Seasonal Water Yield Limitations

Hello, community and software support! My name is Victor and I work for the Environmental Institute of Rio de Janeiro, Brazil. We are running both SDR and SWY to test their potential in forest recovery scenarios. SDR has prooven to be most effective. However we have encountered some limitations regarding SWY. For exemple:

  1. Obtaining monthly Kc values for natural or anthropic vegetation like forests or fallow/pastures is demanding a great effort of calibration, without a precise level of certainty. From the work of Allen et al. 1998, can we consider to use average Kc values for pastures, since they are not cut during the year (abandoned pastures)?

  2. Does SWY consider slope from the DEM when calculating water balance, quick flow and base flow?

Hi, I can only answer #2 which is no. I’m guessing you might be thinking high slope would have less contribution to water balance or something? My understanding is the time periods are long enough that is not necessary to consider. Also if you haven’t seen it, the full model for SWY is described here:

Hi Victor -

For #1, I agree that gathering all of those Kc values is very time-consuming and generally imprecise. So we use the best values that we can find, that seem to represent the system well. I’m not quite sure what you mean by “average” Kc values for pastures, but if this means assigning the same Kc value for all months of the year, that seems fine if you know that the pastures don’t change much during the year. I’ve often used the same Kc value all year, for example tropical evergreen forests, where there isn’t likely to be much change (and certainly no published change) in Kc during the year. It’s more important (and sometimes easier) to find differing Kc values for agriculture and similar land cover types that definitely change over the year.

~ Stacie

Thank you, Stacy! Regarding average Kc, that’s exactly what I meant. I was affraid that using the same values for all months could mask or alter the final result in some way. Indeed, it’s been really hard finding literature about Kc for natural vegetated areas, or pastures that are not submited to seasonal cutting or irrigation (my case, specifically). We tried man alternatives, including estimating Kc via remote sensing. May I ask what value did you use for tropical evergreen forests?

Thank you! Yes, i’m thinking that high slope areas will contribute less to water recharge or base flow. I’m running the model for a very humid tropical basin, with significant variation in slope and altitude, so the time interval of one year would be significant, I would think. Indeed, it is described in the manual that the model does not consider slope for both quick flow and base flow.

Thanks for your response!

Hi Victor and Stacy,

Although this thread was 10 months ago, I find your discussions really helpful. I’m also doing the same process here in South Carolina (SDR and SWY) to value the ecosystem services and as an input to a Marxan software eventually.
But to the Kc point, would it make sense to use the Kc of agriculture based on the cropping season? I used the cropping data layer as landcover since it has detailed crop cover and searched for the Kc of all crops. Then apply the Kc only on months when the crops are in season. For off-season, I used the Kc for barren to simulate the idle cropland period. Would this approach make sense to capture the monthly variation in SWY?

Hi @carlureta -

Yes, it definitely makes sense to use the Kc of agriculture based on seasonal variation for this seasonal model. You’re fortunate to have both detailed crop information and Kc values for them. We have also used the Kc value for bare ground during the fallow season, which of course assumes no cover cropping or other soil management practice is used.

~ Stacie

Hi @swolny ,

Thanks for the response.
This would allow us now to assess the difference if a simulated cover crop or other practices are implemented, versus just the bare ground for ecosystem service change.
Thank you so much. Your response is very helpful.

  • Carl