1. 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
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:

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

3. 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

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

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

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

7. Population and drought risk (Mesoamerican dry corridor)
Population density
Drought risk
ciat 2000
CIAT 2000
Drought risk in Honduras:
High Population density is concentrate in dry areas

8. 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.

9. 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

10. 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).

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

12. Weather daily data analysis
Weather station of Camotan
Data from
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

13. 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

14. 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

15. 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

16. Universidad Politécnica de Madrid Grupo AgSystemsW3
Cooperación.Ag
Cooperación.Ag
es.linkedin.com\pub\cooperación-ag\67\587\b2b
Universidad Politécnica de Madrid Grupo AgSystems