the definition of water yield

Dear NCP team,

I have two questions need your kind support:

1. The definition of water yield for the water yield module: is it correct that water yield= rainfall-evapotranspiration=surface runoff +baseflow+subsurface runoff? if so how about the water retention (or discharged to) in the soil? could I calculate the soil water retention this way: soil water=actual precip-AET-water yield?  

2. Based on Model output, the water yield of  built-up land is larger than that of vegetation land (e.g forest and pasture), the AET for built up land is smaller that AET for vegetation land. Are the results correct?

Thank you very much for your help. Looking forward to your anwer.

Su at Eawag, switzerland


  • PerrinePerrine Moderator, NatCap Staff
    Hi Su, 

    1. Water yield = rainfall - evapotranspiration = surface + subsurface runoff
    (Baseflow is usually defined as the streamflow between rain events, so it comprises subsurface runoff)
    The water retained in the soil ends up being evapotranspired or contributing to subsurface flow, so it is in one of the terms in the equation above.
    Because the model computes long-term water balance, the soil water storage is 0 (so precip - AET - water yield =0)

    2. The results you provide sound logical, and they are a direct result of your choice of Kc values in the model. So yes, usually urban areas produce high amounts of runoff because of impervious areas, which leaves less water available for evapotranspiration.



  • MaryeMarye Member
    Dear  Perrine
    I read one comment given by you. The map gives  volume of water "produced" by the pixel (i.e. precipitation falling on the pixel and not evapotranspired by its vegetation). How can I calculate or get water yield by considering  evapotranspired by its vegetation. 

    Thank you,
  • eawageawag Member

    Dear Perrine,

    Thank you so much for your quick reply. I got it.

    One more question, based on the model result: precip- AET- Water yield is not equals to 0. should I take this as the bias (or error) of the model?

    Thank you again


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