Nitrogen losses from land

Water quality data are collected from 100 sites on rivers and streams throughout the region. 

Waikato Regional Council collects information on the size and location of dairy cow herds and puts this information into a Farm Dairy Effluent Database. We identified the catchment upstream of each 100 river sites. We then used the average dairy cow stocking rate in each catchment from the database to estimate the nitrogen load from the land in that catchment.

Monitoring sites

In 1997 the 100 catchments contained a total of 2,360 dairy herds, comprising a total of about 780,000 cows. The combined area of the catchments is about 13,500 km², or about 57 percent of the combined land area of the region.

The river catchments are grouped into seven zones.

Table 1: Water quality monitoring zones

Monitoring frequency

The ‘Farm Dairy Effluent Database’ is updated each year. This indicator was developed using the 1997 results.

Monitoring history

The Farm Dairy Effluent Database started in 1993. Its coverage has become increasingly comprehensive since then.

Measurement technique

Waikato Regional Council contractors visit each farm in the database and record the herd size (plus other information).

We calculated a relationship between nitrogen losses and dairy cow stocking rate using information from eight moderate to large Waikato region catchments (Vant, 1999) and from the smaller Toenepi catchment (Wilcock et al., 1999). The relationship was calculated as: Nitrogen load (kg/ha/y) = 10.28 x dairy cow stocking rate (cows/ha) + 2.241

The graph shows strong association between nitrogen load and cow stocking rates. The relationship was highly significant (correlation coefficient = 0.93, p <0.1 percent).

The strong relationship between stocking rate and nitrogen yield suggests that the intensity of livestock farming in a catchment is a key factor determining how much nitrogen will be lost to downstream surface waters. The relationship provides a simple means of estimating the likely increase in the mass flow of nitrogen which would follow an intensification of livestock farming.

Three categories of nitrogen load from non-point sources were identified: low, moderate and high.

For each of the 100 catchments, we found the total number of dairy cows present from the ‘Farm Dairy Effluent Database’. Dividing this number by the catchment area gave the average stocking rate for the catchment. This average stocking rate for the catchment then fell into one of the three categories.

For each zone, we calculated an area-weighted average proportion of the total number of catchments which fell into either the low, moderate or high categories. The average proportions of study catchments with low, moderate and high (estimated) nitrogen loads for each zone were then collated and compared.

We used area-weighting because the areas of the study catchments are very different, so that a simple average would have produced a biased result. Area-weighting involves assigning a factor to each result that reflects its contribution to the combined area of the study catchments for each zone.

Nitrogen loads are generally low in catchments in the less developed, upland areas of the Region such as the area around Lake Taupo. In the more developed, lowland parts of the Region, however, nitrogen loads are often moderate to high. Intensive agriculture - both dairy farming and cropping - is a major source of elevated nitrogen loads to waterbodies in our Region.

Guidelines and standards

Table 2: Criteria used to assess and estimate nitrogen loads from catchments.

• The aggregation of the results within each zone to produce a ‘zone average’ obscures any differences between the individual catchments within each zone.
• The study catchments do not encompass the entire area in each of the zones. This means the results may not be fully representative of the results for each of the zones as a whole.

• The process for estimating non-point source nitrogen loads ignores the effects of non-point sources other than dairy farming. In areas where intensive cropping is carried out this may result in a slightly biased result. For example, cropping is an important activity in the Whakapipi catchment (Franklin District), but this catchment makes up less than two percent of the study catchments in the ‘lowland tributaries of the Waikato River’ zone.

• The estimation technique also ignores other processes that may affect the load of nitrogen from the land (for example, differing rates of denitrification in different soil types).

The graph below shows the percent of river catchments in different parts of the region, which have ‘low’, ‘moderate’, or ‘high’ estimated levels of nitrogen loading.