Review of the Forel–Ule Index based on in situ and remote sensing methods and application in water quality assessment

Miao, Yi; Sun, Yonghua

doi:10.1007/s11356-021-18083-0

Cited by 22 publications

(17 citation statements)

References 82 publications

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“…To verify colour patterns in the MA-WS maps, 1 year (2019) of Sentinel-3 Ocean and Land Colour Instrument (OLCI) Level 2 products (300-m resolution pixel) were downloaded on the EUMETSAT Data centre (hereafter S3). The data were processed into OWT maps using another colour scale-the Forel-Ule (FU) colour scale-a historical colour scale standard [50,56,70,71]. The FU colour scale divides water into 21 levels, ranging from dark blue to yellowish brown and was one of the earliest methods used to classify water masses into OWTs (Table 2).…”

Section: Satellite Datamentioning

confidence: 99%

“…Field FU colour class were measured with the Eye On Water (EOW) phone application developed in the European Citclops (Citizens' Observatory for Coast and Ocean Optical Monitoring) project. EOW allows users to collect FU water colour measurements from their smartphone cameras [50,77,78] and has been shown to be a robust application for capturing the FU colour of water with accuracy and precision [79] SSC measurements were acquired using the same method as described above, and the SDD was measured using a standard 30 cm Secchi disk, lowering the disk in the water and measuring to what depth it was still visible [22]. SCC and SDD measurements were matched up with the EOW-FU data and were also used to describe the composition of the OWTs in TS.…”

Section: (B) Optical Datasetmentioning

confidence: 99%

“…Water colour is the result of the presence of marine constituents (SSC, chlorophyll-a [Chl-a] and coloured dissolved organic matter [CDOM]) and their interactions with solar irradiance [49]. Several studies have reported that there is a quantifiable relationship between water colour and water quality parameters, including a strong relationship with turbidity [50][51][52]. Accordingly, water colour is regarded as a simple yet efficient optical parameter for assessing water quality changes [14,53].…”

Section: Introductionmentioning

confidence: 99%

“…Accordingly, water colour is regarded as a simple yet efficient optical parameter for assessing water quality changes [14,53]. It has been used worldwide, including in the GBR, to assess water quality changes related to different turbidity levels, SSC and Chl-a concentrations, and Secchi Disk Depth in inland and marine waters [14,50,[54][55][56][57][58]. Importantly, water colour classification algorithms do not require a full characterisation of regional optical properties using local in situ water quality data and are thus suited to data-limited study areas [50].…”

Section: Introductionmentioning

confidence: 99%

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Using Optical Water-Type Classification in Data-Poor Water Quality Assessment: A Case Study in the Torres Strait

et al. 2022

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For many years, local communities have expressed concerns that turbid plume waters from the Fly River in Papua New Guinea may potentially deliver mine-derived contaminants to the Torres Strait, an ecologically and culturally unique area north of the Australian mainland. Information on suspended sediment transport and turbidity patterns are needed in this data-limited region to identify and manage downstream ecosystems that may be at risk of exposure from the Fly River runoff. This study used MODIS satellite time series and a colour-classification approach to map optical water types around the data-poor Gulf of Papua and Torres Strait region. The satellite data were supported by field data, including salinity and suspended sediment measurements, and used together in qualitative water quality assessments to evaluate the habitats that are likely exposed to Fly River discharge and/or derived sediments. It showed that the Fly River influence in the Torres Strait region is largely limited to the north-east corner of the Torres Strait. The drivers of turbidity vary between locations, and it is impossible to fully separate direct riverine plume influence from wave and tidally driven sediment resuspension in the satellite maps. However, results indicate that coastal habitats located as far east as Bramble Cay and west to Boigu Island are located in an area that is most likely exposed to the Fly River discharge within the region, directly or through sediment resuspension. The area that is the most likely exposed is a relatively small proportion of the Torres Strait region, but encompasses habitats of high ecological importance, including coral reefs and seagrass meadows. Satellite data showed that the period of highest risk of exposure was during the south-east trade wind season and complemented recent model simulations in the region over larger spatial and temporal frames. This study did not evaluate transboundary pollution or the ecological impact on local marine resources, but other recent studies suggest it is likely to be limited. However, this study did provide long-term, extensive but qualitative, baseline information needed to inform future ecological risk mapping and to support decision making about management priorities in the region. This is important for ensuring the protection of the Torres Strait ecosystems, given their importance to Torres Strait communities and turtle and dugong populations, and the Torres Strait’s connectivity with the Great Barrier Reef Marine Park.

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Section: Satellite Datamentioning

confidence: 99%

Section: (B) Optical Datasetmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using Optical Water-Type Classification in Data-Poor Water Quality Assessment: A Case Study in the Torres Strait

et al. 2022

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“…The Forel-Ule colour scale is a visual scale of 21 colours, ranging from blue to green to yellow to brown, that can be used alongside the Secchi disk with the observer typically recording the colour of a submerged Secchi disk at around roughly half the Secchi depth (Wernand and Gieskes, 2012). This visual index of colour can reflect information on the composition of optically active constituents in the water, such as sediment, phytoplankton and yellow substances (Wernand and van der Woerd, 2010b;Wang et al, 2019;Ye and Sun, 2022). In open-ocean case-1 waters (around 70% of the ocean surface; Hu et al, 2012), where optically active water constituents covary in a predictable manner with phytoplankton (Morel and Prieur, 1977), these visual indices can be a powerful predictor of Chl-a concentration (Boyce et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Evaluating historic and modern optical techniques for monitoring phytoplankton biomass in the Atlantic Ocean

et al. 2023

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Traditional measurements of the Secchi depth (zSD) and Forel-Ule colour were collected alongside modern radiometric measurements of ocean clarity and colour, and in-situ measurements of chlorophyll-a concentration (Chl-a), on four Atlantic Meridional Transect (AMT) cruises. These data were used to evaluate historic and modern optical techniques for monitoring Chl-a, and to evaluate remote-sensing algorithms. Historic and modern optical measurements were broadly consistent with current understanding, with Secchi depth inversely related to Forel-Ule colour and to beam and diffuse attenuation, positively related to the ratio of blue to green remote-sensing reflectance and euphotic depth. The relationship between Secchi depth and Forel-Ule on AMT was found to be in closer agreement to historical relationships when using data of the Forel-Ule colour of infinite depth, rather than the Forel-Ule colour of the water above the Secchi disk at half zSD. Over the range of 0.03-2.95 mg m-3, Chl-a was tightly correlated with these optical variables, with the ratio of blue to green remote-sensing reflectance explaining the highest amount of variance in Chl-a (89%), closely followed by the Secchi depth (85%) and Forel-Ule colour (71-81%, depending on the scale used). Existing algorithms that predict Chl-a from these variables were evaluated, and found to perform well, albeit with some systematic differences. Remote sensing algorithms of Secchi depth were in good agreement with in-situ data over the range of values collected (8.5 - 51.8 m, r2>0.77, unbiased root mean square differences around 4.5 m), but with a slight positive bias (2.0 - 5.4 m). Remote sensing algorithms of Forel-Ule agreed well with Forel-Ule colour data of infinite water (r2>0.68, mean differences <1). We investigated the impact of environmental conditions and found wind speed to impact the estimation of zSD, and propose a path forward to include the effect of wind in current Secchi depth theory. We discuss the benefits and challenges of collecting measurements of the Secchi depth and Forel-Ule colour and propose future directions for research. Our dataset is made publicly available to support the research community working on the topic.

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Climate change‐associated declines in water clarity impair feeding by common loons

Piper,

Glines,

Rose

2024

Ecology

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Climate change has myriad impacts on ecosystems, but the mechanisms by which it affects individual species can be difficult to pinpoint. One strategy to discover such mechanisms is to identify a specific ecological factor related to survival or reproduction and determine how that factor is affected by climate. Here we used Landsat imagery to calculate water clarity for 127 lakes in northern Wisconsin from 1995 to 2021 and thus investigate the effect of clarity on the body condition of an aquatic visual predator, the common loon (Gavia immer). In addition, we examined rainfall and temperature as potential predictors of water clarity. Body mass tracked July water clarity strongly in loon chicks, which grow chiefly in that month, but weakly in adult males and females. Long‐term mean water clarity was negatively related to chick mass but positively related to adult male mass, suggesting that loons foraging in generally clear lakes enjoy good foraging conditions in the long run but might be sensitive to perturbations in clarity during chick‐rearing. Finally, chick mass was positively related to the density of docks, perhaps because angling removes large fishes and thus boosts the abundance of the small fishes on which chicks depend. Water clarity itself declined strongly from 1995 to 2021, was negatively related to July rainfall, and was positively related to July air temperature. Our findings identified both long‐term and short‐term water clarity as strong predictors of loon foraging efficiency, and suggest that climate change, through water clarity, impacts freshwater ecosystems profoundly. Moreover, our results identified the recent decrease in water clarity as a likely cause of population decline in common loons.

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Review of the Forel–Ule Index based on in situ and remote sensing methods and application in water quality assessment

Cited by 22 publications

References 82 publications

Using Optical Water-Type Classification in Data-Poor Water Quality Assessment: A Case Study in the Torres Strait

Using Optical Water-Type Classification in Data-Poor Water Quality Assessment: A Case Study in the Torres Strait

Evaluating historic and modern optical techniques for monitoring phytoplankton biomass in the Atlantic Ocean

Climate change‐associated declines in water clarity impair feeding by common loons

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