Essay: Sustainable urban water management

Of the Earth’s 1,386 million cubic kilometres of water, only 2.5% of that quantity is fresh water and nearly one-third of this smaller amount is available for human use (Postel et al., 1996). Urban inhabitants represent 54.5 percent of global population by 2016. About 30.5 percent of global population lives in small urban habitations (cities/towns) with numbers less than 1 million (Demographia, 2016). Small cities/towns are of considerable strategic importance for cultural, economic and social development especially in developing countries.
Water services are a crucial element of the liveability and sustainability of cities (Binney et al., 2010). Water services in urban context primarily has three different operations ”’drinking water supply”’; ”’wastewater collection and treatment”’ and ”’storm water management”’. Water services (water supply) collect water and transport it through buried pipes to consumers through water treatment plant; the accumulated wastewater further goes through another set of buried pipes from consumers to wastewater treatment plants and finally to the source or sink. In most modern cities the storm water also goes through the wastewater system or a separate system to the water body to avoid urban flooding. This infrastructure represents a significant capital investment and future generations will inherit the outcomes of society”’s ongoing investment decisions (Marlow et al., 2010a; Wong and Brown, 2009; Burn et al., 2012). Therefore management of water system is a critical factor in urban sustainability (Schaffer and Vollmer, 2010).
Urban water services to a growing urban population in small cities and towns, especially to the poor who are located in the fringes of cities, is a big if not the biggest challenge for water service providers (Management models for the provision of small town and peri-urban water services in Ghana, 2013). Unlike larger towns or cities, smaller towns often lack the financial, political and human resources to independently plan, finance, manage, and operate their urban water services (Pilgrim et al, 2007). The unit costs of small town water services are generally higher than those of rural water services and large cities as they are not benefitting from the economies of scale and cross-subsidies of large (urban) utilities (Marieke Adank, 2013). Most small cities/towns in developing countries have a water supply system with few having a wastewater collection and treatment system and storm-water management; thereby resulting in incomprehensive urban water management.
Sustainable development has been defined as development that meets the needs of the present without compromising the ability of future generations to meet their own needs (WCED, 1987). Analysing these definitions and putting in the context of cities it reveals that on one aspect it demands provisions to be made to meet the needs of its inhabitants and improve the quality of human life. On other hand it shouldn”’t also challenge the viability of supporting ecosystem””” . . . reducing Ecological Footprint (energy, water, land materials, waste) while simultaneously improving quality of life (health, housing, employment, community . . .) within the capacity constraints of the city”’ (NSW government, 2005).
Sustainable urban water development focuses on the need for a balanced business approach to achieve the ecological, social and economic parameters, within special emphasis on small cities/towns in developing countries. On one hand it promises all inhabitants, especially the poor to have equitable access to water services whereas on the other hand it promises ecological properties of the sink and source is ensured.
Urban water management remains a complex and fragmented area relying on traditional, technical, linear management approaches (Brown and Farrelly, 2007).  Many government, private and non-government players are involved in operating and maintaining urban water infrastructure, with different interest and sustainability approaches. The urban water cycle should be managed as a single system where the interconnectedness of water supply, groundwater, storm water, wastewater, flooding, water quality, wetlands, watercourses, estuaries and coastal waters is recognised (Western Australian Planning Commission, 2008). There is a lack of knowledge of how sustainable development should be attained and how sustainability of various technical systems should be assessed (Hellstorm et al, 2000).
Sustainable urban water management is either managed quantitatively based on economic-ecological indicators, which have a set of boundary values and conditions or qualitatively based on socio-cultural-conservation values, which are determined emotionally. This paper approaches to develop a system of sustainable urban water management which is a combination of indicators (Performance Indicators), which when modified based on certain set of inputs and output (Data Envelopment Analysis) parameters through a linear programming approach to measure relative performance and also simulate the role of stakeholders through Agent Based Modelling to assess the behaviours. This three prong approach will improve the quality of benchmarking and reduce or minimise the shortfall of each approach. This approach will help to take the advantages of different methodologies and comparison between several entities equitably; this approach could be    implemented for a developed or developing urban city. The comparison will result in sustainability benchmarking of urban water services and management using various set of technologies and management principles.
In view of the above, it is therefore suggested to have sustainability benchmarking of urban water management especially for small cities and towns; so that the same set of parameters can be used for developed and developing cities working under different guidelines and schedules.
US President Franklin D. Roosevelt  stated ”’The test of our progress is not whether we add more to the abundance of those who have much; it is whether we provide enough for those who have too little”’. Technology has made great impact on the way that we use and manage our water resources. It has made it much easier to transport water through time and space and in most cases remove or inactivate the harmful elements in water. Yet with such advances we have only increased the schism between the haves and have nots making the urban water distribution unsustainable. Wong (2006) suggested that to advance sustainable urban water management technologies, an understanding of the socio-institutional aspects of governance is required.
Sustainable urban water management is guided by socio-economic and legislative factors making it difficult to understand how single action affects the entire system (Geldof, 1995), leading to technical and management challenges. The world”’s fastest growing cities are located in low- income countries and are characterized by poor water infrastructures and pressures of increasing population and economic development resulting in unsustainable water quality management (Huang et al, 2001). Water is at the core of sustainable development and also at the heart of adaptation to climate change and disaster risk reduction; it is an important link between the climate patters, human sustainability and the ecological balance. The development of water resources for ecological, social and economic processes forms complex management principles, which are associated with the sustainable development of urban centres within the realms of climate change and disaster risk reduction. Safe water is critical in decreasing the disease load thereby improving health, child development, productivity and well-being of population. Changing weather patterns, rising temperature and large variations in precipitation contribute to, increased damages caused by weather related disasters, including floods; one of the major contributors to increasing flood peaks are land use changes and particularly urban development (Roumen et al, 2003).
The emerging controversy about the sustainability of alternative concepts in urban water management depends on different views of sustainability, therefore pressing for a comprehensive but feasible definition (Starkl and Brunner, 2004). Although there has been a paradigm shift in terms of urban water management especially for large cities in developed countries yet there has been very little evidence in terms of benchmarking or urban water management especially for small cities and town in the developing world.
In urban water management, the key aspects of performance management are environmental sustainability, cost reduction, revenue collection, waste management, improved service, and asset management. Better performance management means informed actions rather than unplanned reactions to system failures and organisational malfunctions. When sustainability aspect of urban water management is assessed through performance indicators, it helps to address not only short term and long term issues, but also appropriate sustainable technology. Unfortunately indicators can often be vague when used for benchmarking because of differential input-output parameters and working conditions that exist between different entities. A linear programming based technique for measuring relative performance called data envelopment analysis is being used which involves levelling the performance fields by using relative inputs and outputs but again they fail to assess the behaviour of stakeholders. Given the complexities of managing water resources, agent-based modelling (ABM) can be an effective approach to simulate the views of all parties (Bandini et al. 2009) because stakeholder approach and behaviour are very important to benchmark a process or system.
Performance indicator based benchmarking is very popular and widely used but indicators have some limitations and often fail to compare between two entities that have differential performance criteria”’s. To minimise this limitation the research would use a linear programming based comparison model, which will work on the set of inputs and outputs, often based on normalised indicators, this is called DEA. DEA has several advantages of assessing quantitative and qualitative indicators for benchmarking, yet it fails to model the behaviour and reaction pattern of specific stakeholders; it is therefore suggested to use agent-based modelling which is again a computational model to simulate the behaviour of stakeholders.
The key objective of the research is to develop an advanced sustainability benchmarking or urban water utilities and management through a 3 point approach. The sustainability benchmarking would be done through three tier approach. One would be by using performance indicators, secondly using DEA and last through agent based modelling so that the benchmarking is not only comprehensive but also realistic and real time. The research will make a compendium of performance indicators for sustainability benchmarking of urban water services. These indicators will be assessed through various input-output parameters, for this a linear programming approach will be followed to draw comparisons, known as data envelopment analysis. This approach will reduce the limitations of the indicators. Additionally, organizational perceptions are difficult to assess, therefore a simulation technique popularly known as ”’agent based modelling”’ will be applied to capture behavioural nuances. Below are the specific objectives this research will help achieve:
”’ Understand the present mechanism to assess the performance of urban water services and management and study cases of different cities
”’ Document a list of sustainability indicators through extensive study of different benchmarking of urban water services done globally
”’ Using the list of suitable sustainability performance indicators, assess the urban water services and management over period of a year, to assess the seasonal variation
”’ Screening the performance indicators through several input-output parameter and thereafter benchmark the urban water services and management through data envelopment analysis (DEA). Also asses the scope of improvement of urban water management.
”’ Simulate the behaviour of different urban organisation perception towards sustainable urban water management through agent-based modelling.
The key research question is ”’how performance indicators, agent based modelling, and behaviour simulation, help devise most suitable mechanism to achieve sustainability benchmarking?
Following exploratory questions will also lead to study of key research question:
”’ What are the present mechanism of sustainability assessment and benchmarking of urban water utilities and management?
”’ Which popular and relevant sustainability benchmarking methods are used globally to assess urban water utilities?
”’ What are the best sustainability performance indicators, and input-output parameters which need to be assessed? Which key organisations require behaviour simulation assessment? Is DEA and agent-based modelling a suitable method to assess the sustainability of urban water utilities and management over period of a year?
Although there are many definitions of sustainable development, the most prominent amongst them are from WCED (1987), ICLEI (1996) and IUCN, (1991). Analysing these definitions in the context of urban water, reveals that   they demand provisions to meet the needs of health, hygiene, and development of its inhabitants, especially the urban poor in developing cities; additionally,   they should also support, the ecological viability of resource conservation and waste reduction. Tools and new technologies are facilitating implementation of improved practices at the project scale, such as stormwater treatment systems, models and assessment methods (see for e.g. Chocat et al., 2001; Harremoe” s, 2002; Mitchell, 2006), yet small cities and towns have unsustainable urban water services.
It is within urban areas that most of world”’s resources use and waste generation are concentrated (Hardoy et al, 2001). Being concentrated, cities have an advantage of minimizing infrastructure cost of basic services like water, sanitation and other services like health care and waste disposal. Such concentration of population also raises issues  of hygiene and open spaces for its inhabitants. Technical staff responsible for the management of small town water schemes often does not have ”’.. core skills, which prevents them from managing small piped schemes in an effective, efficient and sustainable way (Marieke Adank, 2013). Apart from financial and technical challenges, other barriers include, institutional fragmentation, poor political leadership, unproductive intergovernmental relations, limited long-term strategic planning, and inadequate community participation (Brown, 2005; Brown and Farrelly, 2009; Hatton MacDonald and Dyack, 2004; Vlachos and Braga, 2001).
Although some recent efforts may be found in the literature (e.g. van der Steen, 2011; van Leeuwen et al., 2011), there is no widely accepted or established method to assess the sustainability level of urban water services. Although there are many challenges towards achieving the sustainable urban water cycle (Brown et al., 2009), it is nevertheless significant to assess how well urban water services are performing in terms of sustainability. Sustainability is usually associated with the triple bottom line framework, composed of social, environmental and economic dimensions or principles (Thornton et al., 2007). Yet some other authors believe that the triple bottom line approach is not sufficient (ASCE and UNESCO, 1998 or Ashley et al., 2003).
The Swedish Foundation for Strategic Environment Research project adopted the metabolism model and ”’health and hygiene”’, ”’social and cultural”’, ”’environmental”’, ”’economic”’, ”’functional”’, and ”’technical”’ categories where the criteria adopted for assessing sustainability were arranged according to their influence on the water and wastewater systems (Hellstrom et al., 2000). Lundlin (2003) also developed a set of sustainability indicators to assess the water and wastewater system. Mitchell (2006) and Monsma et al. (2009) emphasised on integrated urban water management approach for sustainability and considers that all idiosyncrasies of the local context need to be taken into account. Water UK (2010) has 25 indicators to assess the environmental sustainability of water utilities. Research project SWARD developed performance indicator based assessment tool for water services in terms of economic, environmental, social and technical criteria”’s (Ashley et al., 2003, 2004). City Blueprint uses 24 indicators from 8 broad categories to assess sustainability of water utilities including an interactive multi-stakeholder approach (Van Leeuwen and Chandy, 2013).
The fact that the benchmarking has resulted in more than 100 publications not only in Europe, but also worldwide, demonstrates the interest of such a tool within the research community (Jeppsson et al., 2006). In the last few years benchmarking has no longer made headlines, but that is quite possibly because it has now become an established part of business life (Stapenhust, 2009). Benchmarking is defined as the continuous process of measuring products, services and practices against the toughest competitors or those companies recognised as industry leaders”’ (Camp, 2006). Venetucci (1992) defined benchmarking as a process of gathering standards for improvement and insights, which may lead the organization to better performance. McNair and Leibfried (1995) described benchmarking as an external focus on internal activities in order to obtain continuous improvement. It is useful not only for large corporations, but small and medium size companies can reap the benefits of benchmarking as well (McGonagle and Fleming, 1993). Benchmarking creates an atmosphere for change, and provides realistic targets for futuristic improvements and innovations. American Water Works Association defines Benchmarking as ”’a systematic process of searching for best practices, innovative ideas, and highly effective operating procedures that lead to superior performance, and then adapting those practices, ideas and procedures to improve the performance of one”’s own organisation”’ (AWWA, 1996).
Performance Indicators are very popular choice for measuring a system”’s performance and benchmarking. Sustainable Indicators are based on information related to: environmental, operational, personnel, physical, quality of service and economic and financial performance data (Matos et al, 2002). It is important that performance indicators are clearly defined, with a concise meaning and a unique interpretation for each indicator, easy to understand even by non-specialists, easily verifiable (auditable), self-explanatory and always related to well-defined areas and periods of time (Alegre et al., 2000). Performance Indictors may be considered as providing key information needed to define the efficiency and effectiveness of the delivery by an undertaking (Deb and Cesario, 1997).  Indicators may be used as a quantitative or qualitative measure of a particular aspect of an undertaking”’s standard of service (Matos et al., 2003).
Meadows D (1998) states about pitfalls and challenges in choosing and using indicators like ”’over-aggregation”’ (lumping too many things together); ”’Measuring what is measurable rather than what is important”’ (taking easy options); ”’dependence on false model and interpretation”’; ”’over-confidence and incompetence”’. The sustainability indictors proposed to date have therefore tended to concentrate on making best use of available data rather than starting with the question first (Seager, 2001). The reasons that economic and social indicators cannot reflect the full range of factors because no complete list of factors affecting quality of life can be created and the way people weight these factors differs (Ed Diener et al, 2009).
Data envelopment analysis (DEA) is a linear programming based technique for measuring the relative performance of organisational units where the presence of multiple inputs and outputs makes comparisons difficult. DEA is a non-parametric estimation of production functions; it has been used extensively to estimate measures of technical efficiency in a range of industries (Cooper et al., 2000). It is non-parametric because it does not require the analyst to specify a functional form for the production technology (Charnes et al., 1978). DEA estimates either the maximum potential output for a given set of inputs, or the minimum set of input required for a fixed output set; it has primarily been used in the estimation of efficiency. In most management or social science applications the theoretically possible levels of efficiency will not be known (Cooper et al., 2004); DEA is the appropriate tool for efficiency estimation. It has been extensively applied in performance evaluation and benchmarking of schools, hospitals, bank branches, production plants, etc. (Charnes et al., 1994). DEA is therefore a preferred tool to assess sustainability of water services and management.
DEA is also known as extreme point method as it compares input-output of each unit with the best unit in the group. The efficiency score in the presence of multiple input and output factors is defined as efficiency (Srinivas, 2000). DEA provides a comparative monitoring that identifies variations and hence provides encouragement and direction for performance improvement (Abbott et al., 2012). Data Envelopment Analysis (DEA) has proven to be a powerful tool for identifying the best practice frontier (Ali and Lerme, 1997). DEA can be used in various settings where exact numerical values are not possible and also in instances where perception based scores are being used thereby making it a suitable method to measure opinions of stakeholders.
Agent-based modelling (ABM) is a style of modelling in which individuals and their interaction with each other and their environment are explicitly represented in a program (Jeff Schank, 2010). Agent-based simulation has become increasingly popular as a modelling approach in the social sciences because it enables one to build models where individual entities and their interactions are directly represented (Gilbert, 2008). The collective actions of individual components give rise to complex, hard to predict, and changing behaviours of the system (Mitchell, 2009). An ABM framework is developed to simulate urban water resources as a complex adaptive system (Holland, 1995). Several review papers have stressed upon the need to study human activities as a part of water management (Vogel et al., 2015; Wagener et al., 2010).
ABM helps to understand the various interactions between social and cultural infrastructure through a dynamic modelling approach for studying a number of coupled human and natural systems (An, 2012). ABM can be used to simulate a large population like consumers, which can be characterised as agents who make specific decisions about water and land use (Giacomoni & Berglund, 2015). ABM frameworks have been developed to yield new insight about the water availability and satisfaction of water demands based on the interactions of stakeholders, such as farmers (Ng et al. 2011), municipalities (Yang eta la. 2009), hydropower plants, and agencies protecting environmental ecosystems (Van et al. 2010; Guiliani & Castelletti, 2013). Studies use ABM to simulate human behaviors in water end uses and the frequency of changing end uses (Chu et al 2009; Yuan et al 2014); the purchase of water efficient technologies (Klotz & Hiessl, 2005); and the volume of water consumed per day (Moss & Edmonds, 2005). Therefore to assess stakeholder behaviour in sustainability benchmarking, an agent based modelling would be a useful tool to assess the characteristics of various participants.
Measuring and comparison are integral process in our lives and is used in every sphere like ”’car-speed”’, GPA scores etc. Situations which involve human element like satisfaction, aspirations, sustainability and equity are hard to measure quantitatively. Performance ratios such as “sales per employee” or “on-time delivery” and “pupils per teacher” or “average duration of stay” are well known in the private and public sectors respectively but taken alone they give a limited view of performance (Harrison, 2010); it fails to define any unfair practice of sales or low quality of education.
Performance indicators give a better picture of performance but it falls short to answer different aspects of performance like low maintenance cost is good, but poor or deferred maintenance is unsatisfactory. PI can often give variable message susceptible to user”’s interpretations. DEA is a non-parametric linear programming which considers different elements of input and output of a functional unit and thereby measures the efficiency based on how effectively the utility has performed. Within a list of given utilities DEA assumes the unit to be efficient under two conditions (a) if it is not possible to increase any one of the output without increasing and one of the input or decreasing any other output; (b) if it is not possible to decrease any of the input without either decreasing any one output or increasing any other input.
Different stakeholders or agent group react differently to a given situation, most ABM studies use the what-if scenarios to develop insights on water usage, conservation and sustainability (Gal”n et al., 2009; Rixon et al. 2007; Schwarz & Ernst, 2009). ABM is not an accurate measure but helps to simulate the behaviour outcome of any particular stakeholders to a given situation. ABM is often criticized for relying on informal and subjective validation (Edmonds & Chattoe, 2005). Social models are complicated with many features thereby (Bharathy & Silverman, 2012) useful when combined with any numerical method.
This research study will use three approaches to assess sustainability performance or sustainability benchmarking of urban water utilities and management. Using the set of comprehensive indicators it assess the performance perspective using different parameters it further uses DEA to establish efficiency of each utility using the set of inputs-outputs required to achieve the indicator. Since DEA assumes that there is no error in data it is necessary to have higher level of accuracy and validation, similarly based on the utilities processes it is important to choose the kind of DEA tool that needs to be used. Since both the above tool do not simulate the behaviour of stakeholders involved in sustainability of water utilities a third approach of agent-based modelling will be used to overcome this short-coming.
Urban water utilities perform different interactions with water using similar or different technologies and management principles. Utilities are managed by different stakeholders and their national authority; this influence is dependable on the finance, development and political will of the government. Due to variation is working conditions and technology being used it is difficult to directly compare. Using production frontiers will help address this challenge; production frontier (or Production possibility frontier, PPF) are a curve or a boundary which shows the combinations of two or more goods and services that can be produced whilst using all of the available factors efficiently? PF can be calculated using stochastic methods (Battese and Rao, 2002) or non-parametric approach (O”’Donnell et al., 2008). In a stochastic process there can be several outcomes even if the initial state is known whereas in non-parametric methods assumptions on the distribution of sample are not required.
Suitable set of holistic sustainability indicators are required to assess the performance of urban water utility especially in small cities. Urban water utility with low and deferred maintenance cost is not an efficient utility; therefore the holistic indicator should assess the environment functions, physical assets, operational functions and financial sustainability. Comprehensive understanding of urban water based on holistic sustainability indicators gives a better picture. This when assessed through the criteria of simulation of organisational behaviour it gives a better understanding along with sustainability parameters.
DEA is another approach to understand the performance of the urban water utility based on the weight scores of their set of inputs and outputs. The inputs and output that formulate the above indicators are used based on IO-VRS model to assess the efficiency of each water utility. These DEA efficiency scores when tallied with agent-based models simulation it gives a clear idea of the functions of urban water utility.
One of the outputs is a result of literature review and discussions with various benchmarking organizations globally and sustainability initiatives of water utilities.
”’ List of sustainability PI necessary to understand the performance of urban water utilities through sustainability perspective
”’ Explanation of each indicator and the related data required to derive the indicator.
”’ Segregate the indicators between inputs and outputs to be used for DEA.
”’ Data checks and water balance
Another output of the study is the most critical part and herein using DEA benchmarking of urban water utilities will be done using the sustainability data parameters mentioned in previous section. The detailed output will contain the following element:
”’ DEA tools used for analysis and their corresponding data
”’ Factors affecting the efficiency (management and technical factors).
”’ Identify sectors for improvement especially in terms of input measures and also identify peers.
The third and final output of the study would be find the suitable stakeholder whose decision plays the major role in the sustainability of urban water utilities and how they behave in a given condition:
”’ Making a list of key stakeholders
”’ Formulating what-if analysis of each key stakeholder and assess their behaviour pattern.
The research would be helpful to find a set of sustainability indicators for urban water utilities this includes water supply, wastewater treatment and stormwater utilities. This new set of indicator can be used either in developed and developing countries to assess the sustainability performance of urban water utilities. When these sustainability indicators are screened using DEA the utilities can actually learn, develop and adapt observing each other”’s specific areas of good performance. The agent based modelling will help to simulate the characteristics of key stakeholders to the changing scenarios in terms of sustainability.
Develop more local knowledge and interest in urban water utility management ”’ While interacting with people many have reflected that with changing time and within tight budgetary constraints urban water utility has not been able to attract innovations and high quality human resources; this research will be a major step forward in terms of capacity building. There is also a high possibility of publications in terms of sustainability performance management of urban water utilities using a three tier comprehensive approach.