New tool to predict the effects of changing land use

New tool to predict the effects of changing land use
An example of the use of the decision support tool: predicted average annual nitrogen yield (kilograms per hectare per year) across NZ.
NIWA is leading the development of a GIS decision support tool which will predict the effects of changing land use, not only on water quality, but also on human factors such as employment and farm incomes.
Rapid changes in land use can significantly degrade water quality unless they are managed carefully.

New tool to predict the effects of changing land use

An example of the use of the decision support tool: predicted average annual nitrogen yield (kilograms per hectare per year) across NZ.

NIWA is leading the development of a GIS decision support tool which will predict the effects of changing land use, not only on water quality, but also on human factors such as employment and farm incomes.

Rapid changes in land use can significantly degrade water quality unless they are managed carefully. Strict land use controls can prevent environmental damage, but may also cause social and economic hardship. Planners need tools which take all these effects into account.

The Ministry of Agriculture and Forestry (MAF), in association with the Ministry for the Environment and several regional councils, has engaged NIWA and five subcontractors (Lincoln Ventures, Harris Consulting, AgResearch, HortResearch, Landcare Research) in the first stage of the 3-year project.

‘This project addresses a key element of the Government’s Water Programme of Action. Predicting the impact of land use changes is essential to achieving the programme’s main goal of adequate, clean freshwater for all’, says Gerald Rys of MAF.

The decision support tool is intended for use in local and regional government. It can be used to assess planning options, such as whether it is necessary to limit particular activities in some catchments, or to change the balance of land use types to protect surface and groundwater quality. Users will be able to investigate such issues at various levels of detail; for example, whether a national or regional problem is evident in a small catchment or even on a particular farm.