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usle to high (SDR)

Hi InVest users,

my results from the usle are to big. the blue field on the picture shows a agricultural field with almost one hectar. the total soi loss is about **206 t/ha/year** (zonal statistics -> sum of the pixels in the field). the mean value for one pixel in this field is about **0.14 t/ha/year**. i used a dem with a resolution of 2.5m x 2.5m. 
 
the imputdata was as follows: **R=746**(all area); **K=0.27**(all area); **C=0.26** (agricultural area) 
k=2; IC0=0.5; SDR= 0.34

i allready calculated the usle in GIS by myself. i got quite good results. even the ls-raster from the intermediate_outputs is not to high compared to my ls-raster caluclated in GIS. 

the InVest model is calculating succesfully, there is a warning though at the flow acumulation part:

*04/20/2019 10:49:09  natcap.invest.sdr  INFO     calculating flow accumulation*
*04/20/2019 10:49:09  natcap.invest.pygeoprocessing_0_3_3.routing DEBUG    starting flow accumulation*
*04/20/2019 10:49:14  natcap.invest.pygeoprocessing_0_3_3.routing.routing_core **WARNING**  no flow direction found for 0 2 WARNING  no flow direction found for 0 2*
*04/20/2019 10:49:14  natcap.invest.pygeoprocessing_0_3_3.routing.routing_core **WARNING**  no flow direction found for 0 2*
*04/20/2019 10:49:22  natcap.invest.pygeoprocessing_0_3_3.routing.routing_core INFO     calculate transport cells_to_process.size() = 352*
*04/20/2019 10:49:22  natcap.invest.sdr  INFO     calculate ls term*
*04/20/2019 10:49:22  pygeoprocessing.geoprocessing INFO     starting stats_worker*
*04/20/2019 10:49:22  pygeoprocessing.geoprocessing INFO     started stats_worker <Thread(Thread-6, started daemon 11488)>*
*04/20/2019 10:49:26  pygeoprocessing.geoprocessing INFO     100.0%% complete*

not sure if this warning causes proplems calculating the usle...

what do i miss? can anybody help me out here, please?
thank you!
1124 x 739 - 208K
594 x 147 - 13K
179 x 445 - 7K
395 x 172 - 6K
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Comments

  • swolnyswolny Member, NatCap Staff

    One thing that I see about your inputs is that the K (soil erodibility) values seem to be in US units, not metric, so you need to multiply them by 0.1317, which will decrease the final values.

    Also remember that we really need to calibrate models to observed data before we can feel comfortable with the exact values. Without calibration, it's recommended to use relative values and patterns.

    I do see a general trend though in forum posts of people saying that the model overestimates, so we should probably look into that for future updates to the model.

    ~ Stacie

  • bastian87bastian87 Member
    Thnak you very much Stacie! For USLE calculations in GIS i normally used 
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