Market mechanisms to allow trading of impervious cover (2013)
Type of ContentTheses / Dissertations
Thesis DisciplineManagement Science
Degree NameDoctor of Philosophy
PublisherUniversity of Canterbury. Management
AuthorsPinto, Antonioshow all
Problems with storm water runoff are becoming more frequent, and the main cause is the increase of impervious cover (IC). The imperviousness increases stream peak flows, changes peak times, and so changes the flood distribution. Several policies are used to manage flows and flooding; however most have been reported to be inefficient because land owners do not have correct exposure to price incentives and risk. The main contributions of this thesis are an investigation into market mechanisms to price and allocate impervious cover allowances, while managing flood distribution. The market mechanisms are based on the electricity and gas markets which use linear programming formulations. This thesis develops three net pool market mechanisms: Det_MarketIC is a capped and deterministic market for IC, and Sto_MarketIC and Sto_MarketIC_Risk are stochastic market models with flood component penalties and risk positions representing the desired risk from the community respectively. Additionally, a gross pool market was extended under rainfall uncertainty, Gross_MarketIC. The market design is an auction system with operational constraints and bids for IC allowances from participants. The system relates physical routed flows at nodal or control points to these bids. The models clear the market by creating a demand (supply) curve for increments (reductions) in flows at specific places, and accounts for marginal changes in the expected flood damage and flood damage components. The market formulations estimate efficient allocations and prices. Decomposed prices from the market models are shown based on duality, as applied in electricity markets. The dual prices show spatial and temporal effects of flows, which impact at flooding areas. With Sto_MarketIC and Gross_MarketIC, prices account for changes in flood distribution. With Sto_MarketIC_Risk, prices also account for the risk as CVaR in flooding areas. Thus, prices increase as binding risk conditions are tightened. Finally, the net pool models are illustrated using hydrological and hydraulic simulators based on a small catchment located in Canterbury, New Zealand. Allocations and prices varied with the different models. Participants would face increasing prices in their IC allowances due to increments in flood damage.