ABM - Spatial Multi-Agent Simultation of Nitrogen Discharge Trading

A example of use of the multi-agent simulation framework, CORMAS (Common-pool Resources and Multi-Agents Systems), to model the potential nitrogen trading behaviour of key actors under the new regulatory  in the Lake Taupo catchment.

Nutrient discharge from intensive farming [nitrogen (N) leached] is a major cause of poor water quality of rivers and lakes in catchments. Regulators have set up many schemes in some countries to manage and reduce the flow of nutrients into water ways. These include promoting the adoption of less intensive farming systems and setting up trading schemes to buy and sell nutrient discharge credits. Waikato Regional Council has proposed a scheme to restrict N discharge from agricultural activity in the Lake Taupo catchment to improve the water quality of Lake Taupo in the central North Island region of New Zealand. Their proposal includes (a) capping of N produced by farms at current levels of N leached from farms, (b) reducing N flows into the catchment by 20% and (c) allowing the trading of N discharge allowances (NDA) between farmers in the catchment. 

This study describes the use of the multi-agent simulation framework, CORMAS (Common-pool Resources and Multi-Agents Systems), to model the behaviour of key actors (regulator, auctioneer, NDA sellers and NDA buyers) who are endeavouring to improve water quality in the Lake Taupo catchment. The regulator allocates NDA to farmers and reduces total catchment NDA through purchase of NDA, the auctioneer manages a centralised contract protocol for trading in NDA and the farmer buys or sells NDA based on a farm plan that maximises the farmer’s risk adjusted expected income (RAE).


A multi-agent simulation (MAS) can be used to describe the interaction between farmers to supply and purchase NDA within a regulatory framework, and the resulting financial, environmental and landscape impacts. In this study a MAS model is developed in the CORMAS modelling framework to illustrate trade in NDA.  

Entities included in the model are:

Spatial - Landscape (Taupo catchment).

  • Land cover.
  • LUC (land use capability class).
  • Land parcels (i.e. farm boundaries).

Social - Communicating Agents

  • Regulatory Institution – Allocates NDA to farmers and reduces total catchment NDA through purchase.
  • Auctioneer - Manages a centralised contract protocol.
  • Farmers – Base trade on individually optimised farm


This study has shown how the results of an individual farm risk model can be used to characterised NDA traders in the Taupo catchment. This information was used in a multi-agent simulation model where the key actors were farmers, the regulator and an auctioneer of NDA. The proposed allocation of NDA to farmers by regulators in a bid to improve the quality of water in Lake Taupo would result in the creation of  supply of NDA which could be traded.

There are new N mitigation strategies being developed by research organisations that are close to, or new to, the market. They include the use of feed pads that can be used to manage the spreading of nutrients onto farms and the use of nitrification inhibitors. These new technologies can be evaluated in the framework developed in this study and have the potential to significantly to redefine sellers and buyers of NDA in the catchment.

Associated Models

Agent Based Modelling (ABM)

An agent-based model (ABM) (also sometimes related to the term multi-agent system or multi-agent simulation) is a class of computational models for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) with a view to assessing their effects on the system as a whole.


 Dake CKG 2007. Modelling nitrogen discharge trading using spatial multi-agent simulation. MODSIM Conference paper 2007