search

camiloramirezgo / NWSAS-paper-IOP

This is the repository of the NWSAS paper using the IOP template
1 stars 0 forks source link

Comment 3.4 #41

Closed camiloramirezgo closed 3 years ago

camiloramirezgo commented 4 years ago

The GIS-based analysis (clustering) minimizes distance with respect to water demand. Is distance the only metric that influences the cost and decision for locating wastewater treatment facilities? Did you consider a minimum scale (capacity) for operating these facilities, and how the costs would be recovered? Also, why is eliminating administrative boundary constraint desirable when forming clusters (p. 8, lines 5-6)? Do any of the clusters cross national boundaries? According to the Supplement, there is large variation in baseline water extractions by cluster. How would your results change if some clusters with relatively small amount of water extractions are excluded (e.g. if you focused on the top-ten largest cropland and/or population clusters)?

In addition, more generally, since you create and perform analysis at the cluster scale, it is useful to mention the mean or median and min/max ranges for the reduction in water extractions by cluster in the main text (and noting detailed the cluster-scale results are in the Supplement). Same comment applies to energy findings in Fig 9.

For the detailed figures in the supplement (e.g. Figures 8 through 21), the category axis of the bar / column charts is cluster number. This is not helpful when there are 40 clusters and your readers are not as well acquainted with them. Consider a scatter plot of savings with respect to cluster size (by scenario if necessary), placed over a map of clusters.

camiloramirezgo commented 3 years ago

For this a plot sowing water savings from each scenario vs the baseline would be interesting.