Can Forel–Ule Index Act as a Proxy of Water Quality in Temperate Waters? Application of Plume Mapping in Liverpool Bay, UK

Round 1

Reviewer 1 Report

The manuscript submitted is an interesting and a well written manuscript. The authors reported the results of the application of the Forel-Ule Index for short- and long-term mapping of river plumes in Liverpool Bay (UK) using Sentinel-3 A and B OLCI satellite data. The methodology is well described and the conclusions are supported by the results. While the results of Forel-Ule Index show a relatively strong relationship with Water Quality Indicators, it could be used for water quality assessment and contribute to water management. However, the authors should consider these minor revisions such as for: Line 237 the Figure 2 should be in the section 2.5 near where it is cited, it could be relocated between Lines 268 and 269. Line 295, “the shape of the river plume…”  could be rephrased to “Spatial distribution of the river plume…”, please check also for the line 297. On the line 299, there is “Error! Reference source not found”, please fix this. The line 421 is incomplete, please check also line 429.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

See attached comments

Comments for author File: Comments.pdf

Author Response

Please see the attachment. Also the re-written discussion is present here:

4. Discussion

4.1. Water Quality Assessments Based on the Plume Mapping

This study provides the first river plume mapping on monthly annual and climatological basis between 2017-2020 in Liverpool Bay. The automated -workflow developed in this study to map river plumes in Liverpool Bay is a fast, cost-effective and reproducible way of estimating riverine influence on coastal and open waters using a combination of high spatial and temporal resolution Sentinel-3 ocean colour product and the open source SNAP FUI algorithm. Applying Sentinel-3 OLCI satellite data to map plumes in Liverpool Bay provides detailed plume information, thanks to its 300m resolution. Compared to the previous studies it uses higher resolution than MODIS or SeaWiFS (1.0km and 1.1km resolution respectively) [6,10], and better radiometric resolution than MERIS [6].

Sentinel-3 OLCI is a relatively new satellite mission, increasingly applied to -map river plumes [11,13] . The FUI index for the sentinel-3 products has been used worldwide, including in the GBR, to assess water quality changes in marine waters and has already been recognized as a continuation of older ocean colour products, such as MODIS, in the long-term water monitoring programs in the GBR. [11]. As such, using FUI is not only an objective method of mapping  optical water types, including river plumes, applicable worldwide, but it also provides an option to compare regions without the full knowledge of the inherent properties of the water. Thanks to the high spatial, temporal and radiometric resolution of Sentinel-3 OLCI was possible to map river plumes with a higher definition and accuracy than in previous assessment [2] on monthly, yearly and climatological scales from the coastal to offshore waters. The results of this study can be used to improve current water quality programs in Liverpool Bay by refining existing assessment areas.

Formal eutrophication assessments, such as those under WFD and OSPAR, have traditionally used geographically defined assessment areas [2], whereas using FUI to define assessment areas based on river plumes would encompass the full spatial extent of terrestrial impact in the marine environment. This would provide a more holistic approach, since it reflects the nutrient, sediment and other anthropogenic loads from the land to sea, and the specific local hydrological circulations that determine the level of mixing and the extent of the river plume. - In comparison to the more recent assessment areas based on SPM or salinity [2], the SPM and FUI derived plumes are expected to be similar, as shown in Figure 12. This is due to a high correlation between FUI and SPM, since SPM is one of the CPAs directly influencing the optical property of water which FUI is based on. However, the FUI plume maps the river plume also off the coast of Northern Wales, which is not present in the SPM based plume. In contrast, the FUI plume is smaller around the area of the Shell Flat sandbank off the coast of Blackpool. The discrepancies could be due FUI also being influenced by CDOM, chl-a and other CPAs, which will not appear in the satellite-derived SPM plume from [2]. As such, the use of the FUI to map river plumes will be based on more input data that are directly linked with the plumes (CDOM, chl-a -or SPM), hence more representative of the freshwater -loads to the sea.

FUI is an important tool to operationally assess water quality and flood plume influence in the tropical waters of the GBR. Changing extent of river flood plumes have been linked with an increase in extreme weather [12], which is expected to intensify under IPCC climate change scenarios [42]. More extreme and frequent weather events can lead to increased inputs of sediments, nutrients and other pollutants into the coastal seas through river floods. The large scale flooding has been linked to a decline in the health of inshore seagrass communities and coral reefs in the GBR [12]. In addition, numerous studies around the world [43–45] have shown that a change in land management, together with climate change, can result in coastal darkening. Coastal darkening is a phenomenon mainly present off the coast, where increased concentrations of light absorbing and scattering material, such as SPM or CDOM, is suggested to result in a lower amount of available light, hence darkening. This phenomenon was observed in centennial water -samples in the North Sea, and was linked to delays in phytoplankton blooms -[45]. As such, an increase in the number of extreme weather systems and changes in land use in the catchments draining into Liverpool Bay could detrimentally impact the coastal and intertidal ecosystems due to increased run-off into the sea. Cost-effective, repetitive and large-scale monitoring of water type through mapping river plumes presented in this paper, could facilitate defining measures to ensure water quality.

4.2. Future Work and Applications

The method applied in this paper to map river plumes provides new information on the spatial and temporal variations in the plume extents and provides an estimation of water quality through specific waterbodies, but also highlights where additional work is needed to progress the systematic detection of river plume waters. Firstly, this paper suggests that despite 21 FUI colour classes are applicable worldwide, it is important to assess the FUI clustering into waterbody types locally, hence reflect regionally specific optical water characteristics. Both GBR and Citclops waterbody classification in Liverpool Bay identify the river plume has FUI >=10.- In GBR, this represents the Primary river plume [11], whereas this category represents Estuaries, Near-Shore and Coastal class in the Citclops project [20]. The Citclops classes, however, provide more in-detail river plume information and its water quality condition around the coast, which was found to be more suitable for mapping plumes in Liverpool Bay. Conversely, the GBR classification offers more information on the FUI below 10, as opposed to Citclops in offshore waters, which is more adapted to the clearest tropical waters of the GBR. In Liverpool Bay case study, two original open-water classes had to be merged into one due to lack of FUI between 1-5 in the bay. We propose keeping the Citclops classes for the river plume (FUI >=10), meaning Estuaries (FUI 18-21), Near-Shore (FUI 14-17) and Coastal (FUI 10-13), but adding more definition in the original Open-Sea class (FUI 9-1) from the GBR FUI classification (Table 1), which would offer more spatial information away from the coast. As such, a detailed cluster analysis of the classes across the timeseries will be carried out in the future for Liverpool Bay.

Another improvement of the current method lies in using ocean colour gap free products. Since Sentinel-3 OLCI is a passive sensor, it does not penetrate through the cloud cover and the accuracy of the FUI depends on the number of cloudless images. The presence of clouds creates a significant uncertainty in the temperate regions affected by frequent passes of oceanic frontal systems, such as the UK waters. Similarly, the concentration of clouds in a specific area of the daily Sentinel-3 image resulted in an uneven distribution of the available data. Consequently, it was not possible to interpolate data both spatially and temporarily to daily gap free images. Using a combination of different satellite and modelled data in a single gap free ocean colour product could solve this problem in the future. However, ocean colour gap free products used for example to map monthly global FUI using European Space Agency Ocean Colour Climate Change Initiative (CCI) has a resolution of ~4km at Equator [41], which can be unsuitable in the coastal and intertidal areas.

This study shows that FUI could be used as a proxy for qualitative assessment of water in Liverpool Bay, which is in agreement with the studies conducted in other geographic locations, such as the North Sea, Celtic Sea [5,24] or GBR [9,11,12]. More specifically, SPM or turbidity, showed a strong positive correlation with FUI in the above areas and Liverpool Bay, whilst Chl-a suggests a weak positive correlation [5]. Nutrients analysed in this study differ from the previous work which focused primarily on assessing dissolved inorganic nitrogen (DIN) or dissolved inorganic phosphate (DIP) and FUI [11,46]. Nutrient concentrations are highest in the Estuaries, Near-Shore or Coastal waters (or GBR Primary waterbody), and decrease with distance from the coast, in agreement with the description of the water quality in the waterbodies applied from Table 1 and [12]. To further analyse the relationship between water quality constituents and FUI in Liverpool Bay, CDOM, which is one of the primary colour producing agents, and examined in the previous work [5,24] will be included in the future assessment. Similarly, this study did not analyse temperature and water depth, which are physical properties that can indirectly affect optical properties as well as having been shown to be highly correlated with FUI [5,24]. Although, explaining the degree of the river plume variance by the tested variables is beyond the scope of this work and we looked at the relationship of the variables with FUI individually, a regression model that would identify their relative importance to the river plume area is proposed for future work together with the river plume modelling. In addition, as depicted in Figure 1, the in-situ water samples are primarily located in the estuaries and near-shore waters, hence the water data is biased towards the coastal areas. To improve the validation dataset and get a better understanding of the relationship between FUI and water quality constituents, more in-situ samples from the open waters need to be analysed.

Author Response File: Author Response.docx

Reviewer 3 Report

This manuscript seems very well organized.

However, it does not offer anything new and innovative to the scientific community.

The authors transfer an existing technique to a specific region of interest. There is no any novelty in this manuscript regarding image processing and pattern recognition techniques.

The material may technically be of some interest however scientifically is of low importance.

The schematic diagram of the methodology is not novel. Additionally, the authors are not describing analytically each stage and there is not any mathematical support. They used only existing libraries and packages and they are not describing them and their mathematical background.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

No improvements were made in the manuscript.

The comments of the authors justify my decision.

Author Response

Dear Editor, apologies the changes in response to the reviewer 3 were not clear in the manuscript. We changed the manuscript so it reflects better the novelty and importance of the work as you suggested. Please refer to the following lines:

Abstract:

Lines 23-30

Discussion: 

Lines: 460:469 
Lines:477-482
Lines:497-499 (concluding sentences- importance of the whole paragraph)
Lines: 515-517 (concluding sentences- importance of the whole paragraph)
Lines: 520: 523

Conclusion:

Lines: 579-581
Lines: 593-597