Food Security Modelling-UWI, Mona

Transcription

1 ! A Research Proposal Submitted in Partial-fulfilment of the Requirement for the Degree of Master of Philosophy in Physics GLOBAL-LOCAL CARIBBEAN CLIMATE CHANGE ADAPTATION AND MITIGATION SCENARIOS Food Security Modelling-UWI, Mona Supervisory Team: Dr. Michael Taylor, Dr. Jane Cohen, Dr. Leslie Simpson, Dr. Tannecia Stephenson Presenter: Dale Rankine Collaborators:

2 1.The Context: Food Security Ø Rising prices of imported foods, especially cereals and grain legumes Ø Food security: function of accessibility, availability, stability and utilization (FAO 2007) Ø Estimates of 8.3 million undernourished Caribbean residents (CARICOM 2010) Ø Regional food import bill estimated at over USD 2.8 billion in 2011 Ø Changing environmental conditions The Jamaican Food security Context - Over 300,000 undernourished people (FAO 2011) -Food import bill: over USD 1 Billion (MOA 2011) -Imports account for over 70% of food consumed -About 80% of food imports from the United States of America (USA) alone 2

3 1. The Context: Climate Ø Agriculture very Climate Sensi>ve Ø Jamaica (Caribbean) rainfall is bimodal Ø Timing, intensity of Mid- summer drought affects cropping season Ø Early Season and late season crops differ Ø Limited impacts studies and unreliable data Figure 1. Pattern of mean monthly rainfall in the Caribbean. Source: ntsavanna.com 3

4 1. Context: Why A Root Crop? Roots and Tubers 2% Sweet 1% 15% potato is the 6 th most important crop globally Contribution of Root and Tuber crops in share by production volume -the Caribbean: Increased from 2% in 1961 to 9% by Comparative increase of 159% of 1961 Output Source: ECLAC

5 1. The Context : Dilemma of Yield vs Climate SPI Yield (t/ha) SPI Yield (t/ha) SPI-12 Yield SPI-12 Detrended Yield Figure 3. Annual drought index (SPI-12) versus mean annual Sweet potato yields for Jamaica ( ) Source: FAOSTAT; Climate Studies Group, Mona Figure 4. Annual drought index (SPI-12) versus mean annual Sweet potato yields (detrended) for Jamaica ) Source: FAOSTAT; Climate Studies Group, Mona 5

6 2. Methodology: Five Varieties Varietal differences: Colour (Flesh and skin) Texture Foliage Source: CARDI

7 2. Methodology: Site Locations Devon * * Ebony Park * Bodles * Passley Gardnes 7

8 2. The Methodology: The FAO AquaCrop Model The Conceptual Framework Conceptual Framework of AquaCrop Source: Hsiao et al 2011 B=WP x ΣTr [Biomass] (ET=E+T) WP normalised for ET and CO 2 Y=B x HI [Yield] Robust, Accurate yet simple 8

9 2. Methodology and Tools: AquaCrop Data requirements Crop Climate and ET Soil and Fer8lity Minimum Addi8onal for improved Simula8on Research Data Tuber Yield, Harvest Index (HI), Sowing and harves>ng dates, crop life- cycle 10- day or monthly mean maximum and minimum temp, or sunshine hours, wind, humidity, la>tude and eleva>on Textural Class and varia>on with depth, land slope, water holding capacity, na>ve fer>lity of soil, fer>liza>on prac>ce Date of (90%) emergence, data of maturity, Maximum green leaf LAI, canopy cover (periodic), Biomass during crop cycle and at Harvest, Weekly or 10- day mean: daily solar (global) radia>on, or sunshine hours, minimum and maximum temperatures, maximum rela>ve humidity, wind m) Daily rainfall, ET es>mated by long- term water balance Texture of different soil horizons, restric>ve soil layers, type, rate, and date of fer>liza>on ALL recommended parameters. Canopy Cover: Green crop tracker/ace All except for Solar radia>on was not available. ET calculated by FAO ETo calculator Soil sampling 15 and 30cm: Moisture, OM, N,P,K Irriga8on and water in Soil Irriga>on method and schedule, idea of soil water content (recent plan>ng Actual Irriga>on dates and amount, es>mate of soil- plan>ng (Measured) Daily rainfall measured, daily irriga>on amount and schedule 9

10 2. Methodology: Green Crop Tracker Software (Liu & Pattey, 2010) (a) Canopy Cover Measurement a. Overhead Photo b. Photo sub-frame C. Magnified gap fraction (b) C Answer CC= % LAI=

11 3. Results: Model Parameterization (Devon vs Ebony Park) Ebony Park-Rainfed (2013) Yield (t/ha) DAP Measured Simulated 11

12 3. Results: 2012/2013 Parameterization(Summarised) Year Treatment Canopy Cover Biomass Yield Devon RSME (%) E RSME (t/ha) E RSME (t/ha) E Ebony Park 2013 Irrigated Rainfed Irrigated Rainfed Irrigated Rainfed Improvement in model parameterization (2012 vs 2013) Enhanced model performance (in 2013): prediction of yields for both Rainfed (Devon) and Irrigated (Ebony) plants E = 1 i N = 1 N i= 1 ( O i ( O i S ) 12 i O) 2 2

13 3. Results: Model Performance Summarised Final (Total) Biomass (t/ha) Tuber Yield (t/ha) Year Treatment Measured Simulated Devia8on Measured Simulated Devia8on Devon Ebony Park 2013 Irrigated 17.6 ± ± Rain fed 25.2 ± ± Irrigated 16.9 ± ± Rain fed 17.8 ± ± Irrigated 27.8 ± ± Rain fed 14.6 ± ± Deviation = {(simulated- Measured)/Measured} *100 Rainfed Biomass estimation within 20-35% of actual values Best irrigated and rainfed yields within 20-30% of measured values 13

14 3. Results Contribution of the Research to Food Security This Research Project will make an original contribution in at least three ways: 1. Crop Model parameterization for Caribbean Sweet potato-1 st Root Crop in AquaCrop 2. Robust yield predictions of Sweet potato in different agro-ecological zones 3. Climate change impact assessment (of suitable scale) on root Crops 14

15 4. Next Steps: Climate Change Considerations Future Context Assessment: Climate change and water limited scenarios of scale End of Century Projections: much drier Caribbean (JJA); implications Couple climate and crop model outputs Climate Change Impact Assessment: 1. Downscaled climate change data 2. Yield Projection-Irrigated and Rainfed Fractional change in Precipitation changes over the Caribbean from the A1B simulations vs Source: AR4 (IPCC, 2007). 21 model ensemble. 15

16 Preliminary Conclusions I. AquaCrop is user-friendly type model featuring a good balance between robustness and simplicity. II. Its ability to work with a relatively small number of parameters makes it ideally suited to the Caribbean III. The results confirm: model can be used to estimate yields within 20-30% of actual values and the framework is transferable to other crops/locations 16

17 Preliminary Conclusions IV. Great potential to: q Improve cultivar selection, q Enhance yield optimisation, q Conduct sensitivity analyses under water limited/climate change scenarios. V. Results will help to: q Identify, prioritise and implement effective adaptation measures in a timely manner q Inform Policy Options 17

18 THANK YOU 18