IDMP CEE Activity 5.5 by Janos Tamás

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Presentation of 5.5 Demonstration Project

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IDMP CEE Activity 5.5 by Janos Tamás

  1. 1. Presentation of the 5.5 Demonstration Project Prof. Dr. János Tamás 1st Workshop Integrated Drought Management Programme in Central and Eastern Europe, Slovakia Date: 15 – 16 October 2013
  2. 2. Policy oriented study on remote sensing agricultural drought monitoring methods • • • • • Partners of Activity GWP HUNGARY University of Debrecen University of Oradea Institute of Hydrology of the Slovak Academy of Sciences
  3. 3. Key qualifications of partners • 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
  4. 4. Task definition • The drought types: meteorological, hydrological and agricultural • The drought indexes of meteorological and hydrological drought parameters well-measurable and widely tested (temperature, precipitation, humidity, water level etc.) • The agricultural drought least quantified in soil-waterplant environment, the most uncertain drought type. • The main objective of this case study is to formulate concrete practical agricultural drought monitoring method and intervention levels with calibrating for the important crops and fruits (wheat, corn and apple)
  5. 5. 1. Analysis of green and brown water status Finalize OUTPUT 1: An analysis report on the role of soil and crop water content status in waterbalance within different agricultural, landuse and water management practices at rain fed and irrigated systems for the most important crops and fruit (wheat, corn and apple) 2. RS tools for 2. RS tools for vegetation indices vegetation indices 3. Agricultural 3. Agricultural drought decision drought decision support parameters support parameters Finalize OUTPUT 3: Report on integration of RS and GIS tools and intervention levels into drought monitoring system Sept 2013 – Jun 2014 June 2013-Dec 2013 Finalize OUTPUT 2: Toolbox with the concrete identification of remote sensing and GIS data tools for agricultural drought monitoring and forecast May 2014 – Jan 2015
  6. 6. Process flow of RS agricultural drought monitoring methods Meteorological Data Calibration with Drought Index Calibration with available water content SDSS Classification NDVI Time Series Land use mask Soil Physical Data Calibration with Yield statistical data Plant Specific Drought Risk Evaluation Watch Varning Alert
  7. 7. STUDY AREA-SITE SELECTION The Tisa River Basin is the largest subbasin in the Danube River Basin, covering 157,186 km² (19.5%) of the Danube Basin. Sk Drought Risk on Hungarian Great Plain HU Ro
  8. 8. Modis Terra/Aqua Ground res. From 250 m 36 band, Cycle: 1 d 6 Y LONG TIME SERIES of WHEAT NDVI DROUGHT IMPACT
  9. 9. DROUGHT IMPACT ON NDVI BIOMASS NDVI
  10. 10. Relation of NDVI Biomass and Drought YIELD LOSS Biomass -NDVI Relative Yield Loss Potential yield loss is changing in time End result is depend on climatic, soil condition If we calibrate the NDVI TS with real yield loss data and combined with soil data, and meteorological Drought Index, we can estimate the expected different crops yield loss by region by region.
  11. 11. Database Building The case study will utilize the available database prepared for the Tisza River Basin. Crop data – Remote sensing time series Selection of training sites Spectral data noise filtering Rectification (UTM system) Cropping and mosaicing of reference area Indexing Statistical time series data of yields Soil data- digital soil map Common soil physical database of reference area Common topology and coordinate system of reference area Calculation of available water capacity Calculation of water balance on watersheds Meteorological data – Drought Index SPI, fAPAR Sources: USGS, ESA, Literature, Scientific reports, Publications, Media, Statistical reports, Owner data,
  12. 12. Winter Wheat - Yield data sources Winter wheat yield T/County- Tisza Hungarian region Winter wheat –yield/ area- Hungary Hectically yield (Drought effect) Same Growing Area Source: AKI, Hungary
  13. 13. Automatic sensors to control soil water on East-Slovakian plan Tisza river north watershed Slovakian reference site
  14. 14. Measurements of field soil sensors Agrometeorological data Implemented sensor: Groundwater level Soil temperature Available water content Precipitation
  15. 15. Monitoring panel of soil water content Available soil water content on remote controlled panel Water content in different soil layers
  16. 16. CRISURILOR PLAIN – Romanian reference site • • • • The Crisuri Plain is situated in the mid part of the Western Plain (between Barcau and Mures rivers). The total surface area of the plain is 3600 sqkm. Altitudes vary between 90180 m. Along Barcau, Crisul Alb, Crisul Negru, Cigher rivers.
  17. 17. CRISURILOR PLAIN – Meteorological data 12,5 12,5 0C 0C Oradea 12 12 Linear (Oradea) 11,5 Holod Linear (Holod) 11,5 11 11 10,5 10,5 10 10 9,5 9,5 9 y = 0,032x + 9,7834 R2 = 0,2155 8,5 9 y = 0,0386x + 9,6294 R2 = 0,306 8,5 8 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 8 12 12,5 0C 12 11,5 0C 11,5 Săcueni Linear (Săcueni) 11 11 Chişineu Criş Linear (Chişineu Criş) 10,5 10,5 10 10 9,5 9,5 9 9 8,5 y = 0,0354x + 9,7966 2 8,5 y = 0,0164x + 9,9476 2 R = 0,0809 R = 0,2504 8 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 8 AIR TEMPERATURE at Oradea (up left), Holod (up right), Săcueni (down left), Chişineu Criş (down right) meteorological Station from 1975-1980 to present.
  18. 18. CRISURILOR PLAIN –Meteorological Data 950 mm 850 Linear (Oradea) MEAN ANNUAL RAINFALL at Oradea (up left), Holod (up right), Săcueni (down left), Chişineu Criş (down right) meteorological Station from 1994- mm Holod Oradea Linear (Holod) 850 750 750 650 650 550 550 450 y = 0,2548x + 687,37 R2 = 0,0005 y = 1,5343x + 588,36 R2 = 0,0181 350 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 350 a 850 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 450 mm 800 Săcueni 950 mm Chișineu Criş Linear (Chișineu Criş) Linear (Săcueni) 750 850 700 750 650 600 650 550 550 450 400 y = 2,4334x + 536 R2 = 0,0528 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 350 b 450 y = 6,2134x + 488,47 R2 = 0,2042 350 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 500
  19. 19. CRISURILOR PLAIN LANDUSE Nr. crt. Type of land use Surface (ha) Percentage (%) 1 Unirrigated agricultural land 193633,017 55,784 2 Secondary pastures 69458,290 20,010 3 Discontinuous urban and rural space 18086,764 5,211 4 Deciduous forests 17770,277 5,119 5 Swamps 15760,909 4,541 6 Predominant agricultural land mixed with natural vegetation 12894,911 3,715 7 Complex agricultural crops 6057,103 1,745 8 Industrial and commercial bodies 4340,424 1,250 9 Vineyards 3004,937 0,866 10 Water bodies 2367,766 0,682 11 Rivers 1246,070 0,359 12 13 14 Natural pastures Transition shrub areas Rice fields 563,606 548,625 372,402 0,162 0,158 0,107 15 Orchards 243,782 0,070 16 Continuous urban space 222,456 0,064 17 Airfields 136,557 0,039 18 Waste dumps 132,569 0,038 19 Recreational areas 131,535 0,038 20 Coniferous forests 76,446 0,022 Green urban areas 61,998 0,018 21 (source :Institutul Naţional de Cercetare-Dezvoltare „Delta Dunării”: http://www.indd.tim.ro) ) 100,000 347110,444
  20. 20. CRISURILOR PLAIN - SOIL DATA Main soil classes (SourceOSPA Bihor) Main soil types
  21. 21. CRISURILOR PLAIN The distribution of cernoziom soil within Crisurilor Plain (source, Harta Solurilor României, scale 1: 200.000, I.G.F.C.O.T., Bucureşti)
  22. 22. Physical Implementation of different stake holder intervention points - Watch: When a plant water stress is observed in sensitive phenological phases - Early Warning: When relevant a plant water stress is observed, available soil moisture is close to critical, Predicted potential yield loss <10%- Preparation to intervention Warning: When this plant stress translates into significant biomass damage Potential yield loss <20% Alert: when these two conditions are accompanied by an anomaly in the irreversible vegetation damage Potential yield loss <30% Catastrophe: When have to mitigate serious damages. Potential yield loss <40%
  23. 23. SUMMARY • The status of 5.5 activity based on Gantt table of IDMP is correct • Partners almost done data acquisition • Further work focus on data coherency to integrate all data • End of this year we start the 10 years long time series analysis (green and brown water) on reference site
  24. 24. THANK YOU FOR ATTENTION 1st WORKSHOP IDMP, SLOVAKIA

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