Modeling Spatially Correlated Rainfall in GoldSim

 Posted by Jason Lillywhite

Effective water resource management hinges on accurately modeling precipitation. But what happens when rainfall patterns differ significantly between 2 locations within your study area. For example, precipitation on a valley floor compared to the mountainous watershed nearby? This post explores a practical method using GoldSim to simulate precipitation that is linked, or spatially correlated, across different locations. 

We'll use real-world daily rainfall data from two distinct sites in Utah to demonstrate how to set up and parameterize such a model. Read on to see how rainfall correlation between these valley and mountain locations led to more realistic hydrological simulations in GoldSim.

Testing PrecipGen Across Four Sites

Posted by  Jason Lillywhite

This blog post presents the results of testing PrecipGen across four diverse locations to evaluate its performance:

• Australia Plains, AU
• Grand Junction Walker Field, CO, USA
• Dublin, EI
• Orlando, FL, USA

The findings demonstrate that PrecipGen successfully represents both short- and long-term daily precipitation totals at individual locations, validating its ability to replicate observed climatic behavior across varied environments.

To read more about the PrecipGen model and how to use it, please refer to the GoldSim Library where you can read about it and download PrecipGen PAR and PrecipGen for your own use: Precipitation Simulator (PrecipGen) – GoldSim Help Center

Statistical Analysis of Streamflow Time Series

Posted by Jason Lillywhite

Using GoldSim's built-in probabilistic simulation capabilities, it is straightforward to perform statistical analysis of time series data. An example model was built and added to our library, which demonstrates how Monte Carlo simulation is used to analyze daily time series data of streamflow to produce daily, monthly, and annual statistics. In addition to this, the model finds a best fit probability distribution for these statistics.  

Reservoir Inflow Forecasting

Posted by Jason Lillywhite

Last month, at the annual symposium hosted by the Arizona Hydrologic Society, I presented on probabilistic reservoir forecasting using GoldSim. This model combines many existing components available in our library to forecast snowmelt driven runoff inflows to a reservoir and estimates risk of spills and/or shortages.

Building Blocks in GoldSim

Posted by Jason Lillywhite

One of the many strengths of GoldSim is its graphically enhanced user interface, which allows you to quickly build your model from reusable components. During a recent webinar, I built a reservoir operations model that receives water from a snowmelt driven watershed using 6 existing models found in our Model Library. Once I understood what my modeling requirements were, I was able to quickly compile a probabilistic system model that is powerful in demonstrating how to operate a dam that services changing water demands and climate scenarios, which protects against downstream flooding.

Applying the GoldSim WGEN Model to Generate Stochastic Weather Data

Posted by Jason Lillywhite

Now you can let GoldSim do all the heavy lifting for you when simulating weather for your next project. A new GoldSim model example in our library lets you quickly generate the input data required to run the WGEN model, which is a stochastic weather generator built in GoldSim that creates daily stochastic time series of precipitation, temperature, and solar radiation.

This model (called WGENprep) uses time series data to automatically generate the input file you need to run WGEN. The WGEN model requires a lot of statistical information in order to run it and it can be quite a project to develop these inputs. With WGENprep, you can simply input the time series, change the simulation start and end time to correspond to the time series and the model will automatically export all the WGEN input data to an Excel spreadsheet. All you have to do is start up the WGEN model and then copy and paste the data from Excel right into the WGEN dashboard. These models were recently put to the test using some observed historical time series data gathered from the Salt Lake City airport weather station, provided by the NOAA National Centers for Environmental Information website.

Calibration of Watershed Runoff Using AWBM in GoldSim

Posted by Jason Lillywhite

Last month, I presented a Webinar on Runoff Modeling in GoldSim. You can find the video recording of the presentation here. I learned a couple of lessons while building the models used for the demonstration and I thought it would be helpful to write about these lessons in a blog post.

Annual Recurrence Interval of Reservoir Spills

Posted by Jason Lillywhite

Models are built to better inform decisions. Unfortunately, the numerous disparate outputs of statistical models are often difficult to make sense of for the decision makers and/or stakeholders. Compiling the risk of specific events potentially occurring in the future into a single variable can considerably assist the decision makers into comparing the various trade-offs between different scenarios.

One of our long-time GoldSim users, Simon Chambert of Macroscopia submitted a model to our Model Library that is helpful for those looking for the recurrence interval of an event like a pond overflowing. Both the recurrence interval and exceedence probability are computed and displayed for a given set of input parameters that describe the pond design and constraints. This example can be used for other models that need to compute an annual recurrence interval.

Application of the Markov Process Rainfall Model

Posted by Jason Lillywhite

If you have visited our Model Library lately, you might have noticed that we have a nice little example model that demonstrates the use of a Markov process to simulate daily rainfall. You need to specify some key statistical inputs that have some basis on historic data. How do you develop these inputs? How do you know if the Markov model is realistic? I thought it would be helpful to show how this simple example might be applied in a real-world project and try to answer those questions.

*Note that I made changes to the results on 5/20/2016 after I used GoldSim's optimization function to better calibrate the rate variability.

Modeling Runoff from Multiple Catchments using a Vector Splitter

Posted by Jason Lillywhite

If you have some flow of material or a transaction and need to divide it up or allocate it, likely you will use the Allocator or Splitter element in GoldSim. While these elements are very powerful and make the job a lot easier, there is one condition for which it was not specifically built: handling an array of input amounts. To address this, we have added some nice examples to our library that allow you to simulate allocations and splits on arrays of data. These examples provide an easy way to build powerful models that might have otherwise been quite difficult to build and maintain. I tested the array splitter example model using a real-world example that simulates rainfall runoff in a new stormwater management system, and this is described in this post.

Stakeholder Involvement for Environmental Flow Alternatives

Posted by Jason Lillywhite

Sometimes it is a challenge to involve a diverse audience in the modeling process of a complex system. It is important that you adequately reflect the complexities of the system while at the same time present the results clearly and concisely for people that have different perspectives. Recently, Ryan Morrison (USGS) and Mark Stone (Assistant professor at UNM) were able to leverage the visual and dynamic strengths of GoldSim to successfully involve a diverse group of stakeholders in evaluating flow alternatives for the Rio Chama basin, New Mexico. I wanted to highlight this modeling application because of its unique approach within the world of dynamic simulation and to demonstrate the utility of GoldSim's new scenario management capability.