EMPRESA AUXILIAR

At the Carterton LTS, it was observed (Chapter 3) that the NO3-N concentration in the groundwater under the treatment receiving the medium rate of effluent application exceeded the MPL of 11.3 mg/L during June and reached a concentration of 16.6 mg/L. Managers at the site would therefore be interested to know whether changing effluent application strategies immediately prior to and during the “problem” month of June could reduce both the concentration of NO3-N in the leachate, and also the total amount of NO3-N leached. The LEACHN model was used to carry out this scenario analysis.

The first scenario modelled was the original effluent application strategy of 45 mm per week. In the second scenario, this application rate was reduced to 30 mm per week during April and May (a total of 9 effluent applications). The third scenario was similar to the second scenario except that there was an additional reduction in effluent application to 25 mm per week in June (a total of 5 applications).

Scenarios 2 and 3 had less effluent and effluent N applied than scenario 1 (Table 6.5). Not surprisingly therefore, the LEACHN model predicted that both the quantity of drainage and the amount of leached N would also be less in scenarios 2 and 3 than in scenario 1. However, while the predicted reduction in drainage was very similar to the reduction in effluent added, the predicted reduction in N leached in scenarios 2 and 3 was less than the reduction in effluent N applied. This is because much of N leached during the winter months originates from effluent N applied several months earlier. Therefore, any reduction in N leached, as a consequence of reducing effluent applications, results mainly from the reduction in drainage volume rather than a reduced concentration of NO3-N in the drainage water. Indeed, the predicted average NO3-N concentration in the drainage water over the late autumn and winter months is predicted to increase as the volume of effluent applied is decreased (Table 6.5).

Table 6.5: Effluent and effluent N applied in three scenarios, and the resulting predicted drainage, N leached and average N concentration over the whole simulation period (1 December – 18 August) and from 1 April – 18 August.

Scenarios Effluent Application (mm) Effluent N Application (kg/ha) Drainage (mm) Drainage (1 Apr.- 18 Aug.) (mm) N leached (kg/ha) N leached (1 Apr.–18 Aug.) (kg/ha) Average N conc. (1 Apr.–18 Aug.) (mg/L) 1 1710 195 1190 1060 427 353 33.3 2 1575 179 1050 940 418 344 36.6 3 1475 168 940 830 404 330 39.8

Whether this increased NO3-N concentration in the drainage water has a greater impact on the resulting groundwater NO3-N concentration than the overall reduction in the weight of NO3-N leached will depend on the extent to which the groundwater is sourced from areas other than the LTS. However it is apparent that the LEACHN model provides a valuable tool with which the likely impact of management decisions at a LTS can be assessed.

6.4 Conclusions

The LEACHN model has been used with field data to simulate NO3-N leaching at a land treatment site in Carterton District. Based on the calibration process, simulation results, and sensitivity analysis the following conclusions can be drawn:

Comparison of the model against the experimental data from the treatments confirmed that by using measured values for some of the model parameters and varying others within the ranges normally found in the literature, the predicted seasonal and between-treatment pattern of NO3-N concentrations in the soil solution were similar to those observed in the measured soil solution concentrations. However the LEACHN model consistently predicted higher concentrations of NO3-N in the soil solution than were measured. The model was not very sensitive to changes in most of the parameters to do with transformations of inorganic N. But the model was quite sensitive to the values used for bulk density, AEV (a), BCAM (b), N mineralisation rate, base temperature and the Q10 factor. The apparent sensitivity of the model to large (30%) changes in bulk density is not of great concern because any errors in the measurement of bulk density are likely to be much smaller than this. Of real concern however is the sensitivity of the model to the value used for the N mineralisation rate constant. The correct value of this parameter is very difficult to determine and the use of the default value for this parameter in the model is thought to perhaps be the reason for the systematic over-estimation of the NO3-N concentrations by the model. The model predicted that the cumulative drainage would increase as effluent application rate increased, and would also be higher from the pasture plots than the tree plots. Although the weight of NO3-N leached over the

simulation period was predicted to increase with increasing effluent application rate, the concentrations of NO3-N in the leachate were predicted to be much lower in the treatments receiving the high rates of effluent application. Similarly, the NO3-N concentrations in the leachate from the pasture plots were predicted to be lower than the NO3-N concentrations in the leachate from the tree plots.

Evaluation of two possible alternative application strategies to reduce the impact of effluent application on groundwater NO3-N concentrations in winter demonstrated the usefulness of the LEACHN model in such scenario analysis. The simulations demonstrated that although the high NO3-N concentrations in groundwater occurred in winter, simply modifying effluent application rates during late autumn and winter would be unlikely to have a great beneficial effect.

CHAPTER 7