Turbidity Patterns Research Articles

Remotely sensed seasonal dynamics of an estuarine plume in the coastal zone of El Rincón system (Southwestern Atlantic Ocean)

In this work we analyzed 18 years (2003–2021) of MODIS-Aqua daily images and multi-annual monthly mean turbidity maps to provide a comprehensive characterization of seasonal patterns of turbidity in the transitional area between the mouth of the Bahía Blanca Estuary and the adjacent inner shelf (El Rincón coastal system, Argentina). Field measurements collected in the study area were combined with MODIS data processed under different schemes of atmospheric correction before turbidity retrieval. Then, an Empirical Orthogonal function (EOF) analysis was used to assess the temporal patterns of turbidity and their regional variability over the inner shelf. Through a Generalized Linear Model (GLM), changes in the turbidity plume were further associated with environmental forcing (i.e. tides, winds and precipitation) controlling the seasonal dynamics. A strong gradient of decreasing turbidity from the northeast (close to the estuarine region) to the southwest (coastal region) was detected, while a major spatial pattern of annual variability, characterized by decreasing seasonality from northwest to southeast was defined. According to our results, the frequency of northwest wind direction and the impact of the wind mixing are considered as primary factors that shape the seasonal variability of turbidity with a strong winter dominance of largest plume events. The results found in this study are key to understanding the general dynamics of biological activity in the regional waters and the implications that climate variability might have on this complex ecosystem.

Prediction of the Turbidity Distribution Characteristics in a Semi-Enclosed Estuary Based on the Machine Learning

This study addresses the critical challenge of predicting sediment behavior in a semi-enclosed estuary, where the interplay between artificial freshwater discharge and seawater significantly impacts turbidity. Such environments are characterized by complex hydrodynamic interactions that lead to cycles of sediment settling and resuspension, influenced by tidal forces. To tackle this problem, we employed machine learning, leveraging its capability to analyze and predict complex non-linear phenomena. Our approach involved extensive transect observations conducted over two years, encompassing 11 ebb tide and 9 flood tide cycles. These observations were crucial for training the machine learning model, ensuring it captured the nuanced dynamics of sediment behavior under varying hydrodynamic conditions. The necessity of this research lies in its potential to enhance our understanding of sediment dynamics in estuaries, a vital aspect for environmental management and engineering projects. The findings demonstrate a promising alignment between the machine learning model’s predictions and the theoretically assumed sediment behavior, highlighting the model’s effectiveness in deciphering and predicting turbidity patterns in these challenging environments.

Monitoring river turbidity after a mine tailing dam failure using an empirical model derived from Sentinel-2 imagery.

Sudden failure of a mine tailing dam occurred in the municipality of Brumadinho, Minas Gerais, Brazil, on January 25, 2019. Approximately 12 million cubic meters of mine tailings discharged into the Paraopeba River, producing strong environmental and societal impacts, mainly due to a massive increase in turbidity (occasionally exceeding 50,000 Nephelometric Turbidity Units [NTU] (CPRM 2019). Remote sensing is a well-established tool for quantifying spatial patterns of turbidity. However, a few empirical models have been developed to map turbidity in rivers impacted by mine tailings. Thus, this study aimed to develop an empirical model capable of producing turbidity estimates based on images from the Sentinel-2 satellite, using the Paraopeba River as the study area. We found that river turbidity was most strongly correlated with the sensor's near-infrared band (NIR) (band 8). Thus, we built an empirical single-band model using an exponential function with an (R2 of 0.91) to characterize the spatial-temporal variation of turbidity based on satellite observations of NIR reflectance. Although the role of discharged tailings in the seasonal variation of turbidity is not well understood, the proposed model enabled the monitoring of turbidity variations in the Paraopeba River associated with seasonal resuspension or deposition of mine tailings. Our study shows the capability of single-band models to quantify seasonal variations in turbidity in rivers impacted by mine tailing pollution.

Turbidity dynamics of large lakes and reservoirs in northeastern China in response to natural factors and human activities

The water environment has experienced prominent changes worldwide in recent decades, especially in inland waters. As an important lake region in China, the water turbidity of lakes/reservoirs in the Northeast Plain-Mountainous Region (NPLR) remains less understood, especially the influencing mechanisms of regional climatic conditions and human activities. To enhance the knowledge of turbidity dynamics and explanatory variables of NPLR water bodies, long-term turbidity estimates of lakes/reservoirs were derived from Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua observations between 2003 and 2019. The results show that most lakes/reservoirs became less turbid in NPLR during the study period, as indicated by a decreasing turbidity trend of 0.05–2.4 nephelometric turbidity units (NTU)/year. Overall, the decreased turbidity was mainly attributed to the decreased wind speed (from 2003 to 2012, r = 0.85, p < 0.01), but also to the increased normalized difference vegetation index (NDVI) of the forest region (r = −0.80, p < 0.01), with the latter being a result of the forest protection efforts of the Chinese government. The increased snowmelt depth also contributed to a substantial turbidity decline in April. In addition, distinct seasonal patterns of turbidity were observed in the NPLR, with less turbid water in the wet season (i.e., from June to August) and turbid water in the dry season (i.e., October, November, and April in the next year). This result is attributed to the rapid seasonal dynamics of precipitation and runoff. This study provided a comprehensive analysis on the influencing mechanisms of turbidity dynamics in NPLR lakes; in particular, for the first time, revealed the impacts of the national policy-mandated forest development and the snowmelt depth on lake turbidity. These findings will provide vital information for government decision-making in water environment protection in NPLR and other similar areas with densely distributed lakes.

Monitoring Water Turbidity in a Temperate Floodplain Using UAV: Potential and Challenges

The Lake Saint-Pierre (LSP) is a wide (≈300 km2) and shallow (≈3 m) lake created through a widening of the St. Lawrence River. Each spring, freshet makes it the largest floodplain in the province of Quebec. Agricultural practices in the littoral increase the water turbidity, which deteriorate the habitat’s quality of many fish species. However, measuring spatio-temporal turbidity patterns in the LSP floodplain remain difficult because turbidity is highly variable in space and time. This study aims to evaluate the potential to use an Unmanned Aerial Vehicle (UAV) to measure the water turbidity in the LSP’s floodplain. The results show that the UAV can efficiently measure the variation of turbidity in the LSP with a RMSE of 28.22 FNU. We also compared the turbidity retrieved from UAV with those retrieved from Sentinel-2 observations. The results show that the two models are comparable, even if Sentinel-2 yields better results. However, challenges remain when using UAV for turbidity monitoring, such as software limitations for mosaics creation over large water bodies. Nevertheless, the high spatial and temporal information can provide insights into the complex water turbidity patterns which characterize floodplains. The method could help land use management to improve the water quality of these ecosystems.

Turbidity and Estimated Phosphorus Retention in a Reconnected Lake Erie Coastal Wetland

Nearly all of the wetlands in the coastal zone of Lake Erie have been degraded or destroyed since the 1860s, and most of those that remain are separated from their watersheds by earthen dikes. Hydrologic isolation of these wetlands disrupts ecosystem benefits typical to Great Lakes coastal wetlands, particularly the ability to trap sediments and retain nutrients when inundated by runoff and lake water. High-frequency measurements of turbidity and discharge were taken in 2013 and 2014 to observe turbidity and water flow dynamics to estimate total phosphorus flux of a hydrologically reconnected diked wetland pool in the Crane Creek-Lake Erie wetland complex. Modeled estimates suggest the reconnected pool retained 8% of the total phosphorus loading in 2013 and 10% in 2014, which included short periods of phosphorus export to Lake Erie. Water flowing out of the wetland generally had lower turbidity than inflowing water, but flux in and out of the pool varied seasonally and was linked to changes in lake-levels, seiche dynamics, and weather conditions. More frequent storms, higher winds, and stronger seiches in the spring and fall created turbidity patterns that suggest more phosphorus retention than in summer or winter. Estimates suggest that phosphorus was released during the summer when higher lake levels and the absence of frequent storms, larger short-term seiche oscillations, and potentially soil oxygen availability were driving flux dynamics. This study demonstrated that reestablishing lake hydrology through reconnection of wetland pools can reduce loading and alter timing of delivery of total phosphorus to Lake Erie.

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

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.

Buckwheat (Fagopyrum esculentum Moench) characterization as adjunct in beer brewing

Given the scenario of buckwheat cultivation in Brazil, the research was developed evaluating its insertion in beer production as adjunct. The samples of interest were made with 55% (w/w) barley malt and 45% (w/w) buckwheat malt (45BWM), referenced to 100% Pilsen malt beer (AM). The results showed that the buckwheat malt wort had a 96.27% dry base extract, equivalent to the standard result. It also showed that glucose content increased 3 times, while the maltose and maltotriose have balances proportional. The use of buckwheat malt raised the protein content in more than 89%, which is not seen from the use of other adjuncts and showed greater colloidal stability during the storage period, a factor associated with a 4-fold reduction of gluten content. Similar aspects regarding foam and turbidity pattern, although subtle differences in aromatic profile and flavors were present. Nevertheless, these factors show that is possible to use buckwheat as an adjunct in a Pilsen beer. The remaining sugars content gave a perspective on the metabolism of yeast during fermentation and the identification of some compounds by HPLC-MS was also able to demonstrate how buckwheat malt affected yeast metabolism due to wort composition.

Trends in water quality in a subtropical Australian river-estuary system: Responses to damming, climate variability and wastewater discharges

The Logan-Albert estuary in southeast Queensland, Australia, has high biodiversity and supports multiple economic and recreational services. Elevated nutrient and sediment loads have been a longstanding management issue for the estuary. We investigated the spatial and seasonal patterns of nutrients and turbidity along the Logan-Albert estuary and assessed the effects of a recently constructed upstream dam. Nutrient concentrations and turbidity levels were analysed using 15 years of monitoring data from 19 water quality sites throughout the estuary. We hypothesised that the construction of Wyaralong Dam would act as a nutrient and sediment sink which may have positive effects on downstream water quality. Long-term trends of water quality constituents were evaluated using a non-parametric seasonal Mann-Kendall test and the effect of upstream impoundment was assessed with a Before-After Control-Impact (BACI) test. Nutrient concentrations and turbidity levels declined significantly with time in the upper Logan estuary and, to a lesser extent, in the lower Albert estuary. The general improvement of water quality in the upper Logan estuary was attributed to construction of the Wyaralong Dam. Significant decreases in concentrations of total phosphorus (TP) and oxidised nitrogen (NOx-N) along the lower Albert were principally attributed to wetter conditions over the 15-year dataset, which diluted point-source loads from a nearby wastewater treatment plant (WWTP). Our results show that estuarine water quality changes can be highly dynamic with interactions amongst climate and management practices that necessitate long-term monitoring programs with good spatial coverage.

Remote sensing of water turbidity in the Eastern China Seas from Geostationary Ocean Colour Imager

ABSTRACTWater turbidity plays an important role in marine biogeochemical processes and ecosystem. Remote sensing of water turbidity in the Eastern China Seas is still a challenging task due to its large variations spanning more than three orders from coastal highly turbid waters to offshore clear waters. Thus, this study developed a new blended remote sensing algorithm for accurately estimating water turbidity in the whole Eastern China Seas from Geostationary Ocean Colour Imager (GOCI). The general idea of the new blended algorithm is to combine the band forms with the best abilities for deriving water turbidity in turbid waters and relatively clear waters, respectively. Evaluations based on field data showed a good performance of the new blended algorithm with values of the determination coefficient (R2), root-mean-square error (RMSE), mean absolute error (MAE), and mean relative error (MRE) of 0.884, 47.96 NTU, 29.59 and 48.13%, respectively. The proposed algorithm was applied to the GOCI data of 2015; and large spatiotemporal variations of water turbidity in the Eastern China Seas were observed. High values of water turbidity were observed in winter for both coastal and offshore waters, whereas the lowest values were observed in summer. Sediment resuspension drove by wind and tidal forcing, and sediment transportation related to current might be responsible for spatiotemporal variations of water turbidity, while the detailed study is required for further investigations. Overall, this study provides a technological basis which can be used to understand the variation patterns of water turbidity in the Eastern China Seas from GOCI satellite measurements.

Remote Sensing Retrieval of Turbidity in Alpine Rivers based on high Spatial Resolution Satellites

Turbidity, relating to underwater light attenuation, is an important optical parameter for water quality evaluation. Satellite estimation of turbidity in alpine rivers is challenging for common ocean color retrieval models due to the differences in optical properties of the water bodies. In this study, we present a simple two-band semi-analytical turbidity (2BSAT) retrieval model for estimating turbidity in five alpine rivers with varying turbidity from 1.01 to 284 NTU. The model was calibrated and validated, respectively, while using one calibration dataset that was obtained from the Three Parallel Rivers basin and two independent validation datasets that were obtained from the Kaidu River basin and the Yarlung Zangbo River basin. The results show that the model has excellent performance in deriving turbidity in alpine rivers. We verified the consistency of the simulated reflectance and satellite-based reflectance and calibrated the 2BSAT model for the specified bands of high spatial resolution satellites in order to achieve the goal of remote sensing monitoring. It is concluded that the model can be used for the quantitative monitoring of turbidity in alpine rivers using satellite images. Based on the model, we used the Sentinel-2 images from one year to identify the seasonal patterns of turbidity of five alpine rivers and the Landsat series images from 1989 to 2018 to analyze the turbidity variation trends of these rivers. The results indicate that the turbidity of these alpine rivers usually presents the highest level in summer, followed by spring and autumn, and the lowest in winter. Meanwhile, the variation trends of turbidity over the past 30 years present distinctly different characteristics in the five rivers.

Sentinel 2 Analysis of Turbidity Patterns in a Coastal Lagoon

Coastal lagoons are transitional ecosystems with complex spatial and temporal variability. Remote sensing tools are essential for monitoring and unveiling their variability. Turbidity is a water quality parameter used for studying eutrophication and sediment transport. The objective of this research is to analyze the monthly turbidity pattern in a shallow coastal lagoon along two years with different precipitation regimes. The selected study area is the Albufera de Valencia lagoon (Spain). For this purpose, we used Sentinel 2 images and in situ data from the monitoring program of the Environment General Subdivision of the regional government. We obtained Sentinel 2A and 2B images for years 2017 and 2018 and processed them with SNAP software. The results of the correlation analysis between satellite and in situ data, corroborate that the reflectance of band 5 (705 nm) is suitable for the analysis of turbidity patterns in shallow lagoons (average depth 1 m), such as the Albufera lagoon, even in eutrophic conditions. Turbidity patterns in the Albufera lagoon show a similar trend in wet and dry years, which is mainly linked to the irrigation practice of rice paddies. High turbidity periods are linked to higher water residence time and closed floodgates. However, precipitation and wind also play an important role in the spatial distribution of turbidity. During storm events, phytoplankton and sediments are discharged to the sea, if the floodgates remain open. Fortunately, the rice harvesting season, when the floodgates are open, coincides with the beginning of the rainy period. Nevertheless, this is a lucky coincidence. It is important to develop conscious management of floodgates, because having them closed during rain events can have several negative effects both for the lagoon and for the receiving coastal waters and ecosystem. Non-discharged solids may accumulate in the lagoon worsening the clogging problems, and the beaches next to the receiving coastal waters will not receive an important load of solids to nourish them.

Long-Term High-Resolution Sediment and Sea Surface Temperature Spatial Patterns in Arctic Nearshore Waters Retrieved Using 30-Year Landsat Archive Imagery

The Arctic is directly impacted by climate change. The increase in air temperature drives the thawing of permafrost and an increase in coastal erosion and river discharge. This leads to a greater input of sediment and organic matter into coastal waters, which substantially impacts the ecosystems, the subsistence economy of the local population, and the climate because of the transformation of organic matter into greenhouse gases. Yet, the patterns of sediment dispersal in the nearshore zone are not well known, because ships do not often reach shallow waters and satellite remote sensing is traditionally focused on less dynamic environments. The goal of this study is to use the extensive Landsat archive to investigate sediment dispersal patterns specifically on an exemplary Arctic nearshore environment, where field measurements are often scarce. Multiple Landsat scenes were combined to calculate means of sediment dispersal and sea surface temperature under changing seasonal wind conditions in the nearshore zone of Herschel Island Qikiqtaruk in the western Canadian Arctic since 1982. We use observations in the Landsat red and thermal wavebands, as well as a recently published water turbidity algorithm to relate archive wind data to turbidity and sea surface temperature. We map the spatial patterns of turbidity and water temperature at high spatial resolution in order to resolve transport pathways of water and sediment at the water surface. Our results show that these pathways are clearly related to the prevailing wind conditions, being ESE and NW. During easterly wind conditions, both turbidity and water temperature are significantly higher in the nearshore area. The extent of the Mackenzie River plume and coastal erosion are the main explanatory variables for sediment dispersal and sea surface temperature distributions in the study area. During northwesterly wind conditions, the influence of the Mackenzie River plume is negligible. Our results highlight the potential of high spatial resolution Landsat imagery to detect small-scale hydrodynamic processes, but also show the need to specifically tune optical models for Arctic nearshore environments.

Application of Remote Sensing to Identify and Monitor Seasonal and Interannual Changes of Water Turbidity in Yellow River Estuary, China

AbstractWater turbidity is an important indicator for water security and environmental security in the Yellow River estuary. However, due to the complex terrain and harsh climatic environment, it is difficult to monitor the water turbidity over the complex surface of the estuary. In this study we applied a self‐organizing map clustering method, an artificial neural network clustering method, to extract turbidity patterns from the long‐term remote sensing data sets in the Yellow River estuary. Based on the Moderate Resolution Imaging Spectroradiometer data from 2000 to 2015, six turbidity patterns were identified by using the self‐organizing map clustering method: high turbidity pattern, moderate turbidity pattern, low turbidity pattern, very low turbidity pattern, extreme high turbidity pattern and sea ice pattern, and the first four patterns appear every year. All patterns have significant seasonal characteristics, and monthly turbidity is dominated by one of these turbidity patterns. The water turbidity in the estuary has decreased in the past 16 years, and the interannual variation of the turbidity pattern is the result of the combination of the sediment transported into the sea by the Yellow River and the wind and waves on the sea surface.

VIIRS-Derived Water Turbidity in the Great Lakes

Satellite ocean color products from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) since 2012 and in situ water turbidity measurements from the U.S. Environmental Protection Agency’s Great Lakes Environmental Database System are used to develop a water turbidity algorithm for satellite ocean color applications in the Great Lakes for water quality monitoring and assessments. Results show that the proposed regional algorithm can provide reasonably accurate estimations of water turbidity from satellite observations in the Great Lakes. Therefore, VIIRS-derived water turbidity data are used to investigate spatial and temporal variations in water turbidity for the entirety of the Great Lakes. Water turbidity values are overall the highest in Lake Erie, moderate in Lake Ontario, and relatively low in lakes Superior, Michigan, and Huron. Significantly high values in water turbidity appear in the nearshore regions, particularly in Thunder Bay (Lake Superior), Green Bay (Lake Michigan), and Saginaw Bay (Lake Huron). Seasonal patterns of water turbidity are generally similar in lakes Superior, Michigan, Huron, and Ontario, showing relatively high values in the spring and autumn months and lows in the winter season, while the seasonal pattern in Lake Erie is apparently different from the other lakes, with the highest value in the winter season and the lowest in the summer season. A strong interannual variability in water turbidity is shown in the time series of the VIIRS-derived water turbidity data for most of the lakes.

Satellite-based monitoring of contrasting characteristics of suspended sediment discharged from the Red and the Ma river systems along the northern coast of Vietnam

The northern coast of Vietnam has accumulated a significant amount of sediment discharged from the multiple distributaries of rivers such as the Red River and Ma River. While recent decreases of the sediment supply appears to have a significant impact on coastal erosion, the complex network of these distributaries makes it difficult to determine the overall spatiotemporal characteristics of sediment discharges and related topographic changes. The goal of the current study is to develop a satellite-based monitoring system for observation of turbidity discharged from the multiple rivers and to investigate the applicability of the developed monitoring system through a case study on the northern coast of Vietnam. Based on the in-situ observed data, a formula was determined for estimation of the surface water turbidity as a function of the red band reflectance of Moderate Resolution Imaging Spectro-radiometer (MODIS) images. The formula was then combined with a newly determined threshold for cloud-masking to obtain maps of the nearshore turbidity patterns. These maps capture the spatiotemporal water surface turbidity along the entire coast of the Red River Delta and the coast around the Ma River mouth over the past sixteen years with frequency of twice a day. Finally, long-term trends of the turbidity patterns from multiple rivers were compared with the in-situ observation data and it was found that the Red River and the Ma River showed clearly contrasting characteristics, which reasonably explain the recent coastal shoreline changes and characteristics of sediment sampled along the coast.

Using 250-M Surface Reflectance MODIS Aqua/Terra Product to Estimate Turbidity in a Macro-Tidal Harbour: Darwin Harbour, Australia

Turbidity is an indicator of the quality of water and usually exhibits variability associated with changing hydrodynamic conditions, which can be reflected in the sediment dynamics in coastal regions. Darwin Harbour is a typical macro-tidal, well mixed, and complex environment influenced by industries, human activities, and natural factors—including winds, currents, river discharges, waves, and tides. As a case study, hydrodynamics and sediment dynamics in Darwin Harbour are investigated using moderate resolution imaging spectroradiometer (MODIS) measurements. This study focuses on understanding the variability of turbidity, mechanisms that control the variations of turbidity and analyzing field data to determine the main factors that influence the sediment dynamics in Darwin Harbour. The results of this study illustrate the seasonal turbidity variation is mainly influenced by the wind waves. The dredging campaigns in 2013 and 2014 wet seasons contributed to the rise of turbidity in Darwin Harbour. The action of tidal currents appears to be the dominant factor controlling the turbidity pattern in a spring–neap cycle and the turbidity intra-tidal variation. In addition, the turbidity maximum zone (TMZ) near Charles Point is formed by the tidal current convergence based on the results of current modelling.

Reflectances of SPOT multispectral images associated with the turbidity of the Upper Gulf of California

&lt;p&gt;The use of satellite images for the observation and measurement of marine turbidity has been developed mainly with ocean colour sensors, such as MODIS. These images have a maximum spatial resolution of 250 m in their visible and infrared bands. In this research, images of the SPOT sensors were chosen as an alternative to overcome this limited spatial resolution. The objective was to prove the suitability of SPOT to measure turbidity in areas with great spatial variability. As a first step, all the images were standardized and the SPOT wavelength that had the largest association in the Principal Component Analysis was chosen (PCA). The results show that the bands of a SPOT multispectral image are highly redundant. The wavelength of the 610-680 nm (S2&lt;sub&gt;610-680&lt;/sub&gt;) obtained the best association in 89% of the 73 images analysed. The SPOT reflectance (R&lt;sub&gt;rs&lt;/sub&gt;) (S2&lt;sub&gt;610-680&lt;/sub&gt;) was compared with MODIS 620-670 nm (M1&lt;sub&gt;620-670&lt;/sub&gt;), which has already been tested in other research and has proved to be adequate for measuring turbidity. Both sensors performance was similar for low and moderate reflectance but for high reflectance, SPOT (S2&lt;sub&gt;610-680&lt;/sub&gt;) had a better performance than MODIS (M1&lt;sub&gt;620-670&lt;/sub&gt;). Additionally, the SPOT R&lt;sub&gt;rs&lt;/sub&gt; (S2&lt;sub&gt;610-680&lt;/sub&gt;) was associated with standardized Secchi disk depth data, which were measured in situ, to check SPOT suitability. SPOT R&lt;sub&gt;rs &lt;/sub&gt;(S2&lt;sub&gt;610-680&lt;/sub&gt;)images were classified into: 1) cold or warm season, 2) spring tide or neap tide and 3) water flux or reflux. These constructed scenarios allowed to see the result of the Standardized Space Anomalies, which showed the continuous presence of low and medium values in the most oceanic region of the Upper Gulf of California (UGC) and very high values in all the scenarios in the intertidal zone. This research has shown that SPOT R&lt;sub&gt;rs&lt;/sub&gt; (S2&lt;sub&gt;610-680&lt;/sub&gt;) is useful for observing, differentiating and measuring turbidity patterns in areas with very high spatial variability.&lt;/p&gt;

Spatio-temporal analysis of prodelta dynamics by means of new satellite generation: the case of Po river by Landsat-8 data

This paper describes a procedure to perform spatio-temporal analysis of river plume dispersion in prodelta areas by multi-temporal Landsat-8-derived products for identifying zones sensitive to water discharge and for providing geostatistical patterns of turbidity linked to different meteo-marine forcings. In particular, we characterized the temporal and spatial variability of turbidity and sea surface temperature (SST) in the Po River prodelta (Northern Adriatic Sea, Italy) during the period 2013–2016. To perform this analysis, a two-pronged processing methodology was implemented and the resulting outputs were analysed through a series of statistical tools. A pixel-based spatial correlation analysis was carried out by comparing temporal curves of turbidity and SST hypercubes with in situ time series of wind speed and water discharge, providing correlation coefficient maps. A geostatistical analysis was performed to determine the spatial dependency of the turbidity datasets per each satellite image, providing maps of correlation and variograms. The results show a linear correlation between water discharge and turbidity variations in the points more affected by the buoyant plumes and along the southern coast of Po River delta. Better inverse correlation was found between turbidity and SST during floods rather than other periods. The correlation maps of wind speed with turbidity show different spatial patterns depending on local or basin-scale wind effects. Variogram maps identify different spatial anisotropy structures of turbidity in response to ambient conditions (i.e. strong Bora or Scirocco winds, floods). Since the implemented processing methodology is based on open source software and free satellite data, it represents a promising tool for the monitoring of maritime ecosystems and to address water quality analyses and the investigations of sediment dynamics in estuarine and coastal waters.

Spatio-Temporal Variability in a Turbid and Dynamic Tidal Estuarine Environment (Tasmania, Australia): An Assessment of MODIS Band 1 Reflectance

Patterns of turbidity in estuarine environments are linked to hydrodynamic processes. However, the linkage between patterns and processes remains poorly resolved due to the scarcity of data needed to resolve fine scale highly dynamic processes in tidal estuaries. The application of remote sensing technology to monitor dynamic coastal areas such as estuaries offers important advantages in this regard, by providing synoptic maps of larger, constantly changing regions over consistent periods. In situ turbidity measurements were correlated against the Moderate Resolution Imaging Spectrometer Terra sensor 250 m surface reflectance product, in order to assess this product for examining the complex estuarine waters of the Tamar estuary (Australia). Satellite images were averaged to examine spatial, seasonal and annual patterns of turbidity. Relationships between in situ measurements of turbidity and reflectance is positively correlated and improves with increased tidal height, a decreased overpass-in situ gap, and one day after a rainfall event. Spatial and seasonal patterns that appear in seasonal and annual MODIS averages, highlighting the usefulness of satellite imagery for resource managers to manage sedimentation issues in a degraded estuary.