I’m working on setting up the SDR model for my study area and have a couple of questions. My site is located in the US, so I have the benefit of fairly good data availability for all of the necessary inputs, or ways of estimating them. For hydrographic data, I am relying on the National Hydrography Dataset (NHD) from the USGS. I have already compiled the necessary data and am at this point testing out the model to become more familiar with the outputs.
- I’m interested in running multiple landcover scenarios in different sub watersheds within a larger area of interest. While I am using the workbench for initial model test runs, I will be using the Python API in order to automate model runs. In the interest of speeding up run times, I am curious if it is possible to forgo some of the intermediate processing the model does. Specifically, calculating the flow accumulation, flow direction, and the stream rasters. These are provided as part of the NHD, with all of the preceding DEM processing steps already carried out, so they could be directly fed to the model.
I suspect the model’s code is set up such that avoiding these calculations is either not possible, or not trivial. Also, I’m not sure how significant the run time savings would be. When using three workers, my test runs so far have taken around ~37 s, which is not terrible, but ideally could be brought down a bit. Is there any way to avoid doing those calculations?
- Rather than relying on the model to calculate the stream network via the threshold flow accumulation value, I am considering passing the stream network to the model with the “drainages” input, and setting a high threshold value. However, when doing so, I receive an error message (logfile attached). Any idea what might be going on? Note: when I run the model with the exact same inputs, except for no drainages file and a lower threshold value, it runs without issue.
InVEST-natcap.invest.sdr.sdr-log-2023-02-21–10_23_31.txt (2.4 KB)