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Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

Decision analysis and risk models for land development affecting infrastructure systems.

Shital A Thekdi1, James H Lambert

  • 1Center for Risk Management of Engineering Systems and Department of Systems and Information Engineering, University of Virginia, Charlottesville, VA, USA.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|November 5, 2011
PubMed
Summary
This summary is machine-generated.

This study presents a layered modeling approach to manage land development risks impacting infrastructure systems. It helps prioritize solutions to protect essential services from development impacts.

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Last Updated: May 27, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

Area of Science:

  • Infrastructure Systems Engineering
  • Risk Management
  • Urban Planning

Background:

  • Complex infrastructure systems (energy, water, transportation) face increasing risks from adjacent land development.
  • Land development can degrade infrastructure performance and escalate maintenance costs.
  • A proactive, risk-informed approach is crucial to prevent unforeseen issues and costly interventions.

Purpose of the Study:

  • To develop and demonstrate a coordinated, layered modeling framework for managing land development risks to infrastructure.
  • To integrate diverse data sources and expert knowledge for comprehensive risk assessment.
  • To provide a decision framework for prioritizing remedies and mitigating development impacts.

Main Methods:

  • A five-layer modeling approach: system identification, expert elicitation, predictive modeling, investment alternative comparison, and future option analysis.
  • Focus on observable factors influencing land development volatility, including population/employment growth, land use regulations, topography, and economic conditions.
  • Integration into a strategic decision framework assessing risk, cost, and opportunity.

Main Results:

  • The developed framework effectively integrates various data types and expert insights for risk assessment.
  • The approach provides a structured method for prioritizing interventions to mitigate land development impacts.
  • Demonstrated applicability on a large-scale multimodal transportation system facing significant development pressure.

Conclusions:

  • Layered modeling offers a robust strategy for managing complex risks at the interface of land development and infrastructure.
  • This risk-informed approach enables strategic decision-making to protect infrastructure performance and optimize resource allocation.
  • The methodology is adaptable for diverse infrastructure systems and development scenarios.