This is my first time trying to use the InVEST model and I’m hoping to use the Urban Flood Risk Mitigation model to look at mitigating flood risk in portions of Wisconsin’s Driftless region. My question: Is there a way to incorporate topography into the model? The region I’m looking at is characterized by significantly steep hillsides and low-lying valleys. Rain fall on the ridges but the damage is done to the valleys. Is there a way to account for these differences and/or the flow of water?
The region is admittedly not “urban” by any standard, which may not align with the functionality of the model, but I was intrigued by the model and wanted to give it a try anyway!
So, the Urban Flood Risk Mitigation model is intended to model the effect of greenspaces and soil on the damage to buildings and built infrastructure, which doesn’t sound particularly useful to an analysis in the Driftless Zone. With that said, I’d suggest taking a look at the details of the model in the User’s Guide chapter and see if the math of the model could make sense for this region.
My guess is that because of the interesting topography in the area the UFRM model probably won’t produce reasonable results.
While the UFRM model doesn’t handle topography directly, InVEST does have several other models that do route water across the landscape and model the flow of sediment (SDR), nutrients (InVEST NDR) and model seasonal water yield. None of these directly model flood risk, unfortunately.
I’m sorry I don’t have any direct solutions to this, but it sounds like an interesting problem!
@swolny, have you worked around InVEST’s lack of a flood risk model in any of the studies you’ve worked on? Or @RafaSchmitt, would you have any suggestions for modelling flood risk in this region?
The one way that we have used existing freshwater models to give an idea of flooding is with output from the Seasonal Water Yield model. That model gives monthly and annual results for “quickflow”, which is precipitation that runs off of the landscape quickly, during a rain event, and is the flow that mainly causes flooding. We use the quickflow result (could be annual, or over the months that are part of a rainy season, etc) along with the related precipitation map(s), which are inputs to the model, to calculate an index of “flow retention”, using the simple equation
1 - (quickflow / precipitation)
(qickflow/precip) gives an idea of the ratio of precipitation that runs off, and (1-) gives the inverse ratio, the amount of precipitation that does not run off, so is being retained by the landscape. The assumption is that this retention is helping reduce flood risk downstream.
This is very simple, and only provides an index, but it is from a model that is made for mostly natural landscapes, where the Urban Flooding model is specifically designed for urban settings.
Thank you all for the thoughtful responses! It seems like maybe it isn’t the best tool for larger, rural areas. Hopefully I’ll have an opportunity to use it at some point in the future!
I have the same question! In looking at some of the other InVEST models, many of them use DEMs for helping to model water flow and such. So, I’m wondering why a similar component wasn’t built into the Urban Flood model? Like requiring a DEM based watershed or sewershed input instead of vector based. Is that a modification that might be on the horizon?
Thanks for posting to the forums. I’m not aware of any developments for trying to incorporate a DEM into the model. I think the responses above by James and Stacie are the most useful for thinking about modelling flooding.
If anyone has ideas on how a DEM might be incorporated and used we would love to hear them.
I have no real idea on how to incorporate DEM into the UFM model, and this is a bit off topic, but I am modelling a large piece of land (100,000s km^2), and would very much like to see a landscape water runoff model that could be influenced by Topography. Over this same landscape I can already run a SDR/NDR model, which is based on overland flow.
A model that can help me model water volume runoff from a rain event and predict river flood height would be excellent. Someone sufficiently cunning could include priors like how much water is in the ground beforehand (like a model burn in period). Have the model informed by soil characteristics similarly to the flood risk models themselves. Perhaps calibrate the model to observed river height in a non-flood, average rain scenario, and then start tweaking the rainfall volume/distribution to model extreme events or temporal over/under dispersion in rainfall density. With that, I could model the physical effect and cost of replacing Forest with urban fabric, or agriculture with forest, etc over a large landscape.
I imagine that to be a lot of work for the InVEST team, but I endorse it.
Thanks a lot for your suggestions. It is very likely that there is a flood model out there that can do what you describe, and I encourage you to make use of it if it’s the best tool for your job. InVEST is specifically designed to provide (relatively) simple models, for situations where there is not the time, data, money or expertise required to use the more complex ones that others provide. One of our earlier hydrologists told me that, in some ways, it’s much harder to create a scientifically-valid and useful water model that is simple, rather than a complex one. But since our goal is to help a wide range of people begin to take natural capital into account in their decision-making, we try to create models that require minimal expertise and data input, and people can move on to more complex ones as time and resources allow.