Crop rotation nitrogen leaching loss estimate maps


Spatial distribution of estimated mean annual nitrogen (N) leaching losses from crop rotations across New Zealand. A summary of results from APSIM simulations of three generic rotations under six different scenarios, defined by water and N fertiliser management.

The rotations were:

  • Ryegrass and silage maize;
  • Broadacre vegetables (squash, onions, beetroot, sweetcorn, beans, and oats);
  • Intensive vegetables (lettuce, cabbage, spinach, cauliflower, and oats);

Irrigation and fertiliser management setup:

  • No irrigation and fixed fertiliser schedule;
  • No irrigation and flexible fertiliser management, based on soil N status;
  • Irrigation managed to maintain a soil water deficit and fixed fertiliser schedules;
  • Irrigation managed to maintain a soil water deficit and flexible fertiliser management, based on soil N status;
  • Irrigation to fully overcome soil water deficit and fixed fertiliser schedule;
  • Irrigation to fully overcome soil water deficit and flexible fertiliser management, based on soil N status.


Date: February 2024 Version: v1

Owner: Plant & Food Research, Manaaki Whenua Landcare Research, NIWA

Contact: Plant and Food Research (Rogerio Cichota, Steve Thomas)


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Dataset attributes

Spatial extent National. Large lakes and rivers and conservation areas have been excluded
Spatial resolution Raster data developed at 25m resolution, based on simulations using 5km climate grid and soil map with a 1:50000 nominal scale
Temporal extent Annual averages from 30 years simulations, from 1980 to 2010
Temporal resolution Annual averages from simulations at daily time-step
Evaluation method (Validation) This work used the APSIM model framework, which has been developed and tested with field data from New Zealand and elsewhere (more details on and Validation for specific models include water balance, soil N processes, as well as plant growth in response to soil nutrient and environmental factors. No specific evaluation against measured data was made for this set of simulations as there are few datasets available and most of them are used to develop and test APSIM itself. Expert assessment regarding general trends for crop production, irrigation and N usage, and N losses were used during development of this work.
Evaluation result (Numeric)
Evaluation result (Categorical)
Uncertainty method
Uncertainty data format (Numeric)
Uncertainty data format (Categorical)



The maps are of Nitrogen (N) leaching loss estimates derived for a set of crop rotations simulated using the Agricultural Production Systems Simulator (APSIM) model.

Three crop rotation simulations were set up in APSIM consisting of

  1. grass-maize,
  2. broadacre vegetables, and
  3. intensive vegetables.
These were defined after consultation with industry experts.

The simulation setup included the possibility of applying irrigation and nitrogen fertiliser. Irrigation was triggered by soil moisture status, with a treatment maintaining a deficit while another filled the soil up to field capacity. Fertiliser N was applied as urea, with a treatment using a fixed schedule (timing and amounts) while another only added fertiliser if soil status was below given thresholds, depending on plant type and development stage. A time window was defined for each crop for sowing and harvesting. Sowing was triggered when both soil moisture and temperature were appropriate for the crop. Harvest happened when the crop growth reached a crop-specific development stage; crop development was primarily controlled by temperature. If the crop was not 'ready' at the end of the harvest time window a harvest was triggered regardless, with yield penalties. For areas where the growth conditions are marginal for some crops the yields were low and consequently N losses were high, particularly for the treatments with fixed N fertiliser schedule. These locations were not filtered out, it was considered that the high leaching losses mark areas not suitable for crop rotations regardless whether the values are due poor growing conditions or soil-weather combination conducive to leaching. N leached at the bottom of the soil (2 m) was accumulated over the year (from 15-Mar to 14-Mar) and then averaged across 30 years.

Daily weather data was sourced from the Virtual Climate Station Network (VCSN) provided by NIWA and soil parameters from S-map provided by Manaaki Whenua - Landcare Research. Where there is no S-map data, proxies from the Fundamental Soil Layer (FSL) map were used.

Important simulation assumptions:

  • the crop management was unimpeded by external factors such as access to machinery, holidays, weather, etc., and there were no restrictions to access water for the irrigated scenarios.
  • there were no inefficiencies on the application of water and N to the field. Water and N were applied homogeneously to the soil, which was also the case for the return of residues and dung after each defoliation (grazing). Urine returns were deposited in patches assumed to cover 5% of the area each grazing event.
  • simulations of crop growth did not account for pests and diseases, nor nutrient limitations (other than nitrogen).
  • soil and weather data were employed 'as given', with no adjustments for factors such as slope, or high water table. Please note caveats below.


Fitness for purpose / limitations

This table indicates whether the dataset is suitable for different types of questions at different scales.

Note: Users should carefully consider their purpose as this dataset may not be suitable.

Operational Absolute Relative Screening/scoping
Block/farm No No No Maybe
Multi-farms(5+) No No Maybe Yes
Catchment No Maybe Yes Yes
National/regional No Maybe Yes Yes
Caveat(s) The maps show the general variation pattern for N leaching losses from a set of crop rotations across New Zealand. They aim to provide good indication of the effects of climate and soils of N leaching losses at catchment, regional and national scales.
Management uncertainty: The simultations are produced using idealised management. Although the timing of management action like sowing and harvest were allowed to vary and adapt to local conditions, the results for areas with climate more dissimilar to NZ 'average' (e.g. Northland and Central Otago) should be considered as having greater uncertainty. Only areas with Land Use Capability (LUC) of Class 4 and lower were considered.
Spatial uncertainty. The underlying data for soil and climate is coarse, this implies that N leaching loss estimates for smaller areas may be less reliable than for larger areas. The simulation of crop growth assumed no soil limitations other than water and nitrogen and also excluded pests and diseases. It was also assumed that there were no restrictions for management (e.g. equipment availability) or to access resources (e.g. water for irrigation).

Data and Resources