As New Zealand joins with other countries to achieve net zero greenhouse gas emissions by later this century, it will come under increasing pressure from changing economic opportunities and global consumer preferences, the emergence of potentially disruptive new technologies, natural resource constraints, and evolving social and political drivers. New Zealand faces the challenge of developing its economy in ways that will not only be resilient to those future pressures, but also sustain the well-being of both urban and rural communities as well as our natural environment.
High-quality modelling tools and data are essential for making robust decisions on New Zealand’s transition to a low-emission economy in a changing and uncertain world. Drawing from a stocktake of modelling capability and needs in New Zealand developed in collaboration with a broad range of experts, we have identified the need – and opportunity – to develop an integrated framework for climate change mitigation modelling in New Zealand.
Motu’s land-use change simulation model, Land Use in Rural New Zealand (LURNZ), is a computer model that simulates land-use changes at a fine spatial scale (500m X 500m) over New Zealand. The model produces dynamic paths of rural land-use change, and maps of annual rural land use change across New Zealand.
The purpose of LURNZ is to empirically investigate the potential impacts of policies which may alter land-use decisions. When combined with additional components relating to specific issues (for example, LURNZ-climate modules which look at the affects of various emissions trading policies), LURNZ is able to compare environmental policies related to land use that depend on science and that affect the environment in scientifically measurable ways.
An overview of LURNZ, including its applications and key inputs and outputs, can be found here.
We have used the LURNZ model to investigate the potential impacts of climate change, climate change policies and to investigate the relationship between land use and water quality, among other things.
Event: AARES Conference 2016