The value of remote sensing techniques in supporting effective extrapolation across multiple marine spatial scales

The reporting of ecological phenomena and environmental status routinely required point observations, collected with traditional sampling approaches to be extrapolated to larger reporting scales. This process encompasses difficulties that can quickly entrain significant errors. Remote sensing techniques offer insights and exceptional spatial coverage for observing the marine environment. This review provides guidance on (i) the structures and discontinuities inherent within the extrapolative process, (ii) how to extrapolate effectively across multiple spatial scales, and (iii) remote sensing techniques and data sets that can facilitate this process. This evaluation illustrates that remote sensing techniques are a critical component in extrapolation and likely to underpin the production of high-quality assessments of ecological phenomena and the regional reporting of environmental status. Ultimately, is it hoped that this guidance will aid the production of robust and consistent extrapolations that also make full use of the techniques and data sets that expedite this process

Detection and Monitoring of Marine Pollution Using Remote Sensing Technologies

Recently, the marine habitat has been under pollution threat, which impacts many human activities as well as human life. Increasing concerns about pollution levels in the oceans and coastal regions have led to multiple approaches for measuring and mitigating marine pollution, in order to achieve sustainable marine water quality. Satellite remote sensing, covering large and remote areas, is considered useful for detecting and monitoring marine pollution. Recent developments in sensor technologies have transformed remote sensing into an effective means of monitoring marine areas. Different remote sensing platforms and sensors have their own capabilities for mapping and monitoring water pollution of different types, characteristics, and concentrations. This chapter will discuss and elaborate the merits and limitations of these remote sensing techniques for mapping oil pollutants, suspended solid concentrations, algal blooms, and floating plastic waste in marine waters

Earth Observing System. Volume 1, Part 2: Science and Mission Requirements. Working Group Report Appendix

Areas of global hydrologic cycles, global biogeochemical cycles geophysical processes are addressed including biological oceanography, inland aquatic resources, land biology, tropospheric chemistry, oceanic transport, polar glaciology, sea ice and atmospheric chemistry

Relationship between Land Use and Water Quality and its Assessment Using Hyperspectral Remote Sensing in Mid- Atlantic Estuaries

Mid-Atlantic coastal waters are under increasing pressures from anthropogenic disturbances at various temporal and spatial scales exacerbated by the climate change. According to the National Oceanic Atmospheric Association (NOAA), 10 of the 22 estuaries in the Mid-Atlantic, including the Chesapeake Bay, exhibit high levels of eutrophic conditions while seven, including Delaware Bay, exhibit low conditions. Chesapeake Bay is the largest estuarine system in the United States and undergoes frequent eutrophication and low dissolved oxygen events. Although substantially lower in nutrients compared to other Mid-Atlantic Estuaries, the biological, chemical, and ecological status of the Delaware Bay has changed in the past few decades due to high coastal tourism, increased local resident populations, and agricultural activities which have increased nutrient inputs into this shallow coastal bay. As stated by the Academy of Natural Sciences, although the nutrient load has reduced since the Clean Water Act, years of nutrient accumulation, contaminations, and sedimentation have impacted estuarine systems substantially, long-term monitoring is lacking, and ecological responses are not well quantified. Eutrophication within the Bays has degraded water quality conditions advanced by sedimentation. Understanding the quality of the water in any aquatic ecosystem is a critical first step in order to identify characteristics of that ecosystem and draw conclusions about how well adapted the system is in terms of anthropogenic activity and climate change. Determining water quality in intertidal creeks along the Chesapeake and Delaware coastlines is important because land cover is constantly changing. Many of these tidal creeks are lined with forested riparian buffers that may be intercepting nutrients from running off into the waterways. Identifying water conditions, coupled with the marsh land cover, provides a strong foundation to see if the buffer systems are providing the ecosystem services they are designed to provide. Our primary goal in this chapter is to provide research findings on the application of the hyperspectral remote sensing to monitor specific land-use activities and water quality. Along with hyperspectral remote sensing, our monitoring was coupled with the integration of remotely sensed data, global positioning system (GPS), and geographic information system (GIS) technologies that provide a valuable tool for monitoring and assessing waterways in the Mid-Atlantic Estuaries

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM), chlorophyll-a, and pollutants). A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water’s surface. In this review paper, various properties (spectral, spatial and temporal, etc.) of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD)

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

Coordinated aircraft and ship surveys for determining impact of river inputs on great lakes waters. Remote sensing results

The remote sensing results of aircraft and ship surveys for determining the impact of river effluents on Great Lakes waters are presented. Aircraft multi-spectral scanner data were acquired throughout the spring and early summer of 1976 at five locations: the West Basin of Lake Erie, Genesee River - Lake Ontario, Menomonee River - Lake Michigan, Grand River - Lake Michigan, and Nemadji River - Lake Superior. Multispectral scanner data and ship surface sample data are correlated resulting in 40 contour plots showing large-scale distributions of parameters such as total suspended solids, turbidity, Secchi depth, nutrients, salts, and dissolved oxygen. The imagery and data analysis are used to determine the transport and dispersion of materials from the river discharges, especially during spring runoff events, and to evaluate the relative effects of river input, resuspension, and shore erosion. Twenty-five LANDSAT satellite images of the study sites are also included in the analysis. Examples of the use of remote sensing data in quantitatively estimating total particulate loading in determining water types, in assessing transport across international boundaries, and in supporting numerical current modeling are included. The importance of coordination of aircraft and ship lake surveys is discussed, including the use of telefacsimile for the transmission of imagery

Remote sensing, numerical modelling and ground truthing for analysis of lake water quality and temperature

Freshwater accounts for just 2.5% of the earth’s water resources, and its quality and availability are becoming an issue of global concern in the 21st century. Growing human population, over-exploitation of water sources and pressures of global warming mean that both water quantity and quality are affected. In order to effectively manage water quality there is a need for increased monitoring and predictive modelling of freshwater resources. To address these concerns in New Zealand inland waters, an approach which integrates biological and physical sciences is needed. Remote sensing has the potential to allow this integration and vastly increase the temporal and spatial resolution of current monitoring techniques, which typically involve collecting grab-samples. In a complementary way, lake modelling has the potential to enable more effective management of water resources by testing the effectiveness of a range of possible management scenarios prior to implementation. Together, the combination of remote sensing and modelling data allows for improved model initialisation, calibration and validation, which ultimately aid in understanding of complex lake ecosystem processes. This study investigated the use of remote sensing using empirical and semi-analytical algorithms for the retrieval of chlorophyll a (chl a), tripton, suspended minerals (SM), total suspended sediment (SS) and water surface temperature. It demonstrated the use of spatially resolved statistical techniques for comparing satellite estimated and 3-D simulated water quality and temperature. An automated procedure was developed for retrieval of chl a from Landsat Enhanced Thematic Mapper (ETM+) imagery, using 106 satellite images captured from 1999 to 2011. Radiative transfer-based atmospheric correction was applied to images using the Second Simulation of the Satellite in the Solar Spectrum model (6sv). For the estimation of chl a over a time series of images, the use of symbolic regression resulted in a significant improvement in the precision of chl a hindcasts compared with traditional regression equations. Results from this investigation suggest that remote sensing provides a valuable tool to assess temporal and spatial distributions of chl a. Bio-optical models were applied to quantify the physical processes responsible for the relationship between chl a concentrations and subsurface irradiance reflectance used in regression algorithms, allowing the identification of possible sources of error in chl a estimation. While the symbolic regression model was more accurate than traditional empirical models, it was still susceptible to errors in optically complex waters such as Lake Rotorua, due to the effect of variations of SS and CDOM on reflectance. Atmospheric correction of Landsat 7 ETM+ thermal data was carried out for the purpose of retrieval of lake water surface temperature in Rotorua lakes, and Lake Taupo, North Island, New Zealand. Atmospheric correction was repeated using four sources of atmospheric profile data as input to a radiative transfer model, MODerate resolution atmospheric TRANsmission (MODTRAN) v.3.7. The retrieved water temperatures from 14 images between 2007 and 2009 were validated using a high-frequency temperature sensor deployed from a mid-lake monitoring buoy at the water surface of Lake Rotorua. The most accurate temperature estimation for Lake Rotorua was with radiosonde data as an input into MODTRAN, followed by Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2, Atmospheric Infrared Sounder (AIRS) Level 3, and NASA data. Retrieved surface water temperature was used for assessing spatial heterogeneity of surface water temperature simulated with a three-dimensional (3-D) hydrodynamic model (ELCOM) of Lake Rotoehu, located approximately 20 km east of Lake Rotorua. This comparison demonstrated that simulations reproduced the dominant horizontal variations in surface water temperature in the lake. The transport and mixing of a geothermal inflow and basin-scale circulation patterns were inferred from thermal distributions from satellite and model estimations of surface water temperature and a spatially resolved statistical evaluation was used to validate simulations. This study has demonstrated the potential of accurate satellite-based thermal monitoring to validate water surface temperature simulated by 3-D hydrodynamic models. Semi-analytical and empirical algorithms were derived to determine spatial and temporal variations in SS in Lake Ellesmere, South Island, New Zealand, using MODIS band 1. The semi-analytical model and empirical model had a similar level of precision in SS estimation, however, the semi-analytical model has the advantage of being applicable to different satellite sensors, spatial locations, and SS concentration ranges. The estimations of SS concentration (and estimated SM concentration) from the semi-analytical model were used for a spatially resolved validation of simulations of SM derived from ELCOM-CAEDYM. Visual comparisons were compared with spatially-resolved statistical techniques. The spatial statistics derived from the Map Comparison Kit allowed a non-subjective and quantitative method to rank simulation performance on different dates. The visual and statistical comparison between satellite estimated and model simulated SM showed that the model did not perform well in reproducing both basin-scale and fine-scale spatial variation in SM derived from MODIS satellite imagery. Application of the semi-analytical model to estimate SS over the lifetime of the MODIS sensor will greatly extend its spatial and temporal coverage for historical monitoring purposes, and provide a tool to validate SM simulated by 1-D and 3-D models on a daily basis. A bio-optical model was developed to derive chl a, SS concentrations, and coloured dissolved organic matter /detritus absorption at 443 nm, from MODIS Aqua subsurface remote sensing reflectance of Lake Taupo, a large, deep, oligotrophic lake in North Island, New Zealand. The model was optimised using in situ inherent optical properties (IOPs) from the literature. Images were atmospherically corrected using the radiative transfer model 6sv. Application of the bio-optical model using a single chl a-specific absorption spectrum (a*ϕ(λ)) resulted in low correlation between estimated and observed values. Therefore, two different absorption curves were used, based on the seasonal dominance of phytoplankton phyla with differing absorption properties. The application of this model resulted in reasonable agreement between modelled and in situ chl a concentrations. Highest concentrations were observed during winter when Bacillariophytes (diatoms) dominated the phytoplankton assemblage. On 4 and 5 March 2004 an unusually large turbidity current was observed originating from the Tongariro River inflow in the south-east of the lake. In order to resolve fine details of the plume, empirical relationships were developed between MODIS band 1 reflectance (250 m resolution) and SS estimated from MODIS bio-optical features (1 km resolution) were used estimate SS at 250 m resolution. Complex lake circulation patterns were observed including a large clockwise gyre. With the development of this bio-optical model MODIS can potentially be used to remotely sense water quality in near real time, and the relationship developed for B1 SS allows for resolution of fine-scale features such turbidity currents

Global solutions to regional problems: Collecting global expertise to address the problem of harmful cyanobacterial blooms. A Lake Erie case study

In early August 2014, the municipality of Toledo, OH (USA) issued a ‘do not drink’ advisory on their water supply directly affecting over 400,000 residential customers and hundreds of businesses (Wilson, 2014). This order was attributable to levels of microcystin, a potent liver toxin, which rose to 2.5 mg L1 in finished drinking water. The Toledo crisis afforded an opportunity to bring together scientists from around the world to share ideas regarding factors that contribute to bloom formation and toxigenicity, bloom and toxin detection as well as prevention and remediation of bloom events. These discussions took place at an NSF- and NOAA-sponsored workshop at Bowling Green State University on April 13 and 14, 2015. In all, more than 100 attendees from six countries and 15 US states gathered together to share their perspectives. The purpose of this review is to present the consensus summary of these issues that emerged from discussions at the Workshop. As additional reports in this special issue provide detailed reviews on many major CHAB species, this paper focuses on the general themes common to all blooms, such as bloom detection, modeling, nutrient loading, and strategies to reduce nutrients