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Micro-level Agromet Advisory Services using block level weather forecast – A new concept based approach

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Keeping in view the recent variability in weather and climate, the Central Research Institute for Dryland Agriculture (CRIDA), Hyderabad pioneered in starting a flagship research programme of the Indian Council of Agricultural Research (ICAR) named ‘National Innovations in Climate Resilient Agriculture (NICRA)’. The project aims to enhance resilience of Indian agriculture to climate change and climate vulnerability through strategic research and technology demonstration. Under the aegis of NICRA, the All India Coordinated Research Project on Agrometeorology (AICRPAM) of ICAR took up a pilot project during 2010 to develop and disseminate block level AAS through its 25 cooperating centres spread across the country2 towards enabling capacity building of farmers for climate resilience. As part of this, AICRPAM initiated block level AAS in Belgavi district of Karnataka through its Vijayapura cooperating centre.
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SCIENTIFIC CORRESPONDENCE
CURRENT SCIEN CE, VOL. 112, NO. 2, 25 JANUARY 2 017 227
challenges flexibly and responsively
tomorrow, there should be a more equi-
table distribution across geographical re-
gions as well. We see that a large swathe
of India – Bihar, Odisha, Jharkhand,
Chattisgarh, Andhra Pradesh and the entire
north-east with the exception of Assam
does not have a single premier institution.
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Receiv ed 1 October 2016; accepted 20 Octo-
ber 2 016
GANGAN PR ATHAP
A. P. J. Abdul Kalam Technological
University,
Thiruvananthapuram 695 016, India
e-mail: gangan_prathap@hotmail.com
Micro-level Agromet Advisory Services using block level weather
forecast – A new concept based approach
Agromet Advisory Service (AAS) deals
with extension agrometeorology and is
defined as ‘all agrometeorological and
agro-climatological information that can
be directly applied to improve and/or
protect the livelihood of farmers’1. AAS
has been adopted at district level since
2008 by the India Meteorological De-
partment (IMD) and is continued even
now. The district level AAS is provided
to farmers making use of medium range
weather forecast of the National Center
for Medium Range Weather Forecasting
(NCMRWF) and IMD. However, the
validity of blanket advisories dissemi-
nated at district l evel has limitations,
particularly in view of the large variabil-
ity in terms of crops, varieties and spatial
weather anomalies at this level.
Keeping in view the recent variability
in weather and climate, the Central Re-
search Institute for Dryland Agricultur e
(CRIDA), Hyderabad pioneered in start-
ing a flagship research programme of the
Indian Council of Agricultural Research
(ICAR) named ‘National Innovations in
Climate Resilient Agriculture (NICRA)’.
The project aims to enhance resilience of
Indian agriculture to climate change and
climate vulnerabilit y through strategic
research and technology demonstration.
Under the aegis of NICRA, the All India
Coordinated Research Project on
Agrometeorology (AICRPAM) of ICAR
took up a pilot project during 2010 to
develop and disseminate block level
AAS through its 25 cooperating centres
spread across the country2 towards ena-
bling capacity buildi ng of farmers for
climate resilience. As part of this,
AICRPAM initiated block level AAS in
Belgavi district of Karnataka through its
Vijayapura cooperating centre. However,
the forecasts used in t his case were also
of district level. After three years of ex-
perimentation, it was concluded that the
district level for ecasts were indeed not
sufficient to answer the demands of the
block level crop and weather variability
within the district. To overcome this
constraint, special request was made to
Figure 1. Cumulati ve Lorenz cu rve o f F- score versus popula tion.
SCIENTIFIC CORRESPONDENCE
CURRENT SCIEN CE, VOL. 112, NO. 2, 25 JANUARY 2 017 228
IMD to provide block level forecasts
for the 25 AICRPAM NICRA districts.
Since 2014, IMD is providing ‘block
level’ weather forecast for identified dis-
tricts.
This has now enabled AICRPAM to
ingeniousl y devel op and disseminat e
AAS at block level through all its 25 co-
operating centres and Krishi Vigyan
Kendras (KVK) of the respective di s-
tricts. The conceptual diagram of block-
level AAS developed by AICRPAM is
presented in Figure 1. Such advisories
are now designated as micro-level AAS.
AICRPAM centres have initiated micro-
level AAS on pilot basis at 50 villages
across India under this project in the past
two years. The scientific staff receives
block level weather forecast from IMD
website, and advisories are developed in
consultation with Subject Matter Special-
ists of respective KVKs. Another i mpor-
tant and useful concept has been
introduced in micro-level AAS in the
form of appointing ‘Field Information
Facilitat or (FIF)’ to serve as the interface
among the farmers, AICRPAM and
KVK. Further, FIF collects information
(prevailing local weather conditions,
crops and their growth stage, vigour, in-
cidence of pests and diseases, etc.) and
disseminates advisories to the farmers.
Generally, a young and progressive
farmer in the concerned village is identi-
fied for this purpose. Feedback from FIF
provides real situation at village level
based on which and the block level fore-
cast, micro-level advisories are prepared.
Thus the Agrometeorologist of the
AICRPAM centre develops the Agromet
advisory bulletins with the help of SMS
at KVK using the field level crop infor-
mation blended with weather forecasts
and communicate to the FIFs by email
who pass on the bulletins to farmers. The
micro-level AAS is generated in the
name of Program Coordinator, KVK and
is disseminated by multiple communica-
tion modes, viz. mobile text and voice
SMS, display at public places, personal
contact, etc. The feedback obtained from
the farmers is being evaluated for i m-
proving and expanding services for the
benefit of farming community. The
monitory benefits from this AAS ranged
from a few hundred rupees to a few thou-
sand rupees per acre depending on the
crop and weather situation. Accurate
forecasts and their timely dissemination
aided in curtailing the crop losses due to
adverse weather. Losses were also re-
ported on occasions due to erroneous
weather forecasts.
The methodology can be up-scaled to
national level by utilizing the already es-
tablished infrastructure and human re-
source by establishing linkage with line
departments, state agricultural universi-
ties and KVKs established in the country.
The next improvement in AAS will be
through downscaling AAS from block to
village level, for which this methodol ogy
will serve as a template, but automation
will be required for such a giganti c pro-
cess.
1. Stigter, C. J., Agrometeorological ser vices:
Reaching all farmer s with operational in-
formation products in n ew edu cati onal
commitments, CAgM Report 104 , WMO,
Geneva , Switzerland, 201 1.
2. Rao, V. U. M., Bapuji Rao, B ., Sarath
Chandran, M. A., Vij ayakumar, P. and
Rao, A. V. M. S., AICRPAM– National
Innova tions on Climate Resilient Agricul-
ture, Annual Report 2015–16. ICAR–
Central Resea rch Institute for Dryland Ag-
riculture, Santoshnagar, Hyderabad, 2016,
p. 52.
Receiv ed 28 September 2 016 ; revised ac-
cepted 12 November 2 016
P. VIJAY A KUM AR1
A. V. M. SUBBA RAO1
M. A. SARAT H CHANDRAN1, *
H. VENKATESH2
V. U. M. RAO1
CH SRINI VASA RAO1
1ICAR-Central Research Institute for
Dryland Agriculture,
Santoshnagar,
Hyderabad 500 059, India
2AICRPAM-Vijayapura Center,
University of Agricultural Sciences-
Dharwad,
Dharwad 580 018, India
*For correspondence.
e-mail: sarath@crida.in
Figure 1. Conceptual dia gram of block-level AAS.
... In today's context, farmers are increasingly recognizing the value of weatherrelated agricultural services as powerful tools for enhancing farm productivity [22]. Weather-based agro advisories can guide farmers in decision-making both before and during the crop season, facilitating the reduction of production costs, crop losses, and carbon footprints, ultimately leading to increased farm profitability [20,23]. The information on critical limits of weather variables for important crop stages is the basis for the formulation of term sheets for crop-weather insurances [24]. ...
... Further it depends on the willingness of farmers to adapt the news aids for improving their farm productivity and age of the adopter added to his experience in farm practices [30]. In India both India Meteorological Department (IMD) and Indian Council on Agricultural Research (ICAR) disseminate block-level Agro-Advisory Service (AAS) throughout the country [22,23]. Recently, the "All India Coordinated Research Project on Agrometeorology (AICRPAM)" have developed dynamic crop weather calendars (DCWC) for automating agromet advisories using prevailing and forecasted weather [31]. ...
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p>Weather based crop insurance schemes play an important role in helping the farmers recovering their financial losses incurred due to aberrant meteorological parameters. Wheat is a major winter season crop grown in Punjab state. To formulate the weather based “weekly and monthly thumb rule models” for predicting the high yield of wheat, a study with meteorological and crop data (2007–2008 to 2021–2022) was conducted for three major wheat growing locations in the state. The results revealed that ideally the monthly maximum/minimum temperatures/rainfall/sunshine duration during the months of December, January, February and March in the range of 20–23 ℃/5–9 ℃/0–38 mm/5–8 h, 17–20 ℃/3–8 ℃/2–57 mm/4–6 h, 19–25 ℃/5–11 ℃/0–79 mm/5–8 h and 25–30 ℃/10–15 ℃/0–56 mm/8–9 h, respectively are optimum for high yield of wheat. The ideally humid (maximum/minimum relative humidity between 90%–97%/36%–63%) weather from November to February is favourable for optimum growth and development of wheat crop. Similarly, the maximum/minimum temperatures/rainfall/sunshine duration for anthesis and grain filling stage in the range of 14–23 ℃/3–10 ℃/0–55 mm/2–9 h and 18–30 ℃/5–15 ℃/0–26 mm/4–10 h are favourable for high yield of wheat crop. The maximum temperature of >18 ℃ during grain filling stage is optimum for potential yield of wheat. While the abiotic stresses like heavy rainfall, heat stress during grain filling stage are not favourable for the productivity of the crop. So, these critical limits of weather parameters are the basis for providing the weather based insurance to the farmers of the region. </p
... In today's context, farmers are increasingly recognizing the value of weatherrelated agricultural services as powerful tools for enhancing farm productivity [22]. Weather-based agro advisories can guide farmers in decision-making both before and during the crop season, facilitating the reduction of production costs, crop losses, and carbon footprints, ultimately leading to increased farm profitability [20,23]. The information on critical limits of weather variables for important crop stages is the basis for the formulation of term sheets for crop-weather insurances [24]. ...
... Further it depends on the willingness of farmers to adapt the news aids for improving their farm productivity and age of the adopter added to his experience in farm practices [30]. In India both India Meteorological Department (IMD) and Indian Council on Agricultural Research (ICAR) disseminate block-level Agro-Advisory Service (AAS) throughout the country [22,23]. Recently, the "All India Coordinated Research Project on Agrometeorology (AICRPAM)" have developed dynamic crop weather calendars (DCWC) for automating agromet advisories using prevailing and forecasted weather [31]. ...
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Full-text available
Weather based crop insurance schemes play an important role in helping the farmers recovering their financial losses incurred due to aberrant meteorological parameters. Wheat is a major winter season crop grown in Punjab state. To formulate the weather based "weekly and monthly thumb rule models" for predicting the high yield of wheat, a study with meteorological and crop data (2007-2008 to 2021-2022) was conducted for three major wheat growing locations in the state. The results revealed that ideally the monthly maximum/minimum temperatures/rainfall/sunshine duration during the months of December, January, February and March in the range of 20-23 ℃/5-9 ℃/0-38 mm/5-8 h, 17-20 ℃/3-8 ℃/2-57 mm/4-6 h, 19-25 ℃/5-11 ℃/0-79 mm/5-8 h and 25-30 ℃/10-15 ℃/0-56 mm/8-9 h, respectively are optimum for high yield of wheat. The ideally humid (maximum/minimum relative humidity between 90%-97%/36%-63%) weather from November to February is favourable for optimum growth and development of wheat crop. Similarly, the maximum/minimum temperatures/rainfall/sunshine duration for anthesis and grain filling stage in the range of 14-23 ℃/3-10 ℃/0-55 mm/2-9 h and 18-30 ℃/5-15 ℃/0-26 mm/4-10 h are favourable for high yield of wheat crop. The maximum temperature of >18 ℃ during grain filling stage is optimum for potential yield of wheat. While the abiotic stresses like heavy rainfall, heat stress during grain filling stage are not favourable for the productivity of the crop. So, these critical limits of weather parameters are the basis for providing the weather based insurance to the farmers of the region.
... The FIFs are progressive young farmers of a village, and usually work in two-way communication (feedback to AICRPAM/KVK and Information from AICRPAM/ KVK). Thus, accurate forecast and timely dissemination of weather information through AWS, AAS, Kisan Mobile Sandesh (KMS), among others, helps in curtailing crop losses due to climatic vagaries (Kumar et al. 2017). ...
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Chapter
The major factor influencing agriculture, the mainstay of majority of the Indian population, is climate. Both long-term climate change and intra-seasonal climate variability impact the decision-making of farmers. The provision of timely and accurate agromet advisories assumes great importance in this context. This chapter begins with weather-related agricultural risks and climate information needed by farmers in decision-making before and during the crop season. It then discusses the agromet advisory services (AAS)—history, development and present status in India. The dissemination and outreach programmes in the form of farmers’ awareness programmes are also included. It further explores the role of AAS in effective operational decision-making, improvement in crop production and economic impact assessment of AAS in India. The chapter ends with constraints, future challenges and opportunities for AAS in India.
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All India Coordinated Research Project on Agrometeorology (AICRPAM) of ICAR has started the micro-level Agromet Advisory Service (AAS) through its 25 cooperative centers across the country. Microlevel advisory based on weather forecast is the newer dimension of the AAS in the country. Studies on economic impact of these micro-level advisories are uncommon. Therefore, the present study was conducted using the field survey to assess the farmer’s perception and economic impact of micro-level AAS in Vijayapura and Anantapur centers on pilot basis. Two groups i.e. AAS and non-AAS farmers, consisting of 40 farmers in each group were selected through multi-stage stratified random sampling technique. The probit regression model was employed to assess the factors influencing willingness to pay (WTP) for AAS. Majority of farmers (65%) rated micro-level AAS as ‘very good’ on scale of ‘very poor’ to ‘very good’. Majority of non-AAS farmers were aware about micro-level AAS but lagged in adopting the service. It needs further detailed investigation of underlying causes of not adopting the service. Farming experience, education, land holding size and income were found to be most important factors influencing the farmer’s willingness for pay-based services. Results of economic impact revealed that there was 12 to 33 per cent increase in profit for AAS farmers as compared to non-AAS farmers.
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CONTENTS Introduction …………………………………………………………………………………… 2 Basic Concepts and Situations …..………………………………………………………… 7 Box 1: Response Farming .………………………………………………………… 7 Box 2: History of Agrometeorogical Services ……………………………………. 8 Services and Complexity …………………………………………………………………… 10 Box 3: Livelihood of Farmers ……………………………………………………… 10 Basic Organization ………………………………..………………………………………… 13 Box 4. Climate Field Schools Alumni …………...…………..…………………… 14 Categories of Agrometeorological Services, Further Examples, Application Conditions ……………………………………………………………… 16 Box 5: INSAM Contests - Best Examples Of Agromet Services ………………. 22 Box 6: Climate Predictions .……………………………………………………….. 28 Detailed Organization ..……………………………………………………………………… 33 Box 7: Global Framework for Climate Services ............………………………… 36
AICRPAM-National Innovations on Climate Resilient Agriculture
  • V U M Rao
  • B Bapuji Rao
  • M A Sarath Chandran
  • P Vijayakumar
  • A V M S Rao
Rao, V. U. M., Bapuji Rao, B., Sarath Chandran, M. A., Vijayakumar, P. and Rao, A. V. M. S., AICRPAM-National Innovations on Climate Resilient Agriculture, Annual Report 2015-16. ICAR-Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad, 2016, p. 52.