William G. Booty

Trends in Water Clarity of the Lower Great Lakes from Remotely Sensed Aquatic Color

ABSTRACT Satellite observations of aquatic colour enable environmental monitoring of the Great Lakes at spatial and temporal scales not obtainable through ground-based monitoring. By merging data from the Coastal Zone Color Scanner (CZCS) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), monthly binned images of water-leaving radiance over the Great Lakes have been produced for the periods 1979–1985 and 1998–2006. This time-series can be interpreted in terms of changes in water clarity, showing seasonal and inter-annual variability of bright-water episodes such as phytoplankton blooms, re-suspension of bottom sediments, and whiting events. Variations in Secchi disk depth over Lakes Erie and Ontario are predicted using empirical relationships from coincident measurements of water transparency and remotely-sensed water-leaving radiance. Satellite observations document the extent to which the water clarity of the lower Great Lakes has changed over the last three decades in response to significant events including the invasion of zebra mussels. Results confirm dramatic reductions in Lake Ontario turbidity in the years following mussel colonization, with a doubling of estimated Secchi depths. Evidence confirms a reduction in the frequency/intensity of whiting events in agreement with suggestions of the role of calcium uptake by mussels on lake water clarity. Increased spring-time water clarity in the eastern basin of Lake Erie also corroborates previous observations in the region. Despite historical reports of localised increases in transparency in the western basin immediately following the mussel invasion, image analysis shows a significant increase in turbidity between the two study periods, in agreement with more recent reports of longer term trends in water clarity. Through its capacity to provide regular and readily interpretable synoptic views of regions undergoing significant environmental change, this work illustrates the value of remotely sensing water colour to water clarity monitoring in the lower Great Lakes.

Design and implementation of an environmental decision support system

Abstract An environmental decision support system is a specific version of an environmental information system that is designed to help decision makers, managers, and advisors locate relevant information and carry out optimal solutions to problems using special tools and knowledge. The RAISON (Regional Analysis by Intelligent Systems ON microcomputers) for Windows decision support system has been developed at the National Water Research Institute, Environment Canada, over the last 10 years. It integrates data, text, maps, satellite images, pictures, video and other knowledge input. A library of software functions and tools are available for selective extraction of spatial and temporal data that can be analysed using spatial algorithms, models, statistics, expert systems, neural networks, and other information technologies. The system is of a modular design which allows for flexibility in modification of the system to meet the demands of a wide range of applications. System design and practical experiences learned in the development of a decision support system for toxic chemicals in the Great Lakes of North America are discussed.

A decision support system for environmental effects monitoring

The Environmental Effects Monitoring (EEM) Statistical Assessment Tool (SAT) Decision Support System (DSS) has been developed to provide a user-friendly data analysis, display and decision support tool for Canadas federal environmental effects monitoring program for the pulp and paper and mining industries. The target users include industries, consultants, regional EEM coordinators, National EEM Office and scientists involved in EEM-related research. The tool allows the assessment of the effects of effluent from industrial or other sources on fish and benthic populations. Effect endpoints, which are used as indicators of potentially important effluent effects, are measured at effluent-exposed sites and are compared statistically to measures at reference sites, in order to determine if changes have occurred and the magnitude of the changes. The main driver of the EEM-SAT DSS is its rule-based expert system. The results are used in assessing the adequacy of existing regulations for protecting aquatic environments.

Mass balance modelling of priority toxic chemicals within the great lakes toxic chemical decision support system: RateCon model results for Lake Ontario and Lake Erie

Abstract The great lakes toxic chemical decision support system (GLTCDSS) has been developed in order to integrate all of the available information on Tier I and II chemicals in support of designing, implementing and post-auditing the zero discharge and virtual elimination strategies. A modified version of the rate constant model (RateCon) (J. Great Lakes Res. 20 (1994) 625), which is one of three mass balance models incorporated into the system, has been run for anthracene, benzo(a) pyrene (B(a)P), dieldrin, fluoranthene, lead, DDE, DDT, hexachlorobenzene (HCB), mercury, mirex, polychlorinated biphenyls (PCBs), dioxins (TCDDs), pentachlorophenol, and furans (TCDFs) for Lake Ontario. A subset of these has been run for Lake Erie, due to more limited loadings data being available. The steady-state model results indicate that both lakes are still net sinks for metals such as mercury and lead, and that for concentrations in the water column, the model predicted values fall within the observed ranges plus or minus the confidence intervals for PCBs, HCB, B(a)P, mirex, DDE, lead, and anthracene. Currently there is still insufficient data to allow a simple screening level model such as RateCon to be applied for octachlorostyrene, chlordane, toxaphene, heptachlor, 1,4-dichlorobenzene, 3,3′-dichlorobenzidine, hexachlorocyclohexane, 1,6-dinitropyrene, 1,8-dinitropyrene, and tributyl tin, and many of the PAHs. Concentrations to loadings calculations for Lake Erie indicate that either the lake is very far from steady-state and is responding to historically higher loadings or the estimated loadings are extremely underestimated for PCBs, lead, and fluoranthene, assuming that the measured concentrations at the outlet (Fort Erie) are representative of whole lake values.

A multi-level assessment methodology for determining the potential for groundwater contamination by pesticides

A multi-level pesticide assessment methodology has been developed to permit regulatory personnel to undertake a variety of assessments on the potential for pesticide used in agricultural areas to contaminate the groundwater regime at an increasingly detailed geographical scale of investigation. A multi-level approach accounts for a variety of assessment objectives and detail required in the assessment, the restrictions on the availability and accuracy of data, the time available to undertake the assessment, and the expertise of the decision maker. The level 1: regional scale is designed to prioritize districts having a potentially high risk for groundwater contamination from the application of a specific pesticide for a particular crop. The level 2: local scale is used to identify critical areas for groundwater contamination, at a soil polygon scale, within a district. A level 3: soil profile scale allows the user to evaluate specific factors influencing pesticide leaching and persistence, and to determine the extent and timing of leaching, through the simulation of the migration of a pesticide within a soil profile. Because of the scale of investigation, limited amount of data required, and qualitative nature of the assessment results, the level 1 and level 2 assessment are designed primarily for quick and broad guidance related to management practices. A level 3 assessment is more complex, requires considerably more data and expertise on the part of the user, and hence is designed to verify the potential for contamination identified during the level 1 or 2 assessment. The system combines environmental modelling, geographical information systems, extensive databases, data management systems, expert systems, and pesticide assessment models, to form an environmental information system for assessing the potential for pesticides to contaminate groundwater.

Investigation of correlation between remotely sensed impervious surfaces and chloride concentrations

The main objective of this study is to verify the often assumed correlation between impervious surfaces and chlorides that result from the application of road salts, focusing on a case study in the selected six major watersheds within the Greater Toronto Area. Landsat-5 Thematic Mapper images collected in 1990, 1995, 2000, and 2005 and the unsupervised classification technique were utilized in the estimation of percentage imperviousness for each watershed. Chloride concentrations collected at water quality monitoring stations within the watersheds were then mapped against impervious surface estimates and their spatiotemporal distribution was assessed. The remotely sensed impervious surface maps and chloride maps were overlaid in a geographical information system environment for the investigation of their potential correlation. The main findings of this study indicate an average of 12.9% increase in impervious surface areas as well as a threefold increase in chloride concentrations between 1990 and 2005. Water quality monitoring stations exhibiting the highest amounts of chloride concentration correspond with the most impervious parts of the watersheds. The results also show that the increase in imperviousness does generate higher chloride concentrations. Correspondingly, the higher levels of chloride can potentially degrade the quality of surface waters. Through developing a novel integrated remote-sensing approach, the study was successful in identifying areas most vulnerable to surface water quality degradation by road salts.

Application of four watershed acidification models to Batchawana Watershed, Canada

Four watershed acidification models (TMWAM, ETD, ILWAS, and RAINS) are reviewed and a comparison of model performance is presented for a common watershed. The models have been used to simulate the dynamics of water quantity and quality at Batchawana Watershed, Canada, a sub-basin of the Turkey Lakes Watershed. The computed results are compared with observed data for a four-year period (Jan. 1981-Dec. 1984). The models exhibit a significant range in the ability to simulate the daily, monthly and seasonal changes present in the observed data. Monthly watershed outflows and lake chemistry predictions are compared to observed data. pH and ANC are the only two chemical parameters common to all four models. Coefficient of efficiency (E), linear (r) and rank (R) correlation coefficients, and regression slope (s) are used to compare the goodness of fit of the simulated with the observed data. The ILWAS, TMWAM and RAINS models performed very well in predicting the monthly flows, with values of r and R of approximately 0.98. The ETD model also showed strong correlations with linear (r) and rank (R) correlation coefficients of 0.896 and 0.892, respectively. The results of the analyses showed that TMWAM provided the best simulation of pH (E=0.264, r=0.648), which is slightly better than ETD (E=0.240, r=0.549), and much better than ILWAS (E=-2.965, r=0.293), and RAINS (E=-4.004, r=0.473). ETD was found to be superior in predicting ANC (E=0.608, r=0.781) as compared to TMWAM (E=0.340, r=0.598), ILWAS (E=0.275, r=0.442), and RAINS (E=-1.048, r=0.356). The TMWAM model adequately simulated SO4 over the four-year period (E=0.423, r=0.682) but the ETD (E=-0.904, r=0.274), ILWAS (E=-4.314, r=0.488), and RAINS (E=-6.479, r=0.126) models all performed poorer than the benchmark model (mean observed value).

An expert system for water quality modelling

The RAISON-micro (Regional Analysis by Intelligent System ON a micro-computer) expert system is being used to predict the effects of mine effluents on receiving waters in Ontario. The potential of this system to assist regulatory agencies and mining industries to define more acceptable effluent limits was shown in an initial study. This system has been further developed so that the expert system helps the model user choose the most appropriate model for a particular application from a hierarchy of models. The system currently contains seven models which range from steady state to time dependent models, for both conservative and nonconservative substances in rivers and lakes. The menu driven expert system prompts the model user for information such as the nature of the receiving water system, the type of effluent being considered, and the range of background data available for use as input to the models. The system can also be used to determine the nature of the environmental conditions at the site which are not available in the textual information database, such as the components of river flow. Applications of the water quality expert system are presented for representative mine sites in the Timmins area of Ontario.

Assessment of Ecological Responses to Environmental Flow Regimes using a Decision Support System Framework

The Environmental Flows Decision Support System (EFDSS) has been developed to allow the communities and governments in the Murray-Darling Basin of Australia to assess the environmental responses of the lowland floodplain rivers to proposed flow management scenarios. The system integrates a range of qualitative and quantitative ecological models which consider blooms of toxic blue-green algae as well as habitat conditions for fish, floodplain vegetation, and waterbird breeding. It has been designed to accommodate a wide range of users. In this paper the overall design concepts and components of the EFDSS are described.