Sustainable Turf Management Model

With the range of equipment, materials and technologies as well as the time pressures on staff, overall staffing levels and skills shortage within the grounds care industry, the need to manage resources to achieve desired outcomes in a cost-effective and efficient way is a key imperative for a grounds manager. The use of an interactive model (i.e. a decision support system) which focusses on the desired turf surface outcomes can aid in improving decision making in managing turfgrass surfaces.

Posing a question such as ‘Why don't you use the range of data available, whether current or uncaptured at the moment, within a decision support system?' can often be met with the response of ‘We already produce excellent (or suitable) surfaces for the resources we have so don't need such a system, and even if we did, we wouldn't have the time to gather any more data'.

If someone is happy to continue as before, without giving further consideration to whether they are using their (well actually their employer's) resources as effectively and efficiently as possible, and if budgets are of little concern (although even for elite clubs this is still an important factor that grounds managers will need to consider because budgets are not unlimited, and expenditure should still be justified) then clearly they might not be bothered or see the need for a decision support system.

Without being shown the benefits of a decision support system when it is used appropriately to inform on decision-making, then it is quite reasonable to expect the type of typical response given above. Unfortunately, education and training, in particular continued learning throughout a career, has not often taken the level of importance seen within many other industries, with many employers focusing on the needs of the present with limited thought to how improvements within technology etc. can be best incorporated and utilised by the workforce in their processes and procedures.

Continued learning should be a planned process within any organisation so that when changes occur within an industry they can be reviewed and taken advantage of more easily than without a planned process being in place. Having an interactive decision support system (which is essentially a model) can help to support the better use of these available resources, being able to analyse different scenarios to help decide on the ‘best option', which should also improve the financial bottom line of a business.

Different types of model can be developed, but the focus here is to consider some of the features of what might be included within a sustainable turfgrass management model. The following provides just an introduction to some of the complexities in creating an initial baseline model.

What is a model?
This in itself is an engaging and thought-provoking question. A good description for a model is that it provides "abstract representations of the form and functioning of systems" (de Neufville and Stafford, p.257).

A particular requirement of a model is that it should reduce complexity and promote understanding, providing a learning experience that leads to reflection and further investigation (Pearson & Ison, p.14)

Other important requirements of a model are that it should be intuitive to use, readily accessible, for example as a web-based application, and offer clear guidance on outcomes. If a model is to be useful in helping support decision making, then it must be functionality and ease of use will be important criteria.

What is being considered here is the production of a detailed representation of a turfgrass system which can be used to plan maintenance activities in achieving defined performance outcomes. The model will need to factor in the purpose and impact on outcomes of each activity. For example, is the purpose of a fertiliser application to increase grass growth (not really?) or is it to help develop a hard-wearing sward (definitely). Clearly to create the latter there is going to be grass growth but the focus is really on 'development' and 'hard wearing' which is a nuanced difference from a specific aim of encouraging grass growth per se.

What impact will activities and associated soil environmental data also have on root growth, thatch development and soil bulk density in particular? These are all factors that an informed turf manager will want to know when considering any maintenance and management programme. How is the carrying capacity of the surface affected by the management practices undertaken? How is the quality of user experience affected by the range of variables? What are the metrics or indicators to be used to measure and evaluate how successful the management practices have been in achieving, or moving towards, the aim of sustainability? It would certainly be useful if these types of questions could all be answered, or at least have a high probability of accuracy, and agreement, by such a model.

Three major types of models are identified by de Neufville and Stafford (p.261):
1. Naive model, which is a basic construct to help develop ideas further and to demonstrate a concept.
2. Simple correlative forecasting model, which is used for basic forecasting based on some interconnected variables.
3. Causal models based upon a priori understanding of a system, providing insight to the issue being investigated by factoring in cause-and-effect outcomes allowing for a more predictive approach to modelling to occur.

The complexity of the task to devise a comprehensive sustainable turfgrass management (causal) model is not to be underestimated, however, this does not mean it is not something which should not be attempted. In practice this will be a very iterative process as part of a model's ongoing development and refinement.

Modelling something as seemingly simple as estimated grass growth has proven challenging for researchers. A model which aims to incorporate a wide range of core technical data which a grounds manager needs to know to most effectively and efficiently manage a turfgrass surface presents many more challenges but will be of considerable value to managers in relating inputs to usage, quality and sustainability of outcomes.

There is a considerable amount of literature which can be investigated to help provide a useful and informed background to creating an initial model.

A useful starting point is to identify many (others would then follow upon further reflection and review) of the core features which would need to be considered within a sustainable turf management system. The main turf maintenance activities can then be identified along with a rating for how much of an impact the activities might have on the core features. Further information can also be identified to provide an indication of the potential control a turf manager might have on the core features. Advanced technologies such as enhanced lighting, enriched CO2 or undersoil heating are potential ways in which a manager can influence and control some of the core features, although due to installation and running costs these technologies would only be available to those with relatively large budgets.



For a model to reflect sustainability a systems analysis of each activity (i.e. a function) would be needed. This process will help identify the inputs needed to carry out the function, the constraints that might be imposed on it, the resources needed to achieve the activity and then the outputs from the activity. These analyses would most likely form a sub-set of the main model as it is a distinct feature with different calculation requirements.

To help visualise the concept further, but only at the 'naive' stage, the creation of a simple spreadsheet could look at the core features, provide a monthly rating (using a scale of 1.0, meaning optimum, to 0.0 meaning no value is registered) for how the feature might influence a system. A graph can be used to illustrate how the many variables might influence the grass growth (height) as well as potential mowing requirements. At these initial stages the model would be classed as generally juvenile as the formula for the data analysis would mostly be linear in calculation and this would need to be adjusted to better reflect natural growth and the impact the interactions the different variables can have between them, but the main point of the spreadsheet at this early stage would be to demonstrate, visually, some basic theoretical impacts.




Playing experience outcomes would also be included as the model develops, as these will be the key features which users will judge the quality of the surface.