Update README.md

README.md

@@ -9,4 +9,11 @@ In this research, we use documented performance of a real-world UWS as a testbed
 The results indicate an assumption of stationary demands leads to large differences between simulated and observed RRV metrics for all supply scenarios, and especially in supply-limiting conditions when the peak severity is 129\% from the observed.
 The management implications of relying on stationary demands are severe: if seasonal operational decisions were made on these model results, managers might over-estimate seasonal out-of-district water requests by 50\%.
 In contrast, when using non-stationary demands, one can expect system performance error reduction between 30\% to 60\% for average and dry climate conditions, respectively, and accurate RRV metrics.
-Our results further indicate that this UWS is more sensitive to percent changes in per-capita demand relative to percent changes in supply, but because the supply variability is so much greater (158\% vs. demand range of 28\%), we suggest further work to examine the combined (and coupled) influence of both factors in overall system performance.
+Our results further indicate that this UWS is more sensitive to percent changes in per-capita demand relative to percent changes in supply, but because the supply variability is so much greater (158% vs. demand range of 28%), we suggest further work to examine the combined (and coupled) influence of both factors in overall system performance.
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+The ModelOutput folder contains all monthly scale water demands.
+The WD_Scenario_Builder_Monthly2.ipynb loads these demand projections from the CSD-WDM and interpolates them to a daily temporal resolution.
+The DroughtSuplusAverage_Data folder contains all SLC-WDM simulation results.
+Using the SLC_WSM_Performance_Analyzer_SLv2.ipnyb script, we can load all Goldsim SLC-WSM simulations to determine urban water system Reliability, Resilience, and Vulnerability compared to the historical record.
+This scrip also supports figure development and additional analysis functions.