I am currently running the Urban InVEST models for the municipality of Stockholm.
With the flood risk mitigation model (as well as the stormwater retention model) I noticed that forest areas do not seem to retain any runoff.
The curve numbers for the forests are among the lowest for all the categories, which I thought would generally benefit a higher runoff retention. Furthermore, urban green areas, for which I found very similar curve numbers, do retain a lot of runoff.
When comparing the forest and urban green areas to the soil types present, it at first seems as if the runoff patterns do follow the soil types more than the land cover category. Soil group 2 seems to not retain runoff. However, also this trend is not consistent, as can be seen in the squares 1 and 2 highlighted in the attached screenshot, where soil group 2 is not as predominant.
Thanks for posting your input data. I’m looking at it now, and it looks like there’s a mismatch between what some of the integer Values represent in the LULC_subwatersheds_50.tif map (which I think is the one you made maps of, and not LULC_UA_subwatersheds_10.tif, which is also included in the input data) and what they represent in the biophysical table.
For example, a value of 15 in LULC_subwatersheds_50.tif is “Forests”, but in the biophysical table lucode 15 is “Water”. If you’re using this combination of LULC and CSV for modeling, that will definitely lead to the problems you’re seeing, since the model is assigning the curve numbers for Water to Forest pixels.
Hi @swolny, thank you so much for your quick reply!
That was indeed the problem. I double-checked the values in my biophysical table and adjusted them to be in line with the values from the LULC I am using (indeed, the first model run was with the LULC subwatersheds 50 file). Now my model is working smoothly again and the outputs are more along the lines of what one would expect in terms of runoff retention.