I’m trying to understand the mean of the output layer of the model Urban flood risk mitigation.
Particularly, I would like to deepen what does it means “Service.built”.
What I understood is that for each watershed this indicator represents the summation of the R_m3 (runoff retention value) of all pixels included in the watershed multiply for the monetary value related to the potential damage to infrastructures always included in the same watershed. So, this means that the higher is this indicator and better will be the Service of runoff retention related to the “building protection” in a certain watershed.
Please, can you confirm that my interpretation is correct or eventually explain better the significance of this indicator?
Your understanding sounds correct to me! The values in the damage loss table (units: dollars per square meter of building footprint) are applied to the infrastructure vector and summed to get Affected.Build, the total potential dollars of damage loss for the watershed. Then we multiply Affected.Build by the sum of R_m3 across the watershed: Service.built = Affected.Build x sum(R_m3)
So, as I understand it, the Service.built indicator is in units $ * m3. I’m guessing this is because it’s difficult to say exactly how much damage is caused per cubic meter of runoff. So I would use this as a relative value, not an exact measure of savings.
Also keep in mind, the user’s guide says, “Currently, a simple approach to value flood risk retention is implemented, valuing flood risk as the avoided damage for built infrastructure. Alternative approaches (e.g. related to mortality, morbidity, or economic disruption) could be implemented.”
Dear @esoth,
I understand the construction of the serv.built indicator but I still struggle to understand its (non-mathematical) meaning.
I understood that it is an indication of the value of the service and that it depends on the value of the infrastructure in the study area for the amount of run off avoided: but I tried a simulation with low values (10/20/30 euro/m2) of the infrastructure and the result is exorbitant.
service.built is an indicator of avoided damages to built infrastructure in the given watershed, but the user’s guide is clear that:
It should be considered only an indicator, not an actual measure of savings.
Still, I agree that your serv_blt values look like they might be high and it’s not immediately clear why that might be. If you share your inputs here (a file sharing service like dropbox or google drive usually works best), I’d be happy to take a closer look.
Hi James, thanks for your support.
Okay for the indicator…always on that, anyway, we agree that the model can’t calculate the area of infrastructure subject to potential flooding…or rather it does calculate it, but it considers the entire study area as floodable area. Right?
I’ll leave you the link with my input data.
Consider that I have inserted a depth of rainfall of 143mm.
@jdouglass
I add here, a further doubt about one result, namely the values of rnf_rt_idx.
If I understand correctly, these values are defined as the percentage/proportion of retained water to total runoff (Q) or also referred to as flood volume per watershed, so rnf_rt_idx = rnf_rt_m3/flood volume.
But from the results I got, they seem to express the percentage/proportion of water NOT RETENTIONED for each watershed. That is, it seems to me to be the inverse of what is stated, i.e. rnf_rt_idx = (flood volume-rnf_rt_m3)/flood volume
Am I wrong?
If you want to check, the input data is the same as attached in the google drive link above.
Ok found and yes, I was wrong.
Only the first line (first watershed) of my results follows those formulas I posted above (that’s why I was generalizing it).
rnf_rt_idx is the average of run-off retention values (CALCULATED ON PRECIPITATION) per watershed.
And run-off retention values are calculated with eq. 117 in the user guide.
Yes, the model considers the entire study area as floodable. Low-lying regions, for example, are not considered as more or less floodable … the model is relying on rain and soil information instead to estimate retention and flood volumes.
The serv_built indicator is trying to demonstrate the value of the runoff retention services of your landscape. If no water were retained, then that volume of water could, in a worst-case scenario, flood the buildings in your area of interest causing serv_built dollars/euros/unit-of-currency in damage. I think I’m expressing that correctly.
Hi James.
Thanks for the reply and yes you were helpful
It remains to be understood why they were coming such high values in serv.built despite low input values…
I’ll look at it calmly.
Did you ever figure out what serv.built is suppose to indicate? Our team is also trying to figure out why aff_bld cost is being multiplied by the runoff retention volume.
