Cost Benefit and Economic Impact Analysis of the Horizons One Plan. A report prepared for DairyNZ and Horizons Regional Council

Transcription

1 Cost Benefit and Economic Impact Analysis of the Horizons One Plan A report prepared for DairyNZ and Horizons Regional Council 31 October 2013

2 Prepared by: Brian Bell, Director Barry Brook, Associate Nimmo-Bell & Company Ltd Garry McDonald Doug Fairgray Nicky Smith Market Economics Limited Acknowledgements: Thanks to Rick Pridmore and Matt Newman, DairyNZ, who provided overall guidance for the study the 14 anonymous farmers who made their production and financial information available for the representative farms the farmers who we surveyed for their views on the One Plan the Tararua business group who provided us background on concerns around the One Plan Horizons Jon Roygard and Maree Clark for scientific information on the One Plan Barrie Ridler and Roy McCallum of GSL who undertook the linear programming analysis of farm production and financial outcomes under various N leaching assumptions for Scenarios 2 and 3 Alfredo Adler who undertook the Farmax analysis for Scenario 3 (within system changes) members of the collaborative working group who helped us develop the scenarios and allocate the proportionate areas to the representative farms based on rainfall, farm system, soil type and irrigation (or not): Horizons Nic Peet, Peter Taylor, Clare Barton, Derek Ryan DairyNZ Matt Newman, Sam Howard, Kevin Argyle, Logan Bowler. Cover photo: Source Manawatu Gorge Walk Disclaimer While all due care has been taken to ensure the accuracy of information in this report no responsibility or liability is accepted for any errors or omissions of fact or opinion, or for any loss or damage resulting from reliance on, or the use of, the information it contains. Nimmo-Bell and Market Economics have relied upon information provided to them, and assumed without independent verification that the information is accurate and complete. This report is not intended for general circulation or publication, and may not be relied upon by any party, other than the parties to whom it is addressed, without Nimmo-Bell s express written approval. The report has been prepared for the specific purpose stated, and any party that relies on it for any other purpose, without Nimmo- Bell s express written approval, does so at its own risk. ii

3 Table of Contents 1. Executive Summary Objective of the Study One Plan Objective Implementation Method Regional Overview One Plan Trends in water quality Modelling N losses from different policy approaches Setting regulatory targets Changes to in-stream SIN loads under different policy scenarios Approach and Scope of Economic Analysis Constraints and limitations Representative farms Scenarios modelled Direct Impacts Cost Benefit Analysis Methodology Results of CBA Indirect and Induced Impacts Economic Impact Analysis (EIA) Method Limitations Results References Appendix 1: Resource Management Act Appendix 2: Cost Benefit Analysis: Cashflows of Direct Benefits and Costs Appendix 3: Calculation of Total Catchment, Regional and National Economic Impacts A.1 Method overview Appendix iii

4 Tables Table 1: Target catchments (water management sub-zones) and dates when the rules come into force... 6 Table 2: Land use capability One Plan maximum nitrogen leaching values (kg N/ha/yr)... 6 Table 3: Comparison of N leaching under Overseer 5.4 and Table 4: Land use capability One Plan maximum nitrogen leaching/run-off values (kg N/ha/yr) Table 5: Hectares in dairy farming by catchment Table 6: Target water management sub-zones: areas, number of farms and current N losses (area in Table 13.1, 2008) Table 7: Changes in N loss rates (kg N/ha/yr) under different policies, and different % expansion of dairy farming. Attenuation factor Table 8: Tararua: areas attributed to each representative farm (hectares) Table 9: West Coast: areas attributed to each representative farm (hectares) Table 10: Adoption rates for Scenario 2 System Change Table 11: Adoption rate for Scenario 1 Limits Table 12: Summary of results for N Leaching and farm profitability by target zone and regionally (annual at full adoption) Table 13: Scenario present values (MS $6.70/kg) Table 14: Scenario present values (MS $8.12/kg) Table 15: Cumulative net economic impacts, Table 16: Net present value of net economic impacts, Table 17: Net value added impacts, Table 18: Net employment impacts, Table 19: Spatial distribution of employment impacts: Scenario 1 Limits Table 20: Spatial distribution of employment impacts: Scenario 2 System Change Table 21: MW region household projections Table A5.1: Net value added impacts for selected Tararua industries, Table A5.2: Net value added impacts for selected west coast industries, Table A5.3: Net value added impacts for selected rest of Manawatu Wanganui industries, Table A5.4: Net value added impacts for selected rest of New Zealand industries, Table A5.5: Net employment impacts for selected Tararua industries, Table A5.6: Net employment impacts for selected West Coast industries, Table A5.7: Net employment impacts for selected rest of MW region industries, Table A5.8: Net employment impacts for selected rest of New Zealand industries, iv

5 Figures Comparison of Tararua and West Coast N leaching and dairy farm profitability for three scenarios (% change compared with Base)... 2 Figure 1: Horizons boundaries and target catchments (sub-zones)... 5 Figure 2: Comparison of N leaching under Overseer 5.4 and Figure 3: N leaching and the modelling/management gap Figure 4: Cumulative adoption rate used for Scenario Figure 5: Regional impact of N reduction under three scenarios Figure 6: Comparison of Tararua and West Coast N leaching and dairy farm profitability Figure 7: Variation between representative farms Figure 8: Employment impacts over time: Scenario 1 Limits Figure 9: Employment impacts over time: Scenario 2 System Change Figure A1: Summary of modelling framework use to calculate regional and economic impacts for a selected alternative scenario v

6 1. Executive Summary 1 The objective of the study is to undertake a Cost Benefit Analysis and Economic Impact Analysis of the Horizons Regional Council s One Plan nutrient management provisions as it applies to the dairy sector within the Tararua and Coastal Rangitikei (Horizons West Coast) areas of the Region. The methodology was developed in a format that could be applied to other regional freshwater improvement policy initiatives. The methodology does not attempt to quantify the non-market values of the benefits of environmental change. 2 The One Plan regulates existing intensive farming activities including dairy in targeted catchments. It has been identified that intensive farming activities contribute to increased levels of periphytons. Existing dairy farms in target water management sub-zones will either meet nitrogen (N) leaching targets (Limits), according to the Land Use Capability (LUC) of the farms or where they cannot then consent will be granted subject to a reduction in nutrient loss from farm land. 3 The target water management sub-zones include the intensively farmed dairy areas east of the Manawatu Gorge (Tararua) covering 40,675 ha and the coastal Rangitikei and coastal lake areas west of the Gorge (West Coast) covering 25,257 ha. 4 One of the main issues pertaining to dairy farming is N leaching and therefore N leaching limits, are included in the Rules for non-point source discharges. These limits were originally derived with the assistance of Overseer 5.4. Subsequently an upgrade of Overseer to version 6.0 which has an increased focus on soil drainage means some free draining farms would now find it difficult to meet the limits. There is a consenting pathway to manage these farms. 5 This study, funded by DairyNZ and undertaken in collaboration with Horizons Regional Council and DairyNZ staff, attempts to quantify the economic impacts directly on the dairy sector and more broadly on the rural community at the district, region and national levels under three scenarios of N leaching reduction: Scenario 1 (Limits) assumes all farms attempt to meet the Council limits; Scenario 2 (System Change) assumes all farmers will maximise N leaching reduction without reducing profit by more than 10%; Scenario 3 (Within System) assumes farmers will adopt management practices to reduce N leaching while maintaining production and profit. 6 Scenarios 2 and 3 were designed to model possible implications of Horizons Regional Council providing a Restricted Discretionary Consent (RDC). Scenario 3 is the one that most closely aligns with how Horizons Regional Council will be implementing the nutrient management provisions. 7 Fourteen representative farms were chosen for analysis. They represent various biophysical and farm systems. Biophysical aspects included variable rainfall categories in Tararua, and soil types and irrigated or not on the West Coast. Each farm represents a percentage of the total dairy land in each sub zone. 8 Each farm was analysed at various levels of N input using a linear programming (LP) model for Scenarios 1 and 2 and Farmax (farm systems model) for Scenario 3, then run through Overseer 6.0 to provide estimates of N leached per hectare. The resulting revenue, expenditure and profit estimates 1

7 for each farm for each scenario were converted to a per hectare basis for aggregating up to the subzone level, plus a combined estimate. 9 In summary, overall the estimated combined reduction for both sub-zones in N leached from dairy farms is -18% under Scenario 3 (Within System). Scenario 2 (System Change) reduced the N loads from dairy further (-23%) while N reductions under Scenario 1 would result in further reductions (-32%). However, the financial impacts are much higher under Scenario Tararua summary of on-farm changes Gross Farm Business Farm Business N leached Revenue Cost Profit Scenario 1 Limits -33% -30% -26% -45% Scenario 2 System Change -22% -11% -15% 2% Scenario 3 Within system -17% 0% 0% -2% 11 Horizons West Coast summary of on-farm changes Gross Farm Business Farm Business N leached Revenue Cost Profit Scenario 1 Limits -30% -9% -10% -5% Scenario 2 System Change -26% -8% -9% -3% Scenario 3 Within system -20% 0% 2% -6% Comparison of Tararua and West Coast N leaching and dairy farm profitability for three scenarios (% change compared with Base) Tararua West Coast The comparisons for each Scenario in order are: N leached (tonnes), Revenue $m, Expenditure $M and Profit $m. 12 Under Scenario 2 (System Change) and Scenario 1 (Limits), dairying in Tararua district is expected to have larger impacts compared with the West Coast. While the percentage change in N leached is similar on both sides of the Manawatu Gorge dairy farm production and profitability is expected to be reduced by more on the Tararua side under Scenario The assessment of regional and national-level economic impacts is undertaken using two different approaches. First, a multi-regional IO (Input-Output) model is used to ascertain the nature and extent of likely economic impacts (measured using indicators of value added and employment change) for each of the four study areas. Second, very detailed and spatially-defined credit and debit card spending is used for the purposes of obtaining a more in-depth understanding of the likely spatial distribution of employment impacts across the Manawatu Wanganui region. 2

8 14 Based on the IO analysis, Scenario 1 (the Limits Scenario) represents clearly the greatest economic impact for the nation as a whole, calculated as a cumulative undiscounted net loss of $ ,790 million in value added over the period , or an average yearly loss of $ million in value added and 1,280 jobs. The choice of discount rate is important when ascertaining the Net Present Value (NPV) of these impacts. Applying a discount rate of 5% per annum, the total NPV of the value added impact for New Zealand is $ million, compared with $ million when a discount rate of 8% per annum is applied. 15 Regardless of the discount rate applied, the total value added impact for New Zealand under Scenario 2 (Systems Change) is around 30% of that calculated under the Limits Scenario (i.e. an average yearly impact of $ million, or a NPV of $ million for the entire study period applying a discount rate of 5% per annum). The comparative employment losses under the Systems 2 are a little higher, estimated at around 38% of the losses calculated for Scenario 1 (i.e. 480 jobs per year on average). 16 The economic impacts calculated for Scenario 3 (the Within System Scenario) are almost neutral. While there is some spatial variation in impacts across study areas, for the nation as a whole a small change in value added (less than $ million per year) is estimated, along with a small positive gain in employment (52 jobs per year). 17 As expected the analysis shows the economic impacts occurring under both Scenarios 1 and 2 exhibit strong spatial variation. Not only are the impacts concentrated within Manawatu Wanganui compared with other New Zealand regions, the impacts are more strongly concentrated in certain locations within the Manawatu Wanganui region itself. 18 From the analysis based on market data, it is calculated that of the 1,500 jobs lost in 2023 within Manawatu Wanganui under Scenario 1, 830 of these jobs (56 %) are within the Tararua District. Impacts in other districts with target catchments are also significant. For example based on the market data analysis, there are an estimated 140 jobs lost in Rangitikei District during 2023, equating to 9% of the regional employment impact. Nevertheless, the impacts within other districts are not on the same scale as those anticipated for Tararua, particularly when consideration is given to the relative size of each district s economy. The situation is also similar under Scenario 2, with around 58% of the estimated regional employment losses in 2023 occurring just within the Tararua district. Nearly a third of these estimated Tararua impacts occur just within the town of Dannevirke, and a further one-quarter occurs within Woodville. 19 Future population growth within the Manawatu Wanganui region is projected to be focused in the larger urban areas, and to be negative or neutral in most of the smaller towns and rural areas. For areas in which declines in household numbers are expected even without changes in dairying practices, additional disincentives to remain in the area, associated with reduced employment prospects, could exacerbate both the projected decline in household numbers and the consequent economic effects of that decline, including business viability. 3

9 2. Objective of the Study The objective of the study is to undertake a Cost Benefit Analysis and Economic Impact Analysis of the Horizons Regional Council s One Plan nutrient management provisions as it applies to the dairy sector. The methodology was developed in a format that could be applied to other regional freshwater improvement policy initiatives. 2.1 One Plan Objective The One Plan is an integrated plan which guides the management of natural resources in the Horizons Region. It weaves together the previous six separate plans and Regional Policy Statement into one document. The One Plan provides an environmental roadmap directing how the Council manages the Region s resources. The aim of the One Plan is to strike a balance between using the region s natural resources for economic and social wellbeing while keeping the environment in good health. The Big Four issues identified in the One Plan are surface water quality degradation, increasing water demand, unsustainable hill country land use, and threatened native biodiversity. This report is focused on freshwater quality, particularly Nitrogen discharges from dairy farms. The One Plan aims to maintain or improve surface water quality by amongst other things reducing nutrient concentrations (particularly nitrogen) in waterways to levels that decrease periphytons (the proliferation of plants and algae that are present in all water ways). The One Plan identifies intensive farming including dairy in nine target catchments and aims to manage the effects those activities have on water quality including as a major source of nutrients which can cause increased levels of periphytons. New regulations require intensive farmers to apply for consent around nutrient management. The rules apply to various coastal catchments between Otaki and Wanganui and most of the dairying area of the Tararua, excluding farms in the upper Mangahao and the Tiraumea catchments, the lower section of the Rangitikei River, Waikawa and Manakau Rivers (see Figure 1). 4

10 3. Implementation Method Implementation of the One Plan is to be carried out on a target zone basis over a number of years, as set out in Table 1. The Plan recognises that farm systems including sheep and beef, cropping, horticulture and dairy contribute to non-point source nutrient discharge. However, the focus of this study is only on dairy. Figure 1: Horizons boundaries and target catchments (sub-zones) Source: Horizons Note: The decisions version of the proposed One Plan (DVPOP) excludes Coastal Rangitikei (Rang4) and Southern Whanganui Lakes (West 5), but the notified version (NVPOP) and Environment Court version (ECPOP) includes them (Roygard and Clark, May 2012, Map 1). 5

11 Table 1: Target catchments (water management sub-zones) and dates when the rules come into force Catchments Mangapapa Waikawa ( south west coast) Papaitonga (south west coast) Mangatainoka Other coastal lakes Coastal Rangitikei Lake Horowhenua Upper Manawatu above Hopelands Manawatu above gorge Effective date 1 July July July 2016 Source: ECPOP, areas summarised from Table N loss Targets for farms Existing dairy farms in target water management sub-zones will either meet nitrogen (N) leaching targets (Limits), according to the Land Use Capability (LUC) of the farms (Table 2) or where they cannot then consent will be granted subject to a reduction in nutrient loss from farm land. Two scenarios were developed to investigate the likely impacts of reducing N on farms under restricted discretionary consent (RDC). In the One Plan, Table 13.2 provided clear N leaching limits by LUC class over time. The Table is set out below (Table 2) and was established at the time Overseer 5.4 was in use. Information available to Horizons showed N leaching levels in the region were an average of 23 kg/ha/yr with a range of 4 to 53 (see Table 6). Table 2: Land use capability One Plan maximum nitrogen leaching values (kg N/ha/yr) Year LUC I LUC II LUC III LUC IV LUC V LUC VI LUC VII LUC III Source: NVPOP, Table 13.2 Note: Year 1 is the start of the year when the rule comes into force. Values were derived using Overseer Overseer: Implications of changing from version 5.4 to 6.0 Achievement or not of the N leaching limits set out in the One Plan will be assessed on individual farms using Overseer. 1 There have been numerous iterations and versions of the Overseer model developed over time. At the time of the Environment Court hearings, version 5.4 of Overseer was in use. Subsequently, version 6.0 has been released for use. Overseer 6.0 differs from Overseer 5.4 in a number of ways. 1 Overseer 6

12 One of the main changes in version 6.0 is that soil type, particularly the drainage aspect of soils, is given more weight than in version 5.4. The result is that for free draining soils the level of N leaching using Overseer 6.0 is likely to be higher than when Overseer 5.4 is used. The different version of Overseer says for example, a farmer at the north end of the Mangatainoka catchment on LUC III class land who had an average N loss of 28 kg/ha under Overseer 5.4, had this revised up to 44 under Overseer 6.0. This meant his required reduction in year 1 to achieve controlled activity status increased from 21% (28 kg to 22kg) to 50% (44 kg to 22kg) and for year 20 from 35% (28 to 18kg) to 59% (44 kg to 18 kg) to achieve the limit (see Table 3 and Figure 2). The Council recognises however, that in practice there has been no change in the operating system of the farm from that existing under Overseer v 5.4 and therefore consent can be granted. Table 3: Comparison of N leaching under Overseer 5.4 and 6.0 Nx (kg/ha/yr) under different Overseer versions Base Year 1 Year 5 Year 10 Year 20 O O GMP The change from a current estimated 28 to 44 kg N loss/ha/yr does not change the actual amount of N load in-river. The contribution this farm makes to the total load in-river of 159 t SIN/yr (Mangatainoka at SH2, Roygard and Clark, 24 February 2012, table 38) has not changed, but the required reduction to achieve controlled activity level by year 20 has gone from 35% to 59%. Applying, the same percentage change, i.e. 35% would result in moving from 44kg to 29 kg (not 18) as this would achieve the same load in-river at year 20 as before the change to Overseer. Consent is required under both the Controlled Activity (Scenario 1) process where a farm meets Table 13.2 and the Restricted Discretionary process. Recognising that leaching off farm has not altered means that the farmer will get consent. Figure 2: Comparison of N leaching under Overseer 5.4 and 6.0 The key issue is to determine the expected impact under a restricted discretionary consent where an agreement is negotiated between the Council and each farmer to reduce N leached while maintaining farm viability and community vitality. Scenarios 2 and 3 were developed to consider the impacts of reducing N 7

13 loss in order to gain a RDC. All three scenarios assume Overseer 6.0 is used to determine the magnitude of N leaching changes per hectare. 8

14 4. Regional Overview 4.1 One Plan In New Zealand, the Resource Management Act (RMA 1991) directs regional councils to manage freshwater resources in their region. The National Policy Statement for Freshwater Management (NPS 2011) directs regional councils to set water quality limits to provide for freshwater objectives and, where these objectives are not met, time bound targets for water quality are to be specified and policy and plans implemented to ensure that these are met in the future. The Manawatu Wanganui Regional Council (commonly referred to as Horizons), as a part of policy development, has updated existing environmental plans into an integrated planning document known as the One Plan combining the regional policy statement and regional plans including the coastal plan. Under the One Plan, management of nutrients in waterways is primarily aimed at reducing nutrient concentrations to decrease periphytons (proliferations of plant and algal material). The main control of maximum periphyton biomass in unshaded rivers is the frequency of flushing flows that reset their growth through physical removal and scouring of the river bed. However, this is impractical for the management of large channels like the mainstream of the Manawatu River that do not have flow control structures. In this case, the mechanism used is the limitation of the plant available nutrients such as soluble inorganic nitrogen (SIN) and dissolved reactive phosphorus (DRP). Studies have shown that nutrient management is necessary to manage the level both of nitrogen and phosphorus inputs to waterways. Schedule D of the One Plan set out the concentration based targets for nitrogen and phosphorus. These targets apply year round at all flows less than the 20th percentile (flows higher than this are regarded as flood flows), i.e. the standards apply around 80% of the time and not during the 20% of the time when the river is at its highest flows (sometimes referred to as flood flows). The 20th percentile flow exceedance approximate flows required for removing periphyton growth. 2 Water quality is aimed to be managed in an integrated way in the One Plan. Controls are included for point source discharges and non-point discharges. Non-regulatory methods assist with contaminants such as sediment. Discharges of nitrogen from intensive farms are managed for new activities across the Region and within targeted water management sub-zones as shown in Figure 1 and Table 1. Annual controlled activity target limits for N leaching loss are specified for LUC (Land Use Capability) classes which vary according to soil type, topography and climate. The target limits set in the One Plan are shown in Table 2. There is a progressive reduction in the limits over a 20-year period. LUC class codes 3 I to IV are considered to have a high suitability for pasture with V having slight limitations and VI moderate limitations. Horizons has calculated the total area for each LUC class being farmed under dairying in the target catchments. The detail is set out in Table 5 below. 2 3 Roygard J, McArthur K, Clark M Diffuse contributions dominate over point sources of soluble nutrients in two sub-catchment of the Manawatu River, New Zealand. NZ J Marine and Freshwater Research, October. Sub-class modifiers take into account the dominant limitation according to: erosion susceptibility (e), wetness or drainage issues (w), soil limitations such as shallowness, stoniness, low moisture holding capacity (s) and climatic limitations such as coldness, frost frequency and salt-laden wind exposure (c). A third unit level provides an assessment of the severity of the limitation on a scale of

15 Table 4: Land use capability One Plan maximum nitrogen leaching/run-off values (kg N/ha/yr) Year LUC I LUC II LUC III LUC IV LUC V LUC VI LUC VII LUC III Source: The Plan, Environment Court 2013 Note: Year 1 is the year when the rule comes into force. Values for year 1 were derived using Overseer 5.4, while values for subsequent years were derived administratively. Table 5: Hectares in dairy farming by catchment 2008 LUC I LUC II LUC III LUC IV LUC V LUC VI LUC VII LUC VIII Total N Loss Manawatu ,034 41,555 11, ,725 5, , Waikawa , Rangitikei 2,950 8,488 3, , , Total 3,916 40,795 46,136 12, ,161 5, ,238 Source: Derived from Roygard and Clark, 16 May 2012, Table 1. The average current N leaching loss for the whole region is estimated (from a sample of nutrient budgets complied by fertiliser companies using Overseer 5.4 over the period ) at 23 kg N/ha/yr. There is a wide range from 4 to 55 around this estimated mean indicating a variety of LUCs, farm systems and levels of farming intensity. In the target water management sub-zones, the average varies from 12 to 23, across the different LUC Classes, with a range of 4 46 (see Table 6). Assuming a normal distribution, half the dairy farms in the target water management sub-zones would need to reduce N loss in the first year of implementation of the Plan, with some by more than 50% depending on LUC class, if they were to meet the Table 13.2 numbers. Where the numbers cannot be met there is a consenting pathway using RDCs that recognises the N loss reduction that can be achieved on each farm. 4.2 Trends in water quality Information available on the state and trends in water quality and aquatic ecosystem health at sites across the region indicate a generally poor status, relative to Schedule D (One Plan targets) in catchments that have a high proportion of pastoral land use and/or significant point source discharges. 4 According to Roygard and Clark (2012), trends in water quality vary across the region with some improvement in water clarity, E. coli and nitrogen. With respect to N Over the past 10 years, both Rangitikei monitoring sites and three out of four Manawatu sites show significant improvements (Horizons 2013, p17). Phosphorus levels improved in the lower Manawatu but have degraded in the Whanganui, Rangitikei and Upper Manawatu. More than half of the sites monitored for aquatic macro invertebrates (insects, worms, snails, etc.) do not meet the One Plan (Schedule D) MCI 5 ecosystem health targets. Periphyton levels exceed cover and biomass targets at a number of sites downstream of point source discharges (Roygard and Clark (2012). 4 This information in this section is from a joint technical statement by Dr Jonathan Roygard, Kathryn McArthur and Maree Clark Statement of Evidence before the Environment Court dated 14 February The Targets mean the Schedule D for each indicator (nitrogen, phosphorus, periphyton nitrate, MCI, etc) in the Decisions Version of 10

16 Table 6: Target water management sub-zones: areas, number of farms and current N losses (area in Table 13.1, 2008) Catchment Tararua Catchment area (ha) Area in dairy (ha) Total number of dairy farms Number of dairy farms providing N loss Ave N loss kg/ha/yr Overseer 5.4 (range) Mangapapa 2, (19 26) Mangatainoka 43,216 13, (11 40) Upper Manawatu (above Hopelands Mana_1 5) Manawatu above gorge (Mana_9a, 9c and 6) 126,669 20, (12 41) 21,219 6, (12 33) Sub-total Tararua 193,767 40, West Coast Waikawa 7,936 1, Lake Papaitonga 2, Northern Manawatu Lakes 12,521 6, (6 28) Coastal Rangitikei 65,993 13, (10 47) Kaitoke Lake 6, Southern Whanganui Lakes 19,533 1, (4 18) Lake Horowhenua 6,963 1, (14 21) Sub-total West Coast 122,131 25, Target zones 315,898 65, Region 2,229, , (4 55) Source: Maree Clark, Horizons RC The nitrate loads measured in the target catchments (including the Coastal Rangitikei) ranged from approximately twice to more than four times the Target Load set by Horizons in the One Plan (in tonnes per annum). In all cases, non-point sources were the key contributors of contaminants. Also, in many cases target catchments considerably exceeded the phosphorus target loads (Roygard and Clark 24 February 2012, Table 19). In terms of relative contributions to measured loads of N in-river at the Upper Manawatu Gorge dairy contributed 612 tonne (27%) and sheep and beef 1,536 tonne (68%) out of a total of 2,252 tonne. For the Rangitikei at McKelvies dairy contributed 189 tonne (35%) and sheep and beef 101 tonne (19%) out of a total of 543 tonne (Roygard and Clark 24 February 2012,Table 38). 4.3 Modelling N losses from different policy approaches Scenario modelling by Horizons indicates that doing nothing will not maintain or enhance water quality. Based on the LUC loss limit approach to managing nitrogen (also referred to as the natural capital 5 the Proposed One Plan (DVPOP). The water management sub zones listed in Table 13 2 of the DVPOP are referred to as target catchments. The Macroinvertebrate Community Index (MCI) is a biological indicator widely used throughout New Zealand to report on the state of aquatic macro invertebrate communities at freshwater sites and to make inferences about the water quality influencing the site s ecosystem health. 11

17 approach), some improvement may be gained from applying N loss limits to new conversions in the Mangatainoka but not in the Upper Manawatu, Upper Gorge or Waikawa catchments. Large improvements are considered likely only if limits are applied equally to existing dairy farms as well as new conversions. Scenario modelling by Horizons showed that continued degradation of water quality can be expected if loss limits are set above 24 kg N/ha in the Upper Manawatu and 27 kg in the Mangatainoka (estimated based on Overseer 5.4). Any further dairy expansion of the Waikawa is considered likely to affect water quality (Roygard and Clark 14 February 2012, p 68). 4.4 Setting regulatory targets Regulatory targets for nutrients are typically expressed as concentrations to limit nuisance plant growth and ensure ammonia and nitrate levels are not toxic to aquatic life. Point source discharges are managed by daily limits on discharge volume, contaminant load or concentration. Diffuse sources can typically be managed over annual timescales using the nutrient budgeting tool Overseer 6 which estimates losses from farming systems. This approach estimates long-term average annual nutrient loss and is the most commonly used tool to assist farmers to meet voluntary dairy industry nutrient budgeting requirements. The process Horizons follows to assess the regulatory target concentrations in rivers is: 1 determine existing overall loads 2 determine the relative contributions from point and diffuse sources for a range of flows 3 convert the concentration based targets to target loads, including and excluding flood flows 4 assume point source discharge effects do not diminish downstream of the point of discharge (over estimate the impact of point sources) 5 estimate diffuse sources using the flow stratified approach. Using the approach above, the nutrient concentration targets (0.444 g SIN/m 3 and g DRP/m 3 ) were determined to be equivalent to the average annual target loads of 358 t SIN/year and 8.1 t DPR/year at the Manawatu Hopelands site, and 268 t SIN/year and 6 t DRP/year at the Mangatainoka, SH 2 site (Roygard, McArthur and Clark 2011, p9). When calculated for each individual year, the target loads ranged from 54% lower to 45% higher at the Hopelands site and 40% lower to 31% higher at the Mangatainoka site. The variation was explained by variations in flow volumes in each year. Interestingly, 57% of the total volume flow through the Hopelands site occurs in only 20% of the time and at the highest flows. Similarly, for the Mangatainoka, 64% of the total flow volume occurs in 20% of the time. Flood flows are primarily responsible for the within-year variation around the average nutrient loads. When the flood flows are removed, the gap between measured loads and targets increases due to the higher concentrations of nutrients in the low flow periods. In summary, diffuse sources are estimated to contribute up to 98% or more of SIN and 84 88% of the DRP measured loads in the two catchments. This is important information for the setting of the targets as 6 Overseer is software, owned by MPI, AgResearch and Fert Research, that was developed as a farm management tool to assess nutrient losses for New Zealand farming systems. Increasingly, Overseer is used as a regulatory tool, which pushes it beyond design capabilities. Due to the inherent complexities of farm systems, the output of Overseer has significant uncertainties and wide confidence limits that are not compatible with the single figure limits required by the LUC defined tgargets for controlled activity status. Regular upgrades are undertaken, which may result in significantly different results between updates. 12

18 required by the National Policy Statement (NPS 2011) particularly as the previous catchment plan, dated 1998, only regulated point sources. Management of point sources continues to be important, particularly at low flows, when point source discharges are most significant and these are managed through the One Plan. 4.5 Changes to in-stream SIN loads under different policy scenarios Horizons completed scenario modelling for all policy approaches put forward to the Environment Court as set out below. These scenarios were modelled for a range of catchments, e.g. Waikawa, Rangitikei and Manawatu. Sub-catchment areas of the Manawatu were also modelled. The Fonterra policy scenario put forward during the Court proceedings was compared to other policy scenarios at two of the sites. Two key sites have been assessed for the impact of policy changes on in-river SIN loads over the 20-year period of the One Plan(Roygard and Clark 16 May 2012).These are for the management area upstream of Hopelands (Manawatu) and upstream of Mangatainoka at SH2. No details are provided for DRP. Four main approaches were used at the two sites: 1 Horizons: DVPOP LUC limits for year one only applied to existing dairy farms and conversions 2 Fonterra: potentially achievable reductions on existing farms and DVPOP LUC limits for conversions 3 Fish & Game/DoC: NVPOP limits over a 10-year timeframe 4 Single Number Limit: all dairy at 27 kg N/ha/yr Approaches 1 and 2 have broadly similar reductions in overall SIN loads over 20-years. Approach 3 results in more than double the level of reduction compared with 1 and 2. Approach 4 results in an increased SIN load. The most comprehensive information is provided for the area upstream from Hopelands in the Manawatu catchment (see Table 7). The current N loss rate in 2008 was 26.1 kg N/ha/yr. The allowed N loss rate for conversions was set at 21.8 for approaches 1 and 2, 16.3 for approach 3 and 27.0 for approach 4. Over a 20-year implementation period, approaches 1 and 2 showed a 15 to 16% decrease in the N loss rate. Approach 3 had a 37% decrease and approach 4 a 3.5% increase. When this is translated into changes in the in-river SIN load at Hopelands under three levels of dairy expansion, being 5.5%, 11% and 18%, all scenarios show a decrease in SIN load except approach 4 where the load increases. When these same policies are applied at Mangatainoka, approaches 1 and 2 result in decreases in in river SIN loads, at 5.5% and 11% expansion in dairy, but an increase at an 18% expansion on dairy. Information was given as to the observable consequences to in-stream values under the various scenarios at the Hearing Panel for Water (Horizons 2010). Table 7: Changes in N loss rates (kg N/ha/yr) under different policies, and different % expansion of dairy farming. Attenuation factor Policy approach Horizons Fonterra F&G/DoC 27 kg limit Hopelands existing dairy farms N loss rate Attenuation is the loss of N from the water system from the bottom of the root zone of the plant to the point that it reaches a water way through the ground. Attenuation varies from between 0.3 and

19 N loss rate Conversions N loss rate % change in N loss rate existing dairy farms Hopelands % change in-river SIN load 5.5% expansion in dairy % % Mangatainoka % change in-river SIN load 5.5% expansion in dairy % % Source: Derived from Roygard, and Clark, 16 May 2012, Tables 2 7. For the Manawatu catchment, while the average (2008) N loss is 23.4 kg/ha/yr, which is about the limit set in year 1 for LUC III (24 kg N/ha/yr), 31% of land in dairying in the catchment occurs over LUC III and higher (see Table 3). These land classes have considerably lower N loss limits, for example, the 20-year limit for LUC IV is only 13 kg N/ha/yr. In addition, when Overseer was upgraded from version 5.4 to 6.0, some farmers on free draining soils, or with higher rainfall, experienced significant increases to their N loss levels making achievement of controlled activity limits extremely difficult. For example, a farmer at the north end of the Mangatainoka catchment on LUC III class land who had an average N loss of 28 under Overseer 5.4, had this revised up to 44 under Overseer 6.0. This meant the required reduction in year 1 to achieve controlled activity status increased from 14% to 45% and by 59% to achieve the limit in year 20. However, there is an alternative approach for existing dairy farmers which is to describe a plan of action to reduce per hectare N leaching and consent will be granted. The scenario modelling for the Environment Court process focused on the nitrogen loads and compared all of the policy approaches in various catchments. This was to provide an evidence Base for decision making about maintaining and enhancing water quality. The next step of connecting N load to water quality outcome was not completed for the Environment Court process. This was in part due to the lateness of supply of some of the policy approaches. Subsequently, the end of hearing report for the Council level Hearing included some of this type of analysis. 14

20 5. Approach and Scope of Economic Analysis 5.1 Constraints and limitations The approach used in the economic analysis is based on the use of representative farms. Fourteen farms were chosen to represent dairying in the Tararua and West Coast areas. For each farm, a linear programming model (Pannell 1997) was used to represent various scenarios limiting N leaching. The approach used has its limitations. Clearly the degree to which the representative farms represent reality is open to speculation. Care, however, has been taken to ensure the major factors affecting N leaching in the target zones were adequately represented. Overseer is the model used to assess the level of N leached on the representative farms. The Overseer technology itself is an iterative process with the latest available version (6.0.3) generating different outcomes to earlier versions. Thus the use of Overseer itself has limitations. In the real world, there is a whole host of factors which influence performance on individual farms. Examples of such factors include the level of debt or the life cycle stage of the farmer who is making the decisions. It is not possible, in a study such as this, to model the impact of all of these factors. That is not to say they are not important but rather, the complexity of the real world is beyond the scope of this study. The water quality data and information Horizons provided for use in the study comes largely from 2008 (Roygard and Clark 14 February 2012,p 49). Given all the limitations of the approach adopted in the study, it is important to recognise that it is the relative economic impact between the various scenarios and the order of magnitude of the impacts which are the overriding considerations. 5.2 Representative farms The number of representative farms chosen needs to represent the key features influencing N leaching from dairy farms in the target catchments Key features influencing N leaching The level of N leached from an individual dairy farm is determined by numerous factors. Given there are some similarities between dairy farm systems and climate and geographical influences, it is possible to group dairy farms to represent the more dominant factors affecting N leaching levels. In Table 6 above, the breakdown of target zones, area in dairying and number of dairy farms by catchment is shown. In discussion with DairyNZ consultants and Horizons staff familiar with the regions, it was agreed that combining the target zones into two main areas (Tararua and West Coast) made sense. The Tararua catchment includes Mangapapa, Mangatainoka, and Upper Manawatu and Manawatu above the gorge areas. The West Coast catchment includes Waikawa, Lake Papaitonga, northern Manawatu lakes, coastal Rangitikei, Kaitoke Lake, southern Whanganui Lakes and Lake Horowhenua. 15

21 The total catchment area within the two target sub-zones (315,898 hectares) represents 14% of the Region s total land area. Of the total target catchment area, 21% is in dairying on 440 dairy farms. Those 440 dairy farms represent 46% of the 950 total dairy farms in the region. The 440 dairy farms are split between the Tararua and West Coast target catchments as: Tararua catchment: 289 dairy farms with average area of ha, total area 40,675 ha West Coast catchment: 151 dairy farms with average area of ha, total area 25,275 ha In the following section, the different factors affecting N leaching in each of the two catchments are discussed. The factors differ between the Tararua and West Coast catchments Tararua catchment a) Rainfall: Three rainfall zones were identified, annual rainfall of 1000 to 1200 mm (30%); mm (46%); and >1600mm (24%). b) Dairy farming system: The DairyNZ classification system (1 to 5) was used and condensed to low, medium, and high levels of bought in feed. The representation of DairyNZ dairy farm systems is: Low DairyNZ farm systems 1 and 2 (20%) Medium DairyNZ farm system 3 (60%) High DairyNZ farm systems 4 and 5 (20%) c) Level of N used: The level of nitrogen applied affects N leaching and a reasonable spread of levels of applied N was needed for the analysis across the representative farms. d) Irrigation: In the Tararua catchment, there are around 20 dairy farms using irrigation, other than for effluent distribution. It was deemed useful to incorporate an irrigated dairy farm in the representative sample Distribution of representative dairy farms in Tararua target catchment Using the above features, the distribution of the 40,675 ha in dairy farms in the Tararua catchment is shown in Table 8 below. One representative farm was chosen to represent each of the seven categories in this catchment. Table 8: Tararua: areas attributed to each representative farm (hectares) Rainfall mm mm >1600mm Sub-total DairyNZ Farm System Low (1/2) 3,029 3,779 6,808 Medium (3) 9,087 11,337 7,248 27,672 High (4/5) 3,779 2,416 6,195 Sub-totals 12,116 18,859 9,664 40,675 Note: In column 1, figures in brackets denote the DairyNZ farm system nomenclature from the 1 5 scale. 16

22 5.2.4 West Coast catchment In the West Coast target catchment, a different set of factors affecting N leaching were chosen with rainfall excluded as the annual rainfall in this catchment is spread within a much tighter range around a total of 1000mm per annum. The factors are as follows: a) Irrigation: It was decided that the use of irrigation was a more important factor than rainfall. Of the 151 dairy farms in this target catchment, around 35 use significant irrigation systems (15% by area). b) Soil type: For practical purposes, it was decided to consider three main soil types : Sandy soils with impeded drainage (34%) Free draining soils (32%) Other soils with impeded drainage (34%) c) Dairy farming system: It was again deemed important to ensure a reasonable spread of the DairyNZ farm systems across the representative sample Distribution of dairy farms in West Coast target catchment Using the above features, the distribution of the 25,257 ha in dairy farms in the West Coast catchment is shown in Table 9 below. Seven farms were chosen to represent this catchment, one in each category apart from not-irrigated farms other soils with impeded drainage where three farms were given equal weight (i.e. 2,863 ha each). Table 9: West Coast: areas attributed to each representative farm (hectares) Irrigation Irrigated Not irrigated Sub-total Soil type Sandy with impeded drainage 1,975 6,612 8,587 Free draining 1,859 6,223 8,082 Other soils with impeded drainage 8,588 8,587 Sub-totals 3,834 21,423 25,257 Note: Not irrigated other soils with impeded drainage is represented by three farms with 2,863 ha attributed to each. 5.3 Scenarios modelled Three scenarios were designed to quantify the regional impacts of possible N loss reductions from dairy farms Scenario 1: Limits Under Scenario 1, all representative farms are forced to achieve N leaching levels no greater than the target levels specified in Table 13.2 and known as the Controlled Activity Limits. At the initiation of the analysis these limits were to be met by the farms across the time horizon of Year 1, and Years 5, 10, and 20. There was not enough data to model each time segment and mitigations were adopted that either met the 20- year limit or came closest to it. 17

23 5.3.2 Scenario 2: System Change This scenario represents a situation where all dairy farms adopt farm system changes to maximise N leaching reductions while not allowing farm profitability to reduce by more than around 10%. This means some farms will have N leaching levels at or below the Controlled Activity limits and some will operate under a Restricted Discretionary Consent (RDC). Whole farm system changes take some time to implement and assumptions need to be made about the rate of change when using the representative farms to represent all farms in the target zone(s). This is explained for Scenario 3 under the Section (Technology Adoption) below. Choosing the best mitigation strategies for Scenarios 1 and2 Grazing Systems Limited (GSL) was contracted to generate a variety of N leaching iterations from their LP model for each representative farm. The iterations started with an assessment of the current level of N leaching for each farm and then progressively reduced N leaching over a number of iterations. The objective was to use the LP model to find the scenario where N leaching was reduced significantly from the current level but farm profit was not reduced unduly. Selecting this scenario required the exercise of some subjective judgement. This was done using a selection team comprising DairyNZ, Horizons and Nimmo-Bell representatives. The LP model generated an optimum iteration shown as the red dot on Figure 3 below. This takes the current Base resources of the farm (green dot) and optimises profit. This optimum is then constrained with less and less N in the system moving down the solid line until an iteration is reached that meets the target N leached (blue dot). The aim is to achieve the maximum reduction in N leached for the least reduction in operating profit. An arbitrary figure of around 10% reduction in operating profit was chosen by the team as the benchmark. Considerable discussion ensued around whether the N restricted iteration could be directly compared with the Base. It was concluded that there is a modelling and management gap depicted by the difference between the solid line (LP generated outcomes) and the dotted line (existing management). Thus actual performance will be somewhat less than a movement along the solid line, which assumes optimal management and resource allocation. In order to overcome this problem and estimate the likely outcome with existing management, the percentage change in production, revenue and expenditure between the optimum and N restricted iteration is applied to the Base situation. This generates the changes required to arrive at a new point on the dotted line, which has similar N leaching to the N restricted position on the solid line. 18

24 Figure 3: N leaching and the modelling/management gap Source: Adapted from S McCarthy, DairyNZ The changes required with N leaching minimised subject to operating profit no more than a 10% reduction was chosen for Scenario 2. An iteration which depicted the changes required to achieve the N limit (or as close to it as possible) was chosen for Scenario 1. Note that the scenarios represent the changes from the current situation as this is a marginal analysis and only the differences between scenarios are of interest Scenario 3: Within System Scenario 3 assumes N leaching can be significantly reduced without changing the current farming system, i.e. by holding cow numbers and milk production at current levels. A number of mitigation activities are adopted specific to each representative farm and include in no particular order: no N on effluent block except for one farm in which 55 units of N was applied to effluent block less total N with reduction from 90 kg/ha average of the Base farms to 57 kg/ha average rate of N per dressing reduced generally to a maximum of 32 units in a single dressing timing of N application changed. Autumn dressing was eliminated where possible or shifted earlier. Early spring (August) dressings were reduced in rate more frequent N at lower rates for the farms that received higher applications increase N fertiliser in non-effluent area, but reduce N overall in some farms where N use was originally high and therefore the quantity of supplements needed to substitute the N boosted grass was deemed excessive more imported feed, e.g. PKE, or maize silage to make up for the absence of N grown pasture less pasture silage imported and more made on farm as is a high N supplement 19