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Welcome to the GoldSim Model Library!

The Model Library allows GoldSim users to build on the experience and knowledge of other users by sharing models. The complexity of these models varies greatly from simple illustrative models to fairly complex models for specific applications.

Model files may be created in different versions of GoldSim (indicated in each model article). If a model file is saved in an older version of GoldSim than the version that you have, in most cases, the model file should automatically be converted to your version upon opening. If you have any problems with opening model files, email the GoldSim Technology Group or the author contact provided in the model article.

If you are interested in posting a new model, please read How to Post a Model in the Model Library.

Note: If you have QuickTime installed on your machine, depending on your computer settings, when you press the Download button below for a model file, rather than downloading the file, QuickTime may open and try to "play" the model as an audio file! If this happens, simply right-click on the Download button and select Save As from the context menu.

Search the Model Library

You can search the Model Library articles in the Model Library Search Page. To look for particular models, you can search articles by keywords. You may restrict your search by Categories as well.

The following are Categories in the Model Library. You can look though a list of models by clicking a Category name.

Categories
Biology and Ecology Business and Financial Chemistry Contaminant Transport Dashboard Discrete Simulation Engineered Systems Engineering Risk and Reliability Environmental Modeling General Interest Hydraulics Optimization Resources Risk Assessment Water Quality Water Resources

Most Recently Added Models

• Flood Risk Assessment From a Dam Breach:In this model a dam is simulated in near breach conditions. The model combines runoff, storage and routing into a single model to determine the risk of failure and expected cost.
  

• Calibrating a Model Against Data (Model Fitting): In this example, we have a model with several parameters that we want to calibrate to get an optimum fit of our model to a set of data stored in a Time Series Element.
  

• Creating a Dashboard-Specified Discrete Distribution: This model illustrates how an arbitrary discrete distribution can be specified by entering values and probabilities in a dashboard. This cannot otherwise be done using a discrete distribution Stochastic Element.
  

• Single Pool Reservoir with Spillway: Models a reservoir that provides water deliveries to a single water demand input and is constrained by an upper and lower bound on volume capacity. If the water level in the reservoir rises above the upper limit (spillway crest), then the weir equation is employed to discharge water uncontrolled from the reservoir.
  

• Reservoir Spillway - Inserting timesteps for spillway flow: This model employs a simple reservoir to demonstrate how event triggers are used to insert time slices for a more accurate accounting of spillway flows in a model with large timesteps.
  

• Multiple Pool Reservoir with Spillway: A typical multi-pool reservoir is provided in this example model. Generally, reservoirs are operated based on policies that involve multiple pools that are defined to be used for different purposes.
  

• Water Supply Allocation from Reservoir Pools: Water is allocated to multiple water users with different priorities by placing each user in an operating pool of the reservoir. In this simple example, Three users are each assigned a pool in the reservoir. During the simulation, water supply to is curtailed to low priorities if the reservoir level drops.
  

• Reservoir - Groundwater Interaction:
  Groundwater seepage has the possibility to be a significant factor in overall reservoir losses for some sites. However, since the permeability of the bottom of a reservoir tends to decrease over time due to sedimentation, seepage from the reservoir into the surrounding groundwater aquifer is usually ignored.
  

• Grinding Mill Reliability Model: This model describes a grinding mill circuit typically used in mine processing facilities. The model combines equipment, using the GoldSim reliability element along with other elements to reflect the process flows in parallel. The model output reflects area capacity rather than equipment availability, although this data is available within the model if required.
  

• Indexing Records at Random vs. Sequentially: The purpose of this model is to demonstrate two different ways to index a data record for use in a GoldSim model. In this example, the data happens to be in a spreadsheet but the same approach could be implemented on data stored inside a model (in a data element matrix).
  

• Batch File Example: This example file includes two simple batch files. They are both saved in .txt extensions so that you can look at the commands in any text editor.
  

• Game of Life: The Game of Life is a board game where cells are either dead or alive and rules are defined to cause cells to change state. It is provided as demonstration of using the new script element for matrix manipulations.
  

• Triangular Unit Hydrograph Convolution: This model uses a convolution element to solve for the runoff rate from rainfall based on a triangular unit hydrograph. The only input parameters are the time to peak runoff rate, the time from peak runoff to end of runoff, a runoff coefficient, the rainfall rate, and a catchment area.
  

• Lake Biogeochemical Food Web Model: This is a nutrients, phytoplankton, and zooplankton model with dissolved oxygen dynamics for a vertically stratified lake system with river inputs. Equations and empirical relations used are taken for the most part from Chapra 1997 Surface Water Quality Modeling.
  

• Muskingum Channel Routing: This model does Muskingum channel routing, as it is implemented in the Soil Water Assessment Tool model by Texas A& M. It is the simplest form of kinematic wave routing for streamflows. It can simulates systems that have unidirectional flow and travel times in channels, which describes many GoldSim flow routing situations.
  

• One-Dimensional Lake Stratification Model: The purpose of this model is to demonstrate estimation of dynamic lake stratification by applying the one-dimensional stratification method per Tchobanoglous et al. (1987) in a simple reservoir model.
  

• Contaminant Loading Model for a River Network: The purpose of this model is to demonstrate the mass balance calculations of a simple flow network. The mass balance accounts for flow rates, contaminant concentrations, and annual mass loading at each node.
  

• Water Supply Trade-Off Analysis: Tradeoff analysis involves determining the effect of decreasing one or more key factors and simultaneously increasing one or more other key factors in a decision model. This is a systematic approach to balancing the trade-offs between objectives such as minimizing cost and maximizing performance. In this particular model, 3 objectives are taken into consideration including cost, reliability, and sustainability.
  

• Nonpoint Pollutant Buildup and Washoff Model (with Automated Calibration): This is a nonpoint source pollutant buildup and washoff model with automated calibration features. It is a model that could be used for basin planning or TMDL studies.
  

• Pumped Flow with Pump Curve: This model demonstrates the calculation of flow rate through a pump given a pump operating curve and required head upstream of the pump. To solve this problem through iteration, a Script element is used to do a binary search to converge on the solution of pumped flow.
  

• Time Varying Water Demand: The objective of this simple model is to define water usage patters and apply them to a base demand rate to simulate time-varying demands for a water system. The first step is to review historical data to determine a base demand rate and then estimate pattern multipliers. Once the pattern multipliers are determined, they can be applied to varying base demand rates for your system model.
  

• Indexing Historic Records: This model demonstrates the time-shifting capability of a GoldSim time-series element. As the model iterates through 100 realizations, a time-series record is re-sampled at a random year always starting at the day and month set in the simulation settings of the model.
  

• Hydropower Revenue Optimization: This model demonstrates the optimization tool in GoldSim using a simple reservoir and hydropower model. The objective function is to maximize net revenues made from hydropower generation given extra capital costs to modify the system in 4 ways: (1) Increase diversion capacity, (2) Increase outlet capacity, (3) Increase number of days hydropower releases, and (4) Reduce the area of irrigated land.
  

• Species Spreadsheet for CT Models: This spreadsheet can be used as a template to prepare input data for a GoldSim Contaminant Transport model.
  

• Hawk, Dove, Law Abider Model of Gilbert and Troitzsch (2002): Social Dynamics - Hawk, Dove, Law Abider Model of Gilbert and Troitzsch (2002)
  

• Monthly Averages: Calculating monthly averages in date time models
  

• Operate Two Out Of Three Machines at All Times: This model illustrates logic to try to keep 2 out of 3 reliability components operating at any given time, while averaging out the overall operating time among three machines.
  

• WGEN Weather Generation Model: This GoldSim model, which follows the logic of the 1980s Fortran WGEN model, produces daily maximum and minimum temperature, solar radiation, and precipitation time series based on monthly and annual statistics.  Precipitation is modeled as a two-state Markov process.  Maximum and minimum temperature and solar radiation are auto-correlated and cross-correlated and conditioned on precipitation.
  

• Water Balance Model for a Pervious Catchment: This GoldSim model does the calculations of the pervious catchment water balance module of the Hydrologic Simulation Program Fortran (HSPF-PERLND PWATER module).  HSPF is one of the most widely used conceptual rainfall runoff models.  It models surface runoff, interflow, and groundwater outflow as a function of watershed parameters and input rainfall and pan evaporation data.  I have recently modified it to allow uncertainty in input parameters and hence the runoff response.  A user manual is provided and it describes the good agreement in comparisons between GoldSim's calculations and those of HSPF.