Kurt Wolfe

Design of a component-based integrated environmental modeling framework

Integrated environmental modeling (IEM) includes interdependent science-based components that comprise an appropriate software modeling system and are responsible for consuming and producing information as part of the system, but moving information from one component to another (i.e., interoperability) is the responsibility of the IEM software system. We describe and discuss the Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES), a component-based IEM system, from the standpoint of software design requirements which define system functionalities. Design requirements were identified in a series of workshops, attended by IEM practitioners, and reported in the development of a number of IEM software systems. The requirements cover issues associated with standards, component connectivity, linkage protocols, system architecture and functionality, and web-based access, all of which facilitate the creation of plug & play components from stand-alone models through a series of software support tools and standards.

An integrated ecological modeling system for assessing impacts of multiple stressors on stream and riverine ecosystem services within river basins

We demonstrate a novel, spatially explicit assessment of the current condition of aquatic ecosystem services, with limited sensitivity analysis for the atmospheric contaminant mercury. The Integrated Ecological Modeling System (IEMS) forecasts water quality and quantity, habitat suitability for aquatic biota, fish biomasses, population densities, productivities, and contamination by methylmercury across headwater watersheds. We applied this IEMS to the Coal River Basin (CRB), West Virginia (USA), an 8-digit hydrologic unit watershed, by simulating a network of 97 stream segments using the SWAT watershed model, a watershed mercury loading model, the WASP water quality model, the PiSCES fish community estimation model, a fish habitat suitability model, the BASS fish community and bioaccumulation model, and an ecoservices post-processer. Model application was facilitated by automated data retrieval and model setup and updated model wrappers and interfaces for data transfers between these models from a prior study. This companion study evaluates baseline predictions of ecoservices provided for 1990 - 2010 for the population of streams in the CRB and serves as a foundation for future model development.

Demonstration of a consensus approach for the calculation of physicochemical properties required for environmental fate assessments

Eight software applications are compared for their performance in estimating the octanol-water partition coefficient (Kow), melting point, vapor pressure and water solubility for a dataset of polychlorinated biphenyls, polybrominated diphenyl ethers, polychlorinated dibenzodioxins, and polycyclic aromatic hydrocarbons. The predicted property values are compared against a curated dataset of measured property values compiled from the scientific literature with careful consideration given to the analytical methods used for property measurements of these hydrophobic chemicals. The variability in the predicted values from different calculators generally increases for higher values of Kow and melting point and for lower values of water solubility and vapor pressure. For each property, no individual calculator outperforms the others for all four of the chemical classes included in the analysis. Because calculator performance varies based on chemical class and property value, the geometric mean and the median of the calculated values from multiple calculators that use different estimation algorithms are recommended as more reliable estimates of the property value than the value from any single calculator.

Using Integrated Environmental Modeling to Assess Sources of Microbial Contamination in Mixed-Use Watersheds

Microbial fate and transport in watersheds should include a microbial source apportionment analysis that estimates the importance of each source, relative to each other and in combination, by capturing their impacts spatially and temporally under various scenarios. A loosely configured software infrastructure was used in microbial source-to-receptor modeling by focusing on animal- and human-impacted mixed-use watersheds. Components include data collection software, a microbial source module that determines loading rates from different sources, a watershed model, an inverse model for calibrating flows and microbial densities, tabular and graphical viewers, software to convert output to different formats, and a model for calculating risk from pathogen exposure. The system automates, as much as possible, the manual process of accessing and retrieving data and completes input data files of the models. The workflow considers land-applied manure from domestic animals on undeveloped areas; direct shedding (excretion) on undeveloped lands by domestic animals and wildlife; pastureland, cropland, forest, and urban or engineered areas; sources that directly release to streams from leaking septic systems; and shedding by domestic animals directly to streams. The infrastructure also considers point sources from regulated discharges. An application is presented on a real-world watershed and helps answer questions such as: What are the major microbial sources? What practices contribute to contamination at the receptor location? What land-use types influence contamination at the receptor location? and Under what conditions do these sources manifest themselves? This research aims to improve our understanding of processes related to pathogen and indicator dynamics in mixed-use watershed systems.

Capturing microbial sources distributed in a mixed-use watershed within an integrated environmental modeling workflow

Many watershed models simulate overland and instream microbial fate and transport, but few provide loading rates on land surfaces and point sources to the waterbody network. This paper describes the underlying equations for microbial loading rates associated with 1) land-applied manure on undeveloped areas from domestic animals; 2) direct shedding (excretion) on undeveloped lands by domestic animals and wildlife; 3) urban or engineered areas; and 4) point sources that directly discharge to streams from septic systems and shedding by domestic animals. A microbial source module, which houses these formulations, is part of a workflow containing multiple models and databases that form a loosely configured modeling infrastructure which supports watershed-scale microbial source-to-receptor modeling by focusing on animal- and human-impacted catchments. A hypothetical application - accessing, retrieving, and using real-world data - demonstrates how the infrastructure can automate many of the manual steps associated with a standard watershed assessment, culminating in calibrated flow and microbial densities at the watersheds pour point.

Modeling Best Management Practices (BMPs) with HSPF

Y. M. Mohamoud, Rajbir Parmar, and Kurt Wolfe Hydrologist, National Exposure Research Laboratory, USEPA, 960 College Station Road, Athens, GA. E‐mail: mohamoud.yusuf@epa.gov Computer Scientist, National Exposure Research Laboratory, USEPA, 960 College Station Road, Athens, GA. E‐mail: Parmar.Rajbir@epa.gov Computer Engineer, National Exposure Research Laboratory, USEPA, 960 College Station Road, Athens, GA. E‐mail: wolfe.kurt@epa.gov Abstract The Hydrological Simulation Program‐Fortran (HSPF) is a semi‐distributed watershed model, which simulates hydrology and water quality processes at user‐specified spatial and temporal scales. Although HSPF is a comprehensive and highly flexible model, a number of investigators noted the model’s limited capabilities in representing and simulating best management practices (BMPs), such as detention basins and infiltration trenches. We present herein a stand‐alone web‐based HSPF BMP Toolkit that allows HSPF to represent and simulate storage and infiltration BMPs in a more comprehensive way.

Sensitivity analyses for simulating pesticide impacts on honey bee colonies

We employ Monte Carlo simulation and sensitivity analysis techniques to describe the population dynamics of pesticide exposure to a honey bee colony using the VarroaPop+Pesticide model. Simulations are performed of hive population trajectories with and without pesticide exposure to determine the effects of weather, queen strength, foraging activity, colony resources, and Varroa populations on colony growth and survival. The daily resolution of the model allows us to conditionally identify sensitivity metrics. Simulations indicate queen strength and forager lifespan are consistent, critical inputs for colony dynamics in both the control and exposed conditions. Adult contact toxicity, application rate and nectar load become critical parameters for colony dynamics within exposed simulations. Daily sensitivity analysis also reveals that the relative importance of these parameters fluctuates throughout the simulation period according to the status of other inputs.