Sri Lanka

 

Sri Lanka’s economy is highly reliant on climate-sensitive sectors such as agricultural, forestry and energy production. Some adaptation measures have already been adopted in these sectors to promote better environmental management. Programmes have been established for the agricultural sector to manage soil erosion, support better water management and encourage the diversification of agricultural production. In the energy sector policies have been developed to support increased energy efficiency and to reduce associated environmental pollution. In Sri Lanka’s First National Communication of 27 October 2000, it is noted that to effectively respond to anticipated climatic changes the existing adaptation measures need to be extended and action needs to be taken in other areas.

Sri Lanka is a tropical island which lies between 6o and 10o N latitude and between 80o and 82o E longitude. It covers an area of about 65,610 square kilometres and has a maximum width of about 240 km and a maximum length of the island of about 435 km. Sri Lanka has a vast coastal plain with a mountainous area in the southern and central regions. The coastal regions are most vulnerable to climate change and a significant proportion of the population reside in these maritime provinces. The climate in Sri Lanka supports forest growth and virtually the entire land area was once covered with forests. Deforestation has made soils less productive and affected the natural water supply. The majority of water resources in Sri Lanka are generated by the hills in the central region which intercept the moisture-laden monsoonal winds from the south-west and north-east. This creates a unique rainfall pattern and the surface water is transferred by 103 distinct natural river basins that cover 90% of the island. Despite this seemingly favourable position many areas experience droughts that last several months. The available surface water is primarily used for agriculture and hydro-electricity generation. _

Sources: Initial National Communication for Sri Lanka under the United Nations Framework Convention on Climate Change, 27 October 2000.

 

Related Content

Project progress report, November 2017 'Strengthening the Resilience of Smallholder Farmers in the Dry Zone to Climate Variability and Extreme Events' in Sri Lanka'

Project progress report, November 24 2017, on Output 1: Upgrading village irrigation systems and promoting climate resilient farming practices in three river basins of the Dry Zone ('Strengthening the Resilience of Smallholder Farmers in the Dry Zone to Climate Variability and Extreme Events' in Sri Lanka)

Project progress report, November 2017 'Strengthening the Resilience of Smallholder Farmers in the Dry Zone to Climate Variability and Extreme Events' in Sri Lanka'

Strengthening the Resilience of Smallholder Farmers in the Dry Zone to Climate Variability and Extreme Events - Project Factsheet

Factsheet for the GCF-funded project in Sri Lanka, 'Strengthening the Resilience of Smallholder Farmers in the Dry Zone to Climate Variability and Extreme Events'. 2017.

Funding Proposal - GCF Sri Lanka

Green Climate Fund (GCF) Funding Proposal, published 8 June 2017, Sri Lanka ('Strengthening the resilience of smallholder farmers in the Dry Zone to climate variability and extreme events through an integrated approach to water management')

 

Datasets on Climate Change Adaptation

In an effort to connect stakeholders with new data on climate change adaptation actions in Africa and Asia, UNDP is partnering with various sectors of academia, civil society and the private sector to share and analyze datasets gathered through UNDP-supported initiatives across the globe. These datasets will be made available upon request, as a new sharing platform is being developed.

This new initiative is in its nascent stage. Working with academics from leading institutions such as Harvard and Yale, along with partner governments, civil society, think tanks and private-sector partners, UNDP is building a proof of concept and working model to share data and improve analysis.

The overall goal is simple: evidence-based decision-making has the potential to significantly improve the impact of global investments in climate actions. To learn more about the data available and the coalition that is currently forming, please sign up below.

About the data available

Current datasets are available from Africa and Asia. These datasets were collected through UNDP-supported initiatives on the Economics of Climate Change Adaptation in Asia (ECCA) and Climate Information and Early Warning Systems Projects in Africa.

Household surveys were conducted in various countries and will be made available for download and analysis. Future datasets will also be shared with this coalition.

Data Collection and Sampling Methods: 

ECCA Asia

The questionnaire was first translated into the local language and tested twice with local farmers. The data were collected in 2014 by a national team with 300 household surveys. Datasets are available from Bangladesh, Indonesia, Sri Lanka, Thailand and Viet Nam. Information collected in the questionnaire included the following:

  1. Past experience on climate change, communications and adaptation response. Interviewees were asked about their perception about climate change and current sources of weather information.
  2. Detailed farming area information. The survey collected information on farm planting area, fallow land area, and the division of the plots by crops and other livelihood by the household.
  3. Household information. Detailed information on household members, gender and basic infrastructure availability. Data were also collected on the primary and secondary occupation of the head of the households.
  4. Data required to calculate the farmer’s net revenue based on ongoing agriculture practices (crop and livestock). Data were collected on labour available to the household, type of crops grown including by growing season, prices as well as input costs including cost and quantity of fertilizer, irrigation, and machinery. Similar information was collected for livestock farmers.
  5. Global Positioning System (GPS) locations. Location is important when analysing climate impacts so information on the latitude and longitude of farms was collected.
  6. Information on extension services. Detailed information was provided by private extension groups, non-governmental organizations (NGOs), central government agencies, cooperatives and local government to be able to elicit potential policy tools available to support adaptation.

 

Climate Information and Early Warnings Africa

In Africa datasets on climate information and early warnings were gathered from 2000 household surveys. The data were collected between 2015 and 2016 by a national team. Datasets are currently being cleaned, and will be available from Burkina Faso, Liberia, São Tomé and Príncipe, Sierra Leone, Tanzania, Uganda and Zambia.  

The questionnaire was divided into 4 main parts:

  1. Hazard identification by community and household. This section provided information on the different hazards prioritized by communities. This will feed into the EWS system to help target/provide information that will be useful for project delivery.
  2. Past experience on EWS, climate change, communications and responses. This section gathered data that that can be used to evaluate the current EWS system in the countries.
  3. Household information. This section provides detailed information on the kind of household and gender roles and basic infrastructure availability
  4. Information to estimate outcomes of interest – components of farmer (crop and livestock) and fishers revenue, cost and profit: depending on the kind of agent. This section provides data on labor available to the household, type of crops grown if a farmer, the growing season to differentiate different crops and value of EWS information, fertilizer use to estimate costs and inputs, irrigation use and cost, machinery, and similar information for livestock farmers.
  5. GPS locations for geo-spatial information and analysis. Spatial variation is a valuable instrument to help with identification of control and treated groups.

 

Request access to datasets and join the coalition

 

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Datasets: 
ECCA Bangladesh
A total of 360 farm households were interviewed for this study drawn from 7 provinces. Of the sampled households, 87% practised irrigated agriculture while 13% relied on non-irrigated (rainfed) agriculture. Interviewed farmers on average own 7.10 acres of land in total, with those practicing rainfed farming owning larger parcels (average 8.99 acres) relative to those practicing irrigated farming (average 6.81 acres).
ECCA Indonesia
The data collection was conducted in Brantas River Basin in East Java district as agriculture center in Indonesia, particularly in villages in Batu City (> 100 m above sea level) and Mojokerto District (< 45 m above sea level). In each location, 100 farm households were interviewed based on purposive sampling by using size of farmland as selection criteria. The households in the survey reported having about 27 years of farming experience ranging from 1 to 70 years. The average household size is 4, ranging from 1 to 13. The heads of household have an average of 9 years of education with access to electricity by almost all the households. In terms of access to information and telecommunication technology, the majority (68%) of the respondents have a telephone, although only 32% have a computer and 20% have access to the Internet.
ECCA Sri Lanka
Three hundred and twenty-one households were interviewed spanning the agro-ecological zones of the country. About 40% of the sample is from the Central Province of the country while the rest are distributed across the other provinces including the North west and Uva provinces that are about 14% of the sample. The majority of the households in the survey reported having about 20 years of farming experience, with a minimum of four years and a maximum of 60 years. On average, each household consisted of five people (minimum four, max 16) with 10 years of education. The majority (88 percent) of the respondents owned a telephone, while 33 percent had a computer, 18 percent of which had access to the Internet.
ECCA Thailand
A total of 395 farm households were interviewed, drawn from 18 provinces. Of the sampled households, 58% practised irrigated agriculture while 42% relied on non-irrigated (rainfed) agriculture. Interviewed farmers on average own 15.18 acres of land in total, with those practicing irrigated farming owning larger parcels (average 18.89 acres) relative to those practicing rainfed farming (average 10.26 acres).
ECCA Viet Nam
Survey locations were selected to cover each of the ago-ecological zones present across Viet Nam in the context of agriculture production. In each location, the Viet Nam country team surveyed 18 households, with a total of 342 surveyed households. Out of the 342 surveyed households, the team obtained 323 usable questionnaires, of which 306 cover households with cultivation activities. The households in the survey have about 27 years of farming experience ranging from one year to 60 years. The average household size is 4, ranging from 1 to 13. The heads of household have an average of 7.5 years of education with access to electricity by almost all the households. In terms of access to information and telecommunication technology, the majority (96 per cent) of the respondents have a telephone, although only 20 per cent have a computer and 15 per cent have access to the Internet. On average, the respondents owned 7.4 acres of land (2.96 ha) with the majority of planted crops in two seasons, while a few planted all the three seasons. The average annual planted area across the three seasons is 5.5 acres (Figure 11), with 2 acres left fallow, on average. A third of the farmers have less than 2 acres of planted area, while nearly 15 per cent of farmers planted more than 10 acres.
Burkina Faso CI/EWS
Coming soon.
Country: 
Bangladesh
Indonesia
Sri Lanka
Thailand
Theme: 
Agriculture/Food Security
Tools: 
Title: 
Economics of Adaptation Toolkit
Title: 
Survey Questionnaire
Description: 
Countries Conducting Survey: Bangladesh, Cambodia, Indonesia, Mongolia, Nepal, Sri Lanka, Thailand and Vietnam.

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