Assessment of Urban Resilience as an Approach towards Urban Sustainability: A Case of Gurugram India.

Abstract

Indian cities are complex and interdependent system, extremely vulnerable to threats from both natural risks and manmade disasters caused by the growing urban population, migration, depleting resources and terrorism. There are abundant evidences on resource consumption and emissions, biodiversity and land use change to show that Indian cities are responsible for a large part of unsustainable trends which push the planet beyond its ecological boundaries. With expedited urbanization, it becomes imperative to prioritise vulnerability assessment in order to increase resilience and thus attain sustainability. Recent studies indicate that the resilience framework is not consistent; they have either been applied in a natural resource context or focused on a single factor such as socio- economic vulnerability or structural weakness of physical components. Secondly, there is lack of resilience framework for developing nations or local contexts as the applicability of results from developed countries are problematic to instrument technically or theoretically at native scale. Given the diversity of interpretations and application of the resilience assessment in complex urban systems, this paper looks at factors and parameters that influence the Indian cities with major focus on Gurugram.(the third wealthiest city in India, by per-capital income with a massive population but such phenomena growth has overwhelmed city planning even with the availability of funds).The paper further explores the resilience assessment framework based on the five defined and measurable domains including social (education equity, transportation access, health coverage, communication capacity), economic (employment, income, housing capital), institution (migration plan, flood coverage, political fragmentation by Indian institutions such as National Institute of Urban Affairs (NIUA), physical (e.g. water, sanitation, housing and land use), spatial (elevation, spatial and temporal indicators), human (e.g. literacy rate, health insurance) and Environment (e.g. ecosystem services, environmental policies).Various case examples are used to suggest that urban resilience can be conceived as a multidisciplinary framework to analyse the reactive, adaptive and transformative capacities of (and within) the complex urban system of Indian cities.

Introduction

I. INTRODUCTION: RESILIENCE

The term ‘resilience’, roots in disciplines such as physics, psychology and ecology and has been widely used in scientific and political discourse on sustainable development and urban disaster reduction. The origins of the concept of resilience are nebulous and controversial according to the literature. Part of that is keen on identifying its first employment in the field of psychology and psychiatry, linking resilience to Norman Garmezy, Emmy Werner and Ruth Smith. Interestingly, more recent researches highlighted probable previous uses of the concept, dating back till the first century B.C. in the poem “Nature of Things” by Lucretius. In contrast to this view, Alexander identifies its origins in the Classical literature by noteworthy authors such as Seneca the Elder, Pliny the Elder, Ovid, Cicero and Livy .From an etymological viewpoint resilience finds its root in the Latin verb “resil?re”, meaning “to jump back”.

Resilience is a multi-disciplinary and complex concept, hence its analysis and formulation cannot leave aside some related notions such as vulnerability, adaptive capacity and recoverability, especially concerning the built environment issue in face of disruptions. In contrast, the term ‘vulnerability’ tends to characterize in negative terms as a system (for instance, economic sector, city, infrastructure, population) that incapable to cope with contrary effects (Romero Lankao & Qin, 2011). The urban vulnerability research is mainly focused on general environmental change such as political economy, natural stressors and ecological resilience (O’Brien et al., 2009). The studies conducted in the past attempted to answer why and how urban populations are vulnerable, but these researches did not account how to experience and influences from varying stressors work (Parnell et al., 2007; Satterthwaite et al., 2007; Pelling, 2011). 

Later, according to Romero-Lankao and Romero Lankao and Qin (2011) viewed urban vulnerability as an active practice grounded on the incapability of a municipal to manage with stressors which directed to the evolving tender of resilience science. Resilience, on the other hand, reflects a change from vulnerability to response capacity building. Yet, the concept has mainly discussed in related to climate change adaption and disaster management perspective rather than addressing wider sustainability challenges. Therefore, researchers have called to address urban resilience beyond climate change focusing on the holistic approach (Ostadtaghizadeh et al., 2015) .

Cities are an interdependent and complex system, tremendously vulnerable to fears from both natural risks caused by a growing urban population, high population density and terrorism. These made cities to rethink how people and infrastructure are protected and prioritized and climate will affect long terms growth and development, the city of Gurgaon, the third wealthiest city by per-capital income with a massive population but such phenomena growth has overwhelmed city planning even with the availability of funds. (Sahu et al., 2015) The links between poverty and exposure sensitivity attributes are more nuanced in Gurgaon hence much more vulnerable. This city has witnessed enormous change in the last two decades thanks to the proximity to Airport and other economic drivers. The study of resilience keeping in mind the complexity of the urban systems is much needed here. In comparison to any other Indian cities, the transportation system and urban infrastructure and overall quality of life (social inequality, unsafe environment, non-existent public realm) have been below par (Sahu et al., 2015).

A study is required particularly in the Gurgaon’s millennium city in demand to drive the research for urban resilience and drill a step onward by: initially implementing  an method concentrated on larger stresses and scale shocks, and flowing effects through multiple scales as well, comprising circumstances wherever trade-offs in resilience might happen, and then  emphasizing the statement that resilience per se is not the aim in efforts in the direction of sustainability, and that resilience in a specific situation may not continuously share the progressive associations of sustainability. Understanding resilient in import ant as emphasized by the Godschalk (Godschalk, 2003), a resilient city as a capability of surviving and functioning even under extreme stress owing to a supportable network of human groups and physical systems.

II. URBAN RESILIENCE AS AN IMPORTANT DEVELOPMENT IMPERATIVE

Half of humanity i.e about3.5 billion people live in cities today and by 2030, 60% of the world’s population will live in urban areas. The pace of urban growth transformation of global land use is staggering. It is estimated that 1.4 million persons move into urban areas every week. From 2000 to 2030, urban expansion is accelerating 27 fold as compared to 1970-2000 and is expected to add 1.2 million square kilometres, an area equivalent to the entire surface area of South Africa (NAS, 2012). Most of this expansion, nearly 95% - will occur in developing countries, and will be characterized by informal and unmanaged growth (OECD, 2017).

 Urbanization has the potential to lift people out of poverty and increase prosperity. Large cities generate about 75% of global GDP today and will generate 86% of worldwide GDP growth between 2015 and 2030 (Woetzel, 2016). Population growth and rising per capita income are key drivers, accounting for 58 % and 42 % of growth among large cities between 2000 and 2012 (Woetzel, 2016).

Rapid urbanization and unmanaged growth, however, tend to generate unsustainable land use, which is nearly impossible to change after a city grows. It is also associated with high levels of population exposure, especially for the poorest segments, to chronic stresses and shocks including environmental shocks (e.g., floods and earthquakes) and social stresses and shocks (e.g. crime and violence, conflict induced population influx).

The urban poor are disproportionally affected by chronic stress and shocks. By 2030, an estimated 325 million extreme poor will be living in the 49 countries most prone to disasters, and they will disproportionately suffer from shocks (Shepherd, et al. 2013). In these countries, the poorest and most vulnerable will live in the most exposed areas–often in informal settlements on the edge of cities –that have poor access to early warning or adequate infrastructure (ODI, 2016). Efforts to reduce poverty and disaster risks are complementary. Estimates for 89 countries find that if all natural disasters could be prevented next year, the number of people in extreme poverty those living on less than $1.90 a day would fall by 26 million (World Bank, 2017). These risks can undermine sustained economic growth and social progress.

III. COMPREHENDING THE RESILIENCE FRAMEWORK

Based on the reviewed literature, it is perceived that the present research of Resilience framework is still uneven (Cer? et al., 2017). Resilience, in general, is widely considered as a system's capacity to proactively adapt to external disturbances and recover from them. However, the existing resilience framework research is still quite fragmented and the links behind various studies are not straightforwardly accessible.

This is because studies either applied Resilience Assessment in a natural resource management context and or focused on a single factor such as socio-economic vulnerability(Cutter et al., 2003; Kusumastuti et al., 2014; Carreño et al., 2012; Salgado-Gálvez et al., 2016; Frigerio et al., 2016) or structural weakness of physical components (Cimellaro et al., 2010; Gülkan & Langenbach, 2004). Yet, there is a lack of holistic studies accounting for applying it to urban areas. The paper by Koren et al. (2017)  proposed urban system resilience from the perspective of four basic components which affect the system in the circumstance of a usual disaster such as structure, Open space,  buildings and community or could be broadly grouped into two basic components including physical and social. Refer to table:1 for disparity in the way resilience models have been used in the literature for assessment of resilience to natural hazards.

Furthermore, a study done by Tyler and Moench (2012) develops a framework which incorporates empirical and theoretical knowledge of the aspects contributing to resilience with procedures for transforming those ideas into exercise. The framework contains urban systems characteristics, institutions that relates agents and systems, the agents (organizations and people), and patterns of experience to climate change. Moreover, a paper Yoon et al. (2016) develops a methodology for assembling a set of indicators determining Community Disaster Resilience Index (CDRI) in relation to social, human, economic, institutional, and environmental factors. Moreover, a paper discusses for an improved prominence on the institutes of management and risk governance  in understanding the urban resilience. This moves the study of vulnerability away from attention on individuals to also deliberate risk management rules as co-productive of vulnerability and resilience in the City (Zaidi & Pelling, 2015).     

For instance, the study Romero-Lankao et al. (2016) applied a framework of livelihood to illustrate the households in urban Mumbai by the assets and also utilised fuzzy logic approach with an logical order procedure to inspect the effect of exposure, poverty, capacity, and sensitivity on vulnerability. On a similar note, the study by Yenneti et al.(2016) established a composite urban vulnerability index (CUVI) grounded on 13 pointers that form the vulnerability in the urban society and findings shed light on a substantial concentration of social vulnerability in Asian and central States. DasGupta and Shaw (2015) developed a five-dimensional community resilience framework by assessing 19 coastal communities resilience against climate-related disaster in Indian Sundarbans. The author used a systematic questionnaire to survey officials and found the extreme coastal blocs were less resilient. Kumar et al. (2016) conducted a climate change vulnerability study in Bangalore considering three mechanisms, sensitivity, exposure,  and adaptive capacity using Spatial Multi-Criteria Evaluation (SMCE). Findings showed that about 91% of the zone is experiencing a high degree of climate vulnerability.

Table 1: Comparison of the different models used for Resilience Assessment in Literature over a decade.(source: compiled by the author)

Each model is developed in theoretical or conceptual isolation from the others. Thus while there is some overlap in domains/content, differences are also present. For example, the social domain in the BRIC and Climate-DRI, but this is excluded from the Community-DRI . The models can also be differentiated with regard to the domain names and how variables are distributed between them. They also mix demographic (e.g., education, disability) and structural characteristics (land use, housing type) with social and psychological (e.g., social capital) characteristics.

The diversity evident in the above table:1 highlights a need for the development of a common conceptual or theoretical framework from which systematic study can develop. In the absence of the latter, the confusion over the use of the term and how it is assessed and developed will continue.

The models can also be criticized for the lack of inclusion of specific social and psychological factors (e.g., self- and collective-efficacy, sense of community) that have been empirically demonstrated to influence adaptation. The models are also lacking in attempts to quantify the relationships and inter dependencies between variables and particularly between levels of analysis. For example, in the BRIC it could be hypothesized that levels of education and communication capacity could predict levels of political engagement, civic involvement and advocacy

IV. RESILIENCE & INDIAN CITIES

In India, there are few studies that addressed resilience, but all these studies have looked at vulnerability from the socio-economic aspects. Secondly, the recent systematic review, studies had identified a number of challenges in the development of resilience indicators including (1) selection of the input (2) standardization of data (3) criteria weights determination (4) understanding relationship between (5) aggregation of criteria (6) validation of results and finally conducting uncertainty and sensitivity analyses (Beccari, 2016; Rufat et al., 2015). Thirdly, these studies  failed to account spatial indicator as part of their framework (DasGupta & Shaw, 2015) nor used robust analyses such as FDM, ANP or DEMATEL method to quantify and weight interdependent and multiple domains and indicators. Fourthly, Finally, not much attention has been paid to the multiple stakeholder participation in the development of the framework (de Brito & Evers, 2016). Finally, although CPDP under the UNDP flagship has conducted an awareness campaign at the local level Campaigin (2019), that’s not sufficient to address the sustainability.  There is a lack of vulnerability / resilience framework at the local level as the applicability of results from developed countries, or developing countries are problematic to instrument technically or theoretically at the native scale. Besides, the concept of CDR is still not been clearly conceptualized and assessed (Ostadtaghizadeh et al., 2015).

With this background, the proposed study develops natural disaster resilience assessment framework based on the five defined and measurable domains including social (e.g. education equity, transportation access, health coverage, communication capacity), economic (e.g. employment, income, female employment, housing capital), institution (e.g. migration plan, flood coverage, political fragmentation by Indian institutions such as National Institute of Urban Affairs (NIUA), physical (e.g. water, sanitation, housing and land use), spatial (elevation, spatial and temporal indicators), human (e.g. population with more than high school education, health insurance) and Environment (e.g. ecosystem services, environmental policies). The proposed study will use a combination of fuzzy Delphi method and Analytic Network process technique (Guleria & Edward, 2012) or Trapezoidal Fuzzy DEMATEL or the PEOPLES and CCRAM method to identify

Conclusion

Resilience can have desirable and undesirable consequences. Thus, resilience cannot be viewed as a normative desirable goal, but as a descriptor of complex systems dynamics. A shared or common definition of the concept and how it can be measured is required to provide the foundation for the development of the concept and to guide research. The concept has mainly discussed in related to climate change adaption and disaster management perspective rather than addressing wider sustainability challenges. Therefore, researchers have called to address urban resilience beyond climate change focusing on the holistic approach . There are clear gaps in the knowledge and technology that need to be addressed for the advancement of spatial resilience theory and its application. Integrating adaptation and mitigation response actions to climate change in urban-level policies requires comprehensive information on vulnerability patterns, yet a majority of local governments and decision makers in various cities in developing nations lack spatially explicit information on climate change vulnerability and its key drivers. Although we are in the era of ‘big data’,we rarely have data of sufficient temporal and spatial extent or resolution for comprehensively understanding system dynamics – this is especially true for temporal data. The lack of agreement on how the resilience concept translates into a measurable framework creates problems not only with regard to the practical implementation of resilience within at-risk communities, but also for systematic research and the development of policy.

References

[1] Beccari, B. (2016). A Comparative Analysis of Disaster Risk, Vulnerability and Resilience Composite Indicators. PLoS Currents. [Online]. Available from: http://currents.plos.org/disasters/?p=26273. [2] de Brito, M.M. & Evers, M. (2016). Multi-criteria decision-making for flood risk management: a survey of the current state of the art. Natural Hazards and Earth System Sciences. [Online]. 16 (4). pp. 1019–1033. Available from: https://www.nat-hazards-earth-syst-sci.net/16/1019/2016/. [3] Campaigin, A. (2019). About. [Online]. 2019. Available from: https://sdgactioncampaign.org/about-2/. [Accessed: 18 January 2019]. [4] Carreño, M.L., Cardona, O.D. & Barbat, A.H. (2007). A disaster risk management performance index. Natural Hazards. [Online]. 41 (1). pp. 1–20. Available from: http://link.springer.com/10.1007/s11069-006-9008-y. [5] Carreño, M.L., Cardona, O.D. & Barbat, A.H. (2012). New methodology for urban seismic risk assessment from a holistic perspective. Bulletin of Earthquake Engineering. [6] Cer?, G., Rezgui, Y. & Zhao, W. (2017). Critical review of existing built environment resilience frameworks: Directions for future research. International Journal of Disaster Risk Reduction. [7] Chen, G., Tao, L. & Zhang, H. (2009). Study on the methodology for evaluating urban and regional disaster carrying capacity and its application. Safety Science. [Online]. 47 (1). pp. 50–58. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0925753507001865. [8] Cimellaro, G.P., Reinhorn, A.M. & Bruneau, M. (2010). Framework for analytical quantification of disaster resilience. Engineering Structures. [9] Cutter, S.L., Boruff, B.J. & Shirley, W.L. (2003). Social vulnerability to environmental hazards. Social Science Quarterly. [10] DasGupta, R. & Shaw, R. (2015). An indicator based approach to assess coastal communities’ resilience against climate related disasters in Indian Sundarbans. Journal of Child and Family Studies. [11] Filipovic, M. (2007). The analytic hierarchy process as a support for decision making. Spatium. [Online]. (15–16). pp. 44–59. Available from: http://www.doiserbia.nb.rs/Article.aspx?ID=1450-569X0716044F. [12] Frigerio, I., Ventura, S., Strigaro, D., Mattavelli, M., De Amicis, M., Mugnano, S. & Boffi, M. (2016). A GIS-based approach to identify the spatial variability of social vulnerability to seismic hazard in Italy. Applied Geography. [13] Godschalk, D.R. (2003). Urban Hazard Mitigation: Creating Resilient Cities. Natural Hazards Review. [14] Guleria, S. & Edward, J.K.P. (2012). Coastal community resilience: analysis of resilient elements in 3 districts of Tamil Nadu State, India. Journal of Coastal Conservation. [Online]. 16. pp. 101–110. Available from: https://www.jstor.org/stable/41506580?seq=1#page_scan_tab_contents. [15] Gülkan, P. & Langenbach, R. (2004). The European Risk-Ue Project?: An Advanced Approach To Earthquake Risk Scenarios. In: 13 Th World Conference On Earthquake Engineering The Earthquake Resistance Of. 2004. [16] Koren, D., Kilar, V. & Rus, K. (2017). Proposal for Holistic Assessment of Urban System Resilience to Natural Disasters. IOP Conference Series: Materials Science and Engineering. [Online]. 245. pp. 62011. Available from: http://stacks.iop.org/1757-899X/245/i=6/a=062011?key=crossref.669c9190ccf0d91230392c6fc264a85c. [17] Kumar, P., Geneletti, D. & Nagendra, H. (2016). Spatial assessment of climate change vulnerability at city scale: A study in Bangalore, India. Land Use Policy. [18] Kusumastuti, R.D., Viverita, Husodo, Z.A., Suardi, L. & Danarsari, D.N. (2014). Developing a resilience index towards natural disasters in Indonesia. International Journal of Disaster Risk Reduction. [19] O’Brien, K., Hayward, B. & Berkes, F. (2009). Rethinking social contracts: building resilience in a changing climate. Ecology and Society. [Online]. 14 (2). pp. 12. Available from: https://www.ecologyandsociety.org/vol14/iss2/art12/. [20] Orencio, P.M. & Fujii, M. (2013). A localized disaster-resilience index to assess coastal communities based on an analytic hierarchy process (AHP). International Journal of Disaster Risk Reduction. [Online]. 3. pp. 62–75. Available from: https://eprints.lib.hokudai.ac.jp/dspace/bitstream/2115/52643/1/AHP-Disaster Resilience.pdf. [21] Ostadtaghizadeh, A., Ardalan, A., Paton, D., Jabbari, H. & Khankeh, H.R. (2015). Community Disaster Resilience: a Systematic Review on Assessment Models and Tools. PLoS Currents. [Online]. Available from: http://currents.plos.org/disasters/article/community-disaster-resilience-a-systematic-review-on-assessment-models-and-tools/. [22] Parnell, S., Simon, D. & Vogel, C. (2007). Global environmental change: conceptualising the growing challenge for cities in poor countries. Area. [Online]. 39 (3). pp. 357–369. Available from: http://doi.wiley.com/10.1111/j.1475-4762.2007.00760.x. [23] Pelling, M. (2011). The Vulnerability of Cities to Disasters and Climate Change: A Conceptual Framework. In: [Online]. pp. 549–558. Available from: http://link.springer.com/10.1007/978-3-642-17776-7_29. [24] Romero Lankao, P. & Qin, H. (2011). Conceptualizing urban vulnerability to global climate and environmental change. Current Opinion in Environmental Sustainability. [Online]. 3 (3). pp. 142–149. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1877343511000030. [25] Romero-Lankao, P., Gnatz, D.M. & Sperling, J.B. (2016). Examining urban inequality and vulnerability to enhance resilience: insights from Mumbai, India. Climatic Change. [26] Rufat, S., Tate, E., Burton, C.G. & Maroof, A.S. (2015). Social vulnerability to floods: Review of case studies and implications for measurement. International Journal of Disaster Risk Reduction. [Online]. 14. pp. 470–486. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2212420915300935. [27] Saaty, T.L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. Advanced book program. [Online]. McGraw-Hill. Available from: https://books.google.co.in/books?id=Xxi7AAAAIAAJ. [28] Sahu, M., Momin, S., Waghdhare, M., Marathe, S. & Dalal, R. (2015). Gurgaon Almost the Millennium City. Shelter. 16 (1). pp. 60–65. [29] Salgado-Gálvez, M.A., Zuloaga Romero, D., Velásquez, C.A., Carreño, M.L., Cardona, O.D. & Barbat, A.H. (2016). Urban seismic risk index for Medellín, Colombia, based on probabilistic loss and casualties estimations. Natural Hazards. [30] Samari, D., Azadi, H., Zarafshani, K., Hosseininia, G. & Witlox, F. (2012). Determining appropriate forestry extension model: Application of AHP in the Zagros area, Iran. Forest Policy and Economics. [Online]. 15. pp. 91–97. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1389934111001869. [31] Satterthwaite, D., Huq, S., Reid, H., Pelling, M. & Lankao, P.R. (2007). Adapting to climate change in urban areas: the possibilities and constraints in low and middle income nations. [Online]. London. Available from: http://pubs.iied.org/10549IIED/. [32] Schmoldt, D.L., Kangas, J. & Mendoza, G.A. (2001). Basic Principles of Decision Making in Natural Resources and the Environment. In: [Online]. pp. 1–13. Available from: http://link.springer.com/10.1007/978-94-015-9799-9_1. [33] Tyler, S. & Moench, M. (2012). A framework for urban climate resilience. Climate and Development. [Online]. 4 (4). pp. 311–326. Available from: https://www.tandfonline.com/doi/full/10.1080/17565529.2012.745389. [34] Yenneti, K., Tripathi, S., Wei, Y.D., Chen, W. & Joshi, G. (2016). The truly disadvantaged? Assessing social vulnerability to climate change in urban India. Habitat International. 56. pp. 124–135. [35] Yoon, D.K., Kang, J.E. & Brody, S.D. (2016). A measurement of community disaster resilience in Korea. Journal of Environmental Planning and Management. [Online]. 59 (3). pp. 436–460. Available from: http://www.tandfonline.com/doi/full/10.1080/09640568.2015.1016142. [36] Zaidi, R.Z. & Pelling, M. (2015). Institutionally configured risk: Assessing urban resilience and disaster risk reduction to heat wave risk in London. Urban Studies. [Online]. 52 (7). pp. 1218–1233. Available from: http://journals.sagepub.com/doi/10.1177/0042098013510957.

Copyright

Copyright © 2023 Pooja Lalit Kumar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.