National Institute of Water and Atmospheric Research Limited Smart Ideas funded projects

Ocean temperature extremes, also known as marine heatwaves, are becoming more frequent and intense. They have caused widespread damage to marine ecosystems and businesses in the past. These negative impacts are expected to grow in the future as the ocean continues to warm, leaving less time for ecosystems and businesses to recover. Very costly numerical ensemble forecasting systems are used overseas trying to predict these temperatures extremes months in advance, enabling restoration activities and helping businesses to prepare for approaching marine heatwaves. This approach is cost prohibitive in New Zealand and therefore businesses are unprepared, as forecasts of at least 1-3 months are needed to prepare for, and implement, effective actions. Accuracy is also a scientific challenge due to the complex ocean-atmosphere interactions that control the timing and severity of these extreme events. This project aims to develop national forecasting capabilities at a fraction of the cost of classical forecasting systems, using AI with a novel approach that allows predictions for small-scale ocean currents, down to a few kilometres, months in advance. These public forecasts, covering all of New Zealand’s oceans, will allow marine businesses, iwi, and regulators to prepare for the impact of approaching marine heatwaves in their management decisions. This will enhance the competitiveness of New Zealand exports by enabling businesses to better manage their resources, set prices, and improve climate resilience.

After water, sand is the second most consumed natural resource globally. Sand is the main construction aggregate, protects our shorelines from erosion, and provides essential habitats for many aquatic ecosystems. Rivers bring sand to the coast, but human impacts can significantly reduce coastal sand by trapping sand behind dams and reducing the river’s capacity to transport sediment to the coast due to reduced flood capacity downstream. Globally, interruption of river-sand delivery is one of the main causes of increased coastal erosion. In Aotearoa-New Zealand, sand shortages are already threatening coastal habitats of nationally endangered flora and fauna, and contributing to a significant reduction in active sand dunes from their pre-human extent. In gravel-bed rivers, which characterise nearly all rivers in Aotearoa-New Zealand, sand transport occurs in a unique form near the riverbed, making it especially challenging to measure compared to other sediment sizes. Our innovative approach employs cutting-edge techniques to measure sand transport with unprecedented accuracy and resolution. These measurements will enable us to develop a new sand transport formula that incorporates previously unmeasurable factors, allowing us to create a swift and precise model for predicting sand movement from catchments to coasts. The tools developed through this research will inform critical decisions in aggregate extraction planning, flood harvesting, habitat conservation, and strategies to mitigate coastal erosion associated with sea-level rise. Managing the risks of coastal erosion through forced retreat will be extremely costly, and miscalculating the areas at risk of shoreline retreat could be financially devastating. By reducing uncertainties in prediction of sand transport, more effective adaptation strategies can be implemented, minimising the potential for significant economic consequences arising from poorly-informed planning decisions.

New Zealand is flying blind in the way we manage our valuable coastal seafloor. But plumes of sediment flowing out of rivers after storms can been seen in coastal surface waters from space. This suggests a potential for zero-cost, repeated, broad-scale, remote observing of this stressor to improve land-to-sea management efficacy. However, satellites only “see” surface waters. Linking satellite data to seafloor processes at depth and determining how storms influence sediment concentrations in the coastal zone are critical gaps that our research will address. The research will provide evidence to guide holistic land-to-sea management and deliver information on seafloor ecosystem functioning to support objectives of Marine Spatial Plans. Sediments suspended in coastal waters will limit the penetration of light to the seafloor, impacting seafloor primary productivity and the vast array of species (from microbes to mammals) that this productivity supports. A twenty-year time-series of downscaled surface water quality data for the Hauraki Gulf, including storm and non-storm periods, will be created. This will be combined with new strategic sampling of the seafloor (20 site/time combinations) using innovative Aquatic Eddy Covariance oxygen flux assessment techniques, enabling the remotely sensed surface water quality observations to be mechanistically linked to seabed primary productivity rates. A twenty-year monthly time-series of maps of seabed primary production covering an ~8000 km2 area of the Hauraki Gulf will be analysed to detect the effects of storm-loaded sediments and the efficacy of management intervention scenarios mitigating these. The international research team is partnering with Hauraki Māori Trust Board representatives, Auckland and Waikato Regional Council scientists, and leaders of the Revitalising the Gulf governmental response to the Tai Timu Tai Pari Hauraki Gulf Marine Spatial Plan.

New Zealand’s critical infrastructure is highly vulnerable to extreme weather and climate events. ‘Record-shattering’ extreme events, such as the Auckland Anniversary flooding and Cyclone Gabrielle, pose some of the greatest risks, but remain the most difficult to represent even in today’s state-of-the-art climate projections. One reason why these events are so difficult to capture in physics-based climate models is that the size of individual grid cells in the models is too coarse. Another limitation is that the ensemble size of existing climate change projections is not large enough to adequately sample very rare events. Increasing both the spatial resolution and ensemble size of physics-based climate models comes at extremely large computational cost and will remain a major bottleneck for climate projections for at least the next decade. Recent advances in Artificial Intelligence (AI) offer potential for breaking these barriers, but various scientific and technical challenges first need to be overcome. One key hurdle is ensuring AI models can link atmospheric processes with land processes—something necessary to better predict events like heatwaves and droughts, but not yet achieved. Our proposal aims to develop a novel approach to improve the linkage between atmospheric and land surface processes in one single AI model. Due to the substantially enhanced resolution and ensemble size, these climate projections will be tailored towards studying projected impacts of extreme events in unprecedented detail. The improved climate projections will be integrated into RiskScape software, quantifying exposure of vulnerable communities, buildings, and infrastructure to the worst impacts of climate change.

Many of our shallow lakes are ecologically degraded, containing murky algae-rich water (including toxic cyanobacteria) and sediments that have high organic content and oxygen demand. Combined this means little light is available for photosynthesis and submerged plants are unable to transport enough oxygen internally to maintain healthy roots, so submerged plants are lost from the lakes. Much effort has been put into reducing the external sediment and nutrients loads entering waterways from the catchment, to improve the ecological health of shallow lakes. However, alone, these reductions are likely to take many decades to return degraded lake to a healthy ecological state, if at all, because submerged native plants may never return due to the highly organic sediments stopping plant re-establishment and growth of seedlings. This project aims to identify in-lake locations where specific native submerged plants species, of defined heights, receive enough light to maintain healthy roots and survive. We will be do this using our novel method that quantifies oxygen releases from the roots of submerged plants. At NIWA’s Ruakura aquatic research facility, we will quantity how much light native submerged plants need, how much of the plant needs this amount of light, and how this varies with planting density and sediment organic content to enable these plants to maintain healthy roots. We will also quantify the additional positive feedback loops that submerged aquatic plants create by increasing light availability through increasing sediment stability, enhancing sedimentation, and reducing sediment oxygen demand. We will then use lake models to help understand how the re-introduction of submerged plants back into degraded lakes improves conditions for the expansion of these in-lake submerged plant habitable zones, creating overall improvements in lake health.

Aotearoa-NZ needs effective and affordable ways of removing carbon dioxide from the atmosphere to meet commitments to the Paris Agreement and restrict global temperature increase to below 1.5oC; however, our current national climate strategy relies on buying international carbon offsets at considerable cost. The oceans are a major sink for carbon dioxide but this uptake results in lower pH and dissolved carbonate, a process known as ocean acidification that has negative impacts on marine ecosystems. This project will investigate a novel technique to increase marine carbon dioxide uptake whilst also mitigating ocean acidification, by using clean carbonate generated by Direct Air Capture. This project will determine the risks and benefits of combining two carbon removal techniques, Ocean Alkalinity Enhancement with Direct Air Capture together as OAE-DAC, without the need for deployment. Advanced models will generate maps of the potential scale and distribution of carbon removal, and laboratory experiments will determine whether phytoplankton and taonga shellfish species would benefit from additional carbonate. This information will be combined in a Life Cycle Analysis that considers all operational carbon dioxide emissions, to determine the net carbon benefit of OAE-DAC. Project findings will inform national climate strategy and pathways for reducing dependence on overseas carbon credits whilst developing the domestic carbon removal sector. By assessing the potential to protect coastal ecosystems against ocean acidification, this project will also determine the benefits for coastal iwi, communities and economies.

Climate change is impacting our marine resources, communities and businesses. The severity of climate change impacts is highly uncertain, posing considerable challenges to our decision-makers. In this context, it is important that we properly understand how climate change has affected marine resources in the past. Only then will we be able to predict with certainty the future of these resources. 

We are developing a modelling approach to better predict fish abundances in the past, to then be able to forecast fish abundances in the future under climate change and fishing scenarios. This modelling approach considers how space and fishing pressure influence fish abundances over time. 

Our project team brings together experts in fisheries science, climate change modelling, commercial fisheries (including Māori-owned fishing companies), and resource management. Our modelling, scenarios and forecasts are guided by expert knowledge from Moana New Zealand and Te Ohu Kaimoana and renowned national and overseas scientists. Together our project team uses the models to explore climate change and fishing scenarios that are meaningful to New Zealand commercial fishing companies, and contributes towards making our fisheries climate-resilient. 

Our work provides insights into how fish abundances may change among harvest quota management areas and the locations in New Zealand where individual fishing companies operate, in response to future climate and fishing changes. Such knowledge supports strategic foresight and operational flexibility for climate-resilient fisheries. Beyond fisheries assessments and management, our work assists other efforts, such as marine spatial planning that is robust to climate change.

Any questions? Please contact NIWA Arnaud.Gruss@niwa.co.nz Te Ohu Kaimoana Kylie.Grigg@teohu.maori.nz or Fisheries New Zealand Jean.Davis@mpi.govt.nz

Flood frequencies and magnitudes are increasing with climate change. This poses a serious risk to the economy of Aotearoa-New Zealand and the safety of our citizens.

Flood risk mitigation requires accurate flow measurements, for providing public safety warnings, calibrating flood models (forecasting), developing flood protection infrastructure, improving land zoning, allocating water resources (flood harvesting) and monitoring flow trends (climate change).

However, accurate flood measurements are very challenging to make. Recent advances in flood measurement methods have focused on surface image velocimetry from fixed camera stations and drones. These methods are a significant step forward, yet they suffer from three major problems: (1) poor measurement of large floods without visible reference points; (2) the time and funding required to establish fixed camera stations and survey Ground Control Points (GCPs); and (3) channel cross-section changes during floods are not accounted for, reducing the accuracy of flood measurements.

Our smart idea is to develop next-generation flood measurement systems to address these critical shortcomings. We will:

1. Develop stereoscopic camera ‘point and shoot’ flood measurement systems without needing GCPs.
2. Develop new methods for measuring large floods (without visible reference points) using drones with RTK GPS.
3. Quantify cross-section changes during floods and associated uncertainties if depth and surface velocity measurements are not concurrent.
4. Develop aerial Ground Penetrating Radar (GPR) and drone echo sounder systems for measurement of flood cross-sections, that are concurrent with surface velocities.

Our project team includes internationally recognised experts in river remote sensing and flow measurement techniques. These next-generation measurement systems will be used by Aotearoa-New Zealand’s flood management organisations to build our resilience to floods and better prepare Aotearoa-New Zealand for the impacts of climate change."

Flooding is a global issue causing casualties and tremendous asset damages each year. Current flood forecast has focused on one or two flood drivers, which cannot capture the flooding due to compound (pluvial, coastal and riverine) events. An accurate real-time compound flood forecast system is urgently required to prepare New Zealanders for future floods due to extreme weather.

We propose a study to develop a compound flood forecast system to predict extreme flood due to heavy rainfall and storms 48 hours in advance. We will use NIWA’s high-resolution numerical weather prediction, ensembles, river flow forecast and storm tide forecast to drive the state-of-the-art flood model BG-Flood. AI techniques will be used to downscale the flood results to speed up the model while retaining high-resolution output. The forecast system will be set up in the case study area (Gisborne), which has been impacted by extreme flood events such as ex-Tropical Cyclone Gabrielle in 2023.

The proposed system will be a world-leading compound flood forecast system that is powered by a hybrid method of numerical modelling and AI. It will be more accurate and faster than traditional approaches and characterise uncertainties in flood depth and extent in real-time.

The advanced compound flood forecast system will increase local preparedness and reduce losses from flooding. The assessment of contributors to compound floods informs the decision in choosing appropriate flood mitigation measures.

People typically think of ocean waves as a surface phenomenon, encountered as waves breaking along the coast. However, beneath the ocean surface there exists a similar phenomenon - internal waves.  These can be thought of as giant underwater tsunami waves that travel along density layers (distinct vertical layers of different temperature and salinity). Just like the waves at the beach, internal waves can break, creating subsurface turbulence like the swash seen at beaches. The impact of internal wave breaking is noticeable in shelf and coastal waters where they mix cool waters up to the upper ocean, generating pockets of colder water against the backdrop of increasing marine heatwaves and a warming ocean. In doing so, they provide relief from heat stress for marine organisms and generate climate refugia against climate change. However, these internal waves also add stresses to offshore infrastructure, and we need to know where these stressors are in order to appropriately plan expansions to our blue economy. Understanding this effect will become more important for decision-makers as our present response in terms of climate adaptation is currently guided by global models which do not capture smaller scales and processes such as internal waves. This project will address this issue by mapping out the location of internal waves across the motu to identify yet-to-be-discovered marine refugia. Outcomes from this project will better enable us to target marine activities to minimise the impacts of climate change on our blue economy and ecosystems.

Most of Aotearoa-New Zealand’s coastal shellfish and invertebrate habitats have been degraded by multiple stressors from the land and in the sea. Key stressors are the 11-fold increase in sedimentation rates and disturbance from bottom-fishing methods. Oceans are also warming and acidifying. At the top of the South Island/Te Tauihu, shellfisheries have recently collapsed with collateral habitats destroyed.

We hypothesise that rehabilitation and protection of habitats will deliver orders-of-magnitude net benefit in fisheries abundance (finfish, shellfish), enhancing cultural, economic, and environmental outcomes. Importantly, lost habitats provided refugia for juvenile fish, sequestered carbon and sediment and prevented seabed erosion.

Our Smart Idea is to use an interactive model-based approach to assess and demonstrate the relative benefits (cultural, economic) of a range of rehabilitation and protection scenarios designed specifically to engage iwi and stakeholders. To effect lasting change, bold and ambitious science is required. We will reconstruct the distribution of lost habitats, use forensic sediment tracing to determine which land-uses contribute sedimentation, and attempt to estimate the fate of carbon/sediment under different habitat rehabilitation scenarios. A novel Habitat and Environmental Socio-economic module for NIWA’s Nelson Bays ‘Atlantis’ Ecosystem Model will be constructed, to enable full-wellbeing accounting of scenarios.

Our team includes nationally and internationally recognised experts in ecosystem modelling, soil source tracing, and sediment biogeochemistry, supported by scientists from The Nature Conservancy, with international links in ecosystem-based management and rehabilitation. We will engage and collaborate with Kotahitanga mō Te Taiao Alliance iwi and stakeholders to understand their priorities and values around rehabilitation of the marine environment and the scenarios of greatest interest. For example tested scenarios may include retiring forestry on steep slopes, spatially managing bottom fishing and/or protecting and rehabilitating habitats.

We will develop a state-of-the-art snowmelt forecast system to enable more accurate and confident forecasts of river flow and alpine hazards across New Zealand. Forecast outputs will provide both national-scale context and local-scale detail, along with full quantification of uncertainty in the rate, volume and timing of snowmelt. Robust snowmelt forecasts will enable end-users in hazard, energy, agriculture, and tourism domains to better respond to rain-on-snow impacts on river flows and alpine hazards.

Snowmelt forecast will be generated through physics-based ensemble snow modelling that will assimilate newly developed satellite remote sensing products to quantify initial snow cover and depth. Cutting-edge ensemble numerical weather forecast data will be used as snow model input to provide robust uncertainty estimates. Hydrometeorological and snow data from high-elevation weather stations will be used to test the system, ensuring extreme snowmelt rates observed in historical records are well simulated. Given the sparse observation network and large area of New Zealand’s alpine domain, our system is ideally placed to provide a step-change in forecasting snowmelt processes with fine detail at a national scale.

The system will be implemented in NIWA’s operational multi-hazard forecasting system, ensuring forecasts are readily available to end-users and easily ingested into river flow and flood inundation models. The project will include case study catchments where we will test the methods and benefits of integrating snowmelt forecasts with existing river flow forecasts.

The project brings together a team of specialists from NIWA and Otago University supported by international experts in snow modelling and observation. A Project Advisory Group consisting of industry, Māori and government representatives will guide the research and ensure forecast outputs enable better end-user decision-making across New Zealand.

Copper and zinc are essential metals for life, but when concentrations become too high they can be toxic to aquatic organisms. Although naturally occurring, these metals are also incorporated into products widely used in our urban landscape, such as brake pads, tyres, piping and roofing. During heavy rain, worn debris from these are washed into our waterways, resulting in metal concentrations which often exceed water quality guidelines.

Contamination of our freshwaters is increasing as urbanization, mining, agriculture, forestry and climate change effects increase. Toxicity from these metals is contributing to reduced ecosystem health, degrading urban streams with reduced biodiversity and decreased mauri.

Can our native trees come to the rescue? Natural dissolved organic matter (DOM) originating from plants can reduce the toxicity of these metals by binding with them, decreasing their bioavailability. Preliminary research has shown DOM from pōhutukawa and mānuka leaves are highly effective at mitigating copper and zinc toxicity to some aquatic organisms. These are two of natures ‘organic carbon super-producers’, but are there others?

With the objective of avoiding retrofitting urban areas with costly hard engineering to minimise metal inputs to streams, this research is seeking to increase ecosystem health protection by proactively optimising DOM in waterways — using ‘super-producers' in streamside plantings and Green Infrastructure to reduce metal toxicity.

This research will screen plant materials (for example, leaves, bark and woodchips) characterising the DOM and developing relationships with toxicity mitigation to select high affinity and high DOM producing native species. Ecosystem protection will be verified using toxicity tests with selected taonga species (for example, kōura, kākahi or īnanga), generating data for water quality guidelines and the development of guidance for optimal plant selection in riparian and Green Infrastructure applications.

With the COVID-19 pandemic came the “port congestion pandemic”, where ships were forced to wait on anchor for weeks for port calls. This highlighted concerns where intense anchorage use becomes the global norm. Shipping is a desirable lower-emissions option for transporting freight, but port congestion is predicted to increase, with seaborne trade expected to quadruple by 2050. We have little understanding of how routine anchoring practices damage the coastal and marine environment, and undermine our climate resilience. We hypothesise that anchoring practices have detrimental impacts beyond their physical footprint, with implications for broader ecosystems, economies and people who rely on the health of the shallow coastal zone.

This project will deliver a complete characterisation of the footprint of ship anchoring by measuring physical, chemical, biological, ecological changes in case study anchorage sites around Aotearoa-NZ. We will document changes compared to control conditions, biodiversity and ecosystem function to calculate thresholds for impacted environments. Case studies will identify key variables that make marine environments more vulnerable to the impacts of anchoring (for example, high proportion of muddy sediment on seabed may result in prolonged resuspension and redistribution of sediments, and higher potential for carbon release). The distribution of key vulnerabilities will be delineated within case study regions and communicated via partners to other national port and harbour authorities. We will work with industry, manawhenua and local government councils in Aotearoa-NZ, with insights and analogues from global experts to co-develop an environmental framework for planning new or expanding anchorage zones to ensure vulnerable coastal regions are conserved. We aim to redesign anchoring practices under current and future port congestion scenarios to reduce anchoring requirements and develop alternative low impact solutions for the shipping industry.

New Zealand is committed to drastically reduce its greenhouse gas emissions. This includes methane (CH4) emissions from waste and agriculture. However, our ability to accurately measure current emissions, as well as to verify emission reductions, is currently not sufficient. We will develop new technology to measure CH4 emissions from waste and agriculture with great accuracy. Our techniques will be deployed at multiple sites across New Zealand, to assess and demonstrate the performance of the new technology. This will inform operators across the waste industry, as well as livestock farmers and industry developing mitigation techniques. Our method will improve our knowledge of local CH4 emissions, for example the localisation of CH4 emission hotspots and leaks. With this knowledge, operators are enabled to make better informed mitigation decisions, and to meet their emissions reduction targets.

Our technology will improve the reporting of local CH4 emissions. For example, we will quantify the CH4 emissions for specific waste treatment plants. This will also inform national reporting practices for greenhouse gas emissions. Our instruments can be equipped with sensors for other greenhouse gases. This will enable us to expand our observation portfolio beyond this project.

Having the capability to directly measure CH4 emissions will provide certainty on our emissions. This will reduce economic risk associated with the emissions trading scheme and it will empower us to manage mitigation.

This project models the impacts of climate change on lakes, including the effects of climate change on river inflows from the catchment. The focus is on Lake Taupo and the amount of oxygen in its bottom waters. We model the climate up to the year 2100, use that to model the hydrology of the rivers flowing into Lake Taupo, and then model the response in the lake to climate change, using highly detailed 3D lake modelling. We verify the modelling for the present by comparing with observations from lake and river monitoring including the Taupo buoy. We expect that including the climate change effects on the quantity, temperature and density, oxygen content and timing of the inflows from the catchment can provide new insights missing from most research on climate change effects on lakes. We will examine the important question whether climate change, depending on CO2 emission scenarios, will cause bottom water to lose all its oxygen. Changes in vertical mixing during winter and changes in river inflows could result in such a loss of oxygen in the deep water. This would in turn trigger release of phosphorus from the sediments (its concentration in the sediments is high) and potentially lead to eutrophication. The work can provide insights into climate change effects on deep lakes in general, and development of management approaches to mitigate these impacts.

Excessive nitrate levels in our waterways is a nationwide problem. It causes environmental degradation to waterways and coastal areas from eutrophication, affecting values we hold dear (economic, cultural, environmental, health, well-being). Widespread concern over nitrate is a major contributor to broader water quality being consistently the top environmental concern for NZ since at least 2010. However, no current technology is available for widespread use in NZ. Conventional technologies to remove nitrate from wastewater are electricity-intensive, utilise non-renewable-carbon sources to feed conventional denitrifying microbes, and unintentionally generate significant GHG emissions (e.g., CO2, N2O). Municipal wastewater treatment plants (WWTPs) produce 258 kt of CO2-e annually (approximately 0.3% of national emissions) and are a key source of N2O, necessitating emissions reductions in alignment with the Zero Carbon Act.

Our proposed research will address the challenge of developing an energy-efficient, net-zero-emission process for wastewater nitrate removal, requiring minimal capital investment to incorporate into existing/future WWTPs and other water denitrification applications. This will be achieved with through a world-first combination of two types of bacteria with synergistic features: one that is able to denitrify with zero CO2 and minimal N2O across a biofilm surface, and another that can boost the denitrification efficiency by effectively creating an additional surface layer. This technology will enable wide implementation of net-zero carbon wastewater denitrification to potentially remove the majority of point-source nitrates; to improve the health of our waterways and the wellbeing of New Zealanders.

The Problem

Understanding how New Zealand’s climate will continue to change across the 21st century critically depends on sophisticated physics-based climate models. Regional Climate Models are used to enhance the spatial resolution of Global Climate Models, simulate extreme events and enhance the overall relevance for societal decision- making. However, the extreme computational expense of Regional Climate Models presents a major bottleneck for running the required simulations at very high spatial resolution.

Our Solution

To overcome this major scientific challenge, we will construct the first hybrid Regional Climate Model emulator, driven by Artificial Intelligence and informed by physics. This approach will drastically reduce compute times of Regional Climate Models, enabling the first large ensemble (30 models) of very high-resolution (2.2km) nation- wide climate projections. Not previously attempted before, our application of physics-informed AI to regional climate modelling will require significant scientific stretch and involve training petabyte-scale AI models on climate simulations. Despite this challenging goal, preliminary work by our team indicates the potential for a 1000-fold computational speedup compared to current Regional Climate Models.

The Benefits

Our research outputs have the potential to substantially improve decision-making for climate adaptation and support resilience for extreme events. The uptake of this research will also provide substantial benefits to Māori by increasing localized climate resilience and providing opportunities for more strategic investments that enable higher-value products and services.

Methane, an important greenhouse gas, is emitted by livestock as well as wetlands. Livestock industries in Aotearoa-New Zealand will soon be subject to carbon pricing for their greenhouse gas emissions under the Emissions Trading Scheme or equivalent pricing. Methane emissions from nearby wetlands could be wrongly attributed to livestock. This would lead to a competitive disadvantage on the national and international markets.

This study will pioneer the use of a chemical marker in atmospheric methane that will allow a clear distinction between methane emitted from wetlands and by livestock. Additional measurements will provide an improved understanding of how large wetland methane fluxes are in various regions of New Zealand and how they vary with time.

Our research will inform wetland management and restoration projects that enhance carbon storage and biodiversity in wetlands.

In combination, the novel marker and reliable knowledge of wetland dynamics will provide an accurate assessment of the separate livestock and wetland emissions from individual farms to the whole country. Farmers will benefit from fair greenhouse gas accounting for the profitability of their business. Emissions reductions on farms from mitigation technologies will be properly recognised, promoting the uptake and export potential for these technologies.

The study will also ensure accurate accounting of national greenhouse gas emissions, which include a major component of agricultural methane. This is a prerequisite to the fulfilment of New Zealand’s international obligations to combat climate change.

New Zealanders want clear, swimmable freshwaters that are safe for recreational and cultural activities (e.g., waka ama, mahinga kai). However, two-thirds of New Zealand rivers contain pollution above acceptable levels and are often unsuitable for recreation and cultural uses. Current advisory systems rely on historical grading or, at best, 1-7 day-old measurements at a few designated swimming sites so are inadequate in providing timely warnings of poor recreational water quality.

This project will develop ‘Wai-Spy’, a cost-effective, real-time warning system for recreational freshwater quality risks. Wai-Spy will use simple camera systems as in-situ radiometers to monitor visual clarity and microbial quality at freshwater swimming sites before people enter rivers. Wai-Spy will provide hourly estimates throughout the day of visual clarity and E.coli concentration – the two health-related variables that most strongly influence freshwater ‘swimmability’. Wai-Spy will be locally calibrated and validated in partnership with citizen scientists, including iwi/hapū at selected swimming sites using smartphone cameras alongside cultural and community-based water monitoring methods.

Successful delivery of ‘now-casts’ using Wai-Spy can potentially transform monitoring and management of freshwater swimming sites in New Zealand and internationally. Timely, accessible, location-specific warnings of swimming suitability and health risks will support safer and more rewarding freshwater recreation and cultural uses, and reduce the incidence of illnesses and associated health care costs currently arising from contact recreation when freshwater quality is poor. Partnering with councils and iwi/communities will build local capacity to monitor water quality and ensure local relevance, assisting effective communication of real-time risks and guiding appropriate management responses (e.g., signage, closures/rāhui). In turn, this will inform higher-level freshwater decision-making via iwi and council environmental management plans, promoting kaitiakitanga and strengthening participation in freshwater co-management.