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Future Landscapes

Linking Legacies to Wai

Accounting for lag times and natural concentrations of contaminants in groundwater

Duke of Edinburgh observing border dyke irrigation at Winchmore
The Duke of Edinburgh (third from left) observes border dyke irrigation at the Winchmore Research Station Irrigation Scheme. In a border dyke irrigation system, when water is diverted from the main water races into smaller ones, a temporary dam must be created at the outlet to each border, so the water spills through onto pasture. In this image the outlet behind the worker in the water has been closed with a board, the pasture on the right of it has been flattened by the previous flow of water. The worker is lifting a corner of the canvas dam to allow water to flow down to the next temporary dam. We acknowledge the permission of Archives New Zealand to publish this image: [Alexander Turnbull Library: 1/2-04226F (AAQT 6538/1)]. Archives New Zealand, The Department of Internal Affairs, Te Tari Taiwhenua. This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 New Zealand License


Challenge funding: $415,000

Research duration: January 2022 – March 2023

What Are We Doing?

The decisions farmers make today on land can take many years to be reflected in the health of water in our rivers and groundwater. In the past, this ‘lag time’ contributed to a lack of understanding of the intrinsic connection between wai and whenua.

This research will demonstrate the effects of agriculture on our freshwater over the past 170 years and will predict how quickly future land-use decisions will restore the health of degraded water. The project aims to use this knowledge to grow understanding among land stewards of the connection between whenua and wai.

This project will have a focus on groundwater. It will find out how long it takes for changes in land use or intensity to be reflected in nitrate concentrations in groundwater.

How Can The Research Be Used?

  • The lag time between land-use changes (largely intensification) and the increase in the load of nitrate in streams and rivers has been quantified as 4.5 years on average for 77 catchments that capture about 50% of Aotearoa’s agricultural activity.
  • This research will help set realistic timeframes to decrease nitrate concentrations in groundwater, and streams and rivers. If nitrate is not decreasing quickly enough, Councils will have evidence to take further action.

Community Involvement

  • Māori, government (central and local) and peak industry bodies were asked to prioritise land uses, land practices and past and future years to be examined.

Team Snapshot

Research Outputs


The implications of lag times between nitrate leaching losses and riverine loads for water quality policy

McDowell, R. W., Simpson, Z. P., Ausseil, A. G., Etheridge, Z. & Law, R.
Scientific Reports 11, 16450 (2021)

Understanding the lag time between land management and impacts on riverine nitrate–nitrogen (N) loads is critical to understand when action to mitigate nitrate–N leaching losses from the soil profile may start improving water quality. These lags occur due to leaching of nitrate–N through the subsurface (soil and groundwater). Actions to mitigate nitrate–N losses have been mandated in New Zealand policy to start showing improvements in water quality within five years. We estimated annual rates of nitrate–N leaching and annual nitrate–N loads for 77 river catchments from 1990 to 2018. Lag times between these losses and riverine loads were determined for 34 catchments but could not be determined in other catchments because they exhibited little change in nitrate–N leaching losses or loads. Lag times varied from 1 to 12 years according to factors like catchment size (Strahler stream order and altitude) and slope. For eight catchments where additional isotope and modelling data were available, the mean transit time for surface water at baseflow to pass through the catchment was on average 2.1 years less than, and never greater than, the mean lag time for nitrate–N, inferring our lag time estimates were robust. The median lag time for nitrate–N across the 34 catchments was 4.5 years, meaning that nearly half of these catchments wouldn’t exhibit decreases in nitrate–N because of practice change within the five years outlined in policy.

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We are happy to answer any questions about this research and how it can be used.

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