Smart Water Technologies and Techniques E-Book

David A. Lloyd Owen

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Serie: Challenges in Water Management Series
• Sprache: Englisch

Seitenzahl: 554

Veröffentlichungsjahr: 2018

Beschreibung

An Insightful Examination of Smart Water Systems and Technology

Inland water supplies are under increasing pressure. Climate, social, and demographic change have begun tipping the balance toward demand management, as supplies begins to dwindle. Water and wastewater infrastructure will play a central role in the management of this increasingly valuable resource, and Smart Water Technologies and Techniques: Data Capture and Analysis for Sustainable Water Management provides insight on a key part of the solution.

Smart water applications optimise the way water and wastewater services are used, allowing more efficient allocation of limited resources while adding flexibility to the system. Automation, real-time data capture, and rapid interpretation allow utilities and users to monitor, manage, and act on the part of the water cycle that matters to them, minimizing costs of providing service through optimal use of extant assets. 

This book brings together the core principles, key developments, and current state-of-the-art into a single resource that:

• Considers smart water within operational, economic, policy, and regulatory contexts
• Provides a comprehensive overview of the smart water concept and the latest advances in the field
• Examines key considerations and objections raised to date
• Discusses the potential value of smart water, from perception to policy
• Shows how smart water systems can optimize efficiency and flexibility of water and wastewater management
• Explores future directions for smart water development in the pursuit of balanced supply and demand

Although primarily designed for water supply and sanitation, smart water systems may be applied to irrigation, reservoir and dam management, inland water flows, and more, making it a valuable asset as water scarcity begins to spread around the globe. This book answers the questions, assuages concerns, and explains the technology that could revolutionize the way water is accessed and supplied.

Leseprobe

Challenges in Water Management Series

Editor:

Justin Taberham

Independent Consultant and Environmental Advisor, London, UK

Titles in the series:

Smart Water Technologies and Techniques: Data Capture and Analysis for Sustainable Water Management David A. Lloyd Owen 2018 ISBN: 978-1-119-07864-7

Handbook of Knowledge Management for Sustainable Water Systems Meir Russ 2018 ISBN: 978-1-119-27163-5

Industrial Water Resource Management: Challenges and Opportunities for Corporate Water Stewardship Pradip K. Sengupta 2017 ISBN: 978-1-119-27250-2

Water Resources: A New Water Architecture Alexander Lane, Michael Norton and Sandra Ryan 2017 ISBN: 978-1-118-79390-9

Urban Water Security Robert C. Brears 2016 ISBN:978-1-119-13172-4

Smart Water Technologies and Techniques

Data Capture and Analysis for Sustainable Water Management

David A. Lloyd Owen

Envisager Limited Trewindsor Farm Llangoedmor Ceredigion UK, SA43 2LN

This edition first published 2018

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The right of David A. Lloyd Owen to be identified as the author of this work has been asserted in accordance with law.

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Series Editor Foreword – Challenges in Water Management

The World Bank in 2014 noted:

‘Water is one of the most basic human needs. With impacts on agriculture, education, energy, health, gender equity, and livelihood, water management underlies the most basic development challenges. Water is under unprecedented pressures as growing populations and economies demand more of it. Practically every development challenge of the 21st century – food security, managing rapid urbanization, energy security, environmental protection, adapting to climate change – requires urgent attention to water resources management.

Yet already, groundwater is being depleted faster than it is being replenished and worsening water quality degrades the environment and adds to costs. The pressures on water resources are expected to worsen because of climate change. There is ample evidence that climate change will increase hydrologic variability, resulting in extreme weather events such as droughts floods, and major storms. It will continue to have a profound impact on economies, health, lives, and livelihoods. The poorest people will suffer most.’

It is clear there are numerous challenges in water management in the 21st Century. In the 20th Century, most elements of water management had their own distinct set of organisations, skill sets, preferred approaches and professionals. The overlying issue of industrial pollution of water resources was managed from a ‘point source’ perspective.

However, it has become accepted that water management has to be seen from a holistic viewpoint and managed in an integrated manner. Our current key challenges include:

The impact of climate change on water management, its many facets and challenges – extreme weather, developing resilience, storm‐water management, future development and risks to infrastructure

Implementing river basin/watershed/catchment management in a way that is effective and deliverable

Water management and food and energy security

The policy, legislation and regulatory framework that is required to rise to these challenges

Social aspects of water management – equitable use and allocation of water resources, the potential for ‘water wars’, stakeholder engagement, valuing water and the ecosystems that depend upon it

This series highlights cutting‐edge material in the global water management sector from a practitioner as well as an academic viewpoint. The issues covered in this series are of critical interest to advanced level undergraduates and Masters Students as well as industry, investors and the media.

Justin Taberham, CEnv

Series Editor

www.justintaberham.com

Introduction

My involvement with smart water stems from a project examining smart water policy drivers for the OECD (Lloyd Owen, 2012a) and as part of a more general study on urban water services (Lloyd Owen, 2012b). These considered the evolution of smart water as a concept and in reality especially between 2011 and 2012.

‘Smart water’ is not a theory, let alone a paradigm. Rather, it is a catch‐all expression that covers real or near real‐time data collection, transmission and interpretation for improving the delivery of water and wastewater services and optimising the performance of the assets that are used for these. This study is practical in nature, outlining what smart water means from various water management perspectives and how it has been developed and deployed to date. Much of the information is derived from conference presentations and articles in water sector publications rather than academic publications. This book is neither a technical nor an academic study. Instead, it considers smart water’s potential to address a range of challenges currently facing water and wastewater management worldwide. Market drivers are reviewed along with the markets themselves, their size, growth and social, regulatory and environmental drivers. This book considers how the practicalities and prospects of smart water as perceived in 2016–17.

Making technologies work matters. Despite considerable regulatory, financial and political support, slower than anticipated development of practical energy storage has delayed the widespread adoption of electric cars by more than two decades. Smart water hardware development has not seen such technical setbacks. The challenge for commercialising innovation in smart water lies in raising funds and encouraging its adoption in an inherently conservative sector.

The most notable change since 2011–12 has been in the way smart technologies are being applied. The rapid and hitherto unexpected rise of smart phones for example has transformed the scope for mobile smart water monitoring and analytics. In developing economies, this may bring about truly disruptive changes. If a second edition of this book is published at some point in the future, the changes and their impact in those countries are likely to be appreciably greater than those that have been experienced to date.

Another change since 2011–12 is the gradual replacement of theories with realities. A difficult investment climate has meant that a significant number of intriguing innovations seen in 2011–12 have fallen by the wayside. Some of this can be seen as the natural consequence of attrition, yet there is always the fear that genuinely useful innovations can be lost during a particularly hard period for early‐stage companies. A contrary point of view would be that products and services which can reach commercial viability under these circumstances may have the potential to offer a real and lasting benefit to utilities and their customers alike, having proved themselves in such a testing environment. It is also noticeable that despite many setbacks and the usual challenges in bridging the gap between blithe optimism and cooler realities, smart technologies and their applications are being more widely adopted.

Industrial water will only be covered in passing. Given that industrial clients are usually more open to innovation than municipal clients, as they are driven by the need to carry out processes in the most efficient manner, this may appear to be anomalous. This is in part due to the fact that industrial facilities are regarded as stand‐alone entities, rather than being parts of networks, even when they are connected to municipal supplies. Their operations are relatively compact and most water and effluent assets operate above ground, making physical inspections more effective. As industry is driven by the need to be efficient in order to be competitive; smart applications that can improve the value generated by each unit of water consumed will be adopted where needed.

Smart water is evolving in an appreciably faster manner than is usually seen for the development and deployment of goods and services associated with drinking water provision and sewerage and sewage treatment. As a book, this is therefore a child of its time. It aims to present how various goods and services were being developed and deployed at the time of its writing in 2015–17, in the context of the author’s experience with the concept since 2011.

An overview of the ‘trajectory’ of the deployment of smart water products is offered through examining third‐party surveys (Chapters 1and 7) as to their future extent, and at the end there is an attempt to suggest where the various initiatives that have been described could lead us, in terms of a truly integrated water and wastewater management system.

This book would not have been possible without the support, insights and information that a wide variety of people have given me.

Xavier Leflavie and Gerard Bonnis oversaw my project for the OECD in 2011–2012. Sophie Treemolet and Bill Kingdom managed a project on capital efficiency at the World Bank in 2016–17 which provided insights into the potential for smart water in developing economies.

Three organisations have been of particular value in organising conferences dedicated to smart water: The Chartered Institute of Water and Environmental Management (CIWEM), the UK’s professional body for water engineers; SWAN (Smart Water Networks) Forum, a UK based organisation dedicated to developing smart water; and SMi, a conference company that has hosted a series of smart water events. Presentations at their events have been indispensable for developing the case studies. Mark Lane at Pinsent Masons also deserves thanks for the ‘Wet Network’ events he has organised over the past decade along with support from Arup. Oliver Grievson (Anglian Water) has been a great evangelist for smart water as has Global Water Intelligence’s Christopher Gasson, who has combined this with his desire to improve the quality of information about what remains a poorly understood business. Thanks are also due to Bruce Moeller (Aquaspy), David Henderson (XPV Capital), Professor Asit Biswas (Lee Kuan Yew School of Public Policy, NUS Singapore), Rob Wylie (WHEB), Jim Winpenny (Wynchwood), Michael Chuter (Pump Aid), Jack Jones (Sanivation), Philippe Rohner, Arnaud Bisschop, Simon Gottelier and March‐Oliver Buffle (Pictet Asset Management), James Hotchkies (JWH), Michael Deane (NAWC) and many others. Finally, Justin Taberham suggested that I write this book.

References

Lloyd Owen D A (2012a)

Policies to support smart water systems

. OECD, Paris, France.

Lloyd Owen D A (2012b)

The Sound of Thirst: Why urban water services for all is essential, achievable and affordable

. Parthian Books, Cardigan, UK.

Chapter 1What do we Mean by ‘Smart Water?’

Introduction

This chapter considers and defines the terms and expressions associated with ‘smart water’ and places them in the context of water management in the broadest sense. It also presents a range of estimates and forecasts of smart water’s market size and its share of the markets associated with water management and environmental goods and services in general.

1.1 Defining ‘Smart’

1.1.1 ‘Smart’ and Utilities and Public Services

When applied to utilities, environmental and public services, a working definition for ‘smart’ would be the application of data monitoring, transmission, management, and presentation to services in a manner that enhances the efficient use of their operating assets.

It covers data management and communications systems and services (ICT – information and communication technologies) for utilities public and environmental services. It can be seen as a catchier alternative to ‘intelligent’ which has also been applied here.

1.1.2 Smart Consumer Goods

In addition, ‘smart’ has been adopted for a wide variety of consumer goods. In November 2002, Microsoft announced that it was developing the Smart Personal Objects Technology (SPOT) Initiative, for ‘improving the function of everyday objects through the injection of software’ (Microsoft, 2002). While a range of devices were released by third party manufacturers (wristwatches, GPS navigation systems and weather stations) SPOT was discontinued in 2012, in particular due to the development of WiFi as a more efficient data transmission system (Gohring, 2008). Since then, ‘smart’ mobile phones, tablets, watches and cameras have been launched, along with TVs and cars under development.

As will be discussed later, the migration of ‘smart’ into consumer goods such as washing machines, showers and lavatories is set to become a factor in domestic water demand management as the ‘Internet of Things’ (IoT) connects domestic devices into broader data networks.

1.2 ‘Smart Power’ and ‘Smart Grids’

Smart power management for electricity utilities has not been driven by one or a small series of dramatic or disruptive events; it stems from a gradual continuation of demand management approaches. Electricity metering for measuring electricity used was introduced in the 1880s and has been developed ever since, including the introduction of digital metering in the 1990s (Anderson and Fuloria, 2010). Smart electricity metering is being driven by utilities and legislation, especially in the European Union, where at least 80% of meters are meant to be smart by 2020 (European Union, 2009).

Smart electricity meters inform electricity consumers how much power they are using and how much this is costing. Differential daily tariffs can be exploited to take advantage of when it is cheaper to use electricity (the lower the peak level of demand, the cheaper it is overall to produce each unit of electricity) which in turn means that the utilities can smooth out their power generation more than when there is only a single tariff. This approach is a modern refinement of night storage heaters, which have been used for some decades, assisting users to consider when they use electricity for light, heat and hot water and to optimise the time when these are used, to smooth their power demand profiles.

1.2.1 Smart Grids

Electricity grids, whereby utilities link up various power generators into a network offering greater security of supplies and flexibility of capacity were developed in Europe and the USA in the first three decades of the 20th century. In the UK, the Electricity (Supply) Act of 1926 brought about the Central Electricity Board, which rationalised 600 local power generators into regional networks by 1933 which in turn were integrated into the National Grid in 1938 using the 132 most efficient power generators in the UK.

The smart grid is concerned with ensuring the most efficient use of electricity across a network, so that no more generating capacity is deployed at any one time than is needed, matching demand with supplies as closely as possible and ensuring that both the most appropriate generating capacity is deployed (using generators at their optimum output) and with minimal transmission losses. They are also intended to provide the most reliable service under given circumstances and more recently to lower the utility’s environmental impact through renewable energy sources.

According to the Smart Grid Forum (Smart Grid Forum, 2014), a smart power grid is ‘a modernised electricity grid that uses information and communications technology to monitor and actively control generation and demand in near real‐time, which provides a more reliable and cost‐effective system for transporting electricity from generators to homes, businesses and industry.’

Smart electricity grids were made possible by advances in data capture, communication and management through advances in computing, data transmission and metering in the 1980s and 1990s. The first major deployment was in Italy, where the Telegestore programme was launched in 1999 and was completed by 2006, resulting in a comprehensive smart grid and metering infrastructure. Efficiency gains meant that operating spending per customer fell from €80 in 2001 to €49 by 2008 (Drago, 2009). In social (Google) and technical (IEEE Xplore) media, the frequency of the use of ‘smart grid’ entries becomes increasingly frequent from 2008, with the first journal citation having taken place in 1997 (Gómez‐Expósito, 2012).

1.3 Cleantech and Smart Cleantech

The expression ‘Cleantech’ (‘CleanTech’ and ‘Clean Tech’ are also used) is an abbreviation of clean technology. Cleantech covers goods and services that are designed to reduce the environmental impact of utility, environmental and public service activities such as power, waste management, heating and transportation, along with consumer goods associated with these such as washing machines and cars. Cleantech’s driving principal is, wherever attainable, to ‘do more for less’ whereby an innovation both improves the performance of a utility or an allied service, and lowers its costs. It is thereby seen as helping to make essential goods and services more affordable while also improving the efficiency of goods and services and reducing wastage to a minimum.

In practical terms, Cleantech covers goods and services that maintain or improve productivity while lowering energy and material resource needs and lowering operating and manufacturing costs. This is typically brought about through improving efficiency, minimising the resource intensity and reducing the carbon footprint of these offerings. By bringing down the costs of these goods or services, their affordability is also improved, allowing for a more extensive adoption than was possible with traditional approaches.

In the author’s experience, there have been three factors behind the term’s popularity. Firstly, in the late 1980s, the expression ‘environmental services sector’ was initially adopted by the financial services sector for companies involved in waste management, environmental consultancy and contaminated land remediation. The water and sewage sectors were at the time regarded as utilities, and with some exceptions, the impact of environmental drivers on their activities had a low priority. Secondly, in the early 1990s, companies involved in providing environmental goods and services were considered ‘recession resistant, if not recession proof’. During this period (for example there was a recessions in the USA in 1990–91, the UK in 1991–92 and Japan in 1991–93) it became evident that a decline in house building and decreased industrial activity did in fact significantly impact the environmental services sector and the expression lost its attraction to investors. Finally, the succinctness of the term and the way it allowed other applicable activities to be included (in particular, responses to climate change) made it an attractive expression for those involved with the industry in subsequent years.

Cleantech is in particular associated with aiming to decrease a product or service’s environmental footprint, typically in terms of its CO2 generation. The ultimate aim here is to ‘de‐carbonise’ activities so that they are not net generators of CO2. As a result, Cleantech is especially associated with developing and deploying renewable energy technologies.

1.3.1 Smart Cleantech

Smart Cleantech can be seen as an overlay of information processing upon extant systems. For example, the smart grid is the next stage of the adoption of smart Cleantech approaches, that of linking disparate activities together to that they can be monitored and managed in a more efficient manner than before. All aspects of Cleantech can potentially benefit from smart approaches where they enable the impacts of these innovations to be delivered in the most efficient manner.

Along with the smart grid, smart Cleantech is concerned with the automation of systems within Cleantech, managing their interfaces, ensuring that they are self‐healing (for example, through negative feedback loops), by adopting integrated communications for monitoring, supervisory control and data acquisition (SCADA) and delivering usage optimisation and peak demand smoothing. These terms and their potential applicability will be considered in due course.

The principle of ‘doing more for less’ is particularly important in the water sector, which has greater funding challenges than other utilities. Smart water approaches will only be adopted if they allow water utilities and other users improved performance and service delivery and assist them to lower their capital and operating costs.

1.4 Smart Water

Smart water is a term derived from the ‘smart metering’ and ‘smart grid’ sides of the Cleantech industry for lowering electricity usage and making power distribution more effective and efficient. In terms of water, this covers water distribution and usage, wastewater distribution, treatment and recovery, and also covers water flows, quality and saturation in the built and natural environment. It is a concept that has been realised through the development and convergence of information technology, mobile and digital communication and the Internet.

Smart water ‘is something of a catch‐all expression’ (OECD, 2012) for the current and potential impact of data collection, transmission and analysis for water and sewage utilities and domestic, commercial, industrial and irrigation users. As with the smart sectors previously described, smart water is in essence about achieving more while spending less. Despite being a part of water management in various forms for the past decade, in practical terms ‘its definition and role remains a work in progress’ (OECD, 2012). It is not intended to replace how services have been operated, rather to improve them and therefore to become ‘an enabler of innovation, as much as being an innovation itself’ (OECD, 2012).

As a concept, smart water emerged from ‘Cleantech’ in general and ‘smart Cleantech’ in particular, respectively as a suite of technologies designed to minimise and mitigate the impact of human activities on the natural environment and the potential for information technology, data transmission and perhaps, in the future, for using the ‘Internet of Things’ (IoT) to further optimise the effectiveness of such approaches. This is a somewhat radical approach for, as far as water management is concerned, it is a typically conservative activity and in consequence smart water is still at a tentative stage of its development. Indeed, its potential contribution towards addressing key structural challenges facing water and sewage management has not yet been fully appreciated.

A degree of caution is necessary, as it is often tempting to perceive an emergent technology or application as a realised one. Mobile communications provide a useful analogy. In the 1980s and early 1990s, mobile communications were seen as a dynamic and growing activity providing voice and limited data services at a high price to 10% of even 20% of the adult population in the more developed economies. Instead of being a premium service, mobile communications have since evolved into a low cost voice and an increasingly sophisticated data service whose coverage is becoming appreciably greater than that of fixed wire telephone services, especially in developing economies.

There are two ways of considering smart water. Firstly the parts of the water cycle that it can impact and how that impact may be felt and secondly, how it can influence the management of each of these components.

1.4.1 Smart Water and the Flow of Information

Smart water management typically involves five discrete stages in information handling. Data collection, interpretation and management may take place by using approaches such as JCS (data cache management for optimal data handling), CRM (customer relations management via dedicated data management), smartphones as data handlers and GIS (geographic information systems for collecting, analysing and sharing geographic information).

The examples of technologies involved below are in part based upon Heath (2015).

1.4.1.1 Monitoring and Data Collection

A monitoring system that enables the real‐time (or as near to real‐time as is practicable and needed) monitoring of all the necessary information for the effective management of the water service concerned and the collection of the relevant data. For example, in the water distribution mains this would include water flow and pressure, as well as temperature, pH, turbidity and the presence of treatment chemicals and contaminants. The monitoring data is then collected into a form that is suitable for its transmission.

1.4.1.2 Data Transmission and Recovery

The closer to real‐time the data collection is, the greater the necessity that the data can be transmitted without human intervention. For example, the move from manual to automated domestic meter reading.

Getting data in from a number of remote sites covering a water or wastewater network, domestic customers or surface waters requires remote data transmission from the field monitors to the data management centre. This can be carried out through fixed wire or wireless data transmission. Mobile data approaches are driven by the cost of transmitting the data in relation to the value accrued from this information. High value data from a remote point justifies dedicated data transmission, while lower value data such as domestic metering can at the most basic level be gathered by, for example, a drive‐by wireless data collection service.

Data communication may be ‘piggy‐backed’ on to electricity or telecoms networks, through radio transmission, or various mobile data applications.

1.4.1.3 Data Interpretation

Data is collected at a monitoring centre and is processed so that it is in a useable form for its manipulation and presentation. Given the volume of data generated, this needs to be done on an automatic basis. One particular concern here is to ensure that all sources of potentially valid data can be accessed and that the system is open to accepting new data sources as they become available. The hybrid cloud (using private and public cloud‐based data) may be used for integrating data from a wide variety of sources, such as water use, water demand, weather data and forecasts and monitoring external events what may affect water demand.

1.4.1.4 Data Manipulation

Data is interpreted according to each end‐user’s need. At this point, feedback loops may be used to feed new information into predictive models so as to be able to update any forecasts being generated and also to improve the model’s predictive ability through the use of real‐life information rather than simulated data.

1.4.1.5 Data Presentation

Finally, the information that has been gathered and analysed has to be presented in a manner which allows operators to act upon it in the simplest and most effective manner possible. This involves the use of graphics and alerts to inform an operator about any perturbations that ought to be of particular concern, while providing immediate access to the underlying data so that they can appreciate its particular nature. This may involve presenting information through a series of layers that allow operators to focus upon potentially relevant events and to locate and place them within their relevant operational context.

The first four stages can be seen as getting the data that a user needs, with the user acting on this data as presented in stage five. The object of stage five is to assist the user to make an informed decision based on this information. That may range from a domestic customer seeking to modify water usage to keep water (and electricity) bills down, a grower deciding when to irrigate crops or a utility manager considering which water resources to deploy.

The SWAN Forum (Smart Water Networks Forum, an industry group promoting the understanding and application of smart water management, swan‐forum.com) defines data flow across smart networks (Peleg, 2015) as starting from the final outcome and working down to the infrastructure involved. They are as follows:

Automatic decisions and operations.

Data fusion and analysis.

Data management and display.

Collection and communication.

Sensing and control (including smart water meters).

Physical layer (including traditional and bulk meters).

Stages 2–5 are seen by the SWAN Forum as forming the smart water network.

1.4.1.6 From Top–Down to Bottom–Up; Inverting the Flow of Information

Smart water is redefining the way that information is gathered and in whose interest this information is gathered and where it goes. For example, data collection through smart apps on mobile phones allows people in developing economies to monitor their access to safe water and sanitation (and the presence or absence of open defecation) and send this information upwards, rather than relying on the traditional visitations of government officials. Likewise, smart cash transfer approaches using mobile phones have both reduced customer time in paying utility bills and reduced the cost of billing for their utilities.

1.4.2 Smart Water and Managing the Water Cycle

Seven principal smart water applications can be identified. All of these are linked to some extent with the other elements.

1.4.2.1 Potable Water Systems

Optimising the beneficial use of water resources and managing water distribution networks to through minimising non‐revenue water (NRW) and giving consumers tools to control their consumption, while maintaining the appropriate level of water quality and service delivery. This is delivered through a smart water grid and uses smart domestic metering, pressure management, network monitoring and remote leakage detection. Water use minimisation is based on the principle of demand management.

1.4.2.2 Sewerage Systems

Managing the sewerage networks and wastewater treatment works so as to minimise their net energy needs, the best application of assets for transporting and treating wastewater and minimising the environmental impact of the wastewater. This includes managing flows of municipal sewage, industrial effluents, and storm (rain) water and relating these flows to the systems’ storage and treatment capacity. Applications include flow metering and network condition monitoring,

1.4.2.3 Energy Use and Recovery

Minimising the amount of energy needed across the water cycle through controlling energy use, optimising power consumption, and by using water and wastewater flows to generate electricity along with recovering energy embedded in the wastewater. This also extends to nutrient and water recovery from wastewater. This involves network, water treatment and wastewater treatment monitoring to minimise the amount of pumping needed, along with treatment chemicals required and optimising treatment processes for water, nutrient and energy recovery.

1.4.2.4 Smart Environment

The use of real‐time monitoring allied with predictive systems to minimise the response time to any perturbations in each catchment area, including linking treatment works to the monitoring data. Demand management for municipal, industrial and irrigation applications is used to minimise the amount of water that needs to be abstracted from each catchment area, along with real‐time monitoring of water flows through the catchment to maintain the integrity of the water cycle.

1.4.2.5 Flood Management and Mitigation

Real‐time monitoring of rainfall, water flows, soil moisture, and groundwater levels are allied to comprehensive and fully updated data on the flood characteristics of each catchment area to respond to changing water levels and to maximise the time available to respond to potential flooding incidents.

1.4.2.6 Resource Management

Monitoring of surface water, reservoir and ground water levels and quality and to ally this data with current and anticipated water demand from various user types to ensure adequate water availability and to balance demand with the various resources available.

1.4.2.7 Integrated Water Management

Smart water systems offer the potential to deliver closed‐loop systems for municipal and industrial customers through linking up the treatment, distribution and resource recovery processes outlined in the first six examples. The municipal applications would be based on localised systems, serving a smaller town or a sub‐district within a larger utility. This involves distributed rather than centralised treatment facilities with an emphasis on minimising the energy intensity of the water and wastewater networks involved.

1.4.3 Smart Water and the ‘Food, Water, Energy, and the Environment Nexus’

Smart water has a central role to play in the so‐called food, water, energy and the environment nexus (‘the nexus’), especially through water demand management and effluent resource recovery through the nexus. While it is an arresting expression, ‘the nexus’ may well be replaced by a more compelling expression in time.

Nexus‐related themes include irrigation water for agriculture and other applications, nutrient recovery for fertilisers and energy recovery for treatment processes and export. Indirect impacts include lowering water abstraction and utility footprints. There are also direct and indirect interrelationships between resource recovery and the costs associated with maintaining and extending municipal water and sewage services. Water recovery also has an impact on demand and resource management through the impact water reuse on overall water abstraction.

1.5 Water, Smart Water and Cleantech

Water has sometimes had a somewhat uneasy relationship with the rest of the Cleantech sector. This stems from an assumption that pipes, sewers and treatment works do not naturally belong in a sector that is associated with photovoltaics, hydrogen cells and data systems. Such a view does not reflect the fact that water services, gas, telecoms, and electricity provision are utility activities. There are significant cross‐linkages between utilities both in terms of services developed for one utility being adapted for another and where combined services can be offered.

As will be seen, water occupies a small section of the Cleantech sector in terms of funding flows and to a lesser extent in capital and operating expenditure, and the same applies with smart water and smart Cleantech. Compared with many sectors where Cleantech is being developed, water and wastewater are seen as slow moving and risk adverse, with some reluctance by municipal and domestic customers to increase up‐front spending on their utilities, especially on innovative approaches. The challenge in funding associated with water utilities and services is in fact becoming a driver for water Cleantech in general and smart approaches in particular.

With their relatively small market size, water Cleantech and smart water have tended to be seen as an adjunct for other sectors, where extent technologies can be adapted to extend their market reach rather than looking for approaches that are specifically designed to serve the water sector. Likewise, other utilities and service providers are looking for opportunities in water and wastewater for technologies and techniques that were developed for applications in other sectors.

Other links with the rest of Cleantech are emerging through work on de‐carbonising the water and wastewater sector, or making traditionally intensive actions such as water and wastewater pumping and wastewater treatment and recovery energy (and therefore carbon) neutral. Meanwhile, forms of automation are an example of utility services being adopted by other, while smart meters are being developed that combine reading and billing for water and electricity provision.

1.6 Disruption and a Conservative Sector

1.6.1 Why Water Utilities are Risk‐Averse

Risk aversity and an institutionally conservative approach are characteristics of the water sector. Unlike for example electricity, water provision is directly affected by public health and environmental concerns. Water is usually expected to meet applicable levels of purity as well as service delivery expectations both in the reliability of water provision and in aesthetics such as taste and colour. Wastewater treatment and disposal is likewise affected by legislation affecting the way it is handled and discharged into the ambient environment.

In developed economies, any deviation from perfect water and wastewater delivery is considered as unacceptable. Shannon and Weaver (1949) pointed out that when information comes across steadily, it is not noticed (background music for example) until it stops. It is the deviation from a steady state that a consumer does not expect. In the case of water and sewerage, any deviation from a perfect service will be immediately apparent and therefore completely unacceptable.

While access to reliable telecommunications services are desirable and humanity can exist without electricity (albeit, with an even greater loss of utility) access to potable water is essential to life, while the economic and public health costs of poor access to water and inadequate sanitation are considerable.

Another factor is the asset intensity of water services – and even more so for sewerage – in relation to the revenues their activities generate. This leads to concerns about stranded assets, whereby innovation obliges a utility to acquire new systems even though it already has perfectly functional assets. For example, if manual read water meters were recently purchased, this may delay the adoption of smart meters because of the concerns about purchasing these assets twice over.

1.6.2 A Question of Standards

Like other utility services, water and wastewater are typically governed by national standards. For water quality, these are led by the World Health Organization’s guidelines (WHO, 2011) which are then adopted at the national level, for example the Water Supply (Water Quality) Regulations, 2000 in England and Wales. In Europe, a series of directives also cover water and wastewater standards, including; Drinking Water (1998/83/EC), Bathing Water (1976/160/EEC and revised as 2007/7/EC), Urban Wastewater Treatment (1991/271/EEC) and the Water Framework (2000/60/EC).

Regardless of the power source, electricity will be delivered to a common standard across a utility and indeed a country. Likewise, telecommunications services depend on commonly agreed transmission protocols for both fixed‐wire and mobile services. Both services are cheap to transmit over substantial distances between population centres in relation to the revenues these services generate.

In contrast, every water catchment area has its own characteristics. These include the amount of rainfall, its patterns and seasonality, the underlying rocks, geomorphology (the interaction between the landscape and its underlying strata), the presence of aquifers, land use and run‐off, population density and distribution, the relation between renewable water resources and demand, and how water and wastewater is managed within the area.

Water is comparatively expensive to transport across catchment areas in relation to the value of the service. Where a utility uses water from a variety of sources, each source may need a specific treatment regimen before it can be released into the distribution network. Indeed, water from different sources will react differently when passed through the mains network (more acidic water will reach with iron pipes, causing corrosion and discolouration) and domestic networks (more acidic, or plumbosolvent water will dissolve lead pipes and solder, which may raise lead concentrations above the applicable standards).

1.6.3 Disruption in a Conservative Sector

A disruptive technology is one which changes the nature of its intended market. For example, railways, internal combustion engines and commercial flight have had a disruptive influence in the business of transportation, as have the telegraph and fixed‐wire and mobile telephony in communications.

Despite its conservative nature, significant disruptive events have taken place in the water and sewage sectors. Examples of genuinely disruptive developments in water and wastewater services include the first slow sand filtration system for water for large scale water treatment which opened in Paisley, Scotland in 1804 (Huismann and Wood, 1974) and the development of the activated sludge sewage treatment by Edward Arden and William Locket in 1913–14 (Alleman, 2005).

More recently, reverse osmosis for desalination was developed by Sidney Loeb and Srivasa Sourirajan from the late 1950s and the first commercial reverse osmosis desalination at Coalinga, California entered service in 1965 (Loeb, 2006) and membrane technologies for wastewater treatment and water recovery were transformed by the development of the submerged membrane bioreactor in 1989 (Yamamoto et al., 1989).

Most current and anticipated smart water developments are set to offer incremental rather than disruptive improvements in efficiency and cost‐effectiveness. It is the potential ability to integrate and to redouble these incremental benefits into a smart water system that is disruptive.

1.7 The Size of this Market; Estimates and Forecasts

How big is the market for smart water systems and products and how big might it become? A wide number of companies carry out research on the current and forecast size of various technology markets. Data from surveys that are in the public domain (available through press releases, conference presentations or in openly available surveys) is presented in six tables below and placed in its context.

What counts as ‘smart’ varies from survey to survey as well as the actual amount of hardware involved. Because of the broad nature of definitions used for smart water between the companies surveying the sector there is an equally broad range of market estimates as well as forecasts. No survey is likely to be definitive and no one survey may be more accurate than another, but by comparing them, an overall impression can be made. Their value lies in showing how analysts following the sector perceive its current status and its potential growth and how this perception is changing over time.

The differences between market estimates over time also highlight the relatively early stage of this market’s evolution and that it is a sector that is in rapid phase of development. Surveys will vary from year to year due to currency fluctuations against the US dollar as well as changing assumptions about future economic growth.

1.7.1 A Survey of Surveys

A total of 22 surveys and forecasts have been noted, eight covering the overall market (Table 1.1) and 14 looking at specific sub‐sectors (Tables 1.2 to 1.6). A CAGR (compound annual growth rate) has been calculated where it was not initially available, to allow the comparison of growth projections. The Lux (2010) survey was one of the earlier ones notes and forecast growth rates are particularly high because of the small market base at the time of the survey.

Table 1.1 Smart water – overall surveys.

$ billion

Start year

End year

Start

End

CAGR

Lux (2010)

2009

2020

0.50

16.30

37.3%

IDC Energy Insights (2012)

2011

2016

1.40

3.30

18.7%

GWI (2014)

2013

2018

3.62

6.90

13.8%

Marketsandmarkets (2013)

2013

2018

5.43

12.03

17.2%

Transparency (2014)

2012

2019

4.81

15.23

17.9%

Marketsandmarkets (2015)

2015

2020

7.34

18.31

20.1%

Marketsandmarkets (2016a)

2016

2021

8.46

20.10

18.9%

Technavio (2016)

2015

2020

7.00

16.73

19.0%

Adapted from Transparency Market Research (2014); Minnihan (2010); Marketsandmarkets (2013, 2015, and 2016a); IDC (2012) and Global Water Intelligence (2014); Technavio (2016).

Table 1.2 Smart meters.

$ billion

Start year

End year

Start

End

CAGR

TechNavio (2008)

2008

2012

0.24

0.51

20.1%

Lux (2010)

2009

2020

0.21

6.30

36.0%

Pike Research (2011)

2010

2016

0.41

0.86

13.1%

IMS Research (2011)

2010

2016

0.55

0.95

9.5%

Frost+Sullivan (2014)

2013

2017

3.48

5.18

10.5%

IHS Tech (2014)

2013

2020

0.58

1.23

11.5%

Marketsandmarkets (2016b)

2015

2021

3.73

5.67

7.2%

Technavio (2017)

2016

2021

4.83

12.18

20.3%

Research and Markets (2017)

2015

2025

3.75

8.80

8.8%

Adapted from TechNavio (2008 and 2017); Minnihan (2010); Pike Research (2011); IMS Research (2011); Frost and Sullivan (2014); IHS Tech (2014); Marketsandmarkets (2016b) and Technavio (2017).

Table 1.3 Smart water networks.

$ billion

Start Year

End Year

Start

End

CAGR

Lux (2010)

2009

2020

0.16

3.30

31.5%

Navigant Research (2013)

2013

2022

1.12

3.30

12.8%

Frost+Sullivan (2012)

2010

2020

0.35

6.44

33.8%

Navigant Research (2016)

2016

2025

2.50

7.20

11.2%

Adapted from Minnihan (2010), Frost and Sullivan (2012) and Navigant Research (2013 and 2016).

Table 1.4 Leakage management.

$ billion

Start year

End year

Start

End

CAGR

GWI (2014)

2013

2018

1.49

2.80

13.3%

Adapted from Global Water Intelligence (2014).

Table 1.5 Water mapping.

$ billion

Start year

End year

Start

End

CAGR

Lux (2010)

2009

2020

0.02

3.20

56.6%

Adapted from Minnihan (2010).

Table 1.6 Water quality monitoring.

$ billion

Start year

End year

Start

End

CAGR

Lux (2010)

2009

2020

0.11

1.10

23.4%

GWI (2013)

2013

2018

0.08

0.14

13.4%

Adapted from Minnihan (2010) and Global Water Intelligence (2014).

It should be noted that the market estimates and forecasts provided by Marketsandmarkets are higher in their 2015 and 2016 surveys than in the 2013 survey. A lower CAGR forecast for 2016–21 than for 2015–20 reflects a higher initial market size.

The more recent surveys start from an appreciably higher market estimate base and generally point to a market that will be more substantial than previously anticipated.

Looking at their 2013 market estimates for sub‐sectors, GWI (2014) splits the market into four main areas: network optimisation ($726 million), leakage management ($1,494 million), metering and customer services ($1,322 million) and water quality monitoring ($77 million).

While the Navigant 2016 CAGR is lower than the 2013 forecast, the anticipated market size is appreciably greater and indeed the 2016 market estimate is almost the size of the previous survey’s 2020 forecast.

The water testing and analysis market remains dominated by traditional approaches. Marketsandmarkets (2015b) forecasts the overall market, including laboratory systems will be worth $3.5 billion in 2019, growing at 5.2% pa between 2014 and 2019.

According to Aquaspy (Aquaspy, 2013), $210 million was spent on smart irrigation in 2012; $100 million on water irrigation control systems, $30 million on monitoring, $10 million on ‘fertigation’ (combined fertilisation and drip irrigation systems) and $70 million on greenhouse control systems. Marketsandmarkets (2015c) estimates the overall soil moisture sensing market was worth $98 million in 2015. The smart irrigation market is analysed in greater detail in Chapter 7.

Another way of considering smart water in its broader context is to look at overall spending on smart systems and the hardware that is directly related to it such as metering and monitoring hardware. This was examined by GWI (2016) as ‘digital water’ with a market with $20 billion in 2014 and projected to grow to $30 billion pa by 2020. The market sizes for treatment and distribution and collection are seen as broadly equal in size.

The main areas of difference between ‘digital’ and ‘smart’ relate to those elements of testing, metering and sensing, which while part of smart networks, are not smart appliances in themselves. Parts of automation and control will also include non‐smart elements. What these numbers highlight is the non‐smart aspects of water hardware that enable smart systems to operate.

To put the smart water figures into their broader context, Marketsandmarkets (2015) estimates that the smart cities market (covering all urban services) was worth $411 billion in 2014 and will grow to $1,135 billion by 2019. GWI (GWM 2015, 2014) estimates that capital spending in 2013 on water infrastructure was $102 billion, rising to $131 billion by 2018 and $110 billion rising to $142 billion for wastewater over the same period.

1.8 Venture Capital Funding Flows

The information in this section is restricted to that which has been provided at conferences, in press releases and articles that are in the public domain. The awkward relationship between water and the rest of the Cleantech sector is highlighted in Venture Capital spending. For example, Boogar Lists is a USA based database of over 2,000 venture capital and Private Equity firms (Boogar Lists, 2014). It lists 89 Cleantech venture capital funds globally, but these do not include Apsara Capital (London) or XPV Capital (Toronto). These are the only dedicated water Cleantech venture capital funds known to be in operation during this period.

Table 1.7 outlines overall venture capital investment in the water sector between 2006 and 2013.

Table 1.7 Water Cleantech venture capital funding, 2006–13.

Water Cleantech

2006–07

2008–09

2010–11

2012–13

2014–15

Number of VC deals

56

159

204

257

139

VC funding ($ million)

293

915

936

1,023

587

Funding per deal ($ million)

5.2

5.8

4.6

4.0

4.2

Adapted from The Cleantech Group (2011) and i3 (2014, 2015 and 2017).

While there has been a decrease in the average deal size since 2009, the overall level of investment has been maintained. However, in 2016, there were 42 water VC investments, generating $173 million in funding. This is the lowest annual figure since 2006 with an average investment size of $4.1 million (i3, 2017).

Placing these figures, Table 1.8 outlines overall Cleantech venture capital investment and the relative size of water investment.

Table 1.8