Chennai Floods Research Articles

Influence of atmospheric rivers in the occurrence of devastating flood associated with extreme precipitation events over Chennai using different reanalysis data sets

The main focus of the present study is to examine the presence of Atmospheric Rivers (ARs) in the occurrence of Chennai (13.5° N, 80.5° E) flood event over Tamil Nadu which is south-eastern part of Indian peninsular region of India during November to December 2015. The vertically integrated horizontal water vapor transport (IVT) algorithm was used for the detection of ARs using three different reanalysis products, namely, the NCEP-NCAR (National Center for Atmospheric Research), NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) and ECMWF Interim Re-Analysis (ERA-Interim). It is noticed that the occurrence of heavy precipitation events (HPEs) prior to the flood in the Chennai city, has been in good agreement with the presence of ARs during that time. The distribution from TRMM-3B42RT, TRMM-3B42 are validated with the with in situ rain gauge observations over the Chennai city. We have conducted quantitative analysis of IVT and their impact on heavy precipitation events and flood occurred over Chennai city. It is seen that MERRA reanalysis could be able to provide better presence of ARs. The study mainly reveals that persistent ARs of >18 h resulted in extremely heavy precipitation and lead to associated flood over Chennai. Also, the atmospheric conditions, ARs and rainfall simulated from Advanced Research Weather Research and Forecasting model (ARW) show good agreement with reanalysis and observations. Over the given reference period 1979–2015, correlation between IVT and HPEs is statistically significant at 99.5% confidence level. But the correlation between IVT during persistent ARs and corresponding HPEs is statistically significant at 90% confidence level. A large fraction of HPEs occur after ARs, with a small portion of ARs would lead to HPEs. The Chennai gird historical rainfall data is suitably fitted by Extreme Value Distribution (EVD) models. Inference model using the Maximum Likelihood Estimation (MLE) was applied on EVD considering their impact on the shape parameter and the confidence interval width. A Non-stationary generalized extreme value (GEV) analysis, was used to determine the strength of association between the precipitation extremes and IVT. The influence of the location and the scale parameter in the GEV model on different return levels (2-year, 20-year, and 100-year) are explicitly described. The return-level threshold values are found to change with IVT considerably. This study advocates that the detection of ARs can be used as important proxy in identifying the likelihood of occurrence of heavy precipitation/flash flood events for a given location using reanalysis data sets.

Modelling the inter-relationship between factors affecting coordination in a humanitarian supply chain: a case of Chennai flood relief

The humanitarian supply chain (HSC) aims at providing relief to affected people in the wake of a disaster at the right place and at the right time to reduce their suffering. One of the major challenges faced by the HSC is the coordination between various actors. Previous studies have identified the factors affecting coordination but the literature is silent on the inter-dependence between these factors (criteria). In this study, we identify the factors affecting coordination based on the review of extant literature in HSC and interviews with multiple individuals representing various stakeholders involved with the relief activities carried out during the Chennai floods. These factors were grouped into four categories: information sharing, diversity (of the humanitarian agencies), organizational mandates and material convergence. We use a hybrid fuzzy DEMATEL-ANP methodology to identify the interdependence and develop the network relationship diagram by mapping the interdependence between the factors affecting the effective coordination between the actors in HSC. Our results indicate that information exchange between the humanitarian actors (HA) tantamount to achieve coordination in post disaster response phase. However, with the improvement in the post–disaster coordination, the HAs need to focus on pre-disaster preparedness phase through strong alignment of organizational mandates of HAs and focus on the diverse nature of HAs to align their operational strategies through standardized operations, inter-operability of activities and building trust through long term associations.

Children in the 2015 South Indian floods: community members’ views

ABSTRACTLittle is known about children’s experiences and involvement in disaster preparation and recovery, in particular in low- and middle-income countries. Eliciting community members’ perspectives on the 2015 floods in Tamil Nadu, India, may generate useful insights for improving services in low-resource settings. This qualitative study aimed to understand how children in Chennai experienced the floods, as reported by the adults in their community, and to explore children’s involvement in disaster preparedness, response and recovery efforts as reported from the adults’ perspective. We conducted in-depth, semi-structured interviews (N = 48) with family members (n = 36), and with staff of non-governmental organizations (NGOs) (n = 12) who actively participated in relief and recovery efforts. We also conducted two focus group discussions (n = 14) with NGO staff about a year after the 2015 South Indian floods in Chennai, India. Six broad themes regarding children’s experiences and behaviours during and after the floods emerged: (1) unexpectedness of the floods; (2) children’s safety – barriers and facilitators; (3) parents’ reactions – helplessness, fear and pride; (4) children’s reactions – helping hands, fun and fear; (5) barriers to a return to ‘normal’; and (6) a determination to be prepared for next time. Children and families were deeply impacted by the floods, in part owing to a lack of preparation, as perceived by the study participants. It was also clear from the data analysis that caste and socioeconomic status played an important role in the families’ ability to evacuate safely. Helplessness on the part of the parents was apparent, as was children’s concern over recurrence of the flood. Similarly, gender appeared to affect child safety, recovery and other outcomes such as continued education. Priorities for future efforts involve the development and evaluation of child-centred education about flood awareness, child participation and safety.

Flood disasters in the United Kingdom and India: A critical discourse analysis of media reporting

Reports of flooding are becoming more frequent in the UK media, and evidence from the UK Environment Agency indicates that ‘living with flooding’ will become commonplace rather than exceptional. This study is the first to adopt a critical discourse analysis approach to compare UK newspaper reporting of floods in the developed and developing world. We present our analysis of major flood incidents in Northern England and Chennai, India, in 2015. Our findings identify that UK newspapers not only give greater prominence to flooding events that are local but also frame differently those affected. Reports of floods in Northern England reinforced similarities and shared values between victims and assumed readers by drawing upon personal stories, emotions and suffering. By contrast, reports about floods in Chennai portrayed victims as anonymous ‘distant Others’, emphasising the drama of the incident rather than the plight of individuals. We argue that the newspapers’ approach to covering flooding reveals how the Western-dominated global media continue to emphasise difference rather than similarity between people in the developed and developing world, presenting flooding in the United Kingdom as exceptional and flooding in India as normalised. We believe these findings have important implications in the context of globalisation and increasing migration.

Analysis and Early Detection of Rumors in a Post Disaster Scenario

The use of online social media for post-disaster situation analysis has recently become popular. However, utilizing information posted on social media has some potential hazards, one of which is rumor. For instance, on Twitter, thousands of verified and non-verified users post tweets to convey information, and not all information posted on Twitter is genuine. Some of them contain fraudulent and unverified information about different facts/incidents - such information are termed as rumors. Identification of such rumor tweets at early stage in the aftermath of a disaster is the main focus of the current work. To this end, a probabilistic model is adopted by combining prominent features of rumor propagation. Each feature has been coded individually in order to extract tweets that have at least one rumor propagation feature. In addition, content-based analysis has been performed to ensure the contribution of the extracted tweets in terms of probability of being a rumor. The proposed model has been tested over a large set of tweets posted during the 2015 Chennai Floods. The proposed model and other four popular baseline rumor detection techniques have been compared with human annotated real rumor data, to check the efficiency of the models in terms of (i) detection of belief rumors and (ii) accuracy at early stage. It has been observed that around 70% of the total endorsed belief rumors have been detected by proposed model, which is superior to other techniques. Finally, in terms of accuracy, the proposed technique also achieved 0.9904 for the considered disaster scenario, which is better than the other methods.

Geo-anthropogenic aberrations and Chennai floods: 2015, India

The flood occurred in December 2015 in Chennai, the capital city of the state of Tamil Nadu, India, is a major disaster in the history of the region as it caused the loss of 421 human lives, affected over 2 million people and the loss of properties worth of US$ 80,000 million. There were beeline of observations through media and dailies, all attributing the floods to the indiscriminate urbanization. In the context of lack of any scientific observations on the disaster which occurs often, and at the same time the Chennai region is geologically vibrant with active geodynamics viz. tectonics and tectonically induced riverine and coastal geomorphic processes, a study was undertaken involving all the features related to both geodynamics and anthropogeny to unfurl the mysteries behind the recent flood disaster. In the study, ArcGIS-based spatial databases were generated on the (1) flood inundation interpreted from post-flood MODIS satellite data, (2) geodynamic features related to earth movements, riverine/fluvial and coastal geomorphology interpreted from IRS LISS IV FCC and GeoEye satellite data, (3) anthropogenic features viz. encroached drainages, water bodies and the wetlands extracted from IRS and GeoEye satellite data and (4) integrated geo-anthropogenic data. Using these GIS databases, spatial modelling was carried out between the flood inundation data and the geodynamic, anthropogenic and geo-anthropogenic data sets which revealed that these have significantly controlled the December 2015 floods of Chennai city. The GIS-based spatial correlative study between the flood and the geodynamic features indicated that the land arching, deepening and land subsidence related to post-collision tectonics; and the tectonically tutored phenomenon of river migration and the resultant occurrence of huge system of palaeochannels and the complex drainage patterns, and the coastal geomorphic features viz. palaeobeach ridges and swales, defunct swamps and the wide tidal flats have controlled the floods. The study with anthropogenic features indicated that the unmindful obstructions of drainages, encroached water bodies and encroached segments of the tidal flats and the swamps were the loci for the floods, whereas the spatial analysis between the flood and integrated geo-anthropogenic data gave fine resolution information that the anthropogenic features depending upon the geodynamic features with which these are associated determined the floods; for example, (1) the obstructions of drainages along deflected drainages, compressed meanders and tectonic deepening, (2) encroachment of water bodies in zones of deflected drainages and tectonic subsidence and (3) encroachment of tidal flats and encroachment of Pallikaranai swamp in zones of tectonic deepening. These observations have lead to broader remedial strategies.

Study of Gully Pot Monitoring System for Urban Areas

Sewer failure occurs is one of the major problem in urban areas. The major cause of flooding is due to overflow of sewers. Several manholes across residential areas are overloaded due to excess sewage load. This is the main reason for the occurrence of Chennai flood. Inefficient gully pot network is the major reason for the over flooding of mainstream sewage pipes. There is a need for an efficient system design for monitoring a gully pot which is capable of providing required information about sewage block is prior to the occurrence. Wireless Sensor Network (WSN) has been used to monitor the sewer blockages. The blockage will be detected and the detected information has been transmitted to the authority through a GSM and developed in mobile application.

Coordination quality index: a metric for measuring the quality of coordination efforts in humanitarian supply chain

The effectiveness of the coordination practice has a direct consequence on the performance of humanitarian supply chain operations and it becomes imperative for the managers to quantify the effectiveness of the coordination activities. This study aims to provide humanitarian agencies with a tool to measure effectiveness of its coordination strategies. Coordination quality index (CQI) is introduced as an aggregate measure of the degree of implementation of various coordination practices carried out. Furthermore, the application of the proposed methodology is demonstrated in the setting of Chennai flood relief activities. The results indicate that the overall quality score obtained for coordination during the Chennai floods was moderate to low. The major reason for the poor coordination was due to poor information sharing, large diversity of actors and lack of streamlined organisational mandates. It also found that, though there were efforts to improve coordination, the expected benefits of these activities were not achieved.

Coordination quality index: a metric for measuring the quality of coordination efforts in humanitarian supply chain

The effectiveness of the coordination practice has a direct consequence on the performance of humanitarian supply chain operations and it becomes imperative for the managers to quantify the effectiveness of the coordination activities. This study aims to provide humanitarian agencies with a tool to measure effectiveness of its coordination strategies. Coordination quality index (CQI) is introduced as an aggregate measure of the degree of implementation of various coordination practices carried out. Furthermore, the application of the proposed methodology is demonstrated in the setting of Chennai flood relief activities. The results indicate that the overall quality score obtained for coordination during the Chennai floods was moderate to low. The major reason for the poor coordination was due to poor information sharing, large diversity of actors and lack of streamlined organisational mandates. It also found that, though there were efforts to improve coordination, the expected benefits of these activities were not achieved.

North-East monsoon rainfall extremes over the southern peninsular India and their association with El Niño

The present study investigates the relationship between extreme north-east (NE) monsoon rainfall (NEMR) over the Indian peninsula region and El Niño forcing. This turns out to be a critical science issue especially after the 2015 Chennai flood. The puzzle being while most El Niños favour good NE monsoon, some don’t. In fact some El Niño years witnessed deficit NE monsoon. Therefore two different cases (or classes) of El Niños are considered for analysis based on standardized NEMR index and Niño 3.4 index with case-1 being both Niño-3.4 and NEMR indices greater than +1 and case-2 being Niño-3.4 index greater than +1 and NEMR index less than −1. Composite analysis suggests that SST anomalies in the central and eastern Pacific are strong in both cases but large differences are noted in the spatial distribution of SST over the Indo-western Pacific region. This questions our understanding of NEMR as mirror image of El Niño conditions in the Pacific. It is noted that the favourable excess NEMR in case-1 is due to anomalous moisture transport from Bay of Bengal and equatorial Indian Ocean to southern peninsular India. Strong SST gradient between warm western Indian Ocean (and Bay of Bengal) and cool western Pacific induced strong easterly wind anomalies during NE monsoon season favour moisture transport towards the core NE monsoon region. Further anomalous moisture convergence and convection over the core NE monsoon region supported positive rainfall anomalies in case-1. While in case-2, weak SST gradients over the Indo-western Pacific and absence of local low level convergence over NE monsoon region are mainly responsible for deficit rainfall. The ocean dynamics in the Indian Ocean displayed large differences during case-1 and case-2, suggesting the key role of Rossby wave dynamics in the Indian Ocean on NE monsoon extremes. Apart from the large scale circulation differences the number of cyclonic systems land fall for case-1 and case-2 have also contributed for variations in NE monsoon rainfall extremes during El Niño years. This study indicates that despite having strong warming in the central and eastern Pacific, NE monsoon rainfall variations over the southern peninsular India is mostly determined by SST gradient over the Indo-western Pacific region and number of systems formation in the Bay of Bengal and their land fall. The paper concludes that though the favourable large scale circulation induced by Pacific is important in modulating the NE monsoon rainfall the local air sea interaction plays a key role in modulating or driving rainfall extremes associated with El Niño.

ICT and Disaster Management

ICT-mediated public administration is a governance motive in this digital age. Government of India has embarked upon Digital India and Smart Cities Mission to reform public service delivery and governance in the country. However, the recent Chennai floods and the serious inadequacy of official emergency response system calls in question the ability of government to deliver when it is most needed. Public participation is an avowed objective of all government programmes including the development of smart cities or a digitally empowered India. Chennai Floods and the ensuing people-led disaster response and recovery presents a case where voluntary efforts steered disaster management through use of social media as official mechanisms failed. Based on secondary sources, this paper discusses the social media use in Chennai floods disaster and deduces observations for effective social media integration and public participation in governance through proactive government-led intervention.

Health impact of chennai floods 2015: Observations in a medical relief camp

Background: During the year 2015, Chennai and the South Indian coast experienced devastating floods due to unprecedented rains. Indiscriminate damage to housing, communication and transport networks, and health facilities ensued affecting the lives of thousands of people. Objective: To assess the morbidity profile of patients attending the medical camps conducted at Chennai during the postflood period. Methodology: In our study, the investigators with their health team conducted camps in Thiruvallur - one of the worst affected districts during the floods between November and December 2015. Data were collected regarding age, gender, and presenting health problems. Total number of patients seen in camps was 5633. Results: It was observed that among people who came to the camp, common health problems were as follows - 46.84% had acute respiratory tract infections, 24.87% with acute gastroenteritis, 18.6% had fever, and 14.41% with skin problems. Conclusion: Due to provision of safe drinking water and epidemic prevention measures, epidemic outbreaks have been averted. However, strengthening of existing health care systems is required to handle the burden of acute gastrointestinal and respiratory infections during disasters such as floods.

Satellite data planning for flood mapping activities based on high rainfall events generated using TRMM, GEFS and disaster news

ABSTRACTMicrowave satellite data enable the mapping of flooding over large areas, irrespective of cloud and weather conditions. Efficient planning of microwave data for acquiring satellite images over flood-affected areas for flood assessment and mapping needs prior information about the probable flood areas. Analysis of rainfall trend over a particular region over a time can help in predicting the flood-like situation and probable flood areas. Forecasts from weather forecasts models provide a fair idea about high rainfall events. Integration of global rainfall products (Tropical Rainfall Measuring Mission (TRMM)) and global forecast precipitation products (Global Ensemble Forecast System (GEFS)) can help in identifying the probable areas which may attain high rainfall. This advance information about probable high rainfall areas can be used in planning the remote sensing satellites for acquiring the satellite imagery over the area for flood mapping activities. Temporal satellite images integrated with disaster news available on Internet can help in analysing the ground situation (residing or increasing of flood situation). It can help in resource planning and management. The main purpose of this study is to develop a GIS-based framework coupled with automatic procedures for integrating TRMM, GEFS and disaster news using open-source technologies to identify the probable high rainfall area over Indian region and its application in planning acquisition of microwave satellite data sets for flood mapping activities. The high rainfall events identified using TRMM, GEFS and disaster news have been verified with Indian Metrological Department rainfall data during Chennai floods 2015 and Assam floods 2016. The system has been successfully used to plan and acquired satellite data for flood season 2015 and 2016.

How Facebook Framed Messages to Mobilize Residents during Chennai Floods in 2015

With the technological innovations, communication has become tremendously fast making the world small. Social media is one such innovation which began ruling the online culture of interaction. Its instantaneous popularity and timeliness is the best way to communicate around the globe. The top social networkingsite, Facebook, has52 lakhs smartphone users in Chennai, which is the capital city of the Indian state of Tamil Nadu. This trend of accessing Facebook via smartphones makes it handy during crisis when there are power disruptions. Unexpected floods occurred in Chennai in November-December 2015 and Chennai was officially declared a disaster city on December 2. The usually busy Chennai city became standstill with the loss of humans and infrastructure. Communication became a major problem with the mobile networks and landlines going for a toss. The then isolated city had all its sources of communication cut, except access to Facebook and mobile. Facebook was an important tool in disseminating information on Chennai floods in 2015. So, it is important to understand how Facebook framed messages during Chennai floods, which helps to understand its role of reinforcing and public perception of it. Through discourse analysis of the most popular posts of #Chennai Micro, an initiative by RJ Balaji and actor Siddharth in Facebook during the time period December 2 to 6, 2015 are studied. This study examines how crisis was framed by media organizations, non-profit organizations, celebrities, RJ Balaji&Siddharth, and individuals to contribute in bringing Chennai back to normal.

Usage and analysis of Twitter during 2015 Chennai flood towards disaster management

Social media plays a major role in the propagation of information during disasters. This paper mainly contains a study regarding how people of Chennai used social media especially twitter, in response to the country’s worst flood that had occurred recently. The tweets collected were analysed using machine learning algorithms such as Random Forests, Naive Bayes and Decision Tree. By comparing the performances of all the three it was found that Random Forests is the best algorithm that can be relied on, during a disaster. This paper also targeted the sources of the Twitter messages to explore the most influential users of Chennai flood.

Study and Analysis of Chennai Flood 2015 Using GIS and Multicriteria Technique

Terrain characteristics of the land and meteorological properties of the region are the main natural factors for flood. The recent flood in Chennai was unexpected and not triggered by the above factors. Sometimes floods occur when the watershed size is considerably small which leads to the over flow of water inland may due to the encroachment and the urban development of the city. Temporarily used backwater effects in sewers and local drainage channels and creation of unsanitary conditions may cause flooding. Chennai flood was basically claimed to occur due to improper drainage system and underlying strata which was found to be landfill over the ponds and lakes. The Coouam River which flows through the centre of main city was found silting due to the improper drainage facilities and encroachment by the local peoples who causes flood. For the analysis of potentially affected areas Geographical Information System (GIS) integrated with Multicriteria Decision Analysis (MCDA) were employed. Ranking and displaying the potentially risky areas, the spatial Multicriteria analysis was used. It has been revealed that all most all the area’s having populations are likely to be exposed to flood hazard. At the end of study, a map of flood risk areas was generated and studied with a view to assisting decision makers on the consequences posed by the disaster.

The Analysis of Flood Disaster Management in Chennai

Objectives: The prime aim of this study is to build a Humanitarian Assistance Ontology. Methods/Statistical Analysis: The study used literature review methodology which involves a thorough literature search of Chennai flood – 2015 disaster. Search keywords used were social media, ontology, disaster management,water related attributes, Spatial Clustering algorithm. Full text research articles published between 2008 and 2016 were included. Quality assessment criteria were set to determine what to include and exclude for this study. 25 papers were identified as potential units for analysis. Findings: The findings have clearly revealed that only a limited study had been undertaken in the use of social media for knowledge integeration. But there is a need for knowledge towards investigating the data created in disaster management situations. Also, to determine how knowledge coordination can assist higher officials to take decision at the time of emergency situation. The review of 25 final selected papers has indicated that there is a scope for more significant research. In this paper, we build an effort to fragment the social media users who have shared comments about the Chennai recent flood and its disaster and to recognize their demographics. Our findings come as anoutcome of a thorough bibliography study as well as our hands on experiences from social media. Application/Improvements: An innovative outcome of the research was a comprehensive study to build a onto-database to recognize the right information at right time to right people as a new technology in context of crisis response.

The social role of social media: the case of Chennai rains-2015

Social media has altered the way individuals communicate in present scenario. Individuals feel more connected on Facebook and Twitter with greater communication freedom to chat, share pictures, and videos. Hence, social media is widely employed by various companies to promote their product and services and establish better customer relationships. Owing to the increasing popularity of these social media platforms, their usage is also expanding significantly. Various studies have discussed the importance of social media in the corporate world for effective marketing communication, customer relationships, and firm performance, but no studies have focused on the social role of social media, i.e., in disaster resilience in India. Various academicians and practitioners have advocated the importance and use of social media in disaster resilience. This article focuses on the role that social media can play during the time of natural disasters, with the help of the recent case of Chennai floods in India. This study provides a better understanding about the role social media can play in natural disaster resilience in Indian context.

The Chennai floods of 2015: urgent need for ethical disaster management guidelines

India has suffered several natural disasters in recent years. The super cyclone of Orissa in 1999 and the tsunami on the southeastern coast in 2004, both led to major developments in disaster management abilities in the country. Almost a decade after the last major disaster that hit south India, the recent floods in Chennai in 2015 brought to the fore a whole set of ethical considerations. There were issues of inequity in the relief and response activities, conflicts and lack of coordination between the government and non-government relief and response, more emphasis on short-term relief activities rather than rehabilitation and reconstruction, and lack of crisis standards of care in medical services. This paper highlights these ethical issues and the need for ethical guidelines and an ethical oversight mechanism for disaster management and response.

The state and community media

Abstract