Journal of Forest Economics > Vol 36 > Issue

A Theoretical Modeling Framework to Support Investment Decisions in Green and Grey Infrastructure under Risk and Uncertainty

Zehua Pan, University of Waterloo, Canada, z64pan@uwaterloo.ca , Roy Brouwer, University of Waterloo, Canada
 
Suggested Citation
Zehua Pan and Roy Brouwer (2021), "A Theoretical Modeling Framework to Support Investment Decisions in Green and Grey Infrastructure under Risk and Uncertainty", Journal of Forest Economics: Vol. 36: No. . http://dx.doi.org/10.1561/112.00000536

Forthcoming: 30 Sep 2021
© 2021 Z. Pan and R. Brouwer
 
Subjects
 
Keywords
Green InfrastructureDrinking Water SafetyOptimal ControlForest ManagementWildfire RiskClimate Change
 

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In this article:
1. Introduction 
2. Baseline Model 
3. Dynamic Model 
4. The Impact of Wildfires 
5. The Impact of Long-term Climate Change Global warming will increase the probability of extreme weather 
6. Simulation Results 
7. Conclusions 
Appendix 
References 

Abstract

Green infrastructure for source water protection in the form of forest protection and afforestation is gaining interest worldwide. It is considered more sustainable in the long-term than traditional engineering-based approaches. This paper presents a theoretical model to support investment decisions in green and grey infrastructure to deliver safe drinking water. We first develop a static optimal control model accounting for the uncertainties surrounding green infrastructure. This model is then extended to factor in key characteristics surrounding investment decisions aimed at optimizing the stock of green and grey infrastructure. We first include dynamic forest growth, followed by the risk of wildfires and finally the potential offsetting effect of carbon sequestration on long-term climate change and the reduced risk of wildfires. We provide a numerical example to analyze the performance of the different model specifications, interpret their outcomes and draw conclusions to guide future investment decisions in green and grey infrastructure.

DOI:10.1561/112.00000536