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RoA Ministry of Emergency Situations,
State Hydrometeorological and Monitoring Service
Crop Yield Forecasting and Agrometeorological Service
System Development in Armenia
Zara Petrosyan
Yerevan, 30.11.2012
Weather and Agriculture Development of agriculture is unimaginable without reliable
agrometeorological actual data and forecasts
Ապրիլ, 2012
Կիրակի Երկուշաբթի Երեքշաբթի Չորեքշաբթի Հինգշաբթի Ուրբաթ Շաբաթ
1 2 3 4 5 6 7
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29 30
Information base
47 meteostations 1 aerological Remote sensing (Eumetcast) 38 agrometeorological
Agrometeorological observations
• Soil and air temperatures • Water deficit • Effective soil water content • Snow depth • Minimum temperature at the tillering node, soil frost
depth • Precipitation
Phenological observations
• Phenological stages • Timing of farming operations • Implementation of agro-technical measures • Plant damage, winter wheat and fruit viability
Collection and exchange of hydrometeorological information
Republic of Armenia Distribution of Areas
Elevation above sea level, m
Elevation zone area
In thousand sq. km %
400-500 0.02 0.1
500-800 0.53 1.18
800-1000 2.37 8.0
1000-1500 5.43 18.3
1500-2000 9.30 31.3
2000-2500 7.29 24.5
2500-3000 3.80 12.6
3000-3500 0.97 3.3
Over 3500 0.03 0.1
Climate of Armenia
• Subtropical dry continental climatic zone • Existence of all altitudinal zones, except for tropical and
equatorial • January average temperature -5.3 C° • July average temperature 15.1 C° • Annual average precipitation: lowlands - 250-300 mm,
piedmonts - 300-500 mm, mountainous regions 500-800 mm • Temperature low -42.1C° (February 1972, Ashotsq) • Temperature high +43.7C (2011, Meghri).
Forecasts
Agrometeorological Meteorological Hydrological
Dangerous phenomena
Forecast term Short-term Medium-term Seasonal
9
Agrometeorological forecasting
Reliable long-term forecasting would allow the decision-makers to implement:
Correct agricultural planning (sowing, measures, harvesting, etc.)
Effective use of resources Application of protective measures, etc.
Agrometeorological forecasting
Sowing and transplanting time On sowing times of rareripe potato in valleys Anthesis times Forecasting anthesis of apricots, peaches and grapes in
Ararat Valley Crop yield Average total yield in the country for all cereals, grapes,
vegetables (including separately for onion, cabbage, tomato), potatoes, meadow grasses
October 2010 – Start of the EC/FAO Programme on Information Systems to Improve Food Security
Decision-Making
• Study of the state of agrometeorological stations • Information provided • Methods of information transfer
Conclusions and recommendations based on analysis and survey results
Establishment of a Working Group Modernisation of the network Installation of 3 automated stations and 9 automated soil moisture
stations important for agriculture
Improvement of crop yield forecasting Yield forecasting for winter wheat, potatoes and grapes using remote
sensing data
Improvement of service Agromet Bulletin Creating agrometeorological part of the website
Working Group Objectives
Participate in discussions on the results of the yield forecasting for the country’s main crops
Contribute to the improvement of agrometeorological services
Basis for the Crop Yield Forecasting
Meteo data Phenological data Remote sensing data
Information base for Forecasting
Database
www.fieldclimate.com
Weather forecast Data
automation
• cultivated land
• permanent crop
• permanent grassland
• forest
• brush tree
• bare soil
• sparse vegetation
• (water)
• (artificial ground)
Data collection process
Crops
Soils
Weather stations
Remote sensing
0
2000
4000
6000
8000
10000
12000
1975
1976
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1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
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1993
1994
1995
1996
1997
1998
1999
Harvest year
Yie
ld (
kg
/ha)
Vegetation indices
(NDVI/DMP)
Climate data
Crop, soil & management parameters
Crop growth simulation model(s)
Cultivated area
Water balance parameters
Yield prediction
module
Production
Country yield Agricultural statistics
Crop monitoring & Yield forecasting: General Flowchart
Estimates for each YEAR x REGION x CROP on: - Yield = fcal(4 types of Indicators) Trend, Meteorology, Crop growth model, Remote Sensing - Production = Yield x Area
Improvement of service
Publishing a new Agromet Bulletin (4 issues annually) Creating an Agromet website http://grid.am/armMeteo
http://192.168.0.2/index_humidity.php
Agrometeorological bulletin
September 30, 2012 No. 4
Հողի ջրապահունակության շեղումը բազմամյա միջին արժեքներից, մմ
-200,0
-150,0
-100,0
-50,0
0,0
50,0
100,0
150,0
200,0
25 27 29 31 33 35 1 3 5 7 9 11 13 15 17 19
Տասնօրյակ
Ջրապահուն
ակութ
յան
շեղում
ը (2
012
- միջինը
մմ
)
Ապարան Արարատ Արենի Ֆանտան ԳյումրիՄարտունի Մերձավան Օձուն
Ստեփանավան Թալին Ուրցաձոր
Marz Area (ha)
Mean of Yield
(2007-2011)
Yield forecast done in August (qx/ha)
Yield forecast done in
September (qx/ha)
Gegharkunik 13498 163.1, 178.9 189.7 212.5
Kotayk 3258 180.9, 206.1 204.4 210.8
Shirak 3667 187.7, 226.6 212.1 255.9
Syunik 1677 156.9, 168.4 184.4 171.5
Key information
New type of information for servicing agriculture
Agrometeorological website
Weather is increasingly fickle and uncertain under climate change
Weather forecast models improvement Improvement of forecast accuracy Increase of forecast time span Concretizing the location Application of new technologies to assess drought
conditions
Necessary measures
Training and professional development of highly qualified specialists
Modernisation Database upgrade Development of methodological manuals in Armenian
language
Establishment of an Early Warning System
THANK YOU!
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