Universidad Politécnica de Madrid Sustainable development of agriculture and food systems with regard to water Carlos Gregorio Hernández Díaz-Ambrona, Esperanza Arnés Prieto, Omar Marín González Universidad Politécnica de Madrid carlosgregorio.hernandez@upm.es Where we are: Campos de prácticas de Agrónomos Escuela Técnica Superior de Ingenieros Agrónomos Departamento de Producción Agraria Universidad Politécnica de Madrid c/ Senda del Rey 13 Ciudad Universitaria 28040 Madrid Spain Map: http://maps.google.es/maps/ms?msid=207898402125395111835.000493086a81f1847d651&msa=0&ll=40.440464,-3.732852&spn=0.00445,0.011212

How weather variability impact on farming? Piedrahita, Avila 3/7/2010

Weather data A pre-condition for the evaluation of weather risk is comprehensive and accurate weather data for the past and future. Historical data: usually at least 30 years of daily data on key parameters, need to be accessible. Operational weather stations have to be identified and basis weather variables defined, also with regard to cleaning procedures. All countries run weather stations that report data to the World Meteorological Organization (WMO) Low weather data density in developing countries http://www.fao.org/uploads/media/Weather%20Risk%20Management%20for%20Agriculture%20and%20Agri-Business%20in%20Developing%20Countries.pdf

Weather data analysis for farming Key daily parameters: Temperature (maximum, minimum) Precipitation Solar radiation Wind speed Relative humidity (maximum, minimum)

Historical monthly data in Honduras tropico húmedo y tropico seco PARA CHOLUTECA DATOS DE WIKIPEDIA = CLIMA MSN

Drought periods (in red) (drought month if precipitation in mm < double of average temperature in ºC) PARA CHOLUTECA DATOS DE WIKIPEDIA = CLIMA MSN

Population and drought risk (Mesoamerican dry corridor) Population density Drought risk http://gisweb.ciat.cgiar.org/Vulnerabilidad/eventos.htm ciat 2000 CIAT 2000 Drought risk in Honduras: High Population density is concentrate in dry areas

Sequence of drought occurrence and impacts for meteorological, agricultural, and hydrological Sequence of drought occurrence and impacts for meteorological, agricultural, and hydrological. All droughts originate from a deficiency of precipitation or meteorological drought but other types of drought and impacts cascade from this deficiency. Source: National Drought Mitigation Center.

Droughts disasters sorted by continent from 1900 to 2011 Region Number of events Number of death Total affected persons Economic damage (million USD) Africa 269 844,143 317,936,829 5,420 Asia 147 9,663,389 1,666,286,029 33,823 Europe 38 1,200,002 15,482,969 21,461 Latin America and Caribbean 109 77 65,078,841 8,866 North America 14 55,000 11,945 Oceania 19 660 8,027,635 10,703 World 596 11,708,271 2,072,867,303 92,218 Personal note: Number of death by Latin America and Caribbean and Oceania is not well known. Source: Horion et al. 2012.

Guatemala case study Rainfed Maize and bean (57% food consumed) Food security in subsistence agricultural systems of mountainous areas depend on corn and common beans production: Rainfed Maize and bean (57% food consumed) Average farm size 0.90 ha (0.59 ha staples) Crop yield variation due to annual weather variation Main statistics for crop seasons weather parameters from the weather station of Camotan Guatemala (1992 to 2012).

Crop cycles Calculation for each seasons: Primera season (May-August) Postrera season (September-December) Apante season (January-April)

Weather daily data analysis Weather station of Camotan Data from 1992-2012 Calculation: Rainfall (Rain, mm) Reference Evapotranspiration (ETo, mm) Crop evapotranspiration (ETc, mm) Ratio Rain/Eto Wet and dry days Statistical: Average, Maximun, Minimum, Standard deviation, Coefficient of variation (CV), First quartile (25% Percentile), Third quartile (75% Percentile) Drought risk: No risk Rain > ETo; Medium Rain > 0,75 ETo; High risk othecases

Results Drought risk No risk in 75% years Medium risk 25% years Rain/ETo Average 135 67 8 Maximum 211 97 24 Minimum 73 26 1 First quartile (25% Percentile) 104 53 3 Third quartile (75% Percentile) 159 82 11 Drought risk No risk in 75% years Medium risk 25% years High risk 75% years High risk 100% years

Crop cycles Primera season (May-August) No risk in 75% years Postrera season (September-December) Medium risk 25% years to High risk 75% years crop needs irrigation Apante season (January-April) High risk 100% years No cropping without irrigation

Other questions To calculate number of consecutives dry days for primera and postrera seasons To compare year by year: for example a humid year (2010) versus dry year (2002) To identify torrential rainfall events (> 40 mm), some years correspond with hurricane impacts To calculate number of consecutives dry days for primera and postrera seasons: high number of dry day produces crop water stresses To compare year by year: to explore weather variability and crop seasons performance Days with rainfall over 40 mm are considered torrential: to compare with hurricane or tropical storm events

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