A NEW APPROACH IN GENDER VULNERABILITY ASSESSMENT USING MATRIX FRAMEWORK

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1 A NEW APPROACH IN GENDER VULNERABILITY ASSESSMENT USING MATRIX FRAMEWORK Mahin Al Nahian 1*, G.M. tarekul Islam 2 and Sujit Kumar Bala 2 1 Research Assistant, Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh, mahin_149@yahoo.com 2 Professor, Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh, asadh@iwfm.buet.ac.bd ABSTRACT Climae change, its impact and associated vulnerability is gender specific and is magnifying the existing inequalities between men and women. Women becoming the most sufferers due to their gender differentiated roles and lack of access and control over resources. Assessment of vulnerabilitis and risks in the face of changing climate is of utmost importance for improved decision making to reduce the extent of adverse impact. Traditional vulnerability assessment techniques are basically focused on extensive usage of participatory tools providing qualitative assessment on livelihood assets whcih fails to access overall gender dimension of climate change associated vulnerability. This paper tried to develop a way of vulnerability assessment using matrix framework which helps in quantifying vulnerability using simple ranking procedure based on community s perception. Two vulnerability assessment matrixes were developed and used for vulnerability assessment of water resource (from gender perspective) and vulnerability assessment of gender groups (women). Result shows that among the two study areas, water resource and women community from Koyra are more vulnerable comparing to that from Shyamnagar. Though respondnets from Koyra perceive that, water resource is more vulnerable to gradual climate change however, regarding women they identified climate change induced disaster events as major cause of vulnerability. Keywords: Climate change, vulnerability assessment, water resource, gender, gradual change, extreme events 1. INTRODUCTION Climate change, its impact and associated vulnerabilities is presently the most burning issue worldwide. The global warming and its consequent effect of climate change are attributed directly or indirectly to human activities and natural variability that altars the composition of atmosphere; the resultant output now threatens the humankind and its achievement with most diversified and erratic atmospheric and environmental condition, which are predicted to be worsen in upcoming future with increased temperature, erratic nature of rainfall and increase in intensity and frequency of disaster events. However, the climate change and its impact will be felt differently in places with varied magnitude and the poor, least developed and developing countries from Africa and Asia will be the primary victim of natural calamities. The Global Climate Risk Index 2011, which was developed by the German-based organization Germanwatch, recognized Bangladesh as the country most vulnerable to extreme weather events and the one most affected in the period of (Harmeling, 2010). UNDP (2004) identified Bangladesh as the most vulnerable country in the world to tropical cyclones, and the sixth most vulnerable country to floods (GoB, 2009). During the period of 1991 to 2000, Bangladesh has suffered from 93 large scale natural disasters which killed 20 lakh (0.2 million) people and caused loss of properties valued about 59 billion dollar in the agricultural and infrastructure sector (DoE, 2009). The adverse effects of climate change undermine the economic, development, human security, and people s fundamental rights (UNDP). Global environmental change and sustainability science increasingly recognize the need to address the consequences of changes taking place in the structure and function of the biosphere. Research demonstrates that vulnerability is registered not by exposure to hazards (perturbations and stresses) alone but also resides in the sensitivity and resilience of the system experiencing such hazards. This recognition requires revisions and enlargements in the basic design of vulnerability assessments (Turner, 2008). Climate change studies primarily focused on research regarding physical nature of climatic variability and impact of induced disasters and in socioeconomic dimension on the sustainable livelihood aspects and disaster preparedness. However, climate change has a

2 critical and sophisticate gendered dimension and somehow gender perspective of climate change was excluded or overlooked (to a certain degree) in research based work. Vulnerability is gender differentiated. Factors, such as lack of access to and control over basic resources and lack of entitlements, amplify women s vulnerability and undermine their ability to cope with effects of disasters (ActionAid, 2008). The gender-poverty links show that 70 percent of the poor in the world are women and their vulnerability is accentuated by race, ethnicity, and age. When natural disasters and environmental change occur, women and men are affected differently because of traditional, socially-based roles and responsibilities (CCC, 2008). Mortality ration of women in natural disasters also depicts the differentiated vulnerability of women and men in the face of climate change associated predicted future. However, impact of climate change on gender groups especially on women is quite new and there is very limited resources available comparing to the physical dimension of climate change. Major research regarding the gender dimension of climate change primarily initiated after 2007 as the 4th Assessment Report of IPCC succeed to raise tremendous global concern and Bangladesh also gave major importance on the issue. Climate Change Cell (CCC) of GoB, BASTOB and Centre for Global Change (CGC) carried out a very important study (CCC, 2008) which summarized the hydro-geophysical situation specific vulnerability contexts for the women, reported by the vulnerable themselves by conducting field discussions. While the major success of the study lies in assessing spatial vulnerability of women based on different geo-physical context of the country, it doesn t capture the overall gender dimension of climate change vulnerability. How climate change is affecting existing gender relations and its impact in activity; and access and control level was not brought under consideration. Nonetheless, the study is very useful and important one and believed to be the major contribution in including gender consideration in revised NAPA and BCCSAP in Another major initiative linking climate change, gender and vulnerability was carried out by Bangladesh Centre for Advanced Studies (BCAS, 2010), which stated that, the greater number of women victims of various natural calamities clearly depicts that, the unequal risk and exposure across genders. Women are more vulnerable both to the short term recurring climatic events and long term climate induced changes because of gender differences in socially constructed roles and responsibilities that affect mobility, social networks and access to information and local institutions, as well as access to, control and ownership of assets. Though this study analyzed linkage among gender, climate change and vulnerability more analytically, but there are significant gaps in defining vulnerability. It carried out Sustainable Livelihood Framework with a gender lens in the study. Thus, it somehow shifted its focus on the gender analysis from a livelihood view point and included climate change paradigm to qualitatively assess vulnerability. This reflected the traditional process of vulnerability assessment (even when climate change issue was not surfaced in global community) which is primarily rooted into the relation of livelihood and DRR viewpoint. There are some other interesting literatures available on the issue that tried to establish linkage between climate change and gender. However, majority of the studies took a qualitative approach and accessed vulnerability primarily considering the impact of climate change induced disasters on community s livelihood intervention. The shifting from traditional way of socio-economic vulnerability assessment came after the second IPCC report, based on new definitions of climate change associated vulnerability (in light of TAR and FAR) and technological improvement, new set of tools evolved for vulnerability assessment that are capable of dealing with critical climate change scenarios. It is to be noted that, though IPCC defined vulnerability to climate change as function of exposure, sensitivity and adaptive capacity, but does not present vulnerability in terms of an equation, and most frameworks avoid mathematical modelling. Different tools use varied terminologies and techniques for vulnerability assessment and many of which doesn t precisely follow IPCC defined definition as well (Yates, 2010). After the initial analysis these tools use a gender lens to provide view on gender differentiated vulnerability. These methods are gender exclusive; so to capture the full dimension of gender and gender relations during assessing vulnerability to climate change some modification need to be done in traditional way of climate change vulnerability assessment. This paper tried to develop a more precise way of vulnerability assessment using a matrix framework based on perceived response from community. The study also tried to evaluate the performance of the matrix framework in assessing vulnerability from gender perspectives. Cyclone Aila affected Padmapukur union of Shyamnagar from Satkhira and Dakhin Bedkashi union of Koyra from Khulna district have been used as study sites for the study. 2. METHODOLOGY AND DATA COLLECTION

3 The study has developed two vulnerability assessment matrixes to quantify gender dimension of climate change associated vulnerability in simplest way possible. IPCC identified vulnerability in terms of exposure, sensitivity and adaptive capacity which is well recognized in global scientific community. One matrix was used to assess vulnerability of water resource from a gender perspective and the other one was used to capture the vulnerability of gender group. There is some basic difference among the designs as two represent two separate systems. But the first one can be used for vulnerability assessment of any natural system from gender context while the second was could be used to assess vulnerability of any livelihood group or simply community level vulnerability. Both matrixes followed same ranking system. Exposure, Sensitivity and Adaptive Capacity is ranked with a score of 0~3 based on severity and strength of impact. In the ranking system, 0 denotes no impact and 1~3 defines impact from less to moderate and then severe. The primary equation of Vulnerability (V) = Exposure (E) x Sensitivity (S) / Adaptive capacity (A) has been used in calculating vulnerability. The matrix helps in assessing context specific vulnerability (i.e. event wise and extreme wise) and total vulnerability (with average values of exposure, sensitivity and adaptive capacity due to events and extremes). Vulnerability assessment matrixes had been developed collaborating basic ideas from IUCN s A Framework for Social Adaptation to Climate Change: Sustaining Tropical Coastal Communities and Industries which suggested a coupled system module for climate change induced vulnerability assessment (Marshall, 2009) and Yates A matrix for calculating community vulnerability (Yates, 2010). Vulnerability Assessment Matrix For Water Resource (From Gender Perspective) To determine the vulnerability of any system to climate change impacts, it is very important to understand its exposure to gradual change and extreme events, associated sensitivity and inbuilt adaptive capacity. The exposure of water resource to climate change was assessed by identifying the direct impact due to climate variability and change and additional extreme events. The sensitivity of water resource was accessed summarizing the effect due to direct impact from climate change in its bio-physical and socio-economic regime. Any impact from climate change affects the bio-physical regime of the water resources and considering the gender perspective; the effect due to climatic impact is also felt in various socio-economic activities, centred on water or depends directly or indirectly on water resource. So, the effect due to direct climatic impact was summarized under sensitivity heading. Then, in adaptive capacity coping mechanism of water resource itself, and practiced adaptation and mitigation options in human society were summarized and ranked as per their effectiveness. Vulnerability Assessment Matrix For Gender Group (Women) The development design of the matrix lies in the concept of Sustainable Livelihood Framework and Harvard Gender Analytical Framework. Livelihood resources and Gender differentiated triple roles and access and control over resources was summarized as the basic coupled system, one is required to sustain and enhance one another. The exposure to climate change was assessed by summarizing direct impact of climate change on livelihood resources/ capitals (Natural, Human, Physical, Financial and Social). The associated effect on Activity and Access and Control due to climatic impact on livelihood assets were further summarized under sensitivity heading. Activity profile were sub-divided in Productive role, Reproductive role and Community Managed role and Access and Control profile was sub-divided into Resources and Benefit. Thus, overall effect of climate change on gender differentiated triple role as well as access and control over resources were captured. Adaptive capacity was accessed based on practiced coping and adaptation heading. Then using the same ranking formula and equation, vulnerability of gender group was assessed. Vulnerability assessment had been carried out in Focus Group Discussion (FGD) sessions ensuring participation from women community only. Women represent the majority of the gender community and hence, women had been considered as the primary focus group of the study. Two FGDs had been conducted in the study areas to quantify vulnerability based on perceived response from the respondents. 3. VULNERABILITY ASSESSMENT AND KEY FINDINGS

4 Table 1: Vulnerability Assessment Matrix for Water resources Padmapukur, Shyamnagar, Satkhira Exposure (direct impact on water resource) [E] Sensitivity (effect due to direct impact) [S] Adaptive capacity (Change in water use practice) A Context Change in rainfall pattern Change in water availability Salinity intrusion Overall Exposure effect on Bio-physical regime Impact on water recharge Impact on in stream water demand Impact on water quality Impact on water dependent ecosystem effect on Socio-economic regime Impact on drinking water supply Impact on Domestic water use Standard of living Cultivation Navigation Shrimp culture Fishing Overall Sensitivity Coping mechanism in nature Alternative use of water in human society Overall Adaptive Capacity Specific Vulnerability (E x S)/A Total Vulnerability (E x S)/A Long duration summer Increased temperature in summer Short duration monsoon Monson with heavier rainfall No/ less rainfall in Pre/post monsoon Erratic rainfall Average seasonal change Increase in cyclone storm surge frequencyintensity Increase in tidal surge height Water logging River erosion Average extreme events (Score: 0 = no impact; 1 = less impact; 2 = moderate impact; 3 = severe impact)

5 Table 2: Vulnerability Assessment matrix for Water resource Dakhin Bedkashi, Koyra, Khulna Exposure (direct impact on water resource) [E] Sensitivity (effect due to direct impact) [S] Adaptive capacity (Change in water use practice) A Context Change in rainfall pattern Change in water availability Salinity intrusion Overall Exposure Impact on water recharge effect on Bio-physical regime Impact on in stream water demand Impact on water quality Impact on water dependent ecosystem effect on Socio-economic regime Impact on drinking water supply Impact on domestic water use Standard of living Cultivation Navigation Shrimp culture Fishing Overall Sensitivity Coping mechanism in nature Alternative use of water in human society Overall Adaptive Capacity Specific Vulnerability (E x S)/A Total Vulnerability (E x S)/A Long duration summer Increased temperature in summer Short duration monsoon Monson with heavier rainfall No/ less rainfall in Pre/post monsoon Erratic rainfall Average seasonal change Increase in cyclone storm surge frequency-intensity Increase in tidal surge height Water logging River erosion Average extreme events (Score: 0 = no impact; 1 = less impact; 2 = moderate impact; 3 = severe impact)

6 Table 3: Vulnerability Assessment Matrix for Gender Group (women) Padmapukur, Shyamnagar, Satkhira Exposure (impact on livelihood capital) [E] Sensitivity (effect associated with direct impact) [S] Adaptive capacity (A) Context Natural capital Human capital Physical capital Financial capital Social capital Overall Exposure Produc tive role Paid employment Activity Profile Reprod uctive role Activity (without payment) Commu nity manage ment activity Activity (No payment-recreation, motivational, empowering) Resources Access & Control profile Benefit Overall Sensitivity Experience of survival against cyclone & storm surge Major coping strategy Income generation through informal activity (Ex: crab catching, fishing, daily labor, etc) Embankment Major adaptation strategy Long duration summer Increased temperature in summer Short duration monsoon Monson with heavier rainfall No/less rainfall in Pre-Post monsoon Erratic rainfall Salinity intrusion Average seasonal change Increase in cyclone storm surge frequency-intensity Increase in tidal surge height Water logging Cold spell River erosion Average extreme events (Score: 0 = no impact; 1 = less impact; 2 = moderate impact; 3 = severe impact) External Migration Raised house & tubewell Cyclone shelter Overall Adaptive capacity Specific Vulnerability (E x S) / A Total Vulnerability (E*S)/A 2.56

7 Table 4: Vulnerability Assessment matrix for Gender group (Women) Dakhin Bedkashi, Koyra, Khulna Exposure (impact on livelihood capital) [E] Sensitivity (effect associated with direct impact) [S] Adaptive capacity (A) Context Natural capital Human capital Physical capital Financial capital Social capital Overall Exposure Pro duc tive role Paid employment Activity Profile Reprodu ctive role Activity (without payment) Community management activity Activity (No payment-recreation, motivational, empowering) Resources Access & Control profile Benefit Overall Sensitivity Experience of survival Major coping strategy Income generation through informal activity Embankment External Migration Major adaptation strategy Long duration summer Increased temperature in summer Short duration monsoon Monson with heavier rainfall No/less rainfall in Pre-Post monsoon Erratic rainfall Salinity intrusion Average seasonal change Increase in cyclone storm surge frequency-intensity Increase in tidal surge height Water logging River erosion Average extreme events (Score: 0 = no impact; 1 = less impact; 2 = moderate impact; 3 = severe impact) Raised house & tubewell Cyclone shelter Overall Adaptive capacity Specific Vulnerability (E x S) / A Total Vulnerability (E*S)/A 2.61

8 Key Findings Vulnerability of water resource had been accessed for Padmapukur and Dakhin Bedkashi from a gender view point (i.e. primary user is women) and the vulnerability score is, Padmapukur: 1.52 and Dakhin Bedkashi: This means that, water resource of Dakhin Bedkashi is more vulnerable as perceived by women respondents. For water resource, average of context specific vulnerability and total vulnerability is not equal. Average of specific vulnerability always shows slightly higher value. Respondents perceived that, water resource in Padmapukur is more vulnerable to climate change induced disaster events whereas, in Dakhin Bedkashi, respondents perceive that, water resource is more vulnerable to climate change associated gradual changes. Vulnerability assessment was also done for gender groups (i.e. women) as well and the score shows that, vulnerability of women in Padmapukur: 2.56 and vulnerability of women in Dakhin Bedkashi: The result depicts that, women are relatively more vulnerable in Dakhin Bedkashi union comparing to Padmapukur union. For Padmapukur, average of context specific vulnerability is greater that total vulnerability and for Dakhin Bedkashi, they are equal. Also, interestingly, women from Padmapukur perceived that, they are more vulnerable to climate change associated gradual changes whereas in the case of Dakhin Bedkashi, women perceived that, their vulnerability is greatly associated with climate change induced disasters. This difference in perception could be further cross checked with various disaster reports to access the strength of their perception. However, the difference in perception might also be linked to the geo-physical context of the study areas and security of livelihood generation options in the face of climate change. The matrixes were developed to access gender dimension of vulnerability in most simplest way possible, the matrixes follows simple equation and calculation, no complexities were associated with weighted values, provide good opportunity for comparison. However, the major weakness of the system is that, there was no provision to incorporate negative values in the matrix. In absence of that, in only shows the impact but do not define if it was positive or negative. 4. CONCLUSIONS Climate change associated vulnerability and risks assessment are complex in nature especially when carried out in socio-economic regime. Also, gender dimension of climate change is often overlooked or inappropriately accessed. In order to bridge the existing gaps and enhance more precise decision making comparing areas of concern and context specific vulnerability two simple vulnerability assessment matrixes have been developed considering the gender dimension of climate change and performance was evaluated in the study. Though there is some limitation in the study but it can be said that, overall performance of the vulnerability assessment matrixes are satisfactory. ACKNOWLEDGEMENTS This paper is prepared using primary data from the sub-project titled as Impact of Climate Induced Disaster on Gender carried out under Climate Change Study Cell (CCSC), BUET, Dhaka. REFERENCES Harmeling, S. (2010). Global Climate Risk Index 2011: Who Suffers Most From Extreme Weather Events? Weather Related Loss Events in 2009 And Germanwatch. GoB. (2009). Bangladesh Climate Change Strategy and Action Plan 2009, Ministry of Environment and Forests (MoEF), Government of the Peoples Republic of Bangladesh (GoB). DoE. (2009). Climate Change and Vulnerability of Bangladesh. Climate Change Cell (CCC), Department of Environment (DoE). (p.3) Turner et al. (2008). A framework for vulnerability analysis in sustainability science. PNAS. Vol. 100, no. 14. ( Action Aid. (Undated). Participatory Vulnerability Assessment: A step-by-step guide for field staff. Action Aid International. UK. CCC. (2008). Climate Change, Gender and Vulnerable Groups in Bangladesh. BASTOB and Centre for Global Change (CGC). Climate Change Cell (CCC), DoE, MoEF; Component 4b, CDMP, MoFDM. Dhaka.

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