Monthly Baseflow

I would like to map Bsum at montly timesteps, particularly to elucidate increased dry season baseflow in forested areas, regardless of the reduced annual water yield. Is there a way to produced these results with the current SWY model?

Perhaps something like this?
Bi = Pi - AETi - Qfi
i = month

Thanks,
Sergio

While it might be possible to disaggregate the B_{sum} values by month, it’s unfortunately a bit tricky to do because of the annual aggregation and the routing across the landscape. The Pi - AETi - Qfi calculation you mention would be closer to the Local Recharge calculations, which, while related, doesn’t sound like quite what you’re looking for.

I’ll reach out to the team and see if anyone has any suggestions.

True, Recharge won’t capture the so-called “baseflow”. It would be great to hear the team’s thoughts and suggestions regarding this issue.

Thanks,
Sergio

Hi Douglass,

I am wondering if you guys have any suggestions regarding the mapping of Bsum values by month. Or at least being able to interrogate the model on the driest month of the year? This is very reelevant when it comes to model the effects of forest on dry-season flows rather than annual water yield.

Thanks,
Sergio

Hi Sergio,

I’m not sure of the biophysical implications of disaggregating the monthly baseflow from the annual one, when this model was developed it was only validated against annual baseflow. But if you wanted to hack this in yourself you could run the model with all the monthly inputs set to the monthly data you desire then divide the baseflow by 12.

The way we implement the model now we don’t aggregate the baseflow into months since it’s all aggregated into a year, but if we were to do this you’d get the same result with the method I describe above.

Rich

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Hi Sergio: have a look at this paper, in which we present several ways of splitting the annual baseflow into monthly values: Hamel, P., Valencia, J., Schmitt, R., Shrestha, M., Piman, T., Sharp, R. P., et al. (2020). Modeling seasonal water yield for landscape management: Applications in Peru and Myanmar. Journal of Environmental Management , 270 , 110792. https://doi.org/10.1016/j.jenvman.2020.110792

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Thanks Rich and Rafa,

The approach adopted by Hamel et al., 2020 (assuming that the monthly baseflow values were distributed according to the monthly precipitation) is very appealing. However, I think that it is less flexible than Rich’s suggestions. Particularly, when it comes to mapping and “calibrating” dry-season flow conditions. Anyway, I will use and compare both approaches and hopefully revisit this post with some recommendations.

Thanks,

Sergio

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Hi, rich,
I have tried both the two methods(1.assuming that the monthly baseflow values were distributed according to the monthly precipitation;2.run the model with all the monthly inputs set to the monthly data you desire then divide the baseflow by 12) to get the monthly baseflow. I think the method you suggest is more rational, but when I aggregated the 12 baseflow results from method 2 (totally 108mm), the value was larger than the annual baseflow(70mm), could you or anyone give me any suggesrions?

thanks,
Annabelle

Hi Rich,
I wonder if this method also applys to calculated monthly actual evapotranspiration?
Thanks,
Jiangxuan

Hi @oohjiangxuan ,

I’m not sure I understand your question. Could you say a bit more about what you are trying to calculate in the Seasonal Water Yield model?

Thanks,
James

Hi @jdouglass
I have solved the problem. I think I could direct use the monthly actual evapotranspiration provided by MODIS. and calculate the monthly local recharge by L= P-QF-AET.

Thanks for your teams’ reply!!
Jiangxuan

I don’t have any experience with using that particular dataset, but that sounds like it’d work fine!

Best of luck,
James

PS: I’ll close this thread now since it’s been open for several years and we’ve had several separate conversations on it. If you’re coming across this thread, please feel free to open a new one!