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Manuscript number IJDRR_2018_530

Title Urban Disasters Beyond the City: Environmental Risk in ’s Fast Growing Towns and Villages

Article type Research Paper

Abstract India is one of the largest and fastest urbanizing countries in the world. While most scholarly attention has focused on the country’s large cities, towns and villages are also experiencing many of the changes that come with urbanization, including significant increases in environmental risk. In this paper we investigate disaster and climate risk in five fast- growing towns and villages in the District of . We based our research design on the MOVE Framework, a comprehensive and integrative framework for assessing disaster and climate risk. Based on primary and secondary data collected over a 3-year period 2015-2017, we find that our case communities are characterized by rapid spatial growth and change, a dynamic and challenging hazard context, and low government capacity or action to document, govern, or adapt to risk. In each community we find a fast accumulation of risk in the built environment and economy, which may only be “revealed” after a major disaster. The trends we observe — in physical growth, the transformation of economies and the built environment, the mismatch between governance structures and the challenges of urbanization, and the lack of resources for managing growth — are likely common in other small urbanizing places.

Keywords Urbanization; Risk; India; MOVE Framework; Darjeeling; Landslide

Corresponding Author Andrew Rumbach

Corresponding Author's University of Colorado Denver Institution

Order of Authors Andrew Rumbach, Gretel Follingstad

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To view all the submission files, including those not included in the PDF, click on the manuscript title on your EVISE Homepage, then click 'Download zip file'. 1 2 3 Urban Disasters Beyond the City: Environmental Risk in India’s Fast Growing Towns and 4 5 Villages 6 7 Andrew Rumbach1 & Gretel Follingstad2 8 9 Acknowledgements 10 11 The authors gratefully acknowledge research assistance from Rohan Rao, Izabela 12 Petrykowska, Bryan Sullivan, Vivek Mishra, Aachal Tamang and Juanita Mukhia. This study 13 was made possible by a grants from the Office of Research Services at the University of 14 15 Colorado Denver and the DigitalGlobe Foundation. 16 17 Abstract 18 19 India is one of the largest and fastest urbanizing countries in the world. While most scholarly 20 attention has focused on the country’s large cities, towns and villages are also experiencing 21 many of the changes that come with urbanization, including significant increases in 22 environmental risk. In this paper we investigate disaster and climate risk in five fast-growing 23 24 towns and villages in the of West Bengal. We based our research design on 25 the MOVE Framework, a comprehensive and integrative framework for assessing disaster and 26 climate risk. Based on primary and secondary data collected over a 3-year period 2015-2017, 27 we find that our case communities are characterized by rapid spatial growth and change, a 28 dynamic and challenging hazard context, and low government capacity or action to document, 29 govern, or adapt to risk. In each community we find a fast accumulation of risk in the built 30 environment and economy, which may only be “revealed” after a major disaster. The trends we 31 observe — in physical growth, the transformation of economies and the built environment, the 32 mismatch between governance structures and the challenges of urbanization, and the lack of 33 34 resources for managing growth — are likely common in other small urbanizing places. 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 1 Assistant Professor, Department of Urban & Regional Planning, University of Colorado Denver, USA. 51 Corresponding Author. 52 2 PhD student, College of Architecture and Planning, University of Colorado Denver, USA 53 54 55 1 56 57 58 59 1.0 Introduction: India’s Urban Transformation Beyond the City 60 61 Over the past 30 years, urbanization has transformed countries across Asia. From 1990-2014, 62 the population living in Asian cities rose by more than 1 billion, historic growth that will continue 63 for decades (Ellis & Roberts 2016). Urban growth in India reflects these regional trends; in 2011, 64 31.2% of the country’s population (377 million) was classified as urban.3 By 2050, the United 65 Nations estimates that India will add more than 300 million new urban residents, to global cities 66 like Delhi and Mumbai as well as hundreds of “secondary” urban centers with populations over 67 500,000. 68 69 There is another story of urbanization in India, one that is unfolding outside of cities. Across the 70 71 country, villages and towns are experiencing many of the changes that come with urbanization, 72 from shifts in economic activity to higher population densities and transformations of the built 73 environment. The growth in census towns, settlements that are classified as urban in the census 74 but still governed as villages, is illustrative of these trends. The number of census towns tripled 75 from 2001-2011 (from 1,362 to 3,894), accounting for 29.5% of the country’s total increase in 76 urban population (Pradhan 2013; Samanta 2014; Jain 2017).4 India is also experiencing 77 substantial in-situ urbanization, the transformation of rural settlements into urban places without 78 major geographical migration (Jain 2017, citing Zhu 2004; Pradhan 2013). 79 80 81 Urbanization in rural places in India brings distinct challenges. Government capacity to manage 82 development, which is limited in many cities, can be non-existent in many towns and fast- 83 growing villages (Kundu, Bagchi & Kundu 1999; Rumbach 2016b). There is also a distinct lack 84 of fiscal resources available to help towns and villages manage growth. As a whole, India has 85 some of the lowest spending on urban planning and infrastructure in the world, at just 1.1% of 86 GDP (UN-Habitat 2016, p. 11). Development schemes that aim to expand and improve urban 87 infrastructure and housing, like the 50,000 crore rupee ($8 billion) Atal Mission for Rejuvenation 88 and Urban Transformation (AMRUT), do not extend to rural communities. 89 90 91 These trends in urbanization have also led to a substantial increase in environmental risk, from 92 natural hazards and climate change related disasters (Nicholls et al. 2008; The World Bank 93 2012). Numerous studies have documented the factors contributing to increasing disaster risk in 94 large Indian cities, such as inadequate infrastructure (Revi 2005), increasing exposure (Joerin et 95 al. 2012), deficits in hazard and vulnerability related data (Rautela 2016), and a lack of 96 adequate housing and basic services, especially for the urban poor (Ranganathan 2015; 97 Rumbach 2017). Others have demonstrated potential pathways for disaster risk reduction and 98 99 urban climate adaptation through improved planning, infrastructure investment, and policy 100 101 3 As Mukhopadhyay et al. (2016) point out, India is the only country in the world that uses population, 102 population density, and economic character together to define ‘urban,’ a strict set of criteria that leads the 103 country to classify populations living in urban conditions as rural (2). As a point of comparison, the World 104 Bank’s agglomeration index (AI), developed to provide a consistent measure of urbanization across 105 countries, estimates that India is actually 52% urban, a substantial different from the country’s own 106 Census estimates and what Mukhopadhyay et al. describe as India’s “hidden” urbanization. 4 A census towns is defined as an area with more than 5,000 people, a population density of at least 400 107 per square kilometer, and an economic base where more than 75% of the male main working population 108 is engaged in non-agricultural pursuits (Census of India 2011). 109 110 111 2 112 113 114 115 learning (Revi 2008; Mukhopadhyay & Revi 2009; Chu 2016). Yet, few studies have looked at 116 117 the growth of urban environmental risk in fast growing towns and villages. In this paper we ask, 118 how is India’s urban transformation beyond the city shaping disaster risk? We approach this 119 question through a mixed-methods study of towns and villages in West Bengal, one of India’s 120 fastest urbanizing states. 121 122 2.0 Understanding Risk: The MOVE Framework 123 Our main conceptual tool for understanding disaster risk is the MOVE Framework (Birkmann et 124 al. 2013), a comprehensive and integrative framework for assessing vulnerability, risk, and the 125 various actions people and communities make to mitigate, cope with, and adapt to those threats 126 127 (Ibid., 193). The framework does not provide specific risk assessment methods or defined 128 indicators (Birkmann et al. 2013, 207). Instead, it captures the key place-specific factors that 129 produce vulnerability and its “thematic dimensions” (physical, social, ecological, economic, 130 cultural and institutional) (Ibid. 199) and efforts to govern risk or adapt to changing conditions. 131 The holistic nature of the MOVE framework makes it well-suited to diagnosing risk in places that 132 are generally understudied and undertheorized in the disaster studies literature. Instead of 133 presupposing that the fundamental dynamics of vulnerability and risk in fast-growing towns and 134 villages will be similar to other urban or rural contexts, the MOVE Framework allows us to 135 136 conceptualize and assess these dynamics from the ground-up. The framework’s explicit 137 approach of integrating adaptation into the disaster risk reduction (DRR) perspective is also 138 useful in places like India where natural hazards and climate change pose significant and 139 interrelated challenges to urbanizing communities (Schipper & Pelling 2006).5 140 141 [INSERT FIGURE 1 ABOUT HERE] 142 143 This study employs the MOVE framework to study disaster risk in small urbanizing places in the 144 hill areas of the Darjeeling District, the northernmost district of West Bengal (see Figure 1).67 145 146 West Bengal is an important site for understanding urban disaster risk in towns and villages 147 because of the level of growth occurring in small urban places within the state.8 It is also 148 exposed to a broad range of environmental hazards, from heat waves, coastal storms and 149 flooding in the south to earthquakes and landslides in the mountain north, including the 150 Darjeeling District (State of West Bengal 2015). 151 152 3.0 Research Design and Data Collection Methods 153 154 155 156 5 For a full accounting of the MOVE Framework and its theoretical and empirical underpinnings, see 157 Birkmann et al. 2013 and Contreras & Kienberger (2011). 158 6 We partnered with Save the Hills, a community based organization based in the Darjeeling District, to 159 carry out data collection for this study. Save the Hills is a citizens organization dedicated to raising 160 awareness of the risk from natural hazards in the Darjeeling- . 7 161 The Darjeeling District can be divided into two regions, based on topography. The subdivision, 162 located in the southern part of the district, is part of the Bengal plains. In in the north and east are steep hill areas, the foothills of the Himalayan Mountains (Figure 2). Our study focused on these steep, hilly 163 areas, and included the Darjeeling, , and sub-divisions. 164 8 For example, West Bengal has 780 census towns, the highest of any state in India (Pradhan 2013). 165 166 167 3 168 169 170 171 We selected five case-study communities in the Darjeeling District for our study.9 We chose 172 173 communities to represent the range of small places that are seeing rapid urban change in the 174 district, including census towns, fast-growing villages, built-up areas along roads and highways, 175 communities on the outskirts of existing cities, and relatively remote market towns experiencing 176 in-situ urbanization. The case study communities include: 177 178 ● Dungra-Bhamay Gaon (hereafter Dungra) is a village just below the eastern face of the 179 city of Kalimpong, above the Relli River. Historically Dungra was an agricultural area, but 180 from 1991-2011 its population and population density nearly doubled, with intensive 181 growth along paved roadways that lead to Kalimpong. The village has several natural 182 183 springs and provides much of Kalimpong’s privately delivered drinking water. 184 ● Lebong is a town located 8 kilometers north of the city of Darjeeling. Lebong was 185 originally settled by workers from nearby tea gardens and is now known for its race 186 track, sports stadium, and several prominent boarding schools and churches. 187 ● Lower Chibo-Pashyor (hereafter Lower Chibo) is a collection of villages on the steep 188 hillside on the western face of Kalimpong, above the (Rao 2009). Lower 189 Chibo is transected by the main road that links Kalimpong to the plains below. It is one of 190 the most landslide affected communities in the District, with many active slides that have 191 192 cost lives, farmland, and caused damage to buildings and infrastructure. 193 ● Pulbazar is a remote town located along the Chota Rangit River, approximately 20 km 194 west of the city of Darjeeling. Pulbazar, along with the nearby town of Bhijanbari, are the 195 major commercial and market centers for nearby villages and tea estates. 196 ● -Kashyone-Sakyong (hereafter Pedong) is a small town located on the eastern 197 edge of the Darjeeling District. Pedong is located on the Silk Road, a historic trade route 198 that linked India to neighboring . Today, Pedong is home to several well-known 199 boarding schools and is a popular stop for tourists travelling to Sikkim. Pedong includes 200 the dense downtown market area and nearby agricultural communities. 201 202 203 [INSERT FIGURES 2 AND 3 ABOUT HERE] 204 205 3.1 Data Collection Methods 206 Understanding disaster risk in small urbanizing places is challenging due to the lack of available 207 data — on hazards and disasters, the long-range effects of climate change, or the political, 208 social, and economic context of places that contribute to vulnerability. This study included three 209 field visits to the Darjeeling District from 2015-2017 to develop indicators and collect primary 210 211 data on the components of risk described by the MOVE framework (Table 1). Our data 212 collection methods included: 213 214 215 216 9 In February of 2017, the State of West Bengal created the , which was split from the 217 Darjeeling District and has its headquarters in the city of Kalimpong. As of June of 2017, however, the 218 newly created district was yet to be administratively independent, and some important territorial questions were still unresolved. For the purposes of this paper, we refer to the Darjeeling District as it existed prior 219 to this separation, made up of the Darjeeling Sadar, Kalimpong, Kurseong, Mirik, and Siliguri 220 subdivisions. 221 222 223 4 224 225 226 227 ● Semi-structured interviews with 27 key informants that included elected officials and 228 229 bureaucrats from local, district, and state government; leadership of local NGOs; 230 research scholars; and architects, planners, and land developers. 231 ● A household survey with 139 households representing 633 individuals (Table 2). The 232 survey included household and individual-level questions on household composition and 233 demographics, employment, housing and basic services, and experience with natural 234 hazards. Survey households were purposefully sampled to reflect the population living in 235 the geographic boundaries of our case communities, in terms of location as well as 236 housing conditions, employment, and proximity to infrastructure. 237 ● On-the-ground mapping of community assets like infrastructure (roads, bridges, 238 239 drainage), critical facilities (schools, government buildings, healthcare centers), cultural 240 landmarks (temples, churches), and natural hazard areas (i.e. past and active 241 landslides). In each community we worked with local leaders and guides to locate and 242 mark community assets using a handheld GPS unit, which we then brought into a GIS 243 software for further analysis. 244 245 Table 1: Summary of data collection methods and defined indicators 246 247 Components of MOVE Data Collection Method(s) Defined Indicator 248 Framework 249 250 Exposure Imagery analysis; Community Physical growth of buildings 251 mapping; and roadways; buildings 252 located in hazardous areas 253 Physical Dimension Imagery analysis; Community Construction materials 254 mapping; Plans review 255 256 Social Dimension Household survey; Census Age; disability; membership 257 in socially disadvantaged 258 groups 259 260 Economic Dimension Household survey; Census; Household income; variations 261 Interviews in household income; banking 262 account; broader economic 263 conditions 264 265 Environmental Dimension Interviews; Community Ecological systems 266 mapping vulnerable to environmental 267 hazards 268 Lack of Resilience or Societal Household survey; Past experience with 269 Response Capacity Interviews; Plans review hazards; understanding of 270 hazard threats; ration cards; 271 local government 272 preparedness for disaster 273 274 Risk Governance Interviews; Plans review Household insurance; 275 government-led risk reduction 276 277 278 279 5 280 281 282 283 284 and disaster mitigation 285 activities; local risk reduction 286 activities 287 288 Adaptation Plans review; Interviews Future hazards information; 289 Anticipation of environmental 290 change; Plan implementation 291 292 We supplemented these primary data with demographic information from the Indian Census and 293 with high resolution satellite imagery from the DigitalGlobe Foundation. Finally, we reviewed a 294 number of plans and government documents related to disaster and climate planning in the 295 Darjeeling District, primarily the state and district disaster management plans, the state climate 296 297 action plan, and state and district rules and regulations relating to construction and development 298 in landslide prone areas. 299 300 Table 2: Household Survey Overview 301 302 Community Households Individuals 303 Dungra 22 105 304 305 Lebong 29 121 306 307 Lower Chibbo 33 167 308 309 Pulbazar 32 141 310 311 Pedong 23 99 312 Total 139 633 313 314 315 4.0 Environmental Hazards in the Darjeeling District 316 The Darjeeling District is exposed to two major hazards: landslides and earthquakes. It is 317 located in the Eastern Himalayas, a mountainous region with some of the heaviest landslide 318 activity in the world the world (Petley 2012).10 There are hundreds of active landslides in the 319 District. While landslides occur naturally in mountainous areas, they are also triggered by a host 320 321 of anthropogenic activities like deforestation, road construction, mining, and poor management 322 of stormwater in urbanized areas. Such activities can trigger landslide hazards but also 323 destabilize slopes and create the conditions for future events (Michoud et al. 2011). Landslides 324 in the District tend to be highly localized in their incidence and impacts, but collectively have 325 caused a significant number of deaths and injuries, damage to property and infrastructure, and 326 loss of land. 327 328 329 330 331 10 The Geological Survey of India estimates that 12.6% of the country’s landmass is prone to landslides, 332 primarily in the eastern and western Himalayas (The Statesman 2016). 333 334 335 6 336 337 338 339 Landslides are highly correlated with other environmental hazards like heavy precipitation, 340 341 drought, and earthquakes, and often occur in multi-hazard or cascading hazard scenarios 342 (Casagli et al. 20). In 1968, for instance, the heaviest precipitation event in the region’s recorded 343 history triggered over 20,000 landslides, many of which are still active today (Starkel and Basu 344 2000). Other heavy rainfall events in 1899, 1950, and 1958 caused widespread damage 345 (Sankrityayana 2009). Global climate change is expected to intensify historic precipitation 346 patterns in the region to produce heavier rainfall events and longer periods of drought, both 347 associated with increased incidence of landslides (Sharma et al. 2009). 348 349 The Darjeeling District is also located entirely within India’s seismic zone IV, making it prone to 350 351 earthquake hazards that have the potential to collapse older buildings, cause cracks and 352 structural instability in newer buildings, and cause disruption to infrastructure and basic services 353 (NDMA 2016). The region has experienced several recent earthquakes that caused damage 354 and fatalities. The 2011 Sikkim earthquake, for instance, was a 6.9 magnitude event that killed 355 at least 6 people and damaged thousands of buildings and roadways. Similarly, the 2015 Nepal 356 earthquake and its aftershocks caused significant damage to buildings and infrastructure. 357 Scientists contend that the Himalayan region is overdue for an earthquake of 7.8 magnitude or 358 greater, based on historical records (e.g. Billham, Gaur & Molnar 2001). 359 360 361 5.0 Study Results: Key Factors of Vulnerability 362 In this section, we report our findings about the different factors of risk and vulnerability 363 described by the MOVE framework. 364 365 5.1 Exposure 366 Exposure is a measure of human and material assets present in hazardous areas and thereby 367 subject to potential losses (UN-ISDR 2009). In this study we seek to understand risk from 368 landslides and earthquakes, the two key natural hazards that threaten households and 369 370 communities in the Darjeeling District. We use the number of buildings in hazardous areas as 371 our indicator of exposure, because it describes physical assets potentially at risk and is a proxy 372 for human assets and economic activity. 373 374 There are no publicly available hazard maps for the Darjeeling District, or inventories of physical 375 assets like buildings or infrastructure. To measure exposure of buildings, we first created a map 376 of all existing buildings and roadways in the case study communities using high-resolution 377 satellite images (Figure 4). The West Bengal Municipal (Building) Rules, which include special 378 379 provisions for municipalities and notified areas in the hill areas, state that buildings located on 380 inclinations with a slope of 30 degrees or more and/or within 200 meters of a boundary of a 381 sinking zone are in potential danger from landslides (The Gazette 2007, pp. 64-65). We 382 used a digital elevation model (DEM) from ESRI to demarcate areas with 30 degrees or greater 383 slope and indicated active landslide areas based on our community mapping efforts. We then 384 overlaid the hazard data with our building footprint maps, to see how many buildings might be 385 exposed to landslide hazards (see table 3). Across the case communities, between 4.9% and 386 11.1% of the buildings were located in landslide hazard areas. 387 388 389 390 391 7 392 393 394 395 [INSERT TABLE 3 ABOUT HERE] 396 397 398 We were also interested in the temporal patterns of hazard exposure, to understand how the 399 trajectory of urban growth is shaping risk. The population in the hill regions11 of the Darjeeling 400 District has grown by 29% in the past two decades, from 677,796 in 1991 to 875,703 in 2011 401 (India Census 2011). To map the recent physical growth of the case study communities, we 402 analyzed two high resolution, remotely sensed images acquired approximately 10 years apart 403 (Table 3). Once the buildings and roads were digitized into shapefiles (layers) the number of 404 buildings and length of roads (km) were calculated as percentages of the study areas. This 405 analysis allowed us to calculate the change in the overall number of buildings and structures in 406 407 the study areas, the growth in the number of paved roadways, and overall trajectory of growth 408 over a 10-year period (see figure 1). 409 410 [INSERT FIGURE 4 ABOUT HERE] 411 412 Across all of our case communities, we observed significant growth. In Dungra, for instance, the 413 number of buildings grew from 2775 in 2006 to 4499 in 2017, a 62.1% increase. We saw similar 414 rates of growth in the number of buildings in Lebong (65.5%), Lower Chibo (72.1%) and 415 416 Pulbazar (73.9%), and significantly higher growth in Pedong (122.5%). The length of paved 417 roadways, a key infrastructural investment that tends to spur development, also increased 418 substantially. In Dungra, the length of paved roads increased from 12.3 km to 15.9 km, a 29.2% 419 change. We saw lower growth in paved roadways in Lebong (13.9%), but significantly higher in 420 Lower Chibo (39.4%), Pedong (67.1%), and Pulbazar (82.1%). Much of this growth is occurring 421 in hazardous areas, those with greater than 30 degrees of slope. In Dungra, for instance, 43% 422 of buildings located on steep slopes were built in the past 10 years. Similarly, a significant 423 number of buildings on steep slopes in Lebong (39%), Lower Chibo (48%), Pedong (58%), and 424 Pulbazar (58%) were built in the past decade. 425 426 427 The Darjeeling District also faces significant threat from earthquakes. While all people living in 428 the District will potentially be exposed to an earthquake hazard, those living on steep hillsides, 429 near active landslides and in unreinforced concrete buildings are especially vulnerable. We 430 asked households if they had suffered any damage to their housing structure or property from a 431 natural hazard in the past 5 years. Overall, 58% (81) reported having their house or property 432 damaged or destroyed, many by the 2011 and 2015 earthquakes. The vast majority of damage 433 was related to cracks in foundations and walls. The reports of damage varied across our survey 434 435 sample, with the most (72%) in Pulbazar and the least (31%) in Lebong. We discuss further the 436 physical dimensions of vulnerability to earthquake hazards in greater detail in section 5.3.1. 437 438 We would like to note there are several important limitations to this analysis. First, while we 439 examined the exposure of buildings in the study areas to earthquake and landslide hazards, we 440 did not look at the vulnerability of those specific assets to loss. For example, in earthquake 441 zones, the quality of the materials, structural engineering, and construction techniques are 442 443 11 The hill region of the Darjeeling District is defined as the Darjeeling, Kalimpong, Kurseong and Mirik 444 subdivisions. 445 446 447 8 448 449 450 451 important factors that help determine damage to a building and loss of assets within it at the 452 453 time and place of a hazard (e.g. Goda et al. 2015). Further research is needed to understand 454 how vulnerable buildings in the study communities are to such events. Second, our visual 455 analysis of building footprints and growth over time does not account for vertical development, 456 where building owners add additional floors to their structures rather than construct new ones. 457 This is a common strategy in the Darjeeling District, where land suitable for development is 458 scarce. Vertical development also allows owners to expand their homes or businesses when 459 they have the resources to do so. As a result, our analysis very likely underestimates the extent 460 of growth. Third, we based our analysis of buildings located in landslide hazard areas using a 461 DEM with a ground resolution of 30 meters. While this methodology is helpful for our 462 463 approximations of the number of buildings on steep slopes, more detailed analysis in the form of 464 a local landslide susceptibility zonation map is needed to determine exposure of specific 465 buildings (Kanungo et al. 2008). Finally, our mapping of active landslides is based on visual 466 tours in communities using roadways and footpaths, and is not comprehensive. Fully 467 understanding the extent of exposure would require more detailed and complete landslide 468 mapping. 469 470 Table 3: Summary of Remotely Sensed Images Used For Analysis 471 472 Community Image 1 Year Image 1 Satellite Image 2 Year Image 2 Satellite 473 474 Dungra 2006 Quickbird 2017 WorldView-2 475 476 Lebong 2005 Quickbird 2017 GeoEye-1 477 Lower Chibbo 2006 Quickbird 2016 WorldView-3 478 479 Pulbazar 2005 Quickbird 2017 GeoEye-1 480 481 Pedong 2006 Quickbird 2017 WorldView-2 482 483 484 5.3 Multi-dimensional Vulnerability 485 The MOVE framework recognizes that there are multiple and interrelated dimensions to 486 vulnerability which must be addressed within a holistic risk assessment (Birkmann et al. 2013, 487 200). Those included in our study are the physical, social, economic and ecological dimensions 488 of vulnerability.12 489 490 5.3.1 Assessment of the Physical Dimension of Vulnerability 491 The physical dimension of vulnerability describes the potential for damage to physical assets 492 493 from natural hazards (Ibid.). A complete inventory of physical assets in the case study 494 communities and their condition was beyond the scope of our study. However, we did document 495 the construction materials used in the primary living structure of the households we surveyed, 496 as an indicator of the physical vulnerability of the built environment. Construction in the 497 Darjeeling District has changed significantly over the past 3-4 decades, from a vernacular 498 499 12 We did not include the institutional and cultural dimension of vulnerability, which are difficult to define 500 and measure, especially when analyzing risk to future and uncertain events (Birkmann et al. 2013). 501 502 503 9 504 505 506 507 architecture built from bamboo, mud, and grass to buildings made primarily of concrete. While 508 509 concrete structures lend numerous advantages, like the ability to build multi-story buildings, they 510 are also more vulnerable to landslides and earthquakes because of the weight they put on 511 fragile hillsides and their potential for collapse. Heavy concrete buildings, especially those 512 located on steep hillsides, also pose a threat to buildings further down the slope, as they can 513 become part of a landslide that cascades into other structures. For the households we 514 surveyed, we observed the materials used for the walls, roof, and floor. We then categorized the 515 buildings as traditional (mud or concrete floor, bamboo walls and tin roof), mixed (mud or 516 concrete floor, walls at least partially of bamboo, and tin roof), or modern (concrete floors, walls, 517 and tin or concrete roof). We found that just 21% (29) of housing structures were traditional, 518 519 while 42% (58) were mixed and 37% modern (51). Spatially, we observed that new construction 520 was overwhelmingly modern buildings using concrete. When asked about urbanization 521 generally, our key informants describe the transition from traditional materials to concrete as a 522 hallmark of the urban transformation underway in the district. 523 524 5.3.2 Assessment of the Social Dimension of Vulnerability 525 The social dimension of vulnerability is the “propensity for human well-being to be damaged by 526 disruption to individual and collective social systems and their characteristics” (Birkmann et al. 527 528 2013, 200). We used three indicators of social vulnerability in our study: age, disability status, 529 and membership in socially disadvantaged groups. Age has been shown to be an important 530 characteristic of vulnerability (e.g. Flanagan et al. 2011) and is indicated in our study by the 531 number of elderly people in the population. When discussing the social changes that have come 532 with urbanization, our key informants described a general out-migration of younger people from 533 the District to access education and livelihood opportunities in the larger cities in the region 534 (Siliguri, ), state (Kolkata), and country. Our survey results generally supported these 535 observations; 6% of the population of West Bengal is older than 65 compared to 11% of the 536 population in our case study communities. 537 538 539 We also asked our respondents whether they were members of any historically disadvantaged 540 groups, understood in India as a member of a scheduled caste (SC), scheduled tribe (ST), or 541 other backward classes (OBC). Across our survey sample, 70.9% of individuals (449) were 542 members of these groups. Membership varied significantly by place; in Pedong, for example, 543 100% of respondents reported being a member of a disadvantaged group, compared to just 544 43% in Pulbazar. Overall, the share belonging to these groups was consistent with estimates at 545 the national and state level, where 69.3% and 67.5% of the population are members of a SC, 546 547 ST, or OBC, respectively (Government of India 2015). 548 549 Finally, we asked our respondents whether anyone in their household had a physical disability. 550 A small number, just 3%, were reported to be disabled, slightly higher than the national average 551 of 2.1% (Census of India 2011). The relative share of disabled people across case communities 552 ranged from 1% in Lower Chibbo to 6% in Dungra. 553 554 5.3.3 Assessment of the Economic Dimension of Vulnerability 555 556 557 558 559 10 560 561 562 563 The economic dimension of vulnerability is the potential loss of economic value, whether from 564 565 damage to economic assets and/or the disruption of productive capacity (Birkmann et al. 2013, 566 200). We utilized four indicators of economic vulnerability at the local scale: household income, 567 variations in household income, presence of a banking account, and broader economic 568 conditions. Household income is a key indicator of vulnerability because it describes a 569 household’s access to resources to prepare for, protect against, and recover from disaster 570 events, and is “closely coupled with other forms of capital” that are themselves indicators of 571 social vulnerability (Rufat et al. 2015, 474). The households we surveyed reported earning 572 incomes higher than the state and national average. For example, 39% of our respondents 573 earned more than 10,000 rs per month, compared to just 6% in West Bengal and 8% in India 574 575 generally. This indicates that households living in fast urbanizing communities in the Darjeeling 576 District might be better off, income-wise, than the population generally — though a 577 representative survey is needed to confirm this hypothesis. We also found that 24% of 578 respondents were low-income, earning less than 4,000 rs per month, indicating that there are 579 significant numbers of economically vulnerable households within relatively prosperous 580 communities. This finding was reflected in other survey findings, such as the broad range of 581 household living conditions we observed (see section 5.3.1). 582 583 584 The stability of household income is another important indicator of economic vulnerability, as 585 incomes may vary due to the regularity of work or the seasonal nature of earnings. Variable 586 incomes, particularly for low-income households, is a major source of insecurity with 587 implications for vulnerability. Our survey revealed that 62% of households receive varying 588 monthly income due to the irregularity of seasonal tourism and agricultural work, which 589 represents the primary economic base for the District. We also gauged household financial well- 590 being by whether households reported having a bank account, which indicates the presence of 591 savings or an ability to access various social programs requiring electronic banking. A very high 592 proportion (94%) of households in our survey reported having an account, which we view as a 593 594 positive indicator of household economic conditions. A bank account also allows households to 595 access state welfare programs, like post-disaster cash transfer schemes. 596 597 Finally, we asked our interviewees to characterize the economy of the Darjeeling District 598 generally, to understand how urbanization is affecting the nature and geography of economic 599 activities that bear directly on household and community risk. Several key themes emerged, 600 which were supported by our survey findings and by data from the Indian census. The first was 601 about the restructuring of the local economy, which has shifted away from agriculture and 602 603 towards other industries like construction, tourism and education. The decline of agriculture in 604 the region has been acute; census data from 1991-2011 reveals that the percent of main 605 workers reporting cultivation as their primary economic activity fell from 25% to 10%, and 606 agricultural labor fell from 12% to 6%. This was largely consistent with our survey findings, 607 where 14% of respondents reported agricultural employment as their main source of income. 608 During the same time period, the share of employment in non-agricultural industries in the 609 Darjeeling District rose from 63% to 82% (India Census). The decline in agricultural employment 610 in the District is a reflection of the decreasing competitiveness of smallholder farmers who 611 612 cannot compete with the price of food imported from the plains, because of the challenging hill 613 614 615 11 616 617 618 619 topography and rising costs of labor and transportation. As a result, much of the farmland in the 620 621 District now lies fallow or is being used for high-value specialty crops, like large pod cardamom, 622 which do not require a significant amount of labor outside of harvest periods. 623 624 These broader shifts in the economy of the region inform economic vulnerability in at least two 625 important ways. First, the industries that now provide a large share of local economic activity are 626 highly dependent on economic growth (construction) and attracting visitors from outside the 627 region (education and tourism), and are therefore sensitive to shocks. A major earthquake, for 628 instance, could damage local and regional infrastructure, negatively impacting the tourism and 629 educational sectors in the near and long term. This would likely cause a significant economic 630 631 downturn in the region, with additional effects on the construction industry. Second, the drop in 632 agricultural employment has been accompanied by a rise in the number of marginal workers, 633 those who are irregularly employed and work less than half of the days of regular workers 634 (Indian Census 2011). Our interviews and surveys showed that many marginal workers in the 635 Darjeeling District were previously smallholder farmers or agricultural laborers who are now 636 employed as day laborers for the construction industry and on MNNREGA-sponsored 637 infrastructure projects.13 According to the Census, the number of marginal workers in the labor 638 force rose from 2% in 1991 to 8% in 2011. Marginal workers, who are primarily low-income, 639 640 would be especially vulnerable to downturns in the local and regional economy brought about by 641 disaster because of their lack of job security and employment in industries strongly tied to 642 visitors. 643 644 5.3.4 Assessment of the Environmental Dimension of Vulnerability 645 The environmental dimension of vulnerability refers to the potential for damage by hazards to 646 “ecological and bio-physical systems” and their different functions (Birkmann et al. 2013, 201). 647 Through interviews and community mapping we found that a number of systems are vulnerable 648 to earthquake and landslide hazards. Most important, interviewees emphasized how rapid 649 650 urbanization is contributing to the degradation of natural drains, locally known as jhoras. Jhoras 651 are the natural channels through which rainwater flows from the mountaintops to the river 652 valleys below. Jhoras are mostly dry during the summer and winter months, but become fast 653 moving torrents during the monsoon season. As cities at the top of the ridgelines grow, they are 654 producing significantly more runoff from impervious surfaces and wastewater from households 655 and commercial activity. This increased amount of water flowing into the jhoras is contributing to 656 erosion, degrading the channels and creating entirely new zones of instability and associated 657 landslides. Jhoras have also become clogged with plastics and non-biodegradable solid waste 658 659 generated by the growing number of households and businesses uphill, creating further 660 impediments to water flow. Municipal waste collection is virtually non-existent in the Darjeeling 661 District, especially outside the cities. In our household survey, 72% of respondents reported that 662 they burned their trash as their primary means of disposal, while 14% threw their trash directly 663 into a jhora. The degradation of jhoras is a long-term phenomenon, with periods of instability 664 665 13 666 The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), passed in 2005, guarantees at least 100 days of employment for households volunteering to do manual, unskilled labor. 667 MGNREGA projects in the Darjeeling District are largely focused on improving physical infrastructure like 668 footpaths, drains, and irrigation systems, and typically pay higher daily wages than planting or harvesting. 669 670 671 12 672 673 674 675 followed by periods of stabilization. The failure of a jhora at any point in the drainage system 676 677 tends to lead to further degradation uphill, a creeping ecological vulnerability that will eventually 678 threaten the dense settlements and infrastructure that tend to be located on stable ridgelines. 679 680 5.4 Lack of Resilience or Societal Response Capacity 681 Lack of resilience or a society’s response capacity is determined by the “limitations in terms of 682 access to and mobilization of the resources of a community or social-ecological system” in 683 responding to a hazard (Birkmann et al. 2013, 200). We used several household and community 684 level indicators to understand these capacities and limitations in the Darjeeling District. First, we 685 asked households about their past experience and beliefs about hazards, as an indicator of their 686 687 preparedness for future disaster events. Across all households, 41% reported having suffered 688 harm to a past event, whether a death or injury (1%) or damage to their housing structure or 689 property (40%). From follow-up conversations, it was clear that many households had suffered 690 property damage from the recent earthquakes in 2011 and 2015. Beyond their personal 691 experience, we also asked survey respondents to rate the threat that landslides, earthquakes, 692 and wildfires posed to their households on a scale of 1-4, with 1 being “no threat” and 4 being a 693 “serious threat.” The results (table 4) show that a large majority of households believe that 694 landslides (74%) and earthquakes (76%) pose a significant threat (rated as a “3” or “4”) even if 695 696 they themselves have not recently suffered harm. A much smaller (19%) number believe that 697 wildfires pose a significant threat, an expected finding given that wildfire hazards are less 698 common and fewer impacts in the District. 699 700 Table 4: Rate the Threats Posed by Natural Hazards 701 Community & 1 (No threat) 2 (Somewhat of 3 (Threat) 4 (Serious 702 Hazard a threat) threat) 703 704 Dungra 705 -Landslide 3 2 4 13 706 -Earthquake 1 4 7 10 707 708 -Wildfire 12 6 2 2 709 Lebong 710 711 -Landslide 2 5 16 6 712 -Earthquake 0 9 17 3 713 -Wildfire 21 6 2 0 714 715 Lower Chibbo 716 -Landslide 1 1 11 20 717 718 -Earthquake 2 10 10 11 719 -Wildfire 17 5 7 4 720 Pulbazar 721 722 -Landslide 2 9 14 7 723 -Earthquake 1 5 15 11 724 725 726 727 13 728 729 730 731 732 -Wildfire 16 8 6 2 733 Pedong 734 -Landslide 9 3 9 2 735 736 -Earthquake 0 1 19 3 737 -Wildfire 15 7 1 0 738 739 We also asked if each household member had a ration card. A ration card is an important 740 741 document that entitles its holder to a ration of food and other basic goods by the Government of 742 India, serves as a proof of identity for other welfare schemes, and is required for joining voter 743 rolls and participating in other state activities. Ration cards are important for reducing the pre- 744 disaster vulnerability of poor households (Subbaraman et al. 2012) and have been used as a 745 tool for post-disaster response and rehabilitation (Mukherji 2010). Across our survey sample, 746 possession of a ration card was very high, with 95% of eligible households having a card. The 747 highest non-participation rate was in Lower Chibbo at just 8%. 748 749 750 Local and state government preparedness for disasters is another measure of the lack of 751 resilience or societal response capacity, because state institutions tend to be the primary 752 responder to disaster events. The West Bengal Disaster Management Department (WBDMD) is 753 the state agency tasked with all-hazards management, including pre-event risk reduction, 754 disaster response, and long-term recovery. The WBDMD maintains a district headquarter in 755 Darjeeling that undertakes key preparedness and mitigation activities like the creation of 756 disaster management plans and training for civil defense forces. 757 758 759 How do residents of fast-growing communities perceive the preparedness of local government, 760 like the WBDMD, for a major disaster? We asked households to rate local government 761 preparedness on a scale of 1-5, with 1 being “not at all prepared” and 5 being “very prepared.” 762 Overall, households were quite pessimistic, with 68% (75) rating local government 763 preparedness as a 1 or 2. Just 18% (24) rated local government as 4 (prepared) or 5 (very 764 prepared). While these responses were relatively consistent across our case communities, 765 respondents in Chibo-Pashyor and Pulbazar were particularly skeptical of local government 766 preparedness, with more than 70% of respondents giving low (1 or 2) ratings. We also asked 767 households whether they receive warnings about heavy rainfall that might trigger landslides 768 769 during the monsoon season, as an example of the type of disaster preparedness work that local 770 governments might undertake in a landslide-prone region. Across all of our survey households, 771 just 11% reported that they “frequently” or “sometimes” receive warnings about heavy rainfall. 772 Eighty-six percent (86%) reported that they ‘never’ receive such warnings, a fairly consistent 773 finding across all of the case study communities.14 774 775 776 14 Households were also pessimistic that the central government would be capable of providing 777 relief after a major disaster. When presented with the statement “The central government will 778 provide the resources my household and community needs after a major disaster,” 69% (96) of 779 respondents strongly disagreed (63) or disagreed (33). Just 12% (17) agreed and 1% (1) 780 strongly agreed. 781 782 783 14 784 785 786 787 6.0 Risk Governance 788 789 Risk is broadly understood as the probability of negative consequences (such as the loss of life, 790 disruption of livelihoods, or damage to the built environment) when environmental hazards 791 interact with vulnerable conditions (UN-ISDR 2009). Risk governance, then, is constituted of the 792 “decisions and actions” taken by formal (governments and institutions) or informal stakeholders 793 (households) to reduce, mitigate or transfer that risk (Renn 2008; Birkmann et al. 2013, 201). 794 We included two indicators of risk governance in our study. First, at a household level, we asked 795 whether respondents had insurance that might protect against disaster losses. Having 796 insurance allows exposed households to transfer risk and recover more quickly from loss, and 797 widespread insurance coverage can help communities ‘bounce back’ faster and with less 798 799 displacement (Kunreuther 1996; Adams, Hattum & English 2009). In Darjeeling, earthquake and 800 landslide hazards threaten three primary types of loss: human (injury and death), structures and 801 land. Therefore, we asked survey households whether they carried life, health, or property 802 insurance. Ideally, households exposed to hazards would carry multiple types of insurance to 803 transfer risk, but this was not the case. Out of all respondents, more than half (55%) did not 804 have any kind of insurance. Forty percent (56) of households reported having at least one 805 member with life insurance, typically through their employer, while just 3% (4) had both health 806 and life insurance. None had insurance on their housing or land. These results were relatively 807 808 consistent across the different case communities. 809 810 In the absence of private insurance, we asked several of our key informants about government 811 programs to compensate households after a disaster. They responded that it is typical for both 812 the central and state government to provide payments to families after a major disaster event. 813 After landslides killed 38 people in the Darjeeling District in 2015, the Prime Minister provided 814 Rs. 2 lakh (~$3,000) to the families of the deceased, while the state government provided Rs. 4 815 lakh to those families and an additional Rs 1.25 lakh to those injured (Mehta 2015). Our 816 interviewees had two key concerns with these ad-hoc compensation schemes, however. First, 817 818 because landslides tend to be small-scale and highly localized in their impacts, they often fall 819 below thresholds for loss that would garner state and central government attention. Second, 820 these schemes typically do not include compensation for land loss, a unique vulnerability of 821 households living in landslide areas. 822 823 Second, we examined state and district disaster management plans as evidence of the capacity 824 for, and effectiveness of, risk governance by government institutions. The India Disaster 825 Management Act (DMA) of 2005 grants significant responsibilities and authority to state and 826 827 local governments to assess and mitigate risk. As mandated by section 31 of the DMA, the state 828 of West Bengal has recently published its Disaster Management Plan 2015-2016, an update to 829 an earlier plan published in 2008 (State of West Bengal 2016). The Darjeeling District has 830 likewise published its own disaster management plan book (Office of the District Magistrate 831 2016). The state disaster management plans includes a dedicated section on the Darjeeling 832 Hills, and specifically describes the growing incidences of landslide hazards due to human 833 activity, specifically deforestation, changing land-use patterns, increased motorized traffic along 834 fragile roadways, and the “rapid expansion of settlements and towns, especially along the 835 836 roads” (43). The plan finds that “multi-storied buildings without proper planning” on steep slopes 837 838 839 15 840 841 842 843 “increase the load on already deteriorated slopes.” While these findings are more contextually 844 845 specific than in the previous iteration of the plan, they do not connect to any particular analyses 846 or places. According to several of our interviewees and a review of district and local plans and 847 policies, they also do not link to policy changes or programs that have worked to reduce or 848 safeguard development on steep slopes or sinking areas in the district. 849 850 The District plan is less detailed in its analysis. It identifies landslides and earthquakes as the 851 two primary hazards that threaten lives and economic assets in the region, but focuses largely 852 on post-disaster response. In its brief “Mitigation Strategy” section, the plan prioritizes 853 “strengthening of jhora protection wall” and “drainage improvements,” but does not expand on 854 855 these recommendations or share the state’s concern with unchecked development (Office of the 856 District Magistrate 2016 IIa). The large majority of the plan is a directory of key personnel and 857 shelter locations in case of a disaster. 858 859 Finally, we asked our key informants about the role and capacity of village councils (gram 860 panchayats) to manage environmental risk. In West Bengal and India, gram panchayats are the 861 most basic unit of rural government and have the authority to make many decisions important 862 for governing risk that is associated with urbanization, like approving development. Across our 863 864 case communities, we found that there is very weak capacity for risk governance in the 865 panchayats. This is at least partly due to a unique governing arrangement in the Darjeeling 866 District. Beginning in the early 1980’s, local political parties have demanded that the central 867 government create a separate state for the Indian Gorkhas (Nepali Indians), the predominant 868 ethnic group in the Darjeeling District (Bagchi 2012; Besky 2017). The agitation for Gorkhaland 869 turned violent in 1985-1986, which led to the creation of an administrative body called the 870 Darjeeling Gorkha Hill Council in 1988. The Hill Council was granted semi-autonomous status 871 within the state and given significant executive, financial and administrative powers in exchange 872 for an end to the statehood movement. The Hill Council was succeeded by the Gorkhaland 873 874 Territorial Administration in 2011, which assumed similar powers and responsibilities. One 875 consequence of this semi-autonomous governing arrangement has been the end of local 876 panchayat elections, which were last held in 2005. Because the gram panchayats have not 877 been as active over the past 15 years, their planning and development functions are now being 878 nominally performed by the territorial administration. Our interviewees unanimously argued that 879 the already limited capacity for governance at the local level has further eroded, and that the 880 capacity of the territorial administration to manage development at the local level is extremely 881 limited. 882 883 884 7.0 Adaptation 885 Adaptation to environmental risk is the continuous, long-term process of “learning, 886 experimentation, and change,” which shapes vulnerability and is the result of both planned and 887 spontaneous actions pre- and post-disaster (Pelling 2010; Birkmann et al. 2013). Adaptation to 888 natural hazards and climate shifts may require changes to a community’s governance 889 frameworks and/or risk management strategies (Solecki, Pelling & Garschagen 2017). 890

891 892 893 894 895 16 896 897 898 899 The MOVE framework broadly categorizes adaptation into hazard and vulnerability interventions 900 901 (Birkmann et al. 2013, 199). In terms of hazard interventions, there are numerous examples of 902 center and state-led efforts to prevent landslides in the Darjeeling District, especially along 903 roadways. Roads and road cutting are a major source of slope instability in mountainous areas. 904 The regional transportation department (the Border Roads Organization) has invested heavily in 905 drainage culverts, gabion fences, and other “gray” investments that work to limit or reduce the 906 incidence of landslides. These efforts have only been moderately successful, however, given 907 the context of the intervention and the continual cutting of new roadways, which themselves 908 trigger landslides. Away from roads, state-led interventions are less common. In some limited 909 instances, non-governmental organizations have worked to reduce landslides through low-cost 910 911 “green” mitigation measures like planting vetiver grasses, installing lightweight bamboo check 912 dams, and digging water retention pits. These interventions are relatively sporadic and limited, 913 however, and largely made without state support. 914 915 Adaptation can also occur through vulnerability intervention, whether to reduce exposure, 916 reduce susceptibility, or improve resilience. Earlier we described the lack of government action 917 to reduce exposure, whether through risk-informed land-use planning, enforcement of building 918 codes, or the provision of insurance or other risk-transfer mechanisms. Fifteen key informants 919 920 confirmed that development in the district, particularly in towns and villages, is occurring largely 921 without any guiding plans or government strategies (Rumbach 2016a). Further, we asked our 922 interviewees whether past disasters, like the 2011 and 2015 earthquakes or landslides in 2015, 923 had produced learning in governance or changed development practices. In every instance, our 924 key informants said that learning had not happened or had any notable effect on governance. 925 926 The State of West Bengal published its first climate action plan in 2013. The plan describes the 927 changing hazard context for the Darjeeling hills relative to landslide and drought hazards, but 928 includes few specific actions that would intervene to reduce those hazards or vulnerability 929 930 (Government of West Bengal 2013). Instead, it is overwhelmingly focused on the flood-prone 931 districts in the southern part of the state. Further, the portion of the plan that does focus on the 932 hill areas of the state, was written without the active participation of district residents or local civil 933 society. As on environmental NGO leader told us, “it is still a mystery how that plan came about, 934 and who was involved in its writing.” As a result, the plan has very low visibility in Darjeeling, 935 and does not seem to have had any appreciable impact on governance. 936 937 Outside of government, there are numerous civil society organizations working to reduce 938 939 disaster risk or raise awareness about hazards and climate change. These organizations are 940 largely focused on pre-disaster preparedness and post-disaster relief, however, rather than the 941 long-term management of risk. After the 2015 landslides, for example, organizations established 942 seven relief camps and provided food, clean water, and sanitary facilities (Rai 2015). They have 943 also worked to research and affect policy actions on environmental issues related to 944 urbanization and climate change, like the growing crisis over water supply in the district (e.g. 945 Drew & Rai 2016; Rao 2016). 946 947 948 8.0 Conclusion 949 950 951 17 952 953 954 955 These findings reveal the nature and dynamics of environmental risk in fast urbanizing towns 956 957 and villages in the Darjeeling District. They show communities characterized by rapid growth 958 and change, a dynamic and challenging hazard context, and low government capacity or action 959 to document, govern, or adapt to risk. Our study, while limited in important ways, is useful as a 960 heuristic, a tool to establish baseline indicators of vulnerability that can serve as a basis for 961 ongoing study and action (Birkmann et al. 2009, 207). The study also provides useful 962 hypotheses about environmental risk in small urbanizing places elsewhere in India. 963 964 Taken together, these findings show that urbanization has transformed villages and towns in the 965 Darjeeling District in fundamental ways, from the growth and transformation of the built 966 967 environment to the changing dynamics of the local and regional economies. In the context of a 968 complex and fragile mountain ecosystem, urban growth is also seemingly contributing to 969 significant environmental degradation, diminishing key ecosystem goods and services and 970 further enhancing risk. At the same time, urbanization has worked to reduce vulnerability for 971 many households, through a growing diversity and access to economic opportunities and 972 increased delivery of transportation and communications infrastructure. Yet, there is evidence 973 that the benefits of urbanization are not being equally shared; that there may be a concentration 974 of vulnerability for low-income groups, particularly those who are irregularly employed in 975 976 industries that are highly vulnerable to disruption. 977 978 Ultimately, our study shows that there is a mismatch between the pace and scale of 979 urbanization in the Darjeeling District and the capacity of central, state, and local governments 980 to manage it. As Garschagen and Lankao (2016) argue, urbanization is a trend that might be 981 leveraged for vulnerability reduction or to minimize environmental risk. Instead, growth in 982 villages and towns is proceeding largely unplanned and unchecked, greatly increasing the 983 likelihood of future disaster losses. There are many barriers to disaster and risk governance. 984 There is a critical lack of data on the district, about the nature and scale of urbanization, location 985 986 of critical infrastructure, social dynamics accompanying its urban transformation, and on the 987 environmental hazards that threaten lives, property, and economic activity. Equally important, 988 there is a critical lack of demand by government institutions for that data, or to document the 989 changing nature of risk in communities. The government’s record of low engagement around 990 issues pertaining to hazards and disasters is a clear opportunity for elected leaders, given the 991 public’s concern about hazards and lack of confidence in the capacity of the state to intervene in 992 the event of a crisis. 993 994 995 Perhaps most important, urbanization is transforming communities that are still governed as 996 rural. That means that many of the resources and capacities found in larger cities are not 997 available for managing growth and change. Policy-makers in India have begun recognizing the 998 challenges of urbanization in small and medium sized cities, but must also address the 999 urbanization trend in towns and villages. While the government has established many of the 1000 institutional tools and mechanisms necessary to manage environmental risk in these places, like 1001 the disaster management department and mandated plans and development processes, they 1002 have yet to be put to effective use in places like the Darjeeling District (see also Rumbach 1003 1004 2016a). 1005 1006 1007 18 1008 1009 1010 1011 1012 1013 Overall these findings point to a fast accumulation of risk in the built environment and economy, 1014 which may only be “revealed” after a major disaster. Some factors of vulnerability described in 1015 our study are highly specific to the Darjeeling District, especially the crisis of local governance 1016 connected to the Gorkhaland struggle and decades of conflict between the territorial 1017 administration and the state government. Others seem likely to be representative of challenges 1018 of urbanization in fast-growing towns and villages generally. The trends we observe — in 1019 physical growth, the transformation of economies and the built environment, the mismatch 1020 between governance structures and the challenges of urbanization, and the lack of resources 1021 for managing growth — are likely common in many small urbanizing places. Future research 1022 1023 might test these indicators across a broader selection of communities from different states and 1024 districts within India, to identify patterns of vulnerability and key points of divergence. 1025 1026 We finish with a brief reflection on the value of the MOVE framework to understand and assess 1027 disaster risk towns and villages. As discussed earlier, we find that the framework is an effective 1028 tool because it is comprehensive of the factors contributing to vulnerability and risk, but flexible 1029 to accommodate indicators that are contextually appropriate and measurable. Most early 1030 applications of the framework have relied on indicators that are supported by vigorous, routinely 1031 1032 collected, and publicly available data from sources like censuses or municipal utilities, however 1033 (e.g. Zaidi & Pelling 2014; Welle et al. 2014). In small urbanizing places, particularly in 1034 developing countries or regions, these routine data may not exist or be available at a scale that 1035 allows for differentiation within the geographic area of study. For many of the indicators that we 1036 identified for the Darjeeling District, we found it necessary to generate primary data. These data, 1037 which yielded unique and important findings, are both time and resource intensive to collect and 1038 analyze. To understand disaster risk and vulnerability over time, researchers will need to collect 1039 such information on an ongoing basis, a major challenge in places like the Darjeeling District. 1040 This is not unique to the MOVE approach per se, but reflective of the difficulty of 1041 1042 comprehensively studying risk in places without robust institutions and data infrastructures 1043 (Sudmeier & Jaboyedoff 2013). They point to the importance of partnerships between local 1044 governments, researchers, and community organizations to identify, collect, and analyze hazard 1045 and vulnerability data (Mercer et al. 2008). These partnerships are essential so that effective 1046 policy actions to build community resilience can be developed and implemented, not only in 1047 cities but in towns and villages as well. 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 19 1064 1065 1066 1067 Figures 1068 1069 1070 Figure 1: The MOVE Framework 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 Source: Birkmann et al. 2013 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 20 1120 1121 1122 1123 Figure 2: Location of Darjeeling District Within West Bengal 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 Sources: ESRI 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 21 1176 1177 1178 1179 Figure 3: Case Study Communities Within the Darjeeling District 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 Sources: ESRI 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 22 1232 1233 1234 1235 Figure 4: Example of Physical Change Mapping in Dungra15 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 Sources: DigitalGlobe 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279 1280 1281 1282 1283 15 Physical change maps of the case study communities are available by request from the corresponding 1284 author. 1285 1286 1287 23 1288 1289 1290 1291 References 1292 1293 1294 Adams, V., T.V. 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