Satellite Remote Sensing: A Tool to Support Harmful Algal Bloom Monitoring and Recreational Health Advisories in a California Reservoir

被引:0
|
作者
Barreto, Brittany N. Lopez [1 ,2 ]
Hestir, Erin L. [1 ,2 ]
Lee, Christine M. [3 ]
Beutel, Marc W. [1 ]
机构
[1] Univ Calif Merced, Dept Civil & Environm Engn, Environm Syst Grad Grp, Merced, CA 95343 USA
[2] Univ Calif Merced, Banatao Inst, Ctr Informat Technol Res Interest Soc, Merced, CA 95343 USA
[3] CALTECH, Jet Prop Lab, NASA, Pasadena, CA USA
来源
GEOHEALTH | 2024年 / 8卷 / 02期
关键词
remote sensing; harmful algal blooms; public health; CHLOROPHYLL-A; UNITED-STATES; ATMOSPHERIC CORRECTION; CYANOBACTERIAL BLOOMS; INLAND WATERS; COASTAL; LAKE; ALGORITHMS; IMAGERY; TURBIDITY;
D O I
暂无
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Cyanobacterial harmful algal blooms (cyanoHABs) can harm people, animals, and affect consumptive and recreational use of inland waters. Monitoring cyanoHABs is often limited. However, chlorophyll-a (chl-a) is a common water quality metric and has been shown to have a relationship with cyanobacteria. The World Health Organization (WHO) recently updated their previous 1999 cyanoHAB guidance values (GVs) to be more practical by basing the GVs on chl-a concentration rather than cyanobacterial counts. This creates an opportunity for widespread cyanoHAB monitoring based on chl-a proxies, with satellite remote sensing (SRS) being a potentially powerful tool. We used Sentinel-2 (S2) and Sentinel-3 (S3) to map chl-a and cyanobacteria, respectively, classified chl-a values according to WHO GVs, and then compared them to cyanotoxin advisories issued by the California Department of Water Resources (DWR) at San Luis Reservoir, key infrastructure in California's water system. We found reasonably high rates of total agreement between advisories by DWR and SRS, however rates of agreement varied for S2 based on algorithm. Total agreement was 83% for S3, and 52%-79% for S2. False positive and false negative rates for S3 were 12% and 23%, respectively. S2 had 12%-80% false positive rate and 0%-38% false negative rate, depending on algorithm. Using SRS-based chl-a GVs as an early indicator for possible exposure advisories and as a trigger for in situ sampling may be effective to improve public health warnings. Implementing SRS for cyanoHAB monitoring could fill temporal data gaps and provide greater spatial information not available from in situ measurements alone. Lakes often have algal blooms that create a water quality concern, especially when they contain cyanobacteria, which can be toxic to both humans and animals. These harmful algal blooms are of great concern in areas with limited water supply in states such as California. While it is often difficult and costly to collect and monitor toxin concentrations, monitoring concentrations of chlorophyll-a (chl-a) -a measure of how much algae are present-is relatively common and can even be accomplished using satellite remote sensing. There have been multiple studies that have found a relationship between toxins produced by cyanobacteria and chl-a. The World Health Organization (WHO) has recently released (2021) an updated release of their previous 1999 guidance values for toxin monitoring based on chl-a concentration. With satellite data, we were able to measure chl-a concentration in a major reservoir in California, and then classify the chl-a measurements into the WHO's guidance values for toxins. We compared the satellite-based guidance values to the public advisory levels currently set by the California Department of Water Resources. Our results indicate that SRS of chl-a is a reasonable substitute for cyanobacteria toxin advisories, and our framework can be applied to similar cyanobacteria dominated lakes. The World Health Organization (WHO) updated cyanobacteria harmful algal blooms (cyanoHABs) guidelines for chlorophyll-a (chl-a) as a proxy With satellite remote sensing (SRS), we estimated and classified chl-a to compare cyanotoxins advisories used by California This study provides a framework for evaluating public health utility of SRS for enhancing cyanotoxin monitoring globally
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页数:18
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