Land Allocation and Management Catchment Framework (LAM)

Purpose

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.

Description

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):

1. its flexible structure allows its broad adaptation to diverse circumstances (for example, the broadly divergent allocation scenarios studied herein);
2. the calibration of the model is done in a straightforward way, to improve clarity and interpretation of model output (see below for further information);
3. the simplicity of the model structure makes it easier to employ in interdisciplinary modelling and participatory work;
4. the complexity of the model can be altered depending on the quality and quantity of resources available;
5. the model can be efficiently coded in popular nonlinear-optimisation software, such as the General Algebraic Modelling System (GAMS) that allows matrix generation; and
6. the use of optimisation allows the use of a consistent and structured objective to select between multiple alternative outcomes within a complex decision problem, encompassing multiple decision makers and complexities regarding diversity in relative profit.

State of Development	Unknown

Scope

Outcome Areas	Economic, Environmental
Management Domains	Land
Intended End Users	Researcher
Steady State or Dynamic	Steady State
Level of Integration	Economic, Environmental

Input & Output Data

Accessibility

Open/Closed Source	Closed Source
Licence Type	Unknown

User Information

Operating Systems	MS Windows
User Interface	Unknown
Ease of Use	Please Select
Use in Policy Process	Plan (Policy Formulation)

Technical Considerations

Analytical Techniques	Computer General Equilibrium
Keywords	Land use, optimisation, environmental targets, allocation
Key References	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.

Associated Case Studies