Formalisation of indicators

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Formalisation of indicators

Urban Water Security Dashboard: supplement 1

This document provides a calculation procedure for each indicator within the Urban Water Security Dashboard.

Each indicator is described using the following format: Indicator title [ID]

Indicator rationale: shows how the indicator value relates to urban water security Method: data collection and processing

Score: assignment of indicator score [1-5]

Discussion (optionally): reflects on the sensitivity and limitations of the proposed procedure To derive consistent indicator procedures, the following definitions are adopted:

City proper: the part of the city and its population that is located within the administrative municipality boundaries of the city. This definitions follows the terminology proposed in the World Urbanization Prospects report of the United Nations (UN Department of Social and Economical affairs, 2014). It contrasts with alternative definitions of a city that also include suburbs, like ‘urban agglomeration’ or ‘metropolitan area’.

Coastal city: a city located in a near-coastal zone, i.e. less than 10 m above mean sea level (McGranahan et al., 2007) and within 100 km of a shoreline (Small and Nicholls, 2003), for which one reasonably can assume that the sea or ocean has an influence on its water security.

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Table 1.Overview of indicators (tier 1, white) per category (tier 2, grey) and P, S, I or R index (tier 3, black) with their main methods and primary source of data.

Code Name Method Primary source

1000 Pressure-index (Average (1100, 1200)-1)*25

1100 Environmental pressures Average (1110, 1120)

1110 Water scarcity Average (1111, 1112)

1111 Annual precipitation and

variability Search procedure, global study (Peel et al., 2007)

1112 Freshwater scarcity around city Global study (Mekonnen and Hoekstra, 2016)

1120 Flooding Average (1121, …, 1125)

1121 Rainfall intensity and variability Search procedure, global study (Peel et al., 2007)

1122 Storm surge hazard Global study, search procedure (Muis et al., 2016)

1123 Tsunami hazard Global study, search procedure (Peduzzi et al., 2009)

1124 Expected SLR by 2100 Global study (Church et al., 2013)

1125 Area below MSL +1 m and

subsidence Search procedure, global study (USGS and Google, 1996)

1200 Socio-economic pressures Average (1201, …, 1208)

1201 City population Search procedure

1202 Population growth Search procedure

1203 GDP (PPP) Search procedure, national data (World Bank, 2017)

1204 Slums Search procedure, national data (UN, 2015)

1205 Domestic water use City data, search procedure (IB-NET, 2017)

1206 Water footprint of consumption National data (Mekonnen and Hoekstra, 2011)

1207 Water-intensive industries Search procedure

1208 Condition upstream watershed Search procedure

2000 State-index (Average (2100, …, 2500)-1)*25

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2301 Coastal flood protection

infrastructure City data, search procedure (Hallegatte et al., 2013) 2302 River flood protection

infrastructure City data, search procedure FLOPROS (Scussolini et al., 2016) 2303 Stormwater drainage

infrastructure Search procedure 2400 Sanitation infrastructure Average (2401, 2402)

2401 Coverages and leakages of sewer

system Search procedure 2402 Adequacy wastewater treatment Search procedure

2500 Water quality Average (2501, …, 2505)

2501 Surface water quality Search procedure

2502 Polluted sediments Search procedure

2503 Garbage in surface water Images Panoramio (Google, 2016)

2504 Groundwater quality Search procedure

2505

Salt water intrusion in

groundwater Search procedure

3000 Impact-index (Average (3100, …, 3600)-1)*25

3100 Water supply dependencies Average (3101,3102)

3101 Conflicts over water supply Search procedure

3102 Sustainability of urban water

footprint National data

(Mekonnen and Hoekstra, 2016, Hoekstra and Mekonnen, 2012) 3200 Water supply Average (3201, 3202)

3201 People with adequate water

supply National data (WHO and UNICEF, 2015) 3300 Flood protection Average (3301, 3302, 3302)

3301 Coastal flooding

Global study, search procedure Dartmouth Flood Observatory Database (Brakenridge, 2016)

3302 River flooding

3303 Stormwater flooding

3400 Sanitation Average (3401, 3402)

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4100 Institutional framework Average (4101, …, 4105)

4101 Clarity of roles and responsibilities

Questionnaire, see SI 2 for the number of respondents per city. 4102 Horizontal coordination

4103 Vertical coordination

4104 Corruption

4105 Accountability

4200 Planning Average (4201, …, 4205)

4201 Access to data and information

Questionnaire 4202 Financial resources

4203 Effectiveness disaster management 4204 Strategic planning

4205 Degree of public participation

4300 Operational management Average (4301, …, 4304)

4301 Effectiveness water supply management

Questionnaire 4302 Effectiveness sanitation

management

4303 Effectiveness flood protection management

4304 Effectiveness environmental and ecological management

Note:

City-specific data: city-specific data obtained from databases and indices

Global study: global analysis of a certain phenomenon, e.g. on river basin or national scale National data: data on national level

Search procedure: search procedure with prescribed keywords to identify credible sources via (a) Scopus; (b) Google Scholar and/or (c) Google Search.

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Pressure [1000]

We define pressures as the basic factors, root causes and trends that influence and determine the state of the environmental and infrastructural urban water system (cf. EEA, 1999, WWAP 2006, Pires et al., 2016). We distinguish between environmental pressures [1100] and socio-economic pressures [1200] (cf. Hoekstra et al., 1998, Van Leeuwen et al., 2016). Environmental factors concern the natural threats and carrying capacity of the geographical location of the city. Socio-economic factors measure the claim the city is putting on the available resources.

Environmental pressures [1100]

Environmental factors concern the natural threats and carrying capacity of the geographical location of the city. We distinguish between environmental pressures of water scarcity [1110] and environmental pressures of flooding [1120] because managing the risks of water shortage and water excess is key to the concept of water security (Grey and Sadoff, 2007; OECD, 2013). Water scarcity in a city’s vicinity puts a pressure on meeting water demand with supply (Brears, 2017) while cities located in flood-prone areas might suffer from severe flood risks (Hallegatte et al., 2013, 2011).

Environmental pressures scarcity [1110]

We distinguish between two drivers of water scarcity: Annual precipitation and variability [1111] and freshwater scarcity around city [1112]. The first indicator accounts for the yearly amount of precipitation in the city and its distribution over the year. The second accounts for the freshwater scarcity (i.e. the ratio between renewable freshwater availability and consumption) in the area around the city.

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Annual precipitation and variability [1111]

A shortage of precipitation is a direct driver of water scarcity (Iglesias et al., 2007) and therefore a threat to urban water security. Rainwater harvesting possibilities are limited in a water scarce region.

Moreover, little precipitation in the city implies that the surroundings of the city are also dry. Since rainfall is the main source of groundwater, renewable ground- and river water per capita will also be limited (cf. Jiang, 2009). Hence, the city will have to reach far to fulfil its drinking water demand (cf. McDonald et al., 2014) unless there naturally is a large amount of surface water available which is fed from distant sources. The city competes for these resources with other water users. If freshwater is not available, the city will have to use unconventional sources of drinking water like water reuse and desalination technologies which are highly energy consuming (Wen et al., 2017).

Method

1. Derive average yearly rainfall data from a credible local weather authority, alternatively use two credible other sources

2. Determine if there is a significant dry period from the Köppen-Geiger climate classification map (Peel et al., 2007). Climate types with significant dry period are: Am, Aw, As; all B-climates; Cw, Cs; Dw and Ds.

Scoring

1. P < 200 mmy-1 2. 200 ≤ P < 400 mmy-1

3. 400 ≤ P < 600 mmy-1 OR 600 ≤ P < 1000 mmy-1 AND dry period 4. 600 ≤ P < 1000 mmy-1 AND no dry period OR P ≥ 1000 mmy-1 AND dry period 5. P ≥ 1000 mmy-1 AND no dry period

Discussion

We capture the main intra-annual (within a year) rainfall variability using the Köppen-Geiger

classification to identify significant dry periods within the year. However, in many cases, droughts are caused by inter-annual variability (Iglesias et al., 2007; Joshi et al., 2016), for example during El Nino events (Baudoin et al., 2017). This pressure indicator fails to capture these inter-annual events.

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Freshwater scarcity around city [1112]

A lack of freshwater in the area near the city is putting a pressure on the water supply. We assume that a city will have difficulties in satisfying its drinking water demand, when the blue water (renewable

ground- and surface water) availability in the area is low compared to the water consumption. To satisfy the demand, water will be imported from distant sources (sometimes via inter-basin transfers, cf. McDonald et al, 2014). Governments are tempted to overexploit the local available water resources, thereby violating environmental flow requirements (cf. Mekonnen and Hoekstra, 2016). Alternatively, the city will turn to energy-consuming unconventional water sources like desalination or reuse of wastewater (Wen et al., 2017)

Method

Derive the annual averaged monthly blue water scarcity at 30 x 30 arc minute resolution from Mekonnen and Hoekstra (2016).

1. Select the raster cells from Mekonnen and Hoekstra (2016) that overlap with the city proper or border horizontally, vertically or diagonally

2. Remove 50 % of the cells with the highest water scarcity score so that the 50% most water abundant cells remain.

3. Calculate the average water scarcity score 𝑊𝑆̅̅̅̅̅ of the remaining cells. Scoring

1. 𝑊𝑆̅̅̅̅̅ ≥ 2 Severe water scarcity 2. 1.5 ≤ 𝑊𝑆̅̅̅̅̅ < 2 Significant water scarcity 3. 1 ≤ 𝑊𝑆̅̅̅̅̅ < 1.5 Moderate water scarcity 4. 0.5 ≤ 𝑊𝑆̅̅̅̅̅ < 1

5. 𝑊𝑆̅̅̅̅̅ < 0.5 Discussion

One should be cautious when adapting values from a global study with a coarse grid. The study of Mekonnen and Hoekstra gives an impression of global water scarcity, but is inaccurate for some coastal grid cells. These cells directly discharge to the sea, and often do not have an upstream catchment but do have a high population density. In these cells, there is severe water scarcity according to Mekonnen and Hoekstra. In practice, neighbouring cells can be water abundant so that the city can easily fulfil its drinking water demand. For example, Amsterdam is in the water-abundant Rhine-Meuse River Basin. However, there is water scarcity in many of the relevant grid cells around Amsterdam. We work around

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Environmental pressures flooding [1120]

We distinguish between five drivers of flooding. For all cities, rainfall intensity and variability [1121] puts a pressure on the urban drainage system, and also on flooding from rivers (Chen et al., 2010). For coastal cities, an additional threat is coming from storm surges [1122], tsunamis [1123], sea level rise [1124] and the area located below sea level +1 m [1125] (cf. Chan et al., 2012).

Rainfall intensity and variability [1121]

Intensive rainfall is a driver of flooding. The larger the annual precipitation, the larger the required capacity of the urban drainage. The variability of rainfall over the year puts an even larger challenge on providing sufficient drainage in the city during high precipitation events. Insufficient drainage capacity with respect to extreme rainfall events leads to ‘pluvial’ flooding, causing casualties, damage to assets and failure of critical infrastructures (Hammond et al., 2015).

Method

1. Derive the annual precipitation (P) from a local weather station, alternatively use two other credible sources.

2. Determine if there is a significant dry period from the Köppen-Geiger climate classification map (Peel et al., 2007). Climate types with significant dry period are: Am, Aw, As; all B-climates; Cw, Cs; Dw and Ds.

Scoring

1. P > 3000 mmy-1 OR 2000 < P ≤ 3000 mmy-1 AND dry period 2. 2000 < P ≤ 3000 mmy-1 AND no dry period OR 1000 < P ≤ 2000 mmy-1 AND dry period 3. 1000 < P ≤ 2000 mmy-1 AND no dry period OR 500 < P ≤ 1000 mmy-1 AND dry period 4. 500 < P ≤ 1000 mmy-1 AND no dry period OR 200 < P ≤ 500 mmy-1 AND dry period 5. P ≤ 500 mmy-1_{AND no dry period} _OR _{P ≤ 200 mmy}-1_{AND dry period}

Discussion

The main intra-annual rainfall variability is captured by identification of the significant dry periods using the climate classification. However, flood events mainly result from extreme rainfall events that occur on the timescale of minutes to hours (Berggren et al., 2014). Also, inter-annual variability has a major influence on global flood risks, with the El Niño oscillation being the most dominant example (Ward et al., 2014). To give a more accurate representation of the pressure that rainfall is putting on the urban drainage capacity, one would have to study the intensity and recurrence time of extreme rainfall events, and study the influence of inter-annual variations.

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Storm surge hazard [1122]

A storm surge is ‘a volume of water pushed towards the shore by the wind swirling around the moving depression.’ (Straatsma, 2015). Together with the tides and waves, storm surges can cause high water levels along the coast. Storm surges are considered a significant threat to coastal urban areas (Mucerino et al., 2014). Here, we focus on the storm surge induced water level, including the effects of tides and waves but irrespective of the local infrastructure and other governmental responses.

Method

The extreme level with a return period of 100 year that may arise from a storm surge is derived from Muis et al. (2016).

1. For coastal cities, derive the Extreme Sea Level (ESL) with a return period of 100 year. a. Obtain the calculated storm surge level from Muis et al.

b. In (sub)tropical regions, validate the obtained level by searching Scopus: “city name” + “storm surge” OR “cyclone flood” OR “hurricane flood” OR “typhoon flood” since the paper by Muis et al. indicates that storm surges might be underestimated here (for example in New Orleans). If in the recent history (last 100 years) a large storm surge occurred, adapt the observed storm surge level.

2. For non-coastal cities located near a large lake (> 20 x 20 km), search Scopus: “city name” + “storm search” to derive the ESL with a return period of 100 year.

3. For non-coastal not located near a large lake cities, storm surges do not pose a threat to water security. Scoring 1. ESL ≥ 3.5 m 2. 2.5 ≤ ESL < 3.5 m 3. 1.5 ≤ ESL < 2.5 m 4. 0.5 ≤ ESL < 1.5 m

5. ESL ≤ 0.5 OR Non-coastal cities Discussion

Muis et al. (2016) indicate that their model has a general tendency to underestimate extreme sea levels, however this error is general small (< 0.45 m for 90% of the observation stations). However, major errors occur for tropical cyclone-induced storm surges. For example, for New Orleans the predicted extreme sea level is 2-3 m for a 1:1000 y return period while the city was struck by an 8 m storm surge due to

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Tsunami hazard [1123]

With water security as “(…) an acceptable level of water-related risks to people (…)” (Grey and Sadoff, 2007), an indicator for tsunami hazard should not lack in a framework to assess water security. Tsunamis are considered a serious form of coastal flood risk (Dawson et al., 2004), which clearly puts a pressure on the flood security. To reduce risk, drastic infrastructural and non-infrastructural (evacuation plans, warning systems) measures are to be taken to avoid large damage (Raskin and Wang, 2017). Method

For coastal cities:

1. From Peduzzi et al. (Peduzzi et al., 2009) derive the Potential Wave Height of a 1:500 y event (PWH-500).

If the wave height cannot be derived from Peduzzi et al. (2009): 2. Search for “tsunami” AND “city name” on:

a. Scopus;

b. Google Scholar; c. Google;

and estimate the PWH-500 from the first 20 hits.

If nothing can be found on tsunami risk of the city, assume that the tsunami risk is considered very low.

For non-coastal cities: we assume that it is unlikely that a city will be suffer from a tsunami when its elevation is above 10 m or located more than 100 km from the sea or ocean.

Scoring

1. Very tsunami-prone coastal city PWH-500 > 5 m 2. Moderately tsunami-prone coastal city 2 m < PWH-500 ≤ 5 m 3. Little tsunami-prone coastal city PWH-500 ≤ 2 m

4. Coastal city with very low tsunami risk. It is generally understood that tsunami’s will not impact flood security of the city

5. Non-coastal city Discussion

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Expected Sea Level Rise by 2100 [1124]

Sea level rise puts a pressure on the water security of coastal cities (Scheffran and Battaglini, 2011). Infrastructure and adaptation plans will be required to sustain the current coastline and keep the risk of flooding within acceptable limits. Two factors play a role in modelling local sea level rise: global sea level rise and the regional deviations from this global rise (Church et al., 2013). We account for both global and regional effects. We consider absolute SLR rather than relative SLR. Relative SLR also accounts for the effect of land subsidence, which we include in the next indicator [1125].

Method

For coastal cities: adapt the SLR by 2100 predicted by the IPCC (Church et al., 2013, fig. 13.20 C). For non-coastal cities, sea level rise does not pose a threat to urban water security.

Scoring 1. SLR > 0.5 m 2. 0.3 m < SLR ≤ 0.5 m 3. 0.1 m < SLR ≤ 0.3 m 4. 0 < SLR ≤ 0.1 m 5. SLR ≤ 0.1 m OR Non-coastal city Discussion

The choice for scenario C in the study of Church et al. (2013) is arbitrary, we have no reason to think this scenario is more likely than the others. Score categories were chosen with the intention to represent the worldwide differences in SLR. One would get roughly same scores when both the scenarios and the scoring would change proportionally.

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Area below MSL + 1 m and subsidence [1125]

Area below mean sea level + 1 m

The area below sea level puts a pressure on the water security of a city. The larger the area below sea level, the larger the exposure to flooding. Four issues play a role here. (1) One can look at the area exposed to flooding, but also to population or assets exposed like in the OECD series on coastal risks (Hallegatte et al., 2013; Hanson et al., 2011; Nicholls et al., 2008). (2) One can look at the area exactly below sea level, or put the threshold somewhere else, for example 1 m above sea level. (3) One can look at the area currently below sea level, or account for sea level rise and land subsidence in the future. (4) One can take an absolute value [km2] or normalize the results for the total area of the city [%].

Concerning these issues, we made the following decisions:

1. Consider the area exposed to flooding, because calculating the population or assets exposed can only be done by making crude assumptions (cf. Hanson et al., 2011). Moreover, population density has already been included under ‘socio-economic factors’ and the assets in the city will be related to the GDP.

2. The threshold is put on 1 m above sea level, because these areas are also relatively flood prone when storm surges or high river water levels occurs (following Greiving et al., 2011, as cited in EEA, 2012 as adapted in City Blueprint Framework).

3. The area currently below the threshold is decided, because sea level rise and land subsidence are captured in other indicators.

4. It was decided to take a relative measure, because an absolute value will create a bias towards smaller cities.

We end up with the same definition as indicator 6.2 in the Trends and Pressure Framework of the improved City Blueprint framework (Koop and van Leeuwen, 2015).

Subsidence

For many coastal cities, the surface is subsiding faster than the sea level does rise (Deltares, 2015). Therefore, for coastal cities, the land subsidence rate is an important determinant for future flood exposure.

Note: exclude land subsidence due to soil consolidation which will normally take place the first years after a new building is constructed. This kind of consolidation is quite common and is normally anticipated upon in construction projects.

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Land subsidence

Land subsidence is highly variable in time and space. Following Deltares (2015) we define: MCS = Mean current subsidence rate [mm/year]

MSR = Max subsidence rate [mm/year], i.e. max in space (within city proper boundaries) and time (within last 20 years)

3. Search “City name” + “subsidence”: a. Scopus;

b. Google Scholar; c. Google Search.

4. Estimate the MCS and MSR from the first 20 hits. Scoring

First, assign a score based on the EUA: 1. EUA > 20 %

2. 10 % < EUA ≤ 20 % 3. 2 < EUA ≤ 10 % 4. 0 < EUA ≤ 2 % 5. EUA = 0 %

Second, give a penalty when there is significant, widespread subsidence:

- Subtract one point of the assigned score when MCS > 2 mm/y and MSR > 5 mm/y - Subtract another point of the assigned score when MCS > 10 mm/y and MSR > 20 mm/y

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Socio-economic pressures [1200]

Socio-economic pressures measure the claim the city is putting on the available resources. Guaranteeing water security is particularly challenging in “excessively large and rapidly growing urban centres” (Varis et al., 2006), which is captured in ‘City population’ [1201] and ‘Population growth’ [1202]. Especially vulnerable are cities in poverty (Varis et al., 2006), which we measure in terms of ‘GDP in PPP’ [1203] and cities with large ‘Slums’ [1204]. Slums are water insecure areas by definition (UN-Habitat, 2010). We assume that cities with excessive ‘Domestic water use’ [1205] will have difficulties in meeting water supply with demand (Brears, 2017). Further, we assume that a risk is associated with a high ‘Water footprint of consumption’ [1206] when the products are unsustainably produced in their source regions (Hoekstra and Mekonnen, 2016; Schyns et al., 2015). The presence of ‘Water-intensive industries’ [1207] is putting a pressure on the surface- and groundwater quality in developing countries (Kibria et al., 2016) as well as rapidly growing economies (Brindha and Elango, 2012; Zheng and Shi, 2017) and developed countries (Wilson et al., 2005). Finally, the ‘Condition of the upstream watershed’ [1208] puts a pressure on water security, as upstream activities can significantly deteriorate the urban water quality or lead to flooding (van Ginkel, 2015).

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City population [1201]

We assume that the total size of a city (in terms of population) puts a pressure on the water security of a city. A larger city will have a larger ‘footprint’ since it will claim a larger amount of the available resources (cf. OECD, 2016, para. 'Cities by size'). This is particularly relevant from a supply perspective. A larger city will require a larger reach of water supply infrastructure to fulfil the urban water demand (McDonald and Shemie, 2014). Also from an ecological perspective, a larger city has a larger likelihood to exceed the natural carrying capacity of the environmental system; Sekovski et al. (2012) indicate that urbanization is one of the driving forces of environmental problems in coastal megacities.

Method

Find two independent credible sources that estimate the population of the city proper (PCP). Scoring

When adopting a global perspective, it is common to distinguish between megacities (10 million or more) large cities (5 to 10 million), medium cities (1 to 5 million) and small cities (below 1 million) following (Brears, 2017, following UN Department of Social and Economical affairs, 2014).

1. PPC ≥ 10,000,000 Megacities

2. 5,000,000 ≤ PPC < 10,000,000 Large cities 3. 1,000,000 ≤ PPC < 5,000,000 Medium cities 4. 500,000 ≤ PPC < 1,000,000 Small cities 5. PPC < 500,000 Very small cities Discussion

One can question if a large city population will lead to more water insecurity. From a supply perspective, this seems to be a reasonable assumption, because locally available water will generally not be sufficient to fulfil the water demand. On the other hand, one could reason that a large urban population will bring economies of scale. However, from a systems perspective, the latter seems to be a result of adequate response on something that initially is a problem: how to fulfil the water demand of many people?

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Population growth [1202]

A growth of the population puts a pressure on the water security of the city (Jiang, 2009; Sekovski et al., 2012; Varis et al., 2006). Quicker growth requires a quicker response of the government: construction of new infrastructure to secure water supply and sanitation, increase capacity of wastewater treatment and providing sufficient flood protection.

Method

Because the population growth can vary year-by-year, we use the average annual population growth (APG) over the last 10 years.

1. Retrieve data on APG from a governmental website, alternatively find two other credible independent sources.

2. When city-specific data is also not available from other credible sources, use the national urban growth rate, from the Millennium Development Goals and the World Urbanization Prospects report (UN, 1999).

Scoring 1. APG > 2.5 % y-1 2. 1.5 < APG ≤ 2.5 % y-1 3. 0.5 % < APG ≤ 1.5 % y-1 4. 0 % < APG ≤ 0.5 % y-1 5. APG ≤ 0 % y-1 Discussion

Many cities have a high population density. Population growth in those cities mainly takes place in their suburbs. Sometimes, those suburbs are located beyond the boundaries of the city proper. Although growth in these suburbs might exert a pressure on the water security of the city for various reasons, this growth is not accounted for in this indicator. For example, in the greater Jakarta area, population growth rates are up till 3.6 %. However, only a minor part of this growth is taking place within the city proper boundaries (World Population Review, 2017). Hence, we conclude that by adapting the city proper boundaries we tend to underestimate the growth rate in the greater urban areas.

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GDP in PPP [1203]

The Gross Domestic Product (GDP) is a general measure for the wealth of a country. We assume that the economic performance of a city is an important driver of the water security in the city. Larger financial resources will enable the government to respond better to water issues in the city. Instead of using data on GDP, we use Purchasing Power Parity data, which is corrected for “the rate at which the currency of one country would have to be converted into that of another country to buy the same amount of goods and services in each country.” (Callen, 2007). Nominal GDP does not account for different living

standards between nations where PPP does. Especially for developing countries difference can be large (Callen, 2007).

Method

1. Search “City name” + “PPP GDP” on Google

2. From the first 20 hits, estimate the PPP in USD per capita from a recent credible source. If no city specific estimates are found:

3. Use national PPP data provided by the World Bank (2017) Scoring 1. PPP < 10,000 USD cap-1 2. 10,000 ≤ PPP < 20,000 USD cap-1 3. 20,000 ≤ PPP < 30,000 USD cap-1 4. 30,000 ≤ PPP < 40,000 USD cap-1 5. PPP ≥ 40,000 USD cap-1 Discussion

For cities for which no regional or city data is available, the GDP/PPP is most likely underestimated. For all cities for which we identified regional data, the regional PPP was higher than the national GDP; PricewaterhouseCoopers (2009) shows a similar trend.

In a literature review on water security, Zeitoun et al. (2016) warn for assuming too simplistic relations between water security and GDP. They argue that there are many complex reasons between the two, and one should account for this complexity rather than assuming a deterministic relation. We think we meet this criterion by including GDP as one of the determinants of water security, among many other indicators which account for other parts of these complex relations.

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Slums [1204]

UN-Habitat (2010) defines a slum household as “one or a group individuals living under the same roof in an urban area, lacking one or more of the following five amenities:

1. durable housing (a permanent structure providing protection from extreme climatic conditions); 2. sufficient living area (...);

3. access to improved water (water that is sufficient, affordable and can be obtained without extreme effort);

4. access to improved sanitation (a private toilet, or a public one shared with a reasonable number of people); and

5. secure tenure (…).”

Since amenity 1, 3 and 4 explicitly discuss water-security topics, the presence of slums is putting a pressure on urban water security, by definition. Inadequate housing makes people vulnerable to water related hazards. Moreover, slums are often located in unsafe locations. Thus, the presence of slums can also be an indicator for inadequate spatial planning; apparently, the government is unable to respond to the housing demand. In some places, slums are worsening the water security in the rest of the city: in Jakarta, illegal houses in the river banks cause an increase in water levels (Abidin et al., 2015). Method

The percentage of people living in slums (PLiS), is defined as the number of people living in slums divided by the total number of people living in the city proper, as found in indicator [1201].

1. Derive the national value ‘proportion of urban population living in slums’ from the Millennium Development Goals, indicator 7.10 (United Nations Statistical Divison, 2015)

2. Search Google: “City name” + “slum” + “percentage” and assess the first 20 results to estimate the city specific PLiS from a recent, credible source.

3. When step 2 does not provide a value for PLiS, verify the national figure using a qualitative approach. Search Google for “City name” + “slum” and asses the first 20 results. Verify if the used definition of ‘slum’ meets the above UN-Habitat definition and estimate the percentage of PLiS.

For cities not included in the MDGs monitoring program and that are wealthy (i.e., they score 5 on indicator [1203]) step 3 can be skipped.

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Scoring 1. PLiS > 15 % 2. 5 % < PLiS ≤ 15 % 3. 1 % < PLiS ≤ 5 % 4. 0.05 % < PLiS ≤ 1 % 5. PLiS ≤ 0.05 % Discussion

The concept of ‘slum’ is ambiguous in its definition. Although we use the definition proposed by the United Nations, it is often not clear if the same definition is used in the literature we identified. Nuissl and Heinrichs (2013) show that in practice, governments and researchers have different understandings of what a slum is. Referring to UN-Habitat (2003), they show that in 29 cities, 21 different definitions of slums were used. We decided to use the operationalisation of the UN-habitat (2010) and to check if the so-called ‘slums’ indeed lack one of the five amenities. For example, in many cities there are large numbers of migrant workers involved in construction projects (Dubai, Singapore). Often, the housing conditions of these migrant workers are far below that of the other residents, who refer to these migrant areas as slums. However, we found that these slums do not meet the definition proposed by UN-habitat.

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Domestic water use [1205]

The domestic water use (L cap-1 d-1) is defined as the amount of household water that is used per citizen per day. It is the amount of water used for flushing the toilet, washing the car, bathing, cooking, drinking etc. It contrasts with water use in the city for industrial purposes (captured under the water-intensive industries indicator) and with the consumption of virtual water embedded in consumed products. A large domestic water use puts a pressure on the water security of the city, because great effort is needed to fulfil the water demand. Matching supply and demand is a key concept of urban water security (Brears, 2017; Grey and Sadoff, 2007).

Method

Estimate the domestic (household) water use from two independent credible sources.

1. Check if the cities’ water supplier is present in the IB-Net database (International Benchmarking Network for Water and Sanitation Utilities, 2017). Indicator 4.1: ‘Total Water Consumption, l/cap/day’.

2. Search Google: “Water Use” + “City Name”

Alternatively: “Water use per capita” + “City name” Scoring 1. DWU ≥ 300 L cap-1 d-1 2. 200 ≤ DWU < 300 L cap-1 d-1 3. 150 ≤ DWU < 200 L cap-1 d-1 4. 100 ≤ DWU < 150 L cap-1 d-1 5. DWU < 100 L cap-1 d-1 Discussion

There are different methods to estimate domestic water use. Therefore, one should carefully check how the presented figures in reports have been calculated. Often, the total water withdrawal is divided by the number of inhabitants. This will not lead to the figure we are aiming for, because we restrict ourselves to household water use here and exclude the amount of water used by industrial users. Industrial water use is captured in indicator [1207].

The focus of this is indicator is on water supply. Paradoxically, cities with water poverty according to the Human Development Report (United Nations, 2006) (DWU < 50 L) score good on this indicator. Little water use can point on two things: poverty or practicing economical water use.

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Water footprint of consumption [1206]

The water footprint of consumption is the sum of all water consumed by the citizens, including the ‘virtual water’ embedded in goods consumed (Hoekstra et al., 2011). These goods are normally not produced in the city itself (Hoff et al., 2014) but are imported from the hinterland. There is a risk associated with virtual water imports when the production in the source region is unsustainable (Hoekstra and Mekonnen, 2016; Schyns et al., 2015), see indicator [3202]. Therefore, a large water footprint of consumption puts a pressure on the water security of the city.

Method

Since currently no generally applicable method is established to calculate the water footprints of cities (Paterson et al., 2015), adapt the total (green + blue + grey) water footprint of national consumption per capita from Mekonnen & Hoekstra (2011).

Scoring

Boundaries are the (inclusive) percentile scores (20-40-60-80%) of national water footprints of consumption per capita (Mekonnen and Hoekstra, 2011).

1. WF ≥ 5770 L cap-1 d-1 2. 4622 ≤ WF < 5770 L cap-1 d-1 3. 3864 ≤ WF < 4622 L cap-1 d-1 4. 3258 ≤ WF < 3864 L cap-1 d-1 5. WF < 3258 L cap-1 d-1 Discussion

Due to inhomogeneous consumption patterns within the country, the water footprint of consumption per capita in urban areas differs from national water footprints per capita. Vanham et al. (2016) and Hoff et al. (2014) show that urban consumption in Netherlands and Germany is somewhat different from the national average. We expect that in countries with larger inhomogeneity, this deviation is larger. There is some double-accounting between this indicator and the domestic water use indicator [1205], since the domestic water use is also included in the water footprint of consumption. However, the contribution of domestic water use is small compared to the total water footprint of consumption.

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Water-intensive industries [1207]

Water intensive industries are defined as industries that are known for either large water consumption (withdrawal minus return flow) or large water pollution. It is assumed that the presence of certain types of industries will put a pressure on the water security of the city, because they potentially lead to water pollution or large water consumption (Sekovski et al., 2012).

The following industries are identified as potentially polluting (Rasul et al., 2006; Sekovski et al., 2012; Zheng and Shi, 2017):

- processing of food from agricultural products; - manufacture of textile;

- manufacture of pulp, paper and paper products;

- manufacture of raw chemical materials and chemical products; - tanneries and leather;

Method

1. Check if the city is notorious for water polluting industry by searching “city name” + “water pollution industry” on:

a. Scopus;

2. Asses the first 10 hits to estimate the type and scale of the industries present in the city. 3. Search Google for: “city name” +

a. “Food industry” b. “Textile industry” c. “Paper industry” d. “Chemical industry” e. “Leather industry”

4. For each category, evaluate the first 20 hits: is this type of industry present in the city, and what is the scale of the industry?

Scoring

1. Abundant polluting industries present: widespread and heavily polluting

2. Some heavily polluting industries present; OR widespread moderately polluting industry 3. Some polluting industries in the city, but not widespread nor heavily polluting

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Condition upstream watershed [1208]

In case of a city located along a river, the upstream land use of the river basin puts a pressure on the urban water security of the city, both in terms of water supply and water-related hazards (Abell et al., 2017; Remondi et al., 2016). Many types of upstream activity (urban areas, farming, industrial areas, mining, deforestation) can lead to water quality deterioration, large sediment loads and increased run-off during rain storm events (van Ginkel, 2015). Local practices and conditions are the decisive factors that determine if upstream activities are a substantial threat to urban water security.

Method

1. Determine the upstream catchment that can reasonably be assumed to have an impact on the water security of the city.

2. Determine if the upstream catchment has no influence, minor influence or major influence on the urban water bodies:

a. No influence: there is no river through which water from the upstream catchment can reach the city, there also is no indirect influence

b. Minor influence: there is no river from the upstream catchment flowing through the city, however, indirectly (via channels, lakes etc.) the water bodies in the cities are influenced by the upstream catchment

c. Major influence: a river is flowing through the city: the state of water bodies in the city is directly influenced by upstream conditions

3. Get an impression of the state of the watershed by searching Google Scholar “City name” + a. “Flashfloods” b. “Erosion” c. “Deforestation” d. “Mining” e. “Water pollution” f. “Water quality” g. “Industry” 4. Determine if watershed is in a

a. Alarming condition (several serious issues) b. Poor condition (one serious problem)

c. Moderate condition (minor issues, but still can be significantly improved) d. Fair condition (one minor issue that can be improved)

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5. Upstream catchment has major influence and is in good condition OR Upstream catchment has minor influence and is in good/fair condition OR Upstream catchment has no influence or there is no upstream catchment

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State [2000]

State indicators describe the current physical properties of the infrastructural and environmental elements of the urban water system (EEA, 1999 and WWAP, 2006 as cited in Pires et al., 2016). The urban water infrastructure includes the water supply system, the sewer system and the flood protection infrastructure (Loucks et al., 2005). The urban water supply system is often reaching far beyond the city proper boundaries (McDonald et al., 2014). We therefore distinguish between the water quantity [2100] from the drinking water sources and the state of the water supply infrastructure [2200] which treats the raw water and distributes drinking water to the residents. The drinking water sources are usually not located within the city proper, in contrast to the distribution system, of which we only study the part within the city proper. We further distinguish between the flood protection infrastructure [2300], which protects the residents from coastal, riverine and stormwater flooding, and the sewer system [2400] which collects and treats the wastewater.

The environmental system consists of ground- and surface waters which have a quantity and quality dimension. We account for the water quantity under category [2100], and for the quality of surface and groundwater under category [2500].

Discussion

We take a different perspective on the urban water system than in some other literature. We explicitly include the natural surface and groundwater in our definition, where others (e.g. Loucks et al., 2005) define the urban water system as limited to the supply, sanitation and drainage system. The leading principle underlying our definition is to include those physical elements, which state has influence on the functions mentioned under ‘impact’. This has the following consequences:

- Groundwater quantity: we explicitly distinguish between (a) the state of groundwater from which the city withdraws its drinking water [2102], which is not necessarily within the city proper boundaries; and (b) the local groundwater drawdown within the city proper boundaries [2103]. Overexploitation of (a) poses a threat to water supply to the city, whereas overexploitation of (b) may cause land subsidence which eventually can lead to an increase in flood risk.

- Surface water: concerning quantity, we include water beyond the city proper boundaries because this may impact the water supply function. Concerning quality, we focus on water bodies within the city proper because these have a direct influence on urban ecology.

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Water quantity [2100]

The degree of overexploitation of urban water resources is an indicator for urban water security. Cities may withdraw water from natural or man-made reservoirs and lakes, from rivers or from groundwater (cf. The Nature Conservancy, 2017a). Overexploitation of these resources may hinder the water supply and deteriorate the environment (Brears, 2017). Alternatively, the city may turn to unconventional sources of water supply like desalination or recycled wastewater. The water quantity indicators relate to the state of the conventional sources of water supply.

Supply continuity reservoirs and lakes [2101]

Many cities rely on reservoirs and lakes as a source for the water supply (McDonald and Shemie, 2014; Mukherjee et al., 2008). We assume that large buffers of freshwater within reach of the urban

infrastructure have a positive influence on the water security of a city. This indicator captures the supply continuity from these reservoirs. Water insecurity arises when a reservoir or lake on which a city is dependent is suffering from water shortages. Water shortages can originate from too little reservoir inflow or from a reservoir with insufficient storage capacity compared to the urban water demand. Method

1. Identify the reservoirs and lakes within reach of the cities’ supply infrastructure, by: a. searching on Google (“water supply” + “city name”) and

b. consulting the Urban Water Blueprint database (The Nature Conservancy, 2017) c. consulting the Global Reservoir and Dam (GRanD) Database (Lehner et al., 2011) 2. Calculate the following ratios:

a. Maximum storage capacity (SC) to daily urban water demand (WD) in days b. Maximum storage capacity (SC) to daily reservoir inflow (RI) in days c. Only when SC/WD ≥ 365 d: check if WD < RI

Scoring

Step 1: assign score based on SC/WD-ratio (days)

1. SC/WD < 30 d OR No reservoirs or lakes 2. 30 d ≤ SC/WD < 60 d

3. 60 d ≤ SC/WD < 120 d 4. 120 d ≤ SC/WD < 365 d 5. SC/WD ≥ 365 d

Step 2a: for reservoirs with SC/WD < 365 d, subtract one point of the score if the recharge of the reservoir is larger than 1 year (i.e. SC/RI > 365 d), because the reservoir is likely designed too large

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Dependency overexploited aquifers [2102]

Globally, many aquifers are overexploited: water withdrawals exceed aquifers’ recharge rates, leading to depletion (Gleeson et al., 2015; Wada et al., 2010). Groundwater is an important source of urban water supply worldwide (Abell et al., 2017; Han, 1998; McDonald and Shemie, 2014). If a city currently withdraws its water from an overexploited aquifer, this is a source of insecurity since the withdrawal cannot be sustained on the long term. This impacts the security of the water supply and leads to environmental degradation (Sekovski et al., 2012).

We distinguish between dependency on overexploited aquifers in this indicator and local groundwater drawdowns in the next indicator. The former aquifers can be far from the city boundaries, and the main insecurity here arises from insecurity of the water supply. The latter concerns the groundwater directly below the city as a result of decreased recharge and overabstractions, leading to land subsidence, salt water intrusion and pollution of aquifers (Goorden et al., 2015), which is captured in the next indicator. Method

1. Search: “city name” + “groundwater resources” on: a. Scopus;

b. Google Scholar; c. Google Search;

2. Assess the first 20 hits to estimate:

a. the percentage of water a city withdraws from groundwater out of total water demand; b. the ratio between natural recharge and withdrawal: the GroundWater Footprint (GWF)

Gleeson et al. (2012);

c. the depletion time of the aquifer (DTA): the time it takes to deplete the entire aquifer at the current rate of depletion.

3. If city-specific data is not available, estimate GWF and DTA from global studies (BGR and UNESCO, 2013; Gleeson et al., 2012).

Scoring

For cities withdrawing > 20% of total water demand from aquifers: 1. GWF > 5 AND DTA ≤ 50 y

2. 1 < GWF ≤ 5 AND DTA ≤ 100 y OR GWF > 5 AND DTA > 50 3. 1 < GWF ≤ 5 AND DTA > 100 y

4. GWF = 1 5. GWF < 1

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Local groundwater drawdown [2103]

In contrast to the previous indicator, which captured the unsustainability of the water withdrawal, this indicator describes the local groundwater conditions in terms of drawdown of the groundwater table. Drawdown of groundwater levels below the city, as a result of decreased recharge and large

abstractions, might lead to land subsidence, salt water intrusion and pollution of aquifers (Goorden et al., 2015).

Method

1. Search for “city name” + “groundwater” on: a. Scopus;

b. Google Scholar; c. Google Search

2. Assess the first 20 hits and from two independent, credible sources estimate the severity of groundwater drawdown in a qualitative matter, by following the expert judgement of the researchers.

Scoring

1. Groundwater drawdown is considered a major problem 2. Groundwater drawdown is considered a problem

3. Groundwater drawdown has been reported for this city, but is within acceptable limits 4. Minor groundwater drawdown is present, but not considered a problem

5. There is explicit evidence that no groundwater drawdown occurs Discussion

Local groundwater drawdown is not necessarily the same as dependency on an overexploited aquifer, because a city can withdraw its groundwater from far beyond its boundaries, such as for example is the case in Amsterdam (Gemeente Utrecht, 2013). It is possible that local groundwater conditions are good, while the city still depends on an overexploited aquifer. On the other hand, it could be that the overall groundwater availability in the region is sufficient to provide the water demand, but that due to illegal groundwater abstractions and limited infiltration the local groundwater level dropped severely (e.g. Onyancha et al., 2014).

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Water supply infrastructure [2200]

Security of water supply is crucial for the health of the urban population and the economy (Loucks et al., 2005). Water supply is so crucial to urban water security, that many people define urban water security in a narrow way as meeting urban water demand with supply (Brears, 2017). The water supply system consists of preparing drinking water in a treatment plant and transporting it to the users via a

distribution system. Important aspects of the state of the supply system are the coverage of the piped water supply system, the supply continuity, the maintenance and age of the supply system, the metering and pricing system and the quality of the delivered water. Because this is a rather long and closely related list of indicators, we aggregate several indicators and distinguish between (1) the coverage and leakages of the supply system [2201] and (2) the adequacy of the water delivered as input to the system: water quality and continuity [2202].

Coverage and leakages of water supply system [2201]

We assume that an adequate water supply distribution system should cover the whole city and transport the water with a minimum amount of leakages. IB-NET (2017) distinguishes between two types of water supply coverage: households with a direct service connection and households within reach of a public water point. We assume that the minimum acceptable threshold is that all citizens do have access to any of the two types of water supply. A desirable situation is that all people have access to water at their households while the best situation is when the water is delivered with a minor amount of losses. Method

From the IB-NET database, or other credible sources, estimate:

1. The total percentage of people with access to piped water (total access, TA)

2. The percentage with direct service connections at the households (household access, HA) 3. The percentage of non-revenue water (NRW) (≈ unaccounted water rate, leakages) When city-specific data is lacking use national data from the Joint Monitoring Program (WHO and UNICEF, 2015a). Scoring 1. TA ≤ 90 % 2. 90 < TA ≤ 99 % OR TA > 99 % AND HA ≤ 75 % 3. TA > 99 % AND 75 < HA ≤ 99 % 4. TA > 99 % AND HA > 99 % AND NRW > 10 %

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Continuity and quality of water supply [2202]

This indicator measures the water quality and continuity from the supply network. We assume that a minimum acceptable threshold is that water is always available from the network. A higher score for water security can be obtained when the quality of the delivered water is better.

Method

1. Identify the major water supply company of the city

2. Estimate the supply continuity (SC) in hours per day from a credible source: a. IB-NET (2017): indicator 15.1 – Continuity of Service

b. Google Search: “Water supply continuity” + “City name”, assess the first 20 hits 3. Estimate the water quality (WQ) of the supplied tap water:

a. Google Search: “Drinking water quality” + “City name”, assess the first 20 hits Scoring

1. SC ≤ 23 h d-1

2. 23 < SC ≤ 23.95 h d-1

3. SC > 23.95 h d-1 AND WQ is poor: not suitable for drinking

4. SC > 23.95 h d-1 AND WQ is fine: officially suitable for drinking water, but this is generally questioned by the residents

5. SC > 23.95 h d-1 AND WQ is very good: no doubts on suitability for drinking water Discussion

We encountered several cities (Dubai, Hong Kong, Beijing) where the water supply company claims the water quality meets drinking water standards, but where people commonly hold the belief that the water is undrinkable. This belief can have various reasons: (1) the claim of the water supply company is untruthful; (2) the water was indeed properly delivered to the system, but degenerated in the distribution system; or (3) the tap water is safe and the beliefs were false. All these cities were assigned score 4 when the doubts about the water quality seemed widespread based on step 3 of the method.

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Flood protection infrastructure [2300]

Garrick and Hall (2014) show that a risk approach to water security currently is the dominant approach in framing water security (e.g. Grey et al., 2013; Hall and Borgomeo, 2013; UN-Water, 2013). The

assessment of flood risks for coastal cities (Hallegatte et al., 2013; Hanson et al., 2011) is a central issue within this approach. In contrast, from the perspective of urban water management, the focus is mainly on urban drainage (Brown et al., 2009). Anticipating these two types of framing of urban water security, we account for flooding from the coast, rivers and for stormwater flooding due to insufficient drainage. We therefore estimate the flood protection levels of the coastal, riverine and stormwater flood

protection infrastructure.

Coastal flood protection infrastructure [2301]

Coastal cities have to be protected against high water levels and waves in the ocean or sea which may result from high cyclic tides, sea level rise, storm surges or tsunamis (Jha et al., 2012). Inadequate flood protection infrastructure might result to a considerable flood risk, which is a threat to urban water security.

Method

For coastal cities:

1. Derive the estimated (maximum) coastal flood protection level (CFP) in terms of return period (y) from the OECD flood protection database (Hallegatte et al., 2013)

2. For cities not included in this database, search: “city name” + “flood protection level” + “coast” on

a. Scopus;

3. From the first 20 hits, estimate the CFP.

4. When no flood protection level can be found, estimate the CFP from the occurrence of coastal flooding, indicator [3301].

For cities neighbouring large lakes (> 20 x 20 km), perform the search procedure of step 2: “city name” + “flood protection level” + “name lake”

Scoring

1. CFP ≤ 10 y 2. 10 y ≤ CFP < 50 y

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River flood protection infrastructure [2302]

Cities located in the floodplains of rivers, must be protected from river (fluvial) flooding (Jha et al., 2012). This indicator captures the state of the river protection infrastructure in terms of recurrence time of the design flood event.

Method

For cities exposed to river flooding:

1. Derive the river flood protection level (RFP) in years from the ‘design layer’ of the FLOPROS database (Scussolini et al., 2016)

2. For cities not included in the ‘design’ layer of the FLOPROS database, search “city name” + “flood protection (level)” + “river” on:

a. Scopus;

3. From the first 20 hits, estimate the RFP.

4. When no flood protection level can be found, estimate the FRP from the occurrence of river flooding, indicator [3302]

For cities not exposed to river flooding, assign score 5. Scoring

1. RFP < 5 y 2. 5 ≤ RFP < 20 y 3. 20 y ≤ RFP < 100 y 4. 100 y ≤ RFP < 200 y

5. RFP ≥ 200 y OR not exposed to river flooding Discussion

For many cities, the protection level of the infrastructure in terms of return period is not found in literature. Also, inconsistencies between official protection levels – in governmental documents – and actual flood protection levels – as seen from the actual flood events – are not exceptional. Therefore, we often estimated flood protection levels from the observed impacts.

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Stormwater drainage infrastructure [2303]

This indicator captures the state of the urban drainage infrastructure in terms of recurrence time of the design storm event (y). Insufficient stormwater drainage will have an impact on human health and causes damage to assets (Butler and Davies, 2004).

Method

1. Search “city name” + “drainage” on: a. Scopus;

b. Google Scholar; c. Goole Search;

2. Assess the first 20 hits to estimate the recurrence time of the design storm event (DSE) in ordinary residential areas within the city proper.

3. When no recurrence time of the storm event can be found, estimate the DSE from the occurrence of stormwater flooding, indicator [3303].

Scoring

Following recommended European Design frequencies (Butler and Davies, 2004): 1. DSE ≤ 0.5 y 2. 0.5 ≤ DSE < 1 y 3. 1 ≤ DSE < 2 y 4. 2 ≤ DSE < 5 y 5. DSE ≥ 5 y Discussion

The protection level of the urban drainage may vary over the city, with the DSE of city centres usually higher than that of the residential areas (Butler and Davies, 2004). In several cities, we found that flooding occurs more often than expected based on the design storm event. We then estimated the actual DSE based on the occurrence of flood events in step 3.

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Sanitation infrastructure [2400]

Adequate sanitation infrastructure is essential for urban water security. Sanitation facilities are required to ensure human health (UN-Habitat, 2003) and adequate treatment of sewage is needed to prevent water-associated diseases and to guarantee the ecological, recreational and aesthetic functions of water in the city (cf. Brown et al., 2009). We distinguish between the state of the sewage collection system in terms of coverage and leakages [4201] and the adequacy of the treatment of the collected wastewater [2402] (Loucks et al., 2005).

Coverage and leakages of sewer system [2401]

Wastewater management clearly plays a role in achieving water security. In the Millennium

Development Goals, the focus was on providing access to sanitation facilities. Less attention was paid to adequate collection, discharge and treatment of wastewaters from these facilities (World Water Council, 2012, as cited by UN-Water, 2015). A small sewer coverage directly impacts the health of citizens that lack adequate sanitation facilities and negatively influences the quality of water systems and the functions fulfilled by it.

Method

1. Search: “Sewer coverage” + “city name” on a. Scopus;

2. Assess the first 20 hits, and from two independent credible sources, estimate:

a. Sewer coverage (SC), defined as the percentage of households in the city that is connected to a sewage system which is connected to a treatment plant. Not included are: sewage systems that discharge on the surface water without treatment in a plant and alternative forms of sanitation facilities like septic tanks.

b. State of Sewer (SoS), which we define as the current state of the sewer system. The state can be: good, i.e. well-maintained, and not very old, so that there is a minor amount of leakage; moderate, i.e. not so well maintained or rather old, so that is a moderate amount of leakages; poor, i.e. not well-maintained and old, so that there is a large amount of leakages.

Scoring

1. SC ≤ 75 % 2. 75% < SC ≤ 95 %

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Adequacy wastewater treatment [2402]

Via the sewer network, wastewater is transported to a treatment plant. Wastewater treatment is the process of removing pollutants from raw sewage before it is discharged to the surface water (Loucks et al., 2005). The adequacy of the wastewater treatment is an important indicator for urban water security because inadequate treatment leads to high loads of organic matter, pathogens, nutrients and other pollutants in the surface water. This threatens the health of people in the city, the environment and ecology and the recreational-aesthetic function of water in the city.

In the most insecure state, the raw sewage is directly discharged to the surface water. This is not

uncommon in developing countries (cf. Prihandrijanti and Firdayati, 2011). If wastewater is treated, four steps are distinguished (Loucks et al., 2005):

- preliminary treatment: removal of solid materials (waste, large particles, sand); - primary treatment: removal of suspended solids and greases;

- secondary treatment: biological treatment to remove dissolved organic matter and sometimes nutrients;

- tertiary treatment: removal of pathogens, for example by adding chlorine or using UV-light. Several indicators can be proposed to measure the effectiveness of the process, e.g. nutrient recovery, energy recovery, sewage sludge recycling and efficiency of the treatment process (Koop and van Leeuwen, 2015) .

Method

1. Search “City name” + “wastewater treatment” on: a. Scopus;

2. Assess the first 20 hits, and from two independent, credible sources estimate the quality of the treatment process.

Scoring

Majority of sewage receives:

1. no wastewater treatment or only preliminary treatment; 2. only primary treatment;

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Water quality [2500]

In most literature on water security, the focus is on either matching water supply and demand (Brears, 2017) or protection against water-related hazards (Garrick and Hall, 2014; UNESCO-IHP, 2009). Less attention is paid to water quality, most likely because the ecological urban ‘service delivery function’ is usually fulfilled in a later stage than water supply, sanitation and flood protection (Brown et al., 2009). However, several authors argued for a more integrated perspective on water security which also includes water quality (Cook and Bakker, 2012; Zeitoun et al., 2016). We include water quality as a state indicator for urban water security for three reasons: 1) water quality is crucial for fulfilment of

ecosystem services (Stewart-Koster and Bunn, 2016) and the urban water image (recreational/aesthetic) of a city, which we consider important functions of urban water; 2) water quality deterioration may have a direct influence on the security of the water supply; 3) insufficient water quality may result in water associated diseases.

We distinguish between the quality of surface water and groundwater. Related to surface water, urban water bodies become polluted from contaminants of stormwater (Barałkiewicz et al., 2014), from

domestic or industrial discharges or from water pollution in the upstream catchment (Loucks et al., 2005; van Ginkel, 2015). Next to the surface water quality [2501], we measure the degree of sediment

pollution [2502] and the amount of garbage in the surface water [2503].

Related to groundwater, we observe that the key concerns with respect to urban groundwater quality are: the deterioration of groundwater sources due to pollution from anthropogenic sources and salt water intrusion due to overpumping of fresh water aquifers. We capture these aspects in indicator [2504] and [2505] respectively.

A critical review of water quality shows several aspects that complicate the mutual comparison of different data. Water quality can be highly variable over space and time. Further, there are many

different water quality parameters which standards are different from city to city. Moreover, the desired water quality depends on the function of the water body in the city. In the absence of global data on water quality, we based our assessment on city-specific water quality studies. To enable a mutual comparison of these studies, we follow a qualitative assessment in which we assess the extent and severity of the pollution. We follow the expert judgment of the authors of the identified studies, rather than doing a quantitative comparison of water quality parameters.

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Surface water quality [2501]

The quality of surface water is an important constituent of urban water security because it has an impact on human health and the quality of the ecosystem in the city (Stewart-Koster and Bunn, 2016). There are several urban sources of water pollution (Loucks et al., 2005; Scott and Frost, 2017). Stormwater

drainage may bring pollutants from the streets like oil, rubber and polluted sediments. Untreated sewage may enter the surface water through leakages in the sewer system or from direct discharge. Insufficiently treated effluents from industrial and domestic wastewater treatment plants may also contribute significantly to water pollution.

Some main urban water quality issues are (Brears, 2017; Loucks et al., 2005): bacterial contamination (fecal coliform), organic pollution (high BOD, COD, low DO), nutrient pollution (Nitrite-nitrate,

phosphate), inorganic pollutants (heavy metals/toxics), endocrine disruptors and microplastics (Lebreton et al., 2017; Tsang et al., 2016).

Method

1. Identify representative water bodies in the city, using a map. 2. Search on “water quality” + “city name” on:

a. Scopus;

b. Google Scholar; c. Google search.

3. Assess the first 20 hits, and estimate the severity and extent of the pollution based on the (qualitative) expert judgement of the authors in the identified studies.

Scoring

1. Widespread and severe pollution of surface waters

2. Locally severe pollution, but not widespread; OR widespread pollution but not severe 3. Locally pollution, but neither widespread nor severe

4. Incidents of parameters just above acceptable thresholds but in general unpolluted surface water

5. Surface waters are explicitly reported as clean Discussion

The availability of literature on water quality varies from city to city. Moreover, the issues discussed in the literature are diverse and often reflect a difference of scientific development rather than a difference in water quality. For developing countries, one mainly finds literature and reports from NGOs on high

Formalisation of indicators