Response of nitrate leaching to no-tillage is dependent on soil, climate, and management factors: A global meta-analysis.

No tillage (NT) has been proposed as a practice to reduce the adverse effects of tillage on contaminant (e.g., sediment and nutrient) losses to waterways. Nonetheless, previous reports on impacts of NT on nitrate ( NO 3 - ) leaching are inconsistent. A global meta-analysis was conducted to test the hypothesis that the response of NO 3 - leaching under NT, relative to tillage, is associated with tillage type (inversion vs non-inversion tillage), soil properties (e.g., soil organic carbon [SOC]), climate factors (i.e., water input), and management practices (e.g., NT duration and nitrogen fertilizer inputs). Overall, compared with all forms of tillage combined, NT had 4% and 14% greater area-scaled and yield-scaled NO 3 - leaching losses, respectively. The NO 3 - leaching under NT tended to be 7% greater than that of inversion tillage but comparable to non-inversion tillage. Greater NO 3 - leaching under NT, compared with inversion tillage, was most evident under short-duration NT (<5 years), where water inputs were low (<2 mm day-1 ), in medium texture and low SOC (<1%) soils, and at both higher (>200 kg ha-1 ) and lower (0-100 kg ha-1 ) rates of nitrogen addition. Of these, SOC was the most important factor affecting the risk of NO3 - leaching under NT compared with inversion tillage. Globally, on average, the greater amount of NO3 - leached under NT, compared with inversion tillage, was mainly attributed to corresponding increases in drainage. The percentage of global cropping land with lower risk of NO3 - leaching under NT, relative to inversion tillage, increased with NT duration from 3 years (31%) to 15 years (54%). This study highlighted that the benefits of NT adoption for mitigating NO 3 - leaching are most likely in long-term NT cropping systems on high-SOC soils.

Simulation of management strategies to mitigate nitrogen losses from crop rotations in Southland, New Zealand.

BACKGROUND: Nitrogen (N) fertiliser used on crops is among the main sources of water pollution. Reliable measurement of N losses from land uses in catchments is key to designing effective management strategies that minimise those losses at the same time as keeping farms profitable. In the present study, we used a management simulation tool within the Agricultural Production Systems sIMulator (APSIM) to assess the effect of fertiliser management on N leaching from croplands in the Aparima catchment in Southland, New Zealand. The assessment was based on two N-fertiliser regimes: (i) Scheduled (conventional) where, N-fertiliser rates and timing of application followed a prescribed programme, and (ii) Soil-test where, N-fertiliser rates and timing depended on daily analysis of simulated soil N levels. Four rotations (continuous wheat, pasture-wheat-grain oats, wheat-fodder beet-peas and wheat-green oats-fodder beet-peas) were used in the evaluation. RESULTS: APSIM simulated crop productivity with reasonable accuracy. Yields were 2% greater, fertiliser N input was 11% lower and leaching was 20% lower under the Soil-test compared to the Scheduled fertiliser management. These results show the potential of a Soil-test based fertiliser application to increase fertiliser-N use efficiency and reduce the risk of N loss to the Southland catchment water systems. CONCLUSION: The present study demonstrates a dynamic farm systems model can be a viable tool to generate valuable data for assessing the productivity and environmental effects of cropping systems at a catchment scale. © 2021 Society of Chemical Industry.

Combining Restricted Grazing and Nitrification Inhibitors to Reduce Nitrogen Leaching on New Zealand Dairy Farms.

Intensification of pastoral dairy systems often means more nitrogen (N) leaching. A number of mitigation strategies have been proposed to reduce or reverse this trend. The main strategies focus on reducing the urinary N load onto pastures or reducing the rate of nitrification once the urine has been deposited. Restricted grazing is an example of the former and the use of nitrification inhibitors an example of the latter. A relevant concern is the cost effectiveness of these strategies, independently and jointly. To address this concern, we employed a modeling approach to estimate N leaching with and without the use of these mitigation options from a typical grazing dairy farm in New Zealand. Three restricted grazing options were modeled with and without a nitrification inhibitor (dicyandiamide, DCD) and the results were compared with a baseline farm (no restricted grazing, no inhibitor). Applying DCD twice a year, closely following the cows after an autumn and winter grazing round, has the potential to reduce annualized and farm-scale N leaching by ∼12%, whereas restricted grazing had leaching reductions ranging from 23 to 32%, depending on the timing of restricted grazing. Combining the two strategies resulted in leaching reductions of 31 to 40%. The abatement cost per kilogram of N leaching reduction was NZ$50 with DCD, NZ$32 to 37 for restricted grazing, and NZ$40 to 46 when the two were combined. For the range analyzed, all treatments indicated similar cost per percentage unit of mitigated N leaching, demonstrating that restricted grazing and nitrification inhibitors can be effective when used concurrently.

A method to derive nitrogen transport factors for New Zealand's agricultural lands.

Risk index tools have the potential to assist farmers in making strategic decisions regarding their farm design to manage losses of nutrients. Such tools require a vulnerability framework, and these are often based on scores or rankings. These frameworks struggle to take account of interactions between elements of the physical environment. Process-based simulation models inherently take account of interactions and may be a viable alternative to score-based methods. We describe the method to populate a database of transport factors that covers the agricultural lands of New Zealand that is designed for usage as the susceptibility framework within a risk index tool. The method gives both leaching and runoff transport factors and gives values by month. The simulation model used had already been validated for simulating water and nitrogen balances and the generated spatial patterns of the transport factors was validated via expert assessment. These features allow good representation of the risks posed across a wide range of farming activities.•Use of a simulation model to quantify transport factors.•Captures the interactions between soil and weather factors in the physical environment.•Produces a country-wide database intended as a susceptibility framework for a risk index tool.

Identification and testing of early indicators for N leaching from urine patches.

Nitrogen leaching from urine patches has been identified as a major source of nitrogen loss under intensive grazing dairy farming. Leaching is notoriously variable, influenced by management, soil type, year-to-year variation in climate and timing and rate of urine depositions. To identify early indicators for the risk of N leaching from urine patches for potential usage in a precision management system, we used the simulation model APSIM (Agricultural Production Systems SIMulator) to produce an extensive N leaching dataset for the Waikato region of New Zealand. In total, nearly forty thousand simulation runs with different combinations of soil type and urine deposition times, in 33 different years, were done. The risk forecasting indicators were chosen based on their practicality: being readily measured on farm (soil water content, temperature and pasture growth) or that could be centrally supplied to farms (such as actual and forecast weather data). The thresholds of the early indicators that are used to forecast a period for high risk of N leaching were determined via classification and regression tree analysis. The most informative factors were soil temperature, pasture dry matter production, and average soil water content in the top soil over the two weeks prior to the urine N application event. Rainfall and air temperature for the two weeks following urine deposition were also important to fine-tune the predictions. The identified early indicators were then tested for their potential to predict the risk of N leaching in two typical soils from the Waikato region in New Zealand. The accuracy of the predictions varied with the number of indicators, the soil type and the risk level, and the number of correct predictions ranged from about 45 to over 90%. Further expansion and fine-tuning of the indicators and the development of a practical N risk tool based on these indicators is needed.

Data pipeline for managing field experiments.

As agricultural and environmental research projects become more complex, increasingly with multiple outcomes, the demand for technical support with experiment management and data handling has also increased. Interactive visualisation solutions are user-friendly and provide direct information to facilitate decision making with timely data interpretation. Existing off-the-shelf tools can be expensive and require a specialist to conduct the development of visualisation solutions. We used open-source software to develop a customised near real-time interactive dashboard system to support science experiment decision making. Our customisation allowed for: • Digitalised domain knowledge via open-source solutions to develop decision support systems. • Automated workflow that only executed the necessary components. • Modularised solutions for low maintenance cost and upgrades.

S-map parameters for APSIM.

Agroecosystem models have become an important tool for impact assessment studies, and their results are often used for management and policy decisions. Soil information is a key input for these models, yet site-specific soil property data are often not available, and soil databases are increasingly being used to provide input parameters. For New Zealand, the digital spatial soil information system S-map provides geospatial data on a range of soil characteristics, including estimates of soil water properties. We describe a protocol for how properties from S-map can be used as input parameters for the APSIM (Agricultural Production Systems sIMulator) framework. Finally, we investigate how changes in the physical description of soil layers, and soil organic matter pools, affect the various outputs of APSIM.•This paper presents a description of how information from S-map, a digital soil map of New Zealand, can be used for building a soil description for APSIM.•A sensitivity analysis shows the effect of soil layering and the set-up setup, size, and distribution of SOM pools on model outputs, including plant growth and N leaching.

A protocol to build soil descriptions for APSIM simulations.

Soil processes have a major impact on agroecosystems, controlling water and nutrient cycling, regulating plant growth and losses to the wider environment. Process-based agroecosystem simulation models generally encompass detailed descriptions of the soil, including a wide number of parameters that can be daunting to users with a limited soil science background. In this work we review and present an abridged description of the models used to simulate soil processes in the APSIM (Agricultural Production Systems sIMulator) framework. Such a resource is needed because this information is currently spread over multiple publications and some elements have become outdated. We list and briefly describe the parameters, and establish a protocol with guidelines, for building a soil description for APSIM. This protocol will promote consistency, enhancing the quality of the science done employing APSIM, and provide an easier pathway for new users. This compilation should also be of relevance to users of other models that require detailed soil information.•This paper presents a brief description of the models for simulating soil processes in the APSIM model.•The method stablishes guidelines to define the parameters for building a soil description for APSIM.

Understanding spatial and temporal variability of N leaching reduction by winter cover crops under climate change.

Winter cover crops are sown in between main spring crops (e.g. cash and forage crops) to provide a range of benefits, including the reduction of nitrogen (N) leaching losses to groundwater. However, the extent by which winter cover crops will remain effective under future climate change is unclear. We assess variability and uncertainty of climate change effects on the reduction of N leaching by winter oat cover crops. Field data were collected to quantify ranges of cover crop above-ground biomass (7 to 10 t DM/ha) and N uptake (70 to 180 kg N/ha) under contrasting initial soil conditions. The data were also used to evaluate the APSIM-NextGen model (R2 from 62 to 96% and RMSEr from 7 to 50%), which was then applied to simulate cover crop and fallow conditions across four key agricultural locations in New Zealand, under baseline and future climate scenarios. Cover crops reduced N leaching risks for all location/scenario combinations but with large variability in space and time (e.g. 21 to 47% of fallow) depending on the climate change scenario. For instance, end-of-century estimates for northern (warmer) locations mostly showed non-significant effects of climate change on cover crop effectiveness and N leaching. In contrast for southern (colder) locations, there was a systematic increase in N leaching risks with climate change intensity despite a concomitant, but less than proportional, increase in cover crop effectiveness (up to ~5% of baseline) due to higher winter yields and N uptake. This implies that climate change may not only modify the geography of N leaching hotspots, but also the extent by which cover crops can locally reduce pollution risks, in some cases requiring complementary adaptive measures. The patchy- and threshold-nature of leaching events indicates that fine spatio-temporal resolutions are better suited to evaluate cover crop effectiveness under climate change.

Nitrate leaching from suction cup data: Influence of method of drainage calculation and concentration interpolation.

The use of suctions cups is a common practice for estimating nitrate (NO3 -N) leaching under agricultural systems despite the various uncertainties associated with the approach. One major uncertainty is water flux, which is required for calculating NO3 -N leaching loads from measured concentrations. Another problem is the interpolation of NO3 -N concentrations between measurement days. We investigated how differences in water flux, obtained from two different models (EVACROP and APSIM), affect NO3 -N leaching loads. The effect of interpolation of NO3 -N concentrations based on days or drainage was also addressed. The models were set up according to a 2-yr field experiment with spring barley (Hordeum vulgare L. Quinch) with different levels of N fertilization rates on a loamy soil at Flakkebjerg, Denmark. Due to small differences in measured NO3 -N concentrations between sequential samplings, the method of interpolation did not significantly affect NO3 -N leaching in the two periods investigated. Although there is no standard against which leaching losses from different approaches can be tested, results highlight that the modeling of water uptake as affected by N supply influences the amount of drainage and thus calculated NO3 -N leaching. Therefore, for experiments with varying N fertilization levels, the APSIM model, which accounts for N nutrition on crop water use, is likely more accurate. For common fertilization rates, the simpler EVACROP seems appropriate. Thus, when using suction cup data for testing models or for evaluating mitigation options for nitrate leaching, the use of an appropriate model for estimating water fluxes is important.

Nitrate leaching losses during pasture renewal - Effects of treading, urine, forages and tillage.

Pasture renewal is a key component of intensive temperate grassland farming. This practice is performed to improve pasture yields, but it may increase nitrate (NO3-) leaching losses, which can impact on water quality. Farmers face many choices when renewing pasture, however, there is limited information to guide decisions to reduce leaching losses. An experiment was established to study how different management practices and grazing affect biomass production and NO3- leaching during pasture renewal on a heavy soil. Long-term pasture was either re-sown into ryegrass (Lolium perenne) in autumn (GG) or into forage rape (Brassica napus) followed by ryegrass in spring (GCG). Rape was established following ploughing or direct-drilling. Grazing was simulated in winter, whereby split plots ±urine (600 kg N ha-1) and ±treading were established. Nitrate concentrations at 1 m depth were measured with suction cups and drainage predicted using a crop model. Estimated NO3- leaching losses at 1 m depth ranged from 16 to 38 kg N ha-1, with little difference between GCG and GG. However, the risk of future leaching was much greater below GCG plots. At the end of the study, soil NO3- between 0.6 and 1 m ranged from 28 to 130 kg N ha-1 in GCG plots and 1-28 kg N ha-1 in the GG plots. Timing of leaching differed between renewal systems, reflecting the differences in plant N uptake and fallow period. Overall, there was no difference in dry matter production between the two systems. Treading resulted in greater compaction, especially in tilled plots and reduced NO3- leaching by c. 40% - this can be attributed to increased denitrification. Our study demonstrates the complex nature of management and environmental factors and their interaction during pasture renewal. We show that management practices affect the risk and timing of N leaching. Practical implications for farmers are discussed.

Lateral spread affects nitrogen leaching from urine patches.

Nitrate leaching from urine deposited by grazing animals is a critical constraint for sustainable dairy farming in New Zealand. While considerable progress has been made to understand the fate of nitrogen (N) under urine patches, little consideration has been given to the spread of urinary N beyond the wetted area. In this study, we modelled the lateral spread of nitrogen from the wetted area of a urine patch to the soil outside the patch using a combination of two process-based models (HYDRUS and APSIM). The simulations provided insights on the extent and temporal pattern for the redistribution of N in the soil following a urine deposition and enabled investigating the effect of lateral spread of urinary N on plant growth and N leaching. The APSIM simulation, using an implementation of a dispersion-diffusion function, was tested against experimental data from a field experiment conducted in spring on a well-drained soil. Depending on the geometry considered for the dispersion-diffusion function (plate or cylindrical) the area-averaged N leaching decreased by 8 and 37% compared with simulations without lateral N spread; this was due to additional N uptake from pasture on the edge area. A sensitivity analysis showed that area-averaged pasture growth was not greatly affected by the value of the dispersion factor used in the model, whereas N leaching was very sensitive. Thus, the need to account for the edge effect may depend on the objective of the simulations. The modelling results also showed that considering lateral spread of urinary N was sufficient to describe the experimental data, but plant root uptake across urine patch zones may still be relevant in other conditions. Although further work is needed for improving accuracy, the simulated and experimental results demonstrate that accounting for the edge effect is important for determining N leaching from urine-affected areas.