Fernanda Maciel

The use of satellite-based remote sensing imagery for water quality monitoring of inland and coastal waters has become widespread over the last few decades, with the expansion of, and investment in, operational Earth-observing missions. Satellite-based sensors are uniquely suited to provide synoptic, system-wide water quality parameter estimates that supplement traditional field-based sampling methods. The remote sensing of water quality parameter estimates is particularly valuable in systems with high temporal and spatial variability, as well as in areas that are difficult to access, or where agencies lack funding for routine monitoring. However, optically complex inland and coastal waters pose additional challenges for developing robust remote sensing retrieval models for optical properties and water quality parameters. One of the biggest challenges is collecting high quality field measurements that are used to calibrate and validate the retrieval algorithms. Here, we present the current status of satellite missions, field methods that include instruments used and commonly measured parameters, and repositories of historical field data that are relevant to inland and coastal water studies. We then present data requirements for model validation and highlight gaps in validation coverage. Finally, we provide considerations for future field campaigns to improve coordination with remote sensing data collection and ensure that field data is well suited for use in model or algorithm development.

Dense blooms of potentially toxic cyanobacteria have been recorded on the north coast of the Río de la Plata estuary, which affect water quality for recreational or drinking water purposes. In this study we present results of a 7-years monitoring program in a coastal zone (Punta del Tigre, San José, Uruguay), with data of water temperature, conductivity, biomass and composition of cyanobacteria. The main objective was to determine the water temperature and salinity conditions associated with the dominance of cyanobacteria in the phytoplankton of the area studied. The concentration of total microcystins was quantified in selected samples. The blooms were also analyzed in satellite images based on the detection of chlorophyll a threshold. The most frequent species were potentially toxic: Microcystis aeruginosa, M. protocystis, M. novacekii, Dolichospermum circinale and D. uruguayense, often covering large areas in line with the satellite analysis. The concentrations of total microcystins generally exceeded the World Health Organization’s danger alerts for drinking water. Water temperatures above 19 °C, conductivities below 2 mS/cm and salinity below 0.5 were associated with a higher dominance of cyanobacteria in the total phytoplankton biomass. The high frequency of occurrence of these organisms in low conductivity conditions, common in the area, may compromise water quality for various uses, including human consumption. En la costa norte del estuario Río de la Plata se han registrado densas floraciones de cianobacterias potencialmente tóxicas que afectan la calidad del agua para su uso recreativo o potabilización. En este estudio presentamos resultados de 7 años de monitoreo en una zona costera (Punta del Tigre, San José, Uruguay), en los que se determinó temperatura, conductividad, biomasa y composición de cianobacterias. El principal objetivo fue caracterizar las condiciones de temperatura y salinidad que se asocian a la dominancia de las cianobacterias en el fitoplancton de la zona estudiada. Se cuantificó la concentración de microcistinas totales en algunas muestras seleccionadas. Las floraciones se analizaron también en imágenes satelitales a partir de la detección de umbrales de clorofila a. Las especies más frecuentes fueron potencialmente tóxicas: Microcystis aeruginosa, M. protocystis, M. novacekii, Dolichospermum circinale y D. uruguayense, abarcando frecuentemente grandes áreas en concordancia con el análisis satelital. Las concentraciones de microcistinas totales en general superaron las alertas de peligrosidad de la Organización Mundial de la Salud para agua a potabilizar. Temperaturas del agua superiores a 19 °C, conductividades inferiores a 2 mS/cm y salinidad menor a 0,5 se asociaron con una mayor dominancia de cianobacterias en la biomasa total de fitoplancton. La alta frecuencia de ocurrencia de estos organismos en condiciones de baja conductividad, usuales en la zona, puede comprometer la calidad del agua para diversos usos, incluyendo el consumo humano. Na margem norte do Río de la Plata foram registradas densas florações de cianobactérias potencialmente tóxicas, que afetan a qualidade da água para uso recreativo ou para abastecimento de água potável. Neste estudo presentamos os resultados de 7 anos de monitoramento em uma região costeira (Punta del Tigre, San José, Uruguai), determinando a temperatura, a condutividade, a biomassa e a composição de cianobactérias. O objetivo principal foi caracterizar as condições de temperatura e salinidade que estão associadas à dominância de cianobactérias no fitoplâncton da área estudada. A concentração total de microcistina foi quantificada em amostras selecionadas. Os blooms foram também analisados por imagens de satélite com base na detecção de valores limite de clorofila a. As espécies mais frequentes, e que são potencialmente tóxicas, foram Microcystis aeruginosa, M. protocystis, M. novacekii, Dolichospermum circinale e D. uruguayense, cobrindo frequentemente grandes áreas, de acordo com a análise por imagens de satélite. As concentrações de microcistinas totais excederam geralmente os alertas de perigo da Organização Mundial de Saúde para a água potável. Temperaturas da água superiores a 19 °C, condutividades inferiores a 2 mS/cm e salinidade inferior a 0,5 foram associadas a um maior predomínio de cianobactérias na biomassa total de fitoplâncton. A elevada frequência de ocorrência destes organismos em condições de baixa condutividade, comuns na região, pode comprometer a qualidade da água para diversos usos, incluindo o consumo humano.

Coastal waters have high ecological and economic relevance and are globally threatened by intense human activities leading to eutrophication. The decameter resolution of Sentinel-2 Multispectral Instrument (S2-MSI) provides an advantage to detect spatially heterogeneous phenomena that are limited in extent, such as harmful cyanobacterial blooms (cyanoHABs). Chlorophyll-a is typically used in remote sensing of blooms, however, it remains to be evaluated in several coastal regions of the world. The Río de la Plata estuary (South America) provides a key case study due to its highly variable concentrations of suspended sediments, and the increasing frequency of cyanoHABs. Here we evaluate the potential and limitations of S2-MSI indices to retrieve chlorophyll-a in these optically complex waters, obtaining regional algorithms and comparing them to previously available ones. We propose an approach to follow the evolution of chlorophyll-a thresholds (10 and 24μg/L) that can contribute to monitoring programs and early warning strategies of cyanoHABs.

Landsat-8 (L8) and Sentinel-2 (S2) terrestrial satellite missions have shown to contain useful information for aquatic applications. However, quantitative retrieval of water quality parameters, such as turbidity, strongly depend on the performance of atmospheric correction algorithms. Among available processors, ACOLITE (https://odnature.naturalsciences.be/remsem/software-and-data/acolite) is simple to incorporate in imagery processing routines and has shown to have better performance than other processors for sediment-rich waters. Recently (in 2018), it incorporated a new default atmospheric correction approach, the dark spectrum fit (DSF), which remains to be tested in most of the Southern hemisphere coastal areas. In this work, we present new in-situ radiometric measurements collected in the northern coast of the Río de la Plata estuary, South America, during field campaigns along a 2-year period. The data set was used to evaluate the performance of ACOLITE’s DSF and exponential extrapolation (EXP) methods with L8 and S2 imagery, and to recalibrate a turbidity algorithm. The DSF did not perform very well, giving particularly poor results in the near infrared (NIR) bands. However, its performance was greatly improved with an optional sun glint correction (DSF+GC), although some positive bias was still present in the NIR bands. A GC seemed to be most important in dates with higher sun elevation (austral spring and summer), and should be strongly considered for other water bodies in the region and in similar or lower latitudes (35°S). Additionally, the EXP method gave good results in the green-NIR spectral region when a low (5th) percentile aerosol type was selected. Finally, the effect of the atmospheric correction on turbidity retrieval from satellite imagery was assessed: if the red and a NIR band were combined, the effect of the bias in the NIR region was negligible for the DSF+GC method; however, some impact was noticed for the lowest turbidity levels if a single NIR band was used.

This paper presents a GIS-based tool named Arc-BEST (Bioaccumulation Evaluation Screening Tool) to perform spatially distributed bioaccumulation risk analyses. Estimating bioaccumulation risk is important to help predict potentially adverse effects from contaminants on ecosystems and human health, which are key factors in the development of sound public policy. Arc-BEST is based on the BEST model in the U.S. Army Corps of Engineers BRAMS (Bioaccumulation Risk Assessment Modeling System) software, released in 2012. It predicts concentration of concern contaminants in predators' tissues from concentrations in organisms at the bottom of the food chain, and corresponding bioaccumulation factors. Additionally, it estimates carcinogenic and non-carcinogenic risks for humans that consume those species. The greatest contribution of Arc-BEST is that it enables the automated use of digital spatial data sets, which improves model creation speed, analysis and visualization of results, and comparison and cross-referencing with other geographic datasets. Furthermore, the model was improved to consider up to four trophic levels. The code is written in Python and is open-source. In this work Arc-BEST is used as part of a screening-level risk assessment process in order to identify hot spots where further studies and monitoring should be performed to ensure humans and ecosystems health. The tool is successfully applied to a case study in the Laurentian Great Lakes, where long-term effects of polychlorinated biphenyls (PCBs) is performed, based on measured concentrations in zebra mussels (Dreissena polymorpha), and local bioaccumulation factors from previous studies. Zebra mussels have a great filtration capacity and high bioconcentration rates, increasing the bioavailability of contaminants for predator species. PCBs concentrations in different-level predators are predicted. Furthermore, health risks for humans that consume sport fish are estimated for various exposure scenarios. The distribution of the risks in the lakes is analyzed, and critical areas are identified.

Water resources availability presents a high degree of uncertainty in the context of climate change. In this study, the multi-year variability of simulated streamflow for three rivers (Paraná, Uruguay and Negro) in the La Plata Basin (LPB) in the period 1991–2098 is analysed. Simulated streamflow for that period were produced in a two-stage process involving a regional climate model (RCM) and a distributed hydrology model (VIC (variable infiltration capacity)). Outputs from two RCMs (PROMES [Spanish acronym for mesoscale forecast] and RCA [Rossby Centre regional atmospheric climate model]) were used in order to assess the sensitivity of the results to different models. Various spectral methods (singular spectrum analysis, maximum entropy method and multi-taper method) were used in order to detect low-frequency variability modes and preferred quasi-periodicities for annual and seasonal simulated time series. Both simulations generate larger runoff for the twenty-first century than those observed for the twentieth century for the three rivers. For annual time series, the variability in timescales longer than 30 years is detected by one of the simulations for the three rivers, and only weakly for the Negro River in the other. Seasonal variations of the preferred modes of multi-annual variability are apparent. The River Paraná shows a persistent 10-year period during most of the year in the PROMES-VIC simulation. No LFV modes were found for any trimester in any river for PROMES-VIC, while for RCA-VIC simulations, these appeared in austral summer (Negro and Uruguay rivers) or early winter (Paraná River). A striking finding, both for annual and seasonal simulated time series, is the conspicuous presence of pseudo-periods in the 2.5–5 years band that had already been captured in the observed 20th streamflow time series [Maciel, F., Díaz, A., and Terra, R., 2013. Multi-annual variability of streamflow in La Plata Basin. Part I: observations and links to global climate. International Journal of River Basin Management, 11 (4), 345–360.]. This pattern is probably linked to the El Niño–Southern Oscillation (ENSO) phenomenon. These results imply that the well-known relationships between ENSO and precipitation and streamflow anomalies in the LPB are expected to prevail during the twenty-first century.

The observed multi-annual variability of streamflow for three rivers (Paraná River (PR), Uruguay River (UR) and Negro River (NR)) in La Plata Basin (LPB) during the twentieth century is analysed. Several spectral methods (singular spectrum analysis, maximum entropy method and multi-taper method) are applied to annual and seasonal run-off time series in order to capture low frequency variability (LFV) modes and pseudo-periodic patterns. Very robust quasi-periods in the three to six years band are detected for the three rivers, suggesting a strong link with El Niño-Southern Oscillation. Pseudo-cycles of eight to nine years appear in NR and UR. No quasi-periods above 10 years are obtained for any of the rivers. The three rivers exhibit significant LFV components associated with increasing trends that show a clear seasonality. For PR, LFV modes appear between May and December while for UR this occurs during December to April. Both periods cover the whole annual cycle, giving rise to complementary behaviours in the timing of trends of these two rivers. Remarkably, for the three rivers, the most intense increasing trend and the minimum streamflow occur at the same time of the annual cycle. Six global climate indices are selected in order to analyse the relationship between the multi-year streamflow variability modes in LPB and those of global climate: Niño 3.4 (N3.4), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), Southern Annular Mode (SAM) and Global Temperature Trend (GTT). Similar to the rivers, almost all these indices present very robust modes of variability in the 3–4.5 years band. Except for N3.4 and PDO, the indices show significant LFV modes that exhibit a pronounced increase at the common end of their records. The NAO, AMO and SAM seem to behave in a nearly cyclic way with periods longer than 60 years while the GTT increases steadily along the whole register.