Fig 1. Flowchart of the macro management tool for WFE Nexus of geospatial administrative nodes (districts) with core aspects addressed by two DSS processes
Household water food and energy (WFE) expenditures, reflect respective survival needs for which their resources and social welfare are inter-related. We developed a policy driven quantitative decision-making strategy (DMS) to address the domain geospatial entities’ (nodes or administrative districts) of the WFE Nexus, assumed to be information linked across the domain nodal-network. As investment in one of the inter-dependent Nexus components may cause unexpected shock to the others, we refer to the WFE normalized expenditures product (Volume) as representing the Nexus holistic measure. Volume rate conforms to Boltzman entropy suggesting directed information from high to low Volume nodes. Our hypothesis of causality-driven directional information is exemplified by a sharp price increase in wheat and rice, for U.S. and Thailand respectively, that manifests its impact on the temporal trend of Israel’s administrative districts of the WFE expenditures. Welfare mass (WM) represents the node’s Volume combined with its income and population density. Formulation is suggested for the nodal-network WM temporal balance where each node is scaled by a human-factor (HF) for subjective attitude and a superimposed nodal source/sink term manifesting policy decision. Our management tool is based on two sequential governance processes: one starting with historical data mapping the mean temporal nodal Volumes to single out extremes, and the second is followed by WM balance simulation predicting nodal-network outcome of policy driven targeting. In view of the proof of concept by model simulations in in our previous research, here HF extends the model and attention is devoted to emphasize how the current developed decision-making approach categorically differs from existing Nexus related methods. The first governance process is exemplified demonstrating illustrations for Israel’s districts. Findings show higher expenditures for water and lower for energy, and maps pointing to extremes in districts’ mean temporal Volume. Illustrations of domain surfaces for that period enable assessment of relative inclination trends of the normalized Water, Food and Energy directions continuum assembled from time stations, and evolution trends for each of the WFE components.
Sorek, S., Peeters, A., Yuval, F., & Savic, D. (2022). Governance using the water-food-energy Nexus and human-factor measures. PloS one, 17(1), e0261995.
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