A framework for risk-based assessment of urban floods in coastal cities

Many coastal cities in developing countries are at the risk of flooding due to a progressive increase in the built-up areas and poor management of storm water. The flooding situation in coastal cities gets accentuated further due to climate-induced natural disasters such as cyclones and climate change-induced sea-level rise that adversely impact the city's natural drainage potential. This study developed a composite urban flood risk index consisting of three sub-indices and 20 key natural, physical, social, and economic influencing variables for a coastal city (i.e., Cuttack) in eastern India, the intensity of storm run-off being one among the many. The intensity–duration–frequency curve developed shows that the city can experience floods with a peak discharge of 1320 cubic metre per second every alternate year for a rainfall intensity of 2-h duration. The urban flood risk index computed for all the city wards shows that out of the 59 wards, only one ward has low flood risk (index value < 0.40) and 20 wards are at high risk (index value 0.55 and above) from the urban flood. Thereafter, factors leading to high risk due to urban floods were identified and the institutional capacities available with the urban utility for fighting floods analysed.


Introduction
Coastal cities play an important role in a country's economy through their contribution to marine output and the tourism sector (Samonte-Tan et al. 2007;Papageorgiou 2016). However, owing to their unique geographic location, i.e. within the flood plains of large rivers, low elevation areas, and proximity to the coastline, they experience floods on a frequent basis. Flooding is regarded as the most damaging of all natural disasters as it leads to the loss of human life, livestock, property, and infrastructure (Douben 2006). As per the estimates, the total population exposed to coastal flooding would increase to 120 million by 2070 (Hanson et al. 2011), and the global economic exposure to river and coastal 1 3 flooding on account of increase in population density is projected to be USD 158 trillion by 2050(Jongman et al. 2012. Much of this impact will be in the coastal cities of Asia and Africa that continue to experience substantial inward migration (Tibbetts 2002;Brecht et al. 2012).
As is the case worldwide, most of the large coastal cities in India are at the risk of flooding due to a progressive increase in the population, built-up areas, and inadequate or poorly designed storm water drainage systems (Patankar 2015;Kumar et al. 2020). Most of the mega coastal cities in India, for example, Mumbai and Chennai, have suffered major flood-related disasters during the last decade. In such cities, on one hand, the urbanisation leading to land use change is resulting in catchments losing their infiltration capacity that increases the magnitude of peak floods by up to eight times, and flood volumes by up to six times in comparison to flooding in rural areas or the riparian zones (NDMA 2010). Thus, the magnitude of storm run-off is high and it occurs very quickly due to a very short flow duration. On the other hand, the natural drainage potential of coastal cities is adversely impacted due to developments on reclaimed land (Daniela and Marco 2017) and climate change-induced sea-level rise (Marfai and King 2008;Kumar et al. 2020). While the former lead to changes in land use and increase in built-up area, the latter cause inundation of land, both further complicating the flood management in coastal cities.
Floods pose serious challenges to growth and socio-economic development in urban areas (Hammond et al. 2005;Kumar et al. 2020). It disrupts urban transport; power supply and public water supply services, and the functioning of sewerage systems. While it hits the economic activities, the public health impact of urban floods can also be serious (Shoaf and Rotiman 2000;Kumar et al. 2020). The 'poor localities' are generally the worst affected, as the quality of services (water supply, sewerage, drainage facilities) available to them is often very poor, and their ability to cope up with emergencies is poor. The people living in low-lying areas also get affected badly by urban floods due to poor natural drainage.
Within flood research, it has been widely accepted that absolute flood protection cannot be achieved (Schanze 2006). Instead, growing attention has been given to the new paradigm of flood risk management based on the effective establishment of both risk mitigation (structural technical flood defence measures such as dams, dikes, or polders) and adaptation (non-structural, "soft" measures such as preparation of the local people, flood insurances, information management, social networks) measures (Krysanova et al. 2008;Li et al. 2016).
In the past, attempts have been made in India to assess flood risk through flood hazard mapping (Sanyal and Lu 2006;Saxena et al. 2013) and vulnerability assessment of flood hazard (Saini and Kaushik 2012;Rani et al. 2015;Singh et al. 2018). However, to prepare for the risk posed by climate-induced disasters (urban flooding in this case), it is important to assess the hazard, exposure, and vulnerability that risk is composed of (Messner and Meyer 2006;Mauro 2014).
The objective of this research study is to develop an analytical framework for assessing urban flood risks in coastal cities that can support the design of strategies for climate resilience of coastal cities. Section 2 of the paper presents the methodology specifically the framework for the development of the urban flood risk index and its computation. Section 3 discusses results obtained from the analysis of daily rainfall data of the selected coastal region city (Cuttack) in eastern India, intensity-duration-frequency of the storm event, peak flood flow volume, developed urban flood risk index, and computed value of the index for various administrative units (referred to as wards) of Cuttack city. Section 4 discusses various natural, physical, economic, social, and institutional factors that increase the flood risk in Cuttack, the institutional capability available with the city municipal corporation to fight floods, and the usefulness of the risk-based assessment approach in better management of floods in coastal cities. The last section presents the study conclusion.

Description of the study area
Cuttack city is located at latitude 20°31′23′′ and 20°52′30′′ North and longitude 85°47′17′′ and 85°78′80′′ East in the coastal plains region of Odisha in eastern India. It lies in the delta formed by the river Mahanadi and its distributary river Kathajodi. As per the Census of India 2011, the city has a geographical area of 192.5 square kilometres (sq. km) and an overall population of 610 thousand that is distributed among 59 administrative units referred to as wards (GoI 2011) (Fig. 1). The city experiences a tropical wet and dry climate and receives an average annual rainfall of about 1800 mm (mm).
The city has a total drainage network of about 1280 kms (km), out of which only 1.5 per cent is natural and the remaining is the constructed one. The city core area is drained by Main Drain 1 and 2 which empties into river Kathajodi and river Mahanadi, respectively. However, due to the inadequate sewerage infrastructure and poor maintenance of the existing drainage network, large parts of the city face problem of waterlogging during the rainy season.
Furthermore, the city is highly prone to natural disasters such as floods and cyclones due to its topography and geographical location. It is saucer-shaped, has highly fertile deltaic land that is densely populated (3100 people per sq. km), crisscrossed by hundreds of rivers and rivulets, and a short distance (about 80 km) from the Bay of Bengal sea. Also, a large portion of the city has low lying areas with an average elevation of only about 36 m above mean sea level and thus gets submerged easily during floods. Thus, the city qualifies the criteria of being in the coastal region, i.e., within 100 horizontal km of the coastline and 100 vertical metres (m) of the sea level, where the direct and indirect impacts of most of the coastal hazards (e.g., flooding) can be experienced (Small and Nicholls 2003). As per the flood hazard atlas of Odisha, the city falls in 'high' (inundated 7-9 times during 2001-2018) to 'very high' (inundated 10-14 times during 2001-2018) flood hazard categories (NRSC 2019).

Development of intensity-duration-frequency curve and estimation of peak flood flow
The intensity of flood-causing rains and the peak flood volume in the study area was estimated using the historical data on rainfall. For this, the intensity-duration-frequency (IDF) curve of rainfall was developed using the daily rainfall data from 1901 to 2019 for Cuttack city. Out of the 119 years that were considered, the rainfall data were not available for 18 years (1970)(1971)(1972)(1973)(1974)(1975)(1976)(1977)(1978)(1979)(1980)(1981)(1982)(1983)(1984)(1985)(1986)(1987). For estimating the missing rainfall data, the linear regression method was used to establish a correlation between the daily rainfall data of the Cuttack and Bhubaneswar (which is at an aerial distance of 19 km from Cuttack city) cities. Then, the missing data for Cuttack were estimated using a linear regression equation.

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Nevertheless, even for the city of Bhubaneswar, daily rainfall data were missing for five years (1970, 1971, 1972, 1975, and 1976). Using the available 114 years data set on daily rainfall, the maximum daily precipitation that occurred in a particular year was identified for all the years. From the daily (24 h) precipitation data, hourly rainfall depth corresponding to 1, 2, 6, and 12 h was estimated using the Indian Meteorological Department's empirical reduction formula that is presented in Eq. (1). The method is widely used for estimating the short duration rainfall values, especially in areas where the data is scarce or is limited in extent  (Rathnam et al. 2001;Chowdhury et al. 2007;Andimuthu et al. 2019;Namitha and Vinothkumar 2019).
where P t is required rainfall depth in mm, P 24 is daily rainfall in mm, and t is the duration of rainfall in hour (hr).
To determine the return period (frequency) of storms of different intensities and duration, Gumbel's probability distribution was used (Chow et al. 2013). As a first step, the frequency factors ( K T ) for the desired return periods ( T ) were computed using Eq. (2). For this purpose, the return period of 2, 5, 10, 25, and 50 years were considered.
In the second step, the rainfall intensity corresponding to the different durations and their return period was estimated using Eq. (3) which is based on Chow et al. (2013).
where X T is rainfall intensity at a given return period, X is the mean of a particular time, S is the standard deviation, and K T is a frequency factor.
From the estimated rainfall intensity of different duration and frequency, the peak flood flow for the city was estimated using Eq. (4) based on Rodriguez-Iturbe et al. (1979).
where Q T is the design peak discharge in cubic metres per second (m 3 /s), with a return period of T years;I T is the average rainfall intensity of design rainfall in mm/hr, with a return period of T years and with rainfall duration being equal to the time of concentration, and A is the catchment area in km 2 . The time of concentration ( T C ) was estimated using Eq. (5) which is based on Kirpich (1940).
where T C is a time of concentration (minutes),L is the maximum length of travel (m), and S is a slope, that is equal to H/L, where H is the difference in elevation between the most remote point in the watershed/basin and the outlet.

Urban flood risk index development: a framework
Risk comprises three components, hazards, exposure, and vulnerability. It occurs due to the interaction of hazardous climate events occurring within a specific time period and the vulnerability of an exposed society or system to it (IPCC 2014). For this study, a framework for assessing the urban flood risk index, including the three components of flood hazard, exposure of the city to flood hazard, and vulnerability of the community to disruptions caused by flood hazards was mainly developed based on research undertaken by the authors on assessing the climate-induced risk in water, sanitation and hygiene (WASH) (IRAP and UNICEF 2017a, b;Kumar et al. 2020Kumar et al. , 2021, and vulnerability of rural households to the (1) P t = P 24 3 √ t 24 (2) problem of water supply for multiple uses due to climate variability (IRAP, GSDA, and UNICEF 2013; Kabir et al. 2016).
The degree of risks induced by intense storms and floods depends on a variety of natural, physical, social, economic, cultural, environmental, and institutional factors. Many of these factors can change from one locality to another with a region. Hence, the degree of risk posed by urban floods can vary within the same city limits (Kumar et al. 2020).
The magnitude of climate-induced flood hazards is determined mainly by natural and physical factors. These include the probable rainfall intensities, surface morphological condition, groundwater levels, terrain slopes soil infiltration rates, the proportion of impervious cover, the occurrence of high tide (relevant for coastal region cities), etc. (Kumar et al. 2020(Kumar et al. , 2021. The degree of exposure of the assets, services, and properties to urban flood hazards is determined by a whole range of natural, physical, socio-economic, and institutional factors. The exposure can be in the form of accumulation of flood waters in a locality; reduced supply of water from the public system for domestic water needs or reduced access to water supply from the public systems; resulting from the breakage/damage to water supply pipelines due to heavy storms, cyclones and floods or flooding of the localities where standposts are located; extent of damage to raw water treatment, and sewerage infrastructure (including drains, sewage treatment plants, etc.); the extent to which access to water sources and sanitation facilities by the households is affected; chances of contamination of drinking water during collection and conveyance, contamination of water supply lines from sewage due to pipeline breakage; contamination of water in drinking water wells with biological matter and pathogens; and precautions taken by the water utilities and disaster mitigation agencies to prevent flooding of low-lying areas, or prevent water contamination (IRAP and UNICEF 2017a, b; Kumar et al. 2020).
Similarly, the degree of vulnerability of the urban population to the disruptions in the services and damage to assets caused by flood hazards is determined by a whole range of natural, social, cultural, economic, and institutional factors (Kumar et al. 2020). This vulnerability can be due to lack of alternate sources of freshwater for drinking and domestic uses at the household level in the wake of the area getting inundated; population congestion, favourable climatic conditions/weather for the spread of disease, lack of social cohesion and ingenuity; and lack of facilities to treat contaminated water or financial resources to buy bottled drinking water or get medical treatment in the case of water-borne or waterbased or water-related diseases (IRAP, UNICEF, and GSDA 2013; Kabir et al. 2016;Kumar et al. 2021).
Based on the urban flood risk assessment framework discussed above, a composite index was developed to assess the overall 'climate-induced flood risk of urban areas', which captures the degrees of hazard, exposure, and vulnerability.

Computation of the urban flood risk index
For the computation of the urban flood risk index, the data pertaining to the identified natural, physical, social, and economic conditions, and the overall cultural and institutional factors of different wards were collected. These included the natural drainage pattern; overall topographical conditions; the water supply, sewerage, and storm water drainage; power distribution and road network; the social profile; economic conditions of the wards; the conditions with regard to nature and degree of access to water supply and sanitation systems; population density; and climatic conditions. The composite urban flood risk index was estimated for various wards of the Cuttack city by separately computing the values of three sub-indices, viz., hazard subindex , exposure sub-index , and vulnerability sub-index as: The value of each sub-index was computed by adding up the normalised value of each factor that it is composed of. For normalisation, all the factors were given equal weightage and the numerical value (score) assigned to each factor was divided by the total number of factors considered for computing the sub-index. Hence, the maximum value possible for each sub-index and also for the risk index is 1.0 (indicating the highest level of risk). The computed urban flood risk index was used categorising the city wards at high risk, moderate risk, and low risk. For this, the ward-wise computed index values were arranged in ascending order, and the average value of the: first 20 wards (first group) was considered as the benchmark for low risk; 21-40 wards (2nd group) for moderate risk; and the last 19 wards (the third group) was taken as high risk. Following this approach, the overall urban flood risk was considered to be low for the wards with index value up to 0.40, moderate for the wards having index value from 0.41 to 0.54, and high for the wards with index value 0.55 and above.

IDF curve for the Cuttack city
The analysis of the daily rainfall data of Cuttack city shows that rainfall exhibits high interannual variability. Between 1901 and 2019, the maximum daily precipitation varied from 35 to 330 mm (Fig. 2). The variability in maximum daily precipitation as indicated by the coefficient of variation in rainfall was estimated to be 48%.
From the rainfall depths estimated using Eq. (1), the rainfall intensity corresponding to different durations and their mean and standard deviation are provided in Table 1. The  1901 1904 1907 1910 1913 1916 1919 1922 1925 1928 1931 1934 1937 1940 1943 1946 1949 1952 1955 1958 1961 1964 1967 1973 1978 1981 1984 1987 1990 1993 1996 1999  computed K T values using Eq. (2) for different return periods of rainfall are provided in Table 2. The overall results using the estimates of rainfall intensity, duration, and frequency are presented in an IDF curve (Fig. 3). The analysis shows that every alternate year, a rainfall intensity of 39.2 mm/hr (considering rainfall of one-hour duration) can be expected. Every fifth year the rainfall intensity increases to 57.1 mm/hr, and every tenth year to 69 mm/hr. The high one-hour rainfall intensity of 84 mm/hr and 95.2 mm/hr is expected after every 25 and 50 years, respectively.

Estimated peak flood flow for the Cuttack city
The time of concentration ( T C ), using Eq. (5), was estimated at 155 min or 2.6 h. SinceT C represents the time needed for water to flow from the most remote point in a watershed to its outlet, rainfall intensity corresponding to a duration of 2 h and return period of 2, 5, 10, 25, and 50 years was considered for estimating the peak flood flow from the total catchment. The entire city of Cuttack was considered as one watershed for the estimation.
The estimated peak flood flow for the entire city of Cuttack is presented in Fig. 4. Every alternate year a peak discharge of 1320 cu m/s is expected, while a very high peak discharge of 3209 cu m/s can be expected after every 50 years. This means that every alternate year, a discharge of 7 cu m/s/km 2 and every 50 years 17 cu m/s/ km 2 of the catchment area is expected in the city.

Urban flood risk index
An index for assessing the urban flood risk, including the three components of flood hazard, exposure of the city to flood hazard, and vulnerability of the community to disruptions caused by flood hazards, are presented in Table 3. Overall 20 factors that influence risk associated with urban floods were considered based on the framework discussed in Sect. 2.3. Out of these, four factors influence hazard, 10 factors influence exposure, and six factors influence vulnerability. Table 3 also provides the rationale for the selection of all the factors, and criteria used for assigning value to them.

Urban flood risk in Cuttack city
The average sub-index value of flood hazard is 0.57 for the Cuttack city, highest for ward number (no.) 24 (0.813), and lowest for ward no. 57 (0.39) (refer Fig. 5). Since for two of the four parameters influencing the hazards, i.e., magnitude of the annual rainfall of the area and frequency of occurrence of daily rainfall with a magnitude exceeding 100 mm, all the wards are assigned the same value, the major difference is due to the characteristics of land use (extent of impervious area) and the elevation with reference to HFL of the river. For all the wards, the average annual rainfall was above 1000 mm in eight out of the last 10 years (2010-2019), and the daily rainfall exceeding 100 mm occurs after every 2.5 years (refer Fig. 2). The extent of built-up area is highest in ward no. 12, 13, 14, 17, 18, 22, 23, 24, 26, 27, 29, 32, 34, 35, and 39 (refer Fig. 1). Out of these, ward no. 24, 27, 32, 35, and 39 are also the ones with low lying areas (w.r.t. to the HFL). Thus, the hazard sub-index value is among the highest for these wards. It was 0.804 for ward no. 27, 0.811 for both ward no. 35 and for 39, 0.812 for ward no. 32, and 0.813 for ward no. 24. Thus, these five wards are the ones that are expected to generate surplus run-off and to be worst affected during an Higher the proportion of built-up area, the higher will be the run-off A coefficient: ranging from '0' for all pervious area to '1' for fully built-up area (4) Elevation with reference to the mean sea level (MSL) If the area is located above MSL or high flood level (HFL) of the river, then surface drainage will not be problematic; if below, then the danger of flooding is very high A coefficient: '0' if above MSL or HFL, and '1' if below MSL or HFL

Exposure of the city to flood hazards
(1) The presence of storm water drainage system in the locality The storm water drainage systems can reduce the exposure of the locality to the urban flood hazard to an extent Binary coefficient: Yes = '0'; No = '1' (2) Presence of natural drainage system in good condition Presence of natural drainage system will also help evacuate the flood water from the locality A coefficient: '0' if in good condition, otherwise '1' (3) Rainfall intensity for which the storm water drainage system was designed against the intensity of rainfall of the standard return period for the area If the rainfall intensity for the drainage system designed is less than the design storm, then the system will not be in a position to evacuate floodwaters that occur from rare events A coefficient: Ratio of the design rainfall intensity and the rainfall intensity with a return period of 50 years, subtracted from '1'. If the ratio is more than '1', the value of the coefficient should be considered '0' (4) Type of sewerage systems in the locality If the sewers are closed, then overflowing of sewers due to mixing of sewage with storm water which contaminates the latter can be avoided A coefficient: Open sewer = high exposure = '1'; Sewer pipes = no exposure = '0' (5) Proportion of people who are dependent on common water points for municipal water supply Exposure of drinking water to contaminants will be more in the case of common water points (standposts) A coefficient: ratio of people dependent on common water points to total population having access to water sources (6) Proportion of people dependent on common toilets outside the premises or open defecation During floods, access to common toilets located outside the dwelling premises will be restricted A coefficient: ratio of people dependent on common toilets to total population having access to sanitation facilities (2) Provision for alternative power supply in case of 'power blackouts' due to floods Access to alternate source of power supply will reduce the vulnerability to disruptions in power supply due to floods Binary coefficient: Yes = '0'; No = '1' (3) Proportion of people having access to individualised sources of domestic water supply Access to private and individual sources of water supply will reduce the vulnerability to disruptions in public water supply A coefficient: if no one, the value becomes '1'; if all households have, then the value will be taken as '0' (4) Ability of the Disaster Response Force (DRF) to reach the locality on time to undertake food-fighting operations Experience shows that the DRF's ability to reach the affected areas for flood-fighting will reduce the impacts on life and properties A coefficient: '0' if DRF is present and is able to access the locality; '1'if not present and also if present but unable to access intense storm. Overall, 4 wards are categorised under low, 26 wards under moderate, and 29 wards under high flood hazard (Fig. 6). The sub-index for exposure has an average value of 0.44 for the city, with ward no. 6 having the highest (0.59) and wards no. 11 and 14 having the lowest values (each having 0.34) (refer Fig. 7). Out of the 10 key parameters influencing the exposure of the city to flood, for three parameters, all wards have the same score. These parameters are as follows: the condition of the natural drainage system that is poor in all the wards; the high risk power installations (high tension power line) that are present in all the wards; and, the storm water drainage system that is designed for 8 mm rainfall for all the wards. However, the storm water drainage system was absent in 11 wards, these include ward no. 1, 2, 5, 6, 48, 49, 50, 56, 57, 58, and 59. In 45 wards, more than 50% of the existing sewerage system is open. It is more than 75% in 12 wards that include wards no. 7, 28, 48, 49, 51, 53, 54, 55, 56, 57, 58, and 59 (most of the wards in city fringes). Out of these, in ward no. 56, 57, 58, and 59 (all in city fringe area), more than 40% of the population access community toilets and/or practice open defecation. Also, in these four wards, more than 30% of the population access water from the common water supply points. Furthermore, the proportion of people living in temporary structures varies from only 0.36% in ward no. 9 and 34.4% in ward no. 38. Also, ward no. 38 is the one with the highest percentage of dilapidated buildings (20.2%).
The sub-index value is above 0.55 for the eight wards, i.e., ward no. 58 (0.553), 48 (0.557), 57 (0.562), 59 (0.576), 56 (0.577), 2 (0.583), 49 (0.585), and 6 (0.594). All these wards are with no storm water drainage system and have a substantial open sewerage system, increasing exposure of the locality in these wards to the urban flood hazard. Furthermore, in ward no. 56, 57, 58, and 59, a high proportion of the people do not have access to improved water and latrine facilities that increase their exposure to poor quality water, leading to adverse impacts on health. Overall, 27 wards are categorised under low, 24 wards under moderate, and 8 wards under high exposure in case of the flood hazard (Fig. 8).
The vulnerability sub-index average value for the city is 0.46, highest for ward no. 20 (0.65) and lowest for ward no. 59 (0.30) (refer Fig. 9). Out of the six parameters that were considered, two variables had the same score. These include provision for alternative power supply during floods (that was not there in any of the wards) and the ability of the district response force to reach the wards on time to undertake flood fighting operations. Furthermore, the pumping machinery to drain flood water was available on almost all the wards (except for wards no. 2, 4, 5, 6, 20, and 32). However, the provision of boats to evacuate people stuck during floods was not available with any of the wards.
The other main factors influencing the vulnerability of the community to flood hazard are the proportion of poor people, i.e., people living below the poverty line (estimated by considering the slum population), and the population density of the wards. The population density was high in the wards falling in city core areas (no. 17, 19, 20, 23, 26, 27, and 30) and low in the wards towards the city fringes (no. 3,48,49,50,51,55,56,57,58,and 59). However,ward no. 17,25,38,55,56,57, and 58 (a mix of those in core and city fringes) are the ones with more than 40% of the population living in slums.
A high population density and a large proportion of the population living in slums increase the chances of spreading of water-related diseases and vector-borne diseases. Considering the scores on these variables, the vulnerability of five wards, i.e., no. 17 (0.555), 19 (0.556), 23 (0.579), 26 (0.585), and 20 (0.652), is among the highest. Overall, 11 wards are categorised under low, 41 wards under moderate, and only 7 wards under high vulnerability (Fig. 10).

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The city level average value for the urban flood risk index is 0.49, with the highest value for ward no. 20 (0.63) and lowest for ward no. 55 (0.39) (refer Fig. 11). Overall, risk index is high (value 0.55 and above) for 15 wards, i.e., no. 2, 4, 6, 15, 19, 20, 24, 27, 30, 32, 33, 35, 39, 41 and 42, most of them in the city core area (refer Fig. 1). These are the wards with high urban flood hazard and where the vulnerability of the community to disruptions in urban services caused by flood hazards is also high (refer Figs. 6 and 10). Only ward no. 55 has low risk (index value up to 0.40). Though a large number of wards (43 in total) fall in the moderate risk category, some of these wards in the city fringes (especially wards no. 48, 49, 56, 57, 58, and 59) have a high degree of exposure to flood hazards (Fig. 12).

Factors responsible for high urban flood risk in different wards of Cuttack city
Concerning the hazard component, all the wards with greater frequency of occurrence of rainfall (annual and daily) of high magnitude, high proportion of impervious area, and presence of low lying areas are expected to receive floods more frequently than the other wards. The built-up area is more than 70% in wards in the core of the city (refer Fig. 1).
For the exposure component, the wards that lack storm water drainage systems have a substantial proportion of open sewerage systems and have a high proportion of the people without any access to improved water and latrine facilities are at greater exposure to the urban flood hazard. Even the wards that have a storm water drainage system, the design capacity (8 mm) is inadequate to capture the peak flood flow (60 mm for rainfall with a return period of 50 years). Furthermore, none of the wards has a natural drainage system in good condition that increases exposure to floods.
Regarding the vulnerability component, high population density and a large proportion of the population living in slums (poor people) were the two major factors identified for increasing the vulnerability of the community to flood hazards as they increase the chances of spreading water-related diseases and vector-borne diseases. The ward-level highest population density was 69,051 persons/sq. km [based on data presented in GoI (2011) and 1 3 CMC (2020)], and it is expected to increase further in all the wards. Furthermore, about 21% of the total population lives in slums at present (CMC 2020). Thus, the risk-based assessment of floods in Cuttack city highlights that the storm water drainage system is unable to handle severe floods that occur once in 20 or 50 years. Furthermore, with major developments happening in the city with the growth of urban infrastructure that has a potential to increase run-off manifolds due to higher built-up area, and the city becoming densely populated which will increase the wastewater generation per unit area, the current capacity of the storm water drainage system becomes inadequate. However, replacing the existing storm water drainage system with a new one with higher capacity or strengthening the existing storm water drainage network in areas where nothing existed may not be feasible. So, options to reduce the storm water run-off generation need to be explored. Furthermore, the city, being located in the delta of two rivers, poses challenges when it comes to draining out the collected storm water. So there have to be specific interventions to drain out the water, along with strengthening the natural drainage system.

Institutional capacity available to mitigate the impact of floods in Cuttack city
At the state (province) level, Odisha State Disaster Mitigation Authority (OSDMA) prepares response to various natural disasters including cyclones and floods. Also, there is a State Emergency Operations Centre (SEOC) that coordinates with OSDMA and provides support to other key disaster management agencies (identified by the OSDMA) in the event of a major disaster. At the district level, the Collector/District Magistrate (DM) is the head of the district disaster management cell and is in-charge of disseminating warnings and coordinating disaster events for the whole district. At the city level (like Cuttack), the Municipal Commissioner (MC) is a supervising authority for preparing response during a natural disaster. In Cuttack city, the office of the MC is assisted by the officers from other line departments in the city, including water resources, power, transport, Public Health Engineering Organisation (PHEO). For preparing an effective response and ensure coordination with all the agencies involved, a Control Room is set up in the MC's office. All the complaints during a disaster, for instance on water logging, choking of drains, fallen trees, road culvert damages, etc., are received and registered by the Control Room. The Deputy Municipal Commissioner's office is responsible for checking the complaints registered daily and disseminate the information to the relevant agencies for them to undertake corrective measures.
Furthermore, the Cuttack Municipal Corporation (CMC) has prepared a City Disaster Management Plan (CDMA) under a project on 'Developing Resilient Cities through Risk Reduction in the context of Disaster & Climate Change'. It acts as a guidebook for the city administration and concerned stakeholders to prepare, plan, and prevent disasters along with the relief, rehabilitation, and reconstruction post-disaster. Also, there is an ongoing Japan International Cooperation Agency (JICA) assisted 'Odisha Integrated Sanitation Improvement Project' under which two main water drains in the city are being renovated and rehabilitated. The objective is to modify the existing two main drains to reduce the volume and duration of flooding for the two-year design storm. However, the progress in  certain specific stretches is slow as the areas around the main drains (especially main drain 1 that passes through the city core) are encroached and densely populated. However, the CMC has not explored new methods of storm water management that apply the emerging concepts in integrated storm water management, particularly the structural and non-structural measures aimed at controlling floods. As a result, all the city wards (except one) are in the moderate to a high flood risk category (refer to Fig. 12). In this context, the risk-based approach to flood assessment as developed and discussed in this research study can be of major support to the CMC to plan and design new and innovative storm water management interventions, targeted first at the wards at the highest level of risk due to flooding and subsequently for other wards in the city which are at the lower risk.

How a risk-based approach can improve flood management in coastal cities
The coastal cities present a unique challenge to the design of storm water drainage systems. Such areas are vulnerable to the effects of tides, have high groundwater table, and relatively flat terrain conditions that present little scope for swift drainage or natural storage of flood waters. While during high tides, low lying areas get inundated making disposal of storm water difficult, during intense storms, the discharge of storm water through drains is ineffective (due to backflow of water from the river/sea) resulting in water logging and flooding. Furthermore, the climate-induced gradual sea-level rise, though significantly lower than the normal sea-level fluctuations caused by tides and storms, can rapidly increase the frequency and severity of coastal flooding. It has been estimated that even less than 10 cm (cm) rise in sea level can double the flooding potential in the coastal region of the Bay of Bengal (Vitousek et al. 2017).
Risk-based assessment framework for urban floods, as demonstrated for a coastal city, helps to identify the areas that need priority action and also provides insights into the key physical, social, economic, and institutional factors, which need to be altered through various interventions in regions/zones identified as having 'high risk', to reduce the three different dimensions of climate-induced risk and to improve the climate-resilience of the coastal cities. The framework will help guide the preparation of the Integrated Storm water Management Plan focusing on the approaches that would help reduce the flood risk; exposure of the assets, services, and properties to the flood; and to an extent the steps that would reduce the vulnerability of the population.
As per the results from the computation of the urban flood risk index, both structural and non-structural measures can be prioritised to manage storm water. The structural measures are both conveyance-oriented and storage-oriented. While the objective of the conveyance approaches is to collect run-off generated by storm and its rapid conveyance to the point of discharge (river or sea) thus minimising damage, the storage approaches focus on providing temporary storage of storm water run-off and subsequently slow release to the receiving water body (detention), or infiltration into the surrounding soil (retention) (Fig. 13). Non-structural measures usually focus on capacity building at the institutional level, e.g., setting or strengthening early warning flood systems; implementing land use regulations; designing and building climate-resilient water supply infrastructure; and educating the masses about precautions to be exercised during disasters. As demonstrated through the risk-based assessment approach, the integrated storm water management solutions that work for an area, however, would be dependent on a range of natural (climatic, rainfall, soils, and geohydrology), physical factors (natural drainage system, the drainage infrastructure and extent of built-up area in the city) and the institutional capacity available for planning, designing, and managing storm water management systems.

Conclusions and policy Implications
Given the frequent occurrence of climate-related disasters such as floods in many of the coastal cities in the developing world, an index for assessing urban flood risk was developed and computed for the city of Cuttack in eastern India. The developed urban flood risk index consists of 20 key natural, physical, social, and economic influencing variables that are organised into three sub-indices (hazard, exposure, and vulnerability). The flood risk assessment for Cuttack city shows that 15 wards (25% of the total wards in the city) are at high risk from the urban flood and 43 (73%) are at moderate risk. Only one ward, i.e., 55, is at low risk. The flood hazard is moderate to high for 93% wards, exposure to flood hazard is moderate to high for 54% wards, and the vulnerability of the community is 'moderate to high' in 81% of the wards.
Furthermore, the institutional capacity in terms of human resources and infrastructure to manage urban floods is inadequate in the city. Also, the design capacity of the secondary and tertiary storm water drainage system is insufficient (8 mm against a 2 hourly rainfall intensity of about 60 mm for a 50-year return period), the natural drainage system is in the poor condition due to encroachments and a high proportion of the built-up area in the city core area. Also, replacing the existing storm water drainage system with a new one with higher capacity, or strengthening the existing storm water drainage network in areas where nothing existed may not be feasible, as has been experienced under the ongoing JICA assisted drains renovation project.
The developed urban flood risk index can be used for other coastal cities for mapping urban flood risk. The approach will allow for the ranking of cities or pockets within cities in the order of risk posed by urban floods, thereby identifying priority areas where storm water management measures are required.