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(HIP)
BASELINE STUDY ON
Scaling up Inclusive Resilience amongst Water Logged
Communities in South Western Bangladesh(HIP)Project
REPORT PREPARED BY: Programme Quality, Learning &
Research (PQLR) Unit Islamic Relief, Bangladesh
Project implementing by NARRI
Consortium
Programme Quality Learning and Research Unit (PQLR), Islamic Relief Bangladesh
JANUARY, 2017
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BASLINE REPORT Scaling up Inclusive Resilience amongst Water Logging community in south western Bangladesh
STUDY TEAM MEMBER
Md. Murad Pervez Monitoring and Research Officer Programme Quality, Learning & Research Unit Islamic Relief, Bangladesh Emadul Islam Assistant Monitoring and Research Officer Programme Quality, Learning & Research Unit Islamic Relief, Bangladesh Mahmud Hossain Senior Monitoring and Research Officer Programme Quality, Learning & Research Unit Islamic Relief, Bangladesh Team Leader
Munshi Mahabubur Rahman Coordinator
Programme Quality, Learning & Research Unit Islamic Relief, Bangladesh
Advisor
Md. Moniruzzaman Advisor- Programme Quality, Learning & Research Unit
Islamic Relief, Bangladesh
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ACKNOWLEDGEMENT
Baseline study was conducted for the project titled as “Scaling up Inclusive Resilience amongst Water
Logged Communities in South Western Bangladesh” from 3rd week of December 2016 to 1st week
February 2017.
This report is indebted to efforts of many contributors at various stages. First and foremost, we would
like to give special thanks for the surveyed households, who had allocated their valuable time to conduct
interview with them in their busy schedule. We would like to thank Brother Shabel Firuz, Country Director
of Islamic Relief Bangladesh, without his support this study could never been accomplished. We are
deeply indebted to him for his constant encouragement. He guided and motivated us throughout the
study, making the work easy for us.
We are thankful to Md. Moniruzzaman, Advisor of Program quality learning and research department, for
his continuous technical support for the study. Thanks to study team for good endeavor to conduct the
study. Also thanks to twelve enumerators for their good effort of data collection.
Special thanks go to the project implementing partners and Project staff of the project who provided
necessary support to make sure the baseline successfully.
It is also grateful to Md. Munirul Islam, Programme Manager, CDR department of IRB and Naser Shawkat
Haider, Consortium Manager who trusted to undertake the baseline survey and helped to accomplish it
successfully.
We would like to thank Honorable Country Management Team of IRB for their valuable support to
conduct baseline survey of the project.
Last, but not the least, there is most gratefulness to the ECHO who provided the financial assistance for
implementing the project by which it has been possible to complete the baseline survey.
Munshi Mahabubur Rahman Coordinator Programme Quality, Learning & Research Unit Islamic Relief, Bangladesh
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TABLE OF CONTENTS ACKNOWLEDGEMENT ..................................................................................................................................... 3
ACRONYMS AND ABBREVIATION ............................................................................................................ 6
EXECUTIVE SUMMARY ............................................................................................................................ 7
CHAPTER ONE: INTRODUCTION AND OBJECTIVE OF THE STUDY ......................................................... 11
CHAPTER II: METHODOLOGICAL CONSEDARATION AND CHOICE ........................................................ 13
CHAPTER III: SURVEY FINDING .............................................................................................................. 16
SECTION 3.1: DEMOGRAPHIC INFORMATION ....................................................................................... 16
SECTION 3.2: HOUSING STATUS (FOR ALL WEALTH CATEGORY) .......................................................... 18
SECTION 3.3: ACCESS TO WASH ............................................................................................................ 20
SECTION 3.4: MEMBERSHIP IN VARIOUS ORGANIZATIONS .................................................................. 23
SECTION 3.5: LIVELIHOOD PART (FOR THE EXTREME POOR PEOPLE) .................................................. 24
SECTION 3.6: LOAN AND SAVING STATUS OF THE EXTREME POOR PEOPLE ........................................ 26
SECTION 3.7: FOOD SECURITY ............................................................................................................... 27
SECTION 3.8: LIVELIHOOD (MAKING A LIVING OF THE EXTREME POOR PEOPLE) ................................ 29
SECTION 3.9: MIGRATION STATUS ........................................................................................................ 32
SECTION 3.10: RIGHTS (ACCESS TO GOVERNMENT SERVICES & SOCIAL PROTECTION) ....................... 34
SECTION 3.11: CLIMATE CHANGE AND DISASTER MANAGEMENT ....................................................... 35
3.11.1: Distribution types of Hazards Facing Every Year....................................................................... 35
3.11.2: Damage & Shock status ............................................................................................................. 35
3.11.3: Perception regarding reasons behind water logging ................................................................ 37
3.11.4: Suggestion of the respondent to escape water logging: .......................................................... 37
3.11.5: Pre-cautions against Hazards at the Household Level .............................................................. 38
3.11.6: Early Warning System ............................................................................................................... 39
3.11.7: Training on Climate Change and Disaster Risk Reduction ........................................................ 39
3.11.8: Knowledge about Union Disaster Management Committee (UDMC) ...................................... 39
3.11.9: Services Received from UDMC at Pre, During and After Disaster ............................................ 40
3.11.10: Knowledge about School Management Committee (SMC) .................................................... 40
3.11.11: Service from SMC .................................................................................................................... 40
3.11.12: Knowledge about Cyclone Signal ............................................................................................ 41
3.11.13: During Disaster ........................................................................................................................ 41
3.11.14: After Disaster .......................................................................................................................... 44
3.11.15: Functioning of Disaster Management Institution ................................................................... 46
3.11.15.1: DDMC ................................................................................................................................... 46
3.11.15.2: UZDMC: ................................................................................................................................ 46
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3.11.15.3: UDMC: .................................................................................................................................. 47
3.11.15.4: PDMC: .................................................................................................................................. 47
SECTION 3.16: EDUCATION VULNERABILITY IN THE WATER LOGGING AREA....................................... 48
CHAPTER IV: CONCLUSION AND RECOMMENDATIONS ........................................................................ 51
CHAPTER V: ANNEXURE ........................................................................................................................ 52
5.1: SEASONAL CALENDAR: ................................................................................................................... 52
5.2: TARGET VS REALITY ........................................................................................................................ 53
5.3: Additional table and figure ............................................................................................................ 54
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ACRONYMS AND ABBREVIATION
ACRONYMS &
ABBREVIATION
BDT Bangladeshi Taka
CBDP Community Based Disaster Preparedness
CBO Community Based Organization
Beel Marsh land
CCA Climate Change Adaptation
CCDRR Climate Change and Disaster Resilience
CDR Climate Disaster Resilience
CPP Cyclone Preparedness Programme
CRA Community Risk Assessment
DMC Disaster Management Committee
DDMC District Disaster Management Committee
DLS Department of Livestock Services
DMC Disaster Management Committee
DPH Department of public health
FGD Focus Group Discussion
FFWC Flood Forecasting and Warning Centre
HH Household Head
IGA Income Generating Activities
IRB Islamic Relief Bangladesh
KII Key informant Interview
MFI Micro finance institution
NGO Non-government organization
PQLR Programme Quality, Learning and Research
PIP Project Implementation Plan
PWD Person with Disability
PRA Participatory Rural Appraisal
RRAP Risk Reduction Action Plan
SBDP School Based Disaster Preparedness
SMC School Management Committee
SSP School Safety Plan
SSC Secondary School Certificate
SOD Standing Order on Disaster
STW Shallow Tube-well
UDMC Union Disaster Management Committee
UP Union Parishad ( The lowest tier of local government)
Upazilla Sub-District
URA Urban Risk Assessment
UzDMC Upazila Disaster Management Committee
VGD Vulnerable Group Development
VGF Vulnerable Group Feeding
WFP
World food Program
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EXECUTIVE SUMMARY
Water-logging is a pressing concern at the backdrop of climate change that becomes worsens for the people of southwest Bangladesh (Awal, 2014). Three coastal districts of the South West Bangladesh (SWB) have been experiencing problems of water-logging since the early 1980s. Although the dimension of water logging problem was little in the initial stage that slowly increased over the years but the situation has been compounded from 2006 (Unnayan Onneshan, 2006). The most vulnerable Upazilas in terms of damage are Monirampur, sadar, Keshabpur and Jhikargacha of Jessore district. In a view to reduce the vulnerability a project named “Scaling up Inclusive Resilience amongst Water Logged Communities in South Western Bangladesh” has been implementing in two districts (Jessore & Sathkira). The baseline was to explore benchmark vulnerabilities and shocks of the targeted areas. Quantitative and qualitative methods were used for conducting the baseline survey. Quantitative (questionnaire) survey conducted covered 400 households on the basis of simple random, stratified and purposive sampling. For data entry, descriptive statistics and bi-vitiate analysis has been done by using Microsoft Access, Excel and SPSS. The study was carried out in three upazilla named Monirampur, Keshobpur and Satkhira sadar of respective two project implementation district including Jossore and Satkhira. On the basis of wealth ranking, the study took interviewed proportionately 7 percent from rich people, 23 percent middle class or better off, 40 percent poor and 30 percent from extreme poor people. It is mentioned that both livelihood and CCDRR related data was collection from only from extreme poor category people while rest of the three categories HH were covered with only CCDRR related information.
MAJOR FINDING OF THE STUDY Demographic information: Average family size of the HH is 4 where male and female members’ ratio is likely same 51 percent and 49 percent. The sum of the total family member of the surveyed HHs is 1597. Of them, 2 percent is physically challenged; 56 percent HH members are economically active aged (18-64) while 44 percent is children and old aged. In terms of household head, 86 percent are male while 14 percent female.
Housing condition: Most of the wealth categories HHs are living in owned houses except extreme poor people. Among the extreme poor people 22 percent are living neighbor or relatives’ houses. 34 percent HHs living house structure is semi-pcca, 26 percent Tali/tine/bamboo, 16 percent mud/straw, 12 percent Pacca and 5 percent house made by thatched. 80 percent very poor people’s houses have made by the thatched, tali/ bamboo/ tin, and mud/straw while rich people are living in pacca (brick built)/semi-pacca building. By the last water logging and hailstorm, 77 percent houses were damaged. The compare with wealth ranking among the extreme poor households 98 percent houses were damaged in the last year by the natural calamities. Of them, 53 percent houses were significant damaged and 45 percent were minor damaged. Water and sanitation: All of the surveyed households are using safe drinking water. Of which, 96 percent deep and STW tube-well while 7 percent use supply water. 61 percent households reported existing water sources is not sufficient to meet their demand round the year. During the last the water logged in the respective areas’ people suffered safe drinking water. Of them, suffering ratio was high among the satkhira’s people. In-terms of sanitation 17 percent HHs have access to sanitary latrine, 46 percent slab latrine, 20 percent slab (without ring), 11 percent hanging latrine and 6 percent open defecation. On the other hand, apex proportion extreme poor of households, 92 percent, are deprived from sanitary latrine where 14 percent HH are habituated of open defecation. Moreover, 50 percent extreme poor households have no any type of toilet. Water borne and contaminated water related disease : In terms of confront water borne related disease, in last year 59 percent HHs suffered water borne and contaminated water related diseases including diarrhea, dysentery, skin disease, cholera, typhoid, jaundice etc. Among the extreme poor people the suffering ratio by water borne disease was high which was 75 percent.
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Membership in organizations: 28 percent respondents are member of various organizations. All of the poor and extreme poor people are only member of microfinance institutions while rich and middle class people are member in disaster management committee and school management committee, etc.
LIVELIHOOD PART (FOR THE EXTREME POOR PEOPLE)
Average Income, expenditure and asset of the HH: Average monthly income of the extreme poor
households is BDT 4620 while average monthly expenditure is BDT 4632 that means monthly deficiency is
BDT 12. Average productive assets value of the extreme poor people is 5880 BDT while non-productive
assets value is BDT 4386. In addition, only 1 percent extreme poor HHs have cultivable land.
Loan and saving status of the extreme poor people: 19 percent households took loan in the last one year and average loan amount is BDT 16181. It is mentioned that huge number (48%) of HHs took loan for house renovation. 23 percent households have savings which average amount BDT 2639. Food security: Surveyed extreme poor households are suffering food insecurity. 22.5 percent can ensure three meals year round in a day properly. In terms of food consumption scoring, 42 percent HHs are in acceptable dietary cluster while 53 percent HHs are in borderline and 5 percent households are in poor dietary cluster. Livelihood option (Occupation): In terms of livelihood of the extreme poor people, 57 percent are making a living by the day laboring, 19 percents by the rickshaw pulling and motor driving, 5 percent maid servant, 5 percent small business, 4 percent agriculture, 3 percent livestock rearing, 2 percent fishing and 2 percent grocery shop. Livelihood skill: 75 percent HHs have no livelihood skill, 6 percent households have impressive skill, 7 percent is good, 8 percent is fair and 4 percent HHs have poor skill. In terms of receiving skill development training, only 11 percent HHs received skill development training from training providing organization especially NGO.
Alternative climate adaptive livelihood: 21 percent extreme poor people are engaged in alternative livelihood like livestock rearing, poultry rearing, crops and vegetable cultivation, fish cultivation and small business. As a satisfaction level from alternative livelihood, 88 percent HHs reported they are not satisfied with the present form of alternative livelihood option. The reasons of dissatisfaction are lack of capital, water logging, lack of skill & knowledge about climate adaptive livelihood options, salinity, etc.
Suitable climate adaptive livelihood option: In terms of suitable climate adaptive livelihoods in the study locality, the people reported these are water tolerable crop and vegetable cultivation, homestead gardening, bag gardening, fish cultivation, cow rearing, goat and sheep rearing, duck and poultry rearing, small business and crab cultivation and fattening etc. Of these, the respondents reported livestock, crab cultivation and fattening and water tolerable crop and vegetable cultivation are most suitable.
Migration Status: 27 percent targeted people usually migrate for hunting job. Migration tendency have seen among satkhira’s people is higher than other areas. Of them, 80 percent usually migrated to urban area while 20 percent migrated to rural area. Migration rate is higher in July to October because at that time in their locality it is difficult to manage work owing to water logging.
Access to government services & social protection: 62 percent very poor people never approached to get government services while average 14 approached but didn’t get services. Following by 12 percent HHs always get support and similarly 12 percent sometimes gets support. In terms of social safety net services, a total 40 percent HHs received VGF support, 3 percent VGD, 3 percent widow allowance, 3 percent elderly allowance and 2 percent disable allowance.
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CLIMATE CHANGE AND DISASTER MANAGEMENT
Types of Hazards Facing Every Year: The project areas are highly vulnerable for four types of disaster. Types of hazards varied from areas to areas. All four project implementation areas have been facing water logging problem. In addition, salinity problem exists in only one area, namely Satkhira. However, the second most common hazards in all four areas are cyclone and other disaster is hailstorm.
Damage & Shocked status: The last water logged almost 70 percent HHs were affected mostly or partially. It should be noted that 25 percent HHs damaged totally, due to water log. Almost 30 people died in from snack bite in the respective three study areas.
Perception regarding reasons behind water logging: Reasons of water logging are: 1. Siltation in the major river, 2. Unplanned growth of shrimp farming, 3. Encroachments of river bank by the local elite, 4. In absence of regular excavation of canal and river, 5. Local level political influences are visible in making conflict between shrimp farming and indigenous farming, etc.
Pre-cautions against Hazards at the Household Level: In terms of disaster preparedness only 30 percent household have preparedness against hazards and rest of 70 per cent household has no pre-caution. Rich HH is more prepared than ultra poor household.
Early Warning System: 52 percent respondents mentioned there is no early warning system exists in their locality, while 39 percent mentioned they have idea about early warning. The rest of 9 percent told that they don’t know anything about early warning system.
Training on Climate Change and Disaster Risk Reduction: The rate of receiving training about CCA and DRR issues among the respondents is very poor. Out of 400 respondents only 1 (0.5 per cent) received training about DRR issues.
Knowledge about Union Disaster Management Committee (UDMC): 17.5 percent respondents stated that they have idea about UDMC. Of them, 24.3 percent HH have access to UDMC at pre disaster period.
Knowledge about Cyclone Signal: Cyclone signal knowledge among the respondent is poor, only 43 percent respondents know about cyclone signal and rest of 57 percent have no knowledge about cyclone signal.
Took shelter during Disaster: During the disaster 50 percent respondents stated they stayed in own house, 10 stated they stayed in relative house and 40 percent took shelter on roadside, embankment, shelter center and school building. In addition among the four categories, among the very poor people almost 70 percent took shelter on roadside, embankment, shelter center and school building.
Disaster management institution: DDMCs of Jessore and Satkhira are functioning. They arrange regular meeting. DDMC members received training on master trainer and they are aware on SOD and CBDP, SBDP, Resilient Livelihood model.
In terms of UzDMC, all of the UzDMCs are formed but not functioning. They do not arrange meeting regularly. Only conduct need based meeting especially during emergency.
In terms of UDMC, 100 percent UDMC are formed but most of these are not functioning. Neither they conduct monthly meeting nor quarterly meeting.
In addition, PDMC of Monirampur Pourashova has knowledge on CRA. They were involved CRA process previously, which was conducted in Monirampur Pourashova with the funding of World Bank project. But after finish the project their activities have been fizzled out.
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EDUCATION VULNERABILITY IN THE WATER LOGGING AREA
85 percent schools were affected by the last water logged. Of them, 89 per cent schools’ education was stopped owing to affected by the water logging. Due to water logging school was closed average 48 days. 55 percent schools were closed from 51 to 60 days, 20 percent schools was closed 20 -30 days, 13 percent schools 41-50 days, 5 percent schools 31-40 days, 5 percent schools more than 70 days and 3 percent school education were stopped between 61 and 70 days.
Knowledge about SMC varies among the respondent based on their socio-economic status. Total 26 percent respondents have knowledge about SMC and rests of 74 per cent have no knowledge about SMC. The knowledge about SMC is lowest among the poor categories. It is mentioned that in the study area there is no school which has contingency and school safety plan.
INITIATIVE OF POLICY MAKERS AND KEY STAKEHOLDERS TO MITIGATE WATER LOGGED
There are few advocacy committees are exist in the project implementation areas to influence and help to mitigate water logged situation such as Pani (Water) committee, Paribesh bachaw Committee, Nadi Bachaw committee, etc which are not active now. It needs to mentioned, lots of study on water logging have been conducted but specific women & disable related study has not been taken place.
Suggestion of the respondent to escape from water logging: Tidal River management (TRM) is widely appreciated as one important solution to the problem of water-logging, cost effective process of silt management, Multipurpose shelter need to construct in water logged area, Ensure livestock foods and shelter at the time of disaster, Mobilize the DMCs for conducting CRA and URA, Grass plant needed at roadside in order to feed cow at the time of water logging. killa is also necessary to safe crops and livestock. Need to install deep tube-well, repair road and tree plantation.
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CHAPTER ONE: INTRODUCTION AND OBJECTIVE OF THE STUDY
1.1: Introduction and back ground:
his document is a report of the Baseline study of the HIP project of NARRI consortium titled as “Scaling
up Inclusive Resilience amongst Water Logged Communities in South Western Bangladesh”.
Water-logging is a pressing concern at the backdrop of climate change that becomes worsens for the people of southwest Bangladesh (Awal, 2014). Three coastal districts of the South West Bangladesh (SWB) have been experiencing problems of water-logging since the early 1980s. Although the dimension of water logging problem was little in the initial stage that slowly increased over the years but the situation has been compounded from 2006 (Unnayan Onneshan, 2006). The situation is expected to worsen more to the days to come. The cost of people’s suffering therefore must be weighed against the cost of adaptation. A recent study conducted by Hassan (2014) detected water-logging area through Landsat imageries from 1972, 1989 and 2014 in Jessore district. A clear tendency of increasing agricultural damage due to water-logging from 1972 to 2014 is observed. The most vulnerable Upazilas in terms of damage are Monirampur, sadar, Keshabpur and Jhikargacha of Jessore district. About 32,830 hectares were identified as waterlogged areas, which is 13% of the total land. From this analysis, it is found that there is an apparent decline of agricultural land between 1972 and 2014. Agriculture land was 218,769 ha in 1972, which reduced to 96,515 ha in 1989 and further reduced to 55,184 ha in 2014. The main reasons for this downward trend include population pressure, natural disaster, salinity, and urbanization as key driving forces. On the other hand, water bodies have gradually increased over the same period. The recent water logging has brought immense sufferings to around 1.3 million people, affected in Bhabodaha area consisting Monirampur, Abhoynagar, Keshobpur upazilas of Jessore and large portions of Phultala and Dumuria upazilas of Khulna district. The prolonged water-logging has caused significant displacement presenting humanitarian challenges in safe water supply, sanitation, shelter, food security, and employment opportunity. There are areas where people are compelled to live in waterlogged condition for nine months in a year; even many\ cultivated crop lands are permanently inundated losing valuable agricultural production especially rice. Socio-economic and agricultural activities have largely been hampered due to water. Water logging is a global phenomenon, but the way of its prevention and mitigations to date have received little attention. Building a disaster resilient Bangladesh’ initiative is now moving towards. With aiming to enhance inclusive resilience of the most waterlogged affected communities in South Western Bangladesh by scaling-up and institutionalizing inclusive community, school and livelihood resilience amongst water logged communities and government service providers “Scaling up Inclusive Resilience amongst Water Logged Communities in South Western Bangladesh” project has been implementing in the two districts of Bangladesh named Jessore & Sathkira. The project area is very much susceptible to water logging and the target of the project is to scaling up the inclusive resilience among the water logged communities in those south-western areas of Jessore and Satkhira. After the success of DIPECHO-VII and DIPECHO-VIII, this particular project focuses on the area of 75 Unions, 36 Urban Wards and 4 Municipalities of Jessore and Satkhira. The action is to strengthen and expand institutionalization of Disaster Management Committees (DMC) by enforcing implementation of Disaster Management Act (DM Act) and Standing Orders on Disaster (SoD). Standardized approach emphasizes consolidation, and replication of the community led inclusive processes as per the CBDP institutionalization model, School Based Disaster Preparedness (SBDP) approach, resilient livelihood practices and advocating for policy implementation and accountability.
T
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This report is an outcome of the baseline study “Scaling up Inclusive Resilience amongst Water Logged Communities in South Western Bangladesh” project for providing benchmark information on the situation the project aims to change, and establish a basis for comparing the situation before and after the intervention, and for making inferences as to the effectiveness of the project. 1.2 Project Overview Project title: Scaling up Inclusive Resilience amongst Water Logged Communities in South Western Bangladesh Overall project objective: Principle Objective of the project is to enhance inclusive resilience of the most waterlogged affected communities in South Western Bangladesh by scaling-up and institutionalizing inclusive community, school and livelihood resilience amongst water logged communities and government service providers in the districts of Jessore & Sathkira. Project’s Expected Results: The main expected results from the project include: Result 1: CBDP model scaled up across water-logged communities, unions and Upazilla to support inclusive risk informed planning and budgeting Result 2: School Safety Plans (SSPs) in line with SBDP model are promoted amongst education stakeholders at district and sub-district levels. Result 3: Resilient livelihood approach promoted and institutionalized amongst relevant union, sub-district and district service providers to support enhanced food security. Result 4: Policy makers and key stakeholders are more responsive to needs and demands of water-logged communities. Result 5: Rapid humanitarian assistance mobilized and delivered when needed by NARRI Target Area of Intervention The project will be implemented in two districts named Jessore and Satkhira covering six Upazilla namely Keshabpur and Monirumpur of Jessore and Tala, Satkhira Sadar, Kolaroa, and Assasuni of Satkhira which will cover 75 Unions, 36 Wards (urban) and 4 Municipalities. Target Group This project intends to directly benefit 52,223 individuals, 1,143 organisations/ institutions, 400 households and 50 officials in the target area of intervention. The total population of the target area, which is 2,370,011 persons, will be indirectly benefited from different efforts of this project. 1.3 Objectives of the study: The objective of the baseline study is to collect data from the primary and secondary stakeholders of the project for identifying the benchmark status of the project. In Particular, baseline assessment identify and record quantitative as well as qualitative data of the community and context of the locality as well as system, knowledge, awareness, attitude, practice, engagement, activeness and other aspects, for measuring the project progress and impact. Specific Objectives of the study are:
To identify and record current scenario of implementation of the Disaster Management Act, Standing Orders on Disaster and Community Based Disaster Preparedness Model at field level and to identify how much ‘sustainable’ and ‘community based’ as well as ‘inclusive’ the ADP allocations are in practice;
To assess Current practices of School Safety among the schools and identify the practice by which the education department is supporting the schools for risk reduction;
To identify and record community based adaptation and coping strategies in response to local disasters and the available institutional capacity at the local level;
To identify and record the existing system, approach, platform, procedure and fruitfulness of driving community voices to influence the policies in responding the demands/needs related to water-logging issues; and
To identify and record existing system and procedure of humanitarian response with quality and in time.
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CHAPTER II: METHODOLOGICAL CONSEDARATION AND CHOICE
The study employed a mixed approach combining qualitative and quantitative method for data collection and analysis. Data was collected from both primary and secondary sources. Primary data was collected through qualitative and quantitative survey. Household survey was applied for quantitative study. On the other hand, PRA tools, FGD, KII, case study and observation, etc were mainly applied for collecting qualitative information from project related stakeholders such as Community people, community leader, DMCs’ members, government officials, SMCs’ members, project implementation officer & project staff. As a part of literature review the study team has gone through different documents by which they captured secondary information.
Scaling up Inclusive Resilience: Water Logged Communities
Research approach & Broad Methods
Quantitative Methods Qualitative Methods
Desk Review of
existing literature,
Project Documents,
Reports, Sampling,
Checklist
Household survey
with structured
questionnaire
Focus Group Discussion : Community
people
KII: with Government Officials, DMCs, SMC
Case study
Observation
Field data/Information collection
Data Analysis & Triangulation
Draft Report Dissemination and Feedback
Final Report
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Literature Review: Literature review covered relevant journal/article, needs assessment reports, project proposal, Project Implementation Plan (PIP), PRA documents, different reports, etc. Study area selection: The project is implementing at 12 unions in 6 sub-districts in Jessore and Satkhira district. However, the baseline study covered 6 unions (Sadar & Pazia under Keshobpur, Sadar & Bhramorajpur under Satkhira and Horidashkathi & Shamkur under Monirumpur) in three sub-districts named Monirumpur, Kesobpur and Satkhira sador. The mentioned unions were selected purposively as the project implementing it’s livelihood activities in this areas.
Sampling Frame: The targeted respondents were identified using probability sampling including lottery, simple random, systematic and stratified sampling technique to represent the target population with study coverage.
Sample selection: The project targeted 52223 HHs in the respective areas. Of them 400 households (considering 95% confidence level and 5% significance level error margin) were selected for the quantitative data collection.
Determination of Sample size: Primary unit of sampling were the households of the project areas. A representative and statistically significant sampling approach was undertaken. The sample was at 95% confidence level with an accuracy rate or amount of admissible error margin of 5%. The following sampling approach and statistical formula was applied for sample design.
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2
)1(..
...
eNqpz
Nqpz
Where, n = Sample size N = Population size e = Precision rate or amount of admissible error in the estimate p = Proportion of defectiveness or success for the indicator q = 1-p z = Standard normal variable at the given level of significance
In the sampling estimate, given values are:
N = 52,223 (total households covered by the project) e = 0.10 (10% significance level/admissible error margin) p = 0.5 q = factor q (1-p) = 0.5 z = 1.96 (value of standard normal variable at 90% confidence level)
As the project targeted total 52,223 numbers of individuals, so the total sample size for baseline was appear 381. In order to compensate for potential dropouts of the sampled households the total sample size increased to 400 households for the Baseline Assessment.
First and foremost out of 6 sub-districts 3 sub-districts were picked up using lottery sampling. From each upazilla or sub-district 2 unions, a total 6 unions were chosen applied purpose sampling as the project implementing it’s livelihood activities in the selected unions. Moreover, from each union 2 wards were selected using systematic samplings.
However, it is mentioned that wealth categories HHs like rich, middle class, poor and extreme poor were identified using PRA tools. As per ratio of wealth category study sample were selected from each category people.
It is noted that out of total 400 households, 120 extreme HHs were covered for both livelihood and DRR component and rest 280 HHs were covered for DRR component from rest of the three wealth categories people.
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Household Survey: The household survey was carried out through structured questionnaires to capture the response from households. A structured and mostly pre-coded questionnaire was developed through a rigorous and systematic process. The survey was covered a total of 400 households from respective 3 areas. The study team reviewed wealth ranking report and list (A, B, C and D 1category), from the project, and chosen respondents from the wealth ranking list using stratified and simple random sampling. Livelihood related data were collected from D category and DRR and other information collected from all categories proportionately.
Key Informant Interviews: KII was conducted with DRRO (1), PIO -3, Upazila livestock officer-3, Upazilla fisheries Officer-3, Agriculture extension Officer-3, UzDMC-3, UDMC-6, and local NGOs. Focus Group Discussion (FGD): A total of 12 FGDs were conducted with community people, UDMCs’ and
SDMCs’ members.
Composition of the study Team: As Consortium Lead, PQLR unit of IRB conducted the Baseline study while the Focal Persons are part of the team for finalizing the design of the assessment. A quantitative data collection team composed of twelve (12) enumerators putted together for the study and divided into 3 sub-teams at field level throughout the data collection process: In each sub-team four members concentrated on collecting quantitative data through household survey whilst the 3 experienced staff from IRB acted as supervisor for all enumerators and they were responsible to collect qualitative data through FGD, KII, In-depth Interview etc. Data clean, analysis and report preparation has been done by
PQLR-team of IRB. Data processing and data analysis: Data inputted in the FoxPro and MS access and editing, cleaning, query have been done by using the MS access and MS-excel. In addition, for analysis, SPSS-19 used to process the data and produce descriptive table and cross table to finalize report. Description analysis (frequency, average, ration, percentage, classification etc) and cross tabulation analysis has been taken place for data analysis. Report preparation The PQLR unit members of IRB were responsible to prepare draft Baseline Assessment Report which has been presented to Islamic Relief Bangladesh and consortium level through a sharing meeting. Attaining feedback and input from the Focal Persons, the final Baseline Assessment Report is produced.
Road map of the study report: The baseline study report has been laid out main five chapters. First
chapter provides a brief analysis of the study background, project overview and objectives of the study.
Second chapter describes methodology of the study including data source, literature review, sample size
and sampling strategies, data collection methods and tools, data management and quality control , data
processing and data analysis etc. Third chapter presents overall finding of the baseline survey, it
categorizes eight sections including demographic profile of respondent, housing condition, economic
status of the households, water sanitation, status of migration, access to social institutions, livelihood
and food security and cclimate change and disaster management. The fourth chapter tried to conclude
and recommend the study and the projects as per finding. The final chapter consist is annexure, it shows
some relevant finding additional table, cross table and questionnaire of the study.
1 A=Rich, B=Middle class, C=Poor, D=Ultra poor
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CHAPTER III: SURVEY FINDING
SECTION 3.1: DEMOGRAPHIC INFORMATION
This section describes demographic characteristics of the baseline survey. It contains the profile of
respondents and household heads as well as basic information of households. This section shows the
basic Information like number of respondents, household size, age, sex, education, occupation, religion,
physical challenge status and marital status etc of the of respondents, household head and household
members. It also provides distribution of wealth break down and area wise population distribution.
3.1.1: The study was carried out among the 400 households (HH) in three upazilla named Monirampur, Keshobpur and Satkhira sadar of respective two project implementation districts including Jossore and Satkhira. Among the three sub-districts 6 unions were covered by the study. For area wise household distribution the below table shows equal proportion HHs was interviewed from each study Upazilla (Sub-district).
Table 1: Area wise household distribution
Area wise household distribution
District Upazila Frequency Percent Jessore Keshabpur 134 33.5
Monirampur 133 33.3 Satkhira Satkhira Sadar 133 33.3 Total 400 100.0
3.1.2: Type of study respondent Considering the project nature, data and information collection process was designed for two types of people like both livelihood & CCDRR and only CCDRR. The below table shows out of 400 HHs, 30 percent HHs were interviewed for both livelihood and CCDRR and rest of the 70 percent were under CCDRR.
Table 2: Type of study respondent
Of them, the below table depicts a total 43 percent respondents were male while 57 percent were female.
Table 3: Gender of the Respondent
Type of study respondent
Respondent type Count Percent%
Both (livelihood & CCDRR) 120 30
CCDRR 280 70
Total 400 100
1.2: Gender of the Respondent
Response Both (livelihood & CCDRR) CCDRR Total
Count Percent Count Percent Count Percent
Male 12 10 159 56.78 171 42.75
Female 108 90 121 43.21 229 57.25
Total 120 100 280 100 400 100
17
3.1.3: Wealth breakdown The research attempted to move away from the typically used terms for wealth categories such as Rich, middle class, poor and extreme poor. The project conducted wealth ranking for the respective areas from where it is found that average 7 percent people are rich, 23 percent middle class or better off, 40 percent poor and 30 percent extreme poor people. The primary determinant and indicator of differences in wealth is monthly family income and ownership of land has given below table.
Table 4: Wealth group characteristic
The study sample size was 400 households. However, on the basis of wealth ranking, the study took interviewed proportionately from similarly 7 percent rich people, 23 percent middle class or better off, 40 percent poor and 30 percent from extreme poor people. It is mentioned that both livelihood and CCDRR related data were collected from only from very poor category people while rest of the three categories HHs were covered with only CCDRR related information. (Please click here to see area wise wealth category respondent).
3.1.4: Household information: The finding of the study reveals that the average family size of the HH is 4 where male and female members’ ratio is likely same 51 percent and 49 percent. The sum of the total family member of the HHs is 1597. Of them, 2 percent is physically challenged. Of them, 4 persons are blind, 3 persons are lame, 3 persons are deaf & dumb and 14 persons are suffering other disabilities. In terms of religion 67 percent Muslim where as 33 percent Hindu. In terms of age distribution, 56 percent HHs’ members are economically active ages (18-64) while 36 percent is children and 8 percent is old aged. In terms of occupation, 13 percent day labour, 5 percent Agriculture, 3 percent service holders, 6 percent livestock rear, 4 percent driving, 4 percent other menial job, 24 percent students, 19 unemployment and 24 percent is child. (Please click here to see area wise household information in annex -2). 3.1.5: Household head information In terms of household head, in Bangladesh household head is male dominated, the study found that 86 percent households are male headed while 14 percent is female. In terms of aged distribution 85 percent HH members are economically active ages (18-64) while 15 percent is old aged. In terms of occupation 32 percent day labour, 15 percent Agriculture, 5 percent service holders, 3 percent fish cultivation or fishing, 3 percent livestock rear, 7 percent pulling rickshaw or van, 5 percent driving, 21 other jobs (small business, hawker, tailor, maid servant etc) and 6 unemployed. (Please click here to see area wise household head’s information in annex -3)
Wealth group characteristic
Category Average monthly Income (BDT) Cultivate Land ( Bigha)
Rich 38,181 16>
Middle Class 14,870 5-15
Poor 7,144 1-3
Extreme Poor 4620 0-1
7%23%
40%
30%
Wealth category wise respondent
Rich
Middle
Poor
Very poor
Figure 1: Wealth category wise respondent
18
SECTION 3.2: HOUSING STATUS (FOR ALL WEALTH CATEGORY)
In this section the study describes housing condition of the survey households like ownership, structure of house, withstand (living house) from strong disaster, home suffered from any damaged in the last any disaster etc. Moreover, here the study tried to analysis area and wealth rank wise housing condition. 3.2.1: Ownership of house
The pie chart indicates that most of the respondents (92 percent) are living at their own houses while rest of the 8 percent living at neighbors/relatives’ houses with free of cost. However, the below table shows, most of the categories HHs are living owned houses except very poor people. Among the extreme poor people 22 percent are living neighbors or relatives’ houses.
3.2.2: Housing structure
It is revealed that the surveyed population is living in different structure houses including Pacca (brick built), semi-Pacca, tali/CI sheet/bamboo, mud/ straw and thatched houses. Of them, the figure shows 34 percent HHs living house structure is semi-pcca. Following by 27 percent Tali/CI sheet/bamboo, 16 percent mud/straw, 12 percent Pacca and 5 percent houses made by thatched.
The below table depicts most of the, 8o percent, extreme poor people houses made by the Thatched, tali/ bamboo/ CI sheet, and mud/straw while rich people are living in pacca and semi-pacca building.
Wealth category wise house ownership status
Ownership of house
Response
Rich Middle class
Poor Very poor Total
Column N % Column N %
Column N %
Column N %
Column N %
Owned 100.00% 98.94% 96.84% 77.69% 91.75% Rented .00% .00% .00% .83% .25% Mortgaged .00% .00% .00% .00% .00% Living free with neighbor/relative
.00% 1.06% 3.16% 21.5% 7.75%
92%
0%
8%
Ownership of House
Owned
Rented
Living free with neighbor/relative
19
Wealth category wise housing structure
Structure of house
Response
Rich Middle
class
Poor Extreme
poor
Total
Column N
%
Column N
%
Column N
%
Column N
%
Column N
%
Cement building
(pacca)
70.37% 24.47% 2.53% .00% 11.50%
Semi-pacca with
tin roof
25.93% 43.62% 39.87% 19.83% 33.75%
Thatched house .00% .00% 3.80% 12.40% 5.25%
Tali/Tine/bamboo .00% 19.15% 25.95% 38.84% 26.50%
Mud/straw .00% 7.45% 17.72% 23.14% 15.75%
Others 3.70% 5.32% 10.13% 5.79% 7.25% 3.2.3: Living house withstand strong disaster In response to the house protection question 30 percent replied that their houses are strong to be safe if there is strong wind, severe rain, flooding or hail. On the other hand, rest of the houses, 70 percent, is not strong. Of them, 12 percent respondents said their house is totally vulnerable while 39 percent houses will be remaining with minor damage. Following by 19 percent said there will be significant damage.
3.2.4: Home suffered from damaged in the last any disaster The study found that in the last disaster especially water logging and hailstorm 77 percent houses were damaged. Of them, the figure shows 30 percent houses were confronted significant damaged while 47 percent houses caused minor damaged. The compare with wealth ranking below table shows, among the
23%
47%
30%
Home suffred from damage ( natural clamities) in the last year
No
Yes, with minor damaged
Yes, with significant damaged
20
extreme poor households 98 percent houses were damaged in the last year by the natural calamities. Of them, 53 percent houses were significant damaged and 45 percent were minor damaged.
Rich Middle class
Poor Extreme poor
Column N %
Column N %
Column N %
Column N %
Home suffered from any damage
No 70.4% 28.7% 7.1% 2.4%
Yes, with minor damaged 29.6% 57.4% 49.4% 44.7%
Yes, with significant damaged
.0% 13.8% 33.5% 53%
Case -1
Till now I am living in makeshift house, I have no ability to build house
- Zohura
55 years old, widow Zohura Begum lives at Altapol village in Keshobpur sub-district of Jessore. She is making a living by goat and poultry rearing and maid servant as well. Last year water logging, devoured and washed way her house. She took shelter on main road side with her daughter-in-law and a goat. Her poultry was also washed way. For coping she compelled to sale goat with low
price. She has not able build house and now she is living in makeshift house. On the one hand, it was found that all of the area’s house damaged status likely same but significant damaged status is higher in the Keshobpur area. (Please click here to see the details area wise house damaged).
SECTION 3.3: ACCESS TO WASH
In this section the study describes water and sanitation status of the surveyed HHs as well as confronted water borne related diseases status compare with area and wealth rank people. 3.3.1: Access to water
Table: Percentages of families using different source of water
Water Using Purpose Source of water (% of HH) DTW STW Pond Canal Supply
Drinking
78 18 - 4
Cooking
71 21 4 4
Bathing
61 10 23 2 4
Sanitation/ Cleaning
74 11 11 2 2
21
The above table depicts, all of the surveyed households are using safe drinking water. For drinking purpose most of the households, 96 percent, use deep and STW tube-well while 4 percent use supply water. Similarly for bathing, sanitation and livelihood activities the lion proportion households use tube-well water respectively. On the one hand, below figure shows 61 percent households said, existing water sources is not sufficient to meet their demand round the year. Among the three sub-districts satkhira area’s people were safe drinking water condition is worse than other area. The qualitative information found that during the water logging time in the respective areas they suffered safe drinking water.
In addition it also found that the respective HH collect drinking water from average distance 400 yards. Lower limit is 2 yard and upper limit is 2000 yard. 3.3.2: Sanitation status:
In-terms of sanitation, above figure shows only 17 percent HH have access to use sanitary toilet while 46 percent HH use slab latrine. Following by slab (without ring), hanging latrine user and doing open defecation attitude are 20 percent, 11 percent and 6 percent. In terms of very poor people’s sanitation, of them, the apex proportion of households, 92 percent extreme poor households are deprived from sanitary latrine while 14 percent HH are habituated of open defecation.
39%
61%
Suffiecient water round the year
Yes
No
60
59
64
56
57
58
59
60
61
62
63
64
65
Keshabpur Monirampur Satkhira
Pe
rce
nt
Suffering safe drinking water ( especially during water logging)
Open defecation-
6% HH
Slab without ring
20% HH
Hanging Latrine
11 % HH
Slab Latrine
46%HH
Sanitary Latrine
17% HH
14
8
31
39
8
0
5
10
15
20
25
30
35
40
45
Open defecation
Hanging latrine
Slab without ring
Slab with ring
Sanitary latrine
Pe
rce
nt
Sanitation status for the extreme poor people
22
• Owned -50%
• Neighbour-27 %
• Shared - 13 %
• Relatives-10%
Ownership of toilet of very poor HH
• Yes - 32 %
• No - 68 %
Safety issue for females/ children • Yes - 35%
• No - 65%
Healthy
59 % HH suffered
water borne disease
Skin disease
37 % HH
Jaundice
6% HH
Typhoid
7% HH
Cholera
3% HH
Dysentry
41 % HH
Diarrhoea
39 % HH
Moreover, above figure shows of them 50 percent percents extreme poor household’s have no any type of toilet. So, 14 percent do open defecation and 36 percent use relative’s and share toilet. Furthermore, 68 percent extreme poor people think these types of toilet are not safe for female and children as well as 65 percent said the toilet is not healthy. In addition, the below figure depicts average every year toilet need to be repaired due to inundation their house premises.
3.3.3: Water borne and contaminated water related disease In terms of confront water borne related disease the below figure shows, a total 59 percent HHs suffered water borne and contaminated water related diseases including diarrhea, dysentery, skin disease, cholera, typhoid, jaundice etc. Of these, diarrhea, dysentery and skin disease’s epidemic was very much all most average 39 percent.
Average distance of toilet from dweling
Avearge - 30 yard
people use a toilet
Avearage -
5 member use a toilet
Frequency of toilet become unusable
Average -after 1 year
23
3.3.4: Wealth category wise water borne disease On the one hand, compare with four wealth category people the below table shows very poor people and poor people’s diseases epidemic was higher than other. Average 76 percent extreme poor people suffered diarrhea, dysentery and skin disease due to water logging.
Wealth category wise water borne disease
Percentage (%)
SL Rich Middle class Poor Very poor
1 Diarrhea 8 13 56 77
2 Dysentery 7 10 41 76
3 Cholera 1 2 6
4 Typhoid 1 3 7
5 Jaundice 2 6
6 Skin disease 6 9 75
SECTION 3.4: MEMBERSHIP IN VARIOUS ORGANIZATIONS
3.4.1: Membership of organization
In terms of membership in various organizations, the pie chart shows out of 400 HH, 28 percent HH are member of various organizations. The comparison with four wealth category people 4 percent rich people, 8.5 percent middle class people, 12 percent poor people and 6 percent extreme poor people are involved with different organizations as a member. On the one hand, in terms of type of organization the below table shows all of the poor and extreme poor people are only
member of microfinance institutions while rich and middle class people are member in disaster management committee and school management committee.
3.4.2: Membership in various organizations: Membership Percentage (%)
Rich Middle class Poor Extreme poor
Total
MFI 12 6 14 CBO 2 2 DMC 2 2 4 SMC 2 4.5 6.5 Total 4 8.5 12 6 28.5
28%
72%
Membership in various orgabizations
Yes
No
24
SECTION 3.5: LIVELIHOOD PART (FOR THE EXTREME POOR PEOPLE)
This section describes economic status of the extreme poor people like occupation, monthly income, expenditure, productive assets, non-productive assets, land status, saving and loan status.
3.5.1: Average Income, expenditure and asset of the HH
Figure 2: Income, expenditure and assets of the family
Above figure shows average monthly income of the extreme households is BDT 4620 while average monthly expenditure is BDT 4632 that means monthly deficiency is BDT 12. And, average family assets value is BDT 10267.
The column chart depicts 59 percent households’ monthly income is below 5000 BDT from 1000 to 5000 while rest of the 41 percents’ HH average income was above 5000 BDT. Moreover, lower limit monthly income of the family is BDT 1000 and upper limit is BDT 9300.
However, as a comparison of income level of the respective three study sub-districts the figure shows Satkhira’s extreme poor HH average income is higher than other sub-district which is BDT 4923 and lowest average income area is Keshobpur BDT 4192.
Average monthly income
BDT. 4,620Average monthly expediture
BDT . 4,632Average value of family assest
BDT 10267 ( productve & Non-productive)
8.3
14.2
17.519.2 20
6.7
14.2
0
5
10
15
20
25
1000-2000 2001-3000 3001-4000 4001-5000 5001-6000 6001-7000 7000>
Pe
rce
nt
Class interval of income level of HH
25
3.5.2: Assets
Productive and non productive assets
Area Nonproductive Asset Productive Asset Total Asset Value
KESHABPUR 3494 6656 10151 MONIRAMPUR 5022 7806 12827 SATKHIRA 4643 3179 7822 Grand Total 4386 5880 10267
In terms of assets status including productive and non-productive, above table presents average productive assets value of the extreme poor people is 5880 BDT while non-productive assets value is BDT 4386. Compare with three respective areas Monirumpur’s households productive assets value is highest than other area (7806) while lowest value is Satkhira (3179). Among the productive assets the below table shows extreme poor HHs have minimum level of productive assets. Only 12 percent have cow where as 23 percent have goat. Following by poultry, sewing machine, rickshaw and tree are in 43 percent, 5 percent, 8 percent and 24 percent households.
Productive Asset yes no
HH # HH % HH # HH %
Cow 14 12% 106 88%
Goat 28 23% 92 77%
Poultry 51 43% 69 58%
Tree 29 24% 91 76%
Handicraft materials 6 5% 114 95%
Sewing machine 6 5% 114 95%
Shop 2 2% 118 98%
Rickshaw 10 8% 110 92%
Fishing net 4 3% 116 97%
Boat 0% 120 100%
Bicycle/MC 10 8% 110 92%
Agri Equipment 21 18% 99 83%
Non Agri Equipment 78 65% 42 35%
Other asset 12 10% 108 90%
Land: The below table shows, 69 percent extreme poor people have homestead land and only 1 percent have cultivable land and 6 percent have uncultivable land. As a comparison among three area households of Monirumpur and satkhira have no cultivable land. However, average cultivable land value is BDT 2498.
Homestead Land Cultivable Land Un cultivable Land
Area HH #
HH %
Average Amount
HH #
HH %
Average Amount
HH #
HH %
Average Amount
KESHABPUR 33 83% 205,966 1 .3% 295,000 2 5% 42,500
MONIRAMPUR 26 65% 113,269 0% 3 8% 26,000
SATKHIRA 24 60% 97,917 0% 2 5% 7,750
Grand Total 83 69% 145,685 1 1% 2458 7 6% 25,500
26
SECTION 3.6: LOAN AND SAVING STATUS OF THE EXTREME POOR PEOPLE
3.6.1: Loan
The pie chart shows 19 percent households took loan in the last one year. In-terms of comparison with three areas it was found that highest is Minirampur (28 percent HH) than other two areas while satkhira is 20 percent and only 10 percent HH in Keshobpur took loan. (Please click here to see area wise details).
The below figure depicts a total 84 percent approached to NGO’s microfinance while 6 percent to neighbor, 6 percent from money lender and 4 percent from Bank. Average taken loan is BDT 16181. Comparison with area wise loan taken Keshobpur and Satkhira’s loan taken size is high.
The reasons of loan were mostly house re-construction, established IGA, treatment, dowry, education, marriage and repay loan. However, of them, the below figure presents near about half of the HH, 48 percent, took loan for household renovation. Following by 27 percent HH took loan for establishes IGA, 17 percent for treatment etc. It also found that due to disaster especially water logging people took loan for house renovation purpose and treatment purpose.
19%
81%
Taken loan in the last year
Yes
No
18750
13378
18750
16181
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
Kesobpur Monirampur Satkhira Total
Pe
rce
nt
Average took loan
26.09
13.048.70
4.358.70
17.39
47.83
0.00
10.00
20.00
30.00
40.00
50.00
60.00
Establish IGA Repay loan Marriage Dowry Education Treatment House reconstruction
Pe
rce
nt
Purpose of took loan ( Multiple answer - out of 19 %)
84
6 6 4
0
10
20
30
40
50
60
70
80
90
NGO Bank Neigbor Money lender
Pe
rce
nt
Place of took loan
27
3.6.2: Saving status The study findings show there are 23 percent households have savings which total average amount BDT 2639. However, in terms of saving place most of the HHs have saving in the NGO’s microfinance institutions.
SECTION 3.7: FOOD SECURITY
3.7.1: Three proper meals a day round the year
The above figure depicts that among the very poor people only 22.5 percent can ensure three meals in a day properly. Moreover, among the three areas below table shows Satkhira’s households food security is decrepit condition only 12 percent HHs are able ensure proper three meals in a day.
Area wise food sufficiency Proper three a day round the year
Response KESHABPUR MONIRAMPUR SATKHIRA Total
Column N % Column N % Column N % Column N %
Yes 25.0% 30.0% 12.5% 22.5%
No 75.0% 70.0% 87.5% 77.5%
No saving -77 %
Have saving-23 % Average saving -BDT.2639
Place of save money-NGO- 95%
Cash in hand-5 %
Saving
Three proper meals a day 22.5 %
Households
28
However, in terms compare with sesonality, in the Pick season 57 percent HH can afford three meals in a day while in the lean season only 15 percent HH are able proper three meals in a day.
3.7.2: Calculation of food consumption score
The study tried to find out food security of households through measuring food consumption scoring as per guideline of WFP. However, the study found that targeted people are living in food insecurity. 42 percent HH are in acceptable dietary cluster while 53 percent HH are in borderline dietary cluster and 5 percent households are in 2poor diet cluster or poor match. (Please click here to see food scoring
calculation guideline)
2 The value food consumption calculation is (for example) [frequency (7 day/week) * weight (carbohydrate-2), 7 * 2
= 14] and vegetables (7 * 1 = 7). The value 35 comes from an expected daily consumption of staple and vegetables complemented by a frequent (4 day/week) consumption of oil and pulses (staple*weight + vegetables*weight +
oil*weight + pulses*weight = 7*2+7*1+4*0.5+4*3=35).
57
37
51
15
24
42
19
0
10
20
30
40
50
60
proper 3 meals 3 meals with difficulty 2 proper meals 2 meals with dificulty
AP
erc
en
t
Food security profile by season
Pick season
Lean Season
42
53
5
0
10
20
30
40
50
60
acceptable dietary cluster (35>)
borderline dietary cluster (21.5-35)
Poor dietary cluster (
29
SECTION 3.8: LIVELIHOOD (MAKING A LIVING OF THE EXTREME POOR PEOPLE)
In this section study described livelihood, livelihood skills and received skill development training status of the extreme poor people. Moreover, study describes their alternative livelihood option and reason of satisfaction and dissatisfaction level and identified suitable climate adaptive livelihood options. Furthermore, it also describe their accessibility of market system to sell their produce and migration status for livelihood. 3.8.1: Livelihood (Occupation)
In terms of livelihood of the extreme poor people the finding shows on below figure that more than half of the HH, 57 percent, are making a living by the day laboring while second highest 19 percents earn by the rickshaw pulling and motor driving. Rest of the HHs are consecutively 5 percent maid servant, 5 percent small business, 4 percent agriculture, 3 percent livestock rearing, 2 percent fishing and 2 percent grocery shop. 3.8.2: Livelihood skill Livelihood skill is importance to enhance making a living. However, the study assessed livelihood skill among the extreme poor people and found, shows pie chart, two third, 753 percent, HHs has not diversified livelihood skill. Following by only 6 percent households have impressive skill, 7 percent is good, 8 percent is fair and 4 percent HH have poor skill.
3 Very good = have previous experience, got skill development training. Good= have previous experience. Fair =
have indigenous knowledge but have no experience. Poor = have introduce such kind of livelihood. No skill = neither have no knowledge nor introduce with it.
6%7%
8%
4%
75%
Livelihood skill of the extreme poor people
Very good
Good
Fair
Poor
No skill
57
4 3
14
52
53
52
0
10
20
30
40
50
60
Day labour Agriculture Livestock Rickshaw/van puling
Driving motor Bick
Grocery shop Small bussines Tailoring Maid servant Fishing
Pe
rce
nt
Occupation or livelihood of extreme poor people
30
The study tried to assess around 14 livelihoods skill among the surveyed HH. The below table presents of these around more than 60 percent HHs have livestock and poultry rearing skill where as others skills are not satisfactory level.
Livelihood skills of the very poor people
SL Livelihood skill Percentage ( %)
Very good Good Fair Poor No skill
1 Livestock rearing 15 17 20 8 40 100 2 Poultry farming 13 25 18 8 36 100 3 Agriculture 11 12 14 8 55 100 4 Fishing 5 3 8 6 78 100
5 Business 2 4 3 7 84 100
6 Sewing 3 5 6 5 81 100 7 Embroidery 3 1 3 2 91 100
8 Handicrafts 6 5 6 3 80 100 9 Small business
management 4 8 8 7 73 100
10 Financial management 5 5 12 4 74 100 11 Mechanical 2 2 3 1 92 100 12 Driving 6 5 4 1 84 100
13 Carpentry 1 2 1 1 95 100
14 Pottery 1 1 98 100 Average 6 7 8 4 75
3.8.3: HH received skills development training
The above figure show 11 percent HH was received skill development training from training providing organization especially NGO. They received training on cultivation, livestock rearing, poultry rearing, handicraft, sewing, small business etc. (Please click here to see details training received status).
Received Skill develop training-
11% HH
Keshonpur - 5% Monirumpur-5% Satkhira-22.5%
Area wise
31
3.8.4: Alternative climate adaptive livelihood
The baseline study finding shows on pie chart, 21 percent study very poor people are engaged in alternative livelihood. As a comparison among the three areas highest 34 percent HHs are involved in the keshobpur area and second highest is Monirumpur 18 percent HH while lowest only 5 percent in the Satkhira’s HHs are involved in alternative livelihood Activates.
As an alternative livelihood people are mostly involved in livestock rearing, poultry rearing, crops and vegetable cultivation, fish cultivation and small business. (Please click here to see the details alternative livelihood)
3.8.5: Satisfaction level of alternative livelihood option
The study found 88 percent HHs reported they are not satisfied with the present form of alternative
livelihood option. As reasons of not satisfaction, the multiple answered has come from study people. The
below figure shows 60 percent HH reported due lack of capital they have not improved while similar
proportion, 58 percent, said due to water logging their present alternative livelihood were destroyed.
Following by 39 percent HHs reported lack of skill in managing livelihood options, 27 percent is lack of
knowledge about climate adaptive livelihood options, 5 percent lack of demand in the market, 4 percent
lack of access to extension service providers and 3 percent damage land due to salinity.
3.8.6: Climate adaptive livelihood is suitable:
In terms of type of climate adaptive livelihoods are suitable in the study locality, the study found multiple
and diversify responses has come from the study population. The below table reveals suitable climate
adaptive livelihood options are water tolerable crop and vegetable cultivation, Homestead gardening, bag
21%
79%
Engaged in alternative lilihood
Yes
No
3
27
58
39
5 4
60
0
10
20
30
40
50
60
70
Damage land due to salinity
Lack of knowledge about climate
adaptive livelihood options
Water logging Lack of skill in managing
livelihood options
Lack of demand in the market
Lack of access to extension service
providers
Lack of capital
Pe
rce
nt
Reasons of dissatisfaction of livelihood (multiplr answer)
32
gardening, fish cultivation, Cow raring, goat and sheep rearing, duck and poultry rearing, small business
and crab cultivation and fattening etc. Of these, the respondents reported livestock, crab cultivation and
fattening and water tolerable crop and vegetable cultivation are most suitable in their locality.
Type of climate adaptive livelihood are suitable
SL Response Percent
1 Water tolerable crop and vegetable cultivation 30.3%
2 Homestead gardening 10.9%
3 bag gardening 5.9%
4 Fish cultivation 7.6%
5 Cow raring 62.2%
6 Goat and sheep rearing 42.9%
7 Duck and poultry rearing 33.6%
8 Small business 16.8%
9 crab cultivation and fattening 31.1%
In terms of practicing level of climate adaptive livelihood at present, most of the respondents answered
they are not practicing due to have no knowledge on climate adaptive livelihood.
3.8.7: Access to the market
The study found the study populations sell their products at local area and they are not well informed
about market. The major proportions of households are not satisfied with the price of buyer set for
buying their product. They also don’t know about legitimate or best price and don’t access to get market
information.
SECTION 3.9: MIGRATION STATUS
In terms of migration to other place for livelihood, the pie chart shows 27 percent targeted people usually migrate for hunting job. And, as comparison among the three areas below table shows that migration tendency or compelled to migration of satkhira’s people is higher than other area which is 42 percent while lowest migration rate in Monirampur only 13 percent.
The study found major proportion, 80 percent, usually migrated to urban area while 20 percent migrated to rural area. During the migration 74 percent people pull rickshaw. Following by 33 percent work as day
Area wise migration status
Migration to other place for livelihood
Response KESHABPUR MONIRAMPUR SATKHIRA Total
Column N % Column N % Column N % Column N %
Yes 25.0% 12.5% 42.5% 26.7%
No 75.0% 87.5% 57.5% 73.3%
27%
73%
Migration to other place for livelihood
Yes
No
33
labour, 16 percent become garment workers and 6 percent bus helper. In addition, people’s migration tendency is every month of the year. But, among of these month people’s migration propensity is from between July and October because of at that time in their locality difficulties to manage work owing to water logging. Average 1 person of the family members is migrated. Average working month is 3, lower limit is 1 and upper limit is 8 month.
3.9.2: Access to government services
Big city - 50 %
Local urban - 30%
Rural - 20 %
B. Area of migration
44
33
16
6
05
101520253035404550
Rickshaw pulling
Day labor Garments worker
Bus helper
Pe
rce
nt
( o
ut
of
32
%)
Business during migration
34
SECTION 3.10: RIGHTS (ACCESS TO GOVERNMENT SERVICES & SOCIAL PROTECTION)
3.10.1: Access to government services In terms of access to government services, the study identified 8 government service institutions. The pie chart shows average 62 percent very poor people never been approached to get government services while average 14 approached but didn’t get services. Following by 12 percent HH always get support and similarly 12 percent some gets support.
However, among these services the below table shows HHs only get support from health and education
Access to Government Services
SL Response Percentage (%) Always get
support Sometimes get support
Never get support
Did not approach
Total
1 Agriculture 2 8 12 78 100 2 Livestock 9 5 22 64 100 3 Health 35 49 5 11 100 4 Education 50 14 0 36 100 5 Banking 4 5 11 80 100 6 DPHE 3 7 20 70 100 7 Department of women
affaires 3 4 17 76 100
8 Department of fisheries
1 18 81 100
3.10.2: Received Social safety net support In terms of social safety net services, a total 40 percent HHs received VGF support. Following by 3 percent VGD, 3 percent widow allowance, 3 percent elderly allowance and 2 percent disable allowance.
Access to social protection
SL Services Percent
1 VGD 3
2 VGF 40
3 Widow allowance 3
4 Elderly allowance 3
5 Food for work 1
6 Allowance for vulnerable work 0
7 Shelter 0
8 Disable 2
12%
12%
14%62%
Access to goverment services
Always get support
Sometimes get supportNever get support
35
SECTION 3.11: CLIMATE CHANGE AND DISASTER MANAGEMENT (for all categories people)
In this section the study tried describes shock of the study households due to disaster, livelihood status,
and perception of the study people reason behind water logging. Moreover, the study tried to find out
status of community based disaster preparedness and their knowledge, attitude and practices, status of
all tire of disaster management committees and their functionality and responsiveness. Finally describe
suggestion of the study people to resilience and mitigate water logging problem.
3.11.1: Distribution types of Hazards Facing Every Year
The study findings reveal
that the project areas
are highly vulnerable for
four types of disaster.
Types of hazards varied
from areas to areas.
Distribution of data
shows on column chart
that all four project
implementation areas
has been facing water
logging problem. In
addition, salinity problem exists in only one area, namely Satkhira. However, findings of the study also
revealed that the second most common hazards in all four areas are cyclone. A total 52.6 per cent
respondent from all four areas have faced cyclone each year.
3.11.2: Damage & Shock status
Meeting with community people, FGD with UP bodies, KII with project implementation Officer,
Government Official in three Areas the study found the damage and shock status in the water logged
areas are relatively high. Area wise information as bellows:-
Monirampur Upazila: The last water logged almost 60 percent HHs were affected mostly or partially.
Almost 16 people died in from snack bite. It should be noted that 20 percent HHs damaged totally, due to
water log. In addition, 80 per cent of shrimp cultivation was damaged totally, and the almost 90 per cent
livestock sold out with less price. The water logged affected people faced scarcity of drinking water,
sanitation and shelter surprisingly. Privacy and security of women and adolescent girls becomes difficult
in makeshift houses along roadside. Male member of the household spent night at submerged house to
protect immovable assets may be subjected to snake bite, and robbery (disruption to law and order).
Defecation becomes extremely difficult which leaves the environment unhygienic; Health services are
unavailable; schools are closed; markets cannot be reached. Local education institutions were closed
almost average 45 days.
Keshopur Upazila: The last water logged almost 75 percent HHs were affected mostly or partially. It
should be noted that 30 percent HHs damaged totally, due to water log. Almost 9 people died in from
snack bite. More than 50 percent road was inundated. 40 percent people were compelled to take shelter
other area. In addition, 85 percent of fish cultivation was damaged totally, 15 percent livestock died and
the almost 90 per cent livestock sold out with less price, 40 percent poultry were died, 95 percent crops
( Paddy, vegetable, banana, mango and Beatle leaves) were damaged, 70 percent HHs non-productive
99
9
53
5
0
20
40
60
80
100
120
Water logging Salinity Cyclone Flood
Pe
rce
nt
Type of hazards ( Multiple answer)
36
assets were destroyed. The water logged affected people faced scarcity of drinking water, sanitation and
shelter surprisingly. Privacy and security of women and adolescent girls becomes difficult in makeshift
houses along roadside. Male member of the household spent night at submerged house to protect
immovable assets may be subjected to snake bite, and robbery (disruption to law and order). Defecation
becomes extremely difficult which leaves the environment unhygienic; Health services are unavailable;
schools are closed; markets cannot be reached. Local education institutions were closed almost average
45 days.
Case-2 My poultry business was boom,
Due to water logging 400 poultry were died, now I am jobless Munirul
4o years old Munirul, villager at pachim para pazia in Keshobpur Upazilla, was making a living by the
poultry farming. The last water logging disaster his poultry farm was totally destroyed where 400 poultry
were died. Now, his is jobless.
Satkhira Upazila: The last water logged almost 70 percent HHs were affected mostly or partially. It
should be noted that 25 percent HHs damaged totally, due to water log. Almost 5 people died in from
snack bite. More than 55 percent were inundated. 35 percent people were compelled to take shelter
other area. In addition, 90 percent of fish cultivation was damaged totally, 18 percent livestock died and
the almost 90 per cent livestock sold out with less price, 45 percent poultry were died, 95 percent crops
were damaged. The water logged affected people faced scarcity of drinking water, sanitation and shelter
surprisingly. Privacy and security of women and adolescent girls becomes difficult in makeshift houses
along roadside. Male member of the household spent night at submerged house to protect immovable
assets may be subjected to snake bite, and robbery (disruption to law and order). Defecation becomes
extremely difficult which leaves the environment unhygienic; Health services are unavailable; schools are
closed; markets cannot be reached. Local education institutions were closed almost average 45 days.
Shocked due to water logging ( Area wise )
Area wise percentage / count of shocked Shocked Monirumpur Keshobpur Satkhira Death of people 16 person 9 persons 6 person
Affected house 60 % 75% 70%
Totally damaged house 20 % 30% 25 %
Road inundated 50% 50% 45%
People left house /took shelter other place 35% 40% 35%
Crops damaged 90% 95% 90%
Livestock damage 15% 20% 20%
Poultry were died 35% 40% 30%
Livestock sold with less price 90% 85% 80%
Fish cultivation damaged 90% 90% 85%
School stopped 85% 90% 85%
Sanitation disrupted 60% 75% 70%
Scarcity of safe drinking water 60% 75% 70%
Land inundated -all most 10000 Hectors 10500 Hectors 9000 Hectors
37
3.11.3: Perception regarding reasons behind water logging
Hydrology of the Southwest region of Bangladesh encompasses catchment areas of several major river
systems. Water passes through the upper catchment area of Jessore and drain to the Bay of Bengal
through river systems of Khulna and Satkhira. There is something of a consensus on the causes of water
logging – if not its solution – which can be seen in the various literature published on the subject over the
past 10 years. As a result of impeded drainage, rain water accumulates in the naturally occurring
depressed areas called beels and in such other sections of the moribund rivers. In addition, unplanned
aquaculture practice through creating obstruction in the drainage channels caused reduced flow. As can
be seen from the data, annual variations in the magnitude of the problem are observed depending on the
amount of rainfall received during the year. The problem also varies with locations due to differences in
the pattern of drainage congestion. The following reasons behind water logging which was determined by
the different stakeholders-
Siltation in the major river systems is resulting in drainage congestion has been identified as one
of the primary underlying causes of water logging
The largely unplanned growth of shrimp farming may have worsened existing drainage problems
affecting the wider community and make the water logged situation worsen.
Encroachments of river bank by the local elite for unplanned shrimp farming is one of major
cause for water logging
In absence of regular excavation of canal and river caused water logging.
Local level political influences are visible in making conflict between shrimp farming and
indigenous farming.
Case-3
The Hora River, played importance role
to conserve and pass water of Jessore
area. But, due to, day by day, lost her
navigability and encroachments of river
bank by the local elite, this river could
not safe the from water logging.
3.11.4: Suggestion of the respondent to escape water logging:
Tidal River management (TRM) is widely appreciated as one important solution to the problem of
water-logging, being seen as in harmony with nature and a cost effective process of silt
management.
Multipurpose shelter need to construct in water logged area
Ensure livestock foods and shelter at the time of disaster
Mobilize the DMCs for conducting CRA and URA
Grass plant needed at roadside in order to feed cow at the time of water logging.
In this area lack of shelter center, so shelter center build is needed
38
For safe crops and livestock killa is needed.
Need to install deep tube-well
Road need repair
Tree plantation is needed
3.11.5: Pre-cautions against Hazards at the Household Level
Disaster preparedness reduces the
vulnerability of hazards. Household level
precaution about hazards is playing a vital
role to combat losses of disaster. Findings
illustrates on figure that only 30 per cent
household have own precaution against
hazards and rest of 70 per cent household
has no pre-caution against hazards. In
terms of HH categories of the study,
findings depict on table that rich HHs are
more aware about precaution against
hazards than ultra poor household.
Moreover 25 per cent rich HHs did not take any precaution against hazards, while ultra poor HHs are 47.5
per cent.
Category Wealth rank wise HHs precaution Total
Yes No
F % F % Rich 21 75 7 25 100
Middle 69 73.4 25 24.6 100 Poor 99 62.7 59 37.3 100
Ultra poor 63 52.5 57 47.5 100
Distribution of data about types of precaution shows on following figure shows that the respondents had
taken eight types of precaution against hazards. The highest 74 per cent prepared dry food for having at
the time hazards. The second highest 41 per cent respondents preserved fire wood, 32 per cent prepared
moveable woven and 31 percent plinth rising respectively.
74
32
21
41
10
31
6
17
0
10
20
30
40
50
60
70
80
Dry food Moveable woven
Savings Fire wood Tiding house with bamboo
and rope
Plinth rising homestead
First aid box Tree plantation
Pe
rce
nt
Types of Precaution against Hazards ( Multiple answer)
30%
70%
Pre caution against hazards (HH)
Yes
No
39
3.11.6: Early Warning System
The early warning and evacuation system has been playing an important role in saving life during disaster. Data illustrates on figure that the highest 52 percent respondents mentioned there is no early warning system exists in their locality, while 39 per cent mentioned they have idea about early warning. The rest of 9 per cent told that they don’t know anything about early warnin
