Environmental Systems Applications

Ecological & Biological

Ecosystem and Biological Systems Modeling

Ecological & Biological

Predicting behavior of ecological and biological systems is inherently complex and uncertain since they involve systems made up of many component parts that are interrelated, the components interact in complex ways with numerous feedback mechanisms, and in many cases, the systems are poorly characterized. In addition, such systems are often controlled by stochastic variables (i.e., precipitation, temperature) and involve uncertain processes, parameters, and events.

The challenge when evaluating such systems is to find an approach that can incorporate all the knowledge available to planners and scientists into a quantitative framework that can be used to predict the outcome of alternative management approaches, policies and plans. To be effective, the framework needs to be both flexible (so that it can accurately represent the systems) and transparent (so the models can be easily explained to decision-makers and stakeholders).

Salmon model

By combining the power and flexibility of a general-purpose and highly-graphical probabilistic simulation framework with specialized modules to support water quality modeling, GoldSim allows you to create realistic models of complex, real-world multi-media environmental systems for ecological and biological modeling. Using Monte Carlo simulation, you can explicitly represent the uncertainty inherent is these systems in order to carry out risk analyses, evaluate potential environmental impacts, and make better resource management decisions. GoldSim has the power and flexibility to build ‘total system” models of many kinds of ecological or biological systems, ranging from individual organisms to wetlands or entire ecosystems.

Some biological and ecological applications with GoldSim utilize the GoldSim CT (Contaminant Transport) Module, which includes specialized and powerful elements for the simulation of mass transport (e.g., of nutrients or contaminants) within a range of environmental media. Others require only those elements available in the basic GoldSim framework.

Examples

Modules

Technical Papers

  • Managing Complex Water Resource Systems for Ecological Integrity: Evaluating Tradeoffs and Uncertainty

    PhD Dissertation, University of New Mexico – May 2014

    Ryan Richard Morrison

    This is a doctoral dissertation describing the methodology used to develop a probabilistic, dynamic simulation model that evaluates the impacts of environmental flow alternatives. These alternatives implement various water use schemes in the Rio Chama basin in New Mexico. This work evaluates the influence of various flows on cottonwood recruitment, reservoir storage, hydropower production, and whitewater boating. This project used multiple tools with GoldSim's role focusing on the probabilistic and dynamic simulation of the hydroclimatic uncertainties related to management operations in the water system.

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  • Marine Biogeochemical and Ecosystem Modeling

    Course Material for "Introduction to Climate Modeling", University of Bremen –

    Michael Schulz, University of Bremen

    This web page includes links to a presentation describing the use of GoldSim for climate models and also includes a number of example GoldSim Player models.

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  • Mathematic Models to Simulate the Introduction and Spread of Moniliasis of Cacao in Brazil (in Portuguese)

    Report for the Ministry of Agriculture, Livestock, and Supply – March 2010

    Ricardo Sgrillo, CEPLAC

    This report (in Portugese) describes the development of several stochastic and deterministic models to evaluate the risk of introduction and spread of the cacao frosty pod rot disease, from Peru to Brazil.

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  • Stochastic Simulation of Rumen Degradable Protein Surplus in Grazing Dairy Cows

    Animal Feed Science and Technology, Volume 143, Issue 1, pgs. 280-295 – May 2008

    Pacheco, David, AgResearch Limited, Food, Metabolism and Microbiology Section, Grasslands Research Centre

    This paper describes an application of GoldSim that simulates the many factors influencing the quality of a cows' diet, including the weather, level of fertilization, and the age of plants. Stochastic variables for pasture chemical composition and dry matter intake were incorporated in the model. Stochastic simulation may be useful to explore the likelihood of responses to management scenarios designed to increase the efficiency of dietary nitrogen use in pastoral systems characterized by uncertainty and variability.

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  • Quantitative Farm-to-Fork Human Norovirus Exposure Assessment of Individually Quick Frozen Raspberries and Raspberry Puree

    International Journal of Food Microbiology – February 2017

    Jacxsens L, Stals A, De Keuckelaere A, Deliens B, Rajkovic A, and Uyttendaele M, Ghent University

    A quantitative human norovirus (NoV) exposure model describing transmission of NoV during pre-harvest, harvest and further processing of soft red fruits exemplified by raspberries is presented. The outcomes of the model demonstrate the presence of NoV in raspberry puree or individual quick frozen (IQF) raspberry fruits and were generated by Monte Carlo simulations by combining GoldSim and @Risk software. This farm-to-fork model is a useful tool for evaluating NoV mitigation strategies in the soft red fruit supply chain.

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  • Impacts of Large-Scale Stormwater Green Infrastructure Implementation and Climate Variability on Receiving Water Response in the Salt Lake City Area

    American Journal of Environmental Sciences – October 2015

    Chris York, Erfan Goharian and Steven J. Burian, University of Utah

    This study evaluated impacts of Green Infrastructure (GI) as a stormwater management practice on return flows and the further Implications of climate variability. The goal was to create a model to explore the impacts that bioretention and Rainwater Harvesting (RWH) representing GI had using GoldSim and Stormwater Management Modeling (SWMM) software. The software was used to represent impacts that climate variability individually and combined, may have on downstream stakeholders and receiving water systems in Salt Lake city, Utah, USA. Primary stakeholders included downstream water rights users, Farmington Bay waterfowl management area and the migratory birds that rely on Farmington Bay and the advocates that represent them. The steps to reach this goal were broken down incrementally to: (1) Characterize daily inflows to Farmington Bay, (2) Provide daily inflows from natural and urban runoff to the Jordan river, (3) Create a daily water balance model of Farmington Bay, (4) Demonstrate the model with and without stormwater GI and climate variability scenarios and (5) Determine trends of inflow to the Jordan River, duck clubs and Farmington Bay under various scenarios. For this case study the implications of climate variability on the water system are much greater than implementing GI.

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  • Influence of Particle Size and Organic Carbon Content on Distribution and Fate of Aliphatic and Aromatic Hydrocarbon Fractions in Chalks

    Environmental Technology & Innovation – October 2015

    Xingtao Cao, Tracey Temple, Xingang Li, Frédéric Coulon, Hong Sui, Tianjin University and Cranfield University

    In this study, the fate and distribution of the aliphatic and polycyclic aromatic hydrocarbons (PAHs) of diesel fuel in chalk aquifer was investigated using a series of leaching column tests and then modelled using the Contaminant Transport module of the Goldsim software. Specifically the influence of chalk particle size on the behaviour and fate of the hydrocarbons was investigated. The numerical results and the Monte Carlo analysis showed that the migration of the alkanes and PAHs is greatly retarded by the organic carbon in chalk. It is also observed that the initial mass of the alkanes and PAHs and their respective partition coefficients are important for the decaying of the source at the surface immediately after the spill and the rate-limited dissolution is responsible for entrapping the hydrocarbons in the top layer of the chalk. Overall these results can help to better inform risk assessment and help decision for the remediation strategy.

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