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This data is the TGR streamflow scenario tree data as the model input, shown in Fig. 10 of the manuscript, with small perturbations as required by the data releasing policy. The scenario probability of each scenario is shown in Table 1 of the manuscript. We acknowledge Tamilselvi Selvaraj for the open-source available program in the MATLAB file exchange, as shown in the reference. We also acknowledge Sean Turner and Stefano Galelli for their open-source R package "scenario" as shown in the reference.
{"references": ["Tamilselvi Selvaraj (2021). MATLAB code for Constrained NSGA II - Dr.S.Baskar, S. Tamilselvi and P.R.Varshini (https://www.mathworks.com/matlabcentral/fileexchange/49806-matlab-code-for-constrained-nsga-ii-dr-s-baskar-s-tamilselvi-and-p-r-varshini), MATLAB Central File Exchange. Retrieved May 29, 2021.", "Sean Turner and Stefano Galelli (2016) https://cran.r-project.org/web/packages/scenario/scenario.pdf"]}
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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