Estimating estuarine suspended sediment concentration through spectral indices and band ratios derived from Sentinel-2 data: a case of Umzimvubu Estuary, South Africa

The current study was aimed at evaluating the reliability and efficacy of selected remote sensing band ratios and indices in accurately estimating the spatial patterns of suspended sediment concentration level in Umzimvubu Estuary, Eastern Cape, South Africa. Sentinel-2 imagery was acquired on the 29th of March 2022. Band reflectance values were extracted from Sentinel -2 imagery, and laboratory measurements of suspended sediment concentration were obtained from samples collected from fifty (50) sampling points in the estuary on the 29th of March 2022. Sentinel-2 imagery was then validated with the field data in estimating and mapping the suspended sediment concentration. Several remote sensing band ratios Red/(Green plus Near-Infrared), Near-Infrared/Green, Red plus Near-Infrared/Green, Blue(Green plus Red)/Blue and Green plus Near-Infrared)/Blue and indices, that is the Normalised Difference Turbidity Index (NDTI), Normalized Difference Suspended Sediment Index (NDSSI) and Normalized Suspended Material Index (NSMI)) were then used to predict the suspended sediment concentration from Sentinel-2 imagery. The accuracy of band ratios and indices was evaluated by correlating the prediction against the observed suspended sediment concentration from Sentinel-2 imagery. A total of 50 points were randomly surveyed in the Umzimvubu estuary for analyzing suspended sediment concentration. Results indicate that the Blue (Green plus Red)/Blue, the Green plus Near-Infrared)/Blue and NMSI performed well based on their R-squared. The Blue (Green plus Red)/Blue and Green + Near-Infrared)/Blue band ratios had 0.86 and 0, 94, respectively. While NSMI yielded an R-squared of 0,76 and RMSE of 19,2 mg/L. The results in the current study indicate that Sentinel-2 imagery can reliably estimate the concentration of suspended sediment level in the Umzimvubu Estuary using band ratios and indices.Thesis (MSc) -- Faculty of Science and Agriculture, 202

Estimating estuarine suspended sediment concentration through spectral indices and band ratios derived from Sentinel-2 data: a case of Umzimvubu Estuary, South Africa

The current study was aimed at evaluating the reliability and efficacy of selected remote sensing band ratios and indices in accurately estimating the spatial patterns of suspended sediment concentration level in Umzimvubu Estuary, Eastern Cape, South Africa. Sentinel-2 imagery was acquired on the 29th of March 2022. Band reflectance values were extracted from Sentinel -2 imagery, and laboratory measurements of suspended sediment concentration were obtained from samples collected from fifty (50) sampling points in the estuary on the 29th of March 2022. Sentinel-2 imagery was then validated with the field data in estimating and mapping the suspended sediment concentration. Several remote sensing band ratios Red/(Green plus Near-Infrared), Near-Infrared/Green, Red plus Near-Infrared/Green, Blue(Green plus Red)/Blue and Green plus Near-Infrared)/Blue and indices, that is the Normalised Difference Turbidity Index (NDTI), Normalized Difference Suspended Sediment Index (NDSSI) and Normalized Suspended Material Index (NSMI)) were then used to predict the suspended sediment concentration from Sentinel-2 imagery. The accuracy of band ratios and indices was evaluated by correlating the prediction against the observed suspended sediment concentration from Sentinel-2 imagery. A total of 50 points were randomly surveyed in the Umzimvubu estuary for analyzing suspended sediment concentration. Results indicate that the Blue (Green plus Red)/Blue, the Green plus Near-Infrared)/Blue and NMSI performed well based on their R-squared. The Blue (Green plus Red)/Blue and Green + Near-Infrared)/Blue band ratios had 0.86 and 0, 94, respectively. While NSMI yielded an R-squared of 0,76 and RMSE of 19,2 mg/L. The results in the current study indicate that Sentinel-2 imagery can reliably estimate the concentration of suspended sediment level in the Umzimvubu Estuary using band ratios and indices.Thesis (MSc) -- Faculty of Science and Agriculture, 202

Remote sensing and bio-geo-optical properties of turbid, productive inland waters: a case study of Lake Balaton

Algal blooms plague freshwaters across the globe, as increased nutrient loads lead to eutrophication of inland waters and the presence of potentially harmful cyanobacteria. In this context, remote sensing is a valuable approach to monitor water quality over broad temporal and spatial scales. However, there remain several challenges to the accurate retrieval of water quality parameters, and the research in this thesis investigates these in an optically complex lake (Lake Balaton, Hungary). This study found that bulk and specific inherent optical properties [(S)IOPs] showed significant spatial variability over the trophic gradient in Lake Balaton. The relationships between (S)IOPs and biogeochemical parameters differed from those reported in ocean and coastal waters due to the high proportion of particulate inorganic matter (PIM). Furthermore, wind-driven resuspension of mineral sediments attributed a high proportion of total attenuation to particulate scattering and increased the mean refractive index (n̅p) of the particle assemblage. Phytoplankton pigment concentrations [chlorophyll-a (Chl-a) and phycocyanin (PC)] were also accurately retrieved from a times series of satellite data over Lake Balaton using semi-analytical algorithms. Conincident (S)IOP data allowed for investigation of the errors within these algorithms, indicating overestimation of phytoplankton absorption [aph(665)] and underestimation of the Chl-a specific absorption coefficient [a*ph(665)]. Finally, Chl-a concentrations were accurately retrieved in a multiscale remote sensing study using the Normalized Difference Chlorophyll Index (NDCI), indicating hyperspectral data is not necessary to retrieve accurate pigment concentrations but does capture the subtle heterogeneity of phytoplankton spatial distribution. The results of this thesis provide a positive outlook for the future of inland water remote sensing, particularly in light of contemporary satellite instruments with continued or improved radiometric, spectral, spatial and temporal coverage. Furthermore, the value of coincident (S)IOP data is highlighted and contributes towards the improvement of remote sensing pigment retrieval in optically complex waters

Research trends in the use of remote sensing for inland water quality science: Moving towards multidisciplinary applications

Remote sensing approaches to measuring inland water quality date back nearly 50 years to the beginning of the satellite era. Over this time span, hundreds of peer-reviewed publications have demonstrated promising remote sensing models to estimate biological, chemical, and physical properties of inland waterbodies. Until recently, most of these publications focused largely on algorithm development as opposed to implementation of those algorithms to address specific science questions. This slow evolution contrasts with terrestrial and oceanic remote sensing, where methods development in the 1970s led to publications focused on understanding spatially expansive, complex processes as early as the mid-1980s. This review explores the progression of inland water quality remote sensing from methodological development to scientific applications. We use bibliometric analysis to assess overall patterns in the field and subsequently examine 236 key papers to identify trends in research focus and scale. The results highlight an initial 30 year period where the majority of publications focused on model development and validation followed by a spike in publications, beginning in the early-2000s, applying remote sensing models to analyze spatiotemporal trends, drivers, and impacts of changing water quality on ecosystems and human populations. Recent and emerging resources, including improved data availability and enhanced processing platforms, are enabling researchers to address challenging science questions and model spatiotemporally explicit patterns in water quality. Examination of the literature shows that the past 10-15 years has brought about a focal shift within the field, where researchers are using improved computing resources, datasets, and operational remote sensing algorithms to better understand complex inland water systems. Future satellite missions promise to continue these improvements by providing observational continuity with spatial/spectral resolutions ideal for inland waters

Research investigation into the Ventura River watershed: Geoliteracy, stormwater, and community activity

Presently, scientific communities are confronting Earth’s foremost environmental issues using best management practices. However, an increase for need in the synthesis of socio-ecological principles using a multi- and trans-disciplinary approach is required for solutions that benefit both nature and humans. To examine whether a community perceives stormwater runoff as both a local resource and threat to coastal water quality, an online survey of the Ventura River watershed community probed local residents’ understanding of watershed knowledge, beliefs, and behavior with regards to their local environment as it pertained to water resources, especially as affected by human activity. Analysis of 144 participants’ responses and their self-reported water activity, water activity frequency, and perceptions of Ventura River’s discharge and stormwater runoff reveals the community’s behavior regarding exposure to poor water quality in a local coastal environment and, ultimately, the survey participants’ level of geoliteracy concerning their local watershed. A statistical analysis between categorical variables of the survey questions examines relationships between self-reported waterborne illness symptoms and the water activities that participants enjoy regularly and/or perform for work. The survey responses demonstrated common themes in water knowledge that exist throughout this particular coastal community. Additionally, through the use of an optical and historical classification system, the Ventura River’s sediment discharge was examined both remotely and in situ. Multispectral ocean color satellite sensors have been useful in monitoring the water quality of Case 2 waters. Particularly, after severe storm events contaminants can be carried along with storm runoff from urban storm drains and Mediterranean river mouths which then enter coastal and recreationally trafficked water. Earth scientists have observed poor water quality occurring offshore in Case 2 waters near major river mouths and urban areas causing the coastal water column to deteriorate in quality

Analyse der Wasserfarbe von Seen mithilfe räumlich hoch und mittel auflösender Satelliten

Remote sensing techniques can assist traditional lake monitoring approaches by supplying spatial information on optically active lake ecology indicators, i.e. chlorophyll-a (CHL), total suspended matter (TSM), coloured dissolved organic matter (CDOM), and, especially in optically shallow waters, water depth and substrate composition. The present thesis provides an overview on the current research status concerning lake remote sensing and the benefit of time series analyses for lake ecology. To investigate the suitability of Sentinel-2 and Landsat 8 for lake monitoring and their combination with other sensors this thesis focused on two study areas with highly different optical characteristics, i.e. the oligotrophic Lake Starnberg (southern Germany) and the mesotrophic-eutrophic Lake Kummerow (northern Germany). Using the bio-optical model WASI-2D, Sentinel-2A turned out to be suited for retrieving low TSM and CDOM values. The high spatial resolution enabled the differentiation between bare ground and areas covered by submerged aquatic vegetation. Water depth estimations performed well until half Secchi disk depth. Cross-sensor comparisons demonstrated high correlation of CHL among timely acquired, spatially high and medium resolved sensors. Evaluations with in situ data showed that most of the sensor-in situ match-ups were within an uncertainty range of in situ measurements. Analysing a 9-year MERIS time series with FUB/WeW revealed unprecedented information on temporal trends and seasonal behaviour of CHL, TSM and CDOM at the study area Lake Kummerow. Combining CHL, retrieved with the Modular Inversion and Processing System, from different satellite sensors (MODIS, Landsat 7/ 8, Sentinel-2A) enabled detailed observations of phytoplankton development. Such combinations are a step forward to future lake analyses which may integrate remote sensing data, in situ measurements and environmental modelling.Fernerkundungstechniken können das Seemonitoring mit räumlichen Informationen über optisch aktive Indikatoren der Gewässerökologie liefern, z.B. Chlorophyll-a (CHL), suspendierte Schwebstoffe (TSM), Gelbstoffe (CDOM) und insbesondere in optisch flachen Gewässern, Wassertiefe und Substratbedeckung. Die vorliegende Arbeit gibt einen Überblick über den aktuellen Forschungsstand zur Seefernerkundung und den Nutzen von Zeitreihenanalysen für die Seeökologie. Um die Eignung von Sentinel-2 und Landsat 8 für ein Seenmonitoring und deren Kombination mit anderen Sensoren zu untersuchen, konzentrierte sich diese Arbeit auf zwei Untersuchungsgebiete mit sehr unterschiedlichen optischen Eigenschaften: den oligotrophen Starnberger See (Süddeutschland) und den mesotroph-eutrophen Kummerower See (Norddeutschland). Mit dem bio-optischen Modell WASI-2D erwies sich Sentinel-2A als geeignet, um niedrige TSM- und CDOM-Werte zu bestimmen. Die hohe räumliche Auflösung ermöglichte eine Unterscheidung zwischen unbewachsenem und mit Makrophyten bewachsenem Untergrund. Die Wassertiefenbestimmung verlief bis zur halben Sichttiefe gut. Sensorübergreifende Vergleiche zeigten eine hohe Korrelation von CHL zwischen zeitnah erfassten, räumlich mittel und hoch aufgelösten Sensoren. Auswertungen mit in-situ-Daten zeigten, dass die meisten Sensor-in-situ-Match-ups innerhalb eines Unsicherheitsbereichs von in-situ-Messungen lagen. Die Analyse einer 9-jährigen MERIS-Zeitreihe mit FUB/WeW ergab neue Informationen über zeitliche Trends und saisonales Verhalten von CHL, TSM und CDOM im Untersuchungsgebiet Kummerow See. Die Kombination von CHL aus verschiedenen Satellitensensoren (MODIS, Landsat 7/ 8, Sentinel-2A) mit dem Modular Inversion and Processing System ermöglichte detaillierte Beobachtungen der Phytoplanktonentwicklung. Solche Kombinationen sind ein Schritt für zukünftigen Gewässeranalysen, die Fernerkundungsdaten, in-situ-Messungen und Umweltmodellierung integrieren sollten

Spatio-temporal distribution of temperature, salinity and suspended sediment on the deltaic front of the Magdalena River: Influence on nutrient concentration and primary productivity

The characteristics of estuaries depend mainly on the magnitude and variability of river discharge and tidal forcing (Kjerfve, 1994). Estuaries present strong temporal and spatial gradients with respect to their physical, chemical and biological properties, as a result of changes in fluvial contributions (Nogueira et al., 1997). Therefore, biogeochemical processes are extremely complex (Fourqurean et al., 1993; Fernández-Nóvoa et al., 2015). Temperature and salinity are the most relevant features of coastal marine ecosystem dynamics (Urquhart et al., 2013), as variations in these parameters can influence the movement of water masses, water column stratification caused by density differences, transport of sediments, and mixing conditions (Bianchi, 2007; Geyer, 2010; Obeso-Nieblas et al., 2012; Osadchiev et al., 2017). Also, temperature and salinity may play roles in nutrient distributions and concentrations (Windom et al., 2006), and biogeochemical processes and ecological productivity, through alterations in biochemical reactions that regulate the enzymatic processes of respiration and photosynthesis (Xia and Jiang, 2015; Quamrul et al., 2016). The physical dynamics of estuaries/deltas of the micro-tidal domain, which are highly stratified and turbid, have been little studied. Therefore, we lack detailed knowledge regarding relationships among spatio-temporal variations in salinity and temperature, the extent and structure of convergence fronts and the mixed layer, nutrient distribution and primary productivity in this type of estuary

Multidecadal Remote Sensing of Inland Water Dynamics

Remote sensing approaches to measuring inland water dynamics date back more than 50 years. These approaches rely on the unique spectral properties of different waterbodies to delineate surface extents and estimate optically active water quality parameters. Until recently, inland water remote sensing focused largely on localized study domains due to limitations in modelling methods, computing power, and data access. Recent advances in these areas have created novel opportunities for data-driven-multidecadal remote sensing of inland waters at the landscape scale. Here, I highlight the history of inland water remote sensing along with the dominant methodologies, water quality constituents, and limitations involved. I then use this background to contextualize three macroscale inland water remote sensing studies of increasing complexity. The first combines field measurements with remotely sensed surface water extents to identify the impacts of small-scale gold mining in Peru. Our results suggest that mining is leading to synergistic increases in lake area and mercury loading that are significantly heightening exposure risk for people and wildlife. I move from measuring lake extents in Peru to measuring lake color in over 26,000 lakes across the United States. This analysis shows that lake color seasonality can be generalized into five distinct phenology groups that follow well-known patterns of algae growth and succession. The stability of a given lake (i.e. the likelihood it will move from one phenology group to another) is tied to lake and landscape level characteristics including climate and population density. Finally, I move from simple parameters such as quantity and color to estimating multidecadal changes in water clarity in U.S. lakes. I show that lake water clarity in the U.S. has increased by an average of 0.52 cm yr-1 since 1984, largely as a result of extensive U.S. freshwater pollution abatement measures. In combination, these three studies highlight that data intensive remote sensing approaches are expanding the capabilities of inland water remote sensing from local to global scales, and that macroscale remote sensing of inland waters reveals trends and processes that are unobservable using field data alone.Doctor of Philosoph

Pareamento bacia-lagoa usando modelagem hidrológica-hidrodinâmica e sensoriamento remoto

A gestão de recursos hídricos tornou-se cada vez mais complexa devido ao rápido crescimento sócio-econômico e as mudanças ambientais nas bacias hidrográficas nas últimas décadas. Modelos computacionais são importantes ferramentas de suporte na gestão de recursos hídricos e tomada de decisões devido a sua funcionalidade, provendo informações importantes sobre os principais processos físicos, químicos e biológicos, e permitindo melhorar o entendimento desses processos, os quais ocorrem em diferentes escalas espaciais e temporais. Na presente tese, o objetivo foi compreender o funcionamento hidrológico do sistema integrado bacia hidrográfica - lagoa, e os efeitos na hidrodinâmica do lago, utilizando como suporte o acoplamento da modelagem hidrológica - hidrodinâmica, e o uso de técnicas de sensoriamento remoto para o monitoramento de parâmetros de qualidade da água (e.g., clorofilaa, temperatura da superfície d’água e níveis da água). A área de estudo é a bacia hidrográfica da Lagoa Mirim, localizada no sul do Brasil, possuindo uma área total de 58.000 km2 (56% no Uruguai e o restante no Brasil). Foram propostos e testados modelos empíricos para estimativa de clorofila-a emumlago raso subtropical, baseados em imagens do sensor MODIS e técnicas estatísticas. Além disso, foi desenvolvido e avaliado o acoplamento da modelagem hidrológica-hidrodinâmica de grande escala e o sensoriamento remoto. O modelo hidrológico distribuído de grande escala MGBIPH acoplado com o modelo hidrodinâmico IPH-ECO foi utilizado para simular a bacia hidrográfica e os principais componentes hidrodinâmicos da Lagoa Mirim. O modelo mostrou bom desempenho quando comparado com observações de vazões, além de dados provenientes de sensoriamento remoto, através de altimetria espacial. As simulações mostraram importantes aspectos sobre a estrutura de fluxo, campos de velocidade e níveis d’água na lagoa, assim como a influência de grandes rios, forçantes externas como o vento (intensidade e direção) e o impacto do estressor antrópico (retiradas para irrigação) no sistema. As simulações permitiram avaliar aspectos relacionados com as variações espaciais e temporais (diurna, mensal, sazonal e inter-anual) da temperatura da superfície da água, a dinâmica dos fluxos de calor (sensível e latente) e os efeitos de eventos meteorológicos de pequena escala como frentes frias, os quais têm um impacto significativo sobre a temperatura superficial da água e os fluxos de calor na lagoa. Quanto aos modelos empíricos para estimativa de clorofila-a a partir do MODIS, os resultados mostram que um simples e eficiente modelo desenvolvido a partir de análise de regressão múltipla, apresentou ligeiras vantagens sobre os modelos de redes neurais artificiais, modelos multiplicativos não paramétricos e modelos empíricos (e.g., Appel, Kahru, FAI e O14a) usualmente utilizados na estimativa de Chl-a em ambientes aquáticos. Resultados também indicam que é inapropriado generalizar um único modelo desenvolvido a partir do conjunto total de dados, para estimar concentrações de Chl-a na lagoa, o que corrobora a heterogeneidade espacial na distribuição de Chl-a e as diferenças entre regiões (litoral e pelágica). A modelagem hidrológica-hidrodinâmica de grande escala apoiada por informação de sensoriamento remoto, mostrou ser uma abordagem promissora para o entendimento da estrutura e funcionamento de lagoas rasas de grande porte e longo prazo, úteis para a gestão integrada dos recursos hídricos.The last decade, the water resource management is being complex due to the rapid socioeconomic development and environmental changes in river basins. Computations models are important support tools in water resource management and make decision providing important information and allowing a better comprehension of the physical, chemical and biologic processes, which occur in di erent temporal/spatial scales. In this thesis, the objective was to understand the hydrological functioning of the integrated basin- lake system and its e ects on hydrodynamics, using hydrodynamic - hydrodynamic modeling and water quality monitoring (e.g., chlorophyll-a, water surface temperature and water levels) from remote sensing techniques. The study area is the Lake Mirim basin, located between Brazil and Uruguay (basin total area 58.000 km2). Empirical models were proposed and tested to chlorophyll-a estimation in a shallow subtropical lake, based on MODIS imagery and statistics techniques. In addition, we developed and assessed the coupling of large scale hydrological/hydrodynamic modeling and remote sensing techniques. The large-scale distributed hydrological model MGB-IPH coupled with the hydrodynamic model IPHECO were used to simulate the river basin and the hydrodynamic components of the Lake Mirim. The coupled model showed good performance when compared to in-situ measurements and satellite altimetry data. The simulations showed important aspects relate to flow structure, velocity fields and lake water levels, as well as the influence of large rivers, external forcing as such the wind (intensity and direction), and the impact of anthropogenic stressors (irrigation withdrawals) in the system. The simulations allowed assessing the spatial and temporal variations (diurnal, monthly, seasonal and inter-annual) in the water surface temperature, heat fluxes dynamics (sensible and latent) and the e ects of short time-scale events, as such cold fronts passages over the lake, which cause strong impacts on the water surface temperature and heat fluxes in the lake. Regarding the empirical models developed to chlorophyll-a estimation from MODIS imagery, the results showed that a simple and e cient model developed from multiple regression analysis, performed best in comparison with artificial neural network models, non-parametric multiplicative models, and empirical models (e.g., Appel, Kahru, FAI and O14a) common used in the Chl-a estimation in aquatics environments. Results also indicated that is inappropriate to generalize a single model developed from the total datasets to estimates Chl-a in the lake, which corroborates the spatial heterogeneity (Chl-a distribution) and the di erences among regions (littoral and pelagic). The synergy between large-scale hydrological-hydrodynamic modeling, in situ measurements and remote sensing techniques provided a promising approach to improve the comprehension of the structure and ecosystem functioning of large shallow lakes in long-term time scale, useful to water resources management

Remote Sensing of the Aquatic Environments

The book highlights recent research efforts in the monitoring of aquatic districts with remote sensing observations and proximal sensing technology integrated with laboratory measurements. Optical satellite imagery gathered at spatial resolutions down to few meters has been used for quantitative estimations of harmful algal bloom extent and Chl-a mapping, as well as winds and currents from SAR acquisitions. The knowledge and understanding gained from this book can be used for the sustainable management of bodies of water across our planet