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Smart Water and Sanitation

Posted | Updated by Insights team:
Dr. Evangelo Damigos; PhD | Head of Digital Futures Research Desk
  • Competitive Differentiation
  • Sustainable Growth and Tech Trends
  • Energy


Publication | Update: Sep 2020

Water demand is expected to increase by 1/3 by 2050, since climate change and population growth are the main challenges for water.

Out of the global population of some 7.5 billion people, 2.4 billion currently lack access to adequate sanitation facilities, 1.8 billion people use a contaminated source of drinking water and by 2030 the global demand for water is expected to grow by 50%.

Every day nearly 1,000 children die due to preventable water and sanitation-related diseases. It is also estimated that 80% of wastewater resulting from human activities is discharged into rivers or into the sea without any sort of treatment. Clean water is at the core of sustainable development and is critical for socio-economic development, health ecosystems, and for human survival. 

Rapid population growth, coupled with an increase in wealth and dietary changes is expected to increase the global demand for water. The demand for water for domestic purposes (cleaning, sanitation and drinking) is expected to increase from 400km3 to 660-900 km3 by 2030.

 The majority of this demand will occur in cities, and as it is being highlighted in the Citi GPS report “Solutions for a Global Water Crisis,” a number of cities are already facing acute water problems. They are particularly vulnerable because they depend on the water resources from outside their city boundaries, and they face twin challenges: water that is both scarce and water that is polluted.

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According to McDonald, 100 of the largest cities in the world currently occupy less than 1% of land area, however their source watersheds (i.e. rivers, forest, ecosystems) cover over 12% of land area. This is equal to approximately 1.7 billion hectares of land that collects filters and transports water to nearly 100 billion people before reaching man-made infrastructure. Cities play a significant role in the management of water, as they impact both the quantity and quality of water resources due to land use change, over exploitation of water resources and contamination. Therefore it is not only adequate infrastructure that cities need to provide, but sustainable solutions outside their city boundaries.

Infrastructure does play at important part, and in many areas, city infrastructure has not kept pace with the massive urban growth, leaving people without adequate access to clean drinking water and sanitation. The concentration of millions of people into small areas increases the stress on finite water supplies available in or near city centers.

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The inadequate supply of water can cause damage to an economy. One has to just read about the water crisis in Cape Town and the effect that a shortage of water is having on the agriculture sector, on industry, tourism, and on the city’s inhabitants.

The World Health Organization estimates that the total global economic losses related to inadequate water supply and sanitation to be in the region of 0 billion annually. Climate change could also have a severe impact on water supply in many cities, in fact the World Bank ranks water supply and flood protection as one of the three adaptation costs to climate change estimated between .4 and .7 billion per year.

The Citi GPS report, “Solutions for the Global Water Crisis”, estimates that an infrastructure investment of .5 to .7 trillion is needed globally to upgrade, maintain, and build new infrastructure.

Smart Water 

Smart technologies are also revolutionizing the water sector. There are several Smart Water Management tools that are available on the market including smart metering, remote monitoring (SCADA), geographical information systems, and telecommunications systems which allow for the provision of real-time data and therefore real-time improvements to systems. Examples of such applications include WaterWiSe which has currently been deployed by the Singapore Public Utilities Board to monitor online hydraulic and water quality parameters, to detect leakage remotely, and to assimilate real time data into hydraulic models.

K-Water- a company in South Korea has been embracing smart water technologies for a number of its projects (see section on water). K-Water has developed a smart water technology system that includes a core set of integrated smart technologies that are included in the whole process of the water cycle. The company is currently using its technology to help improve water usage in a number of different countries.

Libelium’s Smart Water IoT Solution Quick Report,” summarizes all the benefits, advantages and the most demanded features that stakeholders look for. This report shows how the Internet of Things can help to improve water management issues such as consumption, water usage improvement and cost reduction.

 

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Libelium recently launched the new model of IoT platform for Smart Water quality control:Waspmote Plug & Sense! Smart Water Xtreme. The enhanced device includes top market performance sensors from the most prestigious manufacturers for applications such as potable water monitoring, fish farm management, chemical leakage detection, remote measurement of swimming pools and spas, and seawater pollution.

According to ITU research, “WorldWaterDay: How ICTs are creating smart water and sanitation systems,” information and communication technologies (ICTs) are revolutionizing the management of water resources and may be instrumental in the achievement of the United Nations’ Sustainable Development Goal (SDG) for clean water and sanitation (SDG 6). ICTs and smart water management (SWM) systems are being applied to a variety of development projects for water management and sanitation.

For example, satellite remote sensing of groundwater in Somalia allows researchers to accurately gauge water quality. In Kenya, real-time monitoring of communities reveals their sanitation status. And in South Africa, online data collection allows community-based NGOs to forecast the level of rivers and to identify new sources of fresh water. Additionally, smart water meters can provide individuals, businesses and governments with information about their own water use.

“ICTs are helping on all sides, the providers as well as the consumers. For example, by better monitoring and managing water losses and by giving consumers better ways of reporting water quality or quantity problems,” says Carolien van der Voorden, Senior Programme Officer, Learning and Documentation, Global Sanitation Fund, Water Supply & Sanitation Collaborative Council (WSSCC).

For example, the Ministry of Health in Kenya has implemented a Real Time Monitoring System for Community Led Total Sanitation (CLTS), an online monitoring and evaluation system to track sanitation levels and progress toward their Open Defecation Free Mission. The Somalia Water and Land Information Management (SWALIM) project developed by Food and Agriculture Organization (FAO) has also developed sophisticated systems for monitoring surface and groundwater to support sustainable development of the scarce and valuable water resources in the country.

Advanced monitoring allows for better planning and management, especially during cycles of drought and flooding.

According to ITU’s report, ICT as an Enabler for Smart Water Management, a number of factors are impacting the delivery of already scarce fresh water to millions of people. “Economic growth, changing climatic conditions, rising population and urbanization are all affecting availability of water resources. Moreover, a number of effects linked to climate change, such as lengthy droughts and extreme weather events, are worsening the situation.”

Despite current efforts for water recycling or treatment, it is estimated that over 80% of the wastewater generated by society flows back into the ecosystem without being treated or reused. ICTs could prove to be effective in the treatment and recycling of wastewater and key to tackling the world’s water scarcity crisis.

ITU’s Focus Group on Smart Sustainable Cities has identified key trends in urban smart water management, including ICTs for managing wastewater. For example, in Holon municipality in Israel, the sewage system was plagued with problems such as frequent blockages and overflows. By installing gauging devices equipped with sensors, the municipality was better able to manage its sewer systems and now receives reliable information to monitor its sewer system using a web platform, and sends alerts via short message service (SMS) messages when the level reaches low/high limits.

The Netherlands is leading solutions for wastewater treatment through large-scale private-public investments. The Dutch water management authorities recognize the need to draw together economists, engineers and climate scientists to work together to solve the issue. The Dutch government has promoted effective collaboration among stakeholders though a coordinated Delta Programme, to effectively manage freshwater supplies in the country.

While countries and municipalities are leading investments and projects to sustainably manage water resources, it cannot be overstated the importance limiting, reusing and recycling water usage at the individual level. With new technologies like smart water meters and apps to monitor home usage, ICTs are enabling individuals to better manage their own water use.

Green Infrastructure: A Case Study of Portland

Green infrastructure is a potential solution that could save city money. In Portland, Oregon water quality in the River Willamette had deteriorated dramatically due to frequent spills from the overloaded sewerage network. In 2002, Portland experienced 50 overflow events, discharging around 13 million m3 into local waterways. The choice faced by the city was clear: it could invest in expanding the below ground pipe network by building more grey infrastructure, or it could look upstream and attempt to take water out of the system at the source. This was the basis for the city’s successful Grey to Green initiative. The city budgeted million in stormwater management fees to invest in green infrastructure over 5 years, adding over 100 hectares of eco-roofs, installing 920 green street components, planting over 80,000 trees in yards and along streets and buying over a 1000 hectares of high priority natural areas. Its downspout disconnection program disconnected more than 56,000 downspouts from over 26,000 properties within the

Combined Sewer Overflow area, allowing more than a million cubic meters of stormwater to infiltrate into the ground annually. 

The city has installed street gardens in curb extensions and flow tests have shown these can reduce peak flow from a 25 year storm event by 88 % — enough to protect local basements from flooding and reduce total runoff to the combined sewer system by 85%. The city estimates that resolving flooding and other problems caused by runoff in the region using only conventional infrastructure and pipe solutions would have cost an estimated 4 million, compared with an estimated million using largely green infrastructure. Such measures also provide benefits in terms of enhancing water quality, providing amenity and recreational spaces, adding to urban biodiversity and providing other functions such as carbon sequestration and pollutant trapping on leaf surfaces.

Zero Waste Cities

The city of Ljubljana is committed to the zero waste initiative and aims to increase separate collections to 78% by 2025, reduce total waste generated to 280 kg per inhabitant and reduce yearly residual waste to 60 kg by 2025. Ljubljana is not alone; the city of San Francisco is also working to achieve zero waste by 2020.

It has successfully diverted 90% of its waste from landfills through a number of easy initiatives such as an easy-to-use three bin system for waste, economic incentives for households to recycle and compost more, policies that promote zero waste goals, and extensive education for its residents and businesses about recycling and composting. The costs for their zero waste program are funded solely from the revenue generated through collection rates charged to customers. 

Effective and sustainable waste management is a huge challenge for many cities.

Different cities have different challenges they need to overcome with regard to managing their waste effectively. Ultimately, waste should be viewed as an important resource rather than a problem that needs to be dealt with. Organic waste could be turned into high quality compost, while inorganic waste could either be recycled and reused, or used to create energy, while also providing additional benefits to residents in the form of work opportunities and a better livelihood. Developing a source of revenue from organic waste, can create revenue streams for a company, reduce costs for the disposal of waste for the city and at the same time create a very good product for farmers. Disposing of waste into landfills should be seen as a last resort as it is the least effective way of managing waste and is costly. 

A rapid surge in population in many emerging and developed cities will undoubtedly increase the amount of solid waste that is generated. With the right approach and strategic planning many waste streams can become income streams. 

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Objectives and Study Scope

This study has assimilated knowledge and insight from business and subject-matter experts, and from a broad spectrum of market initiatives. Building on this research, the objectives of this market research report is to provide actionable intelligence on opportunities alongside the market size of various segments, as well as fact-based information on key factors influencing the market- growth drivers, industry-specific challenges and other critical issues in terms of detailed analysis and impact.

The report in its entirety provides a comprehensive overview of the current global condition, as well as notable opportunities and challenges. The analysis reflects market size, latest trends, growth drivers, threats, opportunities, as well as key market segments. The study addresses market dynamics in several geographic segments along with market analysis for the current market environment and future scenario over the forecast period. The report also segments the market into various categories based on the product, end user, application, type, and region.
The report also studies various growth drivers and restraints impacting the  market, plus a comprehensive market and vendor landscape in addition to a SWOT analysis of the key players.  This analysis also examines the competitive landscape within each market. Market factors are assessed by examining barriers to entry and market opportunities. Strategies adopted by key players including recent developments, new product launches, merger and acquisitions, and other insightful updates are provided.

Research Process & Methodology

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We leverage extensive primary research, our contact database, knowledge of companies and industry relationships, patent and academic journal searches, and Institutes and University associate links to frame a strong visibility in the markets and technologies we cover.

We draw on available data sources and methods to profile developments. We use computerised data mining methods and analytical techniques, including cluster and regression modelling, to identify patterns from publicly available online information on enterprise web sites.
Historical, qualitative and quantitative information is obtained principally from confidential and proprietary sources, professional network, annual reports, investor relationship presentations, and expert interviews, about key factors, such as recent trends in industry performance and identify factors underlying those trends - drivers, restraints, opportunities, and challenges influencing the growth of the market, for both, the supply and demand sides.
In addition to our own desk research, various secondary sources, such as Hoovers, Dun & Bradstreet, Bloomberg BusinessWeek, Statista, are referred to identify key players in the industry, supply chain and market size, percentage shares, splits, and breakdowns into segments and subsegments with respect to individual growth trends, prospects, and contribution to the total market.

Research Portfolio Sources:

  • BBC Monitoring

  • BMI Research: Company Reports, Industry Reports, Special Reports, Industry Forecast Scenario

  • CIMB: Company Reports, Daily Market News, Economic Reports, Industry Reports, Strategy Reports, and Yearbooks

  • Dun & Bradstreet: Country Reports, Country Riskline Reports, Economic Indicators 5yr Forecast, and Industry Reports

  • EMIS: EMIS Insight and EMIS Dealwatch

  • Enerdata: Energy Data Set, Energy Market Report, Energy Prices, LNG Trade Data and World Refineries Data

  • Euromoney: China Law and Practice, Emerging Markets, International Tax Review, Latin Finance, Managing Intellectual Property, Petroleum Economist, Project Finance, and Euromoney Magazine

  • Euromonitor International: Industry Capsules, Local Company Profiles, Sector Capsules

  • Fitch Ratings: Criteria Reports, Outlook Report, Presale Report, Press Releases, Special Reports, Transition Default Study Report

  • FocusEconomics: Consensus Forecast Country Reports

  • Ken Research: Industry Reports, Regional Industry Reports and Global Industry Reports

  • MarketLine: Company Profiles and Industry Profiles

  • OECD: Economic Outlook, Economic Surveys, Energy Prices and Taxes, Main Economic Indicators, Main Science and Technology Indicators, National Accounts, Quarterly International Trade Statistics

  • Oxford Economics: Global Industry Forecasts, Country Economic Forecasts, Industry Forecast Data, and Monthly Industry Briefings

  • Progressive Digital Media: Industry Snapshots, News, Company Profiles, Energy Business Review

  • Project Syndicate: News Commentary

  • Technavio: Global Market Assessment Reports, Regional Market Assessment Reports, and Market Assessment Country Reports

  • The Economist Intelligence Unit: Country Summaries, Industry Briefings, Industry Reports and Industry Statistics

Global Business Reviews, Research Papers, Commentary & Strategy Reports

  • World Bank

  • World Trade Organization

  • The Financial Times

  • The Wall Street Journal

  • The Wall Street Transcript

  • Bloomberg

  • Standard & Poor’s Industry Surveys

  • Thomson Research

  • Thomson Street Events

  • Reuter 3000 Xtra

  • OneSource Business

  • Hoover’s

  • MGI

  • LSE

  • MIT

  • ERA

  • BBVA

  • IDC

  • IdExec

  • Moody’s

  • Factiva

  • Forrester Research

  • Computer Economics

  • Voice and Data

  • SIA / SSIR

  • Kiplinger Forecasts

  • Dialog PRO

  • LexisNexis

  • ISI Emerging Markets

  • McKinsey

  • Deloitte

  • Oliver Wyman

  • Faulkner Information Services

  • Accenture

  • Ipsos

  • Mintel

  • Statista

  • Bureau van Dijk’s Amadeus

  • EY

  • PwC

  • Berg Insight

  • ABI research

  • Pyramid Research

  • Gartner Group

  • Juniper Research

  • MarketsandMarkets

  • GSA

  • Frost and Sullivan Analysis

  • McKinsey Global Institute

  • European Mobile and Mobility Alliance

  • Open Europe

M&A and Risk Management | Regulation

  • Thomson Mergers & Acquisitions

  • MergerStat

  • Profound

  • DDAR

  • ISS Corporate Governance

  • BoardEx

  • Board Analyst

  • Securities Mosaic

  • Varonis

  • International Tax and Business Guides

  • CoreCompensation

  • CCH Research Network

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Forecast methodology

The future outlook “forecast” is based on a set of statistical methods such as regression analysis, industry specific drivers as well as analyst evaluations, as well as analysis of the trends that influence economic outcomes and business decision making.
The Global Economic Model is covering the political environment, the macroeconomic environment, market opportunities, policy towards free enterprise and competition, policy towards foreign investment, foreign trade and exchange controls, taxes, financing, the labour market and infrastructure. We aim update our market forecast to include the latest market developments and trends.

Forecasts, Data modelling and indicator normalisation

Review of independent forecasts for the main macroeconomic variables by the following organizations provide a holistic overview of the range of alternative opinions:

  • Cambridge Econometrics (CE)

  • The Centre for Economic and Business Research (CEBR)

  • Experian Economics (EE)

  • Oxford Economics (OE)

As a result, the reported forecasts derive from different forecasters and may not represent the view of any one forecaster over the whole of the forecast period. These projections provide an indication of what is, in our view most likely to happen, not what it will definitely happen.

Short- and medium-term forecasts are based on a “demand-side” forecasting framework, under the assumption that supply adjusts to meet demand either directly through changes in output or through the depletion of inventories.
Long-term projections rely on a supply-side framework, in which output is determined by the availability of labour and capital equipment and the growth in productivity.
Long-term growth prospects, are impacted by factors including the workforce capabilities, the openness of the economy to trade, the legal framework, fiscal policy, the degree of government regulation.

Direct contribution to GDP
The method for calculating the direct contribution of an industry to GDP, is to measure its ‘gross value added’ (GVA); that is, to calculate the difference between the industry’s total pre­tax revenue and its total bought­in costs (costs excluding wages and salaries).

Forecasts of GDP growth: GDP = CN+IN+GS+NEX

GDP growth estimates take into account:

  • Consumption, expressed as a function of income, wealth, prices and interest rates;

  • Investment as a function of the return on capital and changes in capacity utilization; Government spending as a function of intervention initiatives and state of the economy;

  • Net exports as a function of global economic conditions.

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Market Quantification
All relevant markets are quantified utilizing revenue figures for the forecast period. The Compound Annual Growth Rate (CAGR) within each segment is used to measure growth and to extrapolate data when figures are not publicly available.

Revenues

Our market segments reflect major categories and subcategories of the global market, followed by an analysis of statistical data covering national spending and international trade relations and patterns. Market values reflect revenues paid by the final customer / end user to vendors and service providers either directly or through distribution channels, excluding VAT. Local currencies are converted to USD using the yearly average exchange rates of local currencies to the USD for the respective year as provided by the IMF World Economic Outlook Database.

Industry Life Cycle Market Phase

Market phase is determined using factors in the Industry Life Cycle model. The adapted market phase definitions are as follows:

  • Nascent: New market need not yet determined; growth begins increasing toward end of cycle

  • Growth: Growth trajectory picks up; high growth rates

  • Mature: Typically fewer firms than growth phase, as dominant solutions continue to capture the majority of market share and market consolidation occurs, displaying lower growth rates that are typically on par with the general economy

  • Decline: Further market consolidation, rapidly declining growth rates

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The Global Economic Model
The Global Economic Model brings together macroeconomic and sectoral forecasts for quantifying the key relationships.

The model is a hybrid statistical model that uses macroeconomic variables and inter-industry linkages to forecast sectoral output. The model is used to forecast not just output, but prices, wages, employment and investment. The principal variables driving the industry model are the components of final demand, which directly or indirectly determine the demand facing each industry. However, other macroeconomic assumptions — in particular exchange rates, as well as world commodity prices — also enter into the equation, as well as other industry specific factors that have been or are expected to impact.

  • Vector Auto Regression (VAR) statistical models capturing the linear interdependencies among multiple time series, are best used for short-term forecasting, whereby shocks to demand will generate economic cycles that can be influenced by fiscal and monetary policy.

  • Dynamic-Stochastic Equilibrium (DSE) models replicate the behaviour of the economy by analyzing the interaction of economic variables, whereby output is determined by supply side factors, such as investment, demographics, labour participation and productivity.

  • Dynamic Econometric Error Correction (DEEC) modelling combines VAR and DSE models by estimating the speed at which a dependent variable returns to its equilibrium after a shock, as well as assessing the impact of a company, industry, new technology, regulation, or market change. DEEC modelling is best suited for forecasting.

Forecasts of GDP growth per capita based on these factors can then be combined with demographic projections to give forecasts for overall GDP growth.
Wherever possible, publicly available data from official sources are used for the latest available year. Qualitative indicators are normalised (on the basis of: Normalised x = (x - Min(x)) / (Max(x) - Min(x)) where Min(x) and Max(x) are, the lowest and highest values for any given indicator respectively) and then aggregated across categories to enable an overall comparison. The normalised value is then transformed into a positive number on a scale of 0 to 100. The weighting assigned to each indicator can be changed to reflect different assumptions about their relative importance.

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The principal explanatory variable in each industry’s output equation is the Total Demand variable, encompassing exogenous macroeconomic assumptions, consumer spending and investment, and intermediate demand for goods and services by sectors of the economy for use as inputs in the production of their own goods and services.

Elasticities
Elasticity measures the response of one economic variable to a change in another economic variable, whether the good or service is demanded as an input into a final product or whether it is the final product, and provides insight into the proportional impact of different economic actions and policy decisions.
Demand elasticities measure the change in the quantity demanded of a particular good or service as a result of changes to other economic variables, such as its own price, the price of competing or complementary goods and services, income levels, taxes.
Demand elasticities can be influenced by several factors. Each of these factors, along with the specific characteristics of the product, will interact to determine its overall responsiveness of demand to changes in prices and incomes.
The individual characteristics of a good or service will have an impact, but there are also a number of general factors that will typically affect the sensitivity of demand, such as the availability of substitutes, whereby the elasticity is typically higher the greater the number of available substitutes, as consumers can easily switch between different products.
The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
Proportion of the budget consumed by the item. Products that consume a large portion of the consumer’s budget tend to have greater elasticity.
Elasticities tend to be greater over the long run because consumers have more time to adjust their behaviour.
Finally, if the product or service is an input into a final product then the price elasticity will depend on the price elasticity of the final product, its cost share in the production costs, and the availability of substitutes for that good or service.

Prices
Prices are also forecast using an input-output framework. Input costs have two components; labour costs are driven by wages, while intermediate costs are computed as an input-output weighted aggregate of input sectors’ prices. Employment is a function of output and real sectoral wages, that are forecast as a function of whole economy growth in wages. Investment is forecast as a function of output and aggregate level business investment.

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