Applying System Dynamics


The traditional approach in Canada and North America to water infrastructure asset management has been to look at a series of life cycle questions.

The process typically goes like this:
1)    What do we have?
2)    What is it worth?
3)    What condition is it in?
4)    What do we need to do to it?
5)    When do we need to do it?
6)    How much money do we need?
7)    Where do you get the money?

Although this approach has worked well, it does not take into account the full life cycle of water systems, such as interactions between the physical infrastructure, finance and social political sectors.  An example of this is the price elasticity of water demand where increasing water rates can result in permanent water conservation, which in turn can result in a reduction in utility revenue when billing is based on consumption.

If the system has multiple interacting feedback loops, then it is expected to exhibit complex non-linear dynamic behaviour. A system is complex when the system is counterintuitive, it resists policy changes, can be defeated externally when corrective actions are applied and often exhibit long-run response that are contrary to the short-run response. These are all characteristics of water utility systems.

In Rehan et al. (2011), the authors argue that water and wastewater systems are complex systems where significant interconnections and feedback loops exist between the physical, finance and social political sectors. They also show that the impact of feedback loops and complex interactions between integrated water, wastewater, financial and social sectors will have a major impact on the utility long-term financial sustainability if they are not considered.

The researchers did this by constructing the first-known system dynamic model that takes into account complex interactions and feedback loops then run the model to simulate 100 years of system behaviour.

System dynamics (SD) is a methodology and mathematical modeling technique for framing, understanding and discussing complex issues and problems. It was originally developed in the 1950s to help corporate managers improve their understanding of industrial processes.

System dynamics has found application in a wide range of areas, for example population, ecological and economic systems, which usually interact strongly with each other and currently being used throughout the public and private sector for policy analysis and design. What makes using system dynamics different from other approaches to studying complex systems is the use of feedback loops and stocks and flows. These elements help describe how even seemingly simple systems display baffling nonlinearity.

In 2010, myself and Drs. Andre Unger and Carl Haas at the University of Waterloo, in Ontario, Canada, received a Natural Science and Engineering Research Council (NSERC) Collaborative Research Grant to develop a novel system dynamics model for water infrastructure.

Supporting and collaborating in the research project are the local cities of Waterloo, Cambridge and Niagara Falls. The goal of this research project was to develop a systems dynamics water infrastructure tool that can be used to simulate the city’s wastewater and water distribution networks over 50 to 100 years.

The SD modeling approach is developed in Rehan et al. 2013a and 2013b for wastewater utility management. In Rehan et al. 2013a, the SD wastewater model is fully developed while in Rehan 2013b, the developed SD wastewater model is populated using local utility data and used to show how the utility could effectively formulate and test alternative long-term (75 to 100 years) management policies to eliminate the infrastructure deficit and financial sustainability.

In Rashid 2013c ,a fully developed water network is developed. Using data from local Ontario, Canada, water utilities, the SD models have been used to investigate:
1) Long-term (10- to 50-year) fee hike rates required for system financial sustainability,
2) Service and financial performance metrics for pay-as-you-go, borrowing and capital reserving strategies
3) Consumers affordability due to water use charges.
Key findings to date shown by the SD water models are:
1) Water price elasticity of demand has a large impact of the financially sustainable user fee and not accounting for it will result in a significant revenue shortfall.
2) Doing no capital works is a lot more expensive than investing in long-term capital programs.
3) Borrowing to complete capital works programs can be good business especially when reductions in operation costs are order of magnitude greater than borrowing interest costs.
4) The development of cash reserves can be an effectively strategy for some water utilities to reduce future user rate shock.
5) Water rates need to increase annually over the long-term to ensure financial sustainability.
6) Currently, it is normal practice for Canadian water utilities to develop five- to 10-year tactical asset management plans with one- to two-year operational plans. Tactical plans typically include rate increases and development of programs to be completed over the next five years.

Operational plans consist of specific annual capital works and maintenance projects. Rarely are strategic plans developed that look beyond 10 years, even though in New Zealand 30-year plans are now government mandated. When these long-term plans are made, they are often done without taking into account complex inter connections and feedback loops.

Using the SD model five- to 10-year tactical plans, as well as, strategic management plans that range from 10 to 100 years can be developed and tested. By the developing of 10- to 100-year strategic plans  and evaluating and modifying the plan over time, the water utility will be well prepared to ensure that water fees are sufficient to meet current and future needs without any major surprizes and shocks, such as a cohort of pipes reaching a critical age. It will also drive rational and defensible operation plans, long-term rate increases, as well as, cash reserving and borrowing.

Since each water utility has unique characteristics (i.e. pipe materials, age distributions, etc.), a unique representative system dynamics model will need to be constructed if realistic future model forecasts are to be produced. The impact of different strategies on system performance can be simulated using the model. Alternative strategies can be compared in terms of performance indicators, such as fractions of pipes in various internal condition grades, average condition grade of the network, sewage fee, water demand, total sewage and extraneous flows, annual and cumulative values of various expenditure categories, revenues and fund balance of the utility.

The SD model also needs to be tested and validated over time to ensure that the network system is modeled accurately. Collection of performance data over time can be used to calibrate, validate and update the model. Repeating this process will improve customer, regulatory bodies and government agencies confidence in water utilities strategic, tactical and operational asset management, financial and water management plans that can help reduce or eliminate infrastructure deficits over a specified planning horizon (15 to 20 plus years).

The SD model can also be used as education tool for the public and politicians to demonstrate the impact of short-term decisions on the network long-term performance and infrastructure deficits/backlogs. Model data population along with regular updating will also assist the utility identify and understand critical data gaps and how data flows across organizational groups such as engineering, finance, planning, and information technology. This can help identify and reduce information silos within and across the organization which will in turn improve organization efficiencies.
Dr. Mark Knight is executive director of the Centre for the Advancement of Trenchless Technologies (CATT).

References:
Rehan, R., Knight, M. A., Haas, C. T., and Unger, A. J. A. (2011). Application of system dynamics for developing financially self-sustaining management policies for water and wastewater systems, Water Research, 45(16), 4737-4750.
Rehan, R., Knight, M. A., Unger, A. J. A., and Haas, C. T. (2013a). Financially sustainable management strategies for urban wastewater collection infrastructure – development of a system dynamics model. Tunnelling and Underground Space Technology, http://dx.doi.org/10.1016/j.tust.2012.12.003
Rehan, R., Unger, A. J. A., Knight, M. A., and Haas, C. T. (2013b). Financially sustainable management strategies for urban wastewater collection infrastructure – implementation of a system dynamics model. Tunnelling and Underground Space Technology, http://dx.doi.org/10.1016/j.tust.2012.12.004
Rehan, R., Knight, M. A., Unger, A. J. A., and Haas, C. T. (2013c). Development of a system dynamics model for financially sustainable management of municipal watermain networks, Water Research, 47(20), 7184-7205.

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