<p>I have an 2D hydrodynamic model in a approx. 10km² catchment and one rain event that goes one hour with measurements in a 5min interval. The reccurance interval for an event like that is close to 50years. </p>

<p>When I run my simulation software I get the flood heights for every m² in my catchment for every 30min. My question is, how do I validate my result? I guess, ideally I take the flood heights for 10 other rain events with the same intensity and duration and see if it fits my results. But I don't have these information. </p>

<p>what could be approaches to validate my model?</p>

CC BY-SA 4.0
2020-01-19T17:39:43.577Z
The usual approach is to use a simplified setting that can be solved analytically - then you compare numerical and analytical solution.
AtmosphericPrisonEscape
CC BY-SA 4.0
2020-01-19T19:17:44.740Z
ok sounds good. Unfortunately, I don't know you mean by "analytical setting". Could you give me an example, then I can do some research for suitable analytical approaches.
DGIS
CC BY-SA 4.0
2020-01-19T19:21:25.907Z
I said simplified setting - You choose the equations, boundary conditions and model parameters such that you can solve the whole system on paper - then compare to the simulation. Often there are also standard benchmarks that different simulation communities have agreed upon.
AtmosphericPrisonEscape
CC BY-SA 4.0
2020-01-20T01:08:31.303Z
There are multiple levels of model validation and verification that can be performed. Compare to an analytical model, calibrate on one time period and compare to other periods, Apply a stochastic variation based on the uncertainties in your parameters (eg using PEST). I suggest you look at the literature for similar models and see what they did.
haresfur
CC BY-SA 4.0
2020-02-01T11:26:55.050Z
A common method would be to run a simulation using the same starting conditions in your model and another previously published model and see how well they match
Will
CC BY-SA 4.0
2020-02-01T11:31:08.447Z
Hello Will, 

but there are no publications for my study area. But you mean I could do another simulation with another well known model and if the results are nearly the same than my model is probably representing the reality pretty good?
DGIS
<hydrology><models>
how does model validation work? What is needed for an appropriate validation
DGIS
# how does model validation work? What is needed for an appropriate validation

(Asked by: username_0 on 2020-01-19)

I have an 2D hydrodynamic model in a approx. 10km² catchment and one rain event that goes one hour with measurements in a 5min interval. The reccurance interval for an event like that is close to 50years.

When I run my simulation software I get the flood heights for every m² in my catchment for every 30min. My question is, how do I validate my result? I guess, ideally I take the flood heights for 10 other rain events with the same intensity and duration and see if it fits my results. But I don't have these information.

what could be approaches to validate my model?

**Tags:** hydrology, models

> **Comments:**
> **username_1**: The usual approach is to use a simplified setting that can be solved analytically - then you compare numerical and analytical solution.  
> **username_0**: ok sounds good. Unfortunately, I don't know you mean by "analytical setting". Could you give me an example, then I can do some research for suitable analytical approaches.  
> **username_1**: I said simplified setting - You choose the equations, boundary conditions and model parameters such that you can solve the whole system on paper - then compare to the simulation. Often there are also standard benchmarks that different simulation communities have agreed upon.  
> **username_2**: There are multiple levels of model validation and verification that can be performed. Compare to an analytical model, calibrate on one time period and compare to other periods, Apply a stochastic variation based on the uncertainties in your parameters (eg using PEST). I suggest you look at the literature for similar models and see what they did.  
> **username_3**: A common method would be to run a simulation using the same starting conditions in your model and another previously published model and see how well they match  
> **username_0**: Hello username_3,   but there are no publications for my study area. But you mean I could do another simulation with another well known model and if the results are nearly the same than my model is probably representing the reality pretty good?  

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## 0 answers

