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JGCRI / gcamdata

The GCAM data system
https://jgcri.github.io/gcamdata/
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L145.water.demand.municipal needs a new science approach #543

Open pralitp opened 7 years ago

pralitp commented 7 years ago

This issue is mostly a duplicate from the JIRA issue JGCRI-212.

Mostly the approach itself is flawed because the data sets used are too incomplete to be reliable. In addition the dollar year for the "base cost" is being treated as 1975 dollars but most certainly is not.

This is certainly an issue to be addressed after Version 1, I've tagged it as Version 2 for now.

pkyle commented 7 years ago

Irrespective of which version this is addressed in (1 or 2), I think this issue needs to be addressed before the next model release. Right now in this branch, none of our multi-country regions (i.e., 17 of the 32) have defensible estimates of historical municipal water use. Fixing the bugs responsible for this is easy. For me, this is the top of the stack of things to fix once all chunks are translated and the output replicates. (After well deserved celebrations, @bpbond!)

bpbond commented 6 years ago

For me, this is the top of the stack of things to fix once all chunks are translated and the output replicates.

This is really important and I don't want to lose it. Starting new "things to tackle for 1.1" issue. Thanks @pkyle !

Nah, never mind, as long as we tag things correctly (with Pralit did), that's less duplicative.

pralitp commented 6 years ago

To update on the progress of this issue. We have fixed (on the GCAM repo, we will back port to Github soon) the most egregious problem of this issue: aggregating data then interpolating.

However as @mihejazi notes:

I agree with all of these fixes. Well done, Page!!! One thing to point out is that we should consider using the reconstructed historical water use data that we published this year. It builds on the FAO-AQUASTAT dataset, so we don't have to do the interpolation/extrapolation steps. This is not as critical as the fixes that Page has made, but I want to flag it for the future,
Huang, Z., Hejazi, M., Li, X., Tang, Q., Vernon, C., Leng, G., Liu, Y., Döll, P., Eisner, S., Gerten, D., Hanasaki, N., and Wada, Y.: Reconstruction of global gridded monthly sectoral water withdrawals for 1971–2010 and analysis of their spatiotemporal patterns, Hydrol. Earth Syst. Sci., 22, 2117-2133, https://doi.org/10.5194/hess-22-2117-2018, 2018, https://www.hydrol-earth-syst-sci.net/22/2117/2018/

russellhz commented 2 years ago

@pralitp @pkyle seems like this issue can be closed as the main idea has been addressed - my only question is whether Mohamad's point about switching to the Huang et al. 2018 data set is still relevant and worth opening as a JIRA issue?