Inverse relationship between SIF and GPP in moist deciduous forest using CliMA Land output

[Rohanms444]

Hi CliMA Land Team,

I'm currently using CliMA Land to simulate carbon and energy fluxes over a moist deciduous forest as part of my research. While evaluating the output, I've observed that the simulated Solar-Induced Chlorophyll Fluorescence (SIF) does not correlate well with the Gross Primary Production (GPP) in the summer months (roughly DOY 60–180).

Here I am attaching the link to open the graph
https://docs.google.com/document/d/18hgXlOcbbyf3hz1m9-xV2PP_8EFv9oIRciujCWpCumU/edit?tab=t.0

Any suggestions or guidance would be highly appreciated.
Thanks a lot for your great work on this model!

[cfranken]

If you could provide a minimum working example of your code so that we can see what exactly you did, we might be able to provide guidance.

[Rohanms444]

Except for the input data (which corresponds to a moist deciduous forest site in India), I have not made any changes to the code – I am using the example scripts as provided in the repository.

[Rohanms444]

I've been working with the CLIMA Land model's plant hydraulics module, and I noticed something a bit off when I slightly increase the root length (1.0 m to 1.1 m), the plant suddenly starts using all the water from the third soil layer. It feels like even a small root extension gives full access to deeper water, which doesn't seem very realistic. Is there a way to fix this so that water uptake depends more gradually on root depth maybe by tweaking how root length interacts with soil layers or by using a simpler bucket-style model? I'd really appreciate any suggestions.

In this region the soil depth is upto 2m only and the roots are reaching up to 1.2 m. Can u suggest any alternatives how to encounter this.