Distributional Assumptions in Chance Constrained Programming Models of Stochastic Water Pollution

Abstract

In the water management literature both the normal and log-normal distribution are commonly used to model stochastic water pollution. The normality assumption is usually motivated by the central limit theorem, while the log-normality assumption is often motivated by the need to avoid the possibility of negative pollution loads. We utilize the truncated normal distribution as an alternative to these distributions. Using probabilistic constraints in a cost-minimization model for the Baltic Sea, we show that the distribution assumption bias is between 1% and 60%. Simulations show that a greater difference is to be expected for data with a higher degree of truncation. Using the normal distribution instead of the truncated normal distribution leads to an underestimation of the true cost. On the contrary, the difference in cost when using the normal versus the log-normal can be positive as well as negative.

Keywords

Cost effectiveness; Water pollution; Chance-constrained programming; Log-normal distribution; Truncated normal distribution

Published in

Environmental Modeling and Assessment
2009, volume: 15, number: 4, pages: 1-9
Publisher: Springer

SLU Authors

• Elofsson, Katarina

  • Department of Economics, Swedish University of Agricultural Sciences
    

Global goals (SDG)

SDG6 Clean water and sanitation
SDG14 Life below water

UKÄ Subject classification

Fish and Aquacultural Science
Environmental Sciences and Nature Conservation

Publication identifier

• DOI: https://doi.org/10.1007/s10666-009-9205-7

Permanent link to this page (URI)

https://res.slu.se/id/publ/28972