Urban Climate Risk Assessment Report ( GIS & Remote Sensing Tools based)

Conducted GIS & Remote Sensing Tools based assessment of A-Grade Municipalities and District Councils to Identify the most Climate vulnerable municipalities and District Council of Bangladesh.

Programme title: Municipal Investment Finance (MiF) of United Nations Capital Development Fund(UNCDF) , by Z M Sajjadul Islam

1.0         Glossary:

2.0          Introduction:

3.0         Context of Climate induced hazard

4.0          Methodological approach of assessment of Vulnerability of A-type Municipality:

4.1         Identification of Vulnerable A-Type Municipality:

4.1.1      Location map of all A-type Municipality and selected vulnerable of Municipality(A-type) of Bangladesh

4.2          Division wise GIS analysis and selection of vulnerable Municipality  :

4.2.1      Vulnerability analysis of A-type Municipality of Rajshahi Division

4.2.2     Vulnerability analysis of A-type Municipality of Rangpur Division:

4.2.3     Vulnerability analysis of A-type Municipality of Sylhet  Division :

4.2.4     Vulnerability analysis of A-type Municipality of Mymensingh Division :

4.2.5     Vulnerability analysis of A-type Municipality of Dhaka Division:

4.2.6     Vulnerability analysis of A-type Municipality of Khulna Division:

4.2.7     Vulnerability analysis of A-type Municipality of Barisal  Division:

4.2.8     Vulnerability analysis of A-type Municipality of Chottagram  Division:

4.3.        Vulnerability analysis with other variables ( HIES 2011, NCVA, Literacy,   WB Poverty, general employment )

4.3.1      Analysis  of vulnerability in terms of exposure of heat stress in the future ( 2070-2099) :

4.3.2      Poverty analysis  with  World Bank  head count poverty data  ( Upazila wise)

4.3.3      Primary employment on service

4.3.4     Municipality wise  Literacy rate 

5.0          5.0  Selecting vulnerable District Council

5.1         District wise ratio of poverty  ( District wise  head count ratio  of World Bank)

5.2         District Poverty ranking and selection  ( Source : District wise poverty head count ratio  which published in World Bank website in  November 10, 2016 )

5.3         Selection of  16 District Councils from rank

5.4         GIS Maps on selected  16 District Councils from rank

6.0          Reference

Acronym :

CEGIS    Center for Environmental and Geographic Information Services (CEGIS)

DDM      Department of Disaster Management

GIZ         Deutsche Gesellschaft für Internationale Zusammenarbeit

HIES       Household Income & Expenditure Survey (HIES)

IPCC       Intergovernmental Panel on Climate Change

IPUMS  Integrated Public Use Microdata Series project

LGED      Local Government Engineering Department

NCVA    nationwide climate vulnerability assessment

NWRD   National Water Rescue Database

  Glossary :

Adaptation :

The process of adjustment to actual or expected climate and its effects. In human systems, adaptation seeks to moderate harm or exploit beneficial opportunities. In natural systems, human intervention may facilitate adjustment to expected climate and its effects. See also Autonomous adaptation, Evolutionary adaptation, and Transformation

Adaptive  capacity:

The ability of systems, institutions, humans, and other organisms to adjust to potential damage, to take advantage of opportunities, or to respond to consequences.

Coping capacity:

The ability of people, institutions, organizations, and systems, using available skills, values, beliefs, resources, and opportunities, to address, manage, and overcome adverse conditions in the short to medium term. This glossary entry builds from the definition used in UNISDR (2009) and IPCC (2012a).

Exposure  :The presence of people, livelihoods, species or ecosystems, environmental services and resources, infrastructure, or economic, social, or cultural assets in places that could be adversely affected

Hazard :

The potential occurrence of a natural or human-induced physical event or trend, or physical impact, that may cause loss of life, injury, or other health impacts, as well as damage and loss to property, infrastructure, livelihoods, service provision, and environmental resources. In this report, the term hazard usually refers to climate related physical events or trends or their physical impacts. 

Sensitivity:

The degree to which a system or species is affected, either adversely or beneficially, by climate variability or change. The effect may be direct (e.g., a change in crop yield in response to a change in the mean, range, or variability of temperature) or indirect (e.g., damages caused by an increase in the frequency of coastal flooding due to sea-level rise). 

Vulnerability :

The propensity or predisposition to be adversely affected. Vulnerability encompasses a variety of concepts including sensitivity or susceptibility to harm and lack of capacity to cope and adapt.

2.0  Introduction :

In Bangladesh Municipality (Municipal Corporations)  known as Paurasabha which are the  local governing bodies of the cities and towns in Bangladesh. There are 329 Municipality in eight divisions of Bangladesh. Municipality being categorized(type) as A , B & C based on the infrastructures , sprawling status and economical performance. According to LGED 183 A-type Municipally out of 329.

2.0  Introduction :

In Bangladesh Municipality (Municipal Corporations)  known as Paurasabha which are the  local governing bodies of the cities and towns in Bangladesh. There are 329 Municipality in eight divisions of Bangladesh. Municipality being categorized(type) as A , B & C based on the infrastructures , sprawling status and economical performance. According to LGED 183 A-type Municipally out of 329.

3.0 Context of Climate induced hazard:

Hazard can be defined according to IPCC AR5 as the potential occurrence of a natural or human-induced physical event or trend or physical impact that may cause loss of life, injury, or other health impacts, as well as damage and loss to property, infrastructure, livelihoods, service provision, ecosystems, and environmental resources. In this report, the term hazard usually refers to climate-related physical events or trends or their physical impacts.

Due to climate change Bangladesh is now susceptible to frequent and longer period   flooding, drought, sea level rise, frequent cyclone and storm surge, flash floods, etc. The country’s exposure to hazards is compounded by its population’s vulnerability and lack of resources.  The mostly agrarian economy and   the   high   population   density   leave   large   sections of the population exposed to hazards. The United  Nation’s  (UN)  2014  World  Risk  Report  named  Bangladesh  the  7th  most  ‘at  risk’  country( German watch 2018)   for disaster in the world.

1. Flood is an annual phenomenon generally affecting 30 per cent of the country, but up to 70 per cent in extreme years. Flood-related fatalities are decreasing, but economic losses have been increasing over the years. The government has been developing and implementing various measures to better equip the country to deal with floods. Important initiatives include the flood action plan, flood hydrology study, flood management model study, national water management plan, national water policy, flood early warning study and construction of flood embankments and flood shelters. The flood damage potential is increasing due to climate change, urbanization, growth of settlements in flood-prone areas and overreliance on flood control works such as levees and reservoirs. 

2. Flash floods occur during mid-April before the onset of the south-westerly monsoon. In particular, flash floods can decimate an annual rice crop when they occur at harvest time. Crop  decimation  occurred  four  times  between  2004  and  2014  in  the  Haor  region. The city of Sylhet is also prone to flash floods.
3. Rain-fed floods generally happen in the deltas in the south-western part of the country and are increasing in low-lying urban areas. In 1988, record floods inundated 250 square kilometres (sq km) of Dhaka for 3 weeks. Chittagong   also   experiences   monsoon   related   floods.
4. River floods are the most common; the areas are inundated during monsoon season along the river and in cases far beyond the riverbanks. Extreme flooding occurs when  the  rivers  flood  at  the  same  time,  or  when  the  rivers  flood  during  a  heavy  monsoon.  For  example,  in  2012  Bangladesh’s  northern  region  experienced  a  shorter  than  average  flood  period,  while  the  southwestern  region  of  the  country  experienced flooding for 49 days.
5. Storm surge floods occur along the coastal areas of Bangladesh, which has a coastline of about 800 km northern part of Bay of Bengal

• Drought is seasonal in north-western parts of Bangladesh experience drought in the crop season. During the last 50 years, Bangladesh suffered about severe 20 drought episodes. As much as 20 per cent of the main crop – wet season paddy – may be lost in a typical year due to drought. Drought-prone areas are also affected by cold waves with impacts on human health. There is opportunity for supporting resilience to drought through institutional initiatives. The consultations for developing NPDM 2016-2020 strongly suggested the need for addressing drought though structural and non-structural measures.
• Severe cyclones with storm surges sometimes in excess of ten meters frequently impact Bangladesh’s low-lying coast. GoB has a well-coordinated cyclone forecasting, early warning and evacuation system and the cyclone mortality rate has been reduced greatly from 300,000 in 1971 to 138,882 in 1991 for the same category of cyclone. However, growing and higher concentration of assets has resulted in increasing economic losses. Tornadoes are seasonal and occur in the pre-monsoons season. The frequency of tornadoes in Bangladesh is among the highest in the world. The Brahmanaria tornado of 2013 struck 20 villages and killed 31 people and injured around 500 in Brahmanbaria district.

1. Riverbank erosion is a common problem in Bangladesh due to the deltaic topography and it has been forcing people to migrate or resettle. Riverbank erosion has rendered millions homeless; the majority of slum dwellers in large urban and metropolitan towns and cities are victims of erosion. The major rivers like the Jamuna, the Ganges, the Padma, the Lower Meghna, Arial Khan and Teesta are highly erosion-prone. Structural interventions are costly and need to be complemented by non-structural measures, such as erosion prediction and warning. From 2005, prediction activities were funded by the Jamuna-Meghna River Erosion Mitigation Project (JMREMP) and EMIN project of the BWDB and WARPO, and in 2008, by UNDP. 

• Salinity intrusion is an increasing hazard in the coastal areas of Bangladesh, posing a threat to ecosystems, livelihoods and public health and diminishing access to freshwater for household and commercial use. About 20 million people in the coastal areas of Bangladesh are affected by salinity in their drinking water. Bangladesh Water Development Board (BWDB) undertook studies on groundwater availability and found in some coastal districts there was no freshwater layer as deep as 300 meters; in many cases, saline water was found in aquifers at 200 meters.

4.0  Methodological approach of assessment of Vulnerability of A-type Municipality:

Typically quantitative assessment of vulnerability implies that the first two components together represent the potential impact and adaptive capacity is the extent to which these impacts can be averted. Thus vulnerability is calculated by potential impact (PI) minus adaptive capacity (AC). e.g. 

Formula : Vulnerability(V) = Potential impact (PI) [Exposure (E) + Sensitivity (S)] – Adaptive Capacity (AC)   

Calculation of vulnerable Municipality ( V) =   PI  [Spatial Intensity of Multi-hazard ( E+S)] –  AC (Ranking of % Poverty, % literacy, % employment ).

Main weightage given to spatial distribution of physical hazards (expose & sensitivity in the context of landscape) which occurs in geographical position geo-physical settings, global and regional climatic context etc., and this principal variable being generalized by other socio-economical attributes from census survey)     

Sources of datasets used :

Based on available datasets on spatial distribution of hazards in Bangladesh from available secondary sources e.g 

1. A-type Municipality data from LGED website.
2. Multi hazards: National Water Rescue Database ( NWRD, 2011), Bangladesh Delta Plan(BDP) 2100 (BDP2100 study in 2018 ),  CEGIS multi-hazard GIS analytical maps (2016), GIZ conducted CVRA Dec. 2018, DDM Risk Atlas Oct, 2016 etc.  
3. Field varication also being carried by secondary sources e.g satellite image (google earth, Microsoft bing image map) for verifying the geographical position of Municipality and proximity to climatic hotspot.
4. Social vulnerability attribute information from BBS Census survey 2011, HIES (municipality statistics, Municipality wise literacy rate, and world Bank headcount poverty data – prepared in  November 2016 (combined by the 2010 Bangladesh Poverty Maps, the IPUMS sample from the 2011 Bangladesh Census of Population and Housing, and the 2012 Undernutrition Maps of Bangladesh) , Primary employment: Services, National avg (%)

4.1 Identification of Vulnerable A-Type Municipality:

Considering the geographical settings, and recurrently and historically occurrence of hazards all over the country being synthesized and analized with GIS Maps (GIS Map & data from secondary source), and verification done by overlying hotspot on the ESRI satellite image (world bing image) with ArcGIS software. Total 183 A-Type Municipality inserted as layer and superimposed over the multi-hazard layer on GIS analytical map for getting the vulnerability type and factor.

Multiple factors being e.g. topographical characteristics, riverine morphology, geographical position, intensity & frequency of the occurrence of hazard etc being considered for selection of vulnerable 61, moderate vulnerable 41 and most vulnerable 10 of A-grade municipality.  The closest proximity to climatic hotspots, severity of exposure & vulnerability being further considered for choosing 10 most vulnerable A-grade municipality .

4.1.1  Location map of all A-type Municipality and selected vulnerable of Municipality(A-type) of Bangladesh

Figure 1 : A-Type Municipality(Pourashava) classified  by severity of natural hazards ( Note : Stress the map for more clear view)

Data Source: a) National Water Rescue Database ( NWRD, 2011), Bangladesh Delta Plan(BDP) 2100,  CEGIS, Prepared by Z M Sajjadul Islam

• Division wise GIS analysis and selection of vulnerable Municipality  :  

4.2.1 Vulnerability analysis of A-type Municipality of Rajshahi Division:

Figure 2 : Map  Rajshahi Division, Prepared by Z M Sajjadul Islam

Table 1 : Most Vulnerable Municipality from Rajshahi Division

Kakonhat municipality located in the Barind track region and falling under drought of Bangladesh. Other two most vulnerable municipality spotted as Sujanagar of Pabna and Belkuchi of Sirajganj because affected by multiple hazards riverine Flood & Erosion.

4.2.2 Vulnerability analysis of A-type Municipality of Rangpur Division:

Figure 3 : Map  Rangpur Division, Prepared by Z M Sajjadul Islam

Table2 : Moderate Vulnerable Municipality from Rangpur Division

Data source : a) BBS HIES 2011, National Report-Vol 3, Urban area report in August 2014, b) % of Pop affected by national hazards  of GIZ NCVA (nationwide climate vulnerability assessment in Bangladesh) , Dec 2018, c) Head county poverty data of World Bank ( published in World Bank website in  November 10, 2016 )

Kurigram municipality geographically located on the bank of Dharla river. In case of 1998 floods this township experience flooding over the eastern part. Pachagarh municipality experience moderate flash flood when monsoon characterized by torrential precipitation on the upstream basin .    

4.2.3 Vulnerability analysis of A-type Municipality of Sylhet  Division :

Figure 4: Map  Sylhet Division, Prepared by Z M Sajjadul Islam

Table 3: Severe and Moderate Vulnerable A-type Municipality of Sylhet Division

Data source : a) BBS HIES 2011, National Report-Vol 3, Urban area report in August 2014, b) % of Pop affected by national hazards  of GIZ NCVA (nationwide climate vulnerability assessment in Bangladesh) , Dec 2018, c) Head county poverty data of World Bank ( published in World Bank website in  November 10, 2016 )

Sunamganj is the most vulnerable A-type municipality beside Chatak under Sylhet Division. In every given season this township experience flash flooding and localized riverine flooding. Chatak and Golapganj considered as moderate vulnerable municipality.

4.2.4 Vulnerability analysis of A-type Municipality of Mymensingh Division :

Figure 5: Map  Mymensing  Division, Prepared by Z M Sajjadul Islam

Table 4: Severe and Moderate Vulnerable A-type Municipality of Sylhet Division

Data source : a) BBS HIES 2011, National Report-Vol 3, Urban area report in August 2014, b) % of Pop affected by national hazards  of GIZ NCVA (nationwide climate vulnerability assessment in Bangladesh) , Dec 2018, c) Head county poverty data of World Bank ( published in World Bank website in  November 10, 2016 )

4.2.5 Vulnerability analysis of A-type Municipality of Dhaka Division:

Figure 6: Map  Dhaka   Division, Prepared by Z M Sajjadul Islam

Table 5: Severe and Moderate Vulnerable A-type Municipality of Dhaka Division

Data source : a) BBS HIES 2011, National Report-Vol 3, Urban area report in August 2014, b) % of Pop affected by national hazards  of GIZ NCVA (nationwide climate vulnerability assessment in Bangladesh) , Dec 2018, c) Head county poverty data of World Bank ( published in World Bank website in  November 10, 2016 )

Goalanda municipality annexed to a grater confluence of Padma and Brahmaputra river and highly vulnerable to multiple hazards Riverine  Flood & Erosion

4.2.6 Vulnerability analysis of A-type Municipality of Khulna Division:

Figure 7: Map  Kuhulna   Division, Prepared by Z M Sajjadul Islam

Table 6: Severe and Moderate Vulnerable A-type Municipality of Khulna Division

Data source : a) BBS HIES 2011, National Report-Vol 3, Urban area report in August 2014, b) % of Pop affected by national hazards  of GIZ NCVA (nationwide climate vulnerability assessment in Bangladesh) , Dec 2018, c) Head county poverty data of World Bank ( published in World Bank website in  November 10, 2016 )

From the analysis Morrelganj of Bagerhat District identified as most vulnerable  over the southern bay proximity and similarly Satkhira surrounded by multiple hazards as well in terms of SLR, salinity intrusion and recent cyclonic tract to this region.

4.2.7 Vulnerability analysis of A-type Municipality of Barisal  Division:

Figure 8: Map  Barisal    Division ( legend from Bangladesh map  ), Prepared by Z M Sajjadul Islam

Table 7 : Severe and Moderate Vulnerable A-type Municipality of Khulna Division

Data source : a) BBS HIES 2011, National Report-Vol 3, Urban area report in August 2014, b) % of Pop affected by national hazards  of GIZ NCVA (nationwide climate vulnerability assessment in Bangladesh) , Dec 2018, c) Head county poverty data of World Bank ( published in World Bank website in  November 10, 2016 )

Two municipality under Barisal division are highly vulnerable in terms of proximity to river and bay. The Galachipa Municipality under Patuakhai District identified as most vulnerable municipality and Amtali under Barguna District considered as high- to- moderate vulnerable, but the landscape and infrastructures of the township is better than Galachipa and Kalapara. 

4.2.7 Vulnerability analysis of A-type Municipality of Chottagram  Division:

Figure 9: Map  Chottagram   Division, Prepared by Z M Sajjadul Islam

Table 8 : Severe and Moderate Vulnerable A-type Municipality of Chittagong Division

Data source : a) BBS HIES 2011, National Report-Vol 3, Urban area report in August 2014, b) % of Pop affected by national hazards  of GIZ NCVA (nationwide climate vulnerability assessment in Bangladesh) , Dec 2018, c) Head county poverty data of World Bank ( published in World Bank website in  November 10, 2016 )

Most vulnerable municipalities are  Chengerchar and Chandpur of Chandpur district for positioning at the bank of Meghna and recurrently experience multiple hazards Riverine flooding erosion. Among the other vulnerable districts Khagrachari which heavily being impacted by flash and riverine floods and its becoming recurrent over the past 10 years during monsoon season.

Table 10:  Selected 41  A- type Moderate Vulnerable Municipalities   , Data source : BBS HIES 2011, National Report-Vol 3, Urban area report in August 2014
SL	Division	District	Pourashava	A-Type Pourashava	Area (sq. km.)	Ward	Population (Both sex)	Population Density	Literacy Rate(7+years)	Household	Poverty headcount ratio (%)	Poverty Rank 1 >= high to large number as low	Multi Hazard	Proximity to climatic hotspot(River, Sea and others)
	Barishal	Barguna	Amtali	A	6.22	9	15418	2,479	76.7	3395	22.8	83	Severe tidal flooding	Beside Payra River
	Barishal	Barguna	Barguna	A	15.57	9	32235	2,070	75.9	7353	19.2	86	Severe tidal flooding	Between  Payra & BishKhali River
	Chattogram	Brahmanbaria	Akhaura	A	16.42	9	50068	3,049	52.2	11012	26.9	69	Moderate river Flooding	Beside Titas riiver
	Chattogram	Brahmanbaria	Nabinagar	A	12.43	9	34148	2,747	61.5	7505	30.5	60	Moderate river Flooding	Beside Meghna
	Chattogram	Brahmanbaria	Brahmanbaria	A	15.71	9	118992	7,574	53.6	24057	26.0	71	Moderate river Flooding
	Chattogram	Chandpur	Matlab	A	13.42	9	27595	2,056	54.6	6016	51.5	5	Moderate river Flooding
	Chattogram	Cox’s Bazar	Chakoria	A	27.23	9	36691	7,884	59.2	7884	28.5	62	Moderate river   Flooding
	Chattogram	Cumilla	Chouddagram	A	11.98	9	44364	3,703	55.6	7824	34.4	46	Moderate River Flooding
	Dhaka	Dhaka	Dohar	A	7.99	9	19651	2,459	55.9	3889	23.9	79	Severe river Flooding	Beside Padma
	Dhaka	Faridpur	Faridpur	A	19.07	9	122425	6,189	77.1	27574	38.3	36	Moderate river Flooding
	Rangpur	Gaibandha	Gaibandha	A	3.39	9	21200	6,254	71.5	4967	44.8	16	Moderate river Flooding
	Dhaka	Gopalganj	Tungipara	A	4.85	9	18663	3,848	58.5	4156	42.6	25	Moderate river Flooding
	Sylhet	Habiganj	Nabiganj	A	9.37	9	34015	3,630	68.9	6416	26.8	70	Moderate Flash Flooding
	Sylhet	Habiganj	Habiganj	A	8.97	9	69512	7,749	71.3	13517	16.9	89
	Mymensingh	Jamalpur	Jamalpur	A	53.28	12	142764	2,718	62.1	35619	49.8	9	Moderate river Flooding	Beside old Brahmaputra
	Mymensingh	Jamalpur	Melandaha	A	19.25	9	16569	861	44.4	3997	47.2	12	Moderate river Flooding
	Khulna	Khulna	Paikgachha	A	27.78	9	41608	1,498	55.3	8815	42.4	27	Moderate river Flooding
	Dhaka	Kishoreganj	Bhairab	A	10.5	9	21914	2,087	63.6	5276	33.9	48	Moderate river Flooding	Beside Meghna
	Rangpur	Kurigram	Nageswari	A	13.32	9	102988	7,732	74.8	23037	65.0	1	Moderate river Flooding	Beside Kaljani & Brahmaputra
	Rangpur	Kurigram	Kurigram	A	27.04	9	77252	2,857	63.2	17159	58.0	3	Moderate river Flooding	Beside Dharla
	Khulna	Kushtia	Kushtia	A	6.53	9	20522	3,143	60.3	4218	3.0	99	Moderate river Flooding	Beside Gorai
	Dhaka	Madaripur	Shibchar	A	43.92	9	98355	2,239	65.9	22105	38.8	34	Moderate river Flooding	Close to Padma
	Dhaka	Madaripur	Madaripur	A	7.7	9	21930	2,848	50.2	4077	35.0	45	Moderate river Flooding
	Dhaka	Munshiganj	Munshiganj	A	12.95	9	31,320	2,418.53	45.7	7615	30.8	59	Moderate river Flooding
	Dhaka	Narsingdi	Narsingdi	A	14.75	9	185128	40,661	64.4	8837	22.8	82
	Rajshahi	Natore	Singra	A	29.39		33192	1,129	56.8	7955	37.8	38
	Mymensingh	Netrokona	Mohanganj	A	6.97		27193	3,901	65.8	5786	34.3	47	Moderate river & flash  Flooding
	Rajshahi	Pabna	Bera	A	14.14	9	53157	3,759	51.2	10539	39.4	32	Moderate river Flooding	Beside  Gumani and Brahmaputra
	Rajshahi	Pabna	Santhia	A	42	9	62289	1,483	49.7	15298	33.1	53	Moderate river Flooding
	Barishal	Patuakhali	Kalapara	A	9.95	9	55323	5,560	64.3	10613	20.3	84	Severe tidal flooding	Tidal Flooding
	Barishal	Pirojpur	Mathbaria	A	29.41	9	27700	942	53.8	6541	38.0	37	Severe tidal flooding
	Dhaka	Rajbari	Rajbari	A	32.39	9	113322	3,499	69.3	26896	38.7	35	Moderate tidal surge
	Rajshahi	Rajshahi	Charghat	A	10.23	9	27335	2,672	62.6	7128	31.4	55	Severe river Flooding	Bank of  Padma
	Chattogram	Rangamati	Rangamati	A	64.75		84000	1,297	73.1	18355	7.3	97
	Dhaka	Shariatpur	Shariatpur	A	24.92		49535	1,988	62.5	10908	49.8	8	Moderate river Flooding	Beside Padma
	Dhaka	Shariatpur	Damuddya	A	8.02	9	24154	3,012	65.9	5527	47.9	11	Moderate river Flooding	Beside Padma
	Rajshahi	Sirajganj	Shahjadpur	A	11.07	9	64507	5,827	56.1	14226	41.8	29	Moderate river Flooding	Beside Padma,
	Rajshahi	Rajshahi	Godagari	A	11.07	9	64507	5,827	56.1	14226	44.1	19	Moderate river Flooding
	Rajshahi	Sirajganj	Ullapara	A	12.07		47693	3,951	61.9	10526	36.6	43
	Sylhet	Sunamganj	Chhatak	A	17.31	9	65332	3,774	60.5	11926	23.6	80	Severe Flash Flooding	Beside Surma river
	Sylhet	Sylhet	Golapganj	A	4.98	9	20019	4,020	79.3	3985	14.9	90	Moderate river Flooding	Beside Surma river

Table 10:  Selected 61  A- type overall ( Moderate 41 +   vulnerable 10   yellow + most vulnerable  10) Vulnerable Municipalities , Data source : BBS HIES 2011, National Report-Vol 3, Urban area report in August 2014
SL	District	Pourashava	A-Type Pourashava	Area (sq. km.)	Ward	Population (Both sex)	Population Density	Literacy Rate(7+years)	Household	Poverty headcount ratio (%)	Poverty Rank 1 >= high to large number as low	Multi Hazard	Proximity to climatic hotspot(River, Sea and others)
	Bagerhat	Mongla	A	11.85	9	17311	1,461	68.7	4067	41.9	28	Moderate tidal Flooding
	Barguna	Amtali	A	6.22	9	15418	2,479	76.7	3395	22.8	83	Severe tidal flooding	Beside Payra River
	Barguna	Barguna	A	15.57	9	32235	2,070	75.9	7353	19.2	86	Severe tidal flooding	Between  Payra & BishKhali River
	Barishal	Muladi	A	16.96	9	20490	1,208	62.6	4528	58.2	2
	Brahmanbaria	Akhaura	A	16.42	9	50068	3,049	52.2	11012	26.9	69	Moderate river Flooding	Beside Titas riiver
	Brahmanbaria	Nabinagar	A	12.43	9	34148	2,747	61.5	7505	30.5	60	Moderate river Flooding	Beside Meghna
	Brahmanbaria	Brahmanbaria	A	15.71	9	118992	7,574	53.6	24057	26.0	71	Moderate river Flooding
	Chandpur	Matlab	A	13.42	9	27595	2,056	54.6	6016	51.5	5	Moderate river Flooding
	Chandpur	Chengarchar	A	22.66	9	47477	2,095	76	9635	49.9	7	Severe river Flooding	Beside Meghna
	Chandpur	Chandpur	A	5.13	9	20606	4,017	56.6	4712	45.5	15	Severe river Flooding	Beside Meghna
	Cox’s Bazar	Chakoria	A	27.23	9	36691	7,884	59.2	7884	28.5	62	Moderate river   Flooding
	Cumilla	Chouddagram	A	11.98	9	44364	3,703	55.6	7824	34.4	46	Moderate River Flooding
	Dhaka	Dohar	A	7.99	9	19651	2,459	55.9	3889	23.9	79	Severe river Flooding	Beside Padma
	Faridpur	Faridpur	A	19.07	9	122425	6,189	77.1	27574	38.3	36	Moderate river Flooding
	Gaibandha	Gaibandha	A	3.39	9	21200	6,254	71.5	4967	44.8	16	Moderate river Flooding
	Gopalganj	Tungipara	A	4.85	9	18663	3,848	58.5	4156	42.6	25	Moderate river Flooding
	Habiganj	Chunarughat	A	16.5	9	32444	1,966	62.2	5652	27.5	68	Moderate to severe flash flooding	Beside Khoi nRiver( from india)
	Habiganj	Nabiganj	A	9.37	9	34015	3,630	68.9	6416	26.8	70	Moderate Flash Flooding
	Habiganj	Habiganj	A	8.97	9	69512	7,749	71.3	13517	16.9	89
	Jamalpur	Jamalpur	A	53.28	12	142764	2,718	62.1	35619	49.8	9	Moderate river Flooding	Beside old Brahmaputra
	Jamalpur	Melandaha	A	19.25	9	16569	861	44.4	3997	47.2	12	Moderate river Flooding
	Khagrchhari	Khagrachhari	A	13.05	9	47278	3,623	71	10247	19.5	85
	Khulna	Paikgachha	A	27.78	9	41608	1,498	55.3	8815	42.4	27	Moderate river Flooding
	Kishoreganj	Bhairab	A	10.5	9	21914	2,087	63.6	5276	33.9	48	Moderate river Flooding	Beside Meghna
	Kurigram	Nageswari	A	13.32	9	102988	7,732	74.8	23037	65.0	1	Moderate river Flooding	Beside Kaljani & Brahmaputra
	Kurigram	Kurigram	A	27.04	9	77252	2,857	63.2	17159	58.0	3	Moderate river Flooding	Beside Dharla
	Kushtia	Kushtia	A	6.53	9	20522	3,143	60.3	4218	3.0	99	Moderate river Flooding	Beside Gorai
	Madaripur	Kalkini	A	14.22	9	62690	4,409	73.1	14112	33.2	52	Moderate river Flooding
	Madaripur	Shibchar	A	43.92	9	98355	2,239	65.9	22105	38.8	34	Moderate river Flooding	Close to Padma
	Madaripur	Madaripur	A	7.7	9	21930	2,848	50.2	4077	35.0	45	Moderate river Flooding
	Munshiganj	Mirkadim	A	30.92	9	59286	1,917	63	13682	30.8	58	Moderate river Flooding
	Munshiganj	Munshiganj	A	12.95	9	31,320	2,418.53	45.7	7615	30.8	59	Moderate river Flooding
	Mymensingh	Gafargaon	A	5.39	9	29325	5,441	67.7	6513	43.9	21	Moderate river Flooding	Beside old Brahmaputra
	Narsingdi	Narsingdi	A	14.75	9	185128	40,661	64.4	8837	22.8	82
	Natore	Singra	A	29.39		33192	1,129	56.8	7955	37.8	38
	Netrokona	Mohanganj	A	6.97		27193	3,901	65.8	5786	34.3	47	Moderate river & flash  Flooding
	Pabna	Bera	A	14.14	9	53157	3,759	51.2	10539	39.4	32	Moderate river Flooding	Beside  Gumani and Brahmaputra
	Pabna	Sujanagar	A	26.9	9	42299	1,572	81.7	9945	35.4	44	Severe river Flooding	Beside Padma, Severe flood prone
	Pabna	Santhia	A	42	9	62289	1,483	49.7	15298	33.1	53	Moderate river Flooding
	Panchagarh	Panchagarh	A	5.53	9	16017	2,896	65.9	3788	24.2	77	Moderate Flash Flooding	Beside Korotoa River and Talma in ease side
	Patuakhali	Galachipa	A	12.57	9	29098	2,315	67.7	6569	26.0	73	Severe tidal flooding	Beside Galachipa
	Patuakhali	Kalapara	A	9.95	9	55323	5,560	64.3	10613	20.3	84	Severe tidal flooding	Tidal Flooding
	Pirojpur	Mathbaria	A	29.41	9	27700	942	53.8	6541	38.0	37	Severe tidal flooding
	Rajbari	Goalanda	A	27.15	9	59148	2,179	63.3	11460	50.5	6	Severe river Flooding
	Rajbari	Pangsha	A	26.29	9	38704	1,472	47.9	9319	45.7	14	Moderate river Flooding	Beside Padma
	Rajbari	Rajbari	A	32.39	9	113322	3,499	69.3	26896	38.7	35	Moderate tidal surge
	Rajshahi	Kakonhat	A	24.92	9	49535	1,988	62.5	10908	44.1	20	Severe Dorught Prone	Severe Dorught Prone
	Rajshahi	Bagha	A	11.69		27623	2,363	55.4	7044	33.6	49
	Rajshahi	Charghat	A	10.23	9	27335	2,672	62.6	7128	31.4	55	Severe river Flooding	Bank of  Padma
	Rangamati	Rangamati	A	64.75		84000	1,297	73.1	18355	7.3	97
	Satkhira	Satkhira	A	6.35	9	23314	3,671	57.5	4513	43.1	23	Moderate Tidal  Flooding	SLR, Tidal Floods, Salinity
	Shariatpur	Shariatpur	A	24.92		49535	1,988	62.5	10908	49.8	8	Moderate river Flooding	Beside Padma
	Shariatpur	Damuddya	A	8.02	9	24154	3,012	65.9	5527	47.9	11	Moderate river Flooding	Beside Padma
	Sirajganj	Belkuchi	A	28.49	9	158913	5,578	63.2	35556	42.5	26	Severe River Flooding	Beside Brahmaputra River
	Sirajganj	Shahjadpur	A	11.07	9	64507	5,827	56.1	14226	41.8	29	Moderate river Flooding	Beside Padma,
	Rajshahi	Godagari	A	11.07	9	64507	5,827	56.1	14226	44.1	19	Beside padma	Moderate river Flooding
	Sirajganj	Sirajganj	A	5.33	9	19866	3,727	62.8	3784	36.7	42	Severe river Flooding	Beside Brahmaputra River
	Sirajganj	Ullapara	A	12.07		47693	3,951	61.9	10526	36.6	43
	Sunamganj	Sunamganj	A	11.08	9	25461	2,298	44.6	5833	25.1	76	Severe Flash Flooding	Confluence of Surma and Wahumgi river
	Sunamganj	Chhatak	A	17.31	9	65332	3,774	60.5	11926	23.6	80	Severe Flash Flooding	Beside Surma river
	Sylhet	Golapganj	A	4.98	9	20019	4,020	79.3	3985	14.9	90	Moderate river Flooding	Beside Surma river

4.3.  Vulnerability analysis with other variables ( HIES 2011, NCVA, Literacy,   WB Poverty, general employment )

4.3.1  Analysis  of vulnerability in terms of exposure of heat stress in the future ( 2070-2099) : A-type Municipality superimposed over the GIZ NCVA map (nationwide climate vulnerability assessment in Bangladesh)  

Figure 10: Map  heat stress , Data source : Map ofGIZ NCVA map (nationwide climate vulnerability assessment in Bangladesh) , Dec 2018( Prepared by Z M Sajjadul Islam )

4.3.2    Poverty analysis  with  World Bank  head count poverty data  ( Upazila wise)

Figure 11: Map Poverty 

Data Source : Head county poverty data of World Bank ( published in World Bank website in  November 10, 2016 )

4.3.3    Primary employment on service :- Vulnerable Municipality  normalized by Primary employment at service sector( Upazila wise) of World Bank Data  on Primary employment on service :

Figure 11: Map Poverty , Data Source : Head county poverty data of World Bank ( published in World Bank website in  November 10, 2016 ), Prepared by Z M Sajjadul Islam

4.3.3    Primary employment on service :- Vulnerable Municipality  normalized by Primary employment at service sector( Upazila wise) of World Bank Data  on Primary employment on service :

Figure 12: Employment Status , Source : Primary employment on service data of World Bank ( published in World Bank website in  November 10, 2016 ), Prepared by Z M Sajjadul Islam

4.3.4     Municipality wise Literacy rate  :- Vulnerable Municipality  normalized by literacy rate (both sex)

Prepared by Z M Sajjadul Islam

5.0 Selection of  vulnerable District Council:

5.1  District wise ratio of poverty  ( District wise  head count ratio  of World Bank)

Figure 13: District poverty map, Source : District wise  head count ratio  of World Bank ( published in World Bank website in  November 10, 2016 )Prepared by Z M Sajjadul Islam ,

5.2 District Poverty ranking and selection ( Source : District wise poverty head count ratio  which published in World Bank website in  November 10, 2016 )

Barisal Division :

Chittagong Division :

Dhaka Division :

Mymensingh Division :

Khulna Division :

Rajshahi Division :

Rangpur Division :

Sylhet Division :

Source :World Bank  https://www.worldbank.org/en/data/interactive/2016/11/10/bangladesh-poverty-maps

5.3   Selection of  16 District Councils from rank

Table  11 :  vulnerable district councils

Table 12 : All District with poverty rank  

Source : District wise poverty head count ratio  which published in World Bank website in  November 10, 2016

5.4 GIS Maps on selected 16 District Councils from rank (poorer & richer) from Divisions

Figure 14: Selected District council on map, Prepared by Z M Sajjadul Islam ,

Table 12  : Total 183 A-Type Municipality/Pourashava   of Bangladesh : Data source : BBS HIES 2011, National Report-Vol 3, Urban area report in August 2014

6.0  Reference :

1.  World Bank interactive poverty map Used 2010 Bangladesh Poverty Maps, the 2011 Census of Population and Housing sample available from the Integrated Public Use Microdata Series project (IPUMS), and the 2012 Undernutrition Maps of Bangladesh.
2. The 2010 Bangladesh Poverty Maps technical report describing the metholody used to construct the zila and upazila national poverty statistics can be accessed at the following link:                  
3. http://www.worldbank.org/en/news/feature/2014/09/30/poverty-maps
4. The Population and Housing Census sample (IPUMS)  dataset can be accessed at the following link: )      https://international.ipums.org/international-action/sample_details/country/bd
5. The undernutrition maps produced by the World Food Program (WFP) are available at the following link:      https://www.wfp.org/content/undernutrition-maps-bangladesh-2012
6. Detailed information describing the construction of the variables and sources is presented below.     
7.  Poverty (among the population):                      
8. Poverty headcount ratio (%): Percentage of the population that lives below the official national upper poverty line.                                                                                                                                                    
9. Extreme poverty headcount ratio (%): Percentage of the population that lives below the official national lower poverty line.                                                                                                                                               
10. Percentage of population in bottom 40%: Percentage of the population in the zila/upazila  that belongs to the bottom 40% of the national real per capita consumption distribution.

Source: Indicators 5, 6, and 7 come from 2010 Bangladesh Poverty Maps. The total number of poor, extreme poor, and population that belongs to the bottom 40% were computed using indicators 5, 6, 7 and indicator 1 (Total population in the zila/upazila).                                                                                                                 

3.  Primary Employment (among working population):                                                                                    

1. Employment in  Agriculture: If employed, sector of employment is agriculture.                                              
2. Employment in    Industry: If employed, sector of employment is industry.                                                      
3. Employment in   Services: If employed, sector of employment is services.                                       

Source: Indicators 16, 17, and 18 were constructed using Question 25 from the 2011 Census of Population and Housing. Question 25 was asked for persons 7 years of age and older who reported being employed. Question. If employed, field of employment 1) Agriculture , (2) Industry, 3) Service    

  GIZ NCVA (nationwide climate vulnerability assessment in Bangladesh) , Dec 2018,

• National Water Rescue Database ( NWRD, 2011), Bangladesh Delta Plan(BDP) 2100,  CEGIS

Please contact for conducting Urban Risk and Vulnerability Assessment of your country at WhatsApp + 88 01711979179 , Skype: zmsajjad, Email : zmsajjad@yahoo.com