Quantifying Uncertainty to Support Sustainable Planning and Management of Water Supply Infrastructure. Alireza Yazdani Post-Doctoral Research Associate Department of Civil & Environmental Engineering Rice University Presented at: SAMSI Uncertainty Quantification Transition Workshop
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Post-Doctoral Research Associate
Department of Civil & Environmental Engineering
SAMSI Uncertainty Quantification Transition Workshop
May 22nd, 2012
A hypothetical network representation
America's Infrastructure G.P.A. = DA = Exceptional B = GoodC = MediocreD = Poor F = Failing
* Water Distribution Systems (2011), D. Savic, J. Banyard (Eds.), ICE Press.
How does water taste there?
Is the pressure sufficient?
what if these pipes break together?!
what is the cost/impacts of getting water here?
A slightly reconfigured EPANET representation of Colorado Springs WDS
Not to be absolutely certain is, I think, one of the essential things in rationality.
Image taken from: S. Fox (2011), Factors in ontological uncertainty related to ICT innovations, I. J. Manag. Proj. Busin, 4 (1), 137-149.
Pipe Break/Contaminant Ingress
Image from D. Kang, K. Lansey, Scenario-based Robust Optimization of Regional Water/Wastewater Infrastructure,doi:10.1061/(ASCE)WR.1943-5452.0000236
Image: Albert, Barabasi and Bonabeau, (2003), Scale-free Networks, Scientific American, 288, 50-59.
Colorado Springs (CS), USA
City of Houston (COH), USA
Richmond Yorkshire Water (RYW), UK
Demand-adjusted entropic degree (DAED)* combines topology and physics by incorporating the number of links attached to a node, the capacity of the link connections and the way they are distributed while taking into account the demand for water at each node.
* A. Yazdani, P. Jeffrey (2012), Water Resour. Res., doi:10.1029/2012WR011897, in press