OF EXTENSIVE CROPS IN SPAIN sigagroasesor Project. Antonio Mestre AEMET

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1 CUSTOMIZED ADVANCED GIS ADVISORY TOOLS FOR THE SUSTAINABLE MANAGEMENT OF EXTENSIVE CROPS CUSTOMIZED ADVANCED GIS ADVISORY TOOLS FOR THE SUSTAINABLE MANAGEMENT OF EXTENSIVE CROPS IN SPAIN sigagroasesor Project Antonio Mestre AEMET International Conference on Promoting Weather and Climate Information for Agriculture and Food Security Antalya, Turkey 7 9 April 2014

2 l 2 General Objective SigAGROasesor is a demonstration project supported by the EU LIFE+11 programs (Grant agreement reference n LIFE11 ENV/ES/641). This project aims to develop and refine a set of decision-support tools (DST) for extensive agriculture. These tools are being implemented in a web platform to provide on-line services to farmers, allowing them to work more efficiently, effectively and competitively, and by doing so move toward the environmental, economic and social sustainability of the agricultural systems.

3 The partners involved in the project are a set of public regional institutions in Spain. Their aim is to include this new tool in the services provided to the agricultural sector to booster growth and innovation. AEMET is involved in this project as technological partner to provide meteorological and climate support and data Partners: INTIA Instituto Navarro de Tecnologías e Infraestructuras Agroalimentarias; Navarra ITAP Instituto Técnico Agronómico Provincial, Castilla La Mancha NEIKER Instituto Vasco de Investigación y Desarrollo Agrario S.A. Vasque Country Fundació Mas Badia, Catalonia IFAPA Instituto de Investigación y Formación Agraria, Pesquera, Alimentaria y de la Producción Ecológica, Andalusia AEMET Agencia Estatal de Meteorología

4 l 4 KEY ASPECTS OF THE PROJECT The sigagroasesor on line services platform comprises three pillars on which this expert system and decision support tool are based: The application of modern GIS technologies for the management of georeferenced information, making use of soil variability, climate, crop condition, plant health alerts, and biotic and abiotic risks in the decisionmaking process. Web based Decision Support Tools (DST) to systematise the management decisions. Geo referenced Traceability, as a tool to register and manage historical records of Crop Management Units (CMU).

5 l 5 Functionalities: integrated into a collaborative framework Decision Support Tools (DST) consultation To collect all the georeferenced information at farm plot level Management of farm plots and cadastral information. Phenological crop monitoring along the campaign. Integration of climate information, daily meteorological information and quantitative forecasts. Reports of technical and economic management practices at both plot and agrarian exploitation levels.

6 l 6 Who is it for? Group managers Agrarian cooperatives Agribusiness Farmers Advisory Agencies Agricultural technicians Irrigation Communities

l 7 Objectives for targeted users For Group Managers, Agrobusiness and Cooperatives To have information about the location, dimension and potential crop yield of providers.

7 l 7 Objectives for targeted users For Group Managers, Agrobusiness and Cooperatives To have information about the location, dimension and potential crop yield of providers. For Advisory Agencies Communication platform with farmers and cooperatives. Platform to systematize the information generated by farmers and technicians For Farmers Traceability +reports Economical management Technical management Sustainabilty indicators To maintain historical records of each agricultural parcel. Use of technical itineraries (management sequences) Use of DST

Leaching OM Dynamics Extractions ETP Drainage Decision Support Tools DST FERTILIZATION DST IRRIGATION DST VARIETY DST

8 l 8 Simplified scheme of sigagroasesor data and report management MANAGER, COOPERATIVES DATA FARMER REPORTS DATA FARM CMU 1 CMU 2 CMU 4 CMU 3 REPORTS ON time Data NDVI Risk Maps Meteo: Daily+ forecast PROCESSES Phenology Mineralization Leaching OM Dynamics Extractions ETP Drainage Decision Support Tools DST FERTILIZATION DST IRRIGATION DST VARIETY DST CONTROL DST INDICATORS SOIL DATABASE, CROP DATABASE, MAP SERVER, METEO SERVER USERS MANAGEMENT TECHNICAL MANAGEMENT

9 Simplified scheme of sigagroasesor data and report management FARMER FARMS Individual Management Associated Management User DB Administration Reports Pilot programs Cooperatives Technical management groups Input DB maintenance Reports/Statistics INTRODUCTION Basic: CMU Group: CMU INTRODUCTION/Edition Basic: CMU (% apply surf.) Group: CMUs (% surf.) Filters: Crop, Variety Registration CMU Registration PRACTICES CMU Registration FARMING OPERATIONS CMU CROP PRACTICES DATE Administrative subplots Technical DB Crop and variety selection Technical DB CROP VARIETY Sowing date Harvesting date Yield Potential productivity (auto/val.) Management (R/I) Residue Incorporation INPUTS MACHINERY LABOUR PRODUCTS CONTROL Basic Elements (EB) PRODUCT Type Seeds Mineral fertilizers Organic fertilizers Phytosanitary products Contracted Tasks Irrigation water

10 Versión 0 of sigagroasesor Platform l 10 Decision Support Systems Geo referenced Traceability Sustainability Indicators

11 TRACEABILITY TOOL: Agricultural practices management l 11

12 Version 1 of Agroasesor platform l12

13 Version 1 of Agroasesor platform l 13

14 PILOT PROGRAMS l 14 The objective of this action is to validate the sigagroasesor technical recommendations for the different participant regions, for different crops, for different conditions and for different users. Validation of recommendations provided by the different HAD. Validation of the usability of the platform at the user's level. Calibration of the data obtained in order to parameterize the variables VALIDATION PAC: Network of collaborative farmers (99) PPC: Control Pilot Plots (600) Cooperatives PAAP: Network of Plots under Precision Agriculture(41) CALIBRATION DAP: Network of Plots for difusion of Precision Agriculture(2) MPM: Network of Microplots for maintenance (38) GENVCE

15 PILOT PROGRAMS l 15

DECISION SUPPORT TOOLS: DST + NEW TECHNOLOGIES l 16 Integration in the DST N Fertilization of data from N-Sensor in order to provide variable rate N advice in winter

16 DECISION SUPPORT TOOLS: DST + NEW TECHNOLOGIES l 16 Integration in the DST N Fertilization of data from N-Sensor in order to provide variable rate N advice in winter cereal topdressing. Efficiency of N application, adjusted to the crop needs. Reduction of the applied doses (6%) in the plots controlled in Navarre. Better distribution.

17 DECISION SUPPORT TOOLS: DST + NEW TECHNOLOGIES l 17 At experimental field level, reduction of 10% of the N doses applied, while production is maintained.

18 DECISION SUPPORT TOOLS: DST + NEW TECHNOLOGIES l 18 TELEDETECTION. Satellite images Support from images from DEIMOS (20 m pixel). Great coverage, windows of 3000 km 2 in from March till August. Development of different indices: Plan cover fraction NDVI Yield potential.

19 DECISION SUPPORT TOOLS: DST + NEW TECHNOLOGIES l 19 TELEDETECTION. Satellite images satélites

$Not affected by clouds Production of several indices: Plant cover fraction NDVI Yield potential Characterization of resistance patches.$

20 DECISION SUPPORT TOOLS: DST + NEW TECHNOLOGIES l 20 TELEDETECTION. UAVs images (Drons) Support of UAV images (6 cm pixel). Reduced coverage, 1 2 km of radius for flights. Not affected by clouds Production of several indices: Plant cover fraction NDVI Yield potential Characterization of resistance patches. Characterization in campaign for cooperatives

21 RISKS MAPS DECISION SUPPORT TOOLS: DST + NEW TECHNOLOGIES Incorporation in the HAD Historic risks maps, zonal characterization. Campaign risks maps. Algorithms of risks on time in campaign. l 21 Risk map of brown rust (AEMET)

22 Sustainability Indicators l 22 OBJECTIVE: Incorporate environmental criteria to guide economic and social farming practices towards more sustainable production models. The information generated by the participating agencies it is introduced in the CMU to make technical recommendations on the DST should be the basis on which to calculate the indices. Furthermore, through maps, algorithms, data tables, etc. we will incorporate the extra needed information. In this action we will pay special attention to the development of composite indicators such as: nutrient balances, energy balance, GHG emissions balance, carbon footprint and water footprint.

23 COMMUNICATION TOOL l 23 PILOT ROGRAMS: Second level management. Web of the project. Training for Platform use. Diffusion. Professionalization. Traceability Second level managers. Global management: Technical itineraries. Sustainability.

24 l 24 DEGREE OF ADVANCE AND ONGOING ACTIVITIES 1. An initial version of the sigagroasesor platform has been developed in the first year of the project in order to use it in the Pilot demonstration areas, including a preliminary version of four tools: selection of varieties, PK fertilization, N fertilization and irrigation. 2. The GIS Web application has been developed using 100% open source technologies by the company PRODEVELOP, which will also be involved in upgrading the Platform. The new version will include all the improvements needed according to the experience gained in the 2013 agricultural campaign as well as the new support tool for risk of plagues, diseases and weeds. 3. Besides, a DST Indicators will be added to the new version of the Platform to incorporate the selected environmental indicators: Carbon footprint Water footprint and water footprint stress Nutrient Balances Energy Balance Pesticide ecotoxicity Pesticide pressure

25 Management of daily meteorological data and climate data 7 marzo 2013

26 METEO Data Management l26

27 Data provided by AEMET in the framework of sigagroasesor The system is being fed with weather information in near real time from three different data sources : A network of automatic stations with daily data loading (SIAR, EUSKALMET, METEOCAT, AEMET) as input to the System adn assigned to tha agricultural parcel in question (UGC). Raster maps of interpolated meteorological variables: met. data from the current season as well as forecasting ut to 7 days. User s own stations, only available to the owner.

28 Data provided by AEMET in the framework of sigagroasesor Near real time information for every requested AEMET station. Information comes from the archives of AEMET s National Climatological Database. A csv file for each met variable of the selected stations is sent every day, and within 48 hours. These files contain information on the following variables: Daily maximum and minimum temperature Daily maximum and minimum relative humidity Daily precipitation. Wind run (00h to 24h).

29 Data provided by AEMET in the framework of sigagroasesor Outputs from the Operational Water Balance: Daily gridded data ( 5x5 Km resolution) covering all the country for the following variables: (coming from the AEMET Water Balance outputs): 24 H Precipitation. Maximum and Minimum Temperature. Relative Humidity (Daily Mean Value). ETo Soil Moisture content at different depths. Forecasts up to 7 days in advance of ETo, 24 H Precipitation, Maximum and Minimum Temperature and Relative Humidity

30 Data provided by AEMET in the framework of sigagroasesor

31 Climate information for the SigAGROasesor Project Climate information takne from the digital Iberia Atlas (0,5 Km resolution): Monthly mean temperature ( ) Monthly mean of daily minimum temperature( ) Monthly mean of daily maximum temperature ( ) Monthly mean precipitation ( ) Number of days over a specific precipitation threshold for every month ( ) Monthly mean ETo ( ) Risk maps based on specific climate information Climatic maps generated using GIS techniques for the analysis of brown rust (Puccinia spp.) infection risk and shrivelled grain risk in some extensive crops.

32 Example of risk map: Analysis of brown rust (Puccinia spp.) infection risk 32

33 l 33

34 l 34 On line Services Platform sigagroasesor = expert system TRACEABILITY TOOL ADVISORY TOOL COMUNICATION TOOL SUSTAINABILITY INDICATORS Farmers, farm managers Cooperatives Management experts PROGRESS = SHARED KNOWLEDGE

35 Thanks for your attention

Improving food production through innovative Smart Farming services

HIGHER - Better Policy Instruments for High Innovation Projects in the European Regions Improving food production through innovative Smart Farming services Vassilis Kappas (GAIA EPICHEIREIN) v_kappas@c-gaia.gr