Quantification of Resilience Considering Different Migration Biographies: A Case Study of Pune, India

Abstract

Urbanization proceeds globally and is often driven by migration. Simultaneously, cities face severe exposure to environmental hazards such as floods and heatwaves posing threats to millions of urban households. Consequently, fostering urban households’ resilience is imperative, yet often impeded by the lack of its accurate assessment. We developed a structural equation model to quantify households’ resilience, considering their assets, housing, and health properties. Based on a household survey (n = 1872), we calculate the resilience of households in Pune, India with and without migration biography and compare different sub-groups. We further analyze how households are exposed to and affected by floods and heatwaves. Our results show that not migration as such but the type of migration, particularly, the residence zone at the migration destination (formal urban or slum) and migration origin (urban or rural) provide insights into households’ resilience and affectedness by extreme weather events. While on average, migrants in our study have higher resilience than non-migrants, the sub-group of rural migrants living in slums score significantly lower than the respective non-migrant cohort. Further characteristics of the migration biography such as migration distance, time since arrival at the destination, and the reasons for migration contribute to households’ resilience. Consequently, the opposing generalized notions in literature of migrants either as the least resilient group or as high performers, need to be overcome as our study shows that within one city, migrants are found both at the top and the bottom of the resilience range. Thus, we recommend that policymakers include migrants’ biographies when assessing their resilience and when designing resilience improvement interventions to help the least resilient migrant groups more effectively.

Energy Inequality Indicators: A Comprehensive Review for Exploring Ways to Reduce Inequality

“…By adopting a comprehensive approach that takes into account these specific factors, we can ensure that the most vulnerable populations are identified and provided with the necessary support to overcome energy inequality. This approach aligns with the findings of various studies that emphasize the importance of considering multiple dimensions of vulnerability in addressing energy inequality [84][85][86][87][88][89][90][91]. By understanding the unique challenges faced by vulnerable households, policymakers and stakeholders can develop targeted interventions and support mechanisms to improve their access to affordable and reliable energy services.…”

Exploring the relationship between droughts and rural-to-urban mobility—a mixed methods approach for Pune, India

“…Many of the new arrivals settle in peri-urban dwellings or one of the city's over 500 informal settlements ("slums"; Krishnamurthy et al, 2016). In previous work, we showed how the socio-economic status and resilience of migrants strongly depend on their place of origin and type of current residence: those who migrated from urban areas enjoyed 2 years of education more than those of rural origin, are more often living in formal urban housing (92% vs. 77%), and have three times as much water storage available (Link et al, 2021). Furthermore, migrants living in Pune's informal settlements have a significantly lower resilience than migrants living in formal areas.…”

“…Furthermore, migrants living in Pune's informal settlements have a significantly lower resilience than migrants living in formal areas. The least resilient group, ranging below any other migrant group and non-migrant residents, are consequently rural-to-urban migrants currently living informally (Link et al, 2021).…”

Capturing Stakeholders’ Challenges of the Food–Water–Energy Nexus—A Participatory Approach for Pune and the Bhima Basin, India

“…Heat stress impacts the local FWE nexus through higher water and electricity consumption (W-groundwater over-abstraction, E1-energy-intensive lifestyles), lower cooling capacity of thermal power plants, and losses in agricultural yield (F4-access to food, F5-pressure on rural livelihoods) [81]. The basin's population grew from 7.9 million in 1975 to 18.7 in 2015, primarily in urban areas [69], which have become popular migration destinations [70,82]. The per capita GDP (PPP) of Maharashtra has increased more than six-fold since 1980 [83].…”

“…They usually also require additional energy inputs, e.g., delivery by tanker trucks (E1-energy-intensive lifestyles) [95]. As Link et al [82] show, Pune's recent floods hit slum dwellers and rural migrants especially hard (X5-informality), with many casualties and grave economic consequences. The stakeholders were convinced that these are consequences of both climate change and insufficient infrastructure (X1-climate change, W5-costly water system).…”