6.6 mg m-3) and sub-region 2 in September 2005 (= 8.5 mg m-3) (Fig. 4a, 4b, and 4c). However, nFLH had low monthly averages (~0.02 mW cm-2 µm-1 sr-1) in these two months. Therefore, this unexpected change in Chl-a concentration should be due to an overestimation error. In nearshore, higher amounts of CDOM than phytoplankton cause to increase absorption at the blue band (= 443 nm) (Moradi and Kabiri, 2012; Zhao et al., 2015). This

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strong absorption increases Chl-a concentration estimated by OC3 algorithm. Chl-a and CDOM are revealed as dark colors in ERGB image because its blue band is at 443 nm. Monthly average of nFLH was <0.04 mW cm-2 µm-1 sr-1 during normal period except for sub-region 2 in December 2002 (= 0.041 mW cm-2 µm-1 sr-1) and August 2007 (= 0.047 mW cm-2 µm-1 sr-1) (Fig. 4g, 4h, and 4i). These high amounts of nFLH did not prove the presence of algal blooms because monthly averages of Chl-a and Kd490 were <1 mg m-3 and <0.2 m-1, respectively (Fig. 4b and 4e). High concentrations of SS (>5 mg L-1) increase fluorescence signal at the red band (McKee et al., 2007). This increase is due to high turbidity in SS-rich waters (Hu et al., 2011). SS itself does not fluoresce, but its effect on the surrounding light field can obscure the phytoplankton fluorescence signal. Hence, high values of nFLH in these two months should be due to high concentrations of SS including dust deposition over the PG. Ezzati et al. (2012) show that dust deposition over the PG is ~ 4.84 g m-2 yr-1. Fig. 4.

To compare the monthly behavior of these three products with each other, Fig. 5 illustrates their scatter plots in all sub-regions from August 2002 to December 2008. According to Fig. 2, the total number of months including qualified data (in all sub-regions) for the normal and RT conditions were 90 and 6, respectively. The linear regression functions were best fitted with least-square method. According to the linear regressions plotted in Fig. 5a, Kd490 had a near-perfect correlation (R2 >0.9) with Chl-a in both RT and normal conditions. This high correlation did not decrease in CDOM-rich waters. Hence, phytoplankton and CDOM play significant roles in increasing water turbidity or Kd490. 9

nFLH had no meaningful correlation (R2 <0.05) with Chl-a and Kd490 during normal period (Fig. 5b and 5c). Similarly, Zhao et al. (2015) collected 46 samples in the PG and showed that MERIS FLH had weak correlation (R2 = 0.21) with low concentrations of in situ Chl-a (<3.3 mg m-3). Their correlation was a little more than our correlation because their correlation was calculated by hyperbola function. nFLH was not sensitive to CDOM because CDOM has negligible absorption at the red band (Zhao et al., 2009; Hu et al., 2011). Consequently, it can better discriminate RT affected areas in CDOM-rich waters (Hu et al., 2005; Moradi and Kabiri, 2012). On the other hand, a near-perfect correlation (R2 >0.9) was observed among nFLH, Chl-a, and Kd490 during RT period (Fig. 5b and 5c). Accordingly, high correlation among these products can be a proper criterion to find out RT affected areas. Fig. 5.

During normal period, nFLH was usually between 0.01 and 0.03 mW cm-2 µm-1 sr-1. In some months, it was >0.04 mW cm-2 µm-1 sr-1 while monthly averages of Chl-a and Kd490 were <5 mg m-3 and <0.4 m-1, respectively (Fig. 5b and 5c). For example, monthly average of nFLH for sub-region 2 was >0.04 mW cm-2 µm-1 sr-1 during December 2002 and August 2007 while monthly averages of Chl-a and Kd490 were <5 mg m-3 and <0.4 m-1 (Fig. 4b, 4e, and 4h). This increment of nFLH should be because of high concentrations of SS including dust deposited onto the water surface (>5 mg L-1). This means that nFLH alone is not a reliable index to detect algal blooms in SS-rich waters. In September 2005, high monthly averages of Chl-a (>5 mg m-3) and Kd490 (>0.4 m-1) as well as low monthly average of nFLH (<0.04 mW cm-2 µm-1 sr-1) for sub-region 2 (Fig. 4b, 4e, and 4h) should be due to the occurence of a CDOM plume (Hu et al., 2011; Moradi and Kabiri, 2012). So, these 9

products cannot individually discriminate bloom-laden from no-bloom waters. An algal bloom, whether harmful or not, will occur if the values of Chl-a, Kd490, and nFLH are high. According to above results, it is necessary to define a new index, which is least sensitive to CDOM and SS. Aforementioned products have a complementary behavior with each other. Hence, Hybrid Ocean Color Index (HOCI) is defined by Eq. 1. Fig. 6 shows the variation ranges of Chl-a, Kd490, nFLH, and HOCI during RT and normal periods. HOCI average was >1.47 mW cm-2 µm-1 sr-1 mg m-4 during the RT period in all sub-regions. HNA (High Normal Average) of a product is the highest monthly average of that product during the normal period. LRTA (Low Red Tide Average) of a product is the lowest monthly average of that product during the RT period. HNA and LRTA for each sub-region are calculated from the monthly averages of the products in Fig. 4. HNA of HOCI was <0.43 mW cm-2 µm-1 sr-1 mg m-4 in all sub-regions. LRTA of HOCI varied from 3 to 17 times more than HNA in different sub-regions. LRTA/HNA ratio for Chl-a, Kd490, and nFLH was significantly lower than that for HOCI. For sub-region 2, LRTA/HNA ratio was <1 for these MODIS products. This is why these products could not individually discriminate bloom-laden from nobloom waters in high concentrations of SS and/or CDOM. So, HOCI is a better index to detect algal blooms.

3.2. Characterization of C. polykrikoids and T. erythtraeum blooms Fig. 7 demonstrates color maps of Chl-a, nFLH, Kd490, and HOCI as well as ERGB image in the Strait of Hormuz on October 27, 2008. Red arrows in Fig. 7e show the bloom patches characterized by high concentrations of Chl-a and dark reddish color in ERGB image. We selected four stations 7 to 10

10 within these patches (Fig. 7f). In these stations, HOCI increases as Chl-a and Kd490 increase (Fig. 7h). Although nFLH is more than 0.05 ( = LRTA for sub-region 1) for these stations, it had an indeterminate behavior. For instance, nFLH value for station 8 (= 0.14 mW cm-2 µm-1 sr-1) is higher than that for station 9 (= 0.08 mW cm-2 µm-1 sr-1) while Chl-a concentrations for station 8 (= 23.6 mg m-3) is lower than that for station 9 (= 37.6 mg m-3). This means that nFLH cannot quantify intensive algal blooms with high concentrations of Chl-a (>20 mg m-3 ) (Matthews et al., 2012). Fig. 6.

Green arrows in Fig. 7e indicate areas including bright blue color in ERGB image. We chose stations 4 to 6 within these regions (Fig. 7f). High amounts of nFLH (> 0.09 mW cm-2 µm-1 sr-1) and bright color in ERGB image (Fig. 7f and 7h) indicate the presence of SS-rich waters in these stations (Hu et al., 2011). Low values of Chl-a (<5 mg m-3) and Kd490 (<0.4 m-1) reduced HOCI under 0.12 mW cm2

µm-1 sr-1 mg m-4 (Fig. 7h). Therefore, HOCI was not affected by high concentrations of SS. It was

observed as blue or cyan colors in these regions (Fig. 7d). Blue arrows in Fig. 7e represent shallow, turbid coastal waters around the Qeshm Island in the Strait of Hormuz. We selected three stations 1 to 3 around the Qeshm Island. The results show that nFLH value is more than LRTA (= 0.05 mW cm-2 µm-1 sr-1) in sub-region 1 (Fig. 7b and 7h). These high nFLH values were not due to the presence of bloom patches because the values of Chla and Kd490 were <3 mg m-3 and <0.2 m-1, respectively. These regions are revealed as bright colors in ERGB image (Fig. 7e). So, shallow SS-rich waters are available in stations 1 to 3 due to high nFLH value and bright color in ERGB image (Hu et al., 2011; Zhao et al., 2013). High concentrations of SS (> 5 mg L-1) cause to overestimate nFLH in turbid waters with low Chl-a (McKee et al., 2007). High 11

turbidity increases Rrs in whole visible spectrum. However, increase of Rrs(678) is lower than that of Rrs(667) for stations 1 to 3 (Fig. 7g). HOCI was <0.1 mW cm-2 µm-1 sr-1 mg m-4 in these regions (Fig. 7d and 7h) due to low concentrations of Chl-a (<3 mg m-3) and Kd490 (<0.2 m-1). Consequently, HOCI is effective to discriminate algal blooms in SS-rich waters. Fig. 8 shows similar color maps as shown in Fig. 7 for the middle PG on November 19, 2008. Northern waters had higher concentrations of Chl-a than southern ones. Red arrows in Fig. 8e show bloom patches as dark reddish color in ERGB image. Stations 7 to 10 were located within these regions. Similar to the corresponding stations in Fig. 7f, they had high values of Chl-a (>14 mg m-3), nFLH (>0.05 mW cm-2 µm-1 sr-1), Kd490 (>1.0 m-1), and HOCI (>1.0 mW cm-2 µm-1 sr-1 mg m4

). In contrast, higher Kd490 values caused to decrease Rrs at 531, 547, and 555 nm from 0.011 to

0.008 sr-1 (Fig. 7g and 8g). This decrease converted dark reddish to dark brownish color in ERGB image. Green arrows in Fig. 8e illustrate low-medium concentrations of algal blooms as dark grey color in ERGB image. We considered stations 4 to 6 within these parts. Chl-a concentrations for these stations were between 5 and 10 mg m-3 while HOCI values were between 0.1 and 0.5 mW cm-2 µm1

sr-1 mg m-4 (Fig. 8h). Chl-a, nFLH, and Kd490 have detected these algal blooms because their values

are more than their LRTA (Fig. 6b). HOCI color map shows these areas as cyan color due to lowmedium concentrations of algal blooms.

Fig. 7.

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Blue arrows in Fig. 8e represent SS-rich waters as similar as those arrows in Fig. 7e. Stations 1 to 3 were selected within these areas. Replacement of three stations in two sub-regions has not changed their spectral signature (Fig. 7g and 8g). Therefore, ERGB and spectral signature are effective to differentiate SS from algal blooms. Like earlier sub-region, nFLH is unsuccessful to detect algal blooms in SS-rich waters (Fig. 8b and 8h). Fig. 9 demonstrates a part of the northern PG affected by RT on December 23, 2008. Like Fig. 7 and 8, red arrows and stations 7 to 10 represent algal blooms with high concentrations of Chl-a. Increasing Kd490 in this sub-region reduced Rrs at 531, 547, and 555 nm under 0.005 sr-1 (Fig. 9g). It caused to appear a uniform dark grey color in ERGB image. So, spectral signature is unable to quantify different concentrations of algal blooms (Fig. 9g). Another difference between Fig. 9 and two previous figures is increasing Rrs in whole visible spectrum for stations 4 to 6 (Fig. 9g). These stations were located within dark regions in ERGB. They included high values of Chl-a (>10 mg m-3) and Kd490 (>0.7 m-1), and medium nFLH value (between 0.035 and 0.055 mW cm-2 µm-1 sr-1) (Fig. 9h). These values make HOCI higher than minimum HNA (= 0.18 mW cm-2 µm-1 sr-1 mg m-4 in Fig. 6). The spectral signatures of these stations are similar to Trichodesmium erythtraeum bloom (Fig. 10a). C. polykrikoids and T. erythtraeum species with high/medium Chl-a (>5 mg m-3) have a smooth increment in the magnitude from Rrs(443) to Rrs(531), high Rrs at 531 and 547 nm (Simon and Shanmugam, 2012), and HOCI > HNA. In addition, T. erythtraeum has a little trough at 667 nm (Simon and Shanmugam, 2012) and Rrs(667) < Rrs(443). Instead, C. polykrikoids contains a distinct trough at 667 nm, a peak at 678 nm (Simon and Shanmugam, 2012), and Rrs(667) > Rrs(443). These spectral attributes have not been observed in other species such as N. millaris, N. scintillans, and diatoms (Fig. 10a). Fig. 10a 13

represents a pattern of MODIS-derived spectral signature for different types of blooms in the PG, the Oman Sea, Indian ocean, and the East China Sea, according to earlier studies (Simon and Shanmugam, 2012; Dwivedi et al., 2015; Tao et al., 2015). In these studies, the above species were sampled in many field programs. MODIS-derived spectral signature was provided from the extents including algal blooms with high cell density (> 105 cells l-1). The value of Rrs(667)/(Rrs(443) for each type of algal blooms is shown in Fig.10b. Fig. 8. Fig. 9. We used the difference between Rrs(667) and Rrs(443) to differentiate toxic C. polykrikoids blooms from other blooms in the PG. According to Fig. 7i, 8i, 9i, and 10a, Rrs(667)/(Rrs(443) is >1 for C. polykrikoids blooms due to high phytoplankton absorption at 443 nm and high chlorophyll reflectance at 667 nm. However, Rrs(667)/Rrs(443) is not a proper index to quantify C. polykrikoids blooms. For instance, HOCI value for station 7 is lower than that for station 8 while Rrs(667)/Rrs(443) for station 7 is higher than that for station 8. As an alternative, HOCI is able to quantify C. polykrikoids blooms. Hence, the combination of HOCI and Rrs(667)/Rrs(443) is valuable for both discrimination and quantization of different algal blooms. Rrs(443)/Rrs(412) is >1 for T. erythtraeum while it is <1 for N. millaris, N. scintillans, and diatoms due to high phytoplankton absorption at 443 nm (Dwivedi et al., 2015). So, this ratio is suitable to distinguish T. erythtraeum from N. millaris, N. scintillans, and diatoms. Fig. 10c shows a scheme to differentiate C. polykrikoids and T. erythtraeum blooms from other blooms and non-blooms in the PG. In addition to Rrs and HOCI, nFLH is used in this scheme to detect CDOM and SS. Fig. 10. 14

For further investigation of aforementioned products and indices, we selected 50 locations within the PG in two dates (on October 27, 2008 and December 23, 2008) (Fig. 11a and 11b). The first and second dates were chosen during the early and peak periods of RT occurrence, respectively. Fig. 11c shows that Rrs(667)/Rrs(443) was <1 for 44 locations. So, 6 locations were just located within C. polykrikoids affected areas. In two locations as shown in Fig. 11c, HOCI was <0.18 mW cm-2 µm-1 sr-1 mg m-4 (= the minimum HNA of HOCI in Fig. 6). This means that these locations involved C. polykrikoids with low Chl-a (<5 mg m-3). On December 23, 2008, 26 locations were available within C. polykrikoids affected areas (fig. 11d). These locations included C. polykrikoids with high/medium Chl-a (>5 mg m-3) due to Rrs(667) > Rrs(443) and HOCI > 0.18 mW cm-2 µm-1 sr-1 mg m-4. One location in the first date and four locations in the second date, which are outlined in Fig. 10c and 10d, contained T. erythtraeum blooms because of Rrs(667) < Rrs(443), Rrs(443) > Rrs(412), HOCI >0.18 mW cm-2 µm-1 sr-1 mg m-4, and nFLH >0.04 mW cm-2 µm-1 sr-1 (= the maximum HNA of nFLH in Fig. 6) (Fig. 11e and 11f). T

Fig. 11.

Table 1 shows statistical values of mentioned products and indices for non-bloom waters, C. polykrikoids, and T. erythtraeum blooms. Maximum HOCI for non-bloom waters was lower than the minimum HNA (= 0.18 mW cm-2 µm-1 sr-1 mg m-4 in Fig. 6) while minimum HOCI for T. erythtraeum blooms was higher. So, HOCI> HNA can discriminate non-blooms from T. erythtraeum blooms. Such difference was not observed in the ranges of Chl-a, Kd490, and nFLH. In addition, HOCI >0.18 mW cm-2 µm-1 sr-1 mg m-4 and nFLH >0.04 mW cm-2 µm-1 sr-1 can distinguish non-blooms 15

from algal blooms with high/medium concentrations of Chl-a (>5 mg m-3) in the current study area. Rrs(667)/Rrs(443) >1 is a suitable criterion to discriminate toxic C. polykrikoids blooms from other algal blooms in the PG. HOCI had the highest coefficient of variation (= standard deviation to mean ratio) than other parameters in bloom and non-bloom waters. It indicates high variability and quantization of HOCI.

Table 1

4.

CONCLUSIONS

This study investigated the behavior of MODIS Chl-a, Kd490, and nFLH in the PG between 2002 and 2008. Besides algal bloom, CDOM and nutrients play significant roles in increasing Chl-a and Kd490. nFLH was more sensitive to algal blooms than Chl-a and Kd490. It had low correlation with Chl-a and Kd490 in the normal situation. In contrast, it had high correlation with Chl-a and Kd490 in the RT conditions. According to the attributes of three mentioned products, HOCI was defined to separate bloom-laden from no-bloom waters. A high HOCI difference was available between normal and RT periods. However, such difference was not observed for Chl-a, Kd490, and nFLH. The integration of HOCI and nFLH differentiated non-blooms from algal blooms with high/medium concentrations of Chl-a. According to MODIS spectral signature of different types f

blooms in earlier studies, Rrs(667)/Rrs(443) > 1 was recognized as a proper statement to separate C. polykrikoids blooms from other blooms. Rrs(443)/Rrs(412) > 1 was considered as a suitable attribute

to discriminate T. erythtraeum from N. millaris, N. scintillans, and diatoms. In situ validation of these spectral attributes, to evaluate performance, would be an aim of future work. The 16

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Table Captions: Table 1 Statistical parameters of Chl-a, nFLH, Kd490, and HOCI for 100 locations in the PG on 27 October, 2008 and 23 December, 2008. The units of Chl-a, Kd490, nFLH, and HOCI are mg.m-3, m-1, mW cm-2 µm-1 sr-1, and mW cm-2 µm-1 sr-1 mg m-4, respectively. CV = Coefficient of Variation

Figure Captions: Fig. 1. Map of case study. Color rectangles show the boxes of three sub-regions in the PG.

Fig. 2. Number of days including qualified satellite data in months 8 to 12 between 2002 and 2008.

Fig. 3. Color maps of Chl-a, Kd490, nFLH, and HOCI as well as ERGB images covering the PG for four days from October 2008 to December 2008.

Fig. 4. Monthly averages of Chl-a, Kd490, nFLH, and HOCI between 2002 and 2008. Longitude range: 56°20’28”- 56°34’24”, latitude range: 26°22’51”- 27°04’36”. The units of Chl-a, Kd490, and nFLH are mg.m-3, m-1, and mW cm-2 µm-1 sr-1, respectively.

Fig. 5. Scatter plots of monthly averages of Chl-a, Kd490, and nFLH relative to each other during normal and RT periods in all sub-regions. The units of Chl-a, Kd490, and nFLH are mg.m-3, m-1, and

23

mW cm-2 µm-1 sr-1, respectively. Continuous and dashed lines represent regression lines for normal and RT conditions, respectively. R2 is coefficient of determination.

Fig. 6. The variation ranges of Chl-a, Kd490, nFLH, and HOCI during RT and normal periods. Vertical axis is in logarithmic scale. The units of Chl-a, Kd490, nFLH, and HOCI are mg.m-3, m-1, mW cm-2 µm-1 sr-1, and mW cm-2 µm-1 sr-1 mg m-4, respectively.

Fig. 7. Color maps of Aqua Chl-a (a), nFLH (b), Kd490 (c), HOCI (d), ERGB (e), and 10 stations (f) in the eastern PG (latitude range: 24.5-27.5 and longitude range: 54.5-58.0) on October 27, 2008. (g) Rrs from 412 to 678 nm, (h) bar diagrams of Chl-a, Kd490, nFLH, and HOCI, and (i) bar diagrams of Rrs(443), Rrs(667), and Rrs(667)/Rrs(443) for selected stations. Vertical axes of (h) and (i) are in logarithmic scale. The units of Chl-a, Kd490, nFLH, HOCI, and Rrs are mg.m-3, m-1, mW cm-2 µm-1 sr-1, mW cm-2 µm-1 sr-1 mg m-4, and sr-1, respectively.

Fig. 8. Color maps of Aqua Chl-a (a), nFLH (b), Kd490 (c), HOCI (d), ERGB (e), and 10 stations (f) in the middle PG (latitude range: 24.5-27.5 and longitude range: 51.5-55.5) on November 19, 2008. (g) Rrs from 412 to 678 nm, (h) bar diagrams of Chl-a, Kd490, nFLH, and HOCI, and (i) bar diagrams of Rrs(443), Rrs(667), and Rrs(667)/ Rrs(443) for selected stations. Vertical axes of (h) and (i) are in logarithmic scale. The units of Chl-a, Kd490, nFLH, HOCI, and Rrs are mg.m-3, m-1, mW cm-2 µm-1 sr-1, mW cm-2 µm-1 sr-1 mg m-4, and sr-1, respectively.

24

Fig. 9. Color maps of Aqua Chl-a (a), nFLH (b), Kd490 (c), HOCI (d), ERGB (e), and 10 stations (f) in the northern PG (latitude range: 25.5-28.5 and longitude range: 50.0-54.0) on December 23, 2008. (g) Rrs from 412 to 678 nm, (h) bar diagrams of Chl-a, Kd490, nFLH, and HOCI, and (i) bar diagrams of Rrs(443), Rrs(667), and Rrs(667)/Rrs(443) for selected stations. Vertical axes of (h) and (i) are in logarithmic scale. The units of Chl-a, Kd490, nFLH, HOCI, and Rrs are mg.m-3, m-1, mW cm-2 µm-1 sr-1, mW cm-2 µm-1 sr-1 mg m-4, and sr-1, respectively.

Fig. 10. (a) A pattern of MODIS-derived spectral signature for different algal blooms, (b) bar diagrams of Rrs(443),Rrs(667), and Rrs(667)/Rrs(443) for different algal blooms, (c) A scheme for discrimination C. polykrikoids and T. erythtraeum blooms from other features using MODIS data. Vertical axis in part (b) is in logarithmic scale. HNAh and HNAn are the values of HNA for HOCI and nFLH, respectively.

Fig. 11. (a) 50 locations on 27 October, 2007, (b) 50 locations on 23 December, 2008 in the PG, (c) and (d) scatter plots of Chl-a, nFLH, Kd490, and HOCI vs Rrs(667)/Rrs(443) for selected locations in (a) and (b), respectively, (e) and (f) Rrs from 412 to 678 nm for selected locations outlined in (c) and (d), respectively. Vertical axes of (c) and (d) are in logarithmic scale. The units of Chl-a, Kd490, nFLH, and HOCI are mg.m-3, m-1, mW cm-2 µm-1 sr-1, and mW cm-2 µm-1 sr-1 mg m-4, respectively.

25

Strait of Hormuz

Sub-region 1 Sub-region 2 Sub-region 3

1.2

RT

0.9 0.6

R² = 0.99, p <0.05

0.3

R² = 0.98, p <0.05

0 0

(a)

5

10

15

20

0.1 0.08

RT

0.06 0.04

R² =0.94, p <0.05

0.02

25

Monthly Average of Chl-a

Normal

R² = 0.04, p <0.05

0 0

(b)

5

10

15

20

Monthly Average of nFLH

Normal

Monthly Average of nFLH

Monthly Average of Kd490

1.5

25

0.1

Normal RT

0.08 0.06 0.04

R² =0.93, p <0.05

0.02

R² = 0.03, p <0.05

0 0

(c)

0.3 0.6 0.9 1.2 1.5

Monthly Average of Kd490

Sub-region 1

(a)

2.00

1.48

HNA

0.50

LRTA

0.13

LRTA to HNA

0.03 Chl-a

nFLH

Kd490

(b)

HOCI

8.00 2.00

3.40 0.87 0.89

LRTA

0.50

LRTA to HNA

0.13 0.03 Chl-a

nFLH

2.18

3.45

2.00

HNA

0.50

LRTA LRTA to HNA

0.13

(c) 0.03

Kd490

17.33 4.02

Chl-a

nFLH

Kd490

HNA

0.76

Sub-region 3

32.00 8.00

Monthly Average

8.00 1.82 1.45

Sub-region 2

32.00

14.41

Monthly Average

Monthly Average

32.00

HOCI

HOCI

0.012

1.73

C. polykrikoids

1

0.009

0.16

0.1

T. erythtraeum

Rrs(443) 0.07 Rrs(667)

0.01

412 443 469 488 531 547 555 645 667 678

(b)

Wavelength

Yes Rrs(667) > Rrs(443)

HOCI > HNAh

Yes

No No

Diatom

Diatom

0

(a)

0.0001

N. scintillans

N. scintillans

0.003

Rrs(667)/Rrs(443) 0.001

N.millaris

N.millaris

T. erythtraeum

0.006

C. polykrikoids

Rrs (sr-1)

0.68 0.67

C. polykrikoids with high concentrations C. polykrikoids with low concentrations

Yes Rrs(443) > Rrs(412) & HOCI > HNAh

No

T. erythtraeum nFLH > HNAn

Yes

No HOCI > HNAh

CDOM

Yes

Other algal blooms No Yes

SS

No

Clear water

nFLH > HNAn

(c)

Table 1 Statistical parameters of Chl-a, nFLH, Kd490, and HOCI for 100 locations selected within different features in the PG on 27 October, 2008 and 23 December, 2008. The units of Chl-a, Kd490, nFLH, and HOCI are mg.m-3, m-1, mW cm-2 µm-1 sr-1, and mW cm-2 µm-1 sr-1 mg m-4, respectively. CV = Coefficient of Variation

Chl-a

Kd490

nFLH

HOCI

Rrs (667)/Rrs (443)

Min

0.62

0.08

0.008

0.0004

0.32

Non-bloom

Max

7.53

0.49

0.121

0.1736

0.95

(no = 63)

Mean

2.05

0.16

0.033

0.0216

0.68

CV

0.66

0.48

0.742

1.6734

0.22

Min

7.25

0.47

0.057

0.3603

0.74

T. e bloom

Max

21.95

1.61

0.105

2.3727

0.98

(no = 5)

Mean

12.35

0.84

0.077

0.8747

0.90

CV

0.47

0.54

0.230

0.9715

0.11

Min

3.01

0.21

0.015

0.0105

1.01

C. p bloom

Max

361.27

6.40

0.106

209.4803

1.84

(no = 32)

Mean

81.48

3.72

0.074

39.2972

1.24

CV

1.20

0.69

0.287

1.4669

0.15

26