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India Agrometeorological Advisory Service (AAS) Case Study

INDEPENDENT STUDY OF THE AAS PROGRAM FROM A FARMER PERSPECTIVE:

ASSESSING VIEWS FROM THE FRONTLINE

FINAL REPORT

October 15, 2012

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Cover Photo:

Report By: Kalpana Venkatasubramanian, Arame Tall, James Hansen, Pramod K. Aggarwal, Matthias Pfeffer, Vivienne Dersin.

Cite as:

© CCAFS 2012

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Table of Contents

I. INTRODUCTION: CCAFS’ INDEPENDENT EVALUATION OF THE AAS PROGRAM IN INDIA ................ 4

II. BACKGROUND………………………………………………………………………………………………….5

III. ASSESSMENT METHODS………………………………………………………………..……………….12

IV. FINDINGS……………………………………………………………………………….……..……………….16 4.1. ANDHRA PRADESH………………………………………………………………….………16 4.2. HIMACHAL PRADESH.……………………………………………………………………. 24 4.3. PUNJAB.……………………………………………………………………………………….. 33 4.4. WEST BENGAL…..………………………………………………………………………….. 41 4.5. TAMIL NADU.……………………………………………………………………………….. 49 4.6. GUJARAT.…………………………………………………………………………………….. 57

V. DISCUSSION………………………………………………………………………….……..……………….63

VI. SUMMARY OF LESSONS LEARNT………………………………………………………………….75

VII. CONCLUSIONS & POLICY RECOMMENDATIONS…………………………………………..84

VIII. ANNEXES………………………………………………………………………………………….90 8.1. METHODS PRIMER

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I. INTRODUCTION: CCAFS’ INDEPENDENT EVALUATION OF THE AAS PROGRAM IN INDIA

Managing the risk associated with climate variability is integral to any comprehensive strategy for adapting agriculture and food systems to a changing climate. Although farming communities throughout the world have survived by mastering the ability to adapt to widely varying weather and climatic conditions, increasingly erratic climate variability and the rapid pace of other drivers of change are overwhelming indigenous knowledge and traditional coping practices. Effective climate information and advisory services offer great potential to inform farmer decision-‐making in the face of increasing uncertainty, improve management of climate-‐related agricultural risk, and help farmers adapt to change.

CCAFS Theme 2 seeks to enable promising innovations for managing climate-‐related agricultural risk at local and regional levels, addressing existing gaps and supporting improvements in climate-‐related information products and services that enable a range of agricultural risk management interventions. Within this Theme, one of the three objectives is to support risk management through enhanced climate information and services.

Several challenges however confront efforts to use climate-‐related information to improve the lives of smallholder farmers, including:

• Credibility: providing timely access to accurate climate information and services for remote rural communities with marginal infrastructure.

• Salience: tailoring content, scale, format and lead-‐time to farm decision-‐making. • Legitimacy: giving farmers an effective voice in the design and delivery of climate services. • Equity: ensuring that women, poor and socially marginalized groups are served.

Several initiatives in sub-‐Saharan Africa and South Asia have used innovative approaches to overcome these challenges. A few national agrometeorlogical advisory services reach a significant proportion of their farming populations on a sustained basis with information and guidance. One of the oldest and longest standing of these national initiatives is the agrometeorological advisory services in India (which recently announced plans to scale up to 10 million farmers in 2012).

CCAFS partnering with IMD and ICRISAT decided to conduct an in-‐depth study of the agrometeorlogical advisory services in India (which recently announced plans to scale up to 10 million farmers in 2012), with a focus on capturing what is happening at the village level and how it is impacting the rural communities.

The overall objective of India’s Agro-‐Advisory Service (AAS) case study assessment was to provide evidence of use and benefit at the village level; and insights about factors that have contributed to their uptake, impact and sustainability. Although India’s national initiative still features difficulties grappling with the complexities of communicating and applying seasonal forecast information, it demonstrates good practice and provides valuable insights. The time is

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right to learn from and build on examples of good practice in farmer-‐focused climate information and advisory services.

Several recent developments made this assessment timely, hand in hand with the increase in global attention received by Climate services:

• At the World Climate Conference-‐III (WMO, Geneva, September 2009), delegates of 155 nations endorsed a Global Framework for Climate Services (GFCS) “to strengthen the production, availability, delivery and application of science-‐based climate prediction and services.” The GFCS implementation plan targets gaps in climate services in support of four key climate-‐sensitive sectors, including agriculture, in vulnerable developing countries.

• The CSP, launched at the International Conference on Climate Services (New York, October 2011), is a global network of climate service providers, users, funders and researchers. It aims to advance climate services worldwide by fostering collaboration, capturing and sharing knowledge; and filling gaps in knowledge and evidence.

• Improving climate-‐related information products and services for agriculture and food security is part of the agenda of the CGIAR research program on Climate Change, Agriculture and Food Securing (CCAFS), under its Theme, “Adaptation through Managing Climate Risk.” The program is connecting the considerable research capacity of the CGIAR with new climate science and climate service partners, including the CSP.

• India’s AAS has recently received a lot of publicity for reaching 3 million farmers via mobile phone, and for the recently-‐announced plan to scale up to 10 million farmers in 2012.

• An international South-‐south learning workshop on “Scaling Up climate services for farmers in Africa and South Asia” planned for December 10-‐12 in Dakar, Senegal, to share elements of good practice between Africa and South Asia. The objectives of this meeting are synthesize aspects of good practice that can guide investment in climate/weather services for farmers elsewhere in Africa, S. Asia; Strengthen evidence and transferrable lessons, by capturing the perspectives of farmers in select locations; and Showcase as a case study of good practice at the planned S-‐S workshop.

The expected outputs from this joint CCAFS-‐partners assessment were an independent report to be shared ahead of the Dakar South – South workshop, as well as a number of academic journal publications in collaboration with colleagues in India from all participating institutions of this study.

II. Background

The Integrated Agrometeorology Advisory Services (AAS) is a project of the India Meteorological Department that aims to provide a variety of services to farmers including meteorological (weather observation and forecasting), agricultural advisories (identifying weather related stresses and providing advisories based on weather forecasts), extension services (two way communication with users), and information dissemination (through media and other local agencies). The project, which was integrated under the IMD in 2007, is being implemented through a five-‐tier structure that form different components in the service spectrum. Agro-‐met

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Advisory Bulletins are issued at the out to the state and district levels to cater to the needs from national to local scales.

To facilitate the design and implementation of similar programs in other countries, mostly in Africa, requires detailed information about the institutional context in which the project was set up and run, the scientific information used to inform the forecasts and other information conveyed to participant farmers, the ways in which this project has impacted farming practices related to local livelihoods, and how those impacts on farming practice came to pass. The proposed assessment addresses each of these needs independently. Data from the scientific and field assessments will be combined to determine the quality and utility of the information from the perspective of local-‐level farmer project participants, and the perception of impacts and changes in farmer behavior following utilization. The institutional assessment will be used to contextualize the products of the scientific/field assessment analysis for use by interested meteorological services across Africa.

2.1 AAS Program in India

Agriculture being the mainstay of a majority of people in India and an important contributor to economic growth, advances in agrometeorological expertise and its application in agricultural planning and production has been a significant agenda of the Indian Government as early as the 1930s when the division of agrometeorology was started. Since then, a number of initiatives have been undertaken to improve and expand on agrometeorological faculties and facilities across the country. Agrometeorological advisories were first initiated in 1976 to provide state level forecast-‐based advisories to farmers based on short-‐range weather forecasts issued by the Indian Meteorological Department (IMD). Made available to farmers one day in advance, these advisories were inadequate for planning weather based agricultural practices and/or undertake precautionary measures, which required a much longer lead-‐time.

In agriculture, location-‐specific weather forecasts in the medium range held greater salience. In addition, forecast issued had to be fine-‐tuned to the specific requirements of farmers, particularly in recommending activities and modifications to specific agricultural practices. Keeping these in mind, the National Center for Medium Range Weather Forecasting (NCMRWF) was established in 1988 by the Government of India as a scientific mission to develop operational Numerical Weather Prediction (NWP) models for forecasting weather in the medium range (3-‐10 days in advance) scale. For disseminating these forecasts and for building forecast based agricultural advisories, Agro Advisory Service Units (AASUs) were envisioned across the country in all delineated 127 agroclimatic zones. The mammoth task received infrastructural and technical support jointly from the Department of Science and Technology (DST), Indian Meteorological Department (IMD), Indian Council of Agricultural Research (ICAR) and State Agricultural Universities around the country.

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By 2006, 86 fully functioning Agro Advisory Field Units (AAUs) located in State Agricultural Universities and representing a range of agroclimatic zones were receiving medium range weather forecasts twice a week valid for a four-‐five day period from the NCMRWF. Based on these forecasts, the AAUs prepared weather-‐based agro advisory bulletins in consultation with a team of agricultural scientists. The advisory, prepared in both English and a local language was then disseminated to farmers through a variety of communication channels including radio, television, newspapers and telephones. Due to the expansive nature of its production and dissemination the AAS was soon held as an example of a successful multi-‐institutional and multi-‐disciplinary operation to render an invaluable service to the farming community in India. In 2007, the AAS was integrated with the Indian Meteorological Dept (IMD) under the Ministry of Earth Sciences and District-‐level Agrometeorological Advisory Service (DAAS) was launched in June 2008. DAAS aims to generate district level agrometeorological advisories based on weather forecasts and improve dissemination of the same to farmers to help with decision making in crop and livestock management. DAAS continues to be a multi-‐institutional project involving a variety of stakeholders including the Indian Council for Agricultural Research (ICAR), State Agricultural Universities (SAUs), Krishi Vigyan Kendras (KVKs), Department of Agriculture & Cooperation, State Departments of Agriculture/Horticulture/Animal Husbandry/Forestry, NGOs and Media agencies (Fig 1). The entire project runs through a series of services across a five-‐tier structure which includes meteorological (weather observation and forecasting), agricultural (identification of weather-‐sensitive stress and preparing suitable advisory using weather forecast), extension (two-‐way communication with user) and information dissemination (Media, IT and others). In 2011, experimental block level forecasts for a few states was initiated and is currently in the process of expansion.

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Fig 1. Collaborating organizations and their linkages under Integrated Agromet Advisory Services Source: IMD, New Delhi

District Level Agriculture Extension set up (612)

DAO/KVK

ATMA

NCMRWF –Location Specific Weather Forecast development

Dept. of Agriculture & Coop. NCFC/ATMA/CWWG

ICAR- R & D Inputs

Dept. of Space- Crop information

Prasar Bharti

Dept. of Info. Technology

IMD

Agro-Met Services

State Meteorological Centre (23)

IMD

State Crop Weather Watch Group (CWWG)

1. Drought Monitoring Center

2. State RS application centres

3. DAO/KVK/NGOs

AMFU (128 Agro Climatic Zones)- SAUs/ ICAR

Institutions/ IITs

State Department of

Agriculture

Extension Directorate of University

Local Media (AIR/TV/Print)

NGOs

Block Level (B.D.O)

(Farm Input Management)

NGOs

MSSRF

Ministry of Earth Sciences

Government of India

(AAS steering committee)

Village Level

(CSC, DIT)

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2.2 Current Institutional Mechanism and Infrastructure

Today, IMD issues quantitative district level weather forecasts up to 5 days twice a week based on a Multi Model Ensemble (MME) technique. Weather forecasts for seven parameters, namely, rainfall, maximum and minimum temperatures, wind speed and direction, relative humidity and cloudiness as well as weekly cumulative rainfall forecasts are generated. These products are disseminated to Regional Meteorological Centres and Meteorological Centres of IMD located in different states. Experts in these centres value-‐add to IMD forecast products which are then communicated to 130 AgroMet Field Units (AMFUs) located within State Agricultural Universities, Indian Council of Agricultural Research Institutes (ICAR), and Indian Institute of Technology (IITs).

The AMFUs, established by the Ministry of Earth Sciences, represent each of the 130 agro-‐climatic zones in the country, each covering 4-‐6 districts. Apart from recording agrometeorological observations for their zone through manual and automatic weather stations in their zone, these units are assisted by an advisory board consisting of agricultural scientists representing a wide spectrum of agricultural disciplines to prepare district-‐wise agro-‐advisories. These advisories contain location specific and crop specific farm level advisories as well as description of prevailing weather, soil & crop condition, and suggestions for taking appropriate measures to minimize the loss and also, optimize input in the form of irrigation, fertilizer or pesticides.

The AMFUs are also responsible of dissemination of advisory bulletins to farmers in their respective zone. This is done through several communication channels (Fig 2) such as mass media (newspapers, TV and radio) and through the involvement of district level agencies (District Agricultural Offices, Krishi Vigyan Kendras (KVKs), Kisan Call Centres, NGOs) to build on existing extension channels. More recently, cellular phones (voice mails (IVRS) and SMS) and internet are also becoming popular channels of dissemination. SMS service already reaches 2.5 million farmer users across 16 states while IVRS reaches 30000 farmers across 5 states in India. In addition to reaching famers to communication agroadvisory bulletins, a feedback mechanism has also been developed in order to receive inputs from farmers on quality of forecasts, relevance of advisory and effectiveness of dissemination channels. New initiatives are constantly underway to improve and expand dissemination to reach more farmers in a timely manner.

Web-‐based services have been greatly improved and expanded to provide agrometeorological information to users at all times through the Internet. Beginning with 25 centres across different agroclimatic zones in the country, AICRPAM (ICAR) has launched a website (Crop Weather Outlook) for easy and immediate access to agromet information and value added services provided by agricultural institutions. In several states, district-‐wise advisories issued bi-‐weekly are available online for immediate use by users. Linkages are

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also provided to other institutional web-‐links that can provide further information on agrometeorological operations to users.

Fig 2. AAS Institutional Mechanism to reach farmers Source: IMD, New Delhi

2.3 Progress and Assessment of AAS program

Progress and future plans

Several important investments have been made to expand the meteorological infrastructure to improve data collection. Automatic Weather Stations (AWS) are being installed in all AMFUs across the country. Currently more than 40 have been installed with AWS which relays weather data directly to the Earth Station at Pune for further processing.

IMD issues district-‐level forecasts for over 500 districts across India for preparation of district level agro-‐advisories to 130 AMFUs. AMFUs value-‐add to the weather forecasts and prepare agro-‐advisories. They are also engaged in collecting weather indicators through Manual Weather Stations (MWS) in their districts. In several cases, farmers have been trained to record weather data everyday and facilitate in their compilation. To improve dissemination of advisories and reach, linkages have been established with Krishi Vigyan Kendras (KVKs) in all districts who help organize vocational training programs for farmers to impart

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information on latest technologies. Further, links are also being made with the ATMA (Agricultural Technology Management Agency) program which has a well-‐defined structure at state, district and block level to help with dissemination of DAAS.

Going forward, block-‐level advisories based on medium range weather forecasts at the block level are being contemplated and already underway on an experimental basis in a few states since 2011. Elaborate plans are being drawn in identified areas to increase application of agrometeorological expertise and reduce farmer vulnerability including agri-‐insurance greater links with fisheries and livestock sectors. Use of remote sensing techniques as well as crop growth simulation models are further being considered to improve reliability and relevance of agro-‐advisories. Finally, plans to augment extension services to scale up services from 3 to 10 million farmers include establishment of AMFU at district level, linkages with Common Service Centers (CSCs) being set up by the Department of Information Technology, Government of India that provide a range of services to the farming community,

2003-‐2007 AAS evaluation (to be elaborated)

•National Centre for Agriculture Economics and Policy Research, commissioned by NCMRWF

•15 of the 127 AAUs

•6 seasons during 2003–2007

•80 farmers: 40 responding and 40 non-‐responding farmers

•10-‐15% increase in yield

•2-‐5% reduction in the cost of cultivation

2.4 Feedback from AAS stake holders and recommendations

Discussions with staff at IMD, Regional Met Offices, Agromet Field Units and other institutional representatives (NGOs, Krishi Vigyan Kendra’s) involved in the development of the forecast advisories and in its dissemination revealed important aspects of the functioning of the program. This section presents the overall feedback received from their offices for further improvement of the DAAS program.

• Several KVK officers contended that those farmers who received and had begun to use the advisories to inform their decision-‐making had begun to trust and value the information and benefit from them. However, they added that was still scope for integrating farmers perspectives and knowledge into the AAS process, which would greatly enhance reach and usability amongst the farming community.

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• Representatives from AMFUs and KVKs sought greater support for collaborating with and training of local bodies like village Panchayats, farmer clubs, women’s groups and local community organizations to use their existing links with farmers in dissemination of AAS.

• Greater infrastructural support, particularly enhancement of IT capacity at the district/village level was recommended to ensure speedy receipt of advisories through the internet and their timely dissemination in the village.

• Representatives from AMFUs opined that the uptake and response from use of AAS was very encouraging amongst ‘progressive farmers’. However, amongst small and marginal farmers, awareness was still low. More trainings were required to generate interest and motivate farmers to learn about the AAS and use it. Moreover, targeted trainings were necessary, to ensure that all marginal groups are comprehensively included. Sustained efforts were required to encourage use of AAS in decision making, enhance trust and aid effective use.

• In some states, AMFU and Regional Met Centre representatives indicated the need the strengthen capacities of KVKs and improve coordination between KVK and AMFUs. This was crucial to plug the current loopholes in dissemination.

• While ties with other departments were a part and parcel of the AAS process, representatives recommended more systematic ties and procedures with the Department of Agriculture, Horticulture, Soil Services and Animal Husbandry on the dissemination front to leverage the vast network and resources for reaching the end-‐users.

• Representatives in several AMFUs lamented the delay in receiving salaries and budgeted resources for AAS which hampered activities and reduced quality of operations considerably.

III. ASSESSMENT METHODS

3.1. INTENT AND GOAL

In partnership with Indian Meteorological Department (IMD), State Agricultural Universities, ICRISAT the CCAFS Case Study on the AAS aims to synthesize aspects of good practices in climate services in India by capturing evidences of use of climate services at the village level and its impact on rural communities. It envisages strengthening of evidence and offering transferrable lessons that can guide investment in climate/weather services elsewhere in the world. The goal is to showcase best practice in India in climate services by focusing on farmer perceptions without trying to quantify economic benefit. The documentation of best practices and challenges in the provision and use of agroadvisories is expected to guide further investment and targeted efforts in climate/weather services in India, rest of S Asia and Africa.

3.2. Methods

A comprehensive understanding of the pathways through which this project has come to impact the lives of participants was beyond the scope and added value of this evaluation. Such an

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effort would require village-‐level studies of individual farmer behavior and social networks, as well as a comprehensive effort to gauge both current agricultural production and measure it against some form of reconstructed production baseline. Besides, an assessment on the AAS program has already been conducted in 2008 by the National Center for Short Range Weather Forecasts (NCSRWF), with probing results on the economic added value of farmer-‐focused agro-‐meteorological advisories in India (c.f NCSRWF assessment report, 2008).

What we aimed for instead was an independent study of IMD’s AAS program from a farmer perspective, collecting farmers’ perspectives on the products provided by the program (in terms of their legitimacy, credibility, salience and equity) and impacts on farming practices and livelihoods. Insights from this study will hopefully inform future AAS plans, and be shared at a South – South workshop on farmer-‐focused climate services, due to be held in Senegal in early December, 2012.

3.3. FIELD SITE SELECTION

In consultation with the IMD, 6 states across the length and breadth of India were chosen for the study. These were Punjab in the northwest, Himachal Pradesh in the north, West Bengal in the East, Andhra Pradesh in the southeast, Tamil Nadu in the south and Gujarat in the west. In each state, 3 villages from 3 different agroclimatic zones1 were selected. To ensure good representation and also to identify and emphasize variability in forecasts based advisories and their applicability and use, we selected our villages from three different agroclimatic zones in each state.

1 Across India, a total of 130 agroclimatic zones have been identified under the National Agricultural Research Project (NARP) in order to better plan agricultural activities in each region. These zones are characterized by homogenous soil, climate (temperature), rainfall and other agrometeorological characteristics, as well as other indicators, such as availability of water for irrigation, existing crops and cropping patterns and such. Each state in India thus can get divided into anywhere from 2 to 9 agroclimatic zones.

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Map 1 : CCAFS Study Site Selection. 6 states were selected across India. In each state, 3 villages from three different agroclimatic zones were randomly selected.

3.4. Methodology (refer to annex 1: Methods Primer)

The study relies on a mix of quantitative and qualitative data to offer a narrative that helps strengthen evidence and offer transferable lessons in climate/weather services for farmers.

The methodology includes a combination of the following:

• Brief review of program documents (Source: IMD, Regional Meteorological Offices, Agromet Field Units)

• Discussions with staff at IMD, Regional Met Offices, Agromet Field Units and other institutional representatives (NGOs, Krishi Vigyan Kendra’s) involved in the development of the forecast advisories and in its dissemination

• Focus Group Discussions with male and female farmer groups in chosen villages • Structured interviews with male and female farmers in selected villages

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FIELD METHODS

Fieldwork for the project was conducted over a period of approximately 2 months from 15th June to 15th August 2012.

Focus Group Discussions

In each village we began our field interactions by holding focus group discussions with separate male and female groups of farmers. In FGDs we followed a funnel approach, whereby, we began by asking farmers a number of questions related to their agricultural practices. These included questions about kinds of crops (livestock) grown (maintained), reasons, main activities in each crop (livestock), crop wise and activity wise constraints, overall constraints in agriculture (livestock), ways to deal with adversities and such. The main purpose was to involve farmers in discussions regarding challenges in agriculture and in their livelihoods and in doing so observe the extent to which weather/climate and associated variabilities played a significant role in influencing their activities, livelihoods and decision making.

If, and only if, farmers directly or indirectly eluded to weather/climate related factors as a significant influence and mentioned forecast based advisories as useful, were more direct questions about the relevance and usefulness of AAS brought up in the FGDs. FGDs with male and female farmers lasted approximately an hour and a half each.

FGDs with male and female farmers were followed with structured individual interviews with 3 to 4 farmers identified from each group. (Selection criteria for individual interviewees – cover a broad range of socio-‐economic classes wherever possible, variable knowledge of AAS, extent and use of AAS, extent of participation in the FGDs to ensure that those who did not speak much in FGD are selected for individual interactions etc.)

Individual interviews were specifically focused on gaining feedback on reliability, relevance and utility of AAS. The emphasis here was to seek farmers out on specific instances of use of AAS, the kinds of information used, channels through which advisories are received, perceived gaps in content or communication channels and suggestions.

Based on village level data for each state, best practices in AAS in India will be determined along with specific areas of future intervention for further improvement.

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IV. Findings: State-‐Wise Farmer Appraisals of the AAS Program

This chapter will present key findings from state-‐wise appraisals undertaken across India. In each state, 2 to 3 agroclimatic zones were chosen for the purposes of surveying farmers. These zones were chosen for their variability in geography, climate, agricultural landscape and crops farmed, thus enabling the examination of AAS across variable contexts.

While contextual variations abound within each state, here we present state-‐wise farmer appraisal of AAS according to the following four assessment criteria of:

• Credibility/Skill: providing access to accurate climate information and services for remote rural communities with marginal infrastructure.

• Salience: tailoring content, scale, format and lead-‐time to farm decision-‐making. • Legitimacy: giving farmers an effective voice in the design and delivery of climate services. • Equity: ensuring that women, poor and socially marginalized groups are served.

In each village, focus group discussions and interviews conducted with male and female members enabled us to glean answers on these four assessment criteria.

4.1 STATE 1: ANDHRA PRADESH (AP)

4.1.1 Agriculture in the State of Andhra Pradesh

India’s fourth largest state by area and fifth by population, Andhra Pradesh lies on the southeastern coast of India, bordered to the East by the Bay of Bengal and inland by the states of, from north to south, Orissa, Chhattisgarh, Maharashtra, Karnataka and Tamil Nadu. With rice as its main crop, AP has been historically known as the rice bowl of India.

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Andhra Pradesh is sub-‐divided into nine agroclimatic zones in all. Rainfall differences are stark across different zones, and crops diversified. Manifestations of climate change have become evident in recent years. Table xx details the specific agro-‐climatic features of each zone.

Fig. xx: Nine agroclimate zones in the State of Andhra Pradesh (Source: ANGRAU)

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Fig. xx: Rainfall variability and Change within one region of Andhra Pradesh state (Source: ANGRAU)

Out of the nine agro-‐climate zones of Andhra Pradesh, the CCAFS team selected 2 zones for its investigation: Central Telangana Zone (Warangal district) and Southern Telangana Zone (Nalgonda district and Mahbubnagar district). In each zone, one village was randomly chosen to conduct the survey, respectively Baironpalli, Nemani and Gorita.

Large distances and the short time available to the CCAFS evaluation team precluded outreach to farther areas in the state that may have not have been as well served and reached as the three areas selected for the survey. This bias ought to noted in the interpretation of the findings from AP.

Agro-‐climate zones Monsoonal Rainfall (mm)

Crops harvested

1. Krishna-‐Godavari 800-‐1100 paddy, groundnut, jowar, bajra, tobacco, cotton, chilies, sugar, hort crops

2. Southern Zone

700-‐1100 paddy, groundnut, cotton, sugar, millets, hort

3. Southern Telangana

700-‐900 paddy, sunflower, safflower, grapevine, sorghum, millets, pulses, orch

4. High Altitude and Tribal Areas

>1400 hort, millets, pulses, chilies, turmeric

5. North Coastal Zone 1000-‐1100 paddy, groundnut, jowar, bajra, mesta, jute, sunhemp, sesamum, blackgram, hort

6. North Telangana Zone

900-‐1500 paddy, sugar, castor, jowar, maize, sunflower, turmeric, pulses, chilies

7. Scarce Rainfall Zone 500-‐750 cotton, korra, sorghum, millets, groundnut, pulses, paddy

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In total, 114 farmers participated in the appraisal in the state of Andhra Pradesh, of which 44 female and 70 male, characterized as follows:

State of Andhra Pradesh – Respondent Characteristics

Village Name Female Farmers Male Farmers Total N° of Farmers surveyed N° surveyed Avg.

farm size (acres)

% non-‐OC* surveyed

N° surveyed Avg. farm size (acres)


1. Baironpalli 20 4.2 20% 20 n/a n/a 40

2. Nimmani 7 4.4 n/a 15 4.9 n/a 22

3. Gorita 17 3.0 n/a 35 4.7 86% 52

Total 44 3.9 -‐ 70 4.8 -‐ 114

*% non-‐OC surveyed: % Non Open Category, a measure of socio-‐economic marginalization in India; this includes Scheduled Castes (SC), Backward Castes (BC) and other Backward Castes (OBC).

In all three villages surveyed, agriculture served as the primary source of livelihood. In addition livestock (cow, bulls, sheep, goat and poultry) provided supplementary support and livelihood. Few male farmers also engaged in day wage and local businesses. In addition, farmers also engaged in opportunities with the National Rural Employment Guarantee Scheme (NREGA). Key crops across the villages were cotton, paddy, maize, turmeric, pulses, castor and vegetables. All villages face water shortages. Groundwater is available but in short supply. Thus irrigation is done only for a few crops, prominently paddy in all villages. The rest of the crops are predominantly rainfed.

4.1.2 Products delivered by the AAS Program

Across the three villages, farmers mentioned several parameters that they associated with the advisories, which influenced their decision-‐making. These were weather parameters such as rainfall and temperature forecasts and advisories on pest and disease management, crop choices, fertilizer mixes, harvesting decisions, and seed information.

4.1.3 Communication channels used

Farmers across the three villages surveyed in Andhra Pradesh receive forecasts and weather-‐based agro advisories through a collection of channels, some more effective than others. These, as enumerated by farmers and aggregated here, include:

• AAS bulletins distributed by the village Met Centre representative, • AAS bulletins displayed at prominent spots in the village,

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• meetings with the village representative associated with local NGO, • word of mouth and discussions with agro-‐met scientists or representatives, • farmers club meetings in villages, • announcements over microphone • and local TV channels and radio stations.

4.1.4 Assessment Criteria: How salient Is the AAS Program to support local

farmer decision-‐making? 4.1.4.1 Awareness of the AAS Program at Village Level

We found that 90 to 95% of farmers in the three communities surveyed knew of the AAS program. As such, awareness about the AAS program was very high in all three villages surveyed and amongst both male and female farmers. These farmers also indicated that they used the forecasts regularly. Role of women being high in agriculture, awareness and usability of advisories were high amongst women who were also keen on knowing through the AAS and improving their understanding of it.

4.1.4.2 Credibility/Skill

Across all the villages perceived skill level and reliability of forecasts ranged between 60% to 90% for eighty percent of farmers interviewed. About 80% of farmers said that they refer to the advisories more often now than 2 years ago.

4.1.4.3 Salience to local farmer needs

Products delivered

Of all the advisories received (weather parameters such as rainfall and temperature forecasts and advisories on pest and disease management, crop choices, fertilizer mixes, harvesting decisions, and seed information), in all the three villages farmers, particularly women farmers said that they found rainfall forecasts as most crucial to their decision making. Farmers felt that for the most part the information was received in good time, either the day before or the morning when they were going to take decisions.

Uses of AAS advisories: Translating advisories into action to overcome constraints to Agriculture

Constraint #1: Rainfall Variability

Deficit rainfall, farmers opined, was the biggest problem in all three villages. This happened usually during the SW monsoon time, June-‐July-‐Aug-‐Sep. This came up as the no.1 constraint encountered in agriculture, but could be attributed perhaps to the fact that we had gone at a time when the rains were much delayed and farmers were facing problems. Low rains meant low productivity, or delay in sowing. Sometimes they sowed their seeds and then the rains didn’t come, and they would loose all their seeds.

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AAS has been particularly useful by offering rainfall forecasts, which were crucial to determine sowing period, especially if showers on a day were followed by a long drought stretch during the monsoon months. Moreover, the bulletin also gave the exact data on the quantity (mm) of rainfall, which helped farmers judge whether soil moisture was good enough for sowing operations after a rainfall event.

Another important use of AAS was during harvest time. Untimely rainfall at harvest was another weather related risk that ruined crops, particularly paddy and cotton. Farmers felt that getting rain forecasts during these months helped to determine the right harvest time and evade crop losses.

Constraint #2: Pest and Diseases

Crop diseases, usually in July, August and September, came out as the second most important source of constraint in agriculture. Diseases reduced yield quantity as well as quality of yield, and also increased costs of production due to pesticide input.

Sharing their experiences about the AAS, farmers said that earlier they used to use expensive and concentrated pesticides, which was destructive to crop yields as well as personal health. From the advisories, they learnt about using low concentration and low cost pesticides, which saved money by avoiding wastage and also improved health. Timing of pesticide application was also crucial, since rains right after an application would wash it all away. Now, farmers used rainfall forecasts to plan pesticide application.

Documented stories of AAS use by farmers

Male farmer from AP

“I have less land. I used to apply DAP fertilizer every 30 days. Then I started listening to the forecasts and advisories, which said that it should be applied every 15-‐20 days. Since then, I have been able to increase yields in cotton by 4 quintals/acre.

Male farmer from AP

“In vegetables, the advisories informed us to use vermicompost. I did so, and was able to increase yields by 5-‐6 bags (50 kgs. per bag). This started 4 years back”

Female farmer from AP

“Earlier we used to spray fertilizers all over and a lot used to get wasted. We knew that, but still we did it since it was the easiest thing to do. But we learnt from the advisories that by spraying, not only is fertilizer wasted, but also yield is less. It recommended crop

23

based application of fertilizers where quantity of fertilizer is less, but yield is more. Another thing is, fertilizer spraying could be done only by men, because the equipment used for spraying was heavy. With crop based application on the other hand, women can do it too, so I find it beneficial”

Female farmer from AP

“Three years ago, I found out from a weekly advisory that rain was forecast and transplantation of paddy was recommended. I followed the advice and reaped a good crop. Farmers who did not follow the recommendation, delayed transplantation by 15-‐20 days and had lesser yields”

Salience of Communication Channels used

• A Go-‐to Met person at the village level: Women farmers particularly appreciated that they could openly speak to local village representative from the Met office at the village about the advisories and learn more from him.

• Broadcast of AAS advisories at the local level: Broadcast of AAS information over the microphone came out as very helpful too, especially for farmers who could not read the bulletins or required help to interpret them.

4.1.4.4 Equity in reach

Both male and female farmers were equally aware of AAS in the three villages surveyed in AP. However, they were not equally reached by the AAS advisories. Indeed, amongst farmers, those who were members of farmers club, particularly in Baironpalli, were the ones who could participate in its activities and by extension also had better knowledge about the AAS and could use it for their benefit. In addition, women farmers in Baironpalli expressed concern that only male members could be part of the farmers club. That also meant that families with no male members were excluded from membership. Membership was also based on an annual fee, which some farmers’ felt was unaffordable, thus keeping them out of farmers club.

As such, membership in a farmers’ clubs (main outlet for transmission of agromet advisories) ended up as a barrier to women and other socially marginalized groups’ access to agromet advisories and climate information.

4.1.1 Conclusions: Lessons Learnt & Best practices from the State of AP

Overall Use of AAS advisories

Farmers across all villages pointed out that in the last two to three years, use of the AAS had increased considerably in all the three villages. While farmers noted that they have traditionally relied on personal experience and on the lunar calendar to determine type and timing of

24

agricultural operations, they were now increasingly relying on the AAS to inform their decision making.

This was particularly true in Baironpalli, where improved communication channels such as displaying the bulletin in prominent places in the village and announcements over the microphone, as well as interventions by local NGO to make AAS program more useful for farmers, has improved usability amongst farmers. Farmers in Baironpalli added that they tend to exclusively rely on AAS now instead of going by their traditional practices to inform farm-‐based activities. AAS were beginning to make a significant influence on farm-‐based decision-‐making in Nemani and Gorita as well.

The AAS program was ranked number 2 in a list of agricultural support services, with crop compensation schemes and reduction on crop loan interests at the top.

However, membership in a farmers’ clubs (main outlet for transmission of agromet advisories) remains a barrier to women and other socially marginalized groups’ access to agromet advisories and climate information. Other more widely reachable means of communication –such as displaying the bulletin in prominent places in the village and announcements over the microphone, as well as interventions by local NGO to make AAS program more useful for farmers – will have to be privileged.

Farmer recommendations for improvement of the AAS Program (Table)

Additional information sought through AAS

Additional needs Suggested Best practices for Scaling up

1. On alternate crop choices, especially during shortage or delay or rains.

2. On organic cultivation.

1. More training: More village level trainings for both male and female farmers is required to help with better interpretation and use of advisories.

2. Picture messages: Bulletins will be easier to interpret if textual information is elaborated with pictures to improve understanding on kinds of pests etc.

• A Go-‐to Met ressource person at the village level

• Broadcast of AAS advisories on the microphone:

• Display of bulletins in prominent places in the village

• Collaboration with local NGO to make AAS program more useful for farmers

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4.2 STATE 2: HIMACHAL PRADESH (HP)

4.2.1 Agriculture in the State of Himachal Pradesh

Literally translated from Sanskrit as “in the lap of the Himalayas”, Himachal Pradesh lies in the northern tip of India, at the foothills of the Himalayas, bordered by Jammu and Kashmir to the north, to the West by Punjab, South by Haryana and Uttar Pradesh, Uttarakhand on the south-‐east, and by the Tibet Autonomous region to the East. With agriculture, notably horticulture, as the state’s main source of income, HP is India’s fastest growing economy and produces hydroelectric power from its abundant rivers which it sells to neighboring states.

Himachal Pradesh is sub-‐divided into four agroclimatic zones in all. Rainfall differences are stark from the hilly to valley zones. Table xx details the specific agro-‐climatic features of each zone.

Fig. xx: Four agroclimate zones in the State of Himachal Pradesh (Source: HP Agr University)

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Sub Region Monsoonal Rainfall (mm)

Climate Soil type Crops grown

1. Cold & Dry zones

165 Humid to cold arid

Hill soils, mountain,

meadow skeletal, tarai

Wheat, maize, rice, Jowar.

2. High hills

2000 Humid Brown Hill Rice, maize, wheat, rapeseed

3. Low Hills 400 Sub-‐humid Sub-‐mountain, mountain

skeletal, meadow

Wheat, maize, rice, sugarcane.

4. Mid-‐hills

1030 Semi-‐arid to humid

Alluvial (Recent), brown hills.

Wheat, barley, potato.

Fig. xx: Agroclimate zones of Himachal Pradesh state

Out of the four agro-‐climate zones of Himachal Pradesh, the CCAFS team selected 3 zones for its investigation: the mid hills (Kangra district), the low hills (Una district) and the high hills (Kullu district). In each zone, one village was randomly chosen to conduct the survey, respectively Amtrar in the middle hills of Kangra, Bhanjal in the valley area of Una, and Chong in the highlands Kullu.

Large distances and the short time available to the CCAFS evaluation team precluded outreach to the farthest areas of the state, i.e. the dry and cold zones. As such, results from this analysis do not reflect the needs of this last zone. This bias ought to noted in the interpretation of the findings from HP.


State of Himachal Pradesh – Respondent Characteristics

Village Name (District)

Female Farmers Male Farmers Total N° of Farmers surveyed N° Avg. farm % non-‐

OC* N° Avg.

farm % non-‐OC*

27

surveyed size (acres) surveyed surveyed size (acres)

surveyed

1. Amtrar (Kangra)

33 1,075 97% 12 1,25 100% 45

2. Bhanjal (Una)

10 4,2 10% 13 3 0% 23

3. Chong (Kullu)

22 0,775 14% 13 n/a n/a 35

Total 65 2,02 40% 38 2,125 50% 103


Agriculture and Horticulture provided primary livelihood to farmers. In addition livestock (cow, bulls, sheep and goat) provided supplementary support and livelihood. Few male farmers also engaged in day labour in nearby towns and women were involved in commercial stitching and tailoring activities as well. Key crops across all villages were wheat, paddy, maize and vegetables. In the hilly village of Chong, horticulture dominated with apples, plums, peaches and apricot being the important crops. Irrigation, in Amtrar and Chong was provided through canal water and check dams. Bhanjal, being closer to the plains, were predominantly dependent on rainfall and faced water shortages often. This year, with delayed monsoon, Bhanjal was already reeling under water distress when the team visited. They relied on a government provided rig for drinking water.


Across the three villages, farmers mentioned several parameters that they associated with the advisories, which influenced their decision-‐making. These were rainfall forecasts, temperature, wind speed and direction, humidity, pest related information and pest management strategies, information on seed inputs, vermicomposting, and horticulture management (specifically in Chong).


Farmers across the three villages receive forecasts and weather-‐based agro advisories through a collection of channels, some more effective than others.

These, as enumerated by farmers and aggregated here, include:

• farmer meetings at the block level with Agricultural University scientists and experts, • Radio, • news programs on television, • local newspapers,

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• through organizations like NABARD working in select villages, • through active womens’ collectives (especially in Amtrar), • panchayat (village level governing body) meetings in villages, • village level programs such as water shed program by World Bank in Chong, • and through KVK extension officers in some villages (Bhanjal).

4.2.4 Assessment Criteria: How salient Is the AAS Program to support local farmer decision-‐making? 4.2.4.1 Awareness of the AAS Program at Village Level

We found variable levels of awareness of the AAS program among farmers in the three communities surveyed. Farmers in Amtrar displayed the highest knowledge and usability of AAS amongst all the villages with 75% of male farmers and 100% of women farmers acknowledging they knew of the program. In Chong, while male farmers displayed negligible awareness or understanding, women farmers showed greater awareness of AAS and information from the Horticulture Department in nearby town of Bijora, especially in one-‐on-‐one interviews with them. Farmers in Bhanjal said they had only minimum knowledge about the AAS, mainly from occasional meetings held by KVK (Krishi Vigyan Kendra) extension officers in the village.


Amtrar ranked topmost in relevance and accuracy perceptions. Male farmers found the advisories anywhere from 50-‐90% accurate, where as female farmers found it more relevant and almost 100% accurate. Women farmers also found AAS more accurate (50-‐95%) and useful than male farmers in Chong village. In both the villages, women played a much larger role in agriculture and had also been organized into community groups who often attended trainings in agricultural university, horticulture department, interacted with agrometeorologists and agricultural and horticultural scientists and received information on AAS directly.

In Bhanjal, however farmers felt that the advisories, particularly the forecasts fared very badly. They pegged the accuracy of forecasts at around 50% adding that forecasts they heard on radio for Punjab state were more relevant to them. Yet, across all villages, when cross-‐questioned about agricultural support services that farmers found useful, advisories and agricultural related information that farmers received from the agricultural university and trainings at Horticulture research centre came out as most pertinent and useful. Kissan Mela’s (Farmers Fairs) and block level meetings with agricultural experts were also mentioned as particularly favourable in receiving information on type and quality of seeds and other related matters.


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Products delivered




Rainfall variability and erraticity ranked topmost in climate related risks thus rainfall forecasts both during monsoon season (June – October) and rainfall indications during winter months (January – April) were important parameters in influencing decisions. In particular, farmers mentioned rainfall forecast as being crucial for determining sowing operations in monsoon months, and for managing harvest operations which often face risks from excess rainfall during harvesting time (January – March) that destroy harvested crop. Rainfall forecasts were also associated with better planning and water management.

Constraint #2: Temperature Variations

In HP, a second source of climate risk emerged, associated with sudden changes in temperature, especially in the high altitudes. A particularly vexing problem farmers noted was that of frost during March-‐April. Cold, freezing wind during the flowering stage destroyed the flowers thus preventing formation of fruits. On the other hand, higher average temperatures were associated with higher pest incidence and associated threats. Temperature related forecasts were therefore another crucial parameter associated with advisories. It helped farmers to know in advance how temperatures were going to vary in order to take mitigating measures such as lighting fires around orchards to increase temperatures when cold onset was indicated.


Pest and diseases were amongst the top three agricultural constraints mentioned by farmers. Pests and diseases were often linked to variability in weather-‐based parameters such as rainfall, temperatures and humidity. Some common diseases were flies and ants and bacterial infection in vegetables during March – July, seed related infections in paddy in August-‐October, and stem borer in kidney beans. Farmers thus found pest related information in advisories very helpful.


Male farmer from Amtrar, Himachal Pradesh

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“Three years ago, I found out from a weekly advisory that rain was forecast and transplantation of paddy was recommended. I followed the advice and reaped a good crop. Farmers who did not follow the recommendation were delayed transplantation by 15-‐20 days and had lesser yields”

Male farmer from Amtrar, Himachal Pradesh

“Two years ago, the advisory recommended delaying harvesting of wheat crop based on heavy rainfall forecast. I did so and saved my crop. If I had harvested, then heavy rains would have destroyed the harvested grains left in the field”

Female farmer from Amtrar, Himachal Pradesh

“Through the meetings with agricultural experts I learnt how to protect my cucumber crops. I got an apparatus which traps the flies that sit on the plant and destroy it. I have been using it for 5 months now and it has been very helpful in preventing fly attacks”

Female farmer in Amtrar, Himachal Pradesh

“I got to know about vermicomposting through the advisories. I started using it on my onion crop and found the yield to be higher and the quality of onions also improved”

Female farmer from Chong, Himachal Pradesh

“My cabbage crop used to get infected with diseases. I used to spray pesticides but to no avail. I learnt from trainings that I should spray the pesticides at evening, instead of afternoon and then they become much more effective”

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In addition, farmers also provided feedback on communication channels and why certain channels were not appropriate or did not work as well.

Both male and female farmers supported trainings and discussions in villages as superior forms of dissemination channels. Moreover, the team also observed that Amtrar being in closer geographical proximity to Agricultural University in Palampur, was better able to establish channels of communication with the University for timely dissemination of advisories.


Across the 3 villages, female farmers came out as more aware of the AAS program than male farmers. This arguably, was linked to the role women played in agriculture. In Amtrar, women had a larger role to play in agriculture and took interest in using the advisories and benefitted from it. They participated in block level meetings held by agricultural scientists and agrometeorologist and upon return would also share the information amongst other women and men in the village.

This was true in Chong as well. All the women interviewed were part of the local women collectives who played an active role in attending trainings and camps at the Horticulture Research Centre at Bijora and took greater initiative in learning more about the AAS and applying it to their decision-‐making. While the KVK at Chong had appointed one of the women farmers to further disseminate AAS related information in the village, she had yet to make a significant impact on improving awareness and usability in the village.

With respect to information through extension officers from KVKs, women farmers in Bhanjal lamented that such dissemination was restricted to larger landholders in the village only and a majority of small farmers were not part of this network. There also seemed to be gender differences in they type of channel preferred. While male farmers in both Amtrar and Bhanjal rated radio and television as good channels to reach them, women farmers expressed their inability to listen to radio or watch television during the day due to lack of time and engagement with other household and field related activities.

Both male and female farmers supported trainings and discussions in villages as superior forms of dissemination channels.

4.2.5 Conclusions: Lessons Learnt & Best practices from the State of HP


In all 3 villages surveyed, 90% farmers said they used personal experience and relied on traditional farming practices in undertaking farm-‐based decisions. In addition, they also used local lunar calendars, traditional indicators as well as their own observations on weather and crop patterns to determine farm level activities.

32

Only in Amtrar did farmers add that they refer to advisories they receive from agricultural university, on radio and on TV too to help with decision-‐making.

What made advisories penetrate so successfully in Amtrar relative to the other two sites where use of AAS was poor?

From HP, we learnt the following:

-‐ When women farmers are fully engaged, the appropriation and use of AAS is maximal (lesson from Amtrar village);

-‐ Trainings and discussions in villages are the superior forms of dissemination channels: regular trainings at the horticulture department of the university for Amtrar farmers proved critical. When there is sustained Interaction between farmers and agrometeorologists, agricultural and horticultural scientists, high use of advisories ensues;

-‐ Advisories need to be locally salient. Indeed, even within a state, high agroclimate differences are high. This was evident between Palampur Agricultural University (knowledge hub of AAS advisory generation) and the remote low hill parts of Una districts (closest to Punjab in terms of agro-‐climate features) where surveyed Una district farmers did not find provided agro-‐met advisories accurate at all nor salient to their local decision-‐making under a variable climate. As such, local downscaling and value-‐addition is paramount to ensure salience to local farmer needs and usability by farmers.

Farmer recommendations for improvement of the AAS Program in HP


Additional needs Lessons Learnt/Suggested Best practices for Scaling up

1. On water management, especially during times of shortage

2. Access to good quality seeds

1. Advisories through cell phones (voice mails and text messages)

2.Elaborate advisories through television in addition to state level forecasts currently relayed

3. Printed advisory bulletins displayed in all central points in the village.

• Trainings and discussions in villages as superior forms of dissemination channels.

• Local downscaling and value-‐addition is paramount to ensure salience to local farmer needs and

33

usability by farmers.

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4.3 STATE 3: PUNJAB

4.3.1 Agriculture in the State of Punjab

Punjab displays a wide diversity in agro-‐climate zones. Straddling both the low plains and western Himalayas regions, Punjab offers an interesting mix of plain and hill agriculture. The state lies in the northwest of India, bordered by Paskistan to the West, South by Rajhastan and Haryana, and to the east by Himachal Pradesh. With agriculture, notably horticulture, as the state’s main source of income, HP is India’s fastest growing economy and produces hydroelectric power from its abundant rivers which it sells to neighboring states.

Himachal Pradesh is sub-‐divided into four agroclimatic zones in all. Rainfall differences are stark from the hilly to valley zones. Table xx details the specific agro-‐climatic features of each zone.

§ Agro Climatic Region: Trans-Gangetic Plains Region

Sub Region Rainfall mm) Climate Soil Crop 1. Central Plain

Zone (Ludhiana and surroundings)

561 Semi-‐arid to Dry sub-‐humid

Alluvial (Recent) Rice, Wheat, Maize,

Groundnut, Cotton, Gram, Barley, Pear, Guava.

2. Western Plain Zone

(Faridkot and surroundings)

890 semi-‐arid to Dry sub-‐humid

Calcareous

Rice, Wheat, Maize, Bajra, Barley, Sugarcane, Gram,

Moong, Arhar, Oilseed,Vegetables.

3. Southwest Zone (Bhatinda and surroundings)

Scarce Rainfall arid region

360 Arid and Extreme arid

Calcareous, Sierozemic, Alluvial

(Recent), desert

Wheat, cotton, gram, Bajra, rice

§ Agro Climatic Region: Western Himalaya Sub Region

4. Foothills of

Shivalik & Himalayas

Undulating Plain

Zone

variable (see table below)

various (see table below)

various (see table below)

Rice, Wheat, Maize, Sugarcane, Groundnut, ,Sesamum, Kharif

Pulses,(Moong, Mesh, Arhar), gram, Rape&

Mustard, Linseed, Lentil, Peas, Fruits, Vegetables,.

Agro Climatic Features of the Western Himalaya Sub Region in Punjab State

Sub Region Rainfall (mm) Climate Soil Crop

35

High altitude temperate 165 Humid to cold

arid

Hill soils, mountain, meadow

skeletal, tarai

Wheat, maize, rice, Jowar.

Hill temperate 2000 Humid Brown Hill Rice, maize, wheat, rapeseed

Valley temperate 400 Sub-‐humid

Sub-‐mountain, mountain skeletal, meadow

Wheat, maize, rice, sugarcane.

Sub-‐tropical 1030 Semi-‐arid to humid

Alluvial (Recent), brown

hills. Wheat, barley, potato.

Table. xx: Agroclimate zones of Punjab State, from the Plain

(Source: http://dacnet.nic.in/farmer/new/dac/AgroClimaticZones.asp?SCod=16)

Fig. xx: Four agroclimate zones in the State of Punjab (Source: Ludhiana Agr University)

36

Out of the four agro-‐climate zones of Punjab, the CCAFS team selected 3 zones for its investigation: the Piedmond alluvial / Central plain zone (Ludhiana district), the Southwest alluvial plain (Bhatinda district) and the Undulating subregion/Siwalik hills (Hoshiarpur district). In each zone, one village was randomly chosen to conduct the survey, respectively Panglian (in Ludhiana), Mehma Sarja (in Bhatinda) and Achalpur (in Hoshiarpur).

In Punjab the wide diversity in agroclimate features was captured, in an effort to capture the perspectives of farmers from diverse agricultural contexts. We give below the most significant elements of this appraisal.

In total, 86 farmers participated in the appraisal in the state of Punjab, of which 37 female and 49 male, characterized as follows:

State of PUNJAB – Respondent Characteristics Village Name Female Farmers Male Farmers Total N° of

Farmers surveyed

N° surveyed

Avg. farm size (acres)


N° surveyed



1. Panglian

18 1 39% 13 3,2 0% 31

2. Mehma-‐ Sarja

10 5,7 0% 28 9,7 4% 38

3. Achal Pur

9 1,8 0% 8 3,5 13% 17

Total 37 2,8 13% 49 5,5 6% 86


Agriculture served as primary livelihood for farmers. In addition livestock (buffalo, cows, sheep, goat and bulls) provided supplementary support and livelihood. Key crops across all villages were wheat (winter crop), paddy (summer crop), cotton, maize, millet (sorghum and pearl millet) and vegetables. In Panglian and Mehma Sarja, farmers relied on groundwater (extracted through tubewells) for irrigation purposes. In Achalpur, reliance on rainwater was more, though some farmers used groundwater to irrigate a small proportion of their fields.


Across the three villages, farmers mentioned several parameters that they associated with the advisories, which influenced their decision-‐making. These were rainfall forecasts, temperature, humidity, pest related information and pest management strategies, fertilizer application, information on seeds, green manuring, and irrigation decisions.

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• interactions with AMFUs or agricultural university experts, • agricultural programs on television, • newspapers, • Kisan Mela’s (farmer fairs) in the village, • SMS • Internet.



We found variable levels of awareness of the AAS program among farmers in the three communities surveyed. Male farmers in Panglian had the highest awareness about AAS. In comparison, only 50% of male farmers in Mehma Sarja and Achalpur displayed knowledge about AAS.

Women farmers, across all three villages, had no knowledge about the AAS and had never used it to influence their decisions. This was arguably linked to their minimal to non-‐existent role in agriculture. Women were primarily housekeepers in addition to taking care of livestock in some cases. Thus women were left out of most trainings and discussions with agricultural university experts or with extension officers.


Farmers pegged the accuracy of forecasts anywhere from 20% -‐ 90%, with higher accuracy levels in Mehma Sarja and Achalpur. In Mehma Sarja, farmers added that they received the advisories at appropriate times, especially during harvesting and sowing time where weather information was crucial in decision making. In Panglian, farmers found information on pests and also diseases in livestock and medicine important and useful. In Mehma Sarja and Achalpur male farmers felt that advisories were very useful and relevant. 90% said they followed the advice regularly. However, while farmers here found the advisories relevant, majority of farmers in Panglian and Achalpur felt the advisories were not sufficient for farm management strategies because forecasts was not accurate at all times and also was not received on time. In addition, farmers

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with less than an acre of land felt that advisories were not of much relevance to them due to the small scale of operations.


Products delivered



Constraint #1: Difficult Irrigation Planning

Male farmers perceived irrigation related issues as most crucial and important. In Panglian and Mehma Sarja, erratic supply and shortages in electricity caused severe obstructions in irrigation. In addition, sudden rains during harvest time (March-‐April) also damaged crops. In Achalpur, poor rains in winter (Dec-‐March) negatively affected the wheat crop and maize crop. Advisories, in addition to giving rainfall forecasts, provided important information on laser levelling, which determined the optimal level of irrigation in a given field, thus aiding better management of irrigation.


In casual discussions with large farm holding farmers before the interviews, they mentioned severe temperature changes in 2003, 2004 and 2012 which resulted in more diseases and consequently crop failure. Early forecasts in temperature variations apart from helping better prepare and mitigate disease on-‐set, are also crucial for containing diseases and infection in livestock triggered by sudden temperature changes.


Male farmer from Panglian, Punjab

“Agrometeorologists came for a meeting in a nearby village. They informed us about a big rainfall event in 2009 in 2 days. I had earlier delayed nitrogen fertilizer application for wheat. When I heard about the forecast, I immediately hired labor and applied the fertilizer. That was very helpful in keeping my crops healthy”

Male farmer from Mehma Sarja, Punjab

39

“I learnt about new cotton seeds through the advisories. I tried them and harvested a good crop with it”


In addition, farmers also provided feedback on communication channels and why certain channels were not appropriate or did not work as well.

Both male and female farmers supported trainings and discussions in villages as superior forms of dissemination channels. Moreover, the team also observed that Amtrar being in closer geographical proximity to Agricultural University in Palampur, was better able to establish channels of communication with the University for timely dissemination of advisories.


Women in all the three villages were completely unaware or had little knowledge about the AAS program. They lamented being left out of trainings or meetings in the village and felt that exclusive trainings should be held for them.

In Panglian and Mehma Sarja, the richer and progressive farmers received the AAS information regularly and were able to benefit from it. They had better access to it due to their connections with AMFUs or extension officers and resources such as internet access. In some cases they helped organize trainings in the village to disseminate information to others farmers, however this was not always the case. Moreover, in case of special projects in a village, such as the ‘Climate Change’ project in Achalpur, those associated with it were more likely to know about the advisories and benefit from it than those who were not part of the project, thus creating information asymmetries.



Majority of farmers noted that they relied predominantly upon personal experience and traditional knowledge and practices to take farm-‐based decisions. In Achalpur, a few farmers who are associated with an on-‐going project on climate change added that they refer to advisories received through the project. In Mehma Sarja farmers referred to farm calendars that they received during periodical Kisan Mela’s (Farmers Fairs).

From Punjab, we learnt the following:

-‐ Use of an NGO or local project to promote the use of advisories serves to increase reach and appropriation of available agromet advisories, and indent its use in local practice (lesson from Achal pur). In the case of the ‘Climate Change’ project in Achalpur, those associated with it were more likely to know about the advisories and

40

benefit from it than those who were not part of the project, thus creating information asymmetries.

-‐ For smallholder farmers with farm sizes of less than an acre, agromet advisories are not of much relevance due to the small scale of operations.

Farmer recommendations for improvement of the AAS Program in Punjab


Additional needs Lessons Learnt/Suggested Best practices for Scaling

up

1. Information on new varieties of seeds; also on why certain seeds failed and how to prevent it.

2. Wind speed to help decide time for spraying of pesticide, weedicide and fungicide

3. Harvest time for wheat

4. What to do during sudden frost in winter

5. Information on market prices

6. Information on mechanization possibilities on the farm

7. Timely and accurate rainfall forecasts.

1. Display textual copies of advisories in prominent locations in the village such as the Gurudwara (Sikh temple). Common areas also ensure information is evenly disseminated and not restricted to few factions or privileged sections.

2. Specific trainings and meetings for women farmers in the village.

3. Advisories through SMS and voice mails.

4. 24/7 TV Channel exclusively on agriculture.

6. Organize farmers into Kisan groups (Farmers’ Group) on a voluntary basis to help disseminate vital information in the village.

7. Appoint village level volunteers who could receive biweekly advisories from the AMFU and communicate them to the rest of the village.

• Use of an NGO or local project to promote the use of advisories serves to increase reach and appropriation of available agromet advisories, and indent its use in local practice (lesson from Achal pur)

• For smallholder farmers with farm sizes of less than an acre, agromet advisories are not of much relevance due to the small scale of operations.

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4.4 STATE 4: WEST BENGAL (WB)

4.4.1 Agriculture in the State of West Bengal

India’s fourth most populous state with over 91 million inhabitants, home of Kolokota, West Bengal is bordered by the countries of Nepal, Bhutan and Bangladesh, and, from east to south, by the Indian states of Assam, Sikim, Bihar, Jharkhand and Orissa. A major agricultural producer of mainly paddy, jute and tea, the state of WB is the 6th largest contributor to India’s net domestic product.

Fig. xx: WB in India (Source: Maps of India.com)

WB is sub-‐divided into five main agroclimatic zones. Rainfall, topography and climate differences are stark from the hilly to valley zones. Table xx details the specific agro-‐climatic features of each zone.

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Zone Rainfall (mm)

Climate Soil Crops

1. Himalayan Hills

2441 Per humid to humid

Brown Hills Rice, maize, Ragi, potato

2. North-‐East Hills


Red sandy laterite Rice, rapeseed, maize

3. Upper Brahmaputra

2809 Humid to per humid

Alluvial, red loamy

Rice, jute, rapeseed, wheat

4. Southern Hills 2052 Per humid to humid

Acidic soils Rice, maize, sesame, sugarcane

5. Lower Brahmaputra

(Terai floodplain)


Alluvial, red loamy, tarai soils

Rice, rapeseed, wheat, jute, potato

Table. xx: The five agroclimate zones of the State of West Bengal

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Fig. xx: Agroclimate zones of West Bengal state

(Source: NABARD, State Agricultural Plan for West Bengal)

Out of the five agro-‐climate zones of WB, the CCAFS team selected 3 zones for its investigation: the Gangetic floodplain zone (Nadia district), the coastal floodplain region (South 24 Parganas district) and the Undulating lateritic region (Pashim Midinipur district). In each zone, one village was randomly chosen to conduct the survey, respectively Chandamari (Nadia), Prasadpur (South 24 Parganas) and Keshpur (Pashim Medinipur).


State of West Bengal – Respondent Characteristics Village Name Female Farmers Male Farmers Total N°

of Farmers surveyed

N° surveyed



N° surveyed



45

1. Chandamari

8 1,6 0% 10 1,9 0% 18

2. Prasadpur

7 0,4 100% 9 1,266666667 100% 16

3. Keshpur 8 0,8 50% 23 3,1 35% 31

Total 23 0,95 50% 42 2,09 45% 65


Agriculture served as the primary livelihood for farmers across the three villages. In addition livestock (cow, goat, chicken) provided supplementary support and livelihood. Male farmers also indicated to a growing trend of seasonal labour requiring farmers to migrate out into nearby cities, other states and even out of the country. Farmers (both male and female) engaged in local business as well.. Key crops across all villages were paddy, jute and mustard (Chandamari), Betel leaves (Prasadpur), sesame oil and groundnut (Keshpur) and vegetables. Irrigation, in Chandamari and to some extent in Keshpur was provided through shallow pumps and mini wells respectively. In Prasadpur, agriculture was predominantly rainfed.


Across the three villages, farmers mentioned several parameters that they associated with the advisories, which influenced their decision-‐making. These were weather related information including rainfall forecasts, temperature, wind speed and direction, fog, storms, hailstorms and humidity, advisories about choice of crops, sowing time, new seeds, pest and pest management, and irrigation activities.




• seminars and discussions with Agricultural University agrometeorological scientists (BCKV),

• through local NGOs (Ramakrishna Mission), • womens’ self help groups, • discussions amongst farmers in village teashops, • newspapers, • television • and radio.

46


Across all three villages, we found that male and female farmers had very minimal knowledge about the AAS program. During interviews and more probing, male farmers revealed greater knowledge about them and some information on weather and weather related advisories they had received on occasion. In Chandamari, while farmers said they didn’t know about the AAS during FGD, in interviews, 3 out of 4 had received some form of information about AAS. In Prasadpur, only 3 out of the 12 farmers knew about the AAS. In Keshpur, 60% of male farmers and 25% of female farmers from the FGD seem to know about AAS bulletins.

Most information, however, farmers felt, was received and used by few selective farmers in the village depending upon their socio-‐economic positions and status in the village.


In West Bengal, AAS forecasts were found to be of low credibility and relevance. Across the 3 villages, the accuracy of the forecasts from FGDs and interviews was pegged from anywhere between 10-‐20% to about 50-‐60%. About 80% of farmers across all the 3 villages expressed dissatisfaction with the advisories. They said that they don’t find the advisories very relevant and don’t use the advisories. They added that they don’t trust the forecasts enough to use them. Women in Keshpur said that they found the advisories useful but did not find the forecasts accurate. In terms of timeliness, 60% of farmers across the 3 villages said they needed the forecasts at least a week in advance.


Products delivered




In all the three villages, erratic rainfall is a seasonal occurrence. In Chandamari and Prasadpur, paucity of rains during monsoon season negatively effects jute harvesting as well as

47

transplantation activities in paddy. On the other hand, untimely heavy rains during harvest season for rice (October-‐November) destroys the crop as a result of germination of the grains in the field. In Keshpur too, excess rainfall in July-‐October results in flooding from Tomal, Silai and Kasai rivers and destruction of fields and crops. Farmers say that rainfall forecasts are crucial during such times, but on several occasions forecasts are unable to predict with accuracy. Farmers in Keshpur also added that advisories on transplantation technique and seed quality was also very helpful.


Several diseases are linked with seasonal variations. In Prasadpur, ‘Angari’ disease that infects betel leaves occurs during monsoon season. Replenishment of soil every 2-‐3 years and use of large quantity of pesticides are the only mitigation. In Keshpur too, diseases in potato are associated with fog conditions, while paddy crop suffers during severe winter conditions. Farmers say that while pesticide information in advisories are very important, more often than not they have to rely on pesticides available in the local market which may be different from the ones recommended in the advisories.


Male farmer from Chandamari, West Bengal

“I find rainfall forecast useful in deciding time of sowing of Aman rice. Rainfall data helps in irrigation operation”

Male farmer from Keshpur, West Bengal

“Yes, Til and groundnut production have increased a lot since they’ve been using the advice”


In addition, farmers also provided feedback on communication channels and why certain channels were not appropriate or did not work as well. In particular, farmers in both Chandamari and Prasadpur pointed out only a few selective farmers who had links with the BCKV or were part of experimental projects had knowledge about the AAS program and were in a position to benefit from it. While local NGOs such as the Ramakrishna Mission or Sahid Khudiram Sheba Mission did not deliver AAS bulletins, farmers appreciated the agricultural related information on seeds, soil quality and extreme weather forecasts, that were disseminated through these organizations. Particularly noteworthy was that Bangladesh radio was favoured over local radio by farmers in Prasadpur!

48


Women farmers for the most part lamented that they were not part of any meetings and did not directly receive any information about the AAS. They only got some information through their husbands and other male farmers. They insisted that they be included in trainings and meetings on AAS and other agriculture related ones.

Male farmers in both Chandamari and Prasadpur pointed out that only a few farmers, those who were closely associated with the agrometeorological experts at the Agricultural University, and those who were part of experimental projects in Prasadpur received most of the information from AAS and in a position to use the information appropriately. The majority, they said, were left out of the communication.

Women for the most part were not aware of the AAS program, except few women in Keshpur who had some knowledge of it. This could also be linked to their minimal role in agriculture, as women across the state are mostly involved in household related work. In one of the villages (Prasadpur) women help with livestock. In agriculture, women go to the fields only when additional labour is required.

4.4.5 Conclusions: Lessons Learnt & Best practices from the State of WB


Across the three villages surveyed in West Bengal, male and female farmers noted that they relied solely on traditional practices and their own understanding and experience to take farm based decisions.

Further, they women farmers added that experts from the agricultural university came for discussions in the village sometimes, but those were limited to male farmers only. They are not included in any kind of discussions with agricultural experts who at best only invite certain male farmers for such meetings.

In sum, in West Bengal, improvements in the reach of AAS advisories and their salience to local farmer needs are urgent. Farmers suggested a number of needed steps to improve the usability of the AAS program; these are summarized in the table below. They appreciated this study which came to ask them this question, and gave them an opportunity to air their views.

It is hoped that if these steps are proceeded with, significant improvements in farmers’ use of AAS advisories will ensue.

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From WB, we learnt the following:

-‐ Village discussions/trainings on Agromet advisories is a good strategy to increase the reach of advisories. However, Wide community mobilization and inclusion of all farmers within the community (not only male farmers of high socio-‐economic status) is critical during village discussions by Agricultural experts to ensure widespread appropriation and use of AAS advisories. This is a critical strategy to avoid a situation where the majority is left out and only those who are closely associated with the knowledge providers (agrometeorological experts at the Agricultural University, etc.) and those who are part of experimental projects receive most of the information from AAS and in a position to use the information appropriately

-‐ Use of local NGOs is instrumental in this regard to widely mobilize community towards use of agricultural information.

Farmer recommendations for improvement of the AAS Program in WB



1. Crop related information – for example, advance advisories on how to protect cauliflower crop during higher than average temperatures in winter.

2. Information on new techniques to reduce cost of cultivation, new methods of cultivation and technology, seed varieties, better fertilizer mix, suitable pesticides, and unknown diseases.

3. Soil nutrient management strategies

4. Choice of alternative crops during monsoon and winter season

1.Detailed weather forecasts on TV at least 2 -‐3 times a day

2. Door to door information through an appointed volunteer in the village

3. Newspapers

4. More face-‐to-‐face meetings and discussions in the village with agricultural experts that all farmers could attend

6. A toll free number for agromet advice.

7. Advisories to be displayed on notice boards in key locations in the village.

• Face-‐to-‐face meetings and discussions in the village with agricultural experts that all farmers can attend

Wide community mobilization and inclusion of all farmers within the community (not only male farmers of high socio-‐economic status) is critical during village discussions by Agricultural experts to ensure widespread appropriation and use of AAS advisories.

• Use of local NGOs instrumental to widely mobilize community towards use of agricultural information.

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4.5 STATE 5: TAMIL NADU (TN)

4.5.1 Agriculture in the State of Tamil Nadu

Home of the Tamil people since the era of 500 BCE, Tamil Nadu lies on the southernmost part of the Indian peninsula. Bordered, from north to west, by the Union territory of Pondicherry, the states of Andhra Pradesh, Karnataka and Kerala , Tamil Nadu is bound by the Eastern Ghats in its northern flanks, the Nilgiris, Anamalai Hills and Palakkad to the west, by the Bay of Bengal, the Gulf of Mannar and Palk Straight to the east and south East, and finally, by the Indian Ocean in the South.

This wide diversity of climates endows Tamil Nadu with seven agroclimatic zones in all. Table xx details the specific agro-‐climatic features of each zone.

Zone Rainfall (mm) Crops

Cauvery Delta 956.3 paddy, sugar, cotton, groundnut, sunflower, banana, ginger

Northeastern 1109 paddy, cholam, cumbu, ragi, groundnut, sugar, cashew

Western 653.7 paddy, jowar, ragi, turmeric, cotton, oilseeds

Northwestern 849 paddy, wheat, maize, ragi, bajra, sugar, groundnut, cotton, sunflower, tobacco, mango

High Altitude 1857 paddy, groundnut, tea, coffee, vegs

Southern 816.5 paddy, cholam, ragi, cumbu, groundnut, cotton, banana, tobacco

High Rainfall 1456 paddy, coconut, vegs, tea, cashew, banana, rubber

Fig. xx: 7 Agroclimate zones in the State of Tamil Nadu (Source: Coimatore Agr University)

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Out of the seven agro-‐climate zones of Tamil Nadu, the CCAFS team selected 3 zones for its investigation: the Western zone (Dhindugul district), the High altitude and hilly zone (Nilgiris district) and the Northwestern zone (Namakkal district). In each zone, one village was randomly chosen to conduct the survey, respectively Kannivadi (Dhindugul), Melchowhutty (Nilgiris) and Vadavattur (Namakkal).

Large distances and the short time available to the CCAFS evaluation team precluded outreach to all agroclimate regions of the state, notably the Cauvery delta zone, Southern, Northeastern and high rainfall zones were left out of this assessment. As such, results from this analysis should be interpreted witin the bounds our sampling, and do not reflect the needs of farmers across all agroclimate zones in the state. Please refer to other states where sampling already captured farmer perspectives in the context of omitted agroclimate zones.

In total, 46 farmers participated in the appraisal in the state of Tamil Nadu, of which 19 female and 26 male, characterized as follows:

State of Tamil Nadu – Respondent Characteristics Village Name Female Farmers Male Farmers Total N° of

Farmers surveyed

N° surveyed



N° surveyed



1. Kannivadi

9 2,4 15 5,6 93% 24

2. Melchowhutty

3. Vadavattur

10 3,4 50% 11 3,7 35% 21

Total 19 2,9 50% 26 4,65 64% 45 *% non-‐OC surveyed: % Non Open Category, a measure of socio-‐economic marginalization in India; this includes Scheduled Castes (SC), Backward Castes (BC) and other Backward Castes (OBC).

In all villages surveyed, agriculture served as the primary source of livelihood. In addition livestock (cow, buffaloes, goat, chicken) provided supplementary support and livelihood. Few male farmers also engaged in agricultural labour. In addition, farmers also engaged in opportunities with the National Rural Employment Guarantee Scheme (NREGA). Women farmers mentioned tailoring and stitching and social work as other side occupations. Key crops across the villages were different for each village. In Kannivadi, maize, cotton and coconut were main crops, in Melchohutty, potato, tea and vegetables dominated and in Vadavattur, onion, groundnut and fodder crops (sorghum and maize) were primary.

In all villages agriculture is predominantly rainfed. Some part of it though (less than 50%) is served by groundwater irrigation through tubewells.

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Across the three villages, farmers mentioned several parameters that they associated with the advisories, which influenced their decision-‐making. These were weather parameters such as rainfall and temperature forecasts, wind speed and direction, cloud cover, dewfall, frost forecast and advisories on crop selection, disease forecast and pest management in crops and livestock.




• display of AAS at village bulletin boards, • trainings conducted by local institutions or extension units (MSSRF in Kannivadi,

Horticulture Research Station in Melchowhutty, and KVK in Vadavattur), • SMS, • Phone calls, • forecasts on local television channels, • and Internet.



Farmers surveyed in Tamil Nadu displayed high levels of knowledge on the AAS program. Awareness about the AAS program was high (100%) amongst male farmers in all three villages surveyed. Women farmers surveyed in Kannivadi and Melchowhutty also had knowledge about the AAS program, with 100% awareness in the former and 75% in the latter. In Vadavattur, awareness amongst women farmers was much lower, and women represented only 10% of those surveyed with some knowledge about the AAS.


Across the three villages, farmers perceived the accuracy of AAS as between 50-‐90 per cent. Skill and accuracy was perceived higher by male farmers than by female farmers, though in Kannivadi, both male and female farmers found the AAS highly reliable, and both displayed considerable confidence in AAS forecasts and advisories and in using them.

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Lead time of Products delivered

Farmers across all villages held that they received the information with sufficient time to carry out operations. However, they added that it would be favourable to lengthen lead time by a week to ten days.

For the most part, farmers across the board said the lead time was sufficient to carry out operations. But they also added that it would be better to lengthen lead time by a week to 10 days.



Shortage of rainfall and scarcity of water came out as the biggest concern across all three villages. It affected sowing dates and output. In Kannivadi, farmers opined that delayed sowing lead to other issues as well, especially pest infestation. Drought or delayed rains during July-‐August affected cotton crop the most. Based on advisories they undertook mulching (to conserve soil moisture they cover the soil with coir and other natural stuff) and drip irrigation to extend the evaporation process. The other big concern was untimely rains, particularly in Melchowhutty and Vadavattur. Farmers in Vadavattur conveyed that untimely rainfall destroyed the onion crop. They frequently delayed harvesting operations if rainfall was indicated in the forecasts.


In Melchowhutty, due to its hilly location, sudden temperature variations affect the tea crop and string beans. In tea, temperature increases causes blight disease, while in beans, temperature increases increased looper (pest) infestation Farmers relied on advisories to determine pesticide application.


Male farmer from Kannivadi

“I use the wind speed and direction forecast to inform pesticide spray and to provide structural support for crops. I also use rainfall forecasts to determine when to harvest”

Male farmer from Vadavattur, Tamil Nadu

“The advisories are useful for livestock management. I learnt that we should allow the animals to graze immediately after rainfall. I also rely on it for treating diseases in livestock”

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Male farmer from Kannivadi

“If rains are forecast then I postpone irrigation and that saves labour costs associated with it. Rainfall forecasts also help me decide on weeding and fertilizer application”

Female farmer from Melchowhutty

“I have changed weeding operations based on AAS information. I also decide on harvesting operations now by referring to the bulletin”


Farmers also shared feedback on the channels through which they received advisories.

In Kannivadi, farmers remarked that while voice mails through cellular phones was a great way to receive information, it was not working well so far due network issues in the village. With respect to receiving information through MSSRF, farmers expressed concern that farmers who were not members with MSSRF found it difficult to receive AAS as regularly and benefit from them as much as members.

In Melchowhutty, farmers did receive advisories on their cellular phones through SMS, however several of them could not read it because it was in English and not their local language. Farmers were also not familiar with reading SMS messages on their phones and required additional training in such cases.


In Kannivadi and Vadavatur, both male and female farmers were aware of the AAS. However, in Kannivadi, farmers indicated that reach and use of AAS was more in the case of farmers who were members with the MSSRF Knowledge Centre at the village. Most information was communicated through trainings, which only members could attend. Non-‐members are therefore unable access this information on the same scale and depth that the members are able to.

In Kannivadi, women farmers engaged in agriculture typically during the sowing, weeding and harvesting time. Women farmers however have taken a significant interest and initiative in getting information from the MSSRF (M S Swaninathan Research Foundation) Knowledge Centre in the village about AAS and other agriculture related information. One of the women farmers has also been a volunteer for recording of weather data from the Manual Weather Station in the village. Due to her interaction with other women farmers in the village, there was a great deal of enthusiasm amongst women farmers in the village about the usefulness of AAS and on further improvements in it.

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In all three villages, farmers ranked agro-‐advisories and agricultural information as topmost amongst agricultural support services that they received from local institutions or extension services.

However, significant cross-‐village differences in the use of advisories are to noted. In Kannivadi, men and women both displayed considerable confidence in AAS forecasts and advisories and in using them. They receive them regularly from the MSSRF Knowledge centre and use them to determine sowing time, pesticide and fertilizer application and harvesting time. They also attend trainings on agro-‐advisories held by the knowledge centre.

In Melchowhutty and Vadavattur, use of AAS advisories is more timid, as farmers have only recently become familiar with AAS. Men in both villages mentioned relying primarily on traditional knowledge and practices to take decisions on crop management. However, in Melchowhutty, they have started referring to weather forecasts while in Vadavattur, they use the information (which is more tuned to livestock advisories) for pests and disease management for animals. Women farmers in both villages agreed that they had a traditional sowing period based on rains for the crops, which they followed. Further, they depended upon market prices to decide which crops to sow. Moreover, they also shared information with other farmers during village festivals. In the last two villages, thus advisories are not yet the main basis for farm decisions; market prices and traditional sowing calendars still reigning supreme.

Overall the reach and farmer use of AAS advisories in TN is encouraging. Improvements are still needed nonetheless, as identified by farmers in the following table.

From TN, we learnt the following:

-‐ Smallholder farmers can be successfully reached with agromet information using a diversity of communication channels (extension, local knowledge center, face-‐to-‐face village meetings and trainings by agricultural experts, SMS and voice messages, …). Designing and harnessing the power of a tailor-‐made fleet of communication solutions is what it takes to reach remote smallholder farmers at scale;

-‐ Presence of a local agrometeorological knowledge center (the MSSRF Knowledge Centre at the village) improved access and usability of AAS advisories;

-‐ SMS based dissemination and phone calls are effective preferred channels to reach farmers. For those who cannot read advisories, voice messages on the phone are preferred.

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Farmer recommendations for improvement of the AAS Program in TN


Additional needs Lessons Learnt/Suggested Best practices for Scaling

up

1. Improved Resolution -‐ Information is sufficient to manage crop based activities but the resolution needs to be improved for the forecasts, particularly rainfall forecasts.

2. Pest management -‐ Information on new pests expected in each season. More trainings on pest management.

3. Information on rganic farming. At the moment the advice is tailored to conventional chemical based farming and therefore some farmers dont find it useful.

4. On new mechanization tecniques-‐ In the past farmers grew ragi, wheat, and other cereals. Now they don’t, because of labour shortage. Famers wants to find out about machines for harvesting and for sowing seeds.

5. Information related to marketing, cold storage facilities and self help group trainings.

1. TV channels need to have fixed channels and timings to relay advisories and other information related to agriculture. Flash news on all channels on important weather events is necessary.

2. For those who cannot read advisories, voice messages on the phone are preferred.

3. Mobile phone application for AAS should be started.

5. Larger role of farmers in dissemination activities through voluntary involvement and enlistment

6. Specific FM radio station for weather based agro and livestock advisories.

7. Call centre where farmers could call for additional information and assistance.

• Smallholder farmers can be successfully reached with agromet information using a diversity of communication channels (extension, local knowledge center/hub, face-‐to-‐face village meetings and trainings by agricultural experts, SMS and voice messages, …). Designing a tailor-‐made fleet of communication solutions is what it takes to reach remote smallholder farmers at scale;

• Presence of a local agromet knowledge center/hub (the MSSRF Knowledge Centre at the village) improved access and usability of AAS advisories;

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• SMS based dissemination and phone calls are effective preferred channels to reach farmers. For those who cannot read advisories, voice messages on the phone are preferred.

• Local downscaling and improved resolution of the rainfall forecasts is paramount to ensure salience to local farmer needs and usability by farmers.

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4.6 STATE 6: GUJARAT

4.6.1 Agriculture in the State of Gujarat

With a coastline of 1600km and over 60 million inhabitants, Gujarat is an ancient land believed to be home to one of the oldest ports in the world, whose contributions to the history and economic evolution of India are no longer contested.

Gujarat is sub-‐divided into eight agroclimatic zones in all. Cross-‐zonal rainfall differences are stark. Table xx details the specific agro-‐climatic features of each zone.

Agro-‐climate

zone Rainfall (mm) Crops Soils

South 1000-‐1500 cotton, jowar, wheat, sugar, hort

black clay

Middle 800-‐1000 cotton, bajra, tobacco, pulses,

wheat, paddy, maize, jowar, sugar

black soil and some sand

North 625-‐875 tobacco, wheat, jowar, millet, vegs, spices, oilseeds

sandy loam to sandy soils

Heavy Rain (South)

>1500 salty and black

Bhal and Coastal 625-‐1000 groundnut, cotton, bajra, dry wheat pulse, jowar

medium black and salty

South Saurastra 625-‐750 groundnut, cotton, pulses, wheat, bajra,

jowar, sugar

shallow medium black calcareous

North Saurastra 400-‐700 groundnut, cotton, wheat, bajra, jowar,

sugar

shallow, medium black

Northwest 250-‐500 cotton, jowar, groundnut, bajra,

wheat

sandy and salty

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Fig. xx: Agroclimate zones of Gujarat (Source: Maps of India.com)

Out of the eight agro-‐climate zones of Gujarat, the CCAFS team selected 3 zones for its investigation: North Gujarat (Ahmedabad district), Middle Gujarat (Kheda district) and Southern Gujarat (Bharuch district). In each zone, one village was randomly chosen to conduct the survey, respectively Arnej (Ahmedabad), Dharampura (Kheda) and Nikora (Bharuch).

Large distances and the short time available to the CCAFS evaluation team precluded sampling to the remaining regions of the state, i.e. the dry and cold zones. However sampling in the other states captures perspectives from farmers operating in most of the agroclimate features left out.

In total, 77 farmers participated in the appraisal in the state of Gujarat, of which 34 female and 43 male, characterized as follows:

State of Tamil Nadu – Respondent Characteristics Village Name Female Farmers Male Farmers Total N° of

Farmers surveyed

N° surveyed



N° surveyed



1. Arnej

9 17,3 0% 9

2. Dharampura

14 0,53 100% 15 1,95 29

60

3. Nikora

11 6,3 50% 28 10,8 35% 39

Total 34 8,043333333 50% 43 6,375 35% 77 *% non-‐OC surveyed: % Non Open Category, a measure of socio-‐economic marginalization in India; this includes Scheduled Castes (SC), Backward Castes (BC) and other Backward Castes (OBC).

In all villages surveyed, agriculture served as the primary source of livelihood. In Arnej however, agriculture is practiced only once a year during the dry season from November to April. In addition livestock (cow, buffaloes) provide supplementary support and livelihood. Male farmers also engaged in agricultural labour and other jobs around the village. Key crops across the villages were wheat, cotton, millet, sugarcane, potato, chick pea and banana. In two out of 3 villages, agriculture was based on tubewell irrigation. In Arnej, where dry season agriculture was practiced, agriculture was largely rainfed.


Across the three villages, farmers mentioned several parameters that they associated with the advisories, which influenced their decision-‐making. These were weather parameters such as rainfall and temperature forecasts, cloud cover and advisories on pest management and application of fertilizers.




• interactions with agricultural university or KVK staff at Dharampura, • local television channels, • and through AAS bulletins on the village notice board.


We found minimal levels of awareness of the AAS program among farmers surveyed in Gujarat. Across the three villages, about 30-‐40% male famers were aware about the AAS. In Arnej, though farmers knew about it they said that they have received it only once from the KVK but never again since. Women farmers in none of the villages were aware about the AAS. This is

61

arguably linked to their minimal involvement in agriculture. They are not part of any meetings, trainings or discussions with extension officers or agricultural scientists.


Perceptions on accuracy of AAS were low across the villages ranging from 25 percent to 60 percent amongst the farmers interviewed. In Nikora, male famers opined that since they only sow once a year when there is not much variation in weather, weekly advisories were not of much relevance. If at all, they added that forecasts were inaccurate and hence they rarely ever used advisories in decision-‐making. However, in interviews, farmers mentioned getting useful information on cotton crop from the Cotton Research Centre. In Dharampura, 50% of those who knew about the AAS said that the forecasts were not accurate at the village level and hence they were not very relevant.


Products delivered




Water deficiency is a crucial issue across all the villages. It primarily owes to lack of irrigation facility and depleted groundwater or saline water incursion. Monsoonal variability or poor rains in rainfall implies wells don’t recharge. The Narmada canal provides water but only for drinking purposes or for irrigation in a limited number of crops and few times in a season. Low rainfall is also associated with high pest incidence in crops. Advisories, farmers said, were useful in preparing their fields to adjust to variations in rainfall. However, farmers felt that inaccurate weather forecasts were also problematic and caused losses.

Farmers opined that advisories on pests and diseases were useful. However, they added that sometimes recommendations on pesticides were not successful since some pests became resistant to certain pesticides. Moreover, some of the recommended pesticides were not available in the local market thus forcing them to purchase what was available.


Male farmer from Dharmapura

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“Once rains were forecast, but I did not trust the advisory and still decided to harvest. It rained and my harvest was destroyed. Now if I know its going to rain, I harvest early”

Male farmer from Nikora

“Last year, my neighbouring farmer put something in his fields that resulted in a virus that started affecting my crop too. I took it to the Cotton Research Institute who recommended a certain type of medicine which helped to get rid of the virus”

Female farmer from Nikora

“Advisories on fertilizer application and pesticide application are very useful to me”


In all three villages, women didn’t participate much in agriculture. They were not much aware of AAS nor did they receive any AAS information directly and if at all, only through their husbands. They were also not invited for agricultural trainings, meetings or discussions and felt that special efforts needed to be taken to include them in trainings and in information dissemination channels.

Additionally, Political divisions were rife in one of the villages. Therein, the current Sarpanch (Head of the village) was found to be part of a political faction, which is different from the previous one. Thus the village was divided into two groups, and when meetings are arranged in the village, if one group came the other stayed out of it. This has created problems of uneven dissemination in the village with asymmetry in access and use of advisories.

4.6.5 Conclusions: Lessons Learnt & Best practices from the State of Gujarat


Across all three villages, farmers shared that they largely rely on traditional knowledge and customs as well as personal experience to inform their agricultural decisions.

A handful of women surveyed in Arnej noted adjusting sowing dates and select cultural operations such fertilizer application, weeding etc. based on information from agricultural university. However, a review of the socio-‐economic status of surveyed women in Arnej demonstrates their high socio-‐economic status, large land oznership and assumed access to knowledge. Moreover, farmers in Nikora mentioned contacting the Cotton Research Institute for pests and pesticide application in cotton crop.

Why was use of AAS so poor among surveyed farmers in Gujarat?

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From Gujarat, we learnt that for agromet advisories to be used by farmers and useful to support farmer decision making, they need to:

-‐ Be salient to local agroclimate and farmer needs -‐ Be Inlusive of all sections of the community, including women and other marginalized

subgroups, and transcend political and caste divisions. Participation of the latter groups during village agromet discussions / training needs to become a priority.

Farmer recommendations for improvement of the AAS Program in Gujarat



1. Higher resolution forecasts, particularly rainfall.

2. Information on alternate crops, particularly during drought years or poor rains which are sustainable.

3. Information on market price of produce.

4. Help with dealing with wild animals, particularly wild boars that attack crops and farmers.

6. Sharing of new research in agriculture, especially recommendations in new technology and equipment.

1. More village level trainings with farmers

2. Detailed advisories on local TV channels

3. AAS through mobile phones

4. Special trainings for women in villages

Agrometeorological advisories need to:

• Be salient to local agroclimate features in order to support farm decisions

• Be Inclusive of all sections of the community, including women and other marginalized subgroups, and transcend political and caste divisions. Participation of the latter groups during village agromet discussions / training needs to become a priority.

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V. DISCUSSION OF RESULTS: All-‐India Appraisal of the AAS Program

BACKGROUND

Main Livelihoods

Amongst all the states surveyed, agriculture was the main source of livelihood and practiced through out the year except in Arnej, Gujarat, where agriculture is done only once during the dry season from November to April, right after the monsoon and harvest in March – April. In addition to agriculture, livestock in the form of cows, buffaloes, bulls, goat, sheep, and chicken, provide support and supplementary resources such as milk, meat, manure, and draught power.

Apart from this, several farmers also engaged in other occupations either seasonally or yearly for supplementary income, such as day labour or jobs in nearby towns and villages, local businesses (stitching and tailoring for women in particular) and NREGA.

Key crops

While it is difficult to rank key crops across all villages, one can identify major crops that are more common than others and other crops which serve as key in specific regions. The more common crops across the 6 states are wheat, paddy, maize, cotton, mustard, sugarcane, millets and a variety of vegetables. The more region specific crops are betel leaves in Prasadpur (West Bengal) tea in Melchowhutty (Tamil Nadu), and horticulture in Chong (Himachal Pradesh) consisting of primarily apple, followed by pears, plums, peaches, apricot and pomegranate.

Primary water resources

In ten out of eighteen villages surveyed, agriculture was predominantly rainfed. This was particularly so in Andhra Pradesh and Tamil Nadu where groundwater was in less supply, and less so in the other states were some form of irrigation (canals, check dams and groundwater) did exist.

Role of women in agriculture -‐ In two out of the six states surveyed – namely Himachal Pradesh and Andhra Pradesh, women continue to play a significant role in agriculture. In other states, women participated in agriculture to a much lower extent or not at all. What is interesting it to note that across all states, women farmers who played a larger role in agriculture also displayed higher awareness about the AAS. In villages where this was so, it was also observed that overall awareness of AAS was higher owing to greater women’s participation in the process of information dissemination and use.

Overall constraints in agriculture

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Across all the states, shortage of water was the top most cited and perceived constraint in agriculture, the predominant reason being erratic and irregular monsoon rains and poor irrigation facilities.

The team however had good reason to believe the citing of water shortage as the chief constraint may well be associated with the delayed monsoon in India, at the time of field work, which was already beginning to affect water availability and by extension, crop sowing times, choice of crops, and other significant decisions for the season.

Irregular and erratic rainfall was indicated as associated with several problems. Delayed rainfall (particularly during SW monsoon) led to reduced water for land preparation, delayed sowing, or on certain occasions completely abandoning staple crops for alternative options or simply leaving the field fallow. Extended interruptions in rainfall also led to poor irrigation, and poor crop quality. Erratic rainfall was also linked with wastage of fertilizers and pesticides, particularly if rainfall event followed an application resulting in washing away of chemicals. Unanticipated rainfall during harvest time (October-‐November), particularly in rice and wheat also posed risk for harvested grains and their rotting and germination. Finally, excess rainfall proved challenging for water drainage from the fields with risk of water logging in fields and rotting of crops.

Mitigation in these cases was often post-‐event unless farmers rely on advisories and advisories themselves prove accurate in predicting such events. Post-‐event mitigation included tapping into groundwater resources in case of low or delayed rainfall (this was not possible in regions where groundwater levels were already depleted such as in Gujarat or turns saline as one goes deeper like in West Bengal. In case of rains during harvest, most farmers held that there was significant risk of damage to harvested crop unless it is transported away to storage facilities fast enough, or put out to dry.

Following water shortages, pests and diseases was mentioned as the second most important constraint in agriculture across all states. Reasons for heavy pest and disease incidence were associated with weather parameters, foremost being rainfall, temperature and humidity. Examples include ‘angari’ disease in betel leaves during monsoon time (Prasadpur, West Bengal); thrifts in bitter gourd due to irregular rainfall (Chandamari, West Bengal); insects in mustard during winter (Keshpur, West Bengal); potato disease due to heavy fog in winter (Keshpur, West Bengal); looper pest in beans due to sudden temperature increases (Melchowhutty, Tamil Nadu); blight disease in tea leaves due to sudden increases in temperature (Melchowhutty, Tamil Nadu); sheath blight in onion due to frost (Vadavattur, Tamil Nadu); untimely frost in April destroys apple flowers and reduces fruit formation.

Other important constraints mentioned were wild animal attacks (wild boars, wild cows), low profits due to high input costs and decreasing market rates from selling agriculture produce, and labour issues.

In the case of both rainfall variations and pest and disease constraints, farmers often got into heavy debts due to loss of crop, low yields, or when they borrow to re-‐sow their lands. In

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particularly drought-‐ridden years, they look for alternate sources of employment and income. Pest and diseases call for higher investment in pesticides and add further to cost of produce without any equivalent increase in price of produce in the market, which leads to low profits, sometimes not even enough to cover input costs and save for the following seasons’ cultivation.

The two chief constraints being associated with weather parameters thus make evident the potential and scope for weather based agro-‐advisories to influence agricultural decision making, but more importantly mitigate constraints and improve management of limited resources. In several cases, farmers disclosed that early forecasting of rainfall event, or variations in rainfall and other weather indicators helped to better prepare and manage potential losses associated with weather issues and pests and diseases.

Factors influencing farm-‐based decision-‐making amongst farmers

In four out of the 6 states surveyed – namely, Himachal Pradesh, Punjab, West Bengal, and Gujarat – farmers disclosed that they predominantly rely on personal experience, traditional framing practices, lunar calendar and traditional agricultural festivals as indicators for farm-‐based decision-‐making. In some cases they added that they received information on advisories from the agricultural university (this was usually in the village at closest geographical proximity to the agricultural university), while some also mentioned referring to the agricultural calendars that they received during Kisan Melas (Farmer Fairs) in their village (Punjab). While radio and TV were mentioned as a source of information on weather forecasts, these farmers observed were not very specific to their village and hence not helpful.

In Andhra Pradesh and Tamil Nadu, famers expressed considerable confidence in AAS. In Andhra Pradesh, farmers noted that since the last 2 years with better communication of advisories in their villages, they were increasingly relying exclusively upon AAS to take decisions. In Tamil Nadu, farmers added that they regularly used AAS to determine sowing time, pesticide and fertilizer application and harvesting time (Kannivadi, TN). In Vadavattur, livestock farmers observed that advisories had been very useful for them to decide on livestock management and they relied upon it often.

In three out of six states – namely Himachal Pradesh, Andhra Pradesh and Tamil Nadu – farmers ranked advisories and related support from the agricultural university/research station or local NGO/extension institution like the KVK, high on the list of agricultural support services they received. In two cases (HP and TN) it was top most. In the other three states, farmers did not declare any support services as preferential.

OVERALL AAS PROGRAM IMPACT & RELEVANCE FROM FARMER PERSPECTIVE – ALL INDIA

This section draws from interviews conducted with male and female farmers across the six states selected. The village’s chosen for site visits in each state were based on the need to make the survey geographically varied and yet adequately representative. However, contextual

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variations at the village-‐level owing to various social, political and economic factors as well as presence and absence of interventions by local and international organizations indeed rules out expectations of evenness or similarities amongst villages. The results presented here are intended to capture some salient aspects of the AAS intervention from farmers’ perspectives and needs to be treated more as an indication of diversity rather than aiming to be exhaustive.

I. Farmer Awareness

Farmers’ awareness in all states was based upon their knowledge about AAS. While in some cases, farmers may be aware and may use the services to greater or lesser extent, there may be a few cases where farmers may have heard about it once or twice, but since then have neither received it nor used it in their decision-‐making. Keeping this in mind, we find that across the 6 states, a total of 67% of farmers had some awareness about the AAS. Amongst this, men fared far better than women with 88 per cent awareness while only 49 per cent of all women farmers interviewed had any awareness of AAS. State-‐wise, male and female farmers in selected villages in Andhra Pradesh and Tamil Nadu were collectively more aware about AAS as compared to other states. In Punjab, while male farmers were as aware as in Andhra Pradesh and Tamil Nadu, women farmers had no knowledge about AAS. In these states, awareness amongst women was much higher than in other states. Moreover, in states where women’s participation in agriculture was higher (Andhra Pradesh, Tamil Nadu and Himachal Pradesh) the percentage of women who knew about the AAS was higher than in other states. In Punjab and Gujarat, while the percentage of male farmers who knew about the AAS was high, women farmers were woefully left out of dissemination channels. In both states, this coupled with negligible to no women participation in agriculture.

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State-‐wise AAS awareness amongst farmers (in %)

State-‐wise gender disaggregated AAS awareness amongst Farmers (in %)

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Himachal Pradesh


Tamil Nadu Gujarat

% Women Awareness % Male Awareness

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II. Use of AAS

Evidently, there is a clear distinction between farmers knowing about the AAS and farmers being able to use it for their purposes. To determine usability we have used specific instances of AAS use as well as affirmations by farmers about a change in behaviour and agricultural decision making during interviews. In all of the states, usability of AAS was lower than awareness of it. This could be attributable to a number of reasons including low access to information, irregular receipt of information, inability to apply the information to decision making, acknowledgement of low relevancy of AAS information in case of some farmers, and lack of trust in AAS. In several cases, “progressive farmers” (usually socio-‐economically better off farmers with medium to large land holdings and more resources to access and apply AAS information) were in a better position to access and use the advisories in their decision-‐making. Other reasons for low usability amongst farmers who knew about the AAS include –

1. Small size of land and scale of operations – Some small farmers observed that information from the advisory didn’t matter to them much and their traditional practices and experience were enough to manage their fields.

2. Poor access to advisories – In several cases, particularly that of women farmers, they could not use advisories to inform their decision making due to inability to read the advisories, lack of time to watch radio or television where advisories were relayed or low participation in dissemination activities including meetings and discussions in the village. In a few villages, sexist cultural norms prevented women farmers from participating or joining discussions and trainings which were solely attended by male farmers.

3. Low relevance -‐ Marginal farmers with low resources often found it difficult to follow the recommended doses of fertilizers or pesticides due to high costs or shortage of fertilizers in the local market.

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State-‐wise AAS awareness amongst farmers (in %)

Several factors come together to ensure that farmers are aware and are able to use AAS to inform their decision-‐making. Here we give a few important indications of what worked to increase awareness and use of AAS in the surveyed states -‐-‐

• Andhra Pradesh – In recent years improvements in channels of dissemination has played a big role in increasing awareness and use of advisories in the villages visited. Improved communications include regular (biweekly) display of AAS bulletin in prominent places in the village, announcements over the microphone, dissemination of advisories through local NGOs or through representatives of international projects. Farmers, particularly women farmers expressed satisfaction with increased ability to openly access information through NGO representatives in the village who visit often. Broadcast of AAS information over the microphone was also very helpful, especially for farmers who could not read the bulletins or required help to interpret them. Finally, appointment of local farmers from villages to manage and record data from manual weather stations in the village also goes a long way in making the process of information collection and dissemination more inclusive and open. It also increases discussions amongst farmers and spreads information through word of mouth.

• Tamil Nadu – Presence of local agriculture related organizations particularly MSSRF (M S Swaninathan Research Foundation) Knowledge Centre in villages (in Kannivadi for example) has increases both awareness and use of advisories. Presence of such an organization also helps to ensure regular dissemination of advisories. One of the women farmers has also been a volunteer for recording of weather data from the manual weather station in the village. Her role as key personnel in collection of weather data has improved awareness

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% Awareness of AAS % Use of AAS

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amongst other women. Her interaction with other women farmers in the village has created a great deal of enthusiasm amongst women farmers in the village about the usefulness of AAS and on further improvements in it. Regular trainings and discussions with the knowledge centre as well as scientists with agricultural university has also helped to improve comprehension and use of AAS. Specialized AAS -‐ In Vadavattur, advisories are focussed on livestock and developed by Veterinary Laboratory. They focus on the providing livestock related advisories based on weather forecasts and came out as extremely useful for livestock farmers.

• Himachal Pradesh -‐ In some villages (Chong and Amtrar) women played a much larger role in agriculture and had also been organized into community groups who often attended trainings in agricultural university, horticulture department, interacted with agrometeorologists and agricultural and horticultural scientists and received information on AAS directly. These women’s groups were useful to gather important information and disseminate it in their village through discussions and word of mouth. They have also been useful to increase trust in advisories by encouraging use and showcasing benefits through personal experience. In addition, advisories and agricultural related information that farmers received from the agricultural university and trainings at Horticulture research centre came out as most pertinent and useful. Kissan Mela’s (Farmers Fairs) and block level meetings with agricultural experts were also mentioned as particularly favourable in receiving information on type and quality of seeds and other related matters.

• Punjab -‐ In some villages (Panglian and Mehma Sarja) progressive farmers received the AAS information regularly through their initiative and were able to benefit from it. They had better access to it due to their connections with AMFUs or extension officers and resources such as internet and phone access. Progressive farmers also helped organize trainings in the village with other farmers to disseminate information about AAS and regarding its uses. This greatly helped in improving awareness and usability. Moreover, in case of special projects in a village, such as the ‘Climate Change’ project in Achalpur, those associated with it were also exposed to AAS information and how to use it to inform their decision-‐making.

• West Bengal -‐ Farmers here emphasized seminars and discussions with scientists from Agricultural University, Agromet Field Units (AMFUs) and information channels through local NGOs (Ramakrishna Mission) as very useful. In some villages women mentioned receiving information through womens’ self help groups. Improved awareness was also due to increased discussions amongst farmers in village teashops as was noted by farmers.

• Gujarat – Farmers perceived dissemination of AAS through Agriculture University extension

officers as an important and useful communication channel. In addition, farmers also receive specific information through personal contacts with the Cotton Research Institute, particularly for pests and pesticide application in cotton crop.

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III. Skill and Relevance of AAS

Perceptions about accuracy and relevance of AAS across all states varied depending upon a number of factors. While farmers in various villages remarked on the need for higher resolution forecasts, more accuracy in predictions, as well as longer lead-‐times, perceptions on accuracy and relevance seem to have a lot to do with how much of AAS information is available to farmers and influences their decision-‐making. From the data, it is revealing that villages where accuracy and skill level perceptions of AAS were higher were also where awareness and usability of AAS was high amongst male and female farmers. This came out as particularly true in villages where farmers had asserted that they received AAS information regularly and on time, there were fewer gaps in information, they trusted the information more and they were able to better interpret advisories and use it to inform their decision-‐making.

Farmer perceived skill and relevance of AAS across States

• Andhra Pradesh – Across all the villages perceived skill level and reliability of forecasts ranged from 60% to 90% for eighty percent of farmers (male and female farmers together) interviewed. About 80% of farmers said that they refer to the advisories more often now than 2 years ago because of greater access to it and also increased understanding of its relevance to their decision-‐making. AAS program ranked number 2 in list of agricultural support services, with crop compensation schemes and reduction on crop loan interests at the top. In all the three villages farmers, particularly women farmers said that they found rainfall forecasts as most crucial to their decision-‐making. Farmers felt that for the most part the information was received in good time, either the day before or the morning when they were going to take decisions.

• Tamil Nadu – Accuracy of AAS was perceived by farmers anywhere from 50-‐90 per cent across all the villages surveyed. Skill and accuracy was perceived higher by male farmers than by female farmers, though in Kannivadi, both male and female farmers found the AAS highly reliable. In all three villages, farmers ranked agro-‐advisories and agricultural information that they received from local institutions or extension services as topmost amongst agricultural support services. For the most part, farmers across the board said the lead-‐time was sufficient to carry out operations. But they also added that it would be better to lengthen lead-‐time by a week to 10 days.

• Himachal Pradesh – Male farmers in Amtrar perceived advisories anywhere from 50-‐90% accurate, where as female farmers found it more relevant and almost 100% accurate. Women farmers also found AAS more accurate (50-‐95%) and useful than male farmers in Chong village. In Bhanjal, however farmers felt that the advisories, particularly the forecasts fared very badly. They pegged the accuracy of forecasts at around 50% adding that forecasts they heard on radio for Punjab state were more relevant to them. Rainfall variability and irregularity ranked high in climate related risks and thus rainfall forecasts both during monsoon season (June – October) and during winter months (January – April) were important parameters in influencing decisions.

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• Punjab – Farmers pegged the accuracy of forecasts anywhere from 20% -‐ 90%, with higher accuracy levels in Mehma Sarja and Achalpur. In Mehma Sarja, male farmers added that they received the advisories at appropriate times, especially during harvesting and sowing time where weather information was crucial in decision making. In Panglian, male farmers found information on pests and also diseases in livestock and medicine important and useful. In Mehma Sarja and Achalpur male farmers felt that advisories were very useful and relevant. 90% said they followed the advice regularly.

• West Bengal -‐ Across the 3 villages, the accuracy of the forecasts from FGDs and interviews

was pegged low from anywhere between 10 and 60%. About 80% of farmers across all the 3 villages expressed dissatisfaction with the advisories. They said that they didn’t find the advisories very relevant and don’t use the advisories. They added that they don’t trust the forecasts enough to use them. Women in Keshpur said that they found the advisories useful but did not find the forecasts accurate. They noted that advisories on transplantation technique and seed quality was also very helpful. Farmers divulged that while pesticide information in advisories were very important, more often than not they had to rely on different pesticides available in the local market due to unavailability of recommended pesticides in the market. In terms of timeliness, 60% of farmers across the 3 villages said they needed the forecasts atleast a week in advance.

• Gujarat – Perceptions on accuracy of AAS were low across the villages ranging from 25

percent to 60 percent amongst the farmers interviewed. In Nikora, male famers opined that since they only sow once a year when there is not much variation in weather, weekly advisories were not of much relevance. If at all, they added that forecasts were inaccurate and hence they rarely ever used advisories in decision-‐making. However, in interviews, farmers mentioned getting useful information on cotton crop from the Cotton Research Centre. In Dharampura, 50% of those who knew about the AAS said that the forecasts were not accurate at the village level and hence they were not very relevant.

Perceptions about accuracy and relevance of AAS across all states varied depending upon a number of factors. While farmers in various villages remarked on the need for higher resolution forecasts and more accuracy in predictions, perceptions on accuracy seem to have a lot to do with how much of the information is available to farmers and influences their decision-‐making. From the data, it is revealing that villages where accuracy and skill level perceptions of AAS were higher, awareness and usability of AAS was high amongst male and female farmers. This came out as particularly true in villages where farmers had asserted that they received AAS information regularly and on time, there were fewer gaps in information, they trusted the information more and they were able to better interpret advisories and use it to inform their decision-‐making.

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IV. Channels of Communication

Across the six states, farmers commonly mentioned the following channels through which they received AAS information. These are summarized as follows:

• Farmer meetings with agro-‐met scientists/extension officers from agricultural university (or AMFUs) or related institutions like KVK or research centres. These meetings and discussions are preferred when done in the villages, but some farmers also take the initiative to contact key personnel from these institutions for specific information.

• Through local NGOs working in the village on agricultural related issues who help disseminate the advisories.

• AAS bulletins distributed in the village or displayed on notice board in key locations in the village.

• Kisan Melas (Farmer Fairs) organized in the village • Media – Newspapers, Radio and Television • Voice messages and SMS

Challenges in dissemination

1. On some occasions farmers divulged that extension officers from KVK or agricultural university tended to hold meetings and impart information with a few select farmers in a village, while a majority remained outside the information circuit (Bhanjal, HP; Panglian and Mehma Sarja, Punjab; Chandamari and Prasadpur, West Bengal). This was also the case when information was based on membership to farmers’ clubs (Baironpalli, AP) or through a certain experimental project, where only those associated with such clubs or projects had easier access to the information.

2. In some cases, women farmers felt radio and TV were not enough since they never found time to listen/watch it and hence missed out on programs (Amtrar, HP)

3. While SMS services and voice mails were popular, in some cases network problems have prevented them from making a big impact (Kannivadi, Tamil Nadu)

4. For farmers who are unable to read, AAS bulletins on display in the village was not of help. Farmers also mentioned that even when they knew how to read the information, they found it hard to comprehend it due to the heavy technical language.

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V. Farmer Recommendations

Additional information sought through AAS Suggestions on communication channels

• Water management, especially during times of shortage • New varieties of seeds; also on why certain seeds failed

and how to prevent it. • Wind speed to help decide time for spraying of pesticide,

weedicide and fungicide • Determining harvest time for specific crops • Dealing with sudden frost in winter • Information on market prices of produce • Information on mechanization possibilities on the farm • Crop related information related to protecting crop

during sudden variations in temperature • Information on better fertilizer mix • Soil nutrient management strategies • Choice of alternative crops during delays or breaks in

rains. • Information on new pests expected in each season and

suitable pesticides • Information on organic farming. At the moment the

advice is tailored to conventional chemical based farming and therefore some farmers want to know how to switch to organic farming. Those already on organic farming want more information tailored to it in the AAS.

• On new mechanization techniques to reduce cost of cultivation, new machines for harvesting and sowing seeds.

• Information related to cold storage facilities • Help with dealing with wild animals, particularly wild

boars that attack crops and farmers. • Sharing of new research in agriculture

• Advisories through cell phones (voice mails and

text messages) • Elaborate advisories through television channels

in addition to state level forecasts currently relayed

• Flash news on all channels on important weather events

• Printed advisory bulletins displayed in all central points in the village accessible to all (temples, bulletin boards, shops, milk collection booths etc)

• Specific trainings and discussions on AAS for women farmers in the village

• Organizing farmers into Kisan groups (Farmers’ Group) to attend meetings with AMFUs and help disseminate vital information in the village.

• Larger farmer role in dissemination activities through appointment of village level volunteers who could receive biweekly advisories from AMFUs and communicate them to the rest of the village.

• Regular trainings and interactions in the village with scientists that all farmers can attend

• A toll free number (call centre) for agromet advice that farmers can call on for information and clarifications.

• Use of pictures in textual advisories to make them more comprehensible

• Use of less technical language in advisories for easy interpretation

• Mobile phone application for AAS related information

• Specific FM radio station for weather based agro and livestock advisories.

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VI. Summary of Lessons Learnt: All-‐India Appraisal of the AAS Program

6.1. Best practices in provision of AAS in India Cross-‐state aggregate analysis: what worked in provision of agro-‐met advisories? What did not work? Under which specific contexts?

Summary of Farmer recommendations for improvement of the AAS Program (Table)

State Additional information sought through AAS

Additional needs Lessons Learnt/ Suggested Best practices for Scaling up

AP 1. On alternate crop choices, especially during shortage or delay or rains.




• A Go-‐to Met person at the village level

• Broadcast of AAS advisories on the microphone:

• Display of bulletins in prominent places in the village

• Collaboration with local NGO to make AAS program more useful for farmers

HP 1. On water management, especially during times of shortage

2. Access to good quality seeds




• Trainings and discussions in villages as superior forms of dissemination channels.

• Local downscaling and value-‐addition is paramount to ensure salience to local farmer needs and usability by farmers.

Punjab 1. Information on new 1. Display textual copies • Use of an NGO or local

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varieties of seeds; also on why certain seeds failed and how to prevent it.







of advisories in prominent locations in the village such as the Gurudwara (Sikh temple). Common areas also ensure information is evenly disseminated and not restricted to few factions or privileged sections.






project to promote the use of advisories serves to increase reach and appropriation of available agromet advisories, and indent its use in local practice (lesson from Achal pur)

• For smallholder farmers with farm sizes of less than an acre, agromet advisories are not of much relevance due to the small scale of operations.

West Bengal

1. Crop related information – for example, advance advisories on how to protect cauliflower crop


2. Door to door information through an

• Face-‐to-‐face meetings and discussions in the village with agricultural experts that all farmers can attend

Wide community mobilization and

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during higher than average temperatures in winter.




appointed volunteer in the village

3. Newspapers




inclusion of all farmers within the community (not only male farmers of high socio-‐economic status) is critical during village discussions by Agricultural experts to ensure widespread appropriation and use of AAS advisories.

• Use of local NGOs instrumental to widely mobilize community towards use of agricultural information.

Tamil Nadu




4. On new mechanization tecniques-‐ In the past farmers grew ragi, wheat, and other cereals. Now





6. Specific FM radio station for weather based agro and livestock

• Smallholder farmers can be successfully reached with agromet information using a diversity of communication channels (extension, local knowledge center/hub, face-‐to-‐face village meetings and trainings by agricultural experts, SMS and voice messages,..

Designing a tailor-‐made fleet of communication solutions is what it takes to reach remote smallholder farmers at scale;

• Presence of a local agromet knowledge center/hub (the MSSRF Knowledge Centre at the village) improved access and usability of AAS advisories;

• SMS based dissemination and phone calls are effective preferred

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they don’t, because of labour shortage. Famers wants to find out about machines for harvesting and for sowing seeds.


advisories.


channels to reach farmers. For those who cannot read advisories, voice messages on the phone are preferred.

• Local downscaling and improved resolution of the rainfall forecasts is paramount to ensure salience to local farmer needs and usability by farmers.

Gujarat 1. Higher resolution forecasts, particularly rainfall.









Agrometeorological advisories need to:

• Be salient to local agroclimate features in order to support farm decisions

• Be Inclusive of all sections of the community, including women and other marginalized subgroups, and transcend political and caste divisions. Participation of the latter groups during village agromet discussions / training needs to become a priority.

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6.2 Challenges and Opportunities with AAS to support smallholder farmers agricultural decision-‐making Cross-‐state aggregate analysis: Challenges and Opportunities in the provision of salient farmer-‐focused climate services in India


Constraints encountered in Agriculture

Climate/Agricultural Information provided

Decision-‐making process supported by agro-‐met Information

Uses made of information by surveyed Farmers-‐ Farmer testimonies

Constraint #1: Rainfall Variability / erraticity

(came up in all states)

Short-‐range rainfall forecasts

• Crucial for determining sowing operations in monsoon months: especially if showers on a day were followed by a long drought stretch during the monsoon month. Bulletin also gave the exact data on the quantity (mm) of rainfall, which helped farmers judge whether soil moisture was good enough for sowing operations after a rainfall event.

• Important for managing harvest operations which often face risks from excess rainfall during harvesting time (January – March) that destroy harvested crop (AP, HP): Farmers felt that getting rain forecasts during these months helped to determine the right harvest time and evade crop

Female farmer from AP: “Three years ago, I found out from a weekly advisory that rain was forecast and transplantation of paddy was recommended. I followed the advice and reaped a good crop. Farmers who did not follow the recommendation, delayed transplantation by 15-‐20 days and had lesser yields”

Male farmer from Amtrar, Himachal Pradesh : “Three years ago, I found out from a weekly advisory that rain was forecast and transplantation of paddy was recommended. I followed the advice and reaped a good crop. Farmers who did not follow the recommendation were delayed transplantation

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losses. by 15-‐20 days and had lesser yields”

Male farmer from Amtrar, Himachal Pradesh: “Two years ago, the advisory recommended delaying harvesting of wheat crop based on heavy rainfall forecast. I did so and saved my crop. If I had harvested, then heavy rains would have destroyed the harvested grains left in the field”

Male farmer from Vadavattur, Tamil Nadu: “The advisories are useful for livestock management. I learnt that we should allow the animals to graze immediately after rainfall. I also rely on it for treating diseases in livestock”


(came up in all states)

Short range Rainfall forecasts

pest related information in advisories

• Earlier they used to use expensive and concentrated pesticides, which was destructive to crop yields as well as personal health. From the advisories, they learnt about using low concentration and low cost pesticides, which saved money by avoiding wastage and also improved health

• Timing of pesticide application: since rains

Male farmer from AP: “I have less land. I used to apply DAP fertilizer every 30 days. Then I started listening to the forecasts and advisories, which said that it should be applied every 15-‐20 days. Since then, I have been able to increase yields in cotton by 4 quintals/acre.

Male farmer from Kannivadi, Tamil Nadu: “I use the wind speed and direction forecast

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right after an application would wash it all away. Now, farmers used rainfall forecasts to plan pesticide application.

to inform pesticide spray and to provide structural support for crops. I also use rainfall forecasts to determine when to harvest”


(came up for hilly temperate climate zones)

sudden changes in temperature, especially in the high altitudes

Temperature related forecasts

• Helped farmers to know in advance how temperatures were going to vary in order to take mitigating measures such as lighting fires around orchards to increase temperatures when cold onset was indicated

Constraint #4: Difficult Irrigation planning

Due to erratic supply and shortages in electricity + rainfall variability/erraticity

Advisories providing information on laser levelling

• Helps farmers determine the optimal level of irrigation in a given field, thus aiding better management of irrigation.

Constraint #5: Limited traditional knowledge to cope with new threats / old constraints to Agricultural output

Training and advisories on new agricultural techniques to use

Putting the outputs of Agricultural research in the hands of farmers

• Helps farmers gain access to the outputs of frontier agricultural research, and test/put in practice new techniques, fruit of modern agricultural research, to overcome constraints encountered in their agriculture.

Male farmer from Mehma Sarja, Punjab: “I learnt about new cotton seeds through the advisories. I tried them and harvested a good crop with it”

Female farmer from AP: “Earlier we used to spray fertilizers all over and a lot used to get wasted. We knew that, but still we did it since it was the easiest thing to do. But we learnt from the advisories that by spraying, not

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only is fertilizer wasted, but also yield is less. It recommended crop based application of fertilizers where quantity of fertilizer is less, but yield is more. Another thing is, fertilizer spraying could be done only by men, because the equipment used for spraying was heavy. With crop based application on the other hand, women can do it too, so I find it beneficial”

Female farmer from Amtrar, Himachal Pradesh: “Through the meetings with agricultural experts I learnt how to protect my cucumber crops. I got an apparatus which traps the flies that sit on the plant and destroy it. I have been using it for 5 months now and it has been very helpful in preventing fly attacks”

Male farmer from AP: “In vegetables, the advisories informed us to use vermicompost. I did so, and was able to increase yields by 5-‐6 bags (50 kgs. per

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bag). This started 4 years back”

Female farmer in Amtrar, Himachal Pradesh: “I got to know about vermicomposting through the advisories. I started using it on my onion crop and found the yield to be higher and the quality of onions also improved”

Female farmer from Chong, Himachal Pradesh: “My cabbage crop used to get infected with diseases. I used to spray pesticides but to no avail. I learnt from trainings that I should spray the pesticides at evening, instead of afternoon and then they become much more effective”

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VII. CONCLUSIONS & POLICY RECOMMENDATIONS

7.1. Summary of Lessons Learnt/ Scalable Best Practices

Ø Himachal Pradesh:

From HP, we learnt the following:

-‐ When women farmers are fully engaged, the appropriation and use of AAS is maximal (lesson from Amtrar village);

-‐ Trainings and discussions in villages are the superior forms of dissemination channels: regular trainings at the horticulture department of the university for Amtrar farmers proved critical. When there is sustained Interaction between farmers and agrometeorologists, agricultural and horticultural scientists, high use of advisories ensues;

-‐ Advisories need to be locally salient. Indeed, even within a state, high agroclimate differences are high. This was evident between Palampur Agricultural University (knowledge hub of AAS advisory generation) and the remote low hill parts of Una districts (closest to Punjab in terms of agro-‐climate features) where surveyed Una district farmers did not find provided agro-‐met advisories accurate at all nor salient to their local decision-‐making under a variable climate. As such, local downscaling and value-‐addition is paramount to ensure salience to local farmer needs and usability by farmers.

-‐ Information is not enough: Farmers need to be provided with accompanying agricultural measures to ensure use of AAS advisories. These include: Facilitate access to good quality seeds

Ø PUNJAB

From Punjab, we learnt the following:

-‐ Use of an NGO or local project to promote the use of advisories serves to increase reach and appropriation of available agromet advisories, and indent its use in local practice (lesson from Achal pur). In the case of the ‘Climate Change’ project in Achalpur, those associated with it were more likely to know about the advisories and benefit from it than those who were not part of the project, thus creating information asymmetries.

-‐ For smallholder farmers with farm sizes of less than an acre, agromet advisories are not of much relevance due to the small scale of operations.

Ø WEST BENGAL:

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From WB, we learnt that wide inclusion is fundamental in the endeavor to provide salient advisories to remote farmers. Agrometeorological advisories will not generate impact nor be useful until ALL farmers are included in the AAS outrach efforts. Notably:

-‐ Village discussions/trainings on Agromet advisories is a good strategy to increase the reach of advisories. However, Wide community mobilization and inclusion of all farmers within the community (not only male farmers of high socio-‐economic status) is critical during village discussions by Agricultural experts to ensure widespread appropriation and use of AAS advisories. This is a critical strategy to avoid a situation where the majority is left out and only those who are closely associated with the knowledge providers (agrometeorological experts at the Agricultural University, etc.) and those who are part of experimental projects receive most of the information from AAS and in a position to use the information appropriately

-‐ Use of local NGOs is instrumental in this regard to widely mobilize community towards use of agricultural information.

Ø TAMIL NADU:

From TN, we learnt the following:

-‐ Smallholder farmers can be successfully reached with agromet information using a diversity of communication channels (extension, local knowledge center, face-‐to-‐face village meetings and trainings by agricultural experts, SMS and voice messages, …). Designing and harnessing the power of a tailor-‐made fleet of communication solutions is what it takes to reach remote smallholder farmers at scale;

-‐ Presence of a local agrometeorological knowledge center (the MSSRF Knowledge Centre at the village) improved access and usability of AAS advisories;

-‐ SMS based dissemination and phone calls are effective preferred channels to reach farmers. For those who cannot read advisories, voice messages on the phone are preferred.

Ø Gujarat:

6.2 CCAFS Team Recommendations

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The AAS aims to reach 10 million farmers by 2012. To meet this ambitious aim, AAS Progam directors we’ll need to proceed through the steps outline below. This is what farmers are saying. May their perspectives serve to guide the next steps of AAS development in India, and beyond.

Ø In Andhra Pradesh: -‐ Provide additional farmer requested information, notably:

1. On alternate crop choices, especially during shortage or delay or rains.


-‐ Information is not enough: Provide needed accompanying agricultural measures to ensure use of AAS advisories: Facilitate access to good quality seeds

-‐ Diversify and multiply communication channels, as follows:



-‐ Move away from the model of membership in a farmers’ clubs (currently main outlet for transmission of agromet advisories), this is remains a barrier to women and other socially marginalized groups’ access to agromet advisories and climate information.

-‐ Transition towards More widely reachable means of communication –such as displaying the bulletin in prominent places in the village and broadcasting of the forecast/advisory over the microphone– will have to be privileged. Improved communication channels improves usability amongst farmers. Farmers in a surveyed village of AP (Baironpalli) added that they tend to exclusively rely on AAS now instead of going by their traditional practices to inform farm-‐based activities. The use of such democratic means of communication in AP has rendered The AAS program number 2 in a list of agricultural support services, with crop compensation schemes and reduction on crop loan interests at the top.

-‐ Encourage Collaboration with local NGO to make AAS program more useful for farmers and increase penetration / access.

-‐ Encourage the presence of Go-‐to met representative / ressourc eperson at the village level

Ø In Himachal Pradesh: -‐ Provide additional farmer requested information, notably on water management,

especially during times of shortage -‐ Information is not enough: Provide needed accompanying agricultural measures to

ensure use of AAS advisories: Facilitate access to good quality seeds

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Ø In Punjab: -‐ Provide additional farmer requested information, to make AAS advisories salient to

meet their needs:

1. Information on new varieties of seeds; also on why certain seeds failed and how to prevent it.







-‐ Make use of NGOs and local ongoing projects to increase the reach and appropriation of available AAS advisories;


1. Display textual copies of advisories in prominent locations in the village such as the Gurudwara (Sikh temple). Common areas also ensure information is evenly disseminated and not restricted to few factions or privileged sections.






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Ø In West Bengal: -‐ Provide additional farmer requested information, to make AAS advisories salient to

meet their needs:

1. Crop related information – for example, advance advisories on how to protect cauliflower crop during higher than average temperatures in winter.




-‐ Make use of NGOs and local ongoing projects to increase the reach and appropriation of available AAS advisories;



2. Door to door information through an appointed volunteer in the village

3. Newspapers




Ø In TAMIL NADU: -‐ Provide additional farmer requested information, as follows:




4. On new mechanization techniques-‐ In the past farmers grew ragi, wheat, and other cereals. Now they don’t, because of labour shortage. Famers wants to find out about new mechanization techniques, and have access to such machines.


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-‐ Information is not enough: Provide needed accompanying agricultural measures to ensure use of AAS advisories: Facilitate access to machinery for harvesting and for sowing seeds.






6. Specific FM radio station for weather based agro and livestock advisories.


Ø In Gujarat: -‐ Provide additional farmer requested information, notably on water management,

especially during times of shortage

1. Higher resolution forecasts, particularly rainfall.










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India Agrometeorological Advisory Service (AAS) Case Study

Independent Study of IMD’s AAS Program from a Farmer Perspective:

Views from the Frontline

METHODS BRIEF

Introduction

The Integrated Agrometeorology Advisory Services (AAS) is a project of the India Meteorological Department that aims to provide a variety of services to farmers including meteorological (weather observation and forecasting), agricultural advisories (identifying weather related stresses and providing advisories based on weather forecasts), extension services (two way communication with users), and information dissemination (through media and other local agencies). The project, which was integrated under the IMD in 2007, is being implemented through a five-‐tier structure that form different components in the service spectrum. Agro-‐met Advisory Bulletins are issued at the out to the state and district levels to cater to the needs from national to local scales.

To facilitate the design and implementation of similar programs in other countries, mostly in Africa, requires detailed information about the institutional context in which the project was set up and run, the scientific information used to inform the forecasts and other information conveyed to participant farmers, the ways in which this project has impacted farming practices related to local livelihoods, and how those impacts on farming practice came to pass. The proposed assessment addresses each of these needs independently. Data from the scientific and field assessments will be combined to determine the quality and utility of the information from the perspective of local-‐level farmer project participants, and the perception of impacts and changes in farmer behavior following utilization. The institutional assessment will be used to contextualize the products of the scientific/field assessment analysis for use by interested meteorological services across Africa.

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1. OBJECTIVES

A comprehensive understanding of the pathways through which this project has come to impact the lives of participants is beyond the scope and added value of this evaluation. Such an effort would require village-‐level studies of individual farmer behavior and social networks, as well as a comprehensive effort to gauge both current agricultural production and measure it against some form of reconstructed production baseline. Besides, an assessment on the AAS program has already been conducted in 2008 by the National Center for Short Range Weather Forecasts (NCSRWF), with probing results on the economic added value of farmer-‐focused agro-‐meteorological advisories in India (c.f NCSRWF assessment report, 2008).

What we are aiming for is an independent study of IMD’s AAS program from a farmer perspective, collecting farmers’ perspectives on the products provided by the program (in terms of their legitimacy, credibility and equity) and impacts on farming practices and livelihoods. Insights from this study will hopefully inform future AAS plans, and be shared at a South – South workshop on farmer-‐focused climate services, due to be held in Arusha Tanzania in early November, 2012.

The expected outputs from this work will be an independent report to be shared ahead of the Arusha South – South workshop, as well as a number of academic journal publications in collaboration with colleagues in India from all participating institutions of this study.

2. METHODOLOGY

To facilitate the above output, we will conduct an assessment with three main components:

To facilitate the above output, we will conduct an assessment with three main components:

§ An Institutional Assessment § A Science Assessment § and a Field assessment.

Details on the methods that will be utilized under each component of this assessment are details in sub-‐sections below.

2.1. Institutional assessment

a. Developing a historical description of the program: National Level

A narrative describing the program should cover:

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• The origins, rationale, the problem that led to the program (derived from primary documents, including program and project documents, triangulated with key informant interviews). This should include the identification of the early champions that initiated the idea and implemented it, as well as those who carried the project forward (key informant interviews, triangulated where possible with a review of primary documents).

• The organizational flowchart and narrative, showing roles of key institutions, interactions among institutions, interactions across scales. It should cover the range of geographic scales, which ranges from village-‐level governance and process, up to regional and global climate providers (derived from key informant interviews, triangulated with primary documents where applicable).

• The various overlapping initiatives that contribute to/are affected by this program. It appears that multiple projects, with overlapping but different objectives, have contributed to what now appears to be a single program (derived from primary documents, triangulated with key informants and independent sources).

• A narrative timeline about how the program evolved. Key information we are seeking: o The start and end of project funding (from project documents, triangulated with key

informants where needed) § External funding § Government of Mali funding

o The key institutional and political decisions that shaped the project over time (from key informant interviews, triangulated with independent sources and primary documents).

§ This should be linked to funding shifts (or not) o Any high-‐profile meetings or other events in which this project/program was

highlighted (from primary documents, triangulated with key informant interviews) o Any changes in geographic coverage and numbers of farmers participating (from key

informants, triangulated with primary documents where they are available. This may also require triangulation with independent sources and the field-‐based component of the assessment)

§ This should be linked to funding shifts (or not) o Any history of evaluations of the project – who conducted them and why? (from key

informant interviews, to be triangulated with evaluation documents if possible).

• Descriptions of the clients/final end-‐users. How were target users for this project initially identified, and how has this group changed over time (i.e. location, scope, etc.)? How many participants are there now, and how has that number changed over time? Does the project target, or has it ever targeted, anyone else besides farmers? (derived from key informants unless primary documents are available)

• Specific products and services that are provided, and how these have evolved over time • Specific communication channels utilized to reach remote villages, and these have evolved

over the course of the project • Processes such as high-‐level planning, communication, monitoring and evaluation, response

to feedback from farmers and other end users.

Consulting primary sources of information (e.g., project or program documents, minutes of meetings where key decisions were made, interviews with current and past leaders/GTPA members), and triangulating with independent sources, should provide a solid historical description of the program.

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b. Identifying key institutional stakeholders: Project Institutional Setup from National to Local levels

A changing confluence of factors has shaped this project/program and its outcomes. Through key informant interviews, triangulated where necessary with independent sources and documents, we will explore the following factors that either or enable or constrain the current program in India, as a way to inform the experiences of other countries that saw less success in starting up similar programs:

Key questions we will be exploring are as follows:

-‐ Who does information flow from national to local levels, and back? Who are the key stakeholders?

o How do we go from Information to Advisories: is the Gap between weather and agricultural research bridged, from the national to the local levels?

o Are there any canals built-‐in to enable feedback from farmers back to IMD (two-‐way communication)?

Other related questions of interest we will be seeking answers are:

• The institutional and program mandates of the organizational actors relevant to this project, from national to local levels

• The character of the interactions among the institutions working on this program • The resources available to support this project (external grants, government funding, any

private sector investment, in-‐kind contributions of human resources) and changes in those resources over time.

• The character and quality of institutional processes such as design of products and services, targeting, monitoring an evaluation, and learning mechanisms to incorporate feedback.

• The flow of information, products, services, feedback, influence, etc., between regional institutions, national institutions and farm/village-‐level users.

• The quality and function of governance and accountability mechanisms at national and regional scales.

All of these factors, and perhaps others that will emerge through the key informant interviews, combined in different ways at different times to influence the success of the project/program, as well as limit its impact. Understanding how these factors and others were configured at different stages of the program, and how those configurations impacted the project, suggest an approach focused on impact pathways. This approach will focus on understanding the different stages of learning through which the program evolved, elaborating two things:

1) The changing causal chains of activities, outputs and outcomes through which this project/program has achieved its goals

2) The networks of evolving relationships between stakeholders (donors, implementing organizations, and ultimate beneficiaries) that shaped the outcomes of this project/program

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This approach will provide a framework for either describing the chain of factors that has allowed program outputs to lead to uptake and benefit down to the level of farmers and villages, or identifying gaps in implementing an intended or plausible impact pathway.

In India, this information will be integrated with the science assessment and the field assessment to develop a comprehensive picture of the functioning of this program. Results from this assessment will inform other countries’ development of similar programs seeking to provide farmer-‐focused climate services at the village-‐level.

v OUTCOME: Identifying key institutional factors that enable or constrain production, delivery, uptake, impact and sustainability of farmer-‐focused climate services.

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2.2. Science Assessment

List of Products delivered:

-‐ Hazards covered relevant for area? Any new emerging hazards? -‐ What products have had most added value to inform farming decisions at local level?

Any particular stories of behavioral change following reception of a forecast? -‐ Which forecast products are least useful? -‐ Constraints to forecast usability: communication?

Farmer Appraisal of the AAS program will be conducted based on the following Criteria of information services usefulness to decision-‐making at local level:

1. Credibility -‐ Skill level -‐ Confidence in information provided

2. Legitimacy: Giving Farmers a Voice in Information their Receive -‐ Trust -‐ Have a voice -‐ Relating IMD info with traditional forecasters

3. Salience to local needs -‐ Products -‐ Geographic scale -‐ Timing -‐ Translation into early action advisories -‐ Appropriate communication channels to reach remote rural community

4. Equity (gender) -‐ Access by socially marginal groups (does info reach the most vulnerable) -‐ Once information reaches community, who gets the info?

v OUTCOME:

-‐ Which climate services were useful? Which were not? Which institutional setup/communication channels were effective? How has the project impacted farming practices in participating villages? How has receiving weather advisories impacted lives and livelihoods?

-‐ Identification of GAPS between supply and demand -‐ Identification of obstacles to Scalability and Transferability

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2.3. Field assessment

The field assessment rests on qualitative and quantitative data gathering that will be conducted at village-‐level In each target sites selected, to understand which climate services work and why from a farmer perspective.

Figure 1: Project field methods as a daylong program

The assessment team will sample participating villages within a stratified sample of Agromet Advisory Units (AAUs) of different agro-‐climate features that controls for bias in program reach and local service. Each village will be subject to a one-‐day, intensive investigation by a team of four fieldworkers (see Figure 1 for an overview). Village visits will four focus groups, each run by one of the field team members. The focus groups will be stratified by gender and any other community stratification criteria deemed important to control for major social cleavages that might constrain the answers of community members. These focus groups will examine largely non-‐controversial issues related to livelihoods and agriculture in an effort to gain an understanding of baseline practices in the village (see discussion below). To avoid moving focus group participants toward “correct” answers, climate and climate information will NOT be raised directly by field team members in the focus group setting – if the topic emerges organically, it

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will be noted and followed by the field team member, but otherwise these groups will focus on understanding livelihoods and agriculture in the village. These focus groups will create a set of information on which to draw for interviews with key players in each focus group.

At the conclusion of each focus group, the field team member will identify 2-‐4 key participants in the focus group with which to follow up in one-‐on-‐one, semi-‐structured interviews. These interviews will explore issues of income and productivity in a setting that avoids forcing individual farmers to discuss such personal information in a group setting. Further, these interviews will probe for individual deviation from consensus views established in the focus groups. For example, while a focus group might produce a list of a few key crops/varieties grown in the village, an individual interview might identify new varieties not mentioned in the focus group. Such discrepancies can serve as productive starting points for deeper probing of livelihoods and agricultural practice that open pathways to discussion of agro-‐meteorological advisories provided by the AAS program. Away from other villagers and staff of the program, and with their anonymity protected, farmers will likely feel more comfortable telling evaluation staff what information they do and do not use to shape agricultural and livelihoods practice, how they use that information, and what information they want that they do not yet have.

The overall strategy of the field assessment in each village is to move toward explicit probing of the program’s impacts slowly and obliquely until the end of interviews, when the project is explicitly discussed in a context that will make “correct answers” easier to identify and move beyond in our evaluation (see Figure 2).

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Figure 2: Strategic approach for the field assessment

Site Selection Protocol

Sampling method: Stratified sampling based on an area map of India’s agro-‐climatic zones, superposed with map of AAS program participating states, AAUs and villages. This sampling will lead to the selection of five to six main sites across India that represent India’s main agro-‐climatic zones and production systems (Andhra Pradesh, Tamil Nadu, West Bengal, Himachal Pradesh, Punjab, Gujarat). Then participating villages within each state will be selected based on a stratified sample of AAUs within the state (for a maximum of 18 villages pan-‐India, with an average of 3 per site). Criteria for selection of villages within AAUs will have to be defined jointly with IMD. Overall, Villages selected across India for the purposes of this evaluation will need to provide an overall picture of the main agro-‐climatic zones and production systems in the country.

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At the most basic level, this assessment will interview project participating farmers and assess their perspectives on project outcomes and changes in agricultural practices, looking for the following differences from the baseline:

1) The preparation period before planting, including the timing of tillage 2) The choice of crops and varieties by farmers 3) The timing of sowing, thinning, weeding, fertilizer application and harvest 4) The amount of need for replanting due to crop failure 5) The amount of time needed in the fields to ensure an adequate harvest 6) The ability to use fertilizers and pesticides efficiently and effectively (from the perspective of

the farmer) 7) Expected and realized yields

The evaluation sampling strategy will control for several factors that might also impact these differences.

Village Surveying Protocol

-‐ Surveying technique: o 1 team/car to interview participating village o Constant reshuffling of team members across focus groups from village to

village target to minimize data collection bias -‐ Community surveys:

o 2 Focus groups: by gender; within groups: by age and farm size o Individual interviews with 2-‐4 farmers

-‐ Data translation -‐ Data analysis

Focus Groups

During the field assessment, teams will conduct focus groups, working with several groups of 5-‐6 people in each sampling zone. These groups will separately engage groups of male and female project participants. The advantages of focus groups are twofold. First, they facilitate the rapid interaction with a large number of participants (and non-‐participants) in a relatively short amount of time. Second, they serve to minimize the bias created by the limitations of individual memories and motivations in reporting, as members of the group are likely to be aware of any individual misreporting and will question such answers. However, focus groups can also have the effect of homogenizing heterogeneous answers as dominant personalities or a majority of the group might effectively silence significant minority answers. To control for known hierarchy and power issues in India, focus groups will be segregated by gender. Within each gender focus group, (where the most senior men, typically 50 and over, and the most senior women, typically 45 and over, would be steered to distinct sides within the focus groups).

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Every community will likely have place-‐specific issues of hierarchy and power, and for this reason, the evaluation teams will include a qualitative data collector who will have responsibility for recording group dynamics and divergent opinions before they are homogenized into a single group answer (see team structure below). Should the field teams find that the focus groups are clearly over-‐aggregating responses (as evidenced in significant dissent and disagreement in the focus groups over answers to a large number of questions), there are two possible remedies. First, the teams can identify the source of this dissent and disagreement, and in so doing identify new subdivisions of participants and/or non-‐participants that better capture relevant livelihoods and social dynamics. Second, teams can abandon focus groups and work with individual farmers in semi-‐structured interviews, using the same questions designed for the focus groups, and the same adaptive methodology to hone the questions over time.

At the end of each field day, the team should meet and review the outcomes of the focus groups and establish a shared understanding of group dynamics, trends in the questions, questions that should be discarded and questions that need to be added to future focus groups. This information should then be communicated to the other field teams and discussed to come to a project-‐wide agreement on modifications to the questions for focus groups, and to rapidly transfer lessons learned about conducting these groups through the project staff.

Field Team structure

The field evaluation will be carried out by teams of three people: a rapporteur, a qualitative note-‐taker, and a quantitative data recorder. The rapporteur will lead the focus groups, posing questions and following up on answers as appropriate. The rapporteur must have experience with qualitative work in rural communities, and display sensitivity to group dynamics and local context in the phrasing of questions and follow-‐up. The qualitative note-‐taker will have a dual role. The first is to carefully record the answers to the various questions. The second, equally important role is to record information about the group dynamic, such as moments of significant disagreement among the group, and how that disagreement was resolved (a single dominant voice, a trend toward consensus, etc.). This second role is critical for interpreting the findings of the focus groups after the fact. Finally, the quantitative data recorder will record all answers to questions with quantitative answers, ideally using a handheld device to digitize the results in real time, allowing for rapid analysis of some aspects of the focus group findings. Where necessary, these groups should be accompanied by an interpreter.

Ideally, the evaluation will work with four teams, two comprised of men and two comprised of women. The gender of the rapporteur is especially important here, as efforts to elicit gender-‐specific information are often facilitated by conversations with investigators of the same gender.

A significant challenge in qualitative research is investigator bias – in the context of qualitative research conducted by multiple field teams there have been many cases, including a particular well-‐known case documented by Robert Chambers, of research where differences in responses

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were attributable to the people doing the interview/focus group, not to actual differences between people or groups. To control for this problem, sampling zones will not be the exclusive province of a single team. Instead, all teams will work in all sampling zones at the same time, and discrepancies in their findings will be captured in the daily report-‐outs to the wider team. The teams will discuss and resolve these discrepancies, identifying investigator biases wherever possible and making adjustments to address those biases on the fly.

A note on Focus Group data quality

Qualitative data collection does not always require a preset minimum number of interviews to establish rigor and validity. Instead, the project will adopt a grounded theory approach, iteratively revising its questions until the point that focus group sessions no longer produce new questions to pursue, or surprising answers. In short, once the assessment teams can predict with some certainty what the participants in a focus group will say in the course of the group discussion based on who is participating (i.e. men of a particular ethnicity practicing a particular livelihood near a road), they will have achieved what is known as “theoretical saturation,” and can assume a level of rigor and validity in their data. Field experience in other contexts suggests that saturation can occur in as few as 10 interviews/focus groups, if the initial set of questions is well-‐framed and quickly reshaped to reflect learning from initial interviews and focus groups.

A note on Ethics: Data Collection and Management

While informed consent is an important part of ethical research and participant risk management, the data collection and management strategies for the assessment must also minimize these risks to ensure the well-‐being of the participants, and the collection of information that most closely mirror the assessment participants’ view of the project. To address these concerns, data collection will occur via focus groups segregated by these key cleavages. Wives will not be asked to contradict their husbands in a public place, nor will junior members of the community will not be asked to challenge their elders, just to make their voices heard. This first layer of participant risk management will be augmented by anonymizing the data after collection. Names will be recorded at the point of the focus group to ensure that there is no duplicate engagement of individuals in multiple groups. However, once the team has left a sampling zone and the data is formally recorded and transcribed, all names will be removed from the data and replaced with identification numbers. While the assessment will require that we gather personal information, such as age, gender, and marital status, of focus group participants, there is no reason to link the names of the participants to the data for analysis. If possible, village of origin will also be removed, as the stratified sample should provide enough context to interpret the data. In short, we will make it as difficult as possible to trace a particular set of answers to a particular individual, focus group or community. Once transcribed, all field notes and files that contain the names of participants will be destroyed. For the purposes of revisiting data integrity in the future, a single document linking identification

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numbers to names and villages will reside with the principal investigator, in a locked cabinet. This document will only be used if the scientific legitimacy of the evaluation’s sampling is called into question.

2. CONCLUSION REPLICABILITY & TRANSFERABILITY: Identifying gaps in services relative to demand, and opportunities to address gaps

In India, this aspect of the assessment will identify opportunities to strengthen the impact of the current program, and potential opportunities to consider when upscaling. It goes beyond using the current program as a complete package for potential upscaling. The village-‐level component should provide good information about demand that the program does not currently cover effectively. However, experience, awareness of the literature and preliminary interactions with key stakeholders should suggest some products and services that may be provided in other agricultural advisory programs, that might meet known needs in Mali agriculture, and that are not part of the current program. This falls at the intersection of institutional analysis, the planned climate science analysis, and village-‐level evaluation.

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FIELD RESEARCH TASK LIST & TIMELINE

Preparation Tasks:

1) Field sites selection a. Tentatively: Andhra Pradesh, Tamil Nadu, West Bengali, Gujarat, Punjab.

2) Field site background research (Lead: Vivienne): a. Location b. Development indicators & livelihoods c. Agricultural/farming context: farming system, irrigation, wealth of farmers, intensity

of farming d. AAS program e. Literature and document search for any and all livelihoods and agricultural baseline

data for India from xxx and xxx. This search should identify, obtain and assess the contents and quality of any such data. Also Literature search for detailed ethnographic studies of relevant parts of India (these areas will be determined by the sampling zone map) from xxx to xxx. This literature should be rapidly assessed to identify information on livelihoods, social structure and roles and land tenure (among other things), which will inform the initial question sets used by field teams.

3) METHODS development: Field survey questionnaire development and validation 4) Establish Schedule calendar (Leads: Arame / Kalpana) 5) Establishment of a sampling map that illustrates homogeneous sampling zones and the

location of participant villages in those zones: stratified random sampling based on an area map of India’s xxx regions superposed with map of project participating villages. This can be overlain with a layer of roads to help with sampling within sampling zones.

6) Field team composition, and identification of local institutions to get buy-‐in from. In each site needed:

a. Graduate student to serve as Translator/Facilitator (x1) b. Local project staff based in target villages (x1) c. Identification of appropriate teams to conduct the field assessment. Ideally, there

would be four teams – two comprised of men, and two comprised of women. d. Identification of equipment and infrastructure needs to conduct the fieldwork,

including transportation, communication and data collection/entry needs 7) Training of survey team (2 teams of 4each, gender-‐balanced) 8) Advance notice to village authorities and entry point to facilitate time.

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TIMELINE AND DELIVERABLES

1.1. Sequence of Field site visits

Dates Site Selected Districts (agro-‐climatic zone)

Selected Villages

June 21 – 28 Andhra Pradesh 1) Nalgonda 2) Mahboobnagr 3) Warangal

1) Nimani 2) Gorita 3) Bairon

pally June 28 – July 4 Himachal Pradesh 1) Kangra

2) Una 3) Kullu

1) Radh 2) ? 3) ?

July 5 – July 11 Punjab -‐ July 12 – July 20 West Bengal -‐ July 20 – July 29 Tamil Nadu -‐ July 30 – August 8 Gujarat August 8 Return to Delhi

1.2. Field & Institutional Assessment Schedule

Date Activity Responsibility Deliverables Thursday June 21: ANDRAH PRADESH

Arrival in Hyderabad Institutional meetings: § Meeting with program coordinator at Hyderabad Agricultural University

§ Other university staff involved

§ Head of university

Field team § Selection of target AAUs and villages

§ Assignment of graduate student and field staff to facilitate field visits

§ Arrangement of meetings with all relevant stakeholders

Friday 22 June ICRISAT Field team ICRISAT HQ visit Cash advance and wire to field coordinator account

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Saturday June 23 Institutional meetings cont’d: § Training of graduate student and local staff

§ Field work logistical preparation

Field team Appropriation of field methods

Sunday June 24 Village 1 -‐ Monday June 25 Village 2 -‐ Tuesday June 26 Village 3 -‐ Wednesday June 27 Meeting back with

Hyderabad Agricultural University: follow-‐up visit

-‐ Report back to Agricultural University on field activities

Thursday June 28: HIMACHAL PRADESH

Departure for Dharamsala, Himanchal Pradesh Drive to Palampur, Himachal Pradesh (1h) Institutional Meetings: Meeting with nodal coordinator at HP Agricultural Institute

§ Selection of target AAUs and villages


§ Arrangement of meetings with all relevant stakeholders

Friday June 29 Institutional Meetings cont’d: § HP Agricultural university staff involved

§ Training of graduate student and local staff

Drive to Kangra

Saturday June 30 Village 1 Sunday July 1 Village 2 Monday July 2 Drive to Kullu (7 hours)

§ Stop at Palampur: Meeting back with HP Agricultural Institute: follow-‐up visit

Report back to Agricultural University on field activities

Tuesday July 3 Village 3 Wednesday July 4 Data Synthesis

Matthias arrives in Chandigarh

Synthesize and triangulate all data for State

Thursday July 5: PUNJAB

Drive to Chandigarh, Punjab (5 hours)

§ Team meeting

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Arame Departs

Friday July 6

Institutional meetings: § Meet with Met Center at Chandigarh

Drive to Ludhiana (2hr) § Meeting with program coordinator at Ludhiana Agricultural University

§ Other university staff involved in AAS program



§ Arrangement of meetings with other relevant stakeholders

Saturday July 7

Institutional Meetings (cont’d): § Training of graduate student and local staff + Matthias

Sunday July 8 Village 1 Monday July 9 Village 2 Tuesday July 10 Village 3 Wednesday July 11

Data Synthesis Day Synthesize and triangulate all data for State

Thursday July 12

Meeting with Ludhiana Agricultural University: follow-‐up visit Drive back to Chandigarh (2hour)

Friday July 13: WEST BENGAL

Departure for Calcutta, West Bengal Drive to Kalyani (1 hour) Institutional meetings: § Meeting with nodal coordinator at West Bengal Agricultural University




Saturday July 14 Institutional meetings cont’d: § Met Center visit § Head of university § Training of graduate student and local staff

Field work logistical preparation

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Sunday July 15 Village 1 Monday July 16 Village 2 Tuesday July 17 Village 3 Wednesday July 18 Data Synthesis Day Synthesize and

triangulate all data for State

Thursday July 19 Meeting with West Bengal Agricultural University: follow-‐up visit Drive back to Kolkata (1h)

Friday July 20: TAMIL NADU

Depart for Coimbatore, TN Institutional meetings: § Meeting with program coordinator at Tamil Nadu Agricultural University

§ Other university staff involved

§ Head of university




Saturday July 21 Institutional meetings cont’d:

§ Training of graduate student and local staff

Sunday July 22 Village 1 Monday July 23 Village 2 Tuesday July 24 Travel day Wednesday July 25 Village 3 Thursday July 26 Data Synthesis Day Synthesize and


Friday July 27

Meeting back with TN Agr. University: follow-‐up visit Drive to Chennai (4 hour) Meeting with Met Center (afternoon)

Saturday July 28 -‐ Sunday July 29

Off

Monday July 30: GUJARAT

Departure for Anand, Gujarat (Ahmadabad airport)


§ Assignment of

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Institutional meetings: § Meeting with program coordinator at Anand Agricultural University

graduate student and field staff to facilitate field visits


Tuesday July 31 Institutional meetings cont’d: § Other university staff involved

§ Head of university § Training of graduate student and local staff

-‐

Wednesday August 1 Village 1 -‐ Thursday August 2 Village 2 -‐ Friday August 3 Travel

Vivienne & Matthias Depart

Saturday August 4 Village 3 -‐ Sunday August 5 Data Synthesis Day Synthesize and


Monday August 6 Meeting back with Gujarat Agricultural University: follow-‐up visit

Tuesday August 7 Contingency Day Wednesday August 8 Return to Delhi -‐

1.3. Fieldwork Schedule

AAS STUDY DAILY FIELDWORK PROTOCOL & TASKLIST: CHECKLIST

TOWARDS INCREASED EFFICIENCY IN DATA COLLECTION, SYSTEMATIZATION AND ANALYSIS

VILLAGE NAME (DISTRICT/STATE): …………………….………………………………

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Timeline Task Lead Check

Upon arrival in village

Collect data to fill out Observation & Qualitative Data Report, based on:

-‐ Interview with NGO/development worker in community (village baseline info)

-‐ Interview with group of Village elders (to complete Timeline of climate risks)

-‐ Village observation of Vulnerabilities & Capacities

-‐ Other interviews

Vivienne / Kalpana

Morning:

During Focus Groups

Data entry (on computer, in English) at the same time as data collection

All field team members

As FGDs proceed Coordinate video footage:

1. Capture of FGDs process 2. Images of village landscape,

vulnerabilities & capacities (+any other

3. Case Interviews of targeted farmers (5 female farmers, 5 male farmers), Ask each farmer:

. What constraints/difficulties do you face in practicing Agriculture? . Why do you stay in Agriculture despite all these problems? . Is the AAS program/its advisories helping in any way to face these constraints?

Matthias

(with translator)

Upon leaving village

Keep log of data quality limitations:

-‐ Across FGDs -‐ Across village

Kalpana

LUNCH BREAK

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After lunch Enter Remaining Data:

Enter data from 4 male interviews & 4 female interviews, into Interview Data Synthesis Template.

Conduct Daily Village Synthesis:

FILL VILLAGE SYNTHESIS TABLE, based on triangulated information from:

-‐ Observation & Qualitative data report 2 GFDs

-‐ 4 women farmer interviews

-‐ 4 male farmer interviews


Evening Pull out graphs from available daily triangulated data

Matthias

END OF FIELD VISITS

Data Synthesis Day Triangulate data from across 3 villages, displaying:

-‐ Synthesis for women -‐ Synthesis for men -‐ Village


Data Synthesis Evening

Put together PPT presentation of AAS Assessment preliminary results for State

Vivienne

-‐ Draft Preliminary AAS Study Report for the Stare

Kalpana

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