Plant Available Water Content raster and run the model

Kind regards,

My name is Bibi and I am collecting the data to run the InVEST Annual Water Yield Model. I have downloaded the latest version which is 3.10.2. This is my first time using it so I have been learning about it but I lack expertise in GIS as well.

I was close but not successfully running the model because of the PAWC layer.

  1. I have downloaded the layer from Soil and Terrain Database (SOTER) for Latin America and the Caribbean (SOTERLAC), version 2.0 (ISRIC Data Hub) and according to this file (, they have properties such as:
    Bulk density (kg dm-3), available water capacity (cm m-1)
    STPC = Silt mass %
    SDTO = Sand mass %
    CLPC = Clay mass %
    So I had tried to use the SDTO and CLPC values and put them in SPAW and then make the difference between Field Capacity-Wilting point and that result divided by 100 but the maximum result is 0.177 and I am not sure is accurate :frowning:
    image The total list is in page 21 Appendix 2 from

  2. However, I wanted to try using it just to make a test for the model to run but when I put the raster then I got this:

    which instead of work made a problem for other layers :frowning:
    The error message is ‘‘Bounding boxes do not intersect’’ but I made sure that all the layers are projected in WGS_194_UTM_Zone_19S so I do not know what to do.

I kindly appreciate the collaboration.
Have a good day.

Hi @Bibi , thanks for posting,

It does take a bit of GIS experience to setup your data for InVEST. We have some instructional videos here: GIS for InVEST | Natural Capital Project

The one’s on “Coordinate Systems” might be useful to you.

The error message suggests not all the input layers overlap. Since this problem arose after adding the PAWC layer, that one is probably the problem. Even if all the layers have the same projected coordinate system, they still may not overlap in space. If you load all the data in GIS, do all the layers overlap? And do they all appear in the correct place on the globe?

Does the error message also include a long list of coordinates? These are the bounding boxes of all the layers with the :x: . If you can share that information here we can help find the problem.


1 Like

Hello Dave,

Thank you for your fast and sincere reply.

I have checked in detail the training video you recommended to me and followed the exercise with the layers again. Still, I think the problem is related to the PAWC layer since the others overlap when I put them in ArcMap except for that one. I got this sign in the software and I think the problem comes from the way how I made the layer.

Therefore, this makes me come back to my first question. Is it correct the method I used for the PAWC layer? Are the values accurate?

But if not, is there a simple method to create that layer using SOTER for Colombia?
Could you kindly explain me, please?

Additional information from the error is below as shown in the interface:

Thank you for the collaboration.
Have a great day.

Hi @Bibi -

How did you reproject your PAWC layer to UTM? Which tool did you use?

The pixel values for PAWC look ok to me. Did you check out the sample data for Annual Water Yield? The values in the sample data are 0.13-0.19, which is only for one small place in the world, but you’re well within that range.

~ Stacie

Hello Stacie,

Thank you for your kind reply and for confirming about the PAWC values.

I have rewatched the video training an repeated the process. The problem was that the layer I used was not defined and I used the wrong tool but thanks to your great video I realized and made it again. First changed to WGS_1984 and after projecting the raster to UTM.

The model runs successfully :slight_smile:

However I have another question, I know Z is empirically and I have used a value of 4 since I read in a paper okay for tropical climates but s it okay?

Thank you in advance.
Have a good day.


Hi @Bibi. About the Zhang coefficient is true but, Z is the value according your area of study (k is the parameter of calibration of the model). In this study, you can learn and know more about Zhang coefficient.