The Land Allocation and Management (LAM) model is an optimisation modelling approach that explores the economic impacts that various changes to land use policy surrounding water quality. Its aim is to optimise land use in such a way that maximises profit within the proposed land use policy.
The Land Allocation and Management (LAM) model is an optimisation model. It employs an iterative search process to identify how different management activities must change from their current level to minimise the cost incurred by a change in the management environment, such a might occur with the introduction of an N limit. The LAM model utilises a special type of optimisation model, involving a method known as mathematical programming.
This optimisation model approach focuses on alternative steady-state or equilibrium outcomes (single year). It does not study the transition pathways between the current state and where alternative policy outcomes are predicted to lead. The model aims to identify how land management must change from its current level (baseline) to satisfy alternative environmental targets. This equilibrium approach is consistent with standard practice regarding the economic evaluation of alternative environmental policy instruments.
This framework and modelling approach is particularly valuable for estimating the cost of reaching alternative environmental targets.
For modelling a catchment is divided into a high number of diverse spatial zones in the model, each varying by slope, rainfall, and soil type. There is further partitioned into different types of representative farms, based on the typical systems observed in each spatial zone. Within each zone, the model can select from several management strategies, each with its own level of nitrogen loss, profit, and production. The model selects the most-profitable combination of these choices across the catchment, when optimised for a given scenario. The intention is to gain insight into how an average producer in a given rainfall, slope, soil, and land-use partition would profitably respond to the regulatory reality simulated in the model.
This modelling framework is valuable due to its flexibility, straightforward calibration, use of a consistent and defensible objective to select between alternative outcomes, and capacity to efficiently describe trading activity in a market for nutrient entitlements (Doole et al., 2011; Doole, 2015)
Key benefits associated with the application of the LAM framework are (Doole, 2015):
|State of Development||Unknown|
|Outcome Areas||Economic, Environmental|
|Intended End Users||
|Steady State or Dynamic||Steady State|
|Level of Integration||Economic, Environmental|
|Open/Closed Source||Closed Source|
|Operating Systems||MS Windows|
|Ease of Use||Please Select|
|Use in Policy Process||Plan (Policy Formulation)|
|Analytical Techniques||Computer General Equilibrium|
|Keywords||Land use, optimisation, environmental targets, allocation|
Graeme J. Doole, T. Ramilan, David J. Pannell,(2011): Framework for evaluating management interventions for water-quality improvement across multiple agents, Environmental Modelling & Software, Volume 26, Issue 7,Pages 860-872.
Graeme J. Doole (2015): A flexible framework for environmental policy assessment at the catchment level, Computers and Electronics in Agriculture, Volume 114,Pages 221-230.
In response to the National Policy Statement (NPS) for Freshwater Management 2011 this case study was commissioned to assess the possible economic impacts of various proposed policies that were focused on the improvement of water quality nationally using the upper Waikato River as an example.
Graeme Doole, Gemma Moleta and Sandra Barns. (2017): Economic analysis of the re-allocation of nutrient entitlements in the Lake Rotorua catchment. Bay of Plenty Regional Council.