Control and decision making of water supply systems influence economic, political, and social variables on several time horizons. Particularly in Central Asia, the international nature of water resources, large irrigation requirements, and depletion of surface water and aquifers in the arid region call for a systems-level framework to analyze disruptive scenarios and determine a schedule of risk countermeasures. This paper evaluates risk as the influence of scenarios on system order. Through scenario-based multi-criteria decision analysis, system initiatives are prioritized in the baseline and disruptive scenarios. The methods are applied to a case of water policies in Turkmenistan where twelve water policies are ordered according to six system criteria including social, situational, and economic factors. The system order is updated across each of seven disruptive scenarios relating to political, economic, technological, and societal trends and forecasts.

Disruption of complex infrastructures systems involves cascading failures and interdependencies. This paper presents a network-based approach to assessing infrastructure resilience using scenario-based disruptions that remove entire sectors from the network. This approach evaluates system-wide vulnerabilities by modeling structural failures through the removal of nodes from the infrastructure graph. The framework uses a directed graph to represent interdependencies and uses eigenvector centrality to rank sector influence. Disruptive scenarios, including power outages, communication failures, and hybrid threats are applied to evaluate changes in system order. Spearman’s rank correlation quantifies the disruptiveness of each scenario, identifying which sectors experience the most significant shifts in importance. Results show that disruptions to the communications sector cause the greatest reordering of system orders, while disruptions to water & wastewater have a lower impact. The analysis demonstrates how different hazards affect regional resilience and provides insights for decision-makers to schedule the risk countermeasures.

Decision making for resilient infrastructure systems requires methods for assessing risk across political, social, economic, and physical domains. Traditional risk assessments for physical systems often consider only historical data in prioritization and decision making. This paper presents a systems and risk analysis framework to identify resource threats to energy system development priorities. The methods are demonstrated for the case of alternative energy investments in Turkmenistan. Twenty-seven sub-basins are ordered according to three satellite-observed metrics representing energy generation potential. Disruptions to the baseline system order, induced by 30-year forward-looking projection scenarios, are used to identify the most and least resilient sub-basins in the context of energy system development.

Iraq's infrastructure's water and environmental security are influenced by its semi-arid to arid climate, marked by erratic variations, including minimal precipitation, increasing air temperatures, and compromised water quality resulting from reduced inflow in the tributary. The transportation sector plays a vital role in improving economic conditions and mitigating the impacts of climate change. However, critical transportation systems, essential for the movement of goods, information, and people, are jeopardized by water scarcity and climate change. This study develops a sensitivity analysis of the priorities among transportation nodes subject to their disruption by water scarcity and other emergent and future stressors. The stressors include social, technological, regulatory, workforce, market, climate, and hydrologic criteria. This analysis describes the nodes of highest importance and quantifies which scenarios are the most and least disruptive to the system order of nodes. This study includes thirteen order criteria, forty-three nodes, and seven risk scenarios. The paper should interest the system owners and operators who are concerned with monitoring their enterprises' resilience and environmental security.

The resilience of vulnerable populations to environmental extremes is a concern for policymaking across environmental justice, economic development, technology innovation, etc. This study models the resilience of system order for a portfolio of investments, focusing on the spatial distributions of environmental stressors (i.e., precipitation, temperature, soil moisture, and elevation), social vulnerability, and risk exposure. The methodology quantifies risk as a disruption of baseline order under each of several scenarios that combine social and environmental factors, with attention to vulnerable populations. A realistic example is described with features of a southeastern region of the USA. The results and methodology are a rationale for the allocation of investments for economic development and system resilience, balancing among several criteria of social vulnerability and environmental justice.