Latest Articles Include:
- Editorial Board
- Environmental Modelling & Software 24(8):IFC (2009)
- An integrated system for publishing environmental observations data
- Environmental Modelling & Software 24(8):879-888 (2009)
Over the next decade, it is likely that science and engineering research will produce more scientific data than has been created over the whole of human history. The successful use of these data to achieve new scientific breakthroughs will depend on the ability to access, integrate, and analyze these large datasets. Robust data organization and publication methods are needed within the research community to enable data discovery and scientific analysis by researchers other than those that collected the data. We present a new method for publishing research datasets consisting of point observations that employs a standard observations data model populated using controlled vocabularies for environmental and water resources data along with web services for transmitting data to consumers. We describe how these components have reduced the syntactic and semantic heterogeneity in the data assembled within a national network of environmental observatory test beds and how this d! ata publication system has been used to create a federated network of consistent research data out of a set of geographically decentralized and autonomous test bed databases.
- A decision support system for environmental effects monitoring
- Environmental Modelling & Software 24(8):889-900 (2009)
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 Canada's 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 reg! ulations for protecting aquatic environments.
- A top-down framework for watershed model evaluation and selection under uncertainty
- Environmental Modelling & Software 24(8):901-916 (2009)
This study introduces a top-down strategy for model evaluation and selection under uncertainty in which watershed model structures with increasing complexity are applied to twelve watersheds across a hydro-climatic gradient within the United States (US). The models' complexities and their related assumptions provide an indication of the dominant controls on the watershed response at the inter-annual, intra-annual, monthly, and daily time scales as captured in the water balance signatures (or metrics) used in this study. The ability of the models to capture the water balance signatures is evaluated in an ensemble framework with respect to their reliability (Is the model ensemble capturing the observed signature?) and with their shape (Is the model structure capable of representing an observed signature's variability?). Model selection is automated by combining the reliability and shape performance measures in a fuzzy rule system. Our results suggest that the framework c! an be tuned to function as a screening tool that formalizes our model selection process. This fuzzy model selection framework enhances our ability to automatically select parsimonious model structures for large databases of watersheds and therefore provides an important step towards understanding how controls on the watershed response vary with landscape and climatic characteristics. This understanding further advances our ability for model-based watershed classification.
- Uncertainty quantification and apportionment in air quality models using the polynomial chaos method
- Environmental Modelling & Software 24(8):917-925 (2009)
Current air quality models generate deterministic forecasts by assuming perfect model, perfectly known parameters, and exact input data. However, our knowledge of the physics is imperfect. It is of interest to extend the deterministic simulation results with "error bars" that quantify the degree of uncertainty, and analyze the impact of the uncertainty input on the simulation results. This added information provides a confidence level for the forecast results. Monte Carlo (MC) method is a popular approach for air quality model uncertainty analysis, but it converges slowly. This work discusses the polynomial chaos (PC) method that is more suitable for uncertainty quantification (UQ) in large-scale models. We propose a new approach for uncertainty apportionment (UA), i.e., we develop a PC approach to attribute the uncertainties in model results to different uncertainty inputs. The UQ and UA techniques are implemented in the Sulfur Transport Eulerian Model (STEM-III).! A typical scenario of air pollution in the northeast region of the USA is considered. The UQ and UA results allow us to assess the combined effects of different input uncertainties on the forecast uncertainty. They also enable to quantify the contribution of input uncertainties to the uncertainty in the predicted ozone and PAN concentrations.
- Comparison of flow and dispersion properties of free and wall turbulent jets for source dynamics characterisation
- Environmental Modelling & Software 24(8):926-937 (2009)
The objective of this paper is to provide an investigation, using large eddy simulations, into the dispersion of aircraft jets in co-flowing take-off conditions. Before carrying out such study, simple turbulent plane free and wall jet simulations are carried out to validate the computational models and to assess the impact of the presence of the solid boundary on the flow and dispersion properties. The current study represents a step towards a better understanding of the source dynamics behind an airplane jet engine during the take-off and landing phases. The information provided from these simulations can be used for future improvements of existing dispersion models.
- TrajStat: GIS-based software that uses various trajectory statistical analysis methods to identify potential sources from long-term air pollution measurement data
- Environmental Modelling & Software 24(8):938-939 (2009)
Statistical analysis of air mass back trajectories combined with long-term ambient air pollution measurements are useful tools for source identification. Using these methods, the geographic information system (GIS) based software, TrajStat, was developed to view, query, and cluster the trajectories and compute the potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analyses when measurement data are included.
- Adaptive management of natural systems using fuzzy logic
- Environmental Modelling & Software 24(8):940-944 (2009)
Hypotheses about how management practices influence ecosystem services can be tested using a crisp, probability-based, or fuzzy decision rule. The correct decision rule depends on whether: (1) the observed state of an ecosystem service (x) is non-stochastic or stochastic; (2) the true state of the ecosystem service (y) is non-stochastic or stochastic; and (3) the relationship between x and y is deterministic, stochastic, or uncertain. Crisp and probability-based decision rules are not appropriate when the relationship between y and x is uncertain in the sense that the decision maker is unable or unwilling to specify conditional probabilities of y given x. Under these conditions, a fuzzy decision rule is appropriate. A hypothetical case study is used to illustrate how a fuzzy decision rule is used to test hypotheses about whether selective cutting of timber provides greater or less forest biodiversity than clearcutting of timber. The case study describes how to incorpor! ate the decision rule in an active adaptive management framework to sequentially test the extent to which changes over time in other factors influencing ecosystem services, such as greater spread of invasive species due to global warming, alter the efficacy of timber management practices. The fuzzy adaptive management decision rule can be generalized to account for the effects of management practices on multiple ecosystem services.
- Review of the Self-Organizing Map (SOM) approach in water resources: Commentary
- Environmental Modelling & Software 24(8):945-947 (2009)
We provide some additional input and perspectives on Kalteh et al's review of the Self-Organizing Map (SOM) approach (Environ. Model. Softw. (2008), 23, 835–845). Map size selection is a key issue in SOM applications. Although there is no theoretical principle to determine the optimum map size, quantitative indicators such as quantization error, topographic error and eigenvalues have proven to be relevant tools to determine the optimal number of map units. Second, one of the most innovative applications of the SOM is the possibility of introducing a set of variables (e.g., biological) into a SOM previously trained with other variables (e.g. environmental). This can be achieved by calculating the mean value of each environmental variable in each output neuron of a SOM trained with biological variables, or by using a mask function to give a null weight to the biological variables, whereas environmental variables are given a weight of 1 so that the values for biological! variables are visualized on a SOM previously trained with environmental variables only. We conclude that our different levels of expertise represent an opportunity for stimulating cross-fertilisation in the vast field of water research rather than simply yielding a collection of case studies to be re-examined.
- Economics in integrated water management
- Environmental Modelling & Software 24(8):948-958 (2009)
Integrated basin scale analysis that accurately accounts for the impacts of proposed policies on the environment and society's economic welfare can comprehensively and consistently inform water resource policies. Cost benefit analysis (CBA) has considerable potential to support water decisions by consistently appraising proposals in terms of society's total environmental and economic impact in monetary terms. However, the difficulty of correctly applying CBA to environmental programs with complex physical and economic interactions weakens policymakers' confidence in comprehensive economic assessments at the basin scale. This paper describes and illustrates a method by which costs and benefits can be systematically integrated into an integrated physical, institutional and economic analysis for a river basin. A simple hydroeconomic model is presented. Its size is small enough to build, understand, and interpret with paper and pencil. But its structure is sufficiently f! lexible to permit expansion for comprehensive policy design that rests on a foundation of a basin's hydrology, institutional constraints, and economic relations. The use of cost benefit analysis to support environmental policy will always be limited by ethical questions on the distribution of benefits and costs among sectors, income groups, locations, and generations. Nevertheless, hydroeconomic models offer a potential resource to efficiently and consistently integrate hydrologic, economic, and institutional impacts of policy proposals to support basin scale cost-benefit environmental assessments.
- The effect of farm dams and constructed banks on hydrologic connectivity and runoff estimation in agricultural landscapes
- Environmental Modelling & Software 24(8):959-968 (2009)
System coupling and landscape connectivity control the flow of water and sediment through landscapes. Although coupling is well known to control long-term landscape development and shorter-term sensitivity to disturbance, the anthropogenic influences on coupling are seldom considered in hydrologic investigations. In particular, the building of small-scale water diversion (earth banks) and collection (farm dams) infrastructure on hillslopes in dryland agricultural areas may significantly alter hillslope–channel coupling. Twelve sub-catchment basins in a dryland agricultural region were investigated under their natural (ignoring infrastructure) and modified (including infrastructure) conditions to investigate the influence of water collection infrastructure on hydrologic connectivity, and whether manual modification of a Digital Elevation Model (DEM) could account for the impact of these factors in hydrologic simulation of hydrologic and geomorphic processes. Dam numbers and density have both increased over the period of available aerial photography (1965–1999), resulting in an average 39.5% reduction (range 4.3–86.7%) in the area retaining hydrologic connectivity with the basin outlet. Analysis of basins dominated by either banks or dams, and with combinations of both was performed using the Cumulative Area Distribution (CAD), Hypsometric Curve (HC), Simplified Width Function (SWF) and Instantaneous Unit Hydrograph (IUH). The geomorphic descriptors (CAD and HC) showed little change in basin structure as a result of farm dam and bank construction, but hydrologic descriptors (SWF and IUH) indicate that hillslope processes are significantly altered by farm dams and banks. Because runoff models are sensitive to catchment area, incorporating hillslope water capture and diversion infrastructure into the base data sets may offer a solution to improved parameterisation of spatial models of hydrology, particularly in dryland agricult! ural regions.
- Design of a sampling strategy to optimally calibrate a reactive transport model: Exploring the potential for Escherichia coli in the Scheldt Estuary
- Environmental Modelling & Software 24(8):969-981 (2009)
For the calibration of any model, measurements are necessary. As measurements are expensive, it is of interest to determine beforehand which kind of samples will provide maximal information. Using a criterion related to the Fisher information matrix as a measure for information content, it is possible to design a sampling scheme that will enable the most precise parameter estimates. This approach was applied to a reactive transport model (based on the Second-generation Louvain-la-Neuve Ice-ocean Model, SLIM) of Escherichia coli concentrations in the Scheldt Estuary. As this estuary is highly influenced by the tide, it is expected that careful timing of the samples with respect to the tidal cycle can have an effect on the quality of the data. The timing and also the positioning of samples were optimised according to the proposed criterion. In the investigated case studies the precision of the estimated parameters could be improved by up to a factor of ten, confirming th! e usefulness of this approach to maximize the amount of information that can be retrieved from a fixed number of samples. Precise parameter values will result in more reliable model simulations, which can be used for interpretation, or can in turn serve to plan subsequent sampling campaigns to further constrain the model parameters.
- Knowledge-based versus data-driven fuzzy habitat suitability models for river management
- Environmental Modelling & Software 24(8):982-993 (2009)
Aquatic habitat suitability models have increasingly received attention due to their wide management applications. Ecological expert knowledge has been frequently incorporated in such models to link environmental conditions to the quantitative habitat suitability of aquatic species. Since the formalisation of problem-specific human expert knowledge is often difficult and tedious, data-driven machine learning techniques may be helpful to extract knowledge from ecological datasets. In this paper, both expert knowledge-based and data-driven fuzzy habitat suitability models were developed and the performance of these models was compared. For the data-driven models, a hill-climbing optimisation algorithm was applied to derive ecological knowledge from the available data. Based on the available ecological expert knowledge and on biological samples from the Zwalm river basin (Belgium), habitat suitability models were generated for the mayfly Baetis rhodani (Pictet 1843). Data! -driven models appeared to outperform expert knowledge-based models substantially, while a step-forward model selection procedure indicated that physical habitat variables adequately described the mayfly habitat suitability in the studied area. This study has important implications on the application of expert knowledge in ecological studies, especially if this knowledge is extrapolated to other areas. The results suggest that data-driven models can complement expert knowledge-based approaches and hence improve model reliability.
- An environmental indicator to drive sustainable pest management practices
- Environmental Modelling & Software 24(8):994-1002 (2009)
The indicator EPRIP (Environmental Potential Risk Indicator for Pesticide) was released in 1997 with the aim of providing farmers with advice in selecting the most suitable pesticide with the least environmental impact. EPRIP 2, the newly developed, standalone version includes several improvements in the description of driving forces, in particular plant interception, drift and runoff and new database functionalities. EPRIP 2 is based upon the Exposure Toxicity Ratio (ETR) of the predicted environmental concentration (PEC) with toxicological parameters. When several applications of different active ingredients are used within the same pest control strategy, EPRIP 2 calculates a score for each active ingredient and for the overall pest control strategy. The latter evaluation is based on the probability of the EPRIP value exceeding two fixed risk thresholds. The probability of exceeding each threshold is calculated using the risk points of every application in the strate! gy and taking into account the risk points for surface water, groundwater, soil and air.
- Development of a geospatial screening tool to identify source areas of windblown dust
- Environmental Modelling & Software 24(8):1003-1011 (2009)
Soil properties and air-mass backward trajectories were integrated into a geographical information systems (GIS) tool to identify geographical regions that were likely to have significant influence on dust concentrations at Class I national parks and wilderness areas in US. The Windblown Dust Index (WDI) was introduced by spatial analysis of wind erosion and land use/land cover data for North America to identify potential area sources of windblown dust. The spatial probability density maps of backward trajectories were utilized to determine the number of trajectory points that passed near a grid cell at speeds higher than a specified threshold value. Analysis of data for the Salt Creek and White Mountain wilderness areas highlighted the significant potential of both local and regional sources of windblown dust at the two sites, with evidence for seasonal variation. These data are useful in evaluating the importance of windblown dust source areas and developing cost-eff! ective targeted studies and/or mitigation strategies.
- Single bubble dissolution model – The graphical user interface SiBu-GUI
- Environmental Modelling & Software 24(8):1012-1013 (2009)
The presented software application allows GUI-based access to the bubble dissolution model presented by McGinnis et al. [McGinnis, D.F., Greinert, J., Artemov, Y., Beaubien, S.E., Wüest, A., 2006. The fate of rising methane bubbles in stratified waters: what fraction reaches the atmosphere? Journal of Geophysical Research 111, C09007. doi:10.1029/2005JC003183]. It quantifies the dissolution of gas bubbles (containing any combination of CH4, CO2, O2, N2, and Ar) in marine or lacustrine environments based on the initial bubble size, free gas composition and environmental parameters (temperature, salinity, and dissolved gas concentrations). The software enables scientists and engineers to evaluate bubble dynamics in a simple way on Windows® PCs.
- The SMC sample mass calculator for particulate materials
- Environmental Modelling & Software 24(8):1014-1018 (2009)
The SMC Sample Mass Calculator implements a new way of calculating the required sample mass during the sampling of granular materials. The novel approach presented here allows for calculating the required sample mass even when information about the concentrations in the particles is absent. This is of practical interest, because detailed information on the concentrations of the property of interest in each particle is generally difficult to obtain. The SMC requires as input parameters: a particle size distribution, an estimate of the concentration in the population, minimum and maximum concentrations in each particle, the densities of the particles, the shape factor and a value for the tolerated relative standard deviation of the sampling error. The applicability of the SMC is discussed and numerical examples are presented using test data from literature.