Stormwater plume detection by MODIS imagery in the southern California coastal ocean

被引:61
|
作者
Nezlin, Nikolay P. [1 ]
DiGiacomo, Paul M. [2 ]
Diehl, Dario W. [1 ]
Jones, Burton H. [3 ]
Johnson, Scott C. [4 ]
Mengel, Michael J. [5 ]
Reifel, Kristen M. [3 ]
Warrick, Jonathan A. [6 ]
Wang, Menghua [2 ]
机构
[1] So Calif Coastal Water Res Project SCCWRP, Costa Mesa, CA 92626 USA
[2] NOAA NESDIS Ctr Satellite Applicat & Res STAR, Camp Springs, MD 20746 USA
[3] Univ So Calif, Dept Biol Sci, Los Angeles, CA 90089 USA
[4] Aquat Bioassay & Consulting Labs, Ventura, CA 93001 USA
[5] OCSD, Fountain Valley, CA 92728 USA
[6] USGS Coastal & Marine Geol Program, Santa Cruz, CA 95060 USA
关键词
ocean color; sea-spectral reflectance; MODIS; plumes; southern California Bight; 32; degrees; 00; '-34; 30; N; 120; '-117; W;
D O I
10.1016/j.ecss.2008.07.012
中图分类号
Q17 [水生生物学];
学科分类号
071004 ;
摘要
Stormwater plumes in the southern California coastal ocean were detected by MODIS-Aqua satellite imagery and compared to ship-based data on surface salinity and fecal indicator bacterial (FIB) counts collected during the Bight'03 Regional Water Quality Program surveys in February-March of 2004 and 2005. MODIS imagery was processed using a combined near-infrared/shortwave-infrared (NIR-SWIR) atmospheric correction method, which substantially improved normalized water-leaving radiation (nLw) optical spectra in coastal waters with high turbidity. Plumes were detected using a minimum-distance supervised classification method based on nLw spectra averaged within the training areas, defined as circular zones of 1.5-5.0-km radii around field stations with a surface salinity of S < 32.0 ("plume") and S > 33.0 ("ocean"). The plume optical signatures (i.e., the nLw differences between "plume" and "ocean") were most evident during the first 2 days after the rainstorms. To assess the accuracy of plume detection, stations were classified into "plume" and "ocean" using two criteria: (1) "plume" included the stations with salinity below a certain threshold estimated from the maximum accuracy of plume detection; and (2) FIB counts in "plume" exceeded the California State Water Board standards. The salinity threshold between "plume" and "ocean" was estimated as 32.2. The total accuracy of plume detection in terms of surface salinity was not high (68% on average), seemingly because of imperfect correlation between plume salinity and ocean color. The accuracy of plume detection in terms of FIB exceedances was even lower (64% on average), resulting from low correlation between ocean color and bacterial contamination. Nevertheless, satellite imagery was shown to be a useful tool for the estimation of the extent of potentially polluted plumes, which was hardly achievable by direct sampling methods (in particular, because the grids of ship-based stations covered only small parts of the plumes detected via synoptic MODIS imagery). In most southern California coastal areas, the zones of bacterial contamination were much smaller than the areas of turbid plumes; an exception was the plume of the Tijuana River, where the zone of bacterial contamination was comparable with the zone of plume detected by ocean color. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:141 / 152
页数:12
相关论文
共 50 条
  • [1] MODIS imagery as a tool for synoptic water quality assessments in the southern California coastal ocean
    Nezlin, Nikolay P.
    DiGiacomo, Paul M.
    Jones, Burton H.
    Reifel, Kristen M.
    Warrick, Jonathan A.
    Johnson, Scott C.
    Mengel, Michael J.
    [J]. COASTAL OCEAN REMOTE SENSING, 2007, 6680
  • [2] Stormwater runoff plumes in the Southern California Bight: A comparison study with SAR and MODIS imagery
    Holt, Benjamin
    Trinh, Rebecca
    Gierach, Michelle M.
    [J]. MARINE POLLUTION BULLETIN, 2017, 118 (1-2) : 141 - 154
  • [3] An assessment of the transport of southern California stormwater ocean discharges
    Rogowski, Peter A.
    Terrill, Eric
    Schiff, Kenneth
    Kim, Sung Yong
    [J]. MARINE POLLUTION BULLETIN, 2015, 90 (1-2) : 135 - 142
  • [4] The southern California coastal ocean observing system
    Terrill, E.
    Peck, S.
    Hazard, L.
    Davis, R. E.
    DiGiacomo, P. M.
    Jones, B. H.
    Keen, C.
    Moline, M.
    Orcutt, J.
    Stolzenbach, K.
    Washburn, L.
    Helling, H.
    Long, J.
    Magdziarz, S.
    Laugilin, M.
    Kasschau, J.
    [J]. OCEANS 2006, VOLS 1-4, 2006, : 1133 - +
  • [5] Stormwater runoff plumes in the Southern California Bight: A comparison study with SAR and MODIS imagery (vol 118, pg 141, 2017)
    Holt, Benjamin
    Trinh, Rebecca
    Gierach, Michelle M.
    [J]. MARINE POLLUTION BULLETIN, 2017, 121 (1-2) : 435 - 435
  • [6] Impacts of stormwater runoff in the Southern California Bight: Relationships among plume constituents
    Reifel, Kristen M.
    Johnson, Scott C.
    DiGiacomo, Paul M.
    Mengel, Michael J.
    Nezlin, Nikolay P.
    Warrick, Jonathan A.
    Jones, Burton H.
    [J]. CONTINENTAL SHELF RESEARCH, 2009, 29 (15) : 1821 - 1835
  • [7] Relative availability of satellite imagery and ship-based sampling for assessment of stormwater runoff plumes in coastal southern California
    Nezlin, Nikolay P.
    Weisberg, Stephen B.
    Diehl, Dario W.
    [J]. ESTUARINE COASTAL AND SHELF SCIENCE, 2007, 71 (1-2) : 250 - 258
  • [8] A Century of Southern California Coastal Ocean Temperature Measurements
    Rasmussen, Linda L.
    Carter, Melissa L.
    Flick, Reinhard E.
    Hilbern, Mary
    Fumo, James T.
    Cornuelle, Bruce D.
    Gordon, Bonnie K.
    Bargatze, Lee F.
    Gordon, R. Lee
    McGowan, John A.
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2020, 125 (05)
  • [9] Coastal pollution-hazards in southern California observed by SAR imagery: stormwater plumes, wastewater plumes, and natural hydrocarbon seeps
    DiGiacomo, PM
    Washburn, L
    Holt, B
    Jones, BH
    [J]. MARINE POLLUTION BULLETIN, 2004, 49 (11-12) : 1013 - 1024
  • [10] Computing Coastal Ocean Surface Currents from MODIS and VIIRS Satellite Imagery
    Liu, Jianfei
    Emery, William J.
    Wu, Xiongbin
    Li, Miao
    Li, Chuan
    Zhang, Lan
    [J]. REMOTE SENSING, 2017, 9 (10)