Impact 2.2: Opportunities and threats to land resources are recognised and balanced to maintain or enhance the provision of ecosystem services
Key performance indicator: Regional councils and the irrigation, pastoral, horticultural and arable sectors are using knowledge of soil variability to improve the match between land-use practices and land capability.
Research concentrates on identifying opportunities for improving land and water management using best available resource data and innovative modelling and technological approaches. This work supports policy development and land management decision-making.
2010/11 Baseline situation: ‘Ecosystem services’ modelling and decision-making were not widely applied by regional councils, and soil variability was generally only recognised at the landscape scale.
|Precision irrigation tuned to soil variability at the paddock scale achieved water savings of 20–36%, without any reduction in productivity, at three demonstration farms.||Decision-makers, irrigators and developers of land on stony soils have new evidence quantifying the risk of nutrients, microbes and other contaminants leaching to groundwater.||Several regional councils are using our SedNetNZ model to identify erosion-prone areas contributing the most sediment to waterways
|Soil variability underpins the design and storage capacity of effluent management systems that comply with DairyNZ’s code of practice.||Developers of the widely-used nutrient budgeting tool OVERSEER® will benefit from new data on soil properties and soil variability provided through S-map.||ECan and now other regional councils are benefitting from powerful new automated techniques to interpret paddock use and land use change from remote sensing imagery.|
|Complex spatial land-use models predict optimal land use in two case studies, and assess impacts of irrigation scenarios on groundwater nitrogen for the Waimea Plains.||Greater Wellington Regional Council have used our ecosystem services approach to understand where various management interventions would best benefit the Ruamahanga catchment.|
|Policy and planning to stabilise erosion-prone hill country benefit from modelling of future climate effects and new understanding of the ‘non-timber’ value of tree species for erosion.|
Many areas of soft rock hill country in the North Island are prone to erosion. Sediment washed into rivers affects water quality and leads to increased flooding issues. Spatial modelling is a cost-effective way of identifying the most critical sediment-generating areas and then assessing the effectiveness of various land management options in ameliorating the problem. We refi ned an Australian sediment model, SedNet, to specifically address New Zealand’s erosion issues. SedNetNZ simulates the processes that collectively account for the majority of erosion and sediment generation in the New Zealand landscape: sheet and rill erosion, landslides, earthflows, gullies, and bank erosion.
We partnered with Horizons Regional Council to use the Manawatū River catchment as a case study to develop the model. The catchment has major erosion and sedimentation issues, and considerable long-term data already existed to complement our research data. We are continuing to work with Horizons on identifying priorities for major land management change under their $30m Sustainable Land Use Initiative (SLUI). Recent research suggests the council is on track to reduce sediment levels in the river by 40% by 2035.
We are now working with other regional councils to apply SedNetNZ to erosion-prone catchments in similar soft rock landscapes: Hawke’s Bay (Tukituki River), Waikato (Waipa River) and Wellington (Ruamahanga River). The spatial layers developed for these catchments can be used to identify the farms with the highest potential to erode, and provide the councils with not only the farms on which to focus their efforts, but also the likely reduction in sediment volumes should mitigation procedures be put in place. The councils can also use the information to encourage farmers to fence off or protect the stream banks to stop cattle access.
This research is part of the Realising Land’s Potential Portfolio, and was supported by MBIE Core funding and regional councils.
Planning for ecosystem services in the Wellington Region
We have been working with Greater Wellington Regional Council to assess the impacts of management scenarios on ecosystem services in the Ruamahanga catchment in the Wairarapa. Map outputs quantify the effects, making it easy to see and understand where various management interventions would generate the greatest benefit. The approach draws on S-map for detailed mapping of soils and their hydrological properties.
So far, we have assessed the impact of fencing to exclude cattle from waterways, best management practice for dairy effluent ponds, and dung beetles on reducing E. coli reaching waterways. Wetland enhancement and soil conservation work in the eastern hill country will be assessed next. This is the first assessment of sources of E. coli in the landscape and the impacts of various management practices. This will help decision-making and raising awareness for communities on the best farming practices to use for an effective impact on freshwater outcomes. Greater Wellington Regional Council will use these assessments as part of the Whaitua stakeholder engagement process to set water quality and quantity limits. The Whaitua Implementation Plan will develop a prioritised programme of action, with policies and rules created by local people to suit local needs.
This research was part of the Characterising Land Resources Portfolio, and was supported by MBIE Core funding.
Paddock identification using satellite imagery
Landcare Research and Environment Canterbury have been working together to acquire detailed, up-to-date and spatially explicit information on agricultural land. This is critical for many purposes such as environmental modelling of farming impacts and gathering statistics on regional land use. We have developed powerful new automated techniques to interpret remote sensing imagery to determine paddock boundaries and land use within the paddock. Using an area covering about 58,000 paddocks on the mid-Canterbury Plains as a test site, we extracted information on paddock boundaries from a time-series of high-resolution (10-m pixel size) SPOT satellite images. This is a significant achievement (and of considerable benefit to ECan) given that land use on the plains has changed significantly over the past decade or so – mostly conversion into dairy farms. This typically involves major changes to paddock layouts. Cropping farms are also dynamic, with a large variety of crops grown for different purposes, including seed, grain, vegetable and feed crops, and with several crops per year in some paddocks. Our focus has been on identifying key land uses, which may have different environmental consequences, rather than the specific crops. More recently, we have also applied our new methods in other regions, with contracts for Environment Southland and Hawke’s Bay Regional Council.
This work is part of the Characterising Land Resources Portfolio, and was supported by Environment Canterbury and MBIE Core funding.
Predicting erosion, possibility or pipe-dream?
We used existing datasets to investigate shallow landslide erosion of the soft rock hill country of the eastern North Island. This is part of a pilot study that is assessing how the ‘potential erosion’ layer in the NZLRI could be replaced with a more objective approach based on ‘erosion susceptibility’. Our new model, derived from the key attributes controlling landslide distribution (terrain, climate and geology), enables us to predict the relative susceptibility of different locations to shallow landslide erosion. This will help land resource managers with managing the inherently most susceptible parts of the landscape.
In related work for MPI, we reviewed the Erosion Susceptibility Classification (ESC) mapping that was developed to support the proposed National Environmental Standard (NES) for Plantation Forestry. The ESC mapping was originally based on the ‘potential erosion’ layer in NZLRI mapped at c.1:50,000 scale. This has inherent errors when using the data at more detailed scales for forestry planning, leading to misclassification of erosion susceptibility in some areas. The work demonstrates that a more objective and defensible approach is needed for an improved method for assessing erosion susceptibility.
This research is part of the Realising Land’s Potential Portfolio, and is supported by MBIE Core funding and MPI.