Exploring the potential value of satellite remote sensing to monitor chlorophyll-a for US lakes and reservoirs

Abstract

Assessment of chlorophyll-a, an algal pigment, typically measured by field and laboratory in situ analyses, is used to estimate algal abundance and trophic status in lakes and reservoirs. In situ-based monitoring programs can be expensive, may not be spatially, and temporally comprehensive and results may not be available in the timeframe needed to make some management decisions, but can be more accurate, precise, and specific than remotely sensed measures. Satellite remotely sensed chlorophyll-a offers the potential for more geographically and temporally dense data collection to support estimates when used to augment or substitute for in situ measures. In this study, we compare available chlorophyll-a data from in situ and satellite imagery measures at the national scale and perform a cost analysis of these different monitoring approaches. The annual potential avoided costs associated with increasing the availability of remotely sensed chlorophyll-a values were estimated to range between $5.7 and $316 million depending upon the satellite program used and the timeframe considered. We also compared sociodemographic characteristics of the regions (both public and private lands) covered by both remote sensing and in situ data to check for any systematic differences across areas that have monitoring data. This analysis underscores the importance of continued support for both field-based in situ monitoring and satellite sensor programs that provide complementary information to water quality managers, given increased challenges associated with eutrophication, nuisance, and harmful algal bloom events.

Merging of the Case 2 Regional Coast Colour and Maximum-Peak Height chlorophyll-a algorithms: validation and demonstration of satellite-derived retrievals across US lakes

“…5c). Minnesota and Florida are more likely to have matches with OLCI and MERIS because they have some of the highest numbers of chl-a records in the WQP and the most resolvable lake observations from satellites (Papenfus et al, 2020). The analysis to determine the merged algorithm combination with the lowest error yielded a MPH (P) minimum threshold value of 10 µg L −1 and a C2RCC maximum threshold value of 15 µg L −1 , a combination referred to as C 15 -M 10 (Fig.…”

“…Radiometric information such as remote sensing reflectance or inherent optical properties, typically used to constrain the use of in situ observations, are not part of the WQP. The availability of in situ measures was dependent on the organizations voluntarily uploading data to the WQP; thus, observation data may be delayed anywhere from months to years (Papenfus et al, 2020 ). This delay caused the number of available in situ match-ups with OLCI to be considerably lower than for MERIS.…”

“…The spatial and temporal resolution of satellite remote sensing can help reduce costs associated with traveling to sites, laboratory analysis, and staffing to support these activities. Papenfus et al ( 2020 ) reported mean cloud free temporal resolution of United States (US) lakes was 184 days per year with one Sentinel-3 satellite. Satellite remote sensing may also be a cost-effective option for state, regional, or national assessments of lake water quality (Papenfus et al, 2020 ).…”

“…Papenfus et al ( 2020 ) reported mean cloud free temporal resolution of United States (US) lakes was 184 days per year with one Sentinel-3 satellite. Satellite remote sensing may also be a cost-effective option for state, regional, or national assessments of lake water quality (Papenfus et al, 2020 ). However, there are several inherent challenges with using satellite remote sensing for inland water quality monitoring.…”

Space-time monitoring of water quality in an eutrophic reservoir using SENTINEL-2 data - A case study of San Roque, Argentina

“…The use of remote sensing and satellite based on multispectral imaging became increasingly common to answer the need for finer time and spatial monitoring of stressed aquatic ecosystems. It has been widely used to monitor inland, coastal and estuaries water across different global regions [7,8,9]. Large variety of algorithms have also been developed to retrieve [Chl-a] values from several Earth Observation (EO) missions, including MODIS [10], MERIS [11], Landsat 8 [12], Sentinel-2 [13] and recently also for Sentinel 3 [14].…”