Potential contributions on use of HidroMORE model in olive groves vulnerability to CC

1. Regional Knowledge Exchange on Decision-support Tools and Models to Project Improved Strategies for Integrated Management of Land, Water and Livelihoods 22-27 September, 2013, Djerba, Tunisia Potential contributions on use of HidroMORE model in olive grovesvulnerability to CC A. HACHANI, M. OUESSAR, A. ZERRIM

2. OUTLINE Introduction Materials and methods Results and discussion Conclusions and perspectives

3. INTRODUCTION Olive tree • Importance of plantation of olive trees • fluctuation of the olive production

4. Ministryof agriculture, 2001)

5. INTRODUCTION Olive trees • Importance of plantation of olive trees • fluctuation of the olive production Climate change(CC) • Temperature • rainfall • Green house 1

6. Objectives Analyze situation related to climate variability and CC and future projections, Explore different climate scenarios and their effects on water stress olive plantations, Suggest ways and adaptation policies.

7. Study site

8. Location

9. Methodology

10. climatic data: Baseline period, until 2030 and until 2090 Soilmap Land use map Images Landsat 5 and 7 collecting data Geométric and atmospheric correction Treatement NDVI HidroMORE Conceptuel Model

11. CMIP5 – The Fifth Coupled Model Intercomparison Project. The fifth phase of the Coupled Model Intercomparison Project (CMIP5) produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate change. CMIP5 promotes a standard set of model simulations in order to: • Evaluate how realistic the models are in simulating the recent past, • Provide projections of future climate change on two time scales, near term (out to about 2035) and long term (out to 2100 and beyond),

12. Choice of model NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL) develops and uses mathematical models and computer simulations to improve our understanding and prediction of the behavior of the atmosphere, ocean, and climate. GFDL is developing a comprehensive global –high resolution atmospheric model (HiRAM C 360)

13. HidroMore model • HidroMORE is considered as an operational model allowing the calculation of the superficial water budget with a limited number of input data • HidroMore can detect the water stress of vegetation that can be obtained by the soil water balance

14. Inputs & outputs

15. NDVI Cube • NDVI images were calculated from Landsat 5 and 7 TM images downloaded from USGS . The images were geometrically and atmospherically corrected • For joining all the images as bands in a unique image we have to create the images cube sized to the total area.

16. NDVI cube NDVI cube

18. Conceptuel model

19. Results et discussions

20. Climateanalysis R²=0.8 • Test Validation GFDL-HIRAM model

21. Climateanalysis R²=0.8

22. Calibration

23. Checking the water balance algorithmHidroMORE. The result of this comparaison provide an efficiency in the implementation of the methodology made by FAO-56 and HidroMORE. 36

24. ETcadjmap (Baslineperiod) 433mm

25. ETcadjmap (H 2030) 378 mm

26. ETcadjmap (H 2090) 299 mm

27. Rapport ETCadj and ETC

28. ETCadj/ETC

29. Baseline period Horizon 2090 Horizon 2030

30. Adaptative Strategy • Develop prediction systems and early warning of drought, • Minimize the expansion of olive plantations especially to marginal areas, • Encouraging the choice of adapted varieties, • Provide emergency irrigation in case of prolonged droughts,

31. Conclusion The evaluation of water stress of the olive tree within the context of CC in the South East of Tunisia (watershed of OumZessar, Medenine) was made using hydrological modeling (HidroMORE model). Model parameterization was based on already conducted studies in the region while estimations have been made of the other case. In comparison with the reference period (1996-2005) and following the increase in temperature (1°C) and (5°C) and rainfall decrease of (5.4%) and (20%), ET0 recorded an increase of (3%) (9%) and ETCadj was reduced by (2%) and (18%), respectively for the 2030 and 2090 horizons. Thus, it is expected that the land suitable for olive cultivation will experience shrinkage and this cropping system would become increasingly problematic. .

32. Perspectives • Push climate analysis to more detailed levels and explore other scenarios projections related to CC, • In any work of hydrological modeling (such as Hidromore), there is uncertainty at all levels. Thus, improvements can made ​​through: • Further refine the input parameters of the model • Using multiple satellite images, • Consideration of arrangements for collecting runoff and flood • Integrate adaptation scenarios (supplemental irrigation, etc.).

33. Thank You For Your Attention