A group of technical experts has produced computer models of the land use and management changes potentially required to achieve water quality targets for the Waikato and Waipa rivers, and their tributaries.
The models also look at the possible economic impacts of implementing changes, such as switching from farming to forestry or less intensive farming.
The models indicate “very large” changes to land management practices and land use will be needed to meet the legally binding Crown-iwiVision and Strategy for the two rivers, which aims to have them safe to swim in and take food from along their entire length, said NIWA’s Dr Bryce Cooper, the chair of a Technical Leaders Group (TLG).
Four broad scenarios were modelled:
- having the rivers OK for swimming, taking food and healthy biodiversity
- no further water quality decline and improvements in some areas
- a general improvement in water quality for swimming, taking food and healthy biodiversity
- no further degradation.
“The team which has produced the models stresses the actions needed to achieve the improvements in water quality are expected to be implemented over time,” said Dr Cooper.
“The team also stresses the models are a first foundation and just one of the inputs that will be used for plan development purposes. They are not suggested outcomes. It’s expected the next run of scenarios modelled will result in revised figures.”
Improving the quality of the rivers is very complex requiring a robust process where key stakeholders can work out solutions based on solid technical information.
The modelling has been carried out as part of the Healthy Rivers: Plan for Change/Wai Ora: He Rautaki Whakapaipai project, which involves the regional council and river iwi working with stakeholders to develop changes to the regional plan to protect and restore the rivers. The aim of a plan change will be to reduce, over time, sediment, bacteria, nitrogen and phosphorus from entering water bodies (including groundwater). The TLG provides expert advice to this process.
The project’s Collaborative Stakeholder Group (CSG) – which includes representatives from the likes of farming, industry, iwi and local government – will use the models to help develop a recommended plan change.
“The CSG will naturally be taking the economic impact, as well as community and social impacts, of any measures it will propose into account in its deliberations,” said the group’s independent chair Bill Wasley.
“We will use the models as we develop a recommended plan change, which is due to be put before the Waikato Regional Council and river iwi partners next year.
“We want the public to understand the sorts of trade-offs involved in protecting water quality as the plan change process engages with the community in the months ahead about the best way forward,” Mr Wasley said.
He added the CSG is aware of the modelling’s limitations and is using its results for the purpose for which it’s been designed. The model projects total costs, uses an average year and average values, and its sophistication provides results to a subcatchment level. The CSG are having ongoing discussions and are testing the model more through the running of further scenarios.
The TLG’s model suggested the following percentages of land use types in the two rivers’ catchments could be converted to different uses under the various scenarios:
| Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 | |
| Dairy to sheep and beef | 5 | 5 | 5 | 3 |
| Dairy to forestry | 2 | 2 | 2 | 3 |
| Sheep and beef to forestry | 3 | 3 | 3 | 1 |
|
Horticulture to sheep and beef |
2 | 2 | 1 | 2 |
The predicted percentage changes in production for the various sectors modelled were as follows:
| Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 | |
| Dairy | -22 | -10 | -10 | -7 |
| Sheep and beef | -4 | 2 | 1 | 3 |
| Horticulture | -43 | -2 | -10 | -4 |
| Timber | 11 | 11 | 11 | 7 |
The modelled percentage impacts on the various sectors’ profits were as follows:
| Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 | |
| Dairy | -27 | -18 | -16 | -6 |
| Drystock | -14 | 1 | 1 | 4 |
| Horticulture | -153 | 0 | -30 | 2 |
| Forestry | 10 | 10 | 11 | 7 |
The modelled impacts on the number of employees and proprietors were:
|
Change in employment in Waikato region (% change of MECs) (MECs includes employees and proprietors of businesses) |
||||
| Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 | |
| Sheep, beef and grain | 0 | 0 | 0 | 0 |
| Dairy farming | -11 | -6 | -6 | -4 |
| Forestry | 5 | 5 | 5 | 3 |
| Other primary | -6 | 0 | -1 | -1 |
| Agriculture and forestry support | -3 | 0 | -1 | -1 |
| Meat and meat product manufacturing | -6 | -1 | -1 | 0 |
| Dairy product manufacturing | -10 | -4 | -4 | -3 |
| Wood and paper manufacturing | 2 | 2 | 2 | 2 |
| Other manufacturing | 0 | 0 | 0 | 0 |
| Utilities | 0 | 1 | 0 | 0 |
| Construction | 0 | 0 | 1 | 0 |
| Wholesale and retail trade | -1 | -1 | -1 | 0 |
| Transport | -1 | 0 | 0 | 0 |
| Professional/administrative services | 0 | 1 | 0 | 0 |
| Local and central government | -2 | -1 | -1 | 0 |
| Other services | -1 | -1 | -1 | 0 |
| Total loss relative to baseline | -2 | -1 | -1 | -1 |
The present value of the total regional-scale costs ($m) were as follows:
| Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 | |
| Sheep, beef and grain | -1200 | -750 | -775 | 25 |
| Dairy farming | -3313 | -2175 | -2050 | -788 |
| Forestry | 113 | 113 | 113 | 75 |
| Other primary | -525 | 38 | -63 | -25 |
| Agriculture and forestry support | -100 | -13 | -25 | -38 |
| Meat and meat product manufacturing | -388 | -63 | -63 | -25 |
| Dairy product manufacturing | -1025 | -475 | -450 | -325 |
| Wood and paper manufacturing | 125 | 125 | 138 | 88 |
| Other manufacturing | -50 | -13 | 0 | -13 |
| Utilities | 0 | 63 | -13 | -25 |
| Construction | 13 | 13 | 100 | 13 |
| Wholesale and retail trade | -188 | -100 | -88 | -25 |
| Transport | -75 | -25 | -25 | -13 |
| Professional/administrative services | 63 | 125 | 38 | -13 |
| Local and central government | -63 | -38 | -38 | 0 |
| Other services | -1175 | -700 | -688 | -125 |
| Total loss relative to baseline | -7788 | -3875 | -3888 | -1213 |
| % change in regional economy | -3% | -2% | -2% | -1% |