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Climate Change Vulnerability Assessment Report of Birendranagar Municipality
Climate Change Vulnerability Assessment Report of Birendranagar Municipality
I
Executive Summary Nepal’s National Adaptation Plan (NAP) formulation process has proposed a framework for vulnerability and Risk Assessment (VRA) using Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR-5) as a base. The IPCC framework considers risk as a function of hazard, exposure, and vulnerability (GoN, MOPE, 2017). Making decisions and efficiently allocating resources to reduce the vulnerability of communities requires, among other things, an understanding of the factors that make a society vulnerable to climate hazards. This report summarizes the systemic perspective to identify and analyze the vulnerability, resilience, and adaptive capacity within several socio-ecological systems of Birendranagar Municipality of Surkhet district. Though Surkhet district is ranked one of the less vulnerable districts in the National Adaptation Program of Action (NAPA), 2010 by Government of Nepal (GoN), Birendranagar exhibits several range of vulnerabilities on different aspects. In order to identify the vulnerability of different wards of the municipality and to develop the adaptation plans, vulnerability assessment was conducted in all the 16 wards of Birendranagar municipality.
The VRA has been recognized globally as a critical step in adaptation planning and implementation.
(IPCC, 2014) Though assessing vulnerabilities is critical but commonly overlooked foundational step
in developing a comprehensive adaptation plan whatever be the scale. Knowing what vulnerabilities
exist and could therefore be exploited allows communities to pool that information with their
knowledge of potential risks and threats to the communities and build their plans accordingly.
Through the evaluation of physical and biological environment, policies and common practices,
vulnerabilities can be identified and then proactively addressed.
This report summarizes the detailed vulnerability assessment of Birendranagar Municipality divided
into 5 chapters with several sub headings. Chapter 1 is the introductory chapter which briefly
summarizes the Nepal’s climate change context and climate change impacts, Nepal’s vulnerability
ranking along with the VRA framework and background information.
Chapter 2 focuses on the literature on national and international climate change issues, national
policies on climate change such as climate change policy, 2011, National Adaptation Program of
Action, 2010, Local Adaptation Plan of Action (LAPA, 2012) and several climate change issues Nepal is
concerned.
Chapter 3 whereas is an elaborated chapter with methodology and study design which summarizes
VA Framework, Study Approach and Vulnerability Tools and Indicators. This chapter covers the
description about the detail methodological approach and the steps involved in VA.
Chapter 4 is about the Detail Vulnerability Assessment/Data Analysis and Interpretation focusing on
Climate Change Trend and Scenario (Temperature and Precipitation), Extreme Events, Hazards,
Exposure, Sensitivity, Adaptive Capacity, Vulnerability, and Adaptation Planning. Chapter 5 is a
concluding chapter and incorporates the basic findings of the assessment along with the overall
Vulnerability Index (VI) ranking of all the wards. Conclusion and recommendations follows the later
section of this chapter.
II
Abbreviations AR: Assessment Report
CCA: Climate Change Adaptation
CEN: Clean Energy Nepal
CWGs: Cross Cutting Working Groups
DRRMC: Disaster Risk Reduction Management Committee
FGD: Focus Group Discussion
GoN: Government of Nepal
INDC: Intended Nationally Determined Contribution
IPCC: Intergovernmental Panel on Climate Change
LAPA: Local Adaptation Plan of Action
LDCs: Least Developed Countries
MoPE: Ministry of Population and Environment
NAP: National Adaptation Plan
NAPA: National Adaptation Program of Action
NCCSP: National Climate Change Support Program
NPR: Nepalese Rupees
NSMC: Nepalgunj Sub-Metropolitan City
SDGs: Sustainable Development Goals
Sq. km: square kilometers
TWGs: Thematic Working Groups
UNDP: United Nations Development Program
UNFCCC: United Nations Framework Convention on Climate Change
VDC: Village Development Committee
VI: Vulnerability Index
VRA: Vulnerability and Risk Assessment
WEC: Women Empowerment Center
III
Contents Executive Summary ................................................................................................................................. I
Abbreviations ......................................................................................................................................... II
List of Figures ......................................................................................................................................... V
List of Tables ......................................................................................................................................... VI
Chapter 1 ................................................................................................................................................ 1
Introduction ........................................................................................................................................... 1
Background ........................................................................................................................................ 1
Key Terminologies .............................................................................................................................. 2
Purpose of the Study .......................................................................................................................... 4
Study Area .......................................................................................................................................... 4
Chapter 2 ................................................................................................................................................ 6
Literature Review ................................................................................................................................... 6
Chapter 3 ................................................................................................................................................ 8
Methodology and Study Design ............................................................................................................. 8
Vulnerability Assessment Framework ............................................................................................... 8
Study Approach .................................................................................................................................. 9
Vulnerability Tools and Indicators ................................................................................................... 10
a. Indicators for Hazards .......................................................................................................... 10
b. Indicators for Exposure ........................................................................................................ 11
c. Indicators of Sensitivity ........................................................................................................ 11
d. Indicators of Adaptive Capacity ........................................................................................... 11
Chapter 4 .............................................................................................................................................. 12
Detail Vulnerability Assessment/ Data Analysis and Interpretation ................................................... 12
a. Climate Change Trend and Scenario (Temperature and Precipitation) ................................... 12
Analysis of rainfall statistics over the past 30 years ........................................................................ 12
Analysis of temperature statistics over the past 30 years ............................................................... 15
b. Extreme Events ........................................................................................................................ 23
c. Hazards ..................................................................................................................................... 23
d. Exposure ................................................................................................................................... 24
e. Seasonal Calendar .................................................................................................................... 25
f. Crop Calendar .......................................................................................................................... 26
g. Sensitivity ................................................................................................................................. 27
h. Vulnerability Ranking of Households (HH) ............................................................................... 27
i. Impacts of Climate Change on Forest Ecosystem .................................................................... 28
j. Impacts of Climate Change on Agro Ecosystem....................................................................... 29
IV
k. Impacts of Climate Change on Livelihood ................................................................................ 30
l. Impacts of Climate Change on Gender and Marginalized Group ............................................ 31
m. Adaptive Capacity ................................................................................................................ 33
n. Vulnerability ............................................................................................................................. 34
o. Adaptation Planning................................................................................................................. 36
Chapter 5 .............................................................................................................................................. 37
Conclusion and Recommendations ..................................................................................................... 37
Recommendations ........................................................................................................................... 39
References ........................................................................................................................................... 39
Annex ................................................................................................................................................... 39
V
List of Figures Figure 1: Climate Change Vulnerability and Risk Assessment Framework ............................................ 8
Figure 2: Schematic Diagram of Study Design ....................................................................................... 9
Figure 3: Trend in yearly amount of precipitation in Birendranagar, derived from daily measurement
data. Days with missing data are not included in this analysis ............................................................ 13
Figure 4: Number of days with strong rainfall in Birendranagar, classified by amount of rain.
Moderate rain >50-80 mm/day, Heavy rain >80-120 mm/day, Very heavy rain >120-200 mm/day,
Extreme rain >200 mm/day. Days with missing data are not included in this analysis ....................... 13
Figure 5: Amount of rainfall by season in Birendranagar municipality (Pre-Monsoon: Mar-May,
Monsoon: Jun-Sep, Post-Monsoon: Oct, Winter: Nov-Feb). Days with missing data are not included
in this analysis ...................................................................................................................................... 14
Figure 6: Change in annual rainfall projected by the PRECIS climate model for the period 2011-2040
for Nepal (Source: GoN, 2014) ............................................................................................................. 14
Figure 7: Change in annual rainfall projected by the PRECIS climate model for the period 2041-2070
for Nepal (Source: GoN, 2014) ............................................................................................................. 15
Figure 8: Change in annual rainfall projected by the PRECIS climate model for the period 2071-2098
for Nepal (Source: GoN, 2014) ............................................................................................................. 15
Figure 9: Monthly mean temperatures and trend over 31 years in Birendranagar municipality ....... 16
Figure 10: Monthly mean of daily maximum temperatures and trend in Birendranagar municipality
............................................................................................................................................................. 16
Figure 11: Monthly mean of daily minimum temperatures and trend in Birendranagar municipality 17
Figure 12: Trend in annual mean maximum temperature, derived from seasonal averages of daily
maximum temperatures ...................................................................................................................... 17
Figure 13: Trend in annual highest maximum temperatures, derived from seasonal maxima .......... 18
Figure 14: Change in annual maximum temperature projected by the PRECIS climate model for the
period 2011-2040 for Nepal (Source: GoN, 2014) ............................................................................... 18
Figure 15: Change in annual maximum temperature projected by the PRECIS climate model for the
period 2041-2070 for Nepal (Source: GoN, 2014) ............................................................................... 19
Figure 16: Change in annual maximum temperature projected by the PRECIS climate model for the
period 2071-2098 for Nepal (Source: GoN, 2014) ............................................................................... 19
Figure 17: Trend in annual mean minimum temperature, derived from seasonal averages of daily
minimum temperatures ....................................................................................................................... 20
Figure 18: Trend in annual lowest minimum temperatures, derived from seasonal minima ............. 20
Figure 19: Change in annual minimum temperature projected by the PRECIS climate model for the
period 2011-2040 for Nepal (Source: GoN, 2014) ............................................................................... 21
Figure 20: Change in annual minimum temperature projected by the PRECIS climate model for the
period 2041-2070 for Nepal (Source: GoN, 2014) ............................................................................... 21
Figure 21: Change in annual minimum temperature projected by the PRECIS climate model for the
period 2071-2098 for Nepal (Source: GoN, 2014) ............................................................................... 22
Figure 23: Categorization of Very Highly Vulnerable HHs in Birendranagar Municipality .................. 27
Figure 24: Categorization of Vulnerable HHs ....................................................................................... 28
Figure 25: Climate Change Impacts in Forest Ecosystem .................................................................... 28
Figure 26: Climate Change Impacts on Agro Ecosystem ...................................................................... 29
Figure 27: Ward wise scoring of Climate Change Impacts on Livelihood Aspects ............................... 30
Figure 28: Climate Change Impacts on Different Livelihood Resources .............................................. 31
Figure 29: Climate Change Impacts on Different wards based on Ethnicity ....................................... 31
Figure 30: Climate Change Impacts on different Categories ............................................................... 32
VI
Figure 31: Public Perception about Major Threats to Communities ................................................... 33
Figure 32: Vulnerability Index of Wards .............................................................................................. 38
List of Tables Table 1: Recorded Extreme Events in Birendranagar .......................................................................... 23
Table 2: Seasonal variation of different events in Birendranagar ....................................................... 25
Table 3: Comparison of cropping and harvesting of several major crops in Birendranagar ............... 26
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Chapter 1
Introduction
Background
Climate Change has emerged as one of the high-flying challenges throughout the world in recent
decades. Climate Change has impacted all walks of life on the Earth. Climate change poses severe
threats to the countries like Nepal given the undulated terrain and geographic setting; Surkhet is not
an exception, technological and budgetary constraints and least preparedness; poor communities
suffering the most. Nepal is a disaster-prone country, particularly to floods and landslides and will be
more prone and direly affected in the future. Nepal is ranked as the one of the most climate vulnerable
countries to the effects of climate change worldwide. Nepal is the 50th most vulnerable country and
the 58th least prepared country to cope with climate stressors (ND-GAIN index, 2013) while it’s the
top 20 most disaster prone countries in the world (DFID, 2011). Nepal is ranked as the 4th most
vulnerable countries in terms of climate change impacts (IPCC, 2014). More variable precipitation will
have negative impacts on agriculture, particularly the majority of farmers who rely on rain-fed
farming. With an increase in the intensity of summer monsoon rains the risk of flood and landslide
has significantly increased in Birendranagar. Urban centers are of no excuse when it comes to
vulnerability and sustainability.
Nepal Government has endorsed National Adaptation Program of Action (NAPA), 2010, Climate
Change Policy, 2011 and Local Adaptation Plan of Action (LAPA), 2012 to address the challenges and
impacts associated with climate change. All these documents have prioritized local adaptation to
strengthen the communities and minimize the loss and damage of climate change impacts.
Clean Energy Nepal (CEN) together with Oxfam in Nepal and Arboanut conducted vulnerability assessment in all the 16 wards of Birendranagar Municipality, Surlhet highlighting the need for vulnerable communities and municipalities to adapt with the climate change disasters. This study was conducted in two municipalities in the Mid-western region of Nepal, Nepalgunj Sub Metropolitan City (500km west of Kathmandu) in Banke district and Birendranagar Municipality (600km north-west of Kathmandu) in Surkhet district. Supported by the Nordic Development Fund (NDF), this study was facilitated by Bheri Environmental Excellence (Bee) Group; Banke and Environment Development Society (EDS), Surkhet in close coordination local municipalities. The assessment was conducted with reference to and as guided by the LAPA framework and revised as per the IPCC-AR 5. Under various climate change scenarios for Nepal, mean annual temperatures are projected to increase between 1.3-3.8°C by the 2060s and 1.8-5.8°C by the 2090s (INDC, 2016). Nepal Disaster Report, 2013 states that in the past 41 years (1971-2012), the most frequent disasters to hit Nepal are fire, flood, landslides and epidemics respectively. Floods had affected the largest number of families, followed by landslides and epidemics across Nepal. Epidemics had caused the highest number of fatalities, followed by landslides, floods and fire. In 2012, disaster events had damaged 3,559 houses totally or partially, 1,181 livestock were lost and 18% reduction in production of paddy compare to 2011 across Nepal. Total economic loss calculated to be NPR. 1.2 billion (Equivalent to USD 12 million) in 2012. NAPA, 2010 identified ‘urban settlement and infrastructure’ as one of the six priority sectors most
vulnerable to impacts of climate change. NAPA further elaborated climate change impacts in urban
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settlements both directly and indirectly. Direct impacts are disastrous floods and reduction of
freshwater supplies. Indirect impacts could be experienced during extreme weather events when food
prices will increase and/or livelihood assets of vulnerable communities will be damaged. Climate
resilient urban settlements and infrastructure require improved and effective and pro-poor structures
of governance. Capacitated government authorities need to be responsive and accountable towards
the most vulnerable and needy population by ensuring these group’s participation in decision making.
NAPA has indentified two policy gaps;
a) reducing the exposure to impacts of climate change through adopting mitigation measures
and
b) Improving the adaptive and absorptive capacities of the vulnerable communities to enable
them to deal with shocks, stresses and uncertainties and thrive with
Key Terminologies
Adaptive capacity (in relation to climate change impacts): The ability of systems, institutions, humans, and other organisms to adjust to potential damage, to take advantage of opportunities, or to respond to consequences of climate change.
Climate trends: Climate trends are the patterns in climate variables such as temperature and precipitation observed in historic datasets.
Climate projection: A projection of the response of climate system to emissions or concentration scenarios of greenhouse gases and aerosols, or radiative forcing scenarios, often based upon simulations by climate models. Climate projections are distinguished from climate predictions in order to emphasize that climate projections depend upon the emission/ concentration/radiative forcing scenario used, and that these scenarios are subject to substantial uncertainty as they are based on assumptions concerning future socio-economic and technological developments and others that may or may not be realized. Climate extreme events:
Climate extreme is the event occurrence of a value of a weather or climate variable above (or below) a threshold value near the upper (or lower) end of the observed values of the variable such as high temperatures (e.g., heat waves), or extremely heavy rainfall. Disaster: Severe alterations in the normal functioning of a community or a society due to hazardous physical events interacting with vulnerable social conditions, leading to widespread adverse human, material, economic, or environmental effects that require immediate emergency response to satisfy critical human needs and that may require external support for recovery. Exposure: The presence of people, livelihoods, species or ecosystems, environmental functions, services, and resources, infrastructure, or economic, social, or cultural assets in places and settings that could be adversely affected. Hazard: The potential occurrence of a natural or human-induced physical event or trend or physical impact that may cause loss of life, injury, or other health impacts, as well as damage and loss of property, infrastructure, livelihoods, service provision, ecosystems, and environmental resources. In
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this report, the term hazard usually refers to climate-related physical events or trends or their physical impacts. Impacts: Effects on natural and human systems. In this report, the term impact is used primarily to refer to the effects on natural and human systems of extreme weather and climate events and of climate change. Impacts generally refer to effects on lives, livelihoods, health, ecosystems, economies, societies, cultures, services, and infrastructure due to the interaction between climate changes or hazardous climatic events occurring within a specific time period, and the vulnerability of an exposed society or system. Impacts are also referred to as consequences and outcomes. The impacts of climate change on geophysical systems, including floods, droughts, and sea level rise, are subset of impacts called physical impacts. Risk: The potential for consequences where something of value is at stake and where the outcome is uncertain, recognizing the diversity of values. Risk is often represented as the probability of occurrence of hazardous events or trends multiplied by the impacts if these events or trends were to occur. Risk results from the interaction of vulnerability, exposure, and hazard. In this report, the term risk is used primarily to refer to the risk of climate-change impacts. Sensitivity: Predisposition of society and ecosystems to suffer harm as a consequence of intrinsic and context conditions making it plausible that such systems once impacted will collapse or experience major harm and damage due to the influence of a hazard event. Threshold: A critical limit within the climate system that induces a non-linear response to a given forcing. Vulnerability: The propensity or predisposition to be adversely affected. Vulnerability encompasses a variety of concepts including sensitivity or susceptibility to harm and lack of capacity to cope and adapt.
Source: (GoN, MOPE, 2017)
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Purpose of the Study
The VA plays important role in preparing plans for formulation of local climate change action especially the adaptation plans. The policies should be in harmony with knowledge and available resources. The basis of which can be achieved through the assessment to collect basic information and one of such assessment is the vulnerability assessment. Many climate change adaptation efforts aim to address the implications or risks of potential changes in the frequency, intensity, and duration of weather and climate events that affect human and natural systems. VA identifies the basic climatic disasters pertinent in the area and the risks that they are exposed to and also identifies the local level adaptation skills. Besides, every community has their own way to manage and adapt to the extremities but most of them are being practiced without specific ideas on how it actually works, whether or not they are sustainable and if they will be useful and impactful at larger scale. The study targets to develop adaptation plan in two municipalities and leverage resources from
private sectors in financing adaptation actions.
The general objective of this study entitled “Building Resilience and Climate Adaptive Planning in
Urban Centers of Nepal” is urban centers of Nepal become people-centered and resilient to climate
extremes and disasters. The specific objectives of the VA are;
✓ To assess the vulnerabilities of different wards of the municipality
✓ To develop adaptation plans based on the findings of vulnerability study
✓ Empower the communities towards resilience future with appropriate technologies and
adaptation skills
Study Area
Though climate-induced hazards such as fire and epidemics are also prevalent, Surkhet district is more
vulnerable to floods, landslides and droughts. Birendranagar lies 600km North-West of Kathmandu in
Surkhet district. Birendranagar is the capital of Mid-western Development Region. Birendranagar
municipality is populated with 100458 in an area of about 245.06 sq. km with population density of
554.54persons/sq. km (Nepal Gazette, 2017).
Birendranagar is ecologically highly sensitive in respect to forest coverage and population density as
loss of Non Timber Forest Products (NTFP) species, drying of wetland, disruption in agro ecosystem
and spread of invasive species is prominent. Potential chances of landslide and mass displacement is
quite high in the municipality as it is situated in a very fragile geography. The flooding during mid of
August 2014 due to incessant rainfall resulted in massive landslides and flooding in 28 districts, of
which 4 districts namely Surket, Banke, Bardiya and Dang were the most severely affected. A total of
96 persons were reported dead, 32 injured and 115 remain listed as missing. In addition a total of
32,900 households (173,437 individuals) have been affected across Surkhet, Banke, Bardiya and Dang,
including 8,578 houses completely damaged and 24,322 houses partially damaged. In Surkhet 3,866
HHs in 27 VDCs and 1 Municipality were affected of which 1,427 HHs were fully damaged and 2,439
partially damaged. Birendraganar suffered from increased frequency of extreme weather events such
as landslides, floods and droughts resulting to the loss of human lives as well as high social and
economic costs.
District Administration Office (DAO), Surkhet has reported 566 HH totally damaged and 301 HH partial
damaged due to massive flood during 2014 where 7 people lost their lives and 1 reported missing. In
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total, 4304 people were affected due to massive flood that destroyed road, bridge, culvert and other
infrastructures equaling up to NRs. 9,95,00,000. A set of 788 non food items and NRs. 1, 66, 83,850
was distributed as relief in Birendranagar only.
Map of Birendranagar Municipality (Jeevan Jee please add the updated Map if available)
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Chapter 2
Literature Review
Climate change has been a global accord in recent past. Needless to say that Nepal is ranked as the
most climate vulnerable countries in the world. Climate change has already posed an additional
challenge to development, especially to the Least Developed Countries (LDCs), and country with
fragile geology like Nepal. The nation’s weather pattern is becoming unpredictable and there is an
urgent need to aware people about climate change and its impact in building climate resilience.
Climate change has been posing additional challenges to the country's socioeconomic development
(GoN, 2011). Serious efforts made to ensure climate change in general and adaptation to climate
change in particular plays an important role in the country’s development agenda. In the same line
Nepal’s Climate Change Policy (2011) sets out the goal to improve people’s livelihoods through climate
change impact mitigation and adaptation activities. The Goal 11 of the Sustainable Development
Goals (SDGs) which states “MAKE CITIES AND HUMAN SETTLEMENTS INCLUSIVE, SAFE, RESILIENT
AND SUSTAINABLE” has also prioritized the need for resilient cities.
NAPA, 2010 was formulated by the GoN to address the short term urgent and immediate impacts of
climate change basically focusing on adaptation needs. Similarly, LAPA was endorsed and formulated
in 2012 to address medium and long term impacts of climate change. GoN has initiated National
Climate Change Support Program (NCCSP) in 14 different districts of Nepal with support from United
Nation Development Program (UNDP). The project supports the existing policies and initiation led by
different sectors and has been designed in line with Local government agencies and the private
sectors and communities. It especially focuses on the most vulnerable sectors to develop and
implement adaptation plans to make cities more resilient to climate extremes and disasters. The
project is expected to achieve four key outputs which includes
i. imbibing climate adaptation and resilience to vulnerable urban centers
ii. developing adaptation friendly policy, practice and business
iii. equipping vulnerable urban dwellers with information, resources and appropriate technology
to respond to and recover climate extremes and disasters and
iv. Knowledge documentation and dissemination
The GoN has recognized climate change adaptation as fundamental to safeguarding climate vulnerable communities and ecosystems. The country has developed legal policy instruments, devised frameworks and strategies on planning and financing, and implemented a number of projects and programs to enhance the resilience of people and their livelihoods. The GoN as a party to the United Nations Framework Convention on Climate Change (UNFCCC) initiated the National Adaptation Plan (NAP) formulation process in September 2015. Ministry of Population and Environment (MoPE) has engaged seven thematic working groups (TWGs) and two Cross-cutting Working Groups (CWGs), which cover the major climate change sensitive sectors in the NAP formulation process. VRA has been recognized globally as a critical step in adaptation planning and implementation (IPCC 2014a). Another new element is the recognition of evidence that the impacts of climate change involve a number of interacting factors, with climate change adding new dimensions and complications. The implication is that understanding the impacts of climate change requires a very broad perspective as risk is not only determined by climate and weather events (hazards) but also by the exposure and vulnerability of the human and natural systems to these events (IPCC 2014a). In order to reduce risk effectively, it is
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essential to understand how vulnerability is generated, how it increases, and how it builds up (O’Brien et al., 2004). Adaptive capacity is another important element in most conceptual frameworks of vulnerability and risk. It refers to the ability of systems, institutions, humans, and other organisms to adjust to potential damage, to take advantage of opportunities, or to respond to consequences (IPCC 2014). The adaptive capacity of the individual, communities, and the government also matters for reducing impact of climate change (Sharma and Patwardhan 2008). VRA is an important element in the NAP formulation process.
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Chapter 3
Methodology and Study Design
The study was designed and performed as guided by the VRA report on Climate Change and
Vulnerability Assessment Framework. During the preliminary study design, the IPCC - AR 4 report was
also reviewed and was gradually updated as per the framework laid by the VRA using IPCC – AR 5 as
a base. Several national and international documents were also reviewed for the design of the study.
The LAPA framework prepared by NCCSP for Devghat VDC of Tanahu district is one of such. Most of
the indicators defined in the framework and relevant ones have been assessed as far as practicable in
the study area.
Vulnerability Assessment Framework
Nepal’s NAP formulation process has proposed a framework for vulnerability and risk assessment (VRA) using IPCC-AR 5 as a base. The IPCC framework considers risk as a function of hazard, exposure and vulnerability. The framework assumes that the risk of climate related impacts results from the interaction of climate-related hazards (including hazardous events and trends) with the exposure and vulnerability of human and natural systems. Changes in the climate system (trends and scenarios), biophysical system, and socioeconomic processes (including governance and adaptation and mitigation actions) are drivers of hazards, exposure, and vulnerability.
Figure 1: Climate Change Vulnerability and Risk Assessment Framework
Source: VRA Framework and Indicators, GoN, 2017
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Study Approach
The study approach followed a series of steps and procedures which is presented in the schematic
diagram below. The steps of the study approach are briefly described below.
Figure 2: Schematic Diagram of Study Design
1. Modular Training Series
Modular training series was conducted in Birendranagar on Climate Change Adaptation (CCA) and
mitigation and develop a general understanding of climate change impacts, mitigation and adaptation
to the selected mobilizers. One of the objectives was to capacitate the mobilizers and enhance their
knowledge base on climate change issues. The same mobilizers were then mobilized for the data
collection.
2. Vulnerability Assessment Framework Development
A framework was designed for the questionnaire survey through FGD. Several consultations with the
NAP expert team members and government officials were made before finalizing and agreeing the
VRA framework prepared.
Modular Training Series
VRA Framework Development
Orientation on VRA Framework
Focus Group Discussion (FGD)
Data Analysis & Projection
Data Verification/Validation
VRA Report and Adaptation Planning
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3. Orientation on VRA Framework
VRA framework preparation was the followed by orientation on VRA framework to both local
government authorities and the mobilizers and all the variables, indicators and parameters were
defined. This stage also involved some exercises on conducting VRA as social survey through FGD.
4. Focus Group Discussion (FGD)
Focus Group Discussion was conducted at every wards of the municipality, to collect information
and assess the situation and vulnerability index of all wards in different aspects as far as practicable.
5. Data Analysis & Projection
After data collection, the data were entered and tabulated in Microsoft excel for required analysis
and synthesis. After the preliminary findings were drawn, the data and the findings were projected
and shared among the stakeholders for review, validation and verification. Very positive feedbacks
along with request for some additional verification were made by the municipality officials.
6. Data Verification/Validation
The projection was followed by validation and verification of data through comparison with available
references and consultation with the relevant stakeholders. To make sure not to miss the new wards
under the federal structure included, FGD was repeated in those wards which were newly added or
merged into the municipality.
7. VRA Report and Adaptation Planning
After going through all the steps above, VRA report was prepared which will be a foundation for
developing adaptation plans in the wards based on the vulnerability each wards are supposed to be
dealt with.
Vulnerability Tools and Indicators
Vulnerability Assessment survey was conducted in Birendranagar Municipality. The indicators of VA
such as crop calendar, seasonal calendar, major historical calamities were analyzed and significant
changes has been observed in the cropping and harvesting patterns which supports climate change
has altered the agricultural patterns. Also different wards have different level of vulnerability on
different fronts as forest ecosystem, agro-ecosystem and ethnicity. The tools for vulnerability
assessment such as exposure, sensitivity and adaptive capacity were assessed.
The average scoring for the indicators under different tools was derived based on the scoring range
of 1-4 (1=very low or no vulnerable, 2=moderately vulnerable, 3=highly vulnerable and 4=very highly
vulnerable). The indicators defined and evaluated under the tools were as guided by the VRA (GoN,
MOPE, 2017) Report. The major indicators are briefed hereunder.
a. Indicators for Hazards
The indicators under the hazard are climate extreme events such as heat and cold waves, cold and
dry days as well as climate induced hazards like drought, flood, inundation, hailstorm etc were also
assessed. Sector specific hazards included crop (land) inundation, temperature variation, disease
outbreak and seasonal shifting of cropping pattern.
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b. Indicators for Exposure
These indicators were analyzed through the changes in seasonal calendar of current and 25-30 years
back. The crops, cropping and harvesting duration and time of the year were also studied under the
exposure. Impacts on agriculture, livestock, and major historical events were also the indicators under
this theme.
c. Indicators of Sensitivity
The sensitivity is inclination of society or livelihood aspects to suffer or harm as the consequence of
climate change impacts. Impacts of Climate Change in Forest Ecosystem, Agro Ecosystem, Livelihood
and, gender and marginalized groups and Vulnerable HH were assessed.
d. Indicators of Adaptive Capacity
The indicators defined and evaluated under the adaptive capacity included availability of natural
resources and access, trade and technology, economic empowerment, adaptation practice based on
agriculture, resource management, institutional arrangement and resource allocation, provision of
disaster risk reduction management plans (DRRMP)and budget, capacity building, climate resilient
buildings and development practices and the likes. Food security, income, poverty, market networks
and linkages, production and consumption, improved breed and seeds, climate resilient production
are some of the indicators under the study of adaptive capacity.
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Chapter 4
Detail Vulnerability Assessment/ Data Analysis and Interpretation
The major objective of the detailed VA in the wards was to identify the climatic risks and the degree
of vulnerability. Also the assessment aimed at digging down the adaptation skills and practices being
practiced at the local level to combat the impacts of climate change. It was found that different wards
are exposed to different climatic threats and are adapting them differently. Though the degree or the
intensity of the disaster varies with wards, the adaptation practices are common in general. The
economical and social loss and damages associated with the climatic disasters are higher in the wards
which have observed frequent and high intensity events. Capacity is an important element in most
conceptual frameworks of vulnerability and risk. It refers to the positive features of people’s
characteristics that may reduce the risk posed by a certain hazard. Improving capacity is often
identified as the target of policies and projects; based on the notion that strengthening capacity will
eventually lead to reduced risk. Capacity clearly also matters for reducing the impact of climate
change.
The vulnerability associated with the impacts of climate change is known as climate change
vulnerability. Climate change has a wide range of impacts on different aspects of the environment like
biodiversity, agriculture ecosystem, forest ecosystem; ethnicity and livelihood that were assessed
during the VA.
a. Climate Change Trend and Scenario (Temperature and Precipitation)
Observing climate change scenarios and the trend of increasing temperature for over past 30 years
(based on local experience) there has been tremendous turnabout in weather pattern as well as
climatic conditions. Monsoon has almost 2 months of variation whereas the summer and winter has
change about 3 months. Though the annual average precipitation is almost identical, the number of
monsoon days has decreased significantly. This indicates high intense rainfall for a relatively short
period of time. This threatens flash flood and landslide along with several impacts on basic livelihood
resources. The details of seasonal changes and fluctuations are presented in the later section.
Analysis of rainfall statistics over the past 30 years
Based on the available daily rainfall statistics for the period 1985-2015, yearly rainfall in Birendranagar
has been varying between 975 and 2114 mm per year and is on average 1354 mm. The derived tren
dline indicates that the rainfall amount per year has decreased (Error! Reference source not found.).
The analyzed precipitation statistics show that heavy rains do occur regularly (Error! Reference source
not found.). Over the 31-year period, the most extreme reported rainfall event has been 423 mm on
15.08.2014. The largest amount of rain falls during the monsoon season (June-September), on
average 1333 mm (Error! Reference source not found.). During the Pre-Monsoon season (March-
May) the average amount of rain is only 144 mm, while during the winter period (November-
February) the community receives on average 103 mm rainfall.
If we assume that the trend derived from the yearly rainfall amounts over the past 30 years is stable
(Error! Reference source not found.), the projection for the next 30 years would be a decrease in
annual rainfall by 112 mm. This value was compared to the simulation results projected with the
13
PRECIS high-resolution regional climate model (GoN 2014). The PRECIS model forecasts for
Birendranagar a decrease in annual rainfall of 50 to 100 mm by year 2040. The long-term projection
by the PRECIS model predict an increase in annual rainfall between 50 mm and 150 mm by year 2070
and between 250 mm and 300 mm by year 2098.
Figure 3: Trend in yearly amount of precipitation in Birendranagar, derived from daily measurement data. Days with missing data are not included in this analysis
Figure 4: Number of days with strong rainfall in Birendranagar, classified by amount of rain. Moderate rain >50-80 mm/day, Heavy rain >80-120 mm/day, Very heavy rain >120-200 mm/day, Extreme rain >200 mm/day. Days with
missing data are not included in this analysis
14
Figure 5: Amount of rainfall by season in Birendranagar municipality (Pre-Monsoon: Mar-May, Monsoon: Jun-Sep, Post-Monsoon: Oct, Winter: Nov-Feb). Days with missing data are not included in this analysis
Figure 6: Change in annual rainfall projected by the PRECIS climate model for the period 2011-2040 for Nepal (Source: GoN, 2014)
15
Figure 7: Change in annual rainfall projected by the PRECIS climate model for the period 2041-2070 for Nepal (Source: GoN, 2014)
Figure 8: Change in annual rainfall projected by the PRECIS climate model for the period 2071-2098 for Nepal (Source: GoN, 2014)
Analysis of temperature statistics over the past 30 years
The daily mean temperature was calculated from the daily maximum and minimum temperature
values provided by DHM for 1985-2015. Based on the recorded data, the average yearly temperature
has been 22.0°C in Birendranagar during the 31-year period. The monthly mean temperature has
increased by 0.03°C per year (Error! Reference source not found.). An even stronger increase was
found for the monthly mean of the daily maximum temperatures in Birendranagar, namely +0.07°C
16
per year on average (Error! Reference source not found.), while the mean of the daily minimum
temperatures stayed about the same (Error! Reference source not found.).
For the calculation of the monthly mean values, those months with more than 5 missing daily values
were replaced by the average for the same month from all the other years with sufficient data
coverage.
The highest and lowest recorded temperatures between 1985 and 2015 have been 42.8°C
(14.06.2012) and -0.7°C (09.01.2013), respectively.
Figure 9: Monthly mean temperatures and trend over 31 years in Birendranagar municipality
Figure 10: Monthly mean of daily maximum temperatures and trend in Birendranagar municipality
17
Figure 11: Monthly mean of daily minimum temperatures and trend in Birendranagar municipality
Two types of annual maximum temperatures were calculated and trends were derived. Firstly, the
annual mean maximum temperature was derived from seasonal averages: The daily maximum
temperatures were averaged for each season (winter, pre-monsoon, monsoon, post-monsoon) and
the seasonal means were averaged to get the annual value. This parameter shows an increase over
the past 30 years and the derived trend is +0.066 °C/year (Error! Reference source not found.). If we
assume this trend to be stable, the mean maximum temperatures will increase by 1.98 °C over the
next 30 years. Secondly, an annual average of the highest maximum temperatures was derived from
the seasonal maxima: For each season, the highest measured temperature was extracted and the
seasonal maxima were then averaged to get the annual value. This parameter shows an increase over
the past 30 years with a trend of +0.065 °C/year (). If this trend is assumed to be stable, we can expect
an increase of the highest maximum temperatures by 1.95 °C over the coming 30 years.
Figure 12: Trend in annual mean maximum temperature, derived from seasonal averages of daily maximum temperatures
18
Figure 13: Trend in annual highest maximum temperatures, derived from seasonal maxima
In comparison, the PRECIS climate model (GoN 2014) projects an increase of the annual maximum
temperature between 1.0°C and 1.2°C until 2040 for Birendranagar area (Error! Reference source not
found.). The long-term projections by the PRECIS model predict an increase of the annual maximum
temperature between 2.3°C and 2.4°C by year 2070 and between 3.6°C to 3.8°C by year 2098 (Error!
Reference source not found. and Error! Reference source not found.). However, it is not clear from
the GoN 2014 report how the annual minimum was derived, which means it is not clear to which of
the two parameters presented above it would compare best.
Figure 14: Change in annual maximum temperature projected by the PRECIS climate model for the period 2011-2040 for Nepal (Source: GoN, 2014)
19
Figure 15: Change in annual maximum temperature projected by the PRECIS climate model for the period 2041-2070 for Nepal (Source: GoN, 2014)
Figure 16: Change in annual maximum temperature projected by the PRECIS climate model for the period 2071-2098 for Nepal (Source: GoN, 2014)
Similarly, two types of annual minimum temperatures were calculated and trends were derived for
Birendranagar. Firstly, the annual mean minimum temperature was derived from seasonal averages:
The daily minimum temperatures were averaged for each season (winter, pre-monsoon, monsoon,
post-monsoon) and the seasonal means were averaged to get the annual value. This parameter shows
a very small decrease over the past 30 years and the derived trend is -0.003 °C/year (Error! Reference
source not found.). If we assume this trend to be stable, the mean minimum temperatures will
decrease by 0.09 °C over the next 30 years. Secondly, an annual average of the lowest minimum
temperatures was derived from the seasonal minima: For each season, the lowest measured
temperature was extracted and the seasonal minima were then averaged to get the annual value. This
parameter also shows a decrease over the past 30 years with a trend of -0.009°C/year (Error!
20
Reference source not found.). If this trend is assumed to be stable, we can expect a decline of the
lowest minimum temperatures by 0.27 °C over the coming 30 years.
Figure 17: Trend in annual mean minimum temperature, derived from seasonal averages of daily minimum temperatures
Figure 18: Trend in annual lowest minimum temperatures, derived from seasonal minima
21
In comparison, the PRECIS climate model (GoN 2014) projects an increase of the annual minimum temperature between 1.3°C and 1.5°C until 2040 for Birendranagar area (
Figure 19: Change in annual minimum temperature projected by the PRECIS climate model for the period 2011-2040 for Nepal (Source: GoN, 2014)
). The long-term projections by the PRECIS model predict an increase of the annual minimum temperature between 2.9°C and 3.0°C by year 2070 and between 3.4°C to 3.6°C by year 2098 (
Figure 20: Change in annual minimum temperature projected by the PRECIS climate model for the period 2041-2070 for Nepal (Source: GoN, 2014)
22
and
Figure 21: Change in annual minimum temperature projected by the PRECIS climate model for the period 2071-2098 for Nepal (Source: GoN, 2014)
). However, it is not clear from the GoN 2014 report how the annual minimum was derived, which
means it is not clear to which of the two parameters presented above it would compare best.
Figure 19: Change in annual minimum temperature projected by the PRECIS climate model for the period 2011-2040 for Nepal (Source: GoN, 2014)
23
Figure 20: Change in annual minimum temperature projected by the PRECIS climate model for the period 2041-2070 for Nepal (Source: GoN, 2014)
Figure 21: Change in annual minimum temperature projected by the PRECIS climate model for the period 2071-2098 for Nepal (Source: GoN, 2014)
24
b. Extreme Events
Year
Flo
od
an
d
Lan
dsl
ide
Dro
ugh
t
Rai
n w
ith
Hai
lsto
ne
Win
dst
orm
Fire
Thu
nd
erst
or
m
Eart
hq
uak
e
2027/28 13 3 1
2031/32 2
2042/43 2 5 3
2044/45 1 1 1
2046/47 4 1 1 1
2048/49 3 1 1
2051/55 1 1 2
2058 6 1
2061 1 1
2066/67 3 1 1
2069/70 2
2071/72 23 1 10
2073 1
Total 48 5 10 11 5 10 10
Table 1: Recorded Extreme Events in Birendranagar
Major historical events dated back to B.S. 2027/28 were received from the survey. Flood and
landslide, wind storm, fire, thunderstorm and earthquake events are found markedly increased in last
20 years while events of drought and rain with hailstone are not observed during the last 20 years
period. There have been 48 flood and landslide events in last 46 years on which 26 events occurred in
last 20 years. Both the flood and landslide and windstorm occurrence are more frequent since past 2
decades. In 2072, all the 23 wards were affected by massive flood. The flood and landslide is observed
almost every year in average. This might be the result of high intensity rainfall in short time. Similarly,
11 events of windstorm were observed in 46 years where 10 events occurred in last 15 years. This
might have relation on longer drought which we found on seasonal calendar as drought events
promote (trigger) the fire events.
c. Hazards
Floods, landslides, windstorms, hailstorms, dry days and consecutive cold days, epidemic and disease
outbreak are some major indicators on VRA climate induced disasters. The study revealed that
drought, landslide, flood and fire are major hazards in the municipality. Intolerable temperatures
during hot summer days, drought and water scarcity, hazy and fogy winter days has been troublesome
for people in general.
25
d. Exposure
The presence of people, livelihoods, species or ecosystems, environmental functions, services, and
resources, infrastructure, or economic, social, or cultural assets in places and settings that could be
adversely affected is the exposure. The exposure is a measure of how closely the community suffers
or how intensely the climate change impacts are prevalent in that area. It is a relative measure of
people’s interaction and interdependence with the associated impacts. Seasonal calendar, Crop
calendar and major historical incidents/events were studied to assess the exposure.
26
e. Seasonal Calendar
Based on the seasonal calendar, changes in weather events are observed. Monsoon period has
markedly decreased from four and a half months to two and a half months. It has shifted from Jestha
to mid Ashad. The winter has been restricted for just three months that used to be almost five months
while the summer months have increased significantly. Changes are observed in storm events
hailstones occurrence. These changes in seasonal pattern and weather events shows the climate
change have already started to affect the Birendranagar municipality. We can conclude that there
have been significant changes in the seasonal weather pattern based on the seasonal calendar.
Hazard
Situ
atio
ns
Bai
shak
Jest
ha
Ash
ar
Shra
wan
Bh
adra
Ash
oj
Kar
tik
Man
gsir
Po
ush
Mag
h
Falg
un
Ch
aitr
a
Rainfall Before
Winter
Now
Before
Summer
Now
Before
Storms
Now
Before
Hailstorms
Now
Before
Monson
Haze
Now
Cold
Waves
Table 2: Seasonal variation of different events in Birendranagar
27
f. Crop Calendar
Crops Month
Bai
sakh
Jest
ha
Ash
ar
Shra
wan
Bh
adra
Ash
win
Kar
tik
Man
gsir
Po
ush
Mag
h
Falg
un
Ch
aitr
a
Maize Previously
Present
Wheat Previously
Present
Mustard Previously
Present
Cereals Previously
Present
Rice Previously
Present
Vegetables Previously
Present
Soybean/Pea Previously
Present Soybean is No More Cultivated Potato Previously
Present
Table 3: Comparison of cropping and harvesting of several major crops in Birendranagar
Cropping time
Harvesting Time
Off Season farming started
No Cultivation Now
The crop calendar shows variations in cropping and harvesting pattern. The calendar is a comparison
of present and past (25-30 years). Wheat cropping has been decreased by two months while
harvesting pattern is almost identical due to the fluctuations in the seasonal patterns. The farmers
had no option to combat climate change and the changing weather pattern but are left with shifting
the cropping pattern as suited for the seeds they wants. With change in the weather and rainfall
pattern, there have been changes in wheat, mustard and rice cultivation. Especially rice used to be
planted during three months of Ashad, Shrawn and Bhadra and harvested during the two and a half
month from the end of Kartik to Poush. The cropping time has now shortened to just two month of
28
Aashad and Shrawn and harvesting towards the end of Mangsir to Poush. This shortened time of
cropping forced farmers to rely on short availability of monsoon rain and leaves the land uncultivated
forcing to food scarcity and poverty. Similarly, the alteration in cereals cropping is also observed
clearly. Rice and potato are harvested one month earlier than it were done and also decreased the
plantation period. Crop calendar clearly show the changes occurred in plantation and harvesting time
and period. These kinds of fluctuations and shortened cropping time might indicate food insecurity
and short supply. If reports are to be believed, every year, 100 hectares of land becomes barren in
Banke and Surkhet districts only.
From the above findings based on seasonal calendar, crop calendar and major historical incidents,
there have been significant changes in the seasonal calendar and crop calendar. This indicates they
are exposed to several threats. The number and intensity of events are unpredictable, that further
leads to more threats and least preparedness.
g. Sensitivity
It is evident that disasters like flood, landslides, fire, drought, thunderstorm, windstorm, and hailstone
have been repeatedly occurring. From B. S. 2027 to B.S. 2073, the events are being uncertain making
it difficult for preparedness. It has sometimes increased and decreased in some years. From the
findings based on seasonal calendar, crop calendar and major historical incidents, there have been
significant changes in the seasonal calendar and crop calendar. This indicates they are exposed to
several threats. The number and intensity of events are unpredictable, that further leads to more
threats and least time for preparedness.
h. Vulnerability Ranking of Households (HH)
Figure 22: Categorization of Very Highly Vulnerable HHs in Birendranagar Municipality
It was found that ward number 11 has the highest percentage of very highly vulnerable households
with 21.68% followed by ward 2 and 13 with 15.99% and 13.72% respectively. Ward 6 with 1.87% is
the ward with lowest number of very highly vulnerable households.
7.32%
15.99%
1.98%3.67%
9.61%
1.87%
10.95%
5.72%7.65%
3.52%
21.68%
7.35%
13.72%
6.16%
10.80%
5.25%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Very Highly Vulnerable HH Distribution
29
Figure 23: Categorization of Vulnerable HHs
The graph above shows that out of total households in Birendranagar municipality, only 6.75% HH are
very highly vulnerable whereas majority of the HHs are less vulnerable with the impacts of climate
change having a total share of 46.54%.
i. Impacts of Climate Change on Forest Ecosystem
Figure 24: Climate Change Impacts in Forest Ecosystem
To assess the vulnerability in forest ecosystem to climate change, impacts of 11 different hazards on
forest flora and fauna diversity, forest quality, forest management and forest ecosystem services were
considered. The hazards included; drought, storm, thundering, endemics, pests, invasive species,
wildlife attacks, intense rainfall, hailstone, fire and cold waves. The above graph shows that ward
number 14 and 12 are more vulnerable in terms of climate change impacts on forest resources as
compared with the overall wards as highly vulnerable wards. Other wards having score above 2
6.75%
11.60%
35.11%
46.54%
Very HighlyVulnerable HH
Highly VulnerableHH
ModeratelyVulnerable HH
Less/No Vulnerable
Categorization of Vulnerable HH
2.23
1.28
2.16
1.42
1.801.52
2.28
1.57
2.28
1.26
2.56
1.89
2.71
2.05
2.45
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Average Score on Climate Change Impacts on Forest Ecosystem
30
includes ward numbers 1, 3, 8, 10, 15 and 16 with scoring of 2.23, 2.16, 2.28, 2.28, 2.05 and 2.45
respectively. Ward number 11 with score of 1.26 is the ward with lowest vulnerability score on forest
ecosystem.
j. Impacts of Climate Change on Agro Ecosystem
Figure 25: Climate Change Impacts on Agro Ecosystem
Agro ecosystem seems to have more medium impacts due to climate change as the graph shows
above. Ward 15 has the highest score of 2.84 out of 4. Similarly wards 12, 10 and 16 exhibit score of
2.70, 2.50 and 2.50 respectively. The hazards include; landslide, flood and inundation, drought,
invasive species, pests, torrential downpour, thundering and fire. First, the average value of each
hazard was calculated. Ward 6 which has the lowest score of 1.28. This can signify that may people in
ward 6 are not directly involved in agricultural practices or ward 6 lies in the city center with less or
no agricultural practices. For the analysis of the vulnerability of Agro ecosystem, impacts of 8 different
hazards on organisms, cropping pattern, production and change in agro ecosystem were considered.
2.33 2.24 2.31
1.55
2.03
1.28
1.97 1.972.13
2.50
1.34
2.70
2.161.97
2.84
2.50
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Average Score of Climate Chnage Impacts on Agro Ecosystem
31
k. Impacts of Climate Change on Livelihood
Figure 26: Ward wise scoring of Climate Change Impacts on Livelihood Aspects
In this study, five major resources were considered to map the resource vulnerability due to climate
change. The five resources included; (i) Natural resources (Land, water sources, forests, wildlife), (ii)
Economic resources (Agriculture, Animal Husbandry, Foreign Employment, Pension and Business), (iii)
Social resources (Aama samuha, Children club and youth club), (iv) Physical resources (Roads,
Community building, drinking water, Schools and irrigation) and (v) Human resources (teachers,
health assistant and students). First, the average impact value of each resource was calculated. Then,
the average value of the all five resources was taken to calculate a grand average. This grand average
was taken as a resource average vulnerability value for each ward.
From the above diagram, we found that all the wards are moderately vulnerable in terms of resource
vulnerability as the average score lies between 1 and 2. Wards 14, 15 and ward 11 with score of 1.95,
1.91 and 1.82 respectively are the most vulnerable among the 16 wards of the municipality. Different
types of livelihood resources like natural resources, social, physical, economic and human resources
face different level of stresses and we tried to identify the aspects of natural, social, economic,
physical and human resources due to climate change impacts. It is clear that different resources have
different degree of vulnerability on different livelihood aspects which is shown in the figure below.
1.591.75 1.76
1.45 1.48
1.14
1.551.73
1.63 1.661.82
1.60 1.62
1.95 1.911.81
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Average Score of Climate Change Impacts on Livelihood Resources
32
Figure 27: Climate Change Impacts on Different Livelihood Resources
l. Impacts of Climate Change on Gender and Marginalized Group
Figure 28: Climate Change Impacts on Different wards based on Ethnicity
Climate change impacts all social and ethnic groups though the intensity might differ. To assess the
vulnerability of different ethnicity to climate induced hazards, impacts of 7 different climate induced
hazards on human resources, land, forest and biodiversity, water resources and infrastructures and
its consequences on children, youth adult, elderly people, female, male, poor, differently able and
marginalised community were considered. Seven different climate induced hazards include; landslide,
drought, invasive species, fire, disease and insects, hailstone and wind storm.
0.00
0.50
1.00
1.50
2.00
2.50
3.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Natural Resources Economic Sources
Social Physical Sources
Human Resources
2.352.20
2.55
1.841.97
1.26
1.97
1.59
2.25 2.28
1.84
2.31 2.33 2.342.12
1.98
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Climate Change Impacts on Gender and Marginalized Groups
33
Analyzing all these factors, ward 3 is highly vulnerable with score of 2.55 and followed by ward 1 with
2.35 respectively. It might be because of the different adaptation practices carried out by them to
reduce the impacts of climate change on different ethnicity and category. Another factor might just
be that those least vulnerable wards might have a less vulnerable group in comparison to the wards
which are highly vulnerable to climate-induced hazards in terms of different ethnicity and category.
Figure 29: Climate Change Impacts on different Categories
Comparing the vulnerabilities of different categories, differently able, elderly and women are found
to be more vulnerable with average scores of 2.78, 2.74 and 2.48 respectively. Off the 16 wards of the
municipality, 12 wards claimed landslide as the major risk followed by drought and flood as 10 wards
claimed such risks. This chart only shows the hazards having average score equals or greater than 2.
Drought, torrential downpour, pests/insects and landslide, flood and landslide are some of the major
hazards directly or indirectly associated with climate change in Birendranagar. In the graph wards
scoring more than 2 vulnerability score are only presented. Out of 16 wards of the municipality, 14
wards claimed that drought is very pertinent and a major hazard these days. Likewise 13 wards
claimed pests/insects and torrential downpour, 12 wards claimed drought and 8 wards claimed
landslide as other hazards which makes their municipality highly vulnerable as shown in the graph
below.
1.78 1.78 1.83
2.742.48
1.70 1.741.87
1.74
2.78
1.701.87 1.83
1.95 1.91
Vulnerability Score of CCI on different Categories
34
Figure 30: Public Perception about Major Threats to Communities
m. Adaptive Capacity
Adaptation has emerged as an important area of research and assessment among climate change
scientists. Most scholarly work has identified resource constraints as being the most significant
determinants of adaptation. The different wards have different aspects of adaptive capacity and
different approaches to resist the climatic hazards in land, water resources, agriculture, forest
ecosystem, livelihoods. Major Practices which are common in different wards are summarized below.
✓ Use of Pesticides which is not sustainable in long run
✓ Purchasing water from tanker, protection and awareness on natural spring protection
✓ Fire Line preparation to control forest fire
✓ Management of forest resources by community
✓ Green house farming, used of improved seeds, improved shed management for cattle, road
upgrading etc are being done from community level which are very successful in practice
✓ Youths and clubs are involved in awareness campaigns
✓ Drip irrigation, use of bio fertilizers as food preservatives, rain water harvesting, alternative
cropping and cross cropping practices are some notable examples to be considered
✓ Gabion wire and bio engineering in soil stabilization and waste water collection from taps for
irrigating backyard farming, bamboo plantation in river banks for flood control
The wards do not have any alternative adaptation practices and though they have, they are not
sustainable and most of them are not working. Such as removing the invasive species and insects by
manual collection, purchasing water through tanker for irrigation and using generator pumps,
temporary dam construction in river banks, and use of chemical fertilizers are only useful in immediate
effects.
The economic status of the families at the local level can be improved with opportunities for
community people through Women Empowerment Centers (WEC). WEC could be a regular income
generating source for many of the women in the locality itself. Financially strong communities will be
8
1214
1113 13
24
Wards with Average Vulnerability Score equals or >2
35
more robust and will be able to develop adaptation measures in their own context. The other
communities can also replicate the concept in new communities. The experiences from one WEC can
fit into some other communities empowering the whole ward to develop eco-entrepreneurship. The
WEC will be designed to practice climate adaptive, eco-friendly, low carbon products through market
based approach. The capacity of women engaged in such activities will be developed and they can
motivate, influence and encourage other vulnerable communities to follow the footsteps.
n. Vulnerability
Different wards are differently vulnerable with respect to different indicators defined. The VA
revealed several threats and challenges the communities are exposed along with the local level
remedial actions to cope with the climate induced disasters. The adaptive capacity of all the wards
are considered 1.25 (low adaptive capacity) based on the documented adoption practices which are
not significant, non-scientific and non sustainable to meet the needs and the intensity of the impacts
and the exposure they are having. This indicates a clear need to enhance the adaptive capacity to
desired levels.
Also the Exposure they are being facing to the climate change impacts is significantly high in some
seasons and less significant in some seasons. It applies the same in terms of major crops and cropping
pattern. There have been changes in rainfall pattern which has shortened by almost 2 months. The
number of hot summer days has increased by more than 3 months. Though the monsoon has
shortened by 2 months, the annual rainfall is almost identical which implies the rainfall is being more
intense with high chances of flooding and landslide exerting extra threats to livelihood. But some of
the parameters show identical pattern. So, the overall exposure of the wards has been considered at
around 1.75.
o. Flood risk
A modelling approach was applied to analyse the flood risk related to extreme rainfall events for the
rivers and streams in Birendranagar municipality. The approach integrated a Digital Elevation Model,
high-resolution satellite imagery, topographic map data and field measurements on river width and
depth. As part of this analysis, the surface run-off for a heavy rainfall event was modelled.
Furthermore, the depths and cross-section areas of the existing stream channels were compared to
the required channel measures that would be necessary to accommodate all the run-off water from
such a storm event. The modelling results have shown that the river channels are in many places too
small to accommodate the run-off of an extreme rainfall event. Some results are presented in the
figures below. A separate technical report is available that describes the input data, modelling method
and all results in detail.
36
Figure 31. Mean run-off caused by a daily rainfall of 423 mm (reference case: 15.08.2014). For better visualization, the continuous values of the dataset were classified into 9 run-off classes.
37
Figure 32. Locations of field measurement plots and results of hydrological modelling. The labels indicate the Plot ID. Large red circles indicate locations where the measured mean depth of the channel is significantly smaller than the required (modelled) mean depth, for a reference storm event of 423mm rainfall per day, assuming a constant daily flow rate.
p. Adaptation Planning
This will be prepared based on the VRA findings upon the approval and acceptance of this report.
This will be the outcome of next Milestone Reporting.
38
Chapter 5
Conclusion and Recommendations
Climate change impacts everyone but the intensity of the impacts varies significantly among places,
persons, ethnicity, caste, groups, social strata, resources and economic status. The current pace of
urbanization is quickly outstripping government’s capacity to manage urban growth and is taking
place with little coordinated land use or spatial planning. As climate change impacts increase,
vulnerability continues to grow and the burden of poverty falls disproportionately high to some
sectors of society with deeply entrenched inequalities. This results in a proportion of extreme poor
people being more vulnerable to disasters, climate change, and economic shocks.
Different wards have different level of exposure to risks and vulnerability. Climate extreme events
such as drought, landslide, flood, and pests and insects has been threatening livelihoods of people
and especially marginalized communities. Differently able people, women, and elderly people are
more vulnerable to the impacts of climate change. Women face difficulty in collecting and harvesting
the day to day livelihood resources with the burden of added responsibility caused by the
outmigration of the men. Women are left with more family responsibilities as they have unequal
access over the resource use whereby in rural areas, women are responsible for collecting firewood
and fetching water. The drying up of springs, low resource availability has gendered implications as
well.
The indicators defined and assessed in the study shows little variations in overall vulnerability Index.
Several indicators were assessed based on vulnerability, sensitivity, exposure, hazards and adaptive
capacity. Impacts of climate change are not uniformly distributed; it even varies within a short
geographical location. So, specific attention should be given to every minute detail in accessing the
vulnerability indices. Drought and flood (intense rainfall) are prominent climate hazards that have let
several acres of land converts into natural deserts and uncultivated land every year. Due to drought,
productivity is in decline. Livelihood resources like natural, social and economic and human resources
have been impacted by climate change. Climate induced disaster has impacted almost every resources
in all the wards based on the findings.
39
Based on the overall study on adaptive capacity, resource availability and management, technology
and economy, the adaptive capacity of all the wards are considered 2.25 (moderate adaptive
capacity). This can be justified based on the documented adaptation practices, capacity need
assessment, VRA and site specific adaptation approaches, most of which are not significant in long
term but are practicable. Shifting of the cropping pattern, cross cultivation, use of improved seeds,
tunnel farming, rain water harvesting are some common adaptation measures being employed. This
indicates a clear need for uplifting the adaptive capacity to desire levels as these are not applicable in
larger scale. There are regional level offices, and almost every community is connected with network
and mass media which could be a source of information. Regional level radio station, national daily
newspaper, regional hospital, road access to almost every wards, availability of open spaces in city
core areas makes Birendranagar a bit more resilience.
Also the exposure they are being facing to the climate change impacts is significantly high in some
seasons and less significant in some seasons. It applies the same in terms of major crops and cropping
pattern. There have been changes in rainfall pattern which has shortened by almost 2 months. The
number of hot summer days has increased by more than 3 months. Though the monsoon has
shortened by 2 months, the annual rainfall is almost identical which implies the rainfall is being more
intense with high chances of flooding and landslide exerting extra threats to livelihood. But some of
the parameters show identical pattern. So, the overall exposure of the wards has been considered at
around 1.50.
Figure 33: Vulnerability Index of Wards
From the graph, we can say that the vulnerability index of different all the wards of Birendranagar
municipality is less than 2. The overall score of the municipality is 1.2 which means the municipality is
moderately vulnerable to the impacts on climate change. Ward 12 is found to be the most vulnerable
among the 16 wards with Vulnerability Index of 1.42 followed by ward 15 (1.39) and ward 14 and 16
(1.38 each). Though ward 11 comprises the highest fraction of highly vulnerable HH with 21.68%, the
overall vulnerability index is found to be 0.97. The basis for vulnerability ranking is based as follows;
Score 0-1 (low or no vulnerable), score 1-2 (moderately vulnerable), score 2-3 (highly vulnerable) and
score 3-4 (very highly vulnerable).
1.31
1.14
1.34
0.97
1.14
0.79
1.091.21 1.16
1.35
0.97
1.42
1.22
1.38 1.39 1.38
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Vulnerability Index
40
The GIS modelling results have shown that the river channels are in many places too small to
accommodate the run-off of an extreme rainfall event. The results indicate where stream channels
could be widened or deepened in order to prevent harmful floods in the city. At locations where the
modelled (required) channel depth is significantly larger than the actual channel depth, flooding is
expected for strong rainfall events. For these locations it is worth considering the construction or
improvement of dikes along the river banks, plantation of trees or artificial enlargement of the river
bed. The existing channels should be cleaned, well maintained and possibly further excavated to be
able to accommodate all the water flow.
Recommendations
Some of the general recommendations based on the study are listed below.
✓ We highly recommend the municipality to prepare and adopt climate adaptive urban planning
in the days to come
✓ Site specific and ward specific adaptation plans should be prepared and formulated to reduce
the risk of climate change impacts
✓ Provision of Disaster Risk Reduction units should be allocated in every wards equipped with
sufficient materials
✓ The embankments should be properly designed to withstand the highest discharge recorded
✓ Awareness should be raised on climate change impacts and adaptations and should
encourage local residents to practice and promote climate adaptive and environment friendly
business
✓ Flood control measures are recommended where stream channels seem too narrow
✓ Direct flood control measures e.g. dykes along the river banks, plantations, artificial
enlargement of the river bed is recommended for the immediate measures to control flooding
✓ Indirect flood control includes e.g. increasing the green areas inside and around the city, stop
logging of forests in the adjoining mountains is recommended in the long run.
✓ It is recommended to have dense vegetation, which can slow down the water in case of a
flood event, along the rivers on top of the banks
References Vulnerability and Risk Assessment (VRA) Framework and Indicators for National Adaptation Plan
(NAP) Formulation Process in Nepal; Government of Nepal, Ministry of Population and Environment,
May, 2017
Climate Change Local Adaptation Plan of Action; Devghat VDC, Tanahu, Nepal, 2015
General Introduction to National Adaptation Plan Formulation Process in Nepal; Government of
Nepal, Ministry of Population and Environment, 2017
Synthesis of Stocktaking Report for National Adaptation Plan (NAP) Formulation Process in Nepal; GoN, 2017 Nepal Gazette, 2017, GoN
Annex
41
