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Watch: When plant water stress is observed in sensitive phenological phases
Early Warning: Predicted potential yield loss is up to 10%.
Warning:. Potential yield loss is up to 20%.
Alert: Potential yield loss is up to 30%.
Catastrophe:Potential yield loss is up to 40%.
Need to be ensured soil, yield, land use and MODIS NDVI data for the occurrence of drought forecasting. Ensure yield, land use and MODIS NDVI data. The supply of data shall be easily accessible to all. The regular monitoring of drought need to be carried out testing simultaneously with several parameters. Several indices should be used simultaneously for extent and effects of drought, and its versatility assessment which can be accessible on the online page of the EDO and effectively usable in the CEE regions (CDI, fAPAR). The intensity of drought damages and economic losses, which occur during the cultivation of crops on a specific time and field, shall be assessed with the comparatives analyses of the climatic and hydrological factors and the farmer attitude and adaptation These results are the basis of state aid, and any possible determination of compensation.
The yield loss of maize and wheat can be predicted 4-6 weeks before harvest and drought effected sites can be delineated more accurately. The impact of drought on agriculture can be diagnosed far in advance of harvest, which is the most vital need for stakeholders concerning food security and trade. This information can facilitate drought intervention activities reduce impacts of drought on possible stock uncertainty and can facilitate decision makers in more accurate mitigation measures and preparedness plans for a specific region. A new drought related soil moisture regime GIS database were also established in which the data based on water management parameters of high resolution soil data by using different GIS SQLs clearly showed that the impact of drought were more severe in extreme water management soils.
ADMYLFM is extendable for other IDMP CEE countries, since NDVI data and yield loss data from the whole CEE countries can be easily compared the optimal amount of corn and wheat yields (t/ ha) have little difference in the CEE region. In contrast with the conventional agricultural drought indexing methods, which mainly uses point source meteorological data, ADMYLFM can estimate the expected yield loss based on remote sensing data with 250*250 m spatial resolution. MODIS NDVI datasets have 250 m spatial resolution, which means 1 pixel represents 6.25 ha, while fAPAR has 1 km spatial resolution, which corresponds to 100 ha pixel size. In Europe, an average farm size is about 19-20 ha, while in CEE it is less. Therefore the monitoring of drought through the possible yield loss of a specified crop is not appropriate with datasets, such as fAPAR, having low spatial resolution. Therefore both temporally and spatially better spatial resolution provides smaller data oscillation and more homogenous changes of NDVI in pixel scale, than in case of larger resolution.
extension of the monitoring method and risk signalling system for other crop types, which are characteristic is the CEE region and have significant economic role. extension of the monitoring method and risk signalling system for the entire CEE region determination of that amount of water, which is missing for an average yield (t/ha) from an given agricultural area. (This result could assist setting up a better irrigation strategy.) Using the time series analysis of the results of the method, those site can also be identified, where irrigation is often required. Combining these results and soil maps and the drought related soil moisture regime map, those sites can be identified where drought has regular effect. Mapping of yield losses within CEE region in combination with economic losses. This can support to elaborate joint export market strategy of the region and can give information to reduce future stock problems.
Fourth IDMP CEE workshop: Policy oriented study on remote sensing agricultural drought monitoring methods by Janos Tamas
Policy oriented study on
remote sensing agricultural
drought monitoring methods
Prof. János Tamás
IDMP CEE Final Workshop; 21-22 April, 2015, Bucharest, RomaniaApril 20152 www.gwpcee.org
Activity leader: Prof János Tamás
• Hungary (University of Debrecen and GWP HU):
• Applied hydrological remote sensing and GIS;
• Spatial Decision Supporting Systems
• Romania (University of Oradea):
• Geography and Integrated watershed management
• Slovakia (Institute of Hydrology of the Slovak Academy of Sciences):
• Agricultural water management, Soil hydrology
Duration: July 2013 – January 2015
• RS and GIS based Agricultural Drought Monitoring and Yield Loss Forecasting Method for the
important crops and fruits (wheat, corn and apple)
• Integration of Agricultural Drought Monitoring and Yield Loss Forecasting Method (ADMYLFM) to
agricultural drought management
• To develop a process, which can provide information for
estimating relevant drought indexes and drought related
agricultural yield losses more effectively from remote sensed
• New calculation method, which provides early information on
physical implementation of drought risk levels
• Allow the conversion of different purpose drought indices, such as
meteorological, agricultural and hydrological ones, and more water-
saving agricultural land use alternatives
IDMP CEE Final Workshop; 21-22 April, 2015, Bucharest, RomaniaApril 20154 www.gwpcee.org
(1 – 5 risk levels)
• Data acquisition and
• Identification and
calibration of biomass data
and drought risk levels
• Drought risk evaluation
Identification and calibration of drought risk level
(Source: KSH and INSSE)
Normalized yield of maize and wheat (2000-2012)
Identification and calibration of drought risk level
Drought risk and signalling NDVI levels for maize and wheat
Drought risk evaluation and mapping
IWA 13th International Specialised Conference on Watershed and River Basin Management - San Francisco, CA, USA , 9-12 Sept 2014. 7
IDMP CEE Final Workshop; 21-22 April, 2015, Bucharest, RomaniaApril 20158 www.gwpcee.org
1. Remote sensing toolbox for drought monitoring
mapping and yield loss
2. Agricultural Drought Monitoring and Yield Loss
Forecasting Method includes five standard remote
sensing based drought risk (threshold) levels.
3. The economic effect of yield loss on price
4. Integration of our method to drought
IDMP CEE Final Workshop; 21-22 April, 2015, Bucharest, RomaniaApril 20159 www.gwpcee.org
• Capacity building “Training for trainers” meeting in Szarvas, Hungary,
21-23. November 2013.
• TV reports
• National consultancy dialogues, Budapes, Hungary
• IWA 13th International Specialised Conference on Watershed and
River Basin Management - San Francisco, CA, USA , 9-12 Sept 2014
• World Conference on Computers in Agriculture and Natural
Resources, University of Costa Rica, San Jose, Costa Rica, July 27th-
• European Geoscience Union General Assembly, 12-17 April 2015
Follow up outcomes:
• 14th International Conference on Environmental Science and
Technology (CEST2015), 3-5 September 2015, Rhodes, Greece
• Hungarian Hydrologist Council, Szombathely, Hungary 1-3. July 2015.
IDMP CEE Final Workshop; 21-22 April, 2015, Bucharest, RomaniaApril 201510 www.gwpcee.org
• The yield loss of wheat and maize can be predicted 6-12 weeks before
harvest and drought effected sites can be delineated more accurately.
• The impact of agriculture drought on can be diagnosed, which is the most
vital need for stakeholders.
• Facilitates drought intervention activities (Hungarian Cathastrope
Authority, Agricultural Ministry, Farmer Chambers))
• A new drought related soil moisture regime in GIS database (Tisza
watershed) to optimize water governance
IDMP CEE Final Workshop; 21-22 April, 2015, Bucharest, RomaniaApril 201511 www.gwpcee.org
Our method is extendable for other IDMP CEE countries.
In contrast with the conventional agricultural drought indexing
methods, the expected yield loss can be estimated with 250*250 m
spatial resolution based on remote sensing data .
The monitoring of drought through the possible yield loss of a
specified crop is not appropriate with low spatial resolution
datasets, such as fAPAR.
Better spatial resolution with time filtered series, provides smaller
data oscillation and more homogenous changes of NDVI in pixel
Lessons learned and transferability
IDMP CEE Final Workshop; 21-22 April, 2015, Bucharest, RomaniaApril 201512 www.gwpcee.org
The results of 5.5 activities can be strongly link with the
follow up proposal (1-2-3-5) !
Further follow up recommendations:
• Extension of the monitoring method and risk signaling
system for other crop types and/or new satellite mission
(CMOS, PROBE-V) based on TSA image processing
• Developing of better spatial /temporal irrigation strategy
• Interactive web-RS based drought risk and yield loss
• Investigation of the multilateral economic effect of yield
losses within and outside CEE region
IDMP CEE Final Workshop; 21-22 April, 2015, Bucharest, RomaniaApril 201513 www.gwpcee.org