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.
Showing posts with label calibration. Show all posts
Showing posts with label calibration. Show all posts
October 13, 2016
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.
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.
Labels:
awbm,
calibration,
hechms,
hydrology,
optimization,
runoff
May 19, 2016
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.
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.
Labels:
calibration,
climate,
fit,
hydrology,
markov,
model,
optimization,
precipitation,
rainfall,
water
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