Main authors: R.K. Laursen, F. Bondgaard, P. Schipper, K. Verloop, L. Tendler, R. Cassidy, L. Farrow, D. Doody, F. A. Nicholson, J. R. Williams, I. Wright, J. Rowbottom, I. A. Leitão, A. Ferreira, B. Hasler, M. Glavan, A. Jamsek, N. Surdyk, J. van Vliet, P. Leendertse, M. Hoogendoorn and L. Jackson-Blake.
Editor: Jane Brandt
Source document: R.K. Laursen et al. (2019) Evaluation of Decision Supports Tools. FAIRWAY Project Deliverable 5.2 216 pp

 

Contents table
1. Differing focus and application in decision support tools
2. Remarks on farm level DSTs
3. Remarks on catchment and regional level DSTs
4. Main findings from the testing of DSTs
5. General overview of DST functionality
[Note: Because of the resolution of the images, it is difficult to see the detail in some of the figures and tables. See the »full report for more legible originals.]

1. Differing focus and application in decision support tools

The DSTs selected for evaluation in the case study sites differ in their focus and application. In this analysis we have grouped them into the following categories in order to ease comparison and draw conclusions on specific issues:

Farm level DSTs

Aims: Improve individual farm nutrient or pesticide management, contaminant load estimation, identifying cost-effective mitigation measures, compilation of relevant data, documentation of farm management. Two types of DSTs were considered:

  • Improvement of on-farm nutrient management (Mark Online, Düngeplanung, MANNER-NPK, ANCA, NDICEA)
  • Improvement of on-farm pesticide management by considering potential environmental harm (Environmental Yardstick for Pesticides, Plant Protection Online)

Catchment and regional level DSTs

Aims: to identify high-risk areas for losses and prioritise mitigation measures; to identify cost-effective management options to decrease nitrate or pesticide pollution. Three types of DSTs were considered:

  • Risk assessment of pesticide applications (SIRIS, SCIMAP, Phytopixal)
  • Cost-effective measures to reduce nitrate and pesticide loads to water (Farmscoper)
  • Cost-effective allocation, location and choice of nitrogen (N) mitigation measures in order to reduce N loads to water (TargetEconN)

These categories have been used to structure the presentation of the results and conclusions. We conclude with general remarks that apply for all case studies.

2. Remarks on farm level DSTs

In some cases, existing DSTs used in the case study area were evaluated in comparison with the test DST, while in others the motivation for testing the DST was the absence of a useful alternative. Key objectives of the implementation and testing of each DST in the case studies related to i) evaluating the potential benefits/opportunities presented by the DST, ii) identifying any barriers to implementation and iii) assessing stakeholder perception of the DST and these are presented in the following. In Part 2 of this report, a detailed description of the testing of the DSTs in each participating case study site is presented.

2.1 Improvement of on-farm nutrient management

Improvement of on-farm nutrient management was the focus of testing 5 DSTs (Mark Online, Düngeplanung, MANNER-NPK, ANCA and NDICEA) across 5 case study sites. The main results related to the objectives of the testing and the advantages, disadvantages and stakeholder perception for each of the DSTs are summarized below.

Mark Online (developed in Denmark) was tested at Case Study no. 5 in Lower Saxony (Germany). Key outputs from Mark Online include farm fertilizer plans (for arable and grassland crops) to be directly used by farmers, and nutrient balances at both field and farm scales. The objective of testing was to see how fertilizer planning, documentation and control are undertaken in other countries and how the DSTs for that purpose are designed. Mark Online has similarities to Düngeplanung which is already used in Germany and so was a useful comparator DST.

  • Advantages: The key advantage of Mark Online was the comprehensiveness of the model and the inclusion of cross-compliance checking (e.g. it covers Greening targets) - only one tool is required to cover all on-farm nutrient management budgeting. The Danish approach uses a farm-specific N-quota that limits the total amount of fertilizers to be applied, but allows flexibility and farmer judgement on how allocation of nutrients in an agronomically sensible way should take place within the farm. At the same time, it also renders stricter controls within farms possible. The potential to link soil type to yield level, following the Mark Online approach, would have benefits in the Lower Saxony case study in the future.
  • Disadvantages: The complexity of the all-inclusive system, however, means that advisory assistance is necessary for use in most cases. Geographic differences included the need to translate soil types present in Lower Saxony into their Danish equivalents, differences in the Danish and German legal frameworks, and in the way databases are linked. In Denmark more open and linked agricultural databases (e.g. fertilizer sales, stocking rates, manure transport) are available than in Germany.
  • Stakeholder perception: Participating farmers in the case study area liked the modular design of Mark Online and the possibility to compile useful management information within the software. It covers more aspects than the German software Düngeplanung, however, Mark Online reflects current Danish legislation. Although most farmers in the case study complied quite well with it, some would face problems with their current management practice if they had to follow Danish law (e.g. the obligation to establish cover crops, restricted fertilizer use in autumn, strict soil phosphorus - P-levels).

Düngeplanung (developed in Germany) was tested at Case Study no. 8 in Overijssel (Netherlands). The main output from Düngeplanung is a farm-level nutrient plan. The objective of the testing was to evaluate Düngeplanung in comparison with the existing “PerceelVerdeler” DST (parcel distributer). This DST was developed for grassland and fodder crops in the Netherlands but does not extend to arable crops. As Düngeplanung covers all crop types, the testing provided an opportunity to suggest and plan extensions to the existing DST for the benefit of more farmers.

  • Advantages: The conceptual model and specific functions within Düngeplanung could be used to extend the existing Dutch DST for fertilizer planning. Moreover, interesting characteristics are the broad spectre of crops addressed in Düngeplanung as well the consistent and accurate correction of fertilizer rates for residual nutrients that are released by fertilization of crops grown in earlier years. Further exchanges between the Dutch and German developers will be necessary.
  • Disadvantages: Düngeplanung could not be implemented directly in the case study area due to differences in the input data and parameters used in the Netherlands. One of the issues is that rates of organic and mineral fertilizer N and P are limited in the Dutch regulation. On the basis of these limits expressed in kg per ha and the areal of the farm land a farm budget for N and P is established. This budget, just like in Denmark, can be freely allocated to the crops and parcels over a farm. Thus farm fertilizer plans should respect the farm N quota, and when N quota are lower than the fertilizer recommendations, they should suggest an optimal distribution of the N and P quota. Uncertainty regarding the applicability of German fertilizer recommendations to Dutch conditions would also require additional tests and comparisons.
  • Stakeholder perception: Düngeplanung was demonstrated and discussed with farm advisors. They recommended to adopt strong characteristics in the Dutch systems like the PerceelVerdeler and to waive immediate implementation in the current case of Overijssel.

MANNER-NPK (developed in the UK) was tested at Case Study no. 11 in Baixo Mondego (Portugal). The main outputs from MANNER-NPK are estimates of crop available nutrients based on applications of organic manure, as well as N losses and N use efficiency. These can be used to develop on-farm nutrient management plans. The PLANET DST available from ADAS which incorporates MANNER-NPK is an extension tool which could be used for this purpose. The objective of testing in Portugal was to identify a DST which could be used to address nitrate issues affecting drinking water quality. Although fertilizer plans have already been made by some farmers, there are currently no DSTs available for this purpose in Portugal, so the development of a similar DST could be of great benefit.

  • Advantages: A DST with MANNER-NPK’s functionality would be of benefit to farmers in the case study area, since they would have access to information they do not have with the current fertilizer plans. No equivalent exists at present.
  • MANNER-NPK was developed for the UK and uses UK climatic data so the applicability of the DST directly to the case study area is limited. Farm record keeping in the case study area was not accurate enough to provide reliable data on nutrient applications. Currency values and cost estimates provided by the model would also have to be adjusted for Portuguese conditions.
  • Stakeholder perception: There is support for the provision of a similar DST. Clear benefits to users were identified.

ANCA (developed in the Netherlands) was tested in Case Study no. 13 in Dravsko Polje (Slovenia). The main output from the DST is a farm-level assessment of nutrient flows on dairy farms. These can be used to identify management changes on the farm which may reduce emissions and improve sustainability. The objective of the testing at the Slovenian case study site was as a potential DST to demonstrate that dairy farmers have produced milk in accordance with sustainability standards. No equivalent tool is available in Slovenia.

  • Advantages: The DST provides insights into Slovenian farming systems. Use of ANCA highlighted important differences between the farming systems in the Netherlands and Slovenia including poor crop nutrient uptake efficiency from organic fertilizers on Slovenian farms, high GHG emissions due to the lack of modern equipment and looser restrictions on organic nitrate application in The Netherlands (170 kg/ha; derogation for farms with grazing livestock 250 kg/ha) compared to Slovenia (all farms 170 kg/ha).
  • Disadvantages: Differences in farming systems between Slovenia and the Netherlands limited the application of the DST. There is no facility within the DST to alter grazing or cropping systems to be more applicable to Slovenia. Some data, such as soil texture, required for ANCA’s operation are not readily available in Slovenia. Help for users was only available in Dutch.
  • Stakeholder perception: Farmers perceptions differed from advisors. Farmers perceive DSTs as an administrative burden and are concerned about them being difficult to use. Farm advisors were very supportive of DSTs (particularly with a visual display output) and would be keen to get access to them.

NDICEA (developed in the Netherlands) was tested in Case Study no. 5 in Lower Saxony (Germany). The main output from the DST is an estimate of N-mineralisation in the soil. It goes beyond simple N budgeting for each crop since it accounts for the complex interaction of the soil-crop-management system. By integrating live weather data, it takes into account the most variable influence factor for crop development. The objective of the testing was a comparison with the German DST Integrated Plant Production System (ISIP) which also estimates N availability to the crops. Specifically, the testing focussed on whether NDICEA could be more precise in mapping N-dynamics in the soil, since NDICEA considers more information than ISIP concerning soil properties and soil tillage.

  • Advantages: The DST provides information on N availability in the soil, based on the most relevant factors; optionally own (farm) data on soil and crop quality can be used. The DST has a user-friendly design, self-explanatory application and provides results as clear graphical representations.
  • Disadvantages: Output crucially depends on the quality of input data (comprehensive calibration is needed). Since local climate data is not readily available in the case study in Lower Saxony and has a high spatial variability, the obtained results are not reliable.
  • Stakeholder perception: Farmers generally like the idea of having an estimate of N availability in the soil during the growing period. But the feasibility crucially depends on the reliability of the results. Since it was not possible to run the DST with local climate data and validation (with measured against modelled numbers) of the results is missing, there was no benefit for farmers in using it at the current time.

2.2 Improvement of on-farm pesticide management by considering potential environmental harm

Improvement of on-farm pesticide management by considering potential environmental harm was the focus of testing 2 DSTs (Environmental Yardstick for Pesticides and Plant Protection Online) across 3 case study sites. The case study site objectives and the advantages, disadvantages and stakeholder perception for each of the DSTs are summarised below.

Environmental Yardstick for Pesticides (developed in the Netherlands) was tested in Case Study no. 2 in Aalborg (DK) and in Case study no. 3 in Anglian Region (UK). It is a management DST for farmers and advisors, and key outputs include the assignment of environmental impact points for the risk to water and soil organisms, as well as the risk of leaching to groundwater. In Denmark, the objective of the testing was to see how pesticide management and risk assessment is undertaken in other countries and compare it to the Danish pesticide tax system, which reflects the risk of the pesticides. In the UK the Environmental Yardstick for Pesticides was tested to see whether it can supplement existing DSTs, and be used by agronomists and land managers to enhance knowledge of pesticides that can contaminate drinking water resources.

In the following section advantages, disadvantages and stakeholder perceptions are summarised for the testing of the Environmental Yardstick for Pesticides in Aalborg (DK) and Anglian Region (UK) respectively.

Aalborg (DK):

  • Advantages: In Denmark, the key advantage of the Environmental Yardstick for Pesticides was found to be the visual representation of the risk of a pesticide leaching to the groundwater. This visual approach would be beneficial to include in for example the Danish DST Plant Protection Online as it would make it easy for farmers and advisors to understand the risks of pesticides. In Denmark the risk is controlled by taxes on pesticides (i.e. a high tax means high risk). However, no visualisation is provided of whether the tax is high due to risk of leaching to the groundwater, risk to water and soil organisms, human health etc.
  • Disadvantages: Application of the Environmental Yardstick for Pesticides is less relevant to Denmark than the Netherlands, as the Netherlands has more products available for the control of weeds in maize, potatoes and winter wheat. Additionally, the Environmental Yardstick for Pesticides is mostly designed for single products and not mixtures, which means it cannot calculate the risk when products are mixed to avoid the resistance challenge in weed control, pest and fungal diseases.
  • Stakeholder perception: In Denmark stakeholder perception was not evaluated. This was because the risk profiles generated by the Environmental Yardstick for Pesticides for the pesticides allowed for use on maize, potatoes and winter wheat in Denmark did not always match those in the Danish Pesticide taxes. A DST must be more relevant for the stakeholders before involving them in the assessment.

Anglian Region (UK):

  • Advantages: The Environmental Yardstick for Pesticides brings together several interesting sources of information in a way that appears to be more accessible to farmers and agronomists than currently available tools in the UK. The DST is especially valuable as an informative DST. Additionally, pesticides are considered together and can easily be compared.
  • Disadvantages: For implementation and application in the UK, adaptation and new data (e.g. label and authorisation data, integrated pest management (IPM) data) would need to be added; some of this data is less easy to find. Moreover, the DST focus on environmental impact including rate and risk of drift, which is not the only aspect driving product choice. Efficacy, the need for repeated applications, harvest intervals etc. also need consideration. Whilst the red/amber/green (high, medium and low risk) was liked by some, others feared that markets, using selected information, might ask growers not to use ‘red’ (high risk) products even though these might be the best in regard to efficacy.
  • Stakeholder perception: The Environmental Yardstick for Pesticides was found to be a useful DST by most farmers and agronomists. However, they would prefer it to be incorporated into an existing DST.

Plant Protection Online (developed in Denmark) was tested in Case Study no. 9 in Noord Brabant (Netherlands). Plant Protection Online includes several plant protection tools for weeds, diseases and pest control in individual fields. For Noord Brabant the most interesting are ‘the problem solvers’ (Pesticide (mix) selection for specific weed species, diseases or pests in crops respectively); ‘the Identification key’ (identify/recognise weeds, pests and diseases) and ‘users mixture’ (compare efficacy of mixtures on weed species). These tools were tested in the Noord Brabant province because it has been directed to reduce pesticide leaching to groundwater. The Environmental Yardstick for Pesticides is already used in the case study area, but a specific advice tool for farmers does not exist and Plant Protection Online could provide the inspiration for the development of a new DST.

  • Advantages: Plant Protection Online has interesting components that are useful for advisors, e.g. the advice on low/reduced dosages, no treatment and information on damage thresholds.
  • Disadvantages: Plant Protection Online, in its current form, would be difficult to implement in the Netherlands, as it was not developed for Dutch crops and pesticides. Thus the DST is lacking in a number of the crops and pests/diseases present in the Netherlands.
  • Stakeholder perception: It is not practical for farmers as it involves too many steps, too much input data is necessary, and it is not practical for use in the field (e.g. there is no mobile app). If implemented, it would be preferable to incorporate the interesting components of Plant Protection Online into existing apps.

3. Remarks on catchment and regional level DSTs

3.1 Risk assessment of pesticide applications

Risk assessment of pesticide applications was the focus of testing 3 DSTs (SIRIS, SCIMAP and Phytopixal) across 3 case study sites. The case study site objectives and the advantages, disadvantages and stakeholder perception for each of the DSTs are summarised below.

SIRIS (developed in France) was tested in Case Study no. 2 in Aalborg (Denmark) and in Case study no. 4 in La Voulzie (France). The main output from SIRIS is a ranking of pesticides according to their potential to reach surface water and groundwater. In Denmark, the objective of the testing was to see how pesticide risk assessment is undertaken in France and compare it to both the Danish pesticide tax system, which reflects the risk of the pesticides in Denmark, as well as the output from the Dutch DST Environmental Yardstick for Pesticides. In La Voulzie (France) SIRIS was selected as it is one of few DSTs available for predicting pesticide loss at the catchment scale, and it has not yet been tested there. The objective of the testing was to compare the modelled pesticide risk at catchment scale with the measured pesticide concentrations in the groundwater.

In the following section, the advantages, disadvantages and stakeholder perceptions are summarised for the testing of SIRIS in Aalborg (Denmark) and La Voulzie (France) respectively.

Aalborg (Denmark):

  • Advantages: A good surveillance program for experts which can handle leaching of pesticides at catchment level.
  • Disadvantages: The risk profiles generated by SIRIS and the Environmental Yardstick for Pesticides for the pesticides allowed for use in maize, potatoes and winter wheat in Denmark do not always match each other and the Danish Pesticide taxes; e.g. Roundup Bio (glyphosate 360 g/litre) was assessed to have a high risk in France, low risk in the Netherlands and low-medium risk in Denmark. However, comparison of the risk assessments is difficult due to different assessment methods, soil types etc. The differences should be explored further if implementation is to be considered.
  • Stakeholder perception: It is worrying for stakeholders that one DST can indicate that a pesticide should be banned (high risk) in one country, while another DST finds the same pesticide to be safe to use (low risk) in another country.

La Voulzie (France):

  • Advantages: SIRIS is a web-based DST developed for French conditions. It is easy to use for a watershed or water company manager or non-specialist modeller with knowledge relating to transfer of pesticides. Input data is easily available via a database and the DST can easily be applied in other catchments. Overall the DST is suitable for working at the catchment scale and identifies pesticides that must be restricted.
  • Disadvantages: Comparison of results from SIRIS with measured data show differences that are difficult to explain. Some features of the model systematically prevent SIRIS from correctly reproducing the behaviour of certain pesticides. SIRIS does not propose mitigation measures, which means the DST cannot be used for creating scenarios where practices are changed. It is not possible to simulate the impact on groundwater of unauthorized products and metabolites. Difficult to transfer from France for use in other countries.
  • Stakeholder perception: Not evaluated.

SCIMAP (developed in the UK) was tested at Case Study No. 7 site in the Derg cross-border river catchment in Northern Ireland (NI) and the Republic of Ireland (RoI). Overland flow is the primary pathway for contaminants in the case study area. SCIMAP is a GIS-based spatial modelling approach which identifies areas in the landscape (based primarily on an elevation model and incorporated land use information) at greatest risk of overland flow generation, and thus contaminant mobilisation, during rainfall events. DST outputs are maps at a range of scales which can be integrated with other data and used in management decisions. The objective of testing was to assess the potential of the DST as a management tool for stakeholders (water companies, catchment managers) and to aid in prioritising areas for implementing mitigation measures against MCPA pesticide impacts.

  • Advantages: The visual mapping of risk provided by this approach is very useful and intuitive for users. The GIS based system (available also in open source formats) is easy to use with basic training and the maps, once generated, can be used by diverse groups and experience levels.
  • Disadvantages: No consideration of groundwater pathways is included in the model, so it is only applicable in cases where surface flow dominates. The locations of pesticide sources are also not explicitly defined in the model – the user needs to add additional expert information on fields where pesticide applications are likely and combine that with overland flow risk. For the case study the biggest limitation is data availability. The accuracy of the SCIMAP approach is limited by the resolution of the digital terrain model (DTM); a 1-2 m resolution DTM is necessary to resolve high risk areas at sub-field scale and the available 5 m DTM for testing is too coarse. SCIMAP is only as good as the input data used. The software is only available to non-UK users as a web-version going forward and the user must provide all input data.
  • Stakeholder perception: Stakeholders appreciated the ease-of-use of the approach and found the visual maps of results easy to interpret. Some concerns were raised about data availability and costs in NI and RoI. Other countries have LiDAR (light detection and ranging) coverage of the surface of the Earth – in NI/RoI it is only available at high cost from commercial suppliers. The SCIMAP approach is now being used in the INTERREG Source to Tap (»www.sourcetotap.eu) project which is ongoing in the same catchment.

Phytopixal (developed in France) was tested in the Case Study No. 7 site in the Derg cross-border river catchment in Northern Ireland and the Republic of Ireland. Phytopixal is similar in objective to SCIMAP, but is a protocol implemented by the user to produce spatial risk maps that are used to identify areas in the landscape at greatest risk of overland flow, and thus pesticide mobilisation, during rainfall events. The objective of the testing was to assess the potential of the DST as a management tool for stakeholders (water companies, catchment managers) to assess the cost/benefits of available mitigation measures within the catchment.

  • Advantages: As the DST is a protocol rather than an application or toolbox, input data can be selected and defined by the user in whichever GIS platform they are familiar with. Results can be resampled to whichever scale the user requires (farm, sub-catchment or catchment levels).
  • Disadvantages: Phytopixal is a written protocol which has to be developed into a risk assessment framework by the user within whichever GIS software they have access to. This requires a higher level of GIS expertise and more time to set up and test than “off-the-shelf” DSTs. As with SCIMAP, the model is only as good as the input data used.
  • Stakeholder perception: Stakeholders with GIS experience appreciated the protocol-based approach and stakeholders generally found the visual maps of results easy to interpret. As with SCIMAP, some concerns were raised about data availability and costs.

3.2 Cost-effective measures to reduce nitrate and pesticide loads to water

Identifying cost-effective measures to reduce nitrate and pesticide loads to water was the focus of testing the DST Farmscoper at one case study site. The case study site objectives and the advantages, disadvantages and stakeholder perception for the DST are summarised below.

Farmscoper (developed in UK) was tested in the Case Study No. 7 site in the Derg cross-border river catchment in Northern Ireland and the Republic of Ireland. Farmscoper is an advanced export coefficient model which estimates diffuse losses of P, N, pesticides and sediment from single or multiple farms and quantifies the expected impacts and economic costs of mitigating losses to water or the atmosphere. Outputs from the DST are graphical and tabular estimates of contaminant loads, on farm nutrient budgets and the economic costs of measures and combinations of measures.

  • Advantages: Farmscoper is easy to use with an intuitive Excel-based interface. Data are input at farm level and multiple farms can be combined up to catchment scales. The model export coefficient approach has a strong scientific basis. Actual farm data can be used or representative farm type data from censuses. The capability to evaluate the cost-benefits of combinations of mitigation measures is a potentially powerful tool to support water managers in drinking water catchments. Outputs from the DST are clear graphics and tables.
  • Disadvantages: Pesticide usage in the model is not as well-defined as for nutrients and based on general pesticide usage data for England/Wales. Usage in NI/RoI is different and this limits the application of the DST in the case study catchment. It would be possible to modify the DST to account for these differences. Similarly, geo-climatic differences between Ireland and England/Wales mean that runoff estimates are lower than actual when the model is applied. This would require significant re-development of the DST. Farm level data availability is limited in NI/RoI due to farm confidentiality and this will limit the application of the model using individual farm rather than census data. Mitigation measure options and economic costs also need to be updated for NI/RoI
  • Stakeholder perception: Stakeholders were very positive about the potential utility of Farmscoper, particularly in modelling multiple scenarios of mitigation options and identifying which will be most cost-effective. No similar DST exists in NI/RoI and the water companies, in particular, expressed an interest in seeing if the model could be adapted for use. There were some concerns raised about the restrictions of data availability in NI/RoI.

3.3 Cost-effective allocation, location and choice of nitrogen (N) mitigation measures in order to reduce N loads to water

Identifying cost-effective allocation, location and choice of N mitigation measures in order to reduce N load to water was the focus of testing the DST TargetEconN at one case study site. The case study site objectives and the advantages, disadvantages and stakeholder perception for the DST are summarised below.

TargetEconN (developed in DK) was tested in Case Study No. 2 in Aalborg (DK). TargetEconN minimizes the total costs of achieving N load targets in a catchment, down to ID 15 catchment level (i.e. catchments of approximate 15 km2). The model provides detailed results on the cost-effective allocation of N abatement as well as the choice of measures and the amount of each measure. The objective of the testing was to assess how and where to apply N mitigation measures, to minimize the costs of meeting the nutrient load reduction target in the Water Framework Directive (WFD). The testing of TargetEconN will continue as part of Task 5.3 “Assessment of cost and benefits for farmers, water companies and society” in Work package 5 in the FAIRWAY project.

  • Advantages: An advantage of TargetEconN is the identification of which mitigation measures are cost-effective at field parcel level, including which measures to apply.
  • Disadvantages: The data inputs to the model on crops grown and fertilizer inputs are extensive, and was feasible since Denmark has good access to data. A further disadvantage is that the model is set up in GAMS, which is optimisation software that requires expert knowledge to be run.
  • Stakeholder perception: Aalborg Water Utility finds that information down to field level is attractive, but that information about the cost-effective mitigation solutions might not be, as involvement and acceptance by farmers is essential for them and negotiations are part of the solutions. The Ministry of Environment and Food had a contradictory opinion; the Ministry found that field level results are too detailed, but that the assessment of the cost-effectiveness of N mitigation measures is highly relevant.

4. Main findings from the testing of DSTs

The testing of DSTs in the FAIRWAY case study sites has shown that many countries have developed similar DSTs to address similar problems. Thus important steps in the exchange process were to understand what other countries are doing, compare the tested DSTs with existing national DSTs and get some inspiration for enhancing existing DSTs used in the case study sites. In a few cases where no equivalent DST exists, the testing aimed to assess the potential for a DST to be used in that country and to draw on the ideas presented.

The main findings from testing of nutrient management DSTs at the FAIRWAY case study sites are summarised in Table 2.

Table 2. Main findings from the FAIRWAY case study sites testing of nutrient management DST.
The asterisk (*) indicates that these findings recur for Pesticide management DSTs, Table 3.

Nutrient management DSTs
Topic:
  •  All DSTs aim to assist farmers in efficient nutrient use / efficient fertilizer planning.
Input data:
  • Complexity of input data varies* (e.g. number of relevant nutrients).
  • Soil data is an obligatory input, but the DSTs use different soil classification systems.
  • Current crop information is an obligatory input, but information on crop rotation (field history) is not always included.
  • Reliable records on fertilizer use are obligatory, but these are not always available.
  • Weather data is necessary for most DSTs. No single DST covers all EU climate zones.
  • Individual (farm-specific) measurements (e.g. soil mineral N) can be included in some DSTs.
  • Databases must be regularly updated and maintained*.
Output:
  • All DSTs provide information on restrictions on fertilizer use. These, however, are presented in different formats (N-quota, field-specific max. amounts, etc.).
  • Outputs are clear recommendations e.g. max. amounts of fertilizers to be purchased, etc.
  • Advice is provided at different levels* (farm level, field level).
  • The output depends on the quality of the input data*.
  • Mitigation measures: o Hardly any concrete advice on measures*. o But most DSTs can handle catch crops (e.g., Mark Online, Düngeplanung, NDICEA). o Environmental effects of measures are generally not quantified*. o Difficult to transfer from one country to another as the DST is developed for country specific situations (differences in climate, geographic, soil types, fertilizer recommendations, legal frameworks, farming systems, etc.).
Operational issues:
  • Language skills needed (most DSTs and supporting documentation are only available in the local language) and require knowledge of national conditions/site conditions*.
  • DSTs need to be continuously improved e.g. via feedback by users*.
  • DSTs need to be continuously updated and maintained (e.g. to match current law, new findings, etc.)*.
  • Input data has to be updated regularly* (e.g. changes in farm management).

For the pesticide management DSTs several of the main findings from the testing of the nutrient management DSTs recur (marked with an asterisk (*) in Table 2). Some additional findings for pesticide management DSTs are added in Table 3.

Table 3. Additional findings from the FAIRWAY case study sites testing of pesticide management DSTs.
See Table 2 for findings that recur for both Pesticide and nutrient management DSTs.

Pesticide management DSTs
Topic:
  • The DSTs make relevant information accessible and easily available by bringing them together in one tool.
Input data:
  • Exchange of pesticide management DSTs seems difficult because the use of and restrictions on individual pesticides differ from one country to another. Additionally, the risk profiles are not similar.
  • Output for mixtures of products is not always available. This would be beneficial for farmers as they often use this strategy.
  • Pesticide management DSTs that include mitigation measures are difficult to exchange between countries as they have been developed for country- or case study-specific situations and the effectiveness and costs differ regionally.
Output:
  • Several of the tested pesticide management DSTs provide overland flow risk mapping. The visual representation is useful, as it is intuitive.
  • The output and the interpretation can be too simple because not all processes and factors are included in the DST. In this case, a user must understand the background of the DST and its limitations (e.g. only surface water is considered).

5. General overview of DST functionality

For all the DSTs tested, summary information was collated covering cross-case-study issues which could influence future development and implementation. This information was collated and grouped into the following categories: (1) Barriers to exchange (2) Requirements of a DST in terms of functionality, use and access and (3) Stakeholder attitudes to DSTs and mitigation measures.

5.1 Barriers to exchange

During the final selection of the DSTs valuable information about the barriers which may prevent or limit the exchange of a DST from one country to another was collected. The information from each participating case study site was collected in Evaluation Scheme 0 (see Appendix). Additional barriers were identified during testing and are described in Part 2 of this report. Table 4 summarises the identified barriers.

Table 4. Identified barriers to the exchange of DSTs from one country to another.

Barriers Note
Language At the outset of the project, all countries, responding to an assessment of 36 potential test DSTs (see Table 5 in report D5.1, Nicholson et al., 2018), identified language as a key barrier to transferring DSTs from one country to another. As reported in Task 5.1, often the DST and supporting information are only available in the local language (Nicholson et al., 2018).
Lack of support / documentation For some DSTs the case study test groups identified lack of support and supporting documentation as a barrier to exchange.
Specialist software or skills required Some of the complex DSTs require specialised personnel to run them and interpret the results (e.g. the DST requires expertise in GIS).
Software access Some DSTs are commercial products requiring passwords for login. If the DSTs are not owned by project partners, software access has been reported to be a barrier to exchange
Financial cost For several DSTs financial cost has been reported to be a barrier for exchange from one country to another.
Data requirements There is a wide variation in the data requirements for the DSTs as they vary in sophistication. Thus, most case study sites reported that data requirements might be a barrier for transferring a DST from one country to another. For example, in Northern Ireland little farm data is publically available, in contrast to Denmark where a large amount of data is publically available. Since different classification systems are used in different countries, data conversion to the required format is often required. This is crucial since the quality of the input data determines the quality of the output.
Developed based on country specific legislation Some DSTs are developed based on country specific legislation, which is a barrier to a direct exchange of the DSTs. However, part of the DST and/or the principles could be exchanged. For example, Mark Online (DK) was successfully tested in Lower Saxony and it was found that some elements could be integrated into the German system. However the different legislation and its implementation in Denmark and Germany must be respected and limits the direct exchange of a DST between these countries.
Differences between regions (e.g. climate) / farm types Regional differences can present a barrier for exchange (e.g. the precipitation pattern in Britain and Northern Ireland is not the same) or farm types (e.g. farms in Slovenia are much smaller than farms in the Netherlands). Generally, it is difficult to exchange software if it is calibrated to national conditions.

Due to the identified barriers (Table 4), the results of the testing of DSTs in the FAIRWAY case studies concluded that direct exchange and implementation of a DST is generally not possible. In all cases it was reported that some kind of adaption/re-development of the DST would be required first. However, in many cases the exchange of a conceptual model and/or specific functions or modules would be possible.

Furthermore, every country, at some level, seeks ideas/inspiration for developing their ‘own’ DST rather than using an existing DSTs, and often we ‘reinvent the wheel’. DSTs are often developed with government funding to address a specific need in that country or region. The funding is not provided for the benefit of other “potential” users elsewhere in the EU (the additional cost that this would entail cannot be justified). Commercial applications face similar limitations but tend to be less geographically constrained e.g. is Plant Protection Online applied in Denmark, Baltics and Poland. A new EU DST that is currently under development is the Farm Sustainability Tool for Nutrients (FaST) which aims to help all farmers in the EU manage the use of nutrients on their farms (https://ec.europa.eu/info/news/new-tool-increase-sustainable-use-nutrients-across-eu-2019-feb-19_en). The FaST is not yet available for assessment as part of the FAIRWAY project, however it will be interesting to follow the development, performance and implementation of this DST, as it is the first farm nutrient management DST developed with full EU coverage. The strategies it incorporates to avoid the issues and barriers identified in this study will be of great interest to DST developers and stakeholders in all regions.

These findings are very much in line with the research of Rose and Bruce (2018) and Lundström and Lindblom (2018) who concluded that involvement of stakeholders in the development of a DST is a prerequisite to successful implementation. This prerequisite has not been met in any of the attempts to implement the DSTs in the designed exchange processes reported here. A more logical pathway is to organize exchange and inspiration at the level of the researchers involved, and give them the opportunity to set the timing and approach for incorporation of the intellectual harvest of the exchange into their own scientific and stakeholder communities.

5.2 Identification of DST requirements in term of functionality, use, and access

Information on the requirements of DSTs in terms of their functionality (cost, accessibility, data input and output formats, interoperability with other DSTs), use and access was also identified during the testing.

Functionality:

  • A DST must be simple (user friendly, self-explanatory application), not too time-consuming and practical for farmers/advisors to use. However, the level of complexity depends on the target users and the objective of the DST. Sometimes more complexity is needed; particularly for DSTs that operate at the catchment scale and if complex environmental interactions are simulated.
  • DSTs which can complete complex calculations (e.g. nutrient load calculations, pesticide dosage needs etc.) for the user with minimum data input requirement are useful. However, the DST should still provide some flexibility in order to react to specific situations (e.g. extreme weather events, specific regulation in some areas, etc.) and respect user judgement (e.g. on allocation of nutrients in an agronomically sensible way).
  • The DST should support and secure correct advice in regard to e.g. cross-compliance checking.
  • Free availability of reliable data and open source formats are important for innovation, development of (new) DSTs etc. Restricted access to farm data (e.g. in Northern Ireland) limits the extent to which DSTs can be applied and new DSTs developed.
  • Introduction of new regulations (which are usually more complex) must be supported by providing some assistance for those affected. DSTs to ensure that farmers and other end users comply with legislation are helpful. Furthermore, clear information about the derivation of the outputs produced by the DST should be provided (e.g. data source, assumptions applied etc.). However, it must be simple and easy to see whether the legislation/rules are being followed.
  • When new regulations or scientific findings are introduced, DSTs must be updated immediately if they are to retain their relevance and the trust of the end user. A well implemented, simple-to use DST can help to ensure that farmers and other end users comply with legislation.
  • Consistency in outputs between different DSTs is important. For example during testing at the Aalborg (DK) case study site, the Environmental Yardstick for Pesticides, SIRIS and the Danish Pesticide tax system all gave different results for the risk from pesticides applied to certain crops. This does not inspire stakeholder confidence.
  • Financial support/funding is important to develop, update and implement DSTs. Generally, it is important that DSTs are updated regularly to make sure they comply with the newest rules, scientific knowledge etc. in order to increase trust and thus the adoption rate of a DST. Governments may consider paying for upgrades, development etc. as, farmers will rarely pay for them; however, this depends on the type of DST and the benefits farmers can obtain from it.

Use:

  • Advisory assistance is needed in order to encourage farmers to use DSTs, to assist in their application and to interpret their results. Thus, the success of a DST also crucially depends on the skills and experience of the advisor, who should be able to understand both the science and the applicability of the DST.
  • An advisory service system is an important requirement in order to establish recognised communication pathways with farmers. On a personal level, one to one talks are often the most powerful form of communication. Additionally, the advisor must have the skills to communicate complex issues to farmers.
  • When applying a DST, a user must be made aware of any potential financial or other gains in order to change their behaviour (e.g. increased crop yield; reduced pesticide costs; improved water quality).
  • Successful use of a DST is likely if end users and stakeholders to some extend have be involved in the development of the DST, as the DST can be targeted to the needs of the end users.
  • Public recognition of success will be beneficial especially for DSTs applied at catchment level i.e. demonstration of best practice.
  • Government involvement in getting a DST adopted by farmers may, in some cases, increase its uptake and use. Currently adoption is often decided by market forces.

Access:

  • DSTs which are accessible online via PC and mobile apps are likely to have higher take-up, however in some cases poor internet connections may limit the access and lack of technical knowledge may deter some users.
  • Some DSTs should be free because they benefit the environment (common good). However, in many cases farmers use them because they gain economic benefits from reducing the pesticide/nutrient load not because they want to reduce the environmental impact. It is recognised that not all DSTs can be free, as commercial developers must get money to continue to produce and improve the DST if there is no public funding available.

5.3 Attitudes towards decision support tools and mitigation measures

The attitude of users towards the tested DSTs and the mitigation measures incorporated within them can be summarised as follows:

  • A DST must be user-friendly and intuitively designed, i.e. have a clear structure, possibly with a modular design with a stepwise form that helps with fulfilling complex tasks, complying with rules etc.
  • The results must be trustworthy and reliable. Thus, the DST must be based on sound evidence/knowledge. Information on data sources used should be provided.
  • Supplementary information (manuals and supporting documentation) must be available in the national language or at least in English to answer the most frequent FAQ.
  • The DST must be frequently updated to make sure the software complies with the most recent legal restrictions.
  • A centralized and holistic approach should be taken, where data only needs to be entered once. There should not be a multitude of DSTs available for a single purpose as this can lead to confusion; integration of ‘smaller’ DSTs into a single package may be beneficial.
  • DST should contain some “reality checks” in order to avoid data input errors.
  • It is advantageous, if it is possible, to make easy multiannual analysis of data possible.
  • The DST must provide clear results and outputs; graphical representations can be very useful in some cases.
  • It can be useful to provide various ways for data to be input and output (web-interface, excel-sheet, pdf, etc.) to suit the user’s preferences. In FAIRWAY Case study no. 3 in the Anglian Region (UK) agronomists, farm advisors and farmers were asked about their general opinion of DSTs. It was clear from this group of respondents, that DSTs encompassed in existing software were deemed most useful. Detailed background explanations of many of the points above can be found in Part 2 of this report.

 


Notes:

For full references to papers quoted in this article see »References

Download the full report for the Annex and original figures and tables

 

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