case study flood in chennai

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The 2015 Chennai Flood: A Case for Developing City Resilience Strategies

Soumita Chakraborty , Umamaheshwaran Rajasekar

Over the last 25 years, the world has seen a rise in the frequency of natural disasters in rich and poor countries alike. Today, there are more people at risk from natural hazards than ever before, with those in developing countries particularly at risk. This essay series is intended to explore measures that have been taken, and could be taken, in order to improve responses to the threat or occurrence of natural disasters in the MENA and Indo-Pacific regions. Read More . ..  

The Chennai metropolitan region (CMA), with an area of 1,189 sq kms and a population of 8,653,521, is the fourth-largest populated city in India. [1] This city, located in north eastern part of Tamil Nadu is a flat plain bounded on the east by Bay of Bengal and on the remaining three sides by Chengalpattu and Thiruvallur districts. Expansion in terms of area as well as population has led to a shift in land use and land cover patterns across the region.

Situated along the eastern coast of India, Chennai is exposed to violent storm surges and flooding during northeast monsoons (September to November). Although local flooding is an annual phenomenon in selected parts of the city, extreme events, such as the 1918 cyclone and 1985 floods, had faded from people’s memory. [2]  However, history repeated itself in the city and neighboring coastal districts in November-December 2015, when a devastating flood affected more than 4 million people, claimed more than 470 lives and resulted in enormous economic loss. [3]

The sudden and unprecedented nature of the flood led to ad hoc and uncoordinated relief and response activities by different governmental and non-governmental agencies. Industrial and commercial centers were forced to temporarily shut down their production due to loss of power, shelter and limited logistics. Amid the chaos and widespread impact, the event brought people and institutions in and outside Chennai together, to provide support to the victims affected by the flood. Help reached the affected areas and their residents from different sections of society and in variety of forms. The lessons from this case study and others like it can help urban centers elsewhere in Asia to plan for similar eventualities.

Challenges Faced During and Following the Event

Flooding often handicaps the affected community by adversely affecting its educational system, food availability, mobility and access to energy on a daily basis. Chennai was no exception: daily functions became a challenge for the entire city.

School authorities faced numerous challenges, ranging from the sudden need to shift and secure school records / admit cards and postpone exams, to maintaining physical infrastructure and equipping schools to serve as shelters. Following the event, school authorities faced yet another set of daunting tasks related to the resumption of the academic session (e.g. repairing and replacing furniture, etc.) in schools that had been shuttered (for 10 to 33 days) in various parts of the city.

Flooding often handicaps the affected community by adversely affecting its educational system, food availability, mobility and access to energy on a daily basis.

Food logistics arrangements across the affected communities included the unavailability of manufacturing capacity and delivery mechanisms. The lack of accessibility to several parts of Chennai due to severe flooding made identification of delivery points and transport routes more difficult, which deprived some local communities of basic food supplies required for survival. During the first 24 hours of flooding, the main concern of the local supermarkets providing food supplies to surrounding areas, was to safeguard perishable items not only from getting wet but also to keep them from spoiling (since there was no electricity). However, it was critical for them to meet customer demand, keeping in mind the limited food availability and lack of communication within their management team.

First responders and information providers faced difficulties in providing accurate real time information to local communities on flooded areas, accessibility of roads, road condition, traffic flow and current weather scenario.

Flooding of roads, tracks and supporting infrastructure, delayed and suspended provision of necessary services. Moreover, several hospital staff were unable to get to work or extend their support due to being affected by the flood themselves. It was a greater challenge for hospital authorities, to safeguard patients admitted to Intensive and Critical Care units (ICU) or those under ventilation through maintenance of power supply.

The Chennai flood had a devastating impact on businesses, especially on small and medium-sized enterprises (SMEs), who were unprepared and vulnerable to both direct and indirect impacts. Flood water entered the first level of most of the offices and shops, reaching a height of approximately two meters in some areas. This damaged products, stocks, storage units, electrical equipment. In post disaster scenario, several businessmen in Chennai were unable to operate for three months due to lack of process-service delivery, finance, logistics, management implications and loss of customer base. Service station owners too had a hard time in recovering broken cars, fixing damaged engines, car interiors, upholsteries and external impact damages. In post flood scenario fungal attack and rusting were additional issues faced by them to continue their business.

Community-Based Organizations (CBOs) faced a plethora of challenges and obstacles, as did official first responders ...

Community-Based Organizations (CBOs) faced tough challenges, such as contingency planning at zone/ district level, stock piling of relief materials/supplies, arranging for inter-agency coordination, preparing evacuation plans, providing public information and conducting field exercises. Service providers in the transport sector had to undertake route planning and ensure priority management. Situation worsened due to lack of mechanisms to mitigate impacts of flood, such as road closure notification, absence of traffic control warning signs, emergency detour routes, etc. which are essential during such extreme events. Thus, they procured boats and hired fishermen to commute to inundated parts of the city.

Likewise, government officials — first responders, such as the fire department, the National Disaster Response Force (NDRF) and the police, in particular — faced a plethora of challenges and obstacles. They not only had the responsibility of conducting rescue operations, but also of road clearance and provision of other facilities to ensure supply of basic necessities throughout the affected communities. The fire department managed calls, coordinated between departments and controlled water distribution system, in the absence of power for prolonged periods. They had to function with disrupted utility services, clear streets of debris, waste and fallen trees in low lying areas and also ensure steady and quick pumping out of water from flooded pockets. NDRF on the other hand, was required to conduct timely rescue operations with small teams, coordinate with local officials, mobilize limited human resources to priority areas and commute using limited transport vehicles and boats. They also had electricity constraints in setting up onsite operational coordination control room (OSOCC) and shelters for both their team as well as the local community. In some instances, the Chennai police were unable to ensure effective and timely response, due to lack of common command system, clear assignment of duties and demarcation of roles to respective officials, for times of emergency.

Resilience Efforts

Various segments of society assisted local communities and relief providers in affected parts of Chennai to cope with the flood. The Chennai government, private schools and the Parent Association were three strong pillars which supported victims in the aftermath of the flood. School children from Hosur made artefacts for sale at an art show to raise funds for a severely affected government school in Poonamallee. Another group of 15 teachers and 40 alumni of the TVS Academy School of Hosur, travelled to Chennai to help improve the infrastructure of Aringar Anna Government Girls Higher Secondary School, Poonamallee. These groups extended help in painting damaged walls, blackboards and building new toilets. During and post flood, government schools were used as relief camps where food and health issues were partially covered by government and parent association.

Various segments of society assisted local communities and relief providers in affected parts of Chennai to cope with the flood.

Private enterprises, such as restaurants, taxi service providers and automobile service centers, also joined hands with the government to provide relief to the flood affected population. Kolapasi, a Chennai-based restaurant, was turned into a temporary food relief agency. Social media was used for awareness generation on the initiative and also to raise funds. Individuals of all age groups and across all professions, supported this initiative by volunteering to cook, wash utensils, pack and deliver food. About 1.7 lakhs food boxes were distributed across the city.

The ride-hailing company Ola started operating boats, which also provided an important learning for future preparedness measures. They strategically identified water routes for providing service to even the most inaccessible areas. They also helped the Fire Department in conducting their rescue operations. Similarly, a vegetable and milk supply chain, Heritage Fresh, sold their commodities at a subsidized rate when prices in parts of Chennai were on the rise. Mobile vegetable shops also put in efforts to reach out to as many flood affected people as possible. Online food service providers, such as Zomato, added one extra meal on behalf of the company for every order that was placed for the stranded people.

The impact of flood on health sector was a complex issue, as the threats to health were both direct (for example, flash flood) and indirect (for example, a hospital needing to be closed due to flooding). To protect and promote health of patients and minimize health risks, sustained treatment for chronic infectious disease were provided through voluntary camps. 51 patients were evacuated and ICU wards were shifted to first floor; special care was taken while shifting new born babies, mental patients, elderly or patients with disabilities; cleanliness was ensured by internal experts using prescribed norms and dosage of chemicals and sump pumps were installed in hospitals to drain out water. Adequate stock of medicine, injections and IV fluids (intravenous) were available for continued medical care of the patients. Immediate actions in response to the flash flood situation from the ESIC was to direct all capacities of the existing health care system towards flood relief, prevention of disease outbreak, water disinfection and vigilance for future outbreaks.

Funds for energy and fuel supply were of least priority, but their demand was high in slums and remote areas where it was required for the survival of sick family members, the elderly and children. Organizations like Oxfam, provided support through the provision of energy and fuel supply to households. Private companies like Servals Pvt Ltd. initiated a similar program of providing specially designed rehabilitation kit, which included a kerosene stove, water filter, utensils, disinfectant, etc. to the slum dwellers, manual laborers and villagers in the worst hit areas, who were not covered under government programs. Along with the kit, training was also provided to ensure optimum utilization of the given products. 

Small- and medium-sized enterprises (SMEs) suffered both direct (physical) and indirect (man-days/ sales) loss. They demanded government to provide interest free loans and delay their tax payment along with other repayments. SMEs took adequate measures to build resilience against future floods through installation of electrical points at a raised height and flood defense barriers within their premises, securing databases by using online recovery systems, etc.

Vehicle service stations, such as Harsha Toyota collected and repaired cars that broke down due to water logging. Company ordered its dealerships to take extra space for flood affected cars while insurance companies were asked to clear their claims on time. They also provided discounted service packages, such as completely waiving labor charges, and offering ten percent discounts on spare parts, roadside assistance, loyalty points of up to Rs. 20,000, 50 percent discounts on car renewal and an exchange bonus up to Rs. 30,000 to flood-affected areas. The 2015 Chennai flash flood made all the car companies (e.g., Toyota, BMW, Renault, Maruti, Hyundai, Nissan, etc.) rethink and develop more sustainable business continuity plan for production, maintenance and parking. Several online and local sellers including a number of automobile portals, such as Copart, has a separate page exclusively for cars damaged in Chennai floods for holding auctions.

Hotel authority liaised with local authorities (i.e., police and fire service and incorporated emergency plans and services wherever possible. Guests were relocated and although flood kits (water proof clothing, blanket, candle/torches, etc.) was provided to all, there is a need to strengthen response and relief capacity of hotels.

Community-Based Organizations (CBOs), such as Tamil Nadu Thowheed Jamath (TNTJ) mobilized over 700 volunteers for carrying out rescue, relief, rehabilitation and reconstruction work, which included arranging food, shelter, cleaning up after flood water resided, waste management, spraying of insecticides and distribution of relief kit. They used half-cut plastic tank boats to rescue stranded people, conducted community based training programmes in health risks and fostered behavioral changes to support all social groups. TNTJ also became one of the coordinating facilitator through establishment of community, zone and district level mechanism with local partners, frontline workers and line departments.

Social media, such as Facebook, Twitter, and Google Maps, played an important role in bringing all the service providers and individuals to work together for reducing the impact and helping the flood affected population recover better. These platforms helped disseminate information, broadcast further warnings, inform people of the undertaken initiatives, call for volunteers in respective sectors, crowdsource and map the waterlogged or inundated areas. Professor Amit Sheth and his team at Wright State University in the United States carried out a new National Science Fund (NSF)-funded project, the Social and Physical Sensing Enabled Decision Support for Disaster Management and Response. This technology was mobilized  to monitor and analyze social media and crowdsourcing for better situational awareness of Chennai flood. Companies, such as BSNL, Paytm, Airtel and Zomato, also pitched in to help Chennai flood victims.

Towards Building Urban Disaster Risk Resilience

The 2015 Chennai flood caused by the torrential downpour brought city life to a standstill. It affected socio-economic condition of the district, maimed critical infrastructure, stranded animals and humans, disrupted services and flooded major parts of the city. The incorporation of flood preparedness measures will help reduce the extent of their impact on people, their life and property in future, along with giving them better coping abilities.

Best practices from Chennai flood case study should be used to strengthen existing risk handling capacities as well as learn lessons, to help replicate similar initiatives for preparedness of other Indian cities. This will also enable the government to coordinate and collaborate with similar service providers across the city for conducting efficient rescue and response operations in future. Best practices extrapolated from this case study could also prove useful to local and national officials from countries throughout Asia and the Middle East, all of whom continue to wrestle with the complex challenges associated with responding to responding to natural disasters in urban settings.    

Prioritized interventions and emergency responses which can be used to reduce urban risk, redevelop city plans and ensure effective disaster relief operations in future are listed below.

➢ As was reflected in the initiatives undertaken by several CBOS, particularly TNTJ, disaster response should address the humanitarian imperative; adhere to the principles of neutrality and impartiality; and ensure local participation and accountability, along with respecting local culture and custom. Thus, awareness generation and capacity building programs should promote inclusive flood disaster management approaches. Operational and sustainable livelihood models should be developed in the aftermath of such emergencies for weaker sections of the society. Disaster resistant shelters, public buildings and critical infrastructure, such as water and sewerage networks, need to be improved in order to avoid water logging and enhance community resilience.

➢ Cities need to develop broadcasting systems to inform the affected community about real time extreme events in different locales and provide updates on current road, flood, weather, food and energy supply scenario. Social media helps develop a two-way communication which helps acquire real time information from the community itself.

➢ Development of city disaster risk resilience strategy will better enable government and non-government organizations in phasing out adaptation and mitigation measures during normalcy.

➢ To ensure community level disaster preparedness, designed trainings should include actions or steps to be taken by citizen prior to, during and after disaster scenarios. Emergency respondents need to have basic first aid skills, such as airway management, bleeding control and simple triage.

➢ Emotional impact of the event on both workers as well as victims need to be addressed and documented for informing city disaster management plan.

➢ GIS-based evacuation plans, including current flood water flow, emergency routes, water depth, obstacles and possible search and rescue (SAR) interventions, need to be prepared. Existing capacity needs to be strengthened and assistance programmes should be provided to existing or new SAR teams at district and state level, for future preparedness. In addition, there is also a need to prepare Flood Risk Maps highlighting availability of grocery stores, restaurants, public utilities, food storage units, hospitals, residential homes for elderly people, high flood prone areas, etc.

➢ Communication systems, including early warning and public awareness mechanisms, need to be established in order to disseminate information during adverse conditions. (There is also an urgent need to prioritize child protection for the prevention of child trafficking during disasters.)

➢ Adaptation strategies need to ensure raised utility and reduced food cost through development and strengthening of local food suppliers. Food supply chain should be maintained by improved coordination and efficiency between producers, suppliers and retailers.

➢ Local flood plain maps, should inform construction practices (e.g., selection of appropriate materials for walls and floors).

➢ In flood-prone areas, water proofing should be mandated for emergency facilities like- power control room, water treatment plants, sewerage plants, etc. Emergency food and assets (generator sets, fuel) area should be at an elevated level to prevent inundation due to flooding.

Note: The detailed assessment of interventions undertaken during and post Chennai floods was funded by Rockefeller Foundation under the Asian Cities Climate Change Resilience Network program. The study was conducted by Taru Leading Edge and IFMR Chennai.

[1] “Chennai Metropolitan Urban Region Population 2011 Census,” accessed May 29, 2017, http://www.census2011.co.in/census/metropolitan/435-chennai.html .

[2] Deepa H. Ramakrishnan, “Memories of Rain Ravaged Madras,” The Hindu, December 9, 2015, accessed May 29, 2017, http://www.thehindu.com/news/cities/chennai/floods-in-madras-over-years… .

[3] “Letter from Chennai- Saving a home from floods,” The National, January 17, 2015, accessed May 29, 2017, http://www.thenational.ae/world/south-asia/20151213/letter-fromchennai-saving-a-home-from-the-floods ; “When Chennai was logged out and how,” Deccan Chronicle, accessed March 29, 2017; and http://www.deccanchronicle.com/151203/nation-currentaffairs/article/when-chennai- was-logged-out-and-how.B. Narasimhan, “Storm water drainage of Chennai: Lacuna, Assets, and Way Forward.” Presentation made at “Resilient Chennai: Summit on Urban Flooding,” hosted by 100 Resilient Cities in partnership with the Corporation of Chennai (2016). 

The Middle East Institute (MEI) is an independent, non-partisan, non-for-profit, educational organization. It does not engage in advocacy and its scholars’ opinions are their own. MEI welcomes financial donations, but retains sole editorial control over its work and its publications reflect only the authors’ views. For a listing of MEI donors, please click her e .

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From rains to floods: a case of chennai in 2015.

The city of Chennai, capital of the state of Tamil Nadu, is the fourth largest and one of the fastest growing metropolises of India. Located at 13°N, 80°E, the city is on the east coast of India and faces the Bay of Bengal making it naturally prone to tropical cyclones. The city is also water-scarce and has the lowest per capita availability of water among the four metro cities of India.

The unique feature of Chennai’s rainfall is that the major share is received during the northeast monsoon in the months of October to December. In November and December of 2015, Chennai received unprecedented levels of rainfall leading to the overflow of the arterial Adyar river, which in turn led to floods in the city. Multiple low-lying areas in the city were inundated for days together; massive rescue and evacuation efforts had to be undertaken in areas where houses were getting submerged.

Rescue efforts being undertaken via boats.

Photograph by rsriramtce. Accessed via Wikimedia Commons on 22 June 2021. Click here to view source .

Airborne evacuation and relief provision were rendered impossible due to the flooding of the city’s sole airport whose secondary runway had incidentally been constructed over what was once a part of the Adyar river. The flood carried with it an economic cost and the global insurance company Munich Re estimated the loss in and around Chennai to be at the tune of USD 3.5 billion, making it among the most costly global events of the year, second only to the Nepal earthquake.

The city is no stranger to flooding. In 2007, a Drescher et al. study on risk perception consisting of analysis of flood risk exposure and the development of flood risk maps showed that flooding is a regular occurrence. The study documented a total of 26 floods from 1943 to 2006 and noted a sharp increase in the number of flooding events from the 1970s. Before this could be categorized as a direct correlation of climate change, the study also highlighted, based on the meteorological data from 1813, that there has been no increase in the rate of rainfall received annually over the years. Floods of 1996 and 2005 had been caused by strong single rainfall events exacerbated by manmade pressures.

What is interesting to note is that in the month of November in 2015, the event in large part was referred to as “Chennai Rains,” including on social media. An article on 18 November in the newspaper Mint for instance opened by reporting that Chennai “woke up to a clear sky on 17 November after a week of incessant downpour that threw life out of gear” and called the city “water-logged.” A cursory scan of media coverage of 2015 now shows that it is widely cited as the “Chennai floods.” How, when, and why did “rains” become “floods”?

First, despite the state’s impressive rescue efforts, the events of 2015 reiterated the lack of understanding of the city’s natural drainage systems. The state’s decision to drain the excess water from one of the city’s three main reservoirs added to the already-heightened volume of the Adyar river which is part of its natural flow pattern, leading to sudden flooding.

Historical increase of the built-up area.

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Second, the state’s decision led to flooding in parts of the city that had earlier been immune to water-logging. These new areas which flooded were the affluent neighborhoods of Chennai, bringing the dangers of haphazard urban planning to everyone’s doorsteps as a reality to immediately confront.

Third, and perhaps most important, postmortem studies on the floods illustrated how rapid and unchecked urbanization had taken its toll on the city’s wetlands and made the city vulnerable. A study by Care Earth Trust showed the increase in built-up area over the decades corresponding to the decrease in the area of wetlands and waterbodies. In recent times, there is a tendency to externalize the cause of a natural disaster to climate change, making it difficult to visualize and identify immediate causes and solutions. In this case, the emphasis on how a disaster that deeply affected the psyche of the city could have been avoided through better urban planning and management has enabled residents of the city to understand this as something within control.

After the 2015 floods, the city has witnessed a mobilization of government, civil society, and academia towards concepts such as flood risks and urban resilience. Discussions on hydrology as a key metric for urban planning and on the need for livelihood safety nets for the urban poor are entering the mainstream planning agenda. In contrast to earlier waterlogging events, post-2015 there is an increased emphasis on the restoration of the city’s wetlands and natural hydrological courses. While this has taken root in theory in urban planning, it needs to translate into practice on a larger scale.

How to cite

Vencatesan, Anjana. “From Rains to Floods: A Case of Chennai in 2015.” Environment & Society Portal, Arcadia (Summer 2021), no. 23. Rachel Carson Center for Environment and Society. doi:10.5282/rcc/9323 .

ISSN 2199-3408 Environment & Society Portal, Arcadia

2021 Anjana Vencatesan This refers only to the text and does not include any image rights. Please click on the images to view their individual rights status.

• Anand, Jay, and Uma Ramachandran. Role of Various Sectors in Demonstrating Resilience During Chennai Flood 2015 . New Delhi: TARU Leading Edge, 2016. ( Link )
• Bhaskar, Avantika, G. Babu Rao, and Jayshree Vencatesan. “Characterization and Management Concerns of Water Resources around Pallikaranai Marsh, South Chennai.” In Reconsidering the Impact of Climate Change on Global Water Supply, Use, and Management , edited by Prakash Rao and Yogesh Patil, 102–121. Hershey, PA: IGI Global, 2017. doi:10.4018/978-1-5225-1046-8.ch007
• Disaster in Chennai Caused by Torrential Rainfall and Consequent Flooding . (2016), Report no. 198, Department related Parliamentary Standing Committee on Home Affairs, Rajya Sabha, Parliament of India.
• Drescher, Axel, Rüdiger Glaser, Constanze Pfeiffer, Jayshree Vencatesan, Elke Schliermann-Kraus, Stephanie Glaser, Marco Lechner, and Paul Dostal. (2012). “Risk Assessment of Extreme Precipitation in the Coastal Areas of Chennai as an Element of Catastrophe Prevention.” 8. Forum DKKV/CEDIM: Disaster Reduction in Climate Change, Karlsruhe University, October 2007.
• Pfeiffer, Constanze, Stephanie Glaser, Jayshree Vencatesan, Elke Schliermann-Kraus, Axel Drescher, and Rüdiger Glaser. “Facilitating Participatory Multilevel Decision-Making by Using Interactive Mental Maps.” Geospatial Health 3, no. 1 (2008): 103–112. doi:10.4081/gh.2008.236
• Warrier, S. Gopikrishna. “Encroached wetlands, cut trees increase climate risks in Chennai.” India Climate Dialogue , 23 October 2017. ( Link )
• Anjana Vencatesan, “[Commentary] Looking Beyond the Chennai City, at the Chennai Watershed,” Mongabay , 16 April 2019.
• Care Earth Trust: “Landuse Change and Flooding in Chennai”
• “80% of Chennai was wetland in 1980s, now 15%.” The Times of India , 5 September 2016.
• Drought, Mud, Filth, and Flood: Water Crises in Australian Cities, 1880s–2010s (Virtual Exhibition)
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Near real time flood inundation mapping using social media data as an information source: a case study of 2015 Chennai flood

• Dhivya Karmegam   ORCID: orcid.org/0000-0003-3307-8704 1 ,
• Sivakumar Ramamoorthy 2 &
• Bagavandas Mappillairaju 3  

Geoenvironmental Disasters volume  8 , Article number:  25 ( 2021 ) Cite this article

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During and just after flash flood, data regarding water extent and inundation will not be available as the traditional data collection methods fail during disasters. Rapid water extent map is vital for disaster responders to identify the areas of immediate need. Real time data available in social networking sites like Twitter and Facebook is a valuable source of information for response and recovery, if handled in an efficient way. This study proposes a method for mining social media content for generating water inundation mapping at the time of flood. The case of 2015 Chennai flood was considered as the disaster event and 95 water height points with geographical coordinates were derived from social media content posted during the flood. 72 points were within Chennai and based on these points water extent map was generated for the Chennai city by interpolation. The water depth map generated from social media information was validated using the field data. The root mean square error between the actual water height data and extracted social media data was ± 0.3 m. The challenge in using social media data is to filter the messages that have water depth related information from the ample amount of messages posted in social media during disasters. Keyword based query was developed and framed in MySQL to filter messages that have location and water height mentions. The query was validated with tweets collected during the floods that hit Mumbai city in July 2019. The validation results confirm that the query reduces the volume of tweets for manual evaluation and in future will aid in mapping the water extent in near real time at the time of floods.

Introduction

Change in climate, urbanization and other human activities across the globe disturbs the hydrological cycle and cause various water related issues like water pollution, floods, droughts, etc., (Lyu et al. 2019a ; Luo et al. 2019 , 2020 ). Especially cities face the problem of uneven distribution of rainfall very often which leads to subsequent urban floods (Lyu et al. 2019b ; Zou et al. 2020 ). Flash flood disasters leave a massive social, environmental and psychological impact on the affected community (Duan et al. 2016 ). Unanticipated heavy precipitation within a short time span followed by flash floods in urban areas causes a greater loss in terms of lives, infrastructure and properties (Duan et al. 2014 ). In the past decade, occurrence of urban floods increased drastically across India (Rafiq et al. 2016 ). Flood extent or water depth details are required immediately after the disaster to identify inundated areas that need quick attention(Blyth 1997 ). Emergency managers need appropriate and rapid information about severity of flooding for planning rescue and response operations. Information on variations in flood water depth with respect to time and space were required for effective flood risk management (Luo et al. 2018 ; Mu et al. 2020 ). The unexpected, quick nature of flood in urban localities due to very intense rainfall restricts getting water depth information during floods. In general inundation map is prepared based on the field data, remote sensing data and hydraulic models(Grimaldi et al. 2016 ). Field data will be collected by sending field workers to the flooded areas, inspect the highest water mark after floods and based on this inundation maps will be generated. Collecting field data have practical difficulties and fail to provide timely data regarding flood extent. For instance, during Chennai flood 2015, authorized official report on inundation map was released by Disaster Management Support (DMS) Division, National Remote Sensing Centre (NRSC/ISRO), India on March 2016 after a field survey that was carried out on December 24 to 26, whereas flood disaster occurred on December 2 2015 (National Remote Sensing Centre 2015 ). Utilizing remote sensing data for rapid water extent mapping have some limitations that includes restricted availability(Mason et al. 2012 ), limited spatial and temporal resolutions(McDougall and Temple-Watts 2012 ). Apart from these traditional data content, user generated crowd sourced content called volunteered geographical information(VGI) were also widely used for water extent mapping and validation(McDougall 2011 ; Hirata et al. 2018 ; Rollason et al. 2018 ). Geo referenced data from social media like Facebook, Twitter, etc., are also considered as VGI. The role of social media in management of disaster situations was widely researched in past decade (Lindsay 2011 ; Verma et al. 2011 ; Cameron et al. 2012 ; Middleton et al. 2014 ; Takahashi et al. 2015 ; Anson et al. 2017 ). Social media data ascending from the affected population has the potential to aid in creating situation awareness and planning response and rescue operations (Huang and Xiao 2015 ; Lin et al. 2016 ; Mart et al. 2017 ). As the data from social media are posted real time with no time delay, the same can be mined for rapid water inundation mapping.

Although social media was widely used as a tool for information dissemination, early warnings and situational awareness during floods (David et al. 2016 ; Kaewkitipong et al. 2016 ; Lin et al. 2016 ; Yadav and Rahman 2016 ; Alias et al. 2020 ), exploring its utilization in water depth mapping was at infancy. Few recent studies investigated the potential of using social media information in inundation mapping (Eilander et al. 2016 ; Brouwer et al. 2017 ; Li et al. 2018 ). Information got from social media about water depths were used in studies to validate the flood extent from other bases and frameworks (Cervone et al. 2016 ; Smith et al. 2017 ). Previous researches also examined the possibility of using water logging information in social media along with other sources of information for inundation mapping and risk assessment (Zhang et al. 2016 ; Rosser et al. 2017 ; Wu et al. 2018 ). To the best of our knowledge, the usage of social media content for real time inundation mapping during floods is explored least in Indian context. One of the biggest challenges of utilizing social media data during disasters is huge volume of posts shared by people on different aspects. Extracting useful and required information from the noisy, volumous text becomes a barrier for emergency managers (Hiltz and Kushma 2014 ). Earlier studies filtered the flood related content based on hash-tags or geographic locations (Lu et al. 2015 ; Woo et al. 2015 ; Murzintcev and Cheng 2017 ), but again segregating inundation information containing messages from the flood related post becomes a laborious task.

In this article, results of a feasibility study to filter and utilize social media content for flood mapping in Indian context was provided. Flooding in the Chennai city (Tamil Nadu), India in December 2015 was one of the worst devastating, unexpected flooding events in India. At the time of Chennai floods, affected people used social networking sites as a communication platform and that helped in identification of people in need. Social media platforms played a major role after floods in rescue and relief operations (Prakash and Anand 2016 ). Disaster management stakeholders and volunteers utilized social networking sites to connect people in need and people who came forward to offer help (Yadav and Rahman 2016 ). Hence Flooding event in Chennai 2015 was considered as the case scenario in this study. Flood extent map was generated using social media information on water depths and location posted during Chennai floods 2015 and validated against field data collected after floods. A simple keyword based query was developed to filter social media data that contains water depth information in case of urban floods in India. The developed query was also validated with another disaster scenario.

Study setting

Greater Chennai Corporation (GCC), which is located at the state of Tamil Nadu in India, was considered as our study area. GCC is divided in to fifteen zones, which is further subdivided into 200 wards. Chennai city receives almost 60% of the annual rainfall during north east monsoon period (from October to December). Due to flat topography, some localities in Chennai deal with the problem of poor drainage during monsoons. Chennai experienced severe flooding due to heavy rainfall and the normal life of the population across the city was troubled in 1976, 1985, 1996, 2005 and 2015. That is approximately once in every decade (National Remote Sensing Centre 2015 ). During 2015, as per meteorological reports, Chennai received very heavy rainfall of 1471.6 mm, far excessive than that it receives usually (915.6 mm—Normal rainfall) during the monsoon between October and December (Indian Meteorological Department (IMD) 2016 ). City experienced one episode of substantial rainfall in the end of November 2015 about 1049 mm, which filled up all the water bodies and water logging in some low lying areas. Again extremely high intensity of rainfall was recorded on December 1 and 2, 2015 at Nungambakkam and Chembarambakkam rain gauge stations, that flooded the entire city. There was sudden increase in water levels about 6–8 m in many areas across the city on December 1st 2015. In few residential areas water entered in to the houses and reached till first floor and in some localities even up to second floor. The population unaware of this sudden rise in water level were stranded at the terrace without any basic needs like food, water, etc. (National Disaster Management Authority (NDMA) Government of India 2017 ). As per government reports, around 1.8 million people from various localities were sent to relief camps at the time of flood. As estimated by media, approximately 500 people lost their lives and there was around 200 million Rupees economic losses due to flood (Mujumdar et al. 2016 ). Figure  1 shows the ward map of GCC (Chennai Corporation 2011 ) with its zone name shown.

Ward map of Greater Chennai Corporation

Methodology

Flood depth mapping.

Data from Twitter and Facebook public pages were utilized in this study for getting water depth information. The process followed for generating water extent maps from social media content is provided in Fig.  2 .

Framework of water extent mapping from social media data

As the objective is to generate water extent map rapidly in real time, messages posted on Twitter and Facebook public pages between 1 December 2015 and 3 December 2015 were considered. In Facebook, messages shared in public pages only were considered because messages posted by individuals are restricted to public access based on their privacy settings. But the messages shared in the public pages can be used without restriction. The public pages in Facebook created before December 3rd 2015 to share the details about flood situation and rescue activities in Chennai were identified. In Twitter, the hash-tags related to floods 2015 were identified by general look up of the tweets. Twitter messages in English and Tamil with the identified hash-tags and tweets that originated from Chennai (25 miles around Chennai geographical coordinates—search option in Twitter) in the above mentioned time frame were collected. The messages in Twitter and Facebook pages were screened manually to identify the messages that have both location and water depth information regarding the flood situation. The location information from the geo-coded messages was obtained directly from the coordinates specified. In other messages, the location was derived either from the address provided in the text or from the image shared. Then the geographical coordinates of the specified location was derived utilizing using Google Maps. Following location the extraction of location, water depths in these locations needs to be derived. In some messages, the data on water depth was specified directly in feet and meter. An example message where the height of water was specified straight in a particular location is provided below:

“Kannan Avenue (2nd Floor), Near annai arul hospital, Mudichur Road, Old Perungulathur. Stuck up in second floor with a kid. No power and food. Area with surrounded with 11ft water”

There were also messages where the water height in particular area was mentioned with reference to some other aspects like up to first-floor, or hip-level, etc. One such example message is given below:

“Managed to get out of west mambalam. Water levels we at knee/calf level at arya gowda road till panigraha hall.”

Figure  3 shows an example message posted in Facebook, from which location and water height were derived from the text. In the message shown in Fig.  3 , the geo-coordinates of the location were extracted based on the address and land mark provided using Google Maps. The water height at that location was mentioned as “up to 1st floor”, that which means the water height will be approximately 3 m.

Example message with location and water height mentions

Figure  4 shows two images (a and b) posted on social media, from which water height and location were extracted. In the first image (Fig.  4 a), location was derived from the text and water height from the image. In the second image (Fig.  4 b), both location and water depth were derived from the photo shared. Messages that reveal, a particular locality that had no water logging was also considered as water depth point. Example messages that reveal no inundation are given:

“Our flat in #ValmikiNagar, # Thiruvanmiyur is dry with Internet and electricity. Please get in touch if you need help #ChennaiFloods” “Loyola college, Nungambakkam has accommodation for rain victims. They have electricity”

Sample images in social media with reference to location and water height

Once the water height and locations were derived, they were mapped over the base map of Greater Chennai Corporation using Quantum geographical information system (QGIS). The water height points that were outside the geographical extent of the city were excluded. The water inundation map to the extent of Chennai city was generated by interpolating the water height points using Inverse Distance Weighting (IDW) interpolation in QGIS. IDW is one of the commonly used deterministic, spatial interpolation methods in hydrological modelling. IDW interpolation assumes that nearer values are more connected than farther values and this method works best with dense point values in flat zones (Ly et al. 2013 ).

The generated water extent map after interpolation was validated with water height points reported after the field assessment by the Disaster Management Support (DMS) Division, National Remote Sensing Centre (NRSC), India (National Remote Sensing Centre 2015 ). A field survey was done by DMS, NRSC, along with the Indian Institute of Technology (IIT) Madras on 24th and 25th December 2015 to collect data on water depth marks in the flood-affected areas in and around Chennai. From this report, field information on water depths in twelve locations were used to validate the water height derived from social media data. The water height in those these twelve locations (where actual information on water depth is available) was extracted from the interpolated map generated using social media content. In order to examine the significance in the difference between the averages of two water heights (actual water depth and depth resulting from social media data), t-test was performed. Root mean square error (RMSE) was calculated to understand the error between the actual heights and water heights generated from social media.

Query development

A simple keyword-based query particularly attuned to Indian urban setting was proposed to filter the messages that have both location and inundation information. Based on the experience on manual screening of messages posted during Chennai flood scenario, the keywords which the affected population used to mention the water depths in their messages were identified. Water depth keywords are usually a combination, such as a number followed by metre or feet (5 feet, 10 cm), number followed by floor (for example—2nd floor), or indicative levels like ankle-high and neck-deep. Location information keywords include area and road names in the city. The query was framed in such a way that the messages will be filtered if it contains both the location and inundation keywords. The query was framed in MySQL, an open-source database management system. As the water depth keywords were identified based on the experience with manual screening of Chennai flood data, we validated the filtering query with tweets collected during the floods that hit Mumbai city in July 2019. The tweets related to Mumbai floods in 2019 were collected using search API based on the hash-tags related to Mumbai floods. Areas and road names of Mumbai city was used as the location keywords in that query.

The Facebook pages related to Chennai flood, 2015 and the Twitter search query was given in Additional file 1 . On manual screening, we derived 95 points with geographical coordinates and water height from ground level. Figure  5 shows the distribution of water height points over the base map.

Distribution of water height points

The derived water height and location (geographical coordinate) were given in Additional file 2 . Among these, 72 points were within the geographical extent of Chennai. The generated water extent map for the entire city by IDW interpolation was given in Fig.  6 .

Water inundation map after interpolation

The actual water height from field survey report and water height from interpolated map got from social media at the 12 locations were tabulated in Table 1 . As per the results of the t-test, there was no significant difference between mean of the actual data and the extracted data of the water height from social media. The root mean square error between the actual data and the extracted social media data (water height) was 0.3.

The query in MySQL filters the messages, if it contains both water depth and location keywords. The combination of inundation keywords was handled using regular expressions in MySQL. The query was validated using the tweets collected during Mumbai flood and that was 17,846 messages excluding duplicates and re-tweets. When these messages were filtered using the query, it returned 156 tweets. On checking the tweets manually we found that, 102 messages had water depth and location information that will be used for rapid water extent mapping. The query written to filter messages regarding Mumbai flood data was given in Additional file 3 . The screen shot of the executed query in MySQL workbench with results was given in Fig.  7 . Sample tweets that had location and water height mentions, filtered by the query were given below.

“my college basement was floodedwalked in neck deep water with my colleagues up to lbs marg and then on in waist deep water walked home for nearly an hour and half this is from bhandup to mulund mumbairains” “water raises above 3 feets at cm high school badlapur water has started entering kitchen godown and classrooms destroying uniforms and food. mumbairains badlapur mahalaxmiexpress ndrf mumbairainsliveupdates”

MySQL Workbench—Keyword based query and results (screen shot)

This study examined the feasibility of using social media data, for water depth mapping in Indian disaster scenarios. This article is the proof of concept that confirms the potential of utilizing social media information for rapid flood mapping in Indian context for immediate response and recovery.

The water depth map was generated from information in Twitter and Facebook messages, for the case of Chennai flood, 2015. Based on derived water height points, we found that localities in Saidapet, Jafferkhanpet and Ashok nagar had the highest water depth more than 4 m. During flood, Chembarambakam , one of the tanks that supplied water to the city, breached due to unexpected heavy downpour, releasing thousands of cusecs of water in to Adyar River(Mujumdar et al. 2016 ). As Adyar River flows through the city, the areas lying in close proximity to the river were highly inundated. That might be the reason for very high water depth in above mentioned areas, as they are closely located to the Adyar River. The interpolated water extent map also confirms that the areas close to Adyar River had higher water levels. As per the results, the wards in Kodambakkam (ward 142) and Adyar (ward 171) zones had water height greater than 6 m. Both these ward are located in the bank of the river. These areas were also reported among the worst affected areas during floods (National Remote Sensing Centre 2015 ). We found that the error between the field data and social media data was about ± 30 cm. This can be acceptable as this map was generated rapidly in real time at the time of disaster, when no other source of data was available. The main advantage of using social media data in emergency situations is that they are available at near real time and also from the affected population, who are the eye witnesses of the disaster situation (Fohringer et al. 2015 ). The query that filters messages based on keywords reduces the volume of messages considerably for manual screening. This handles the problem of information overload and aids in creating the flood map in time. We believe that if this query is applied to the streaming online data in future during floods in India, this will provide flood extent or inundation information without delay for emergency management. This will aid in planning the rescue operations in accordance with the need of affected population.

As the water depth and locations are extracted manually with approximations, there is a possibility of inaccuracies in data. But at emergencies, when the information on flood is very scarce, this information will definitely give some understandings towards the flood situation. In case of Chennai floods, some of the localities had power cuts and network issues. This prevented the affected population from updating the flood status in social media. So there is also a possibility that updates from highly inundated and affected areas may be limited in social media. Instead using social media information as stand-alone information source, it can be used along with other sources like remote sensing data and already available Digital Elevation model to fill the information gap during crisis.

Previous researches also mention that there is a possibility of uncertainties regarding location information in social media posts (Brouwer et al. 2017 ; Ogie and Forehead 2018 ). Development of national scale integrated framework to fuse multiple data sources (social media, remote sensing, topographic and environmental data) in real time by duly taking into account uncertainties in data sources for the purpose of generating precise real-time water depth maps at the time of flood could be a focus area for future research.

This study presented a method and keyword based query to filter messages from social media that support extraction of water height information for near real time flood inundation mapping during urban floods in India. The results of the application circumstance Chennai flood, 2015 was positive. The advantage of proposed methodology to use social media information for mapping is the rapid availability of data when compared to other traditional sources of information like remote sensing, satellite data, etc., particularly in urban setting. In future, during floods this rapid flood map in real time will improve situational awareness and aid in efficient flood management. Social media information on water heights will close the information openings in traditional information sources. In future mapping framework and tool can be developed that automatically derive information from social media by text and image analysis and integrating with other sources of information available to acquire a more accurate inundation maps in real time.

Availability of data and materials

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Disaster Management Support

National Remote Sensing Centre

Indian Space Research Organization

Volunteered geographical information

Greater Chennai Corporation

Quantum geographical information system

Inverse Distance Weighting

Root mean square error

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School of Public Health, SRM Institute of Science and Technology, Tamil Nadu, Chennai, 603203, India

Dhivya Karmegam

Department of Civil Engineering, SRM Institute of Science and Technology, Chennai, Tamil Nadu, 603203, India

Sivakumar Ramamoorthy

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Conceptualization and methods: BM, SR and DK. Data collection and analysis: DK. Supervision: BM and SR. Writing Draft: DK. Review and editing draft manuscript: BM and SR. All authors read and approved the final manuscript.

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Supplementary Information

Additional file 1..

List of Facebook community pages and Twitter search query for data collection.

Additional file 2.

Location and water height derived from social media data.

Additional file 3.

MySQL Query.

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Karmegam, D., Ramamoorthy, S. & Mappillairaju, B. Near real time flood inundation mapping using social media data as an information source: a case study of 2015 Chennai flood. Geoenviron Disasters 8 , 25 (2021). https://doi.org/10.1186/s40677-021-00195-x

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Urban Flood Management – A Case Study Of Chennai City

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Flood is one of the significant and frequent disasters in the world. Of these more than 50% of the events occur in Asia. Every year there is loss of human life, animals, houses, goods and property due to the outrage of floods. Urban areas are witnessing drastic population growth resulting in decreasing rainwater infiltration and increase in runoff and flood peak. Severe and frequent flooding events are possibly due to climate change, socioeconomic damage, migration, development practices and political instability, which constantly reshape flood vulnerability. As a part of an integrated urban flood studies at KSNDMC, we are developing a plan for " Urban storm water flood management " –for Bangalore city, which is often subjected to monsoon fury. This paper describes the causes, circumstances and impact of flooding events in Bangalore city. In an urban scenario, like Bangalore, floods occur due to natural phenomenon such as heavy and / or high intensity rainfall, human factors such as blocking of storm water drains, population growth leading to improper land use & unplanned settlements etc. The immediate impact of floods will be mainly on the public transportation because of water submerging the roads, urban settlements in low laying areas due to inundation, chocking of storm water drains inundating the surrounding houses. In the Developing countries, like India, the activities of Flood management are handled by government and are still adopting a reactive approach during floods. This should be changed to proactive action which enhance effectiveness of management and reduce losses. For planning and implementing an effective short and long term flood management plan participation and cooperation between Government, non-governmental, private agencies and public is a prerequisite.

Dr. Sunny Agarwal

IJRASET Publication

Floods are water-induced disasters that lead to temporary inundation of dry land cause severe damage to the target location, such as human loss and properties and infrastructures. Knowing that floods are part of human life and that this natural phenomenon can't be fully controlled, it's essential to focus on necessary steps to improve knowledge about preventing damages. This project discusses the floods in major cities in India-Chennai, Mumbai, Kolkata, and Delhi, the main reasons behind it, and how to prevent the floods from happening on the whole. I.

Irrigation and Drainage

Bart Schultz

IAEME Publication

Urban flood is mostly seen in urban areas. They may be due to heavy rainfall, adverse topographical conditions and anthropogenic factors, lead to destruction of drainage, damage to buildings, and even loss of life and property. Now in order to control such problems, systematic urban flood studies are necessary. This study is focused on the mapping and spatial analysis of urban flood vulnerability in Vrishabhavathi valley watershed, Bengaluru using Analytical Hierarchy Process (AHP), GIS and remote sensing techniques. Few causative factors for flooding considered are rainfall, slope, drainage density, land use, building density, road density, non-existing natural drainage and non-existing Lake. The thematic map of these factors was converted into raster maps. Numerical weight and ranking scores will be assigned to each element factor according to fundamental scale of AHP technique. Urban Flood Vulnerability Zone (UFVZ) map is computed using weighted overlay analysis of GIS technique and classified into five categories, viz., very low, low, moderate, high and very high flood zone classes. UFVZ map was compared with the flood prone locations exist in Bengaluru city to assess the accuracy of result. The plot of flood prone locations on flood vulnerability zone map evident that, 50% of flood prone locations found under moderate flood vulnerability zone. This result depicts the fact that, urban flood vulnerability is highly influenced by anthropogenic factors than natural factors in urban environmental study area. The predicted flood vulnerability zones are found to be in good agreement with known flood prone locations.

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Architecture Research

p-ISSN: 2168-507X    e-ISSN: 2168-5088

2012;  2(6): 115-121

doi: 10.5923/j.arch.20120206.01

Urban Flood Management – A Case Study of Chennai City

Ar. K. Lavanya

Crescent School of Architecture, B.S.Abdur Rahman University, Chennai, 600073, India

Copyright © 2012 Scientific & Academic Publishing. All Rights Reserved.

In the recent decades, Indian cities are witnessing devastating floods more often due to heavy rainfall, cyclones, etc., Though Tamil Nadu is not under flood risk prone zone as mapped by meteorological department (New Delhi), within the local body there are few low-lying areas which are susceptible to inundation which also depends mainly on the developments near major drainage systems, encroachment of water bodies, inability of major canals to carry heavy rains, overflowing reservoirs. Chennai, one of the fast growing metros is likely affected by the lack of drainage mainly due to uncontrolled developments of concrete spaces, encroachment of major drainage channels, shrinking of marshlands, etc,. Though Urbanization, the vital factor of response for the flood risks is coupled with the climatic variability and ecological imbalances. The paper discusses causative factors responsible for flood risks in Chennai, the immediate need for proper flood risk reduction and management strategies.

Keywords: Urban Flood, Flood Management, Flood Risk, Chennai Flood

Cite this paper: Ar. K. Lavanya, "Urban Flood Management – A Case Study of Chennai City", Architecture Research , Vol. 2 No. 6, 2012, pp. 115-121. doi: 10.5923/j.arch.20120206.01.

Article Outline

1. prologue of chennai, 1.1. growth of chennai city, 2. history of chennai floods, 2.1. causes of chennai floods ( table 1 ), 2.2. direct factors, 2.2.1. increase in rainfall, 2.2.2. urbanization, 2.2.3. topography, 2.3. indirect factors, 2.3.1. inadequate and poor drainage systems, 2.3.2. solid waste disposal & vehicle parking on roads, 3. master plan & flood mitigation in chennai – a quick review, 4. findings & recommendations, 5. sequence of actions to hurl out from the flood hazard (both structurally & non-structurally).

Enhancing Blue-Green Infrastructures for Flood and Water Stress Management: A Case Study of Chennai

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• Nadeem Ahmad 13 &
• Quamrul Hassan 13  

Part of the book series: Lecture Notes in Civil Engineering ((LNCE,volume 353))

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• International Conference on Trends and Recent Advances in Civil Engineering

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The urban water system has been severely affected across the globe in the recent decades due to rampant urbanisation, industrialisation and climate change. Many cities in India have witnessed a rise in the frequency of urban flooding as well as water scarcity. Chennai, the fourth largest metropolitan city lying on the southeast coast of India and the capital of the state of Tamil Nadu, is severely facing both flooding and water scarcity. In 2015, the city suffered the most disastrous flood in a century. More than 400 human casualties were reported; about USD 80,000 million loss were estimated and about 2 million people were very badly affected. While four years later in June 2019, the city was surprisingly hit by ‘Day Zero’ and all of its major reservoirs ran dry. With the rapid urbanisation, the blue and green spaces of the city have been drastically decreased. This paper focuses on the roots of flooding and water scarcity issues of the city. The paper further explores ‘Blue-Green Infrastructure’ (BGI) approach to integrate flood management along with water crisis management as an innovative, sustainable and nature-based solution. The paper also explores the emerging concept of BGI and analyses the existing plans and research projects in some major global cities and further, the possibility of their implementation in India. It is observed that adaptation of BGI measures (wetlands, lakes, ponds, rivers, swales, rain gardens, parks, green roofs etc.) minimises the flood risks as well as water stress including other urban ecosystem services (UES) to derive multiple benefits regarding ecological, socio-economic and overall urban well-being.

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Ahmad, N., Hassan, Q. (2024). Enhancing Blue-Green Infrastructures for Flood and Water Stress Management: A Case Study of Chennai. In: Nagabhatla, N., Mehta, Y., Yadav, B.K., Behl, A., Kumari, M. (eds) Recent Developments in Water Resources and Transportation Engineering. TRACE 2022. Lecture Notes in Civil Engineering, vol 353. Springer, Singapore. https://doi.org/10.1007/978-981-99-2905-4_8

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Fulton County officials say by law they don't control Fani Willis' spending in Trump case

Leaders of Georgia’s Fulton County say they had no legal power to control District Attorney Fani Willis’ spending or her hiring of former special prosecutor Nathan Wade

ATLANTA -- Leaders of Georgia's Fulton County testified Friday before a special state Senate committee that they had no legal power to control District Attorney Fani Willis' spending or her hiring of former special prosecutor Nathan Wade.

The Republican-led committee is probing Willis' hiring of Wade to lead a team to investigate and ultimately prosecute Donald Trump and 18 others accused illegally trying to overturn the 2020 presidential election in Georgia. Willis and Wade have acknowledged a romantic relationship with each other.

In one example of the kind of threats Willis has been receiving, federal officials announced that a California man was indicted on April 24 on charges of transmitting interstate threats against Willis. Ryan Buchanan, the U.S. attorney in Atlanta, said Marc Shultz, 66, of Chula Vista made threatening comments against Willis in the comment streams of two YouTube videos in October, pledging violence and murder including a statement that she “will be killed like a dog.”

Shultz's indictment wasn't available in online court records on Friday. Those records show Shultz appeared before a judge in San Diego on Thursday and was released on bail. A federal public defender representing Shultz didn't immediately return an email seeking comment Friday. Buchanan said Shultz would be formally arraigned in Atlanta in June.

Trump and some other defendants in the case have tried to get Willis and her office removed from the case, saying the relationship with Wade created a conflict of interest. Wade stepped down from the prosecution after Fulton County Superior Court Judge Scott McAfee in March found that no conflict of interest existed that should force Willis off the case. But he ruled that Willis could continue prosecuting Trump only if Wade left. Trump and others are appealing that ruling to a higher state court.

The allegations that Willis had improperly benefited from her romance with Wade resulted in a tumultuous months in the case as intimate details of Willis and Wade’s personal lives were aired in court in mid-February. The serious charges in one of four criminal cases against the Republican former president were largely overshadowed by the love lives of the prosecutors.

Willis told reporters Friday that she had done nothing wrong.

“They can look all they want," Willis said. "The DA’s office has done everything according to the books. We are following the law. I’m sorry that folks get mad when everybody in society can be prosecuted.”

Willis is running for reelection this year and faces a Democratic opponent, Christian Wise Smith in a May 21 primary. Early voting for that election is ongoing.

But the lawyer who initiated the effort to remove Willis, Ashleigh Merchant, has also claimed that Wade's firing violated a state law that required approval of the hiring of a special prosecutor by the county commission.

Fulton County Commission Chairman Rob Pitts, a Democrat, and Fulton County Attorney Soo Jo both told the committee that while the law appears to require county commission approval, judges decades ago interpreted the law in such a way to give Willis the freedom to hire who she wants without approval. Jo, who represents the commission, cited three separate Georgia Court of Appeals cases backing up that point

“What I have found is that the court has rejected the proposition that this particular statute requires a district attorney to obtain explicit permission from a county prior to appointing a special assistant district attorney,” Jo said.

State Sen. Bill Cowsert, the Athens Republican who chairs the committee, disputed that interpretation when questioned by reporters after the hearing.

“I think the clear language of the statute says that that requires county approval, and especially where it’s funded by the county,” Cowsert said.

He went on to suggest the committee, which doesn't directly have the power to sanction Willis, might change the law to give counties more control over spending by state officers funded by counties, including district attorneys and sheriffs. Fulton County officials said they don't believe they currently can control how Willis spends money once it's appropriated to her.

Cowsert said increased county oversight would be “extraordinarily complex" for district attorneys managing funds contributed by more than one county. While Willis and 15 other district attorneys in Georgia only prosecute cases from one county, others prosecute cases from as many as eight counties.

Senate Democratic Whip Harold Jones II of Augusta said the hours of questioning over details of how Fulton County budgets money shows the panel is “on its last legs," noting three of six Republicans didn't appear for a committee meeting called on short notice.

“They’re not even interested in this anymore,” Jones said. “There’s nothing else to talk about, quite frankly. And we found that out today.”

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Kenya’s devastating floods expose decades of poor urban planning and bad land management

Chartered Consultant in Hydrology and Water Resources, Visiting Research Fellow, King's College London

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Sean Avery is affiliated with: Hydrological Society of Kenya, Water Resource Associates, Kings College London, University of Gent

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Floods in Kenya killed at least 169 people between March and April 2024. The most catastrophic of these deaths occurred after a flash flood swept through a rural village killing 42 people . Death and destruction have also occurred in the capital, Nairobi, a stark reminder of the persistent failure to keep abreast of the city’s rapid urbanisation needs. Sean Avery , who has undertaken numerous flood and drainage studies throughout Africa, unpacks the problems and potential solutions.

Are floods in Kenya causing more damage? If so, why?

Floods are the natural consequence of storm rainfall and have an important ecological role . They inundate flood plains where silts settle, riverbed aquifers are recharged and nutrients are gathered. Annual rainfall in Kenya varies from 2,000mm in the western region to less than 250mm in the drylands covering over 80% of Kenya. But storm rainfalls are widespread. This means that floods can occur in any part of the country.

The impact of floods has become more severe due to a number of factors.

The first is how much water runs off. In rural areas, changes to the landscape have meant that there’s been an increase in the amount of storm runoff generated from rainfall. This is because the natural state of the land has been altered through settlement, roads, deforestation, livestock grazing and cultivation. As a result, a greater proportion of rainfall runs off. This runoff is more rapid and erosive, and less water infiltrates to replenish groundwater stores.

The East African Flood Model , a standard drainage design tool, demonstrates that by reducing a forested catchment into a field for livestock pasture, for instance, the peak flood magnitude can increase 20-fold. This form of catchment degradation leads to landslides, dams can breach, and road culverts and irrigation intakes are regularly washed away.

Land degradation in sub-Saharan rangelands is omnipresent, with over 90% rangeland degradation reported in Kenya’s northern drylands . Kenyan research has recorded dramatic increases in stormwater runoff due to overgrazing.

Second, human pressure in urban areas – including encroachment into riparian zones and loss of natural flood storage buffers through the destruction of wetlands – has increased flood risks. Riparian zones are areas bordering rivers and other bodies of water.

By 2050, half of Kenya’s population will live in urban areas. Green space is progressively being filled with buildings and pavements. A large proportion of urban population lives in tin-roofed slums and informal settlements lacking adequate drainage infrastructure. As a result, almost all of the storm rainfall is translated into rapid and sometimes catastrophic flooding.

Third, flood risks are worse for people who have settled in vacant land which is often in low-lying areas and within flood plains. In these areas, inundation by flood waters is inevitable.

Fourth, Nairobi’s persistent water supply shortages have led to a proliferation of boreholes whose over-abstraction has resulted in a dramatic decline in the underground water table’s levels. This leads to aquifer compression, which is compounded by the weight of buildings. The result is ground level subsidence , which creates low spots where stormwater floods collect.

What should be done to minimise the risks?

Rural areas require a different set of solutions.

Natural watercourses throughout Kenya are being scoured out by larger floods due to land use pressures. These watercourses are expanding and riparian vegetation cover is disappearing. The flood plains need space to regenerate the natural vegetation cover as this attenuates floods, reducing the force of runoff and erosion.

There are existing laws to protect riverbanks, and livestock movements in these areas must also be controlled. Any building or informal settlement within riparian areas is illegal and would otherwise be exposed to the dangers of floods. Enforcement is a challenge, however, as these areas are favoured by human activities and often these people are among the poorest.

Urban areas have a host of particular challenges that need to be addressed.

Take Nairobi, Kenya’s capital city. The physical planning process is hindered by corruption . Inappropriate and unsafe developments proliferate alongside inadequate water supply, wastewater and solid waste disposal infrastructure. Sewage effluent is often discharged into stormwater drains, even in high-class areas of the city. And there is little control of development in the growing urban centres bordering Nairobi, with transport corridors being congested. Throughout the country, laws that protect riparian zones are flouted.

None of this is sustainable.

Each municipality is obliged to provide infrastructure that includes an effective engineered stormwater drainage network. And in parallel, wastewater and solid wastes must be separately managed.

The typical stormwater drainage network comprises adequately sized earth and lined channels, and pipes and culverts that convey the stormwater to the nearest watercourse. Constant maintenance is essential, especially before the onset of rains, to avoid blockage by garbage and other human activities.

Modern-day urban flood mitigation measures include the provision of flood storage basins. Unfortunately this is impossible in Nairobi where developments are built right up to the edge of watercourses. Constrained channels thereby cause upstream flooding as there is nowhere else for the water to go.

Attempts have been made to reverse urban riparian zone encroachments , but these efforts faltered due to legal repercussions. To this day, unscrupulous developers encroach with impunity .

It’s essential that the authorities demarcate riparian boundaries and set aside buffer zones that cannot be “developed”.

• Urbanisation
• Deforestation
• Groundwater
• Water catchment
• East Africa
• Sub-Saharan Africa

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