Progress in Disaster Science 7 (2020) 1 0 0 1 1 0

C o nt e nts lists a v ail a bl e at S ci e n c e Dir e ct

Pr o gr ess i n Disaster Science

I:: L S b VI E R j o ur n al h o m e p a g e: w w w. e l s e v ier.co m/locate / p d i s a s

R e g ul ar arti cl e Li n ki n g I P C C A R 4 & A R S fra me works for assessing vulnerability and risk to cli mate change in the Indian Bengal Delta

Shouvik Das a, * , A mit G h os h a, S u g at a H a zr a a, Tuhin Ghosh a, Ricardo Safra de Ca mpos b, * , Sourav Sa manta a a J a d av p ur U niversity , K olk at a, I n di a b U niversity of Exeter, Exeter , U K

A R TI C L E I N F O A B S T R A C T

Arti cl e hi st or y: The ter m 'vulnerability' is used to exa mine the interlinkages bet ween hu mans a n d t h eir s o ci al a n d physical surround- R e c ei v e d 2 9 M ar c h 2 0 2 0 i n gs. T his a p pr o a c h is si mil ar t o t h e I P C C A R 4 's (2007) conceptual fra me work of v ul n er a bilit y t o cli m at e c h a n g e. T h e R e c ei v e d i n revised for m 3 0 M a y 2 0 2 0 I P C C A R 5 (2014) introduces a ne w approach and ter minology that is in line with the concept of ris k, t h us diff eri n g A c c e pt e d I J u n e 2 0 2 0 fro m the previous understanding of vulnerability as mentioned in the I P C C A R 4. This study atte mpts to link the ne w A v ail a bl e o nli n e 6 J u n e 2 0 2 0 c o n c e pt of risk ( A R5) with the previous concept of v ul n er a bilit y ( A R 4). B as e d o n I P C C A R 4 a n d A R 5 fra me works, dif- ferent bio-physical a n d socio-econo mic variables have been used for vulnerability ( A R4) and risk ( A R5) assess ments in K e y w or d s: Intergovern mental Panel o n Cli mate Change t h e 5 1 sub-districts (co m munity develop ment blocks) of the Indian p art of Ganges- Brah maputra- Meghna Delta (Indian V ul n er a bilit y B e n g al D elt a or I B O) applying principal co mponent analysis ( P C A). The results sho w that Basanti is t h e m ost v ul n er a- Ris k bl e s u b- distri ct usi n g t h e A R 4 approach, whereas is found to be the highly exposed to risk using the A R 5 a p- Adaptive capacity proach. Both sub-districts ar e spatially contiguous a n d with si milar geographic characteristics which reflects the D elt a v ali dit y of t h e I P C C fra me works of assess ment Pri n ci p al c o m p o n e nt a n al ysi s © 2020 The Authors. Published by Elsevier Lt d. T his is a n open access article under the C C B Y li c e ns e ( htt p://creativeco m mons.org/licenses/by/4.0 /).

1. Introduction econo mic sectors like w at er resources, agriculture a n d food security, h u m a n h e alt h, a n d biodiversity [8,9]. Agricultural pr o d u cti o n w orl d- In its Fifth Assess ment Report, t h e Intergovern mental Panel o n Cli- wi d e is alr e a d y b ei n g a d v er s el y affected by i n cr e a si n g t e m p er at ur e, m at e Change (IP C C) m e nti o n s t h at " C o a st al s y st e m s a n d l o w-l yi n g changes in precipitation, a n d t h e e xtr e m e events associated wit h cli- ar e a s will i n cr e a si n gl y e x p eri e n c e a d v er s e i m p a ct s s u c h as s u b m er- m at e v ari a bilit y [1 0 - 1 2 ,1 2 5 ]. F urt h er m or e, cli m at e c h a n g e h a s t h e gence, coastal flooding, a n d c o a st al er o si o n d u e t o r el ati v e s e a l e v el p ot e nti al t o r e d u c e cr o p yi el d s b y i n cr e a si n g s oil s ali nit y [ 1 3- 1 5 ]. ri s e " ( [ 1 ], p. 3 6 4). L o w-l yi n g d elt a s ar e hi g hl y s e n siti v e t o c h a n g e s Ot h er ecosyste m based livelihoods such as fisheries a n d a q u a c ult ur e i n s e a ! e v e [ 2,1 2 4 ]. At l e a st 1 0 0 million people are at v er y hi g h ris k, ar e alr e a d y u n d er m ulti pl e str e s s e s i n cl u di n g acidification, c h a n g e s li vi n g wit hi n 1 m of m e a n s e a l e v el [ 3 ]. It is e sti m at e d t h at b y 2 0 5 0, i n s e a te mperatures, extre me events, a n d s e a le vel rise a n d r el at e d e c o- > 1 million people in t hr e e m e g a deltas na mely Ganges- Brah maputra- l o gi c al c h a n g e s [1 0 ,1 6 ]. Cli m at e c h a n g e is al s o i m p a cti n g o n t h e M e g h n a d elt a ( Bangladesh a n d I n di a), M e k o n g d elt a ( Vi et n a m) a n d w at er r e s o ur c e s b y c h a n gi n g t h e fl o o d or dr o u g ht frequency, w at er Nil e d elt a ( Egypt) will be directly affected b y sea-level rise [ 4]. T he availability, a n d seasonality of w at er discharge [1 7 , 1 8 ]. Cli mate var- s urf a c e ar e a of fl o o di n g i n 3 3 d elt a s ar o u n d t h e w orl d is e sti m at e d t o i a bilit y a n d r el at e d e xtr e m e e v e nt s alr e a d y p o s e a s eri o u s t hr e at t o i n cr e a s e b y 5 0 % u n d er s e a level rise [ SJ a n d f or I n di a n Bengal Delta p e o pl e' s li v es t hr o u g h i m p a ct s o n li v eli h o o d s, s u c h as d e cr e a s e s i n (I n di a n p art of Ganges- Brah maputra- Meghna Delta or I B O) s u c h i n- cr o p pr o d u cti o n, food insecurity, a n d d e str o y e d h o m e s [1 9 ,2 0 ]. T h e cr e a s e c o ul d b e a s hi g h as 7 0 % [ 6]. It is als o e sti m at e d t h at wit h o ut h e alt h syste m is also sensitive to cli mate variability [2 1 ], a n d t h e i n- pr ot e cti o n fr o m s u b m er g e n c e a n d er o si o n, 7 2 t o 1 8 7 milli o n p e o pl e t er a cti o n of cli mate variability wit h food security c a n exacerbate mal- would be displaced b y 2 1 0 0 [ 7]. n utriti o n [2 2 ]. Cli m at e c h a n g e is li k el y t o i m p a ct t h e r ur al, p o or, Cli mate change, including cli mate variability a n d e xtr e m e e v e nt s disabled, elderly, marginalized population, which f urt h er exacerbates c a n dir e ctl y a n d i n dir e ctl y i m p a ct o n t h e e n vir o n m e nt a n d s o ci o- existing social vulnerabilities [2 3- 2 6 ]. Al o n g wit h br o a d-s c al e i nfl u- ences, local factors also aff e ct v ul n er a bilit y at t h e h o u s e h ol d l e v el [ 1 2 ]. In addition, p o p ul ati o n pr e s s ur e, l a n d us e c h a n g e a n d m or e i n-

• Corresponding authors. tensive agricultural use, a n d ur b a ni z ati o n c a n magnify risks a n d e x p o- E- m ail addresses: geo.shk@ grnail.co m, ( S. Das), r.safra-de-ca mpos @ exeter.ac.uk. s ur e t o cli m at e c h a n g e i m p a ct s [2 5 ]. These factors c a n r e s ult i n t h e ( R. S afr a d e C a m p o s). displace ment of vulnerable people, in a n i n cr e a s e d n u m b er of tr a p p e d

htt p :// d x. d oi. or g/ 1 0 .1 0 1 6 /j.pdisas.2020.100110 2 5 9 0- 0 6 1 7 / © 2 0 2 0 T h e A ut h ors. P u blis h e d b y Els e vi er Lt d. T his is a n open access article under the C C B Y li c e ns e (htt p :// creativeco m mons.org/ li c e ns es/ b y / 4. 0 /).

/ S. D a s et a L Pr o gr ess i n Disaster Science 7 ( 2 0 2 0) 1 0 0 1 1 0

p o p ul ati o n s a n d dri v e i nt er n al a n d i nt er n ati o n al f or ms of p o p ul ati o n ad ministrative, de mographic a n d socio-econo mic characteristics of t h e m o v e m e nt [2 7 ,2 8 ,2 9 ,1 2 1] . study area. Section 3 describes the data and the methodological approach P oli c y a n d s ci e ntifi c c o m m u niti e s ar e p arti c ul arl y i nt er e st e d o n of t h e st u d y. S e cti o n 4 dis c uss es r es e ar c h fi n di n gs a n d t h e fi n al s e cti o n c o n- cli m at e c h a n g e i mpacts/vulnerabilities/risks b e c a u s e of t h eir fr e- cludes the manuscript. q u e n c y, m a g nit u d e a n d persistence [1,3 0 ,31] . Vulnerability i n p arti c- ul ar is a k e y c o n c e pt f or cli m at e a n d social sciences [3 2 ,3 3 ]. T h er e ar e 2. D es c ri pti o n of t h e I n di a n B e n g al D elt a m a n y diff er e nt d efi niti o n s of v ul n er a bilit y i n t h e lit er at ur e [3 4- 3 8 ]. To quantify multi-di mensional issues using variables as proxies, previ- The Ganga- Brah maputra- Meghna ( G B M) delta is one of t h e w orl d's ous studies h a v e e m pl o y e d t h e I P C C w or ki n g definition of vulnerabil- m ost d y n a mi c d elt as, a n d it c o v ers m ost of Bangladesh and parts of W est it y ( 2 0 0 7), w hi c h is a c o m bi n ati o n of e x p o s ur e, s e n siti vit y, a n d Bengal in [4,4 1- 4 3 ]. The Indian part of the Ganges- Brah maputra- a d a pti v e c a p a cit y [ 1 2, 3 9 ]. T h e Fifth Assess ment Report C A R S) of t h e Meghna delta is kno wn as the Indian Bengal Delta (I B D) [4 4 ,4 5 ]. T h e I P C C i ntr o d u c e s t h e c o n c e pt of ris k. T his a p pr o a c h is diff er e nt fr o m I B D, a natural ha bitat of the Royal Bengal Tiger, presents a co mplex ecosys- t h e c o n c e pt of v ul n er a bilit y a s e x pr e s s e d i n t h e IPCC AR4 [ 4 0 ]. t e m d e v el o p e d b y a n i ntri c at e s yst e m of ti d al ri v ers, m u dfl ats, a n d s alt-t ol- H e n c e, t h er e is li mit e d u n d er st a n di n g a n d e m piri c al w or k o n ris k as- erant mangrove forests [ 45]. The socio-econo mic profile of the I B O is n o n- sess ment follo wing the IP C C A R S a p pr o a c h. unifor m due t o its g e o gr a p hi c al s etti n gs a n d p o p ul ati o n c o m p ositi o n, a c c ess T h e m ai n p ur p o s e of t hi s st u d y is t o li n k t h e n e w c o n c e pt of ri s k to differe nt sets of r es o ur c es, a n d u n a v ail a bilit y of s uffi ci e nt fr es h w at er. C A R S) wit h t h e e xi sti n g c o n c e pt of v ul n er a bilit y ( A R 4) u si n g t h e The study area is 14,054 sq. k m and co mprises of 51 sub-districts within b a si c u n d erl yi n g a s s u m pti o n s pr e s e nt i n b ot h IP C C fra me works. This t wo large districts -North 24 Parganas and (Fi g. 1 ). st u d y a s s e s s e s t h e v ul n er a bilit y ( A R 4) a n d risk ( A RS) at t h e l o c al According to the 2011 census, the total p o p ul ati o n of I B O is 1 8. 1 7 level (sub-district) to identify cli m at e c h a n g e i m p a ct h ot s p ot s t o pr o- milli o n, of w hi c h 9. 2 9 milli o n (51 %) ar e m al e a n d 8. 8 8 million ( 49 %) vi d e i n p ut for successful a d a pt ati o n o pti o n s a n d miti g ati o n m e a s ur e s. ar e f e m al e [4 6 ,1 2 2 ]. T h e p o p ul ati o n d e n sit y i n 2 0 1 1 w a s 1 2 9 3 p er- T his st u d y also tries t o i d e ntif y t h e r o b u st a p pr o a c h for assessing t h e s o ns p er s q. k m a n d t h e d e c a d al gr o wt h r at e b et w e e n 2 0 0 1 a n d 2 0 1 1 vulnerability / ri s k t o cli m at e c h a n g e. was 15 %. North 2 4 Parganas is the most p o p ul at e d di stri ct wit h a p o p- T his m a n us cri pt is or g a nis e d as f oll o ws: t h e first s e cti o n pr o vi d es a n i n- ul ati o n of 1 0 milli o n a n d t h e p o p ul ati o n d e n sit y of 2 4 4 5 p er s o n s p er troduction to cli mate change, lo w-lying areas and vulnerability, and the s q. k m. T h e t ot al p o p ul ati o n of S o ut h 2 4 P ar g a n a s is 8. 1 6 milli o n gaps in literature t h at are addressed b y this study. Section 2 provides a n d gr o wi n g at a n e sti m at e d r at e of 1. 8 2 % p er y e ar, w hi c h is hi g h er

Fi g. 1. T he study area map of I n di a n B e n g al D elt a.

2 / S. D a s et a L Pr o gr ess i n Disaster Science 7 ( 2 0 2 0) 1 0 0 1 1 0

t h a n t h at of t h e st at e of ( 1. 3 8 %) a n d In di a ( 1. 7 6 %) b e- 0. 5 9 milli o n h a ( 4 2 % of t otal area) [ 4 9 ]. The average size ofl a n d h ol d- t w e e n 2 0 0 1 a n d 2 0 1 1. C e ns us d at a ( 2 0 1 1) s h o w s t h at t h e s e x r ati o i n gs is 0. 6 1 ha. Overall soil conditions ar e favourable for agricultural i n I B O is 9 5 5 f e m al e s p er 1 0 0 0 of m al e s w h er e a s t h e s e x r ati o i n acti vities, b ut t h e sali ne soil of S o ut h 2 4 P ar g a n a s di stri ct is c o n si d- W e st B e n g al is 9 5 0 a n d I n di a is 9 4 0 . T h e cr u d e lit er a c y r at e is er e d unecono mical [5 0 ]. The presence of several rivers, creeks a n d c a- 7 2. 3 1 %, a n d t h e male literacy r at e ( 7 6. 3 9 %) is hi g h er t h a n the fe male nals is beneficial to t h e cr o p pi n g p att er n of this delta. T he m aj or cr o p lit er a c y ( 6 8. 0 4 %). T h e p er c e nt a g e of scheduled caste ( S C) a n d s c h e d- gr o w n i n t h e d elt a is ri c e. T h e yi el d r at e of ri c e is 2 6 9 8 k g p er h e ct ar e uled tribe (S T) p o p ul ati o n t o t ot al p o p ul ati o n is 2 7. 4 9. This percent- i n N ort h 2 4 P ar g a n a s a n d 2 3 2 2 k g p er h e ct ar e i n S o ut h 2 4 P ar g a n a s a g e is > 5 0 % i n s e v er al s u b- di stri ct s li k e Hi n g al g a nj, B a s a nti, [ 4 9 ]. Gr a d u al i n cr e a s e i n s oil s ali nit y f or c e d cr o p far mers to choose Sandeshkhali-I & II. I B O h as t h e hi g h e st pr o p orti o n ( 6 6 .5 0 %) of p o p- s alt t ol er a nt cropping practices instead of traditional cultivation prac- ul ati o n a g e d 1 5- 6 4 y e ar s w hi c h is r efl e ct e d i n t h e a g e d e p e n d e n c y ti c es. Al o n g wit h agriculture, rural people practice multiple secondary r ati o i. e. 0. 5 1, w hi c h i n di c at e s t h e w or ki n g- a g e p o p ul ati o n f a c e a livelihood activities such as aquaculture, honey collection, b o at m ai n- m o d er at e b ur d e n i n s u p p orti n g t h e n o n- w or ki n g a g e p o p ul ati o n. t e n a n c e a n d n et m a ki n g [5 1 ] . Total workforce in I B O is 6. 5 4 milli o n, a n d the male work participa- The Indian Bengal Delta is hi g hl y sensitive to cli mate c h a n g e i m- ti o n r at e is 5 7 %, whereas the fe male participation is only 1 4 %. F e m al e p a ct s i n cl u di n g s e a level rise, coastal erosion, salinization, fr e q u e nt w or k er s ar e mainly engaged in household industries b ot h i n r ur al a n d c y cl o n es, a n d fl o o ds [ 4 5 ,5 2 ] (Fi g. 2 ). I n t h e p a st t hr e e d e c a d e s, t h e ur b a n ar e as. Relative Mean Sea Level ( R MSL) has risen to t h e or d er of 8 m m [5 3 ] I n I B O, 5 7 % of t h e t ot al p o p ul ati o n li v e i n r ur al ar e a s [4 6 ,1 2 2 ]. t o 1 2 m m [5 4 ] p er y e ar i n the Bay of B e n g al. T h e r at e is significantly T h e y ar e m ai nl y d e p e n d e nt o n a gri c ult ur e, w or ki n g as c ulti v at or s hi g h er t h a n e arli er o b s er v ati o n s a n d al s o c o n si d er a bl y hi g h er t h a n a n d a gri c ult ur al l a b o ur er s. Ar o u n d 3 2 % of I B O i n h a bit a nt s ar e e x- t h e gl o b al m e a n ( 3. 2 m m p er y e ar). Wit h a c c el er at e d s e a l e v el ri s e tr e m el y p o or [4 7 ,4 8 ]. T h e t ot al cr o p p e d ar e a d uri n g 2 0 1 0- 1 1 w a s a n d s u b s e q u e nt c h a n g e s i n t h e h y dr o d y n a mi c r e gi m e, t h e I B O f a c es

s s ·o· o" E ""u Ill I) 1 o _s 1 0 2 0 3 0 ::. •-- = =--- = = ==ii k m "'? ~ .!! ( L e g e n d < - N o rt h 2 4 P ar g a n a s S o ut h 2 4 P ar g a n a s - W at er b o d y .... ""u - M a n gr o v e Ill... \ I-

z 0 b N N

B A Y

Fi g. 2. C y cl o n e tr a c ks o n I B O i n t h e l ast 1 0- 1 5 y e ars.

3 / S. D a s et a L Pr o gr ess i n Disaster Science 7 ( 2 0 2 0) 1 0 0 1 1 0 s e v er e l a n d loss. A mong 1 0 2 islands, 3 islands, viz. L o h a c h or a a n d [65]. According to I P C C A R4, vulnerability is a function of t hr e e f a c- S u p ari b h a n g a a n d N e w M o or e ( P ur b a s h a) [5 4 ,5 5 ] ar e alr e a d y s u b- t ors w hi c h ar e exposure, sensitivity, a n d a d a pti v e c a p a cit y [1 2 ,6 5 ]. m er g e d i n t h e w e st er n r e gi o n of t h e delta. Severe c o a st al er o si o n is Exposure in A R 4 is t h e m a g nit u d e a n d d ur ati o n of t h e cli mate-related being observed in several ot h er islands- Ghora mara, Sagar, Mousuni, stress s uc h as a dr o u g ht or change in precipitation, w h er e a s sensitivity J a m b u d wi p, N a m k h a n a, G-Plot, Dhanchi, Bulcheri, D uli b h a s a ni, is t h e d e gr e e t o w hi c h t h e s y st e m is aff e ct e d b y t h e cli m at e r el at e d Dalhousie, Bhangduni islands a n d coastal villages [5 6- 5 9 ]. T h e e ntir e str e s s or e xtr e m e e v e nt s . A d a pti v e c a p a cit y in A R4 refers to t h e p o p ul ati o n s of t h e vill a g e s of Khasi mara, B ai s b a n p ar a, K h a si m ar a syste m's ability to withstand or recover fro m the extre me events/da m- Char, Laksh mi N ar a y a n p ur a n d B a g h p ar a of G h or a m ar a i sl a n d h a d a g e [1 2 ,4 0 ,6 5 ,6 6 ]. to leave its usual place of r esi d e n c e a n d seek refuge in n e ar b y isl a n ds such as Sagar [2 8 ,5 6 ,60,61 ]. Recent st u di e s s u g g e st t h at in Mousuni V = J ( E, S, AC ) i sl a n d 2 2 4 f a mili es ar e likely to be displaced wit hi n t h e n e xt 5 y e ar s d u e t o t h e i m p a cts of coastal erosion [5 9 ]. T h e B a y of B e n g al n or m all y w h er e, V = Vulnerability, E = Exposure, S = Sensitivity a n d A C = registers 7 % of the major cyclones of the world [62] a n d the frequency A d a pti v e C a p a cit y. of high to very high intensity cyclones has increased b et w e e n 2 0 % t o It h as t o b e n ot e d t h at t h e a d a pti v e c a p a cit y of a syste m deter mines the 2 6 % i n t h e l a st 1 2 0 y e ars [6 3 ,6 4 ]. v ul n er a bilit y b y m o d ul ati n g e x p os ur e a n d s e nsiti vit y [6 7 ]. I nt e n s e c y cl o n e s s u c h a s Ail a ( 2 0 0 9), B ul b ul ( 2 0 1 9), A m p h a n The Fifth Assess ment Report of t h e I P C C ( A R5) introduces a ne w ap- ( 2 0 2 0) as well as s e v er e fl o o ds h a v e c a u s e d m a s si v e d e v a st ati o n t o proach and ter minology. This approach is si milar to the concept of coastal regions. For exa mple, in May 2 0 0 9, c y cl o n e Ail a hit as m a n y disaster risk, which differs fro m the current understanding of vulnerability as 3 4 s u b- di stri ct s, 1 6 ur b a n l o c al b o di e s, a n d 3 7 0 4 vill a g e s i n t h e as m e nti o n e d i n t h e I P C C A R 4 [ 40 ]. A c c or di n g t o I P C C A R 5, ris k is 't h e po- I B O d a m a gi n g 3 8 0 t h o u s a n d h o u s e s a n d i m p a cti n g al m o st 2. 4 5 mil- tential for consequences where so mething of v al u e is at stake and where the li o n p e o pl e a n d 0. 1 2 milli o n h e ct ar e s of a gri c ult ur al ar e a [4 7 ]. C y- o ut c o m e is u n c ert ai n, r e c o g ni zi n g t h e di v ersit y of v al u es. It is often repre- cl o n e A m p h a n, w hi c h m a d e l a n df all o n 2 0t h M a y of 2 0 2 0, h a s s e nt e d as t h e pr o b a bilit y of occurrence of hazardous events or trends mul- b arr ell e d t hr o u g h t h e I B O at wi n d s p e e d s of u p t o 1 9 0 k m p h a n d ti pli e d b y t h e i m p a cts if t h es e e v e nts or trends occur' ( [ 1 ], p. 1048). The h e a v y r ai n s, d e str o y e d t h e ri v er e m b a n k m e nt a cr o s s t h e S u n d ar b a n t er m 'ris k' is us e d pri m aril y t o r ef er t o t h e ris ks of cli mate-change i mpacts which has led to salt w at er e nt eri n g t h e land (Fig . 2). Ho me d wellings [2 2 ] (Fi g. 3 ). a n d infrastructure rebuilt aft er cyclone Aila have b e e n l ost d u e t o t h e m o st r e c e nt cyclone. The ar e a s w or st hit b y A m p h a n ar e Ghora mara, K a k d wi p, N a m k h a n a, S a g ar a n d Patharprati ma . I n t h e aft er m at h of R = J ( H , E, V ) t h e c y cl o n e, it is e sti m at e d t h at > 0. 2 million far mers could be severely aff e ct e d, p ot e nti all y triggering a w a v e of h u m a n mi gr ati o n fr o m t h e w h er e, R = Ris k, H = H a z ar d, E = Exposure, and V = V ul n er a bilit y. I B O. The ter ms 'exposure' a n d 'vulnerability' ar e c o m m o n b ut us e d dif- ferently in I P C C A R 4 a n d A R 5. According to I P C C A R5, exposure is 't h e 3. Vulnerability and risk: li n ki ng n e w c o n c e pts pr e s e n c e of people, livelihoods, species or ecosyste ms, environ mental functions, services, a n d resources, infrastructure, or econo mic, social, T h e I nt er g o v er n m e nt al P a n el o n Cli m at e C h a n g e (IP C C) defines or c ult ur al a s s et s i n pl a c e s a n d s etti n g s t h at c o ul d b e a d v er s el y af- v ul n er a bilit y i n t h e F o urt h Assess ment R e p ort ( A R 4) as 't h e d e gr e e f e ct e d' ( [ 1 ], p. 1 0 4 8) a n d vulnerability is 't h e propensity or pr e dis p o- to which geophysical, biological a n d socio-econo mic syste ms ar e s us- siti o n t o b e a d v er s el y aff e ct e d ' ([1 ], p. 1 0 4 8). V ul n er a bilit y i n A R 5 c e pti bl e t o, a n d u n a bl e t o c o p e wit h, a d v er s e i m p a ct s of cli m at e includes the concepts of sensitivity (susceptibility to har m) a n d a d a p- c h a n g e, i n cl u di n g cli m at e v ari a bilit y a n d e xtr e m e s' ([ 3 1 ], p. 7 8 3). tive capacity. H a z ar d is a n e w t er m in A R5, defined as 't h e p ot e nti al T h e t er m ' v ul n er a bilit y' i n A R 4 is used to refer to t h e v ul n er a bl e s ys- occurrence of a n at ur al or h u m a n-i n d u c e d p h ysi c al e v e nt or tr e n d or t e m itself (e.g. lo w-lying islands or c oastal cities); a n d t h e i m p a ct t o p h ysi c al i m p a ct t h at may cause loss of lif e, i nj ur y, or ot h er h e alt h i m- t hi s s y st e m (e.g. flooding of c o a st al citi e s a n d a gri c ult ur al l a n d s) p a ct s, a s w ell as d a m a g e a n d l oss t o pr o p ert y , i nfr a str u ct ur e, j

Sociaoecono mic l/ 1 N at ur al P at h w a y s 0n V ari a bi lit y ; 8 0 Adaptation and o m Miti g ati o n n n _ _ _A cti _ o n _ ..., l/lm O Z Anthropogen ic Cli m a t e C h a n g e = -_G _ o v er_ n _a n c _ e ...l _ l/l ~ n

E MI S SI O N S and Land use Change

Fi g. 3. T h e contributing factors of ris k. ( Adapted fro m l P C C ARS , 2 0 1 4 , P.1 0 4 6.)

4 / S. D a s et a L Pr o gr ess i n Disaster Science 7 ( 2 0 2 0) 1 0 0 1 1 O S e le c ti o n of V ar ia bl es i Te st t he A pp mpriatene; s of F M ulti o olli n Mri t y Principal C o mponent Sa mpling Adequacy A n alys is I d e ntit y M atri x

I n put - C orr el ati o n M atri x S e n siti vit y E x p o s ur e ---+- ----I E xtr a cti o n M et h o d - Principal C o mponent A nalysis A d a pti v e C a p a cit y V ul n er a bilit y R ot ati o n - Vari m a x wit h K ais er N or m ali z at io n Ei g e n v al u e > 1

IP C C Contributing Fa ctors u s i ng E q. 1 V ul n er a bilit y i Nor maliz ation u s i ng E q. 2 V uln erability (A R4 ) i Ri s k( A R S ) Fi g. 4. General logic of t wo different approaches (I P C C A R 4 & A R S). usi n g E q . 5 - --- In d e x ---• usi n g E q . 6

Fi g. 5. Methodological fra me work of vulnerability ( A R4) a n d risk ( A RS) assess ments. li v eli h o o d s, s er vi c e pr o vi si o n, e c o s y st e m s, a n d e n vir o n m e nt al r e- s o ur c e s'([ l ], p. 1 0 4 8). I n b ot h IP C C's A R4 a n d A R 5 working definitions it is cl e ar t h at v ul- nerability a n d risk include a n external ele ment, which is cli mate-related p h y si c al a n d socio-econo mic v ari a bl e s h a v e b e e n s ele ct e d u n d er t e n stress (e.g. extre mes weather events) represented by the "exposure" ac- major co mponents (concepts) -cli mate variability, natural hazards, de- c or di n g t o A R 4 a n d " h a z ar d " i n A R 5, as w ell as a n i nt er n al el e m e nt, mographic profile, socio-econo mic status, livelihood activity, h u m a n r e- which co mprises "sensitivity" a n d "adaptive capacity" i n A R 4 a n d " e x- source capacity, econo mic security, infrastructure, basic facilities a n d p os ur e " a n d "vulnerability" in A R 5 . The internal ele ment describes the a gri c ult ur al livelihood str at e gi e s (T a bl e s 1 & 2 ). T h e first t w o m aj or m o d er ati n g attri b ut e s (socio-econo mic, physical or e n vir o n m e nt al) of co mponents are related to the external el e m e nt w hi c h i n t h e A R 4 is c at- t h e s yst e m. It c a n b e s ai d t h at t h e t er mi n ol o g y e m pl o y e d i n b ot h t h e egorized as exposure, and as ' h a z ar d' i n t h e A R 5. Cli m at e v ari a bilit y h as I P C C assess ment reports is diff er e nt b ut the basic underlying assu mp- been measured by the average st a n d ar d d e vi ati o n of t h e m o nt hl y - m a x- tions follo w a si milar logic (Fig. 4 ). i mu m and mini mu m te mperatures a n d precipitation over last 3 0 y e ars. Frequent cyclones, floods, coastal erosion are the m aj or environ mental 4. Methodology and materials str ess ors i n I B D therefore these h a v e been used to m e a s ur e t h e s e c o n d m aj or c o m p o n e nt n a m el y n at ur al h a z ar d s. T h e d at a s o ur c e s of cli- T h e c o n str u cti o n of a n i n d e x b a s e d o n specific sets of v ari a bl e s is m at e-r el at e d str ess or e xtr e m e s e v e nt s ar e National Re mote Sensing c o m m o nl y u s e d i n q u a ntit ati v e a p pr o a c h e s t o ass ess v ul n er a bilit y C e ntr e (2003-2014), Indian Meteorological Depart ment ( 1 9 5 1- 2 0 1 4), [3 2 ,3 4 ]. Previous st u di e s h a v e e m pl o y e d a wi d e r a n g e of m et h o d s United States Geological Survey (2001 & 2 0 1 1). b as e d o n I P C C contributing factors -exposure, sensitivity, a n d a d a pti v e I n a d diti o n, ei g ht m aj or c o m p o n e nt s s h o w a n i nt er n al el e m e nt, c a p a cit y t o q u a ntit ati v el y ass ess v ul n er a bilit y at diff er e nt s c al es w hi c h c o m pri s e s s e n siti vit y a n d a d a pti v e c a p a cit y i n A R 4 a n d e x p o- [ 1 2, 2 6 ,3 9 ,4 0 ,6 6 ,6 8- 7 1 ]. In this study, v ul n er a bilit y a n d risk indexes s ur e a n d v ul n er a bilit y i n A R5. In ter ms of socio-econo mic r e s o ur c e s have been constructed at t h e s u b- distri ct l e v el usi n g t h e d at a r e d u cti o n ( e. g., l o w-i n c o m e gr o u p s, r ur al p o p ul ati o n, illit er at e s a n d f e m al e s) technique - ' Principal Co mponents Analysis' (P C A) using the Statistical a n d physical mobility (e.g., children, aged, a n d disabled persons) peo- Package for the Social Sciences (SPSS) soft ware version 2 2 (Fi g . 5). A pl e w h o ar e di s a d v a nt a g e d ar e oft e n c o n si d er e d t o b e t h e m o st v ul n er- si milar approach has been used i n previous studies on vulnerability as- a bl e t o cli m at e c h a n g e i m p a ct s. F e m al e s h a v e m or e c h all e n g e s t o s ess m e nt [3 7 ,7 1- 8 2 ]. P C A is the most co m mon statistical m et h o d us e d overco me fro m the disasters c o m p ar e d t o m al es d u e to fa mily care re- to extract a s maller a n d more coherent set of uncorrelated (orthogonal) s p o n si biliti e s, s e ct or- s p e cifi c e m pl o y m e nt, a n d l o w er w a g e s [3 7 ] . co mponents fro m a large n u m b er of variables [83 ]. First co mponent ac- R ur al p o p ul ati o n ar e m or e v ul n er a bl e d u e t o l o w i n c o m es a n d gr e at er counts for the largest possible a m o u nt of v ari ati o n i n the original vari- d e p e n d e n c y o n n at ur al resources [26]. People w h o s e m ai n livelihood a bl es, a n d e a c h f oll o wi n g c o m p o n e nt a c c o u nt s f or as m u c h of t h e is d e p e n d e nt o n a gri c ult ur e ar e s e v er el y i m p a ct e d b y cli m at e v ari a bil- re maining variability as possible [8 0 ,8 3 ,8 4 ]. it y a n d n at ur al h a z ar d s [3 7 ]. It is n ot e d t h at a fe w variables like pop- B as e d o n t h e I P C C A R 4 a n d A R 5 w or ki n g d efi niti o n s, t h e m et h o d- ul ati o n d e n sit y, r ur al p o p ul ati o n a n d a gri c ult ur al d e p e n d e nt s h a v e ological fra me works of v u ln er a bilit y a n d ri s k h a v e b e e n d e si g n e d f or b e e n c o n si d er e d as e x p o s ur e i n A R 5 a n d as s e n siti vit y i n A R 4. M ar- t his st u d y. T h e t er m ' v ul n er a bilit y' i n A R 5 h as b e e n divided into 'sen- gi n al w or k er s h a v e w or k f or < 6 m o nt h s i n a y e ar, ar e e c o n o mi c all y siti vit y ' a n d ' a d a pti v e c a p a cit y' for the si mplification of t h e m et h o d o- di s a d v a nt a g e d p e o pl e [9 8 ]. P o v ert y is a v ari a bl e t h at c a pt ur e s l a c k lo gi c al fr a m e w or k of ris k. I n ot h er w or d s, ri s k is t h e f u n cti o n of f o ur of a c c e s s t o r e s o ur c e s a n d i n c o m e o p p ort u niti e s [9 7 ]. O n t h e ot h er f a ct ors w hi c h ar e h a z ar d ( H), e x p o s ur e ( E), s e n siti vit y ( S) a n d a d a p- h a n d, lit er at e p e o pl e w h o ar e w or ki n g i n t h e f or m al s e ct or h a v e a c c ess tive capacity ( A C). to early- warning i nf or m ati o n a n d c a n pl a n i n a d v a n c e h o w to respond t o cli m at e r el at e d str e s s or e xtr e m e e v e nt s [3 7 ,1 0 2 ,1 1 3 ]. A c c ess t o 4. 1. Selecti o n of v ari a bles s a nit ati o n, s af e dri n ki n g w at er, el e ctri cit y, a n d i nfr a str u ct ur e s s u c h as r o a d d e n sit y, h e alt h a n d e d u c ati o n al i n stit ut e s d et er mi n e t h e a bil- Based on a co mprehensive revie w of t h e lit er at ur e a n d available sec- it y of t h e s y st e m t o r e s p o n d t o a n d r e c o v er fr o m t h e i m p a ct s of e x- o n d ar y d at a s ets, 3 3 t h e or eti c all y i m p ort a nt a n d p oli c y-r el e v a nt bi o- tr e m e e v e nt s [1 0 9 ] . T h e socio-econo mic d at a s et s u s e d i n t hi s st u d y

5 / S. D a s et a L Pr o gr ess i n Disaster Science 7 ( 2 0 2 0) 1 0 0 1 1 O

T a bl e 1 A detailed description of the selected variables for vulnerability and risk assess ments.

S L no. Concepts Variables E x pl a n ati o n of v ari a bl es I P C C References contributing f a ct ors Cli m at e M a xi m u m Standard deviation of t he a v e r age daily m axi mu m te mper at u re by month last 3 0 y e ar is a v er a g e d El [1 2 ,8 5 ] variability te mperature 2 Mi ni m u m Standard deviation of the average daily mini mu m te mperature by month last 3 0 year is averaged E 2 [1 2 ,8 5 ] te mperature 3 A v erage Standard deviation of t h e a v e r age monthl y precipitation last 3 0 year is averaged E 3 [1 2 ,8 5 ,8 6 ] preci pitatio n 4 Natural Flood Percentage of area inundated with high return period flood during last 1 0 y e ars E 4 , Hl [1 2 ,3 9 ,8 6- 9 1 ] 5 h a z a r ds C y cl o n e Interpolated (ker nel density esti mation) wind speed ( m / s) of tropical cyclone over la st six decades E 5 , H 2 [1 2 ,9 2 ] 6 C o ast al er os io n R at e of coastal erosion (sq. k m / y ear) E 6 , H 3 [9 2 ,9 3 ] 7 Demographic Population Number of p e o pl e p er square kilo metre Sl, E Xl [7 3 ,9 4 ] pr ofil e d e nsit y 8 A v er a g e A v er a g e n u m b er of p e o pl e p er h o u s eh ol d S 2 , S Sl [3 7 ,9 5 ] h o u s e h o l d siz e 9 F e m al e P er c e nt a g e of fe male population to total population S 3, S S 2 [3 7 ,3 9 ,7 3 ] population 1 0 Child population Percentage of population und er 7 years age ( 0- 6 a g e gro up) to total population S 4, S S 3 [3 7 ,3 9 ] 1 1 Socio-econo mic S o ci all y P er c e n ta g e of scheduled caste a n d scheduled tribe population to total population S 5, S S 4 [5 9 ] st at us disadvantaged p e o pl e 1 2 F o o d i ns e c urit y Percentage of households that c a n man age less than one or o n e sq u are m eal a day for the major p art S 6 , S S 5 [3 9 ,8 5 ] of t h e y e ar 1 3 Land holding Percentage of households without land holding S 7, S S 6 [5 9 ] 1 4 P o v ert y Percentage of population living belo w the poverty line (BP L) S 8, S S 7 [2 6 ,3 7 ,9 6 ,9 7 ] 1 5 Rural population Percentage of rural population to total population S 9, E X 2 [2 6 ,3 7 ,7 7 ] 1 6 Livelihood Agricultural Percentage of cultivators and agricultural labours (depende nt o n agriculture) to total working S10, E X 3 [3 7 ,8 5 ] a cti v ity dependency population 1 7 Marginal workers Percentage of marginal workers (not w or k f or t h e m aj or p art of the referen c e p e ri o d i. e. < 6 m o nt hs) Sll , S S 8 [9 8 ] to total working population 1 8 Non- workers P er ce nt a g e of total non- workers (not work at all i n any econo mically productive activ ity - students, Sl 2, S S 9 [7 3 ,9 9 ,1 0 0 ] (dependents) persons engaged in household duties, depend ents) to total p o p ul a ti o n 1 9 Human Literacy rate Percentage of literates to the total population age 7 years a n d a b o v e Al, A Cl [1 0 1 ,1 0 2 ] 2 0 re s o ur c e W o r k Percentage of total workers (main and m ar gi nal) to total population A 2, A C 2 [1 0 3 ] c a p a c ity participation rate 2 1 E c o n o mi c S al ari e d j o b Percentage of population working in organised/for mal sector (regular salaried e mployed) A 3, A C 3 [1 0 4 ] 22 security H o m e o w n e r s hi p Percentage of households have their o w n h o m e A 4 , A C 4 [3 7 ,8 2 ] 2 3 Hous ehold assets Percentage of households have household assets A 5 , A C 5 [2 6 ,5 9 ,9 0 ,1 0 5 ] 24 Infrastructure P u c c a h o u s e s Percentage of households living in Pucca houses (per manent struc t ure) A 6, A C 6 [5 9 ] 2 5 Health care Number of health care centres A 7, A C 7 [1 0 6 ] c e ntr e s 2 6 E d u c ati o n al N u m b er of educational institutes A 8, A C 8 [ 1 0 7 ] i nstit utes 2 7 R o a d d e n si t y L e n gt h of roads (in k m) per sq. k m A 9, A C 9 [1 0 8 ] 2 8 Basic facilities Sanitation Perce nt a g e of households have sanitation facility within pre mises A 1 0, A C 1 0 [1 0 9 ] 2 9 Electricity Percentage of households have electricity connection All, A Cll [9 0 ,1 0 9 ] 3 0 Safe drinking Perce nt a g e of households reported tap water fro m treated source as m ain source of drinking wat er Al 2, A C 1 2 [1 1 0 ] w at e r 3 1 A gr o Ii v eli h o o d Cr o ps N u m b er of crops gro wn in a year A13, AC13 [1 2 ] 32 strategies Irrigation Percentage of irrigated area to total cul tivat e d ar e a A 1 4, A C 1 4 [1 1 1 ] 3 3 F e rtili z e r N u m b er of f ertili z er d e p ots A 1 5, A C 1 5 [1 1 2 ] I P C C A R 4 : E - ex p os ur e , S - s e nsiti vit y, A - a d a pti v e c a p a cit y; I P C C ARS : H -hazard, E X -exposure, S S - s e nsiti vit y; A C -adaptive capacity. All t h e v ari a bl es ar e s h o wi n g t he p o siti ve ( +) f u n cti o n al r el ati o ns hi p wit h I P C C contributing factors which means the higher the value, higher the hazard/ exposure / se nsi- tivity/adaptive capacity. are available in Census of India (2001 & 2011), Bureau of Applied Eco- variables have been considered by excluding the c orr el at e d v ari a bl e s n o mi cs & Statistics (2011), United Nations Develop ment Progra m me (Tab le 3). The issue of m ulti- c olli n e arit y c a n als o b e i d e ntifi e d b y -I n di a ( 2 0 0 9 & 2 0 1 0). l o o ki n g at t h e d et er mi n a nt of t h e R- m atri x CI RI), w hi c h s h o ul d b e > 0. 0 0 0 0 1 [8 4 ]. 4. 2. Testi n g t he appropriateness of pri nci p al c o m p o ne nt a n alysis In the present study, the sa mple size is 51 sub-districts of IBO. T h e subjects-to-variables (S T V) ratio is different for the different contrib- All variables are m e a s ur e d at the interval-level. The i nitial analysis uti n g f a ct ors i n di c at e d i n t h e I P C C fr a m e w or k b ut it is n ot l o w er r e v e al e d t h at s o m e of t h e socio-econo mic variables ar e highly corre- than 3 (3:1 ratio) [1 1 4 ]. Histogra m , box plot a n d descriptive statistics l at e d wit h e a c h ot h er. F or e x a m pl e, 'a gri c ult ur al d e p e n d e n c y' is have been used to identify t h e outliers in S P S S soft ware. The Kaiser- hi g hl y c orr el at e d wit h 'landholding', ' P u c c a h o u s e s' is c orr el at e d M e y er- Ol ki n ( K M O) t e st [1 1 5 ] has been used to measure the sa mpling wit h ' el e ctri cit y' a n d 'h o u s e h ol d a s s et s'. It is ver y difficult to d et er- a d e q u a c y a n d als o t o d et e ct multi-collinearity in the data. Using the mi n e the unique c o ntri b uti o n t o a c o m p o n e nt of t h e hi g hl y c orr el at e d Bartlett 's Test of Sphericity [1 1 6 ], a n ot h er t est of the strength of t h e variables. To address this li mitation, t h e list of variables has been re- r el ati o n s hi p a m o n g v ari a bl e s h a s b e e n p erf or m e d , a n d this tells d u c e d t o 2 9 variables in A R 4 fra me work by re moving r e d u n d a nt v ar- w h et h er correlation matrix is considerably different fro m a n i d e ntit y ia bles (r > ± 0.8) to avoid multi-collinearity (highly c orr el at e d) a n d m atri x [8 0 ]. R es ults a cr oss all t ests s u g g est t h at principal co mponent si n g ul arit y (perfectly c orr el at e d). I n t h e c as e of AR5 fra me work, 2 8 analysis is a n appropriate approach to interrogate the data.

6 / S. D a s et a L Pr o gr ess i n Disaster Science 7 ( 2 0 2 0) 1 0 0 1 1 O

T a bl e 2 w h er e Xij is t h e n or m ali z e d v al u e of C F (j) wit h r es p e ct t o s u b- distri ct (i), Xi D es cri pti v e st atisti cs of t he selected variables for vulnerability a n d risk assess ments. is t h e a ct u al v al u e wit h r es p e ct t o s u b- distri ct (i), a n d Mi n Xj a n d Ma x Xj ar e V ari a bl es R a n g e M e a n St d. d e vi ati o n the mini mu m a n d maxi mu m values, respectively, of C F (j) a m o n g all t h e s u b- distri cts. Maxi mu m te mperature 0. 1 4 0. 4 3 0. 0 2 2 Mi ni m w n te mperature 0. 0 8 0. 4 1 0. 0 2 T h e n or m ali z e d v al u e r a n g e s fr o m 0 t o 1. T h e n e xt st e p aft er 3 Average precipitation 1 2 9. 1 7 3 0 1. 6 0 2 2. 6 8 n or m ali z ati o n is t o c o m bi n e all t h e n or m ali z e d C Fs i nt o si n gl e c o m p os- 4 Fl o o d 1. 0 0 0. 1 3 0. 2 0 it e i n d e x. 5 C y cl o n e 1. 0 0 0. 5 9 0. 3 2 A c c or di n g t o t h e fr a m e w or k pr o p o s e d b y F uss el a n d Kl ei n [3 3 ], e x- 6 Coastal erosion 1. 0 0 0. 0 7 0. 1 8 p o s ur e ( E) a n d s e n siti vit y ( S) t o g et h er c o m p o s e t h e p ot e nti al i m p a ct 7 P o p ul ati o n d e nsit y 4 8 3 7. 3 4 1 6 8 2. 2 1 8 6 4. 0 1 8 Average household size 1. 2 9 4. 5 0 0. 2 9 ( PI), w hil e a d a pti v e c a p a cit y ( A C) is t h e p ot e nti al of a s y st e m t o 9 Fe male population 1. 2 9 4 8. 7 8 0. 2 4 c o p e wit h these i mpacts. 1 0 Child population 8. 5 2 1 2. 2 9 1. 8 4 1 1 Socially disadvantaged people 6 2. 0 5 3 3. 4 3 1 5. 5 6 Pl = E x S ( 3) 1 2 Food insecurity 1 6. 1 1 4. 5 4 2. 8 6 1 3 Without land holding 6 3. 0 1 6 0. 6 7 1 3. 4 6 1 4 P o v ert y 5 8. 4 5 3 1. 7 6 1 3. 3 0 It c a n b e s ai d t h at p e o pl e w h o li v e i n e x p o s e d ar e a s a n d ar e al s o 1 5 Rural population 7 6. 1 1 8 5. 0 0 1 9. 0 0 s e n siti v e t o cli m at e c h a n g e i m p a ct s ar e li k el y t o b e c o m e a ' p ot e nti al 1 6 Agricultural dependency 7 0. 1 0 4 4. 4 7 1 8. 6 2 v ul n er a bl e gr o u p '. T hi s p ot e nti al v ul n er a bl e gr o u p c a n b e di vi d e d 1 7 Marginal workers 4 4. 9 8 2 8. 2 9 1 2. 3 3 i nt o t w o - wit h a n d wit h o ut a d a pti v e capacity. The l att er p art will b e Non- workers 1 8 2 0. 2 5 6 3. 6 9 3. 0 9 a n i m m e di at el y vulnerable group, a s t h e y c a n n ot c o p e wit h cli m at e 1 9 Literacy rate 1 9. 2 0 7 7. 1 0 4. 7 6 2 0 Work participation rate 1 6. 4 2 3 6. 2 3 2. 8 2 c h a n g e i m p a ct s [3 9 ]. I n ot h er w or d s, a s y st e m is m or e v ul n er a bl e if 2 1 S al ari e d j o b 2 4. 1 4 1 3. 2 3 5. 2 6 it is e x p o s e d a n d s e n siti v e t o t h e i m p a ct s of cli m at e c h a n g e a n d h a s 2 2 Ho me o wnership 1 7. 4 0 9 4. 8 6 3. 4 8 o nl y li mit e d/ n o c a p a cit y t o a d a pt. 2 3 H o u se h ol d ass ets 3. 5 0 0. 6 1 0. 7 8 Vulnerability therefore can be expressed with the follo wing mathe mat- 2 4 Pucca houses 7 4. 6 0 4 7. 7 6 2 1. 6 3 2 5 H e alt h c ar e c e ntr e s 1 3. 0 0 6. 0 0 3. 5 0 i c al e q u ati o ns: 2 6 Educational institutes 5 6 0. 0 0 5 1 6. 6 9 1 3 5. 0 3 2 7 R o a d d e nsit y 1 0. 2 1 1. 5 4 1. 7 0 V = Pl- Pl x A C ( 4) 2 8 Sanitation 6 5. 4 0 6 7. 1 7 1 7. 4 8 2 9 El e ctri cit y 8 8. 8 0 4 3. 8 6 2 3. 3 9 or, 3 0 Safe drinking water 8 4. 0 0 1 4. 2 1 1 8. 6 7 3 1 Cr o ps 8 5. 7 1 4 9. 5 8 2 3. 5 8 V = P!( l- A C) ( 5) 3 2 Irrigati o n 9 3. 5 0 4 0. 1 1 2 3. 5 1 3 3 F ertili z er 3 7 1. 0 0 9 5. 2 7 8 2. 3 3 E q. (5) has also been e mployed in the final calculation of risk, where V ali d c as es ( N) = 5 1. 'potential i mpact' is the co mbination of hazard, exposure, a n d s e nsiti vit y (Fi g. 6 ). 4. 3. Pri nci p al c o m p o n e nt a n al ysis a n d.fi n al c al c ul ati o n R = H x E x S ( l- A C) ( 6) T h e c orr el ati o n m atri x h as b e e n u s e d as a n i n p ut t o P C A t o e xtr a ct t h e pri n ci p al c o m p o n e nt s, as t h e v ari a bl e s ar e n ot st a n d ar di z e d [8 0 ]. T h e fi n al v al u e r e pr e s e nt s c urr e nt v ul n er a bilit y a n d ris k of I B O i n O nl y t h o s e c o m p o n e nt s wit h a n ei g e n v al u e (t h e v ari a n c e s e xtr a ct e d c h a n gi n g cli m at e conditions. T h e v al u e f or v ul n er a bilit y a n d ris k i n- b y t h e c o m p o n e nt s) > 1. 0 h a v e b e e n r et ai n e d u si n g t h e "eigenvalue- dexes ranges fro m Ot o 1, wit h hi g h er values reflecting hi g h er d e gr e e greater-than-one " r ul e pr o p o s e d b y K ai s er [ 1 1 7 ]. T h e v ari m a x ( or- of vulnerability a n d ris k. Fi n all y, t h e e ntir e r a n g e h a s b e e n e q u all y di- t h o g o n al) r ot ati o n h a s b e e n o pt e d t o i m pr o v e t h e i nt er pr et a bilit y of vi d e d i nt o five categories a n d e a c h is assigned a q u alit ati v e i n di c at or c o m p o n e nt s [8 4 ]. F or t h e c o m p ut ati o n of a co mposite index, co mpo- of v ul n er a bilit y a n d risk (fro m v er y l o w t o v er y hi g h). I n or d er t o vis u- n e nt s c or e c o effi ci e nt s h a v e b e e n e sti m at e d. C o m p o n e nt s c or e s ar e ali z e a n d a n al y z e t h e r e s ult s i n a g e o gr a p hi c c o nt e xt, t w o s e p ar at e t h e s c or es of e a c h c as e, o n e a c h c o m p o n e nt. m a p s h a v e b e e n pr e p ar e d using Arc GIS soft ware (10.5). T o c al c ul at e t h e v al u e of the contributing factors indicated in the I P C C for all the sub-districts, co mponent score coefficients ar e multiplied by 5. R e s ult s a n d di s c u s si o n the proportion of the corresponding co mponent's variance a n d s u m m e d these products in S P S S soft ware [80 ]. The value of contributing factors I B O i n h a bit a nt s ar e f a ci n g m ulti pl e challenges associated wit h cli- h as b e e n c al c ul at e d usi n g t h e f or m ul a: m ati c h a z ar d s a n d u n d er- d e v el o p m e nt. Cyclone, coastal er o si o n / e m- b a n k m e nt br e a c hi n g a n d fl o o di n g ar e t h e h a z ar d s t h at aff e ct t h e CF = L_ (Fi / TV ) * F Si ( I) d elt a r e gi o n q uit e frequently. T h e l o w i nt e n sit y cyclonic disturbances ori gi n at e d i n t h e B a y of B e n g al o c c ur al m o st e v er y y e ar a n d s e v er e c y- cl o ni c st or m s li k e Ail a- 2 0 0 9, B ul b ul- 2 0 1 9, a n d A m p h a n- 2 0 2 0 al s o w h er e, C F is a n c o ntri b uti n g factor (hazard, exposure, sensitivity a n d m a k e l a n df all i n t h e d elt a fr o m ti m e t o ti m e. I n m o st c a s e s, s ali n e a d a pti v e capacity), Fi is t h e p er c e nt a g e of v ari a n c e e x pl ai n e d b y e a c h fl o o ds ar e t h e r e s ult of e m b a n k m e nt br e a c hi n g a n d st or m s ur g e s. c o m p o n e nt (i), T V is t h e t ot al v ari a n c e e x pl ai n e d b y all t h e r et ai n e d R es ults d eri v e d fr o m t h e a n al ysis of m ulti- h a z ar d d at a (flood, cyclone, c o m p o n e nt s, F Si is t h e c o m p o n e nt s c or e c o effi ci e nt s o n e a c h a n d c o a st al er o si o n) of I B O s u g g e st t h at c o a st al s u b- di stri ct s s u c h as c o m p o n e nt (i) . G o s a b a, B a s a nti, P at h ar pr ati m a, K ult ali, Hi n g al g a nj, a n d The value of the C F c a n b e p ositi v e or n e g ati v e, m a ki n g diffi c ult t o us e it S a n d e s h k h ali-II s u b- di stri ct s ar e at v er y hi g h ri s k. A n ot h er i s s u e f or fi n al c al c ul ati o n. It is necessary to n o n n aliz e all t h e C Fs to ensure that w hi c h m a g nifi e s t h e ri s k i n t h e r e gi o n is e c o n o mi c v ul n er a bilit y of they are co mparable. This has been carried out using the methodology de- its inhabitants. T h e c o nti n u o u s d e gr a d ati o n of n at ur al r e s o ur c e s a n d v el o p e d f or t h e c al c ul ati o n of the Hu man Develop ment Index [118]. The u n s u st ai n a bl e p att er n of e c o n o mi c a cti vit y c o m bi n e t o i n cr e a s e l o c al e q u ati o n is e x pr ess e d as: p o v ert y, w hi c h f urt h er e x a c er b at e s t h e e xi sti n g v ul n er a bilit y of t hi s delta. Monsoon d e p e n d e nt m o n o cr o p pi n g e c o n o m y pr e v ail s i n m o st .. (Xi- Mi n Xj ) ( 2) of t h e physically v ul n er a bl e ar e a s of I B O, wit h e x c e pti o n of m ulti pl e Xl] = ( M a x X J- Mi n X J ) cr o p pr a cti c e s in fe w places. F urt h er m or e, li mit e d a c c ess t o m ar k et s

7 / S. D a s et a L Pr o gr ess i n Disaster Science 7 ( 2 0 2 0) 1 0 0 1 1 O

diffi c ult e c o n o mi c tr a d e, w hi c h i n t ur n cr e at e s p o v ert y. B a s a nti, S a n d e s h k h ali II, S a n d e s h k h ali I, K ul pi, C a n ni n g II, P at h ar pr ati m a, N a m k h a n a a n d K ult ali s u b- di stri ct s h a v e 4 5 % of t h eir p o p ul ati o n i n c o n diti o n s of c hr o ni c poverty. This p o v ert y is a s s o ci at e d wit h f o o d i n- s e c urit y, m al n utriti o n, illiterac y, l a c k of pri m ar y h e alt h s er vi c e s a n d a c c ess t o dri n ki n g w at er a n d s a nit ati o n facilities. The spatial assess ment of v ul n er a bilit y/ri s k i n t h e d elt a is a cr ucial el e m e nt to consider, as it varies fro m place to place. Based o n t h e r e- s ults of P C A, v ul n er a bilit y a n d ris k h a v e b e e n e sti m at e d a n d m a p p e d V u l n er abil it y R isk/Impac t f or all t h e sub-districts of I B O (Table 3). In t h e v ul n er a bilit y a n al ysis ( A R4), t wo c o m p o n e nt s h a v e a c c o u nt e d f or 7 5. 3 7 % of t h e t otal vari- a n c e i n t h e d at a of e x p os ur e, w h er e a s t hr e e c o m p o n e nt s of sensitivity a n d f o ur c o m p o n e nt s of a d a pti v e c a p a cit y h a v e a c c o u nt e d f or 7 3. 9 6 % a n d 7 3. 8 0 % of t h e t ot al v ari a n c e respectively. It is i m p ort a nt t o n ot e t h at t h e first c o m p o n e nt has explained the m a xi m u m v ari a n c e i n t h e d at a. For the first co mponent i n A R 4, maxi mu m and mini mu m te mperature, av- er a ge preci pit n.ti o n, c o ast n.l er osi o n, a gric ul 1 1. 1r al dependency, liter acy r ate, h o use- h ol d assets, s a nit ati o n have sho wn markedly higher positive loadings, while v ari a bl es like landholding a n d ho me o wnership have sho wn strong negative loadings. Loadings refer to the correlations bet ween the variables a n d t h e co mponents, a n d they range fro m - 1 t o + 1. The second co mponent ex- pl ai ns t h e v ari ati o ns i n fl o o d, cycl o ne, aver a ge h o use h ol d size, c hil d p o p ul ati o n, Fi g . 6. I P C C contributing factors for final calculation of vulnerability ( A R4) a n d ris k cr o p diversity , irri g ati o n. The third co mponent explains f e m al e p o p ul ati o n, ( A RS) indexes.

T a bl e 3 P C A results for the Indian Bengal Delta: Vari max rotation factor matrix. V ari a bl es Co mponent ( AR4) Co mponent ( AR5)

2 3 4 1 2 3 4

1 Maxi mu m te mperature 0. 7 5 5 - 0. 4 7 4 N. A. 2 Mini mu m te mperature 0. 8 1 6 3 A v er a g e p r e ci pit ati o n 0. 8 0 0 4 Fl o o d 0. 7 6 8 0. 8 4 3 5 C y cl o n e 0. 8 8 1 0. 7 6 2 6 Coastal erosion 0. 8 8 5 0. 7 6 1 7 Population density N. C. - 0. 9 5 9 8 Rural population N. C. 0. 9 4 7 9 A v er a g e h o u sehold size 0. 9 0 4 0. 9 2 1 1 0 F e m al e p o p ul ati o n 0. 8 6 6 0. 6 9 3 1 1 C hil d p o p ul ati o n 0. 8 5 0 0. 9 2 1 1 2 S o ci all y di s advantaged people 0. 4 7 6 - 0. 4 0 8 - 0. 6 8 9 1 3 Food insecurity 0. 5 6 7 0. 7 9 3 1 4 Without land holding - 0. 9 2 5 - 0. 5 0 9 0. 7 3 7 1 5 P o v ert y 0. 6 9 0 0. 4 8 0 0. 5 7 6 - 0. 4 1 5 0. 5 4 1 1 6 Agricultural dependency 0. 9 1 1 0. 9 4 0 1 7 Marginal workers 0. 7 0 8 0. 4 1 7 0. 6 4 3 - 0. 5 5 3 1 8 Non- workers - 0. 5 0 6 0. 6 7 9 0. 8 1 0 1 9 Literacy rate 0. 7 6 7 S a m e 2 0 Work participation r at e 0. 7 6 7 2 1 S al ari e d j o b N. C. 2 2 Ho me o wnership - 0. 8 7 6 2 3 Household assets 0. 8 6 6 2 4 P u c c a h o u s es N. C. 2 5 H e alt h c ar e c e ntr e s - 0. 5 2 0 2 6 Educational institutes 0. 7 7 7 2 7 R o a d d e n sit y 0. 7 6 8 2 8 Sanitation 0. 7 6 2 0. 4 5 5 2 9 El e ctri cit y 0. 6 5 9 0. 5 4 4 3 0 Safe drinking w at er 0. 8 3 1 3 1 Cr o ps 0. 8 5 7 3 2 Irrigati o n 0. 8 2 2 0. 4 0 7 3 3 Fertilizer 0. 5 1 4 P er c e nt of v ari a n c e E x p os ur e 4 5. 2 1 7 3 0. 1 6 7 H a z ar d 6 2. 3 1 2 Sensitivity 3 3 . 9 6 9 2 3. 7 8 5 1 6. 2 0 7 E x p os ur e 9 0. 0 7 6 Adaptive capacity 2 7. 0 2 0 1 6. 6 5 0 1 5. 0 9 9 1 5. 0 3 5 Sensitivity 3 1. 9 7 8 2 4. 7 2 0 1 7. 3 4 9 Extraction method: Principal Co mponent Analysis; rotation method: Vari max with Kaiser Nor malization. a. A d a pti v e c a p a cit y is s a m e f or A R 4 a n d A R S. b. Only one co mponent was extracted. The solution cannot b e r ot at e d. N. C. = n ot considered (to avoid multi-collinearity issue); N. A. = not applicable (as per definition of h a z ar d i n I P C C A R S). Suppress s mall coefficients (absolute value belo w 0.40). St atisti c al t ests: K ais er- M e y er- Ol ki n M e as ur e of Sa mpling Adequacy ;:,, 0. 700; Deter minant of C orr el ati o n M atri x ;:,, 0.00001; Bartlett's Test of Sphericity = 0. 0 0 ( Si g nifi c a nt); Co m munalities ( Average) ;:,, 0. 7 5 0.

8 / S. D a s et a L Pr o gr ess i n Disaster Science 7 ( 2 0 2 0) 1 0 0 1 1 O

a r o a d de nsity a n d s afe dri nki n g w ater . The fourth co mponent which is m ai nl y E x p os u re r el at e d t o a d a pti v e c a p a cit y e x pl ai ns w ork p artici p ati o n r are a n d e d uc ati o n al 1. 0 i nstil 1 1tes. The results based o n risk analysis C A R S) approach reveal a slight differ- ent scenario. One co mponent has explained 62.31 % of the variance in the d at a of hazard and 90.08% in case of e x p os ur e. F or s e nsiti vit y, t hr e e c o m- ponents have explained 74.0S % of the variance. Adaptive capacity is s a m e as i n v ul n er a bilit y a n al ysis ( A R 4). Fl o o d, c o ast al er osi o n, aver a ge h o use- A d a pti ve C a p acit y Se nsi tivity h ol d size, c hil d p o p ul ati o n, r ur al p o p ul ati o n, a gric ult ur al de pe n de ncy h a v e sho wn higher positive loadings and p o p ul ati o n de nsity has sho wn negative -- B a s ant i -- S a n d cs h k h ali - 11 - Sa n d es h k hali- 1 -- G os a b a -- 1 li n g al g a nj - Canning-II loadings. The second co mponent explains the variations in l a n d h ol di n g, -- K u lt ali -- P at h ar pr ati m a - Ja y n a g ar- 11 non- workers and third co mponent explains f o o d i nsec urity, fe m ale p o p ul ati o n. It is understood that eight variables largely deter mine the contributing fac- b t ors of vulnerability a n d ris k ar e flood, coas ml er osi o n, a gric ult ur al de pe n- de ncy, aver a ge h o use h ol d size, l a n d h ol di n g, h o use h ol d assets, s a nit ati o n, a n d r ur al p o p ul ati o n. The cli mate change i mpact hotspots (vulnerability and risk) have been i d e ntifi e d at t h e s u b- distri ct l e v el c o nsi d eri n g b ot h t h e I P C C working defi- niti o ns of A R 4 a n d A R S (Fi gs. 8 & 9 ). Adaptive Capacity E x p os u r e Fi g. 7a and b sho ws the influence of the contributing factors indicated b y I P C C on top 10 most vulnerable sub-districts ( A R4), and top 10 highest risk sub-districts C A R S) . Coastal sub-districts like Gosaba, Basanti, Sandeshkhali-II, , and Patharprati ma are at gr e at est ris k/ v ul n er a bil- S e nsiti v ity it y d u e t o b ot h hi g h er s e nsiti vit y a n d l o w er a d a pti v e c a p a cit y. - G os a b a - B as a nti - Sandeshkha li-1 1 T h e r es ults i n di c at e t h at t h e m aj orit y of t h e v ul n er a bl e c o m m u niti es ar e -- K ult ali - l li n gal g a nj - Patharprati ma - Ca n n i ng- II - S a n d eshkhali-1 - N a m k h a n a li vi n g i n t h e m ar gi n al ar e as of t h e d elt a (Fi gs. 8 & 9 ). B as a nti is assessed as the most vulnerable sub-district according to the A R 4 approach whereas G os a b a is found to be exposed to highest risk based on the A R S m et h o d . Fi g. 7. a. T o p 1 0 m o st v ul n er a bl e s u b- distri cts i n t h e I n di a n B e n g al D elt a . b. T o p 1 0 hi g h est ris k su b- distri cts i n t h e I n di a n B e n g al D elt a. B ot h ar e s p ati all y c o nti g u o us a n d geographically si milar. Basanti is b or- dered by vulnerable sub-districts Canning-II, Sandeshkhali-II and Gosaba and Sundarban forests. Gosaba is the last settle ment at the margin of t h e deep forests of the Indian Sundarban. Li mited livelihood opportunities,

8 8 ° 30' E 8 9 ° 1 S' E ~ ,------~---.,------L-E~ G- E-- D---, ~ O INDI A N BEl\" GALDELT A .. M N N _j K m. N I I I I I 0 1 2. 5 2 5

D E S 1- 1 z z

N N N

1 3 A Y 0 F 1 3 E G A L

ss 0 3 o· E 8 9 ° I S' E

Fi g . 8. V ul n er a bilit y m a p of I n di a n B e n g al D elt a (f oll o wi n g t he I P C C A R 4 approach, 2007).

9 / S. D a s et a L Pr o gr ess i n Disaster Science 7 ( 2 0 2 0) 1 0 0 1 1 0

ss 0 J O' E 8 9 ° 1 5' E z ~------~---- ~------~------~ ~

"' L E G E N D 0,.., 0 l N Dl A..'\' 8 £.'I G A L D E L T A ,.., N N _\ RI S K K m. N I I 0 12 .5 2 5

E S H z .,0 N N

B A Y 0 r- B E N G A L

s s •3 o• E 8 9 ° l 5' E

Fi g. 9. Ris k m a p of Indian Bengal Delta (follo wing the I P C C A R S approach, 2014).

• • • • • • V u lnerability ( A R4) A m d a n g a S warup R R~ll+l'"kur B aduriJagdah Ri s k ( A R 5) S o n ar p ur 5 0 B ar a s at- 1 Sa ndeshkhali- 1 1 · ,,. B ar a s at- 1 1 Sandeshkhal i - 1 14:~ J.:· .•• •.. B arr n e k p u r- 1 S a g a r ...... • • ..... Barrnckpur-1 1 ·: _ .. R a j ar hat ...... B ar ui p ur Patharprati ma . . B a sa nti N a m k h a n a ... i -1 2 0 M o gr a h a t - II '• , I Basirhat-11 ,•,• Mograhat - I .•··. .. •·-··· • ·•=: tli-~.·•• Bhan gar- I Mi n a k h a n ,•.-·· • ··~: '. .. ••· ... B h a n g ar- 1 1 · =·· • ·...... Mathurapur-11 Bishnupur-1 "• ·. Mathurapur-1 • •·•···•··. ":.Ii-.. Bi shnupur-11 ·· ... .. ,..·· M a n dirb az ar ·· .. ..·.. . B o n g a o n K u ltali ,,,";Iii Budge- Budge- I

K ul pi It: Bu dge- Budge-II

K a k d wi p i. _ : ·• C a n ni n g-I : .• Ja y n a g a r- 11 ••• • C a n ni n g- I I J a y n a g ar- 1 D c g a n g a Hi n g a lg a nj Di a m o n d .. H as n a b a d Di a m o n d Ha rlf~bra-!-labra-1 Gosab Qaighht' Jta

Fi g . 1 0. S u b- distri ct l e v el r el ati v e r a n ki n g ofl n di a n B e n g al D elt a.

1 0 / S. D as et a L Pr o gress i n Disaster Science 7 ( 2 0 2 0) 1 0 0 1 1 0

poor socio-econo mic and institutional resilience, and increasing bio-physi- through skill develop ment projects, eco-touris m develop ment may help to c al v ul n er a biliti es c o m bi n e t o m a k e t h es e t w o s u b- distri cts t h e m ost v ul n er- i mprove the standard of li vi n g of r esi d e nts a n d reduce the overall able and exposed to highest risk in the I B D [ 1 23]. Other vulnerable ( A R4)/ v ul n er a bilit y a n d ris k. highest risk ( A R S) sub-districts are Sandeshkhali-1 & II, Hi n g al g a nj, Ca n- ning-II, Kultali, Patharprati ma. These sub-districts have maxi mu m vulnera- A ut h o r c o nt ri b uti o ns bility /risk, and have the potential to be adversely affected by cli mate change, where focused adaptation measures are i m mediately needed. The S D contributed to conception a n d d at a c oll e cti o n, d at a a n al ysis a n d least vulnerable sub-districts ( A R4) ar e Barrackpur-1 & II, -II, manuscript preparation. Budge- Budge-I, Bishnupur-II and lo west risk sub-districts C A R S) ar e A G, S S prepared the maps. Barrackpur-1 & II, Budge- Budge-I, Thakurpukur- , Bagdah. All S H, T G, R S C provided critical contributions to the final version of t h e s u b- distri cts ar e cl os er a n d c o n n e ct e d t o K ol k at a cit y a n d fall wit hi n t h e K ol- m a n us cri pt. kata Metropolitan Area ( K M A) which results in greater advantages i n t er ms of li v eli h o o d o p p ort u niti es a n d a c c ess t o fr o ntli n e s er vi c es. It can be noted Declaration of co mpeting interest that local governance plays a n i mportant role to deal with these variations of v ul n er a bilit y / ris k as t his r e q uir es l o c al k n o wl e d g e t o t ar g et a d a pt ati o n or The authors declare that they have no kno wn co mpeting financial inter- miti g ati o n i nt er v e nti o ns. ests or personal relationships that could have appeared to influence the The most significant difference bet ween the results of the A R 4 a n d A R S work reported in this paper. approaches is t h e c h a n g e i n s u b- distri ct l e v el r el ati v e r a n ki n g (Fi g. 1 0 ). T h e o v er all l e v el of v ul n er a bilit y / ris k ( v er y l o w t o v er y hi g h) is al m ost t h e i d e n- Ackno wledge ment ti c al f or all t h e s u b- distri cts (Fi gs. 8 & 9 ). T his r es ult s u g g ests a li n k b et w e e n the ne w concept of ris k ( A R S) a n d t h e e xisti n g c o n c e pt of vulnerability The authors thank colleagues fro m School of O c e a n o gr a p hi c St u di es ( A R 4). It can be noted that the concept of exposure or syste m (people, live- and DE C C M A-India tea m who provided insight and expertise that was i m- li h o o ds, et c.) i n A R S is more adequate to identify the vulnerable co m muni- mensely helpful for the research. ties in any areas. This is considered as a n a d v a nt a g e of A R S o v er t h e A R 4 T his w or k is c arri e d o ut u n d er the Deltas, vulnerability and Cli mate fra me work. C h a n g e: Mi gr ati o n a n d A d a pt ati o n ( D E C C M A) pr oj e ct (I D R C 107642) un- d er the Collaborative Adaptation Research Initiative i n Afri c a a n d Asi a 6. C o n cl usi o ns ( C A RI A A) progra m me with financial support fro m the U K G o v er n m e nt 's Depart ment for International Develop ment ( DFI D) a n d the International This study provides a representation of t h e ris k of a c o ast al r e gi o n f ol- Develop ment Research Centre (I D R C), Canada. The vie ws expressed in this lo wing the I P C C A R S approach. Applying the I P C C A R 4 a n d A R S fr a m e- work are those of the creators and do n ot n e c ess aril y r e pr es e nt t h os e of works to the sa me d at a set, t wo different sub-districts located in the I B O D FI D a n d I D R C or its Boards of Governors. delta have been identified to b e the most vulnerable or exposed to highest risk. Interestingly, the t wo sub-districts are spatially contiguous and geo- References gr a p hi c all y si mil ar. T his is als o si mil ar f or ot h er s u b- distri cts of I B O. T h e difference bet ween the results of the A R 4 a n d A R S approaches is the change [ 1] J P C C. I n: Fi el d C B, B arr os V R, Dokken DJ , Mach KJ , Mastrandrea M D, Bilir T E, i n s u b- distri ct l e v el r el ati v e r a n ki n g. T his s u g g ests a li n k b et w e e n t h e n e w Chatterjee M, E bi KL , Estr a d a YO , Ge n o v a RC , Gi n n a B, Kiss el ES , Le v y AN , c o n c e pt of ris k ( A R S) a n d t h e e xisti n g c o n c e pt of v ul n er a bilit y ( A R 4). Mac Cracken S, M astr a n dr e a PR , W hit e ll, e dit ors. Oi m a te change 2014: i mpacts, ad- T h e f o c us of t h e I P C C A R S is on the syste m (exposure) and n ot o n t h e a pt ati o n, a n d v ul n er a bilit y. P art A: gl o b al a n d s e ct or al as p e cts . C o ntri b uti o n of w or k- i m p a ct(s) of h a z ar d o n t h e s yst e m. T his is considered as a n a d v a nt a g e of i n g gr o u p II to the fifth assess ment report of the Intergovern mental Panel o n Oi m at e Change. ca mbridge, United Kingdo m and Ne w York, N Y, U S A: Ca mbridge University A R S o v er t h e A R 4 fra me work. The concept of vulnerability i n A R S is pr e- Press; 2014 [ 1 1 3 2 p p] . sented as not-dependent on exposure and hazard [119]. I P C C A R S fr a m e- [2] Wong PP, Losada l J, G att us o J- P, Hi n k el J, K h att a b i A, M ci n n es K L, et al. C o ast al s ys- work helps to identify the adaptation measures based on the current te ms and lo w-lying areas. I n: Fi el d C B, B arr os V R, Dokken DJ , Mach KJ , M astr a n dr e a M D, Bilir T E, C h a tterj e e M, E bi K L, Estr a d a YO , G e n o v a R C, Gir m a B, Kisse l ES , Le v y weaknesses of a syste m, and also sho ws the cli mate-resilient path ways A N, Mac Cracken S, Mastrandrea P R, W hit e L L, e dit ors . Cli m at e c h a n g e 2 0 1 4 : i m p a cts, t h at can reduce the cli mate change i mpacts [1 2 0 ]. It can be said t h at a d a pt ati o n, a n d v ul n er a bilit y. P art A: gl o b al a n d s e ct or al as p e cts. C o n tribution of I P C C A R S offers a robust approach for vulnerability a n d risk reduction working group II t o t h e fift h assess ment report of the Intergovern mental Panel o n Cli- mate Change. ca mbridge, United Kingdo m and Ne w York, N Y, U S A: Ca mbridge Uni- u n d er a n u n c ert ai n f ut ur e. v ersit y Press; 2 0 1 4. p. 3 6 1- 4 0 9. This study can help to prepare location specific e mergency plans/re- [3] Zhang K, Douglas BC , Leather man S P. Global war mi ng a n d coastal erosion. Cli m sponses to co mbat hazards associated with cli mate change and variability. Change. 2004;64(1):41-58. [ 4] Eri cs o n J P, V ori:is mart y CJ, Di n g m a n S L, W ar d L G, Meybeck M. Effective sea-level rise These responses could be in the for m of i mple mentation of a forecasting a n d d elt as: c a us es of c h a n g e a n d h u m a n di mension i mplications. Global Plan et syste m for extre me weather events in co mbination with grass root disse m- Change. 2006;50(1):63-82. i n ati o n of these forecasts. The construction of multipurpose cyclone and [ 5] S y v its ki JP , K ett n er AJ, O v er e e m 1, H utt o n EW , H a n n o n M T, Br a k e nri d g e G R, et al. Si nl u n g d elt as d u e t o h u m a n a c ti vities. N at Ge osci. 2 0 0 9; 2( 1 0) :6 8 1. fl o o d s h elt ers w o ul d h el p i m pr o v e t h e r esili e n c e of i m p a ct e d c o m m u niti es. [ 6] Br o w n S, N i c holls R J , L a z ar AN , H o m b y DD , Hill C, H a zr a S, et al. W h at ar e t he i m pli- Other response strategies such as retreat and realign ment of e mbank ments, c ati o n s of s e a- le v el ris e f or a 1. 5, 2 a n d 3 ·c rise in global mean te mperatures in the m a n gr o v e pl a nt ati o ns, i ntr o d u c e sl ui ci n g of s maller creeks could be also i m- Ganges- Brah maputra- Meghna and other vulnerable deltas? Regional Environ mental pl e m e nt e d at t h e l o c al le vel. Change . 2018:1-14. [ 7] Ni c h olls RJ, M ari n o v a N, Lo we J A, Bro wn S, V elli n g a P, D e G us m a o D, et al. S e a-l e v el S c ali n g u p e xisti n g c e ntr al a n d state govern ment sche mes b y m e c h a- ris e a n d its p ossi bl e i m p a cts gi v e n a ' b e y o n d 4 C w orl d' i n t he t wenty-first century. nis ms s u c h as s ust ai n a bl e a gri c ult ur al pr a cti c es, di v ersifi c ati o n t o off-f ar m Philosophical T ransactions of t h e R o yal S o ci et y of L o n d o n A: M at h e m ati c al, P h ysi c al activities, seasonal e mploy ment sche mes in agriculture to support to and Engineering Sciences. 2011;369(1934): 1 6 1- Sl. [ SJ Fi el d C B, editor. Cli mate change 2014-i mpacts, adaptation and vulnerability: regional far mers/marginal workers and create alternative and sustainable livelihood aspects. Ca mbridge University Press; 201 4. o pti o ns i n r ur al ar e as, wit h a s p e ci al f oc us o n w o m e n a n d y o ut h, c a n als o b e [ 9] U N F C C C. Oi m at e change: i mpacts, vulnerabilities and adaptation in developing c o u n- funda mental to reduce the present inherent vulnerability of a s yst e m. B y tries. Bonn , Ger many: United Nations Fra me work Convention o n Cli m at e C h a n g e , Cli- m at e Change Secretariat ( U NFCCC); 2007. https: //u nf c c c.i nt/r e s o ur c e / d o cs / doing so, it will also address the socio-econo mic and environ mental issues publications/i mpacts.pdf. that threatens the lives of the inhabitants of i n cli m at e-s e nsiti v e ar e as of [1 0] F A O. T h e st a te of food and agriculture -cli mate change, agriculture and food security. I B O and drives distress migration as a response to recurrent extre me events F o o d a n d Agriculture Organization of the United Nations978-92-5-109374-0; 2016. htt p :// w w w.f a o .or g/ 3 / a-i 6 0 3 0 e. p df. such as cyclones, floods. In situ responses such as safe drinking water, san- [ 1 1] Fi el ds S. Why Africa 's cli mate change burden is greater. Environ Health Perspect. 2005; itation facilities, pri mary health services, multiple livelihood options 113: A534-7.

1 1 / S. D as et a L Pr o gress i n Disaster Science 7 ( 2 0 2 0) 1 0 0 1 1 0

[ 1 2] H a h n M B, Riederer A M, Foster S O. The livelihood vulnerability index: a prag matic ap- [43] Woodroffe CD , Ni c h olls RJ , S ait o Y, C h e n Z, G o o d br e d S L. L a n ds c a p e varia bilit y a n d proach to assessing risks fro m cli mate variability a n d c h a n g e- a c as e st u d y i n M o z a m- t h e r e s p o n s e of Asi a n m e g a d e it a s t o e n vir o n m e nt al c h a n g e. Gl o b al c h a n g e a n d i nt e- bique. Global Environ Chang. 2 0 0 9 F e b 1; 1 9( 1): 7 4- 8 8. gr at e d c o ast al m a n a g e m e nt Dordrecht: Springer; 2006; 2 7 7- 3 1 4. [ 1 3] C h e n J, Mueller V. Coastal cli mate change, soil salinity a n d h u m a n migration in Ban - [ 4 4] L a z ar A N , Ni c h olls RJ, P a y o A, Ada ms H, Mortreux C, S u c k all N, et al. A m et h o d t o as- gladesh. Nature Cli mate Change. 2 0 1 8; 8( 1 1): 9 8 1- 5. s ess mi g r ati o n a n d a d a pt ati o n i n d elt a s: a pr eli mi n ar y f a st tr a c k a s s e s s m e nt ( N o. [ 1 4] T e h SY , K o h H L. Cli m at e c h a n g e a n d soil salinization: i mpact o n agriculture, w at er a n d 1 0 7 6 4 2). D E C C M A w or ki n g p a p er , d e ltas, v ul nera bilit y a n d cli mate chang e: mi gr ati o n food security. I nt er n ati o n al J o ur n al of Agriculture , Forestry a n d Plantatio n. 2016;2: a n d adaptation, I D R C projec~ 2015. 1- 9. [ 4 5] Ni c h olls RJ , A d g er WN , H utt o n C W, Hanson SE, L a z ar A N, Vi n c e nt K, et al. Sustainable [15] To maz A, P al m a P, Alvarenga P, Gonc;a!ves M C. Soil sali nit y risk i n a cli m at e c h a n g e d elt as i n t h e Anthropocene. Deltas i n t h e Anthropoc ene. Cha m: Palgrave Mac millan ; s c e n ari o a n d its effect o n cr o p yi el d. Cli m at e c h a n g e a n d s oil i nter a cti o n s. Els e vi er; 2 0 2 0; 2 4 7- 7 9. 2 0 2 0. p. 3 5 1- 9 6. [46] Census of I n di a Pri mary census a b str a ct N ort h 2 4 P ar g a n as & S o ut h 2 4 P ar g a n as: Of - [16] Shelton C. Cli m at e c h a n g e a d a pt ati o n i n fis h eri es a n d aquaculture . F A O fish eri es a n d fi c e of t h e R e gi str ar G e n er al a n d Co m missioner, Govern ment of I n di a; 2 0 1 1. aquaculture circular (F A O) e n g n o . 1088; 2014. ( 4 7] G o W B. Distri ct h u m a n d e v el o p m e nt r e p ort: S o ut h 2 4 Parganas. Depart ment of D e v el- [17] Bhadra T, Das S, H a zr a S, B ar m a n B C. Ass essi n g t h e d e m a n d, availability a n d a c c essi - o p m e nt & Pl a n ni n g, Govern ment of W est B e n g al; 2 0 0 9. bilit y of p ot a bl e w at er i n I n di a n S u n d ar b a n biosphere reserve area. I nt J R e c e nt S ci [ 48] G o W B. Distri ct h u m a n d e v el o p m e nt report: North 2 4 P ar g a n as . D e p art m e nt of D e v el- Res. 2 0 18;9(3) [25437-25]. o p m e nt & Planning, Govern ment of W es t B e n g al; 2 0 1 0. [18] Didovets I, Lobanova A, Bronstert A, Snizhko S, M a ul e C F, Kr ys a n o v a V. Assess ment of [ 49] D S H B. Distri ct st atisti c al h a n d b o o k - N ort h 2 4 P ar g a n as & S o ut h 2 4 Parganas. Bureau cli mate change i mpacts on water resources in three re pre s e ntative Ukrainian catch- of Applied Econo mics & St atisti cs, G o v er n m e nt of W es t B e n g al; 2 0 1 1. m e nt s using eco-hydrological m o d e lling. Water. 2017;9(3):204. [50] Hajra R, Ghosh T. Agricultural productivity, household p o v ert y a n d mi gr ati o n i n t h e [19] Olsson L, O p o n d o M, Tschakert P, Agra wal A, Eri ks e n S E. Li v eli h o o d s a n d p o v ert y . Cli - I n di a n S u n d ar b a n D elt a. El e m Sci A nt h. 2 0 1 8; 6( 1) . m a te change 2014: i mpacts, adaptation, a n d vulnerability. P art A: gl o b al a n d s e ct o r al [51] Danda M , Sri sk a nt h a n G, G h o s h A, Bandyopadhy a y J, H a zr a S. I n di a n S u n d ar b a n s aspects. Contribution of working group II to the fifth assess ment report of the Intergov- delta: a vision. Ne w Delhi: World Wide Fund for Nature- I ndi a; 2 0 1 1; 4 0. er n m e nt al P a n el o n Cli mate Change ; 2 0 1 4. [52] Rah man M M , Gho sh T, Salehin M, Gh osh A, Haque A, Hossain MA , et al. Ganges- Brah- [ 2 0] P at er s o n SK , O'D o n n ell A, L o o mis D K, H o m P. T h e s o ci al a n d e c o n o mi c eff e ct s of maputra- Me g h n a Delta , Banglades h a n d I n di a: a tr a n s n ati o n al mega-delta. De ltas i n shoreline change: North Atlantic, South Atlantic , Gulf of M e xi c o , a n d Great Lakes re- t h e Anthropocene. Cha m: Palgrave Ma c millan; 2 0 2 0 ; 2 3- 5 1. gional overvie w. M A: Eastern Research Group Inc, Lex mgton; 2 0 1 0 . [ 5 3] P et hi c k J, Orford J D. Rapid rise i n effective sea-level i n s o ut h w e st Bangladesh: its [21] Wood ward A, S mith K R, Ca mpbell -Lendru m D, Cha d e e D D, H o n d a Y, Li u Q, et al. Cli - c a u s es a n d c o nt e m p or ar y r at e s. Gl o b al Pl a n et C h a n g e. 2 0 1 3; 1 1 l :2 3 7- 4 5 . htt p s:/ / m at e c h a n g e a n d h e alt h : o n t h e l at est I P C C r e p ort. T h e L a n c et. 2014;383(9924) : d oi .or g/ 1 0. 1 0 1 6 /j. gl o pla c h a .2 0 1 3. 0 9 .0 1 9 . 1 1 8 5- 9. (54] Hazra S, Mukhopadhyay A, Mukherjee S, Akhand A, Chand a A, Mitra D, et al. Dis a p- [ 2 2] O p p e n h ei m er M , C a m p o s M, W arr e n R, Bir k m a n n J , L u b er G, O ' Neill B, et al. E m er g e nt p e ar a n c e of t h e n e w M o or e Isl a n d fr o m t h e s o ut h er n m o st c o a st al fri ng e of t h e ris ks a n d key vulnerabilities. Cli mate change 2014: i mpacts, ad a pt ati o n , a n d v ul n er a- S u n d ar b a n D elt a- a c a s e s t u d y. J o ur n al of t h e I n di a n S o ci et y of R e m ot e S e nsi n g. bilit y. P art A: gl o b al a n d s e ct or al as p e cts. C o ntri b uti o n of w or ki n g gr o u p II t o t h e 2 0 16;44(3):479-84. fifth assess ment report of t h e I nt erg o v er n m e nt al P a n el o n Cli mate Change . Ca mbridge, [55] Hazra S, G h os h T, B a ksi A, R a y N. Sea level change: its i mpact o n We st Bengal coast. U nit e d Ki n g d o m a n d N e w Y or k , N Y, U S A: C a m bri d ge University Pr e ss; 2 0 1 4 . Indian J Geogr Environ. 2 0 0 1; 6: 2 5- 3 7. p. 1 0 3 9- 9 9. [56] Gho sh T, Hajra R, M u k h o p a d h y a y A. Isla n d er os io n a n d afflicted p o p ulati on: crisis a n d [ 2 3] D as g u pt a P, M ort o n JF, D o dr n a n D, K ar a pi n ar B, Meza F, River a-Ferre MG , et al. R ur al p oli ci es t o h a n dl e cli mate change. In: Filho W Leal , et al, editors. International perspec- areas. Cli m Change . 2014:613-57 . ti v es o n cli mate change. S witzerland : Springer International Publishing ; 2 0 1 4 . [24] Kasperson R E, K as p ers o n J X. Cli m at e c h a n g e, vulnerability , a n d social justice. Stock- [57] Hazra S, Dasgu pt a R, S a m a nt a K. Cli m at e c h a n g e - se a level rise- a n d socio econo mic hol m: Risk a n d Vulnerability Progra m me, Stockhol m Environ ment Institute; 2 0 0 1. i m p a ct o n S u n d ar b a n, W e st B e n g al. I n: G h o s h S, e dit or. Gl o b al w ar mi n g i n c o nt e xt [ 2 5] Szabo S, Brondizio E, R e n a u d FG , H etri c k S, Ni c h olls RJ , Matt h e w s Z, et al. Population t o t h e Indian sub-continnent. Hu mbolt Club Calcutta; 2009. p. 2 7- 3 5. d y n a mi cs, d elt a vulnerability a n d environ mental change: co mparison of the Mekon g, [58] Hazra S, S a m a nt a K, Mukhopadhyay A, Akhand A. T e m p or al c h a n g e d et e cti o n ( 2 0 0 1- G a n g e s-Br a h m a p utr a a n d A m a z o n d elt a regions. Sustainabilily Science. 2 0 1 6; 1 1( 4): 2 0 0 8) of t h e S u n d ar b a n-fi n al r e p ort. Kolkata: School of O c e a n o gr a p hi c St u di e s, 5 3 9- 5 4. J a d a v p ur Univer sily a n d W WF-!ndia , S u n d ar b a n Progra m me; 2010; 1 2 8. [26] Vincent Katharine . Creating a n i n d e x of social vulnerability to cli mate c h a n g e f or Af- [ 5 9] S a m a nt a B, D as S, H a zr a S. Micro level vulnerability assess m e nt of a c o m m u nit y li vi n g rica. , 56 Tyndall Center for Cli mate Change Research; 2004; 41 Working Paper. i n M o u s u ni Isl a n d i n t he I n di a n S u n d ar b a n: a n i nt e gr at e d st u d y e m p lo yi n g [27] Adger WN , P ul hi n JM, B ar n ett J , D a b el k o GD , Hovelsrud G K, Le v y M, et al . H u m a n s e- geoinfor matics. Environ ment a n d earth observation. Springer International Publishing; curily. Ca mbridge University Pres s; 2 0 1 4. 2 0 1 7. p. 1 9 5- 2 1 3. [ 2 8] Mortreux C, d e C a m p o s R S, A d g er WN , G h os h T, D as S, A d a ms H, et al. P olitical e c o n- (60] Hazra S, Bak shi A. Environ mental refugees fro m vanishing islands. I n: Bhattacharya P, o m y of pl a n n e d relocation: a m o d el of a cti o n a n d i n a cti o n i n g o v er n m e nt responses. Hazra S, editors. Environ ment a n d h u m a n security. India: Lancers Books Publi cations; Gl o b E n vir o n C h a n g. 2018;50:123-32 . 2 0 0 3. p. 2 1 9- 2 7. [ 2 9] d e C a m p o s RS , Codjoe S N A, Adger W N, M ortr e u x C, H a zr a S, Si d di q ui T, et al. W h er e [ 6 1] H a zr a S, G h o s h T, D a s g u pt a R, S e n G. S e a l e v el a n d a s s o ci at e d c h a n g es i n t h e p e o pl e li v e a n d move in deltas . Deltas i n the Anthropocene. Cha m: Palgrave Mac mil - Sundarban. J Science a n d C ul t ur e. 2 0 0 2; 6 8( 9- 1 2): 3 0 9- 2 1. l a n; 2 0 2 0; 1 5 3- 7 7. [ 6 2] D u b e S K, R a o A D, Si n h a PC , Murty TS, Bahulayan N. St or m s ur g e i n t h e B a y of Be n g al [ 3 0] I P C C. Cli m a t e c h a n g e 2 0 0 1: i m p a cts, ad a pt ati o n, a n d vulnerability. Contrib ution of a n d Arabian Sea: the proble m a n d its prediction. Mausarn. l 9 9 7; 4 8( 2): 2 8 3- 3 0 4. working group II t o t h e t hir d ass ess m e nt report. Ca mbridge, U K: Ca mbridge University [63] Singh OP. Long t er m tr e n ds i n t h e fr e q u e n c y of s evere cyclone of Bay of Bengal: obser- Pr e ss; 2 0 0 1. v ati o n a n d si mulations. Mousa m. 2 0 0 7; 5 8( 0: 5 9- 6 6. [ 3 1] I P C C. I n: P arr y M L, Canziani OF , Palutikof JP, van d er Li n d e n PJ , H a n s o n CE , e dit ors. [ 6 4] Si n g h O P, Ali k h a n T M , R a h m a n M S. H as t h e fr e q u e n c y of intense tropical cyclones in- Cli m at e c h a n ge 2007: i mpacts, a d a pt ati o n a n d vulnerability. Contribution of w or ki n g cr e as e d i n the North Indian Ocean? Curr Sci. 2 0 0 2; 8 0( 4): 5 7 5- 8 0. gr o u p II t o t h e fourth assess m e nt r e p ort of t h e i nt erg o v er n m e nt al p a n el o n cli m at e [ 6 5] S c h n ei d er S H, Se menov S, P at w ar d h a n A, B ur to n !, Magadza C H D , O p p e n h ei m er M, change. Ca mbrid ge, U K: C a m bri d g e U ni v ersit y Pr e ss; 2 0 0 7 [ 9 7 6 p p.]. et al . Assessing key vulnerabilitie s a n d t h e ris k fr o m cli m at e c h a n g e. I n: P arr y M L , [32] Adger WN . Vulnerability . Glob Environ Chang . 2 0 0 6; 1 6( 3): 2 6 8- 8 1. Canziani OF, P al uti k of J P, v a n d er Linden PJ, H a n s o n C E, e dit or s. Cli m at e c h a n g e [33] Fussel H M, Kl ei n RJ T. Cli m at e c h a n g e vulnerability assessments: an evolution of c o n - 2 0 0 7: i m p a cts, a d a pt ati o n a n d vulnerability, c o ntri b uti o n of w or ki n g gr o u p II t o t h e ceptual thinking. Cli m Change. 2 0 0 6 ; 7 5: 30 1- 2 9. fourth assess m e nt r e p ort of t h e I nt er g o ve r n m e nt al P a n el o n Cli m at e Change. Ca m- [ 3 4] A d g er WN , Br o o ks N, Bentha m G, Agne w M, Eri ks e n S. I n: T. R, editor. Ne w indicators bri d g e, U K: Ca mbridge Univer sity Press; 2007. p. 7 7 9- 8 1 0. of v u l ner a bilit y a n d a d a pti v e c a p a cit y. U K: T y n d all C e ntr e f or Cli m at e C h a n g e Re- [ 6 6] E bi K, K o v a ts RS , M e n n e B. A n a p pr o a c h f or assessing h u m a n health vulnerability a n d s e ar c h; 2 0 0 4. p u bli c h e alt h interventions t o a d a pt to cli mate change. Environ Health P er s p e ct 2 0 0 6; [35] Brooks N, N eil A d g er W, Mi c k Kell y P. T h e d et er mi n a nt s of vulnerability a n d a d a pti v e 1 1 4: 1 9 3 0- 4. c a p a cit y at t h e n ati o n al l e v el a n d t h e i mplications for adaptation. Gl o b Environ Chang . [67] Adger W N, A gr a w al a S, Mir z a M M Q, C o n d e C, O' Bri e n K, P ul hi n J, et al . Assess ment of 2 0 0 5; 1 5( 2): 1 5 1- 6 3. a d a pt ati o n practices, o pti o n s, c o n s tr ai nts a n d c a p a cit y . I n: P arr y M L , C a n z ia ni O F , [ 3 6] Brook s Nick. Vulnerability, risk a n d adaptation: a conceptual fra me work. Tyndall Cen - Palutikof J P, van d er Linden PJ, Hanson C E, editors. Cli mate c h a n g e 2 0 0 7 : i m p a cts, a d- tre for cli mate c h a n ge research working paper, 3 8 . ; 2 0 0 3. p. 1- 1 6 . a pt ati o n a n d vulnerabilily . Contribution of w or ki n g gr o u p II t o t h e fourth assess ment [37] Cutter Susan L, Boruff Bryan J, Lynn Shirley W. Social vulnerability t o e n vir o n m e nt al re p ort of t h e I ntergovern mental Panel o n Cli mat e Change. Ca mbridge , U K: C a m bri d g e hazards. Social science quarterly . 2 0 0 3; 8 4( 2) :2 4 2- 6 1 . U ni v er sit y Pr ess; 2 0 0 7. p. 7 1 7- 4 3 . [ 3 8] K ell y P M, A d g er W N. T h e or y a n d pr a cti c e i n assessing vulnerability to cli mate c h a n g e [ 6 8] O' Bri e n K, L ei c h e n k o R, K el k ar U, V e n e m a H, A a n d a h l G, T o m p ki n s H, et al. M a p pi n g a n d facilitating adaptation. Cl i m Change . 2 0 0 0; 4 7( 4): 3 2 5- 5 2. vulnerability t o multiple stressors: cli mate change a n d globalization i n I n di a. Gl o b E n - [39] Nguyen C V. D e v e lo p m e nt a n d application of a social vulnerability i n d e x at t h e l o c al viron Chang. 2 0 0 4; 1 4: 3 0 3- 1 3. s c al e; 2 0 1 5. [69] Pol sky C, N eff R, Y a m al B. B uil di n g c o m p ar a b l e gl o b al c h a n g e v u ln er a bilit y as- [ 4 0] Fritzsche K, Schneiderbauer S, Bubeck P, Kienberger S, B ut h M, Z e bis c h M, et al T h e s e s s m e nt s: t h e v ul n er a bilit y s c o pi n g di a g r a m. Gl o b E n vir o n C h a n g. 2 0 0 7; 1 7: vulnerability sourcebook: concept a n d guidelines for standardised vulnerabi lit y ass ess- 4 7 2- 8 5. ments. Ver lag ni c ht er mittelbar; 2014. [70] Sullivan C. Calculating a w at er poverty index. World D e v. 2 0 0 2; 3 0: 1 1 9 5- 2 1 0. [41] Nicholls RJ, H utt o n C W , L a z ar A N , All a n A, A d g er W N , A d a m s H, et al. I nt e gr at e d [ 7 1] Z ur o v e c 0, C a dr o S, Sit a ul a B K. Q u a ntit a ti v e a s s e s s m e nt of vulnerability to c li m at e a s s e s s m e nt of s o ci a l an d e n vir o n m e nt al s u st ai n a bilit y d y n a mi c s i n t h e G a n g e s- c h a n g e i n r ur al municipaliti es of B o s ni a a n d Herzegovina. Sustainability. 2 0 1 7 ;9( 7) : Brah maputra- Me g h n a d elt a , B a n gl a d e s h. E st u ar C o a st S h elf S ci. 2 0 1 6; 1 8 3: 1 2 0. 3 7 0- 8 1. [ 7 2] A nt o n y GM , R a o K V . A co mposite index to explain variations in poverty, health, nutri- [ 42] Nicholls RJ, Ad ger W N, H utt o n C W , Hanson S E, editors. Deltas i n the Anthropocene . ti o n al s t at u s a n d s t a n d ar d of living: use of m ulti v ari at e statistical m et h o d s. P u bli c P al gr a v e. I S B N 978-3-030-23517-8; 2019. H e alt h . 2 0 0 7; 1 2 1: 5 7 8- 8 7.

1 2 / S. D as et a L Pr o gress i n Disaster Science 7 ( 2 0 2 0) 1 0 0 1 1 0

[ 7 3] A n n a s I, G a vris A. Social vulnerability assess ment using spatial multi-criteria analysis [ 1 0 0] S u S, Pi J , W a n C, Li H, Xi a o R, Li B. categorizing social vulnerability patterns i n C hi- ( S E VI m o d el) a n d t h e Social Vulnerability Index (So VI model)-a case study for Bucha- nese coastal cities. Ocean Coas t Manag . 2 0 1 5; 1 1 6: 1- 8. rest, Ro mania. Natural hazards a n d e art h syste m sciences. 2013;13(6):1481. [101] Mccarthy JJ, C a n zi a ni O F , L e ar y N A, Dokken DJ , White K S. Cli m at e c h a n g e 2 0 0 1: i m- [ 7 4] A n n ~ J uli a n a, Gavri~ Alexandro . Census-based social vulnerability assess ment for B u- p a cts , a d a pt ati o n a n d vulnerability. Ga mbridge: Ca mbridge University Press; 2001. c h ar e st Procedia Environ mental Sciences. 2 0 1 6; 3 2: 1 3 8- 4 6. [ 1 0 2] Br e n k ert A L, M al o n e EL . Modeling vulnerability a n d resilience to cli m at e c h a n g e: a [75] Dunning C M, Durden S. Social vulnerability analysis m et h o d s for corps planning. U S c as e st u d y of I n di a a n d Indian states. Cli m Change . 2 0 0 5 ;7 2 :5 6 . A n n y C or ps of Engineers. 2011 R e p ort A v ail a bl e at:. htt ps: //w w w.i wr.usace.ar my. [103] Dhar A. Workforce participation a m o n g t h e elderly in India: struggling for e c o n o mi c mil/ Portals/70 /docs/ i wrreports /2011- R-07 . pelf. security. Indian J Labour Econ. 2014;57(3). [76] Dunning C Mark , Durden Susan E. Social vulnerability analysis: A co mparison of t o ols. [ 1 0 4] M a n n.il a S. I nf or m al e m pl o y m e n t a n d vulnerability in less developed markets. Sustain- Institute for. Water Resources; 2013. a bl e working lives. Dordrecht: Springer; 2015; 1 7- 3 3 . [ 7 7] Fekete Alexander. Validation of a social vulnerability index i n c o nt e xt t o ri v er-fl o o ds i n [105] Vincent K. Uncertainty i n adaptive capacity a n d t h e i mportance of s c al e. Gl o b E n vir o n Ger many. Natural Hazards a n d E art h Syste m Sciences. 2009;9(2):393-403 . C h a n g . 2007;17(1):12-24 . [78] Fotso J, Kuate-defo B. Measuring socioecono mic status in h e alt h research in develop- [106] Yoo G, H wang J H, Choi C. Develop ment a n d application of a methodology for vulner- ing countries: should w e b e f o c usi n g o n households, co m munities, or b ot h ? S o ci al I n- ability assess ment of cli m at e c h a n g e i n coastal cities. Ocean Coast Manag. 2011;54(7): dicators Research. 2 0 0 5; 7 2: 1 8 9- 2 3 7. 5 2 4- 3 4. [79] Holand Ivar S, L uj al a P ai vi, R 0 d J a n Ketil. Social vulnerability assess ment for Nor way: [107] Bryant C R, S mit B, Br kl a ci c h M, J o h n st o n T R, S mit h ers J , C hi otti Q, et a!. Adaptation in a quantitative approach. Norsk Geografisk Tidsskrift- Nor wegian J o ur n al of G e o gr a p h y. Canadian agriculture to cli matic variability a n d change. Societal a d a pt ati o n to cli mate 2011;65(1):1-17 . varia bilit y a n d c h a n g e . Dordrecht: Springer; 2000; 1 8 1- 2 0 1. [ 8 0] Kris h n a n Vij a y a Constructing a n area-based socioecono mic index: a principal co mpo- [108] Brooks N, A d g er W N. Ass essi n g a n d e n h a n ci n g a d a pti v e c a p a cit y. A d a pt ati o n p oli c y n e nt s a n al ysis a p pr o a c h . Ed monton , Alberta: Ear ly Child Develop ment Mapping Pro- fra me works for cli mate change: d e v e lo pi n g str at e gi es, p o li ci es a n d m e a s ur e s; 2 0 0 5. j e ct; 2 0 1 0. p. 1 6 5- 8 1. [81] Opiyo F E, W as o n g a O V, N y a n git o MM . M e as uri n g h o u s e h o ld vulnerability to cli mate- [109] Cannon T, T wigg J, R o w ell J. Social vulnerability, sustainable livelihoods a n d dis as- i n d u c e d str ess es i n pastoral rangelands of Kenya: i mplications for resilience progra m- t ers; 2 0 0 3. ming. Pastoralis m. 2014;4(1):10. [110] Spence N, W alt ers D. "Is it safe?" Risk perception a n d dri nl

1 3 /