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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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515–5 24.
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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.