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SIMULATING THE IMPACT OF CLIMATE CHANGE ON YIELD
REDUCTION OF VEGETABLE CROP PROPAGATION USING CROPWAT-8
                                    by
                  EWEMOJE, T. A. and ASHAOLU, P. O.
Agricultural and Environmental Engineering Department, University of Ibadan,
                             Ibadan, Nigeria.
   Introduction                             Results
• Man’s activity such as deforestation      Inconsistent variability in climate
  has lead to climate change.               change under CD, NI and DI.
• Climate change has both negative and      Yield reduction was low under CD
  positive impact on agriculture.           and high for both DI and NI.
• This impact can be determined using       No significant difference (p<0.05)
  sensitivity analysis.                     between CD and NI.
• A simulation model is needed to carry     Significant differences existed, at p <
  out sensitivity analysis.                 0.05 between DI and CD, also
• CROPWAT model was used.                   between at DI and NI.
                                            Coefficient of determination (R2) is
  Objectives
                                            close to 1 therefore model is valid.
• Simulation of climate change impact
                                            Yield reduction was low between July
  on vegetable propagation using
                                            and October, depicting better yield
  CROPWAT-8.
                                            during rainy season.
• Analyse weather forecasting for a 9-
  year period for vegetable crop yield in
  response to climate change.
• Model crop yield sensitivity to
  changes in weather data in a tropical
  environment.
  Methods                                     Source: www.fao.org/nr/water
• Study area: Ibadan, Nigeria.              Conclusion
• Data: Climatic, Soil and Crop.            Climate change is not constant
• Irrigation Schedule: No Irrigation,       phenomenon, its ever changing.
  irrigation (NI) and Critical Depletion    Critical depletion is most preferred
  (CD) with Definite Interval (DI).         under uncertainty in variability of
• Statistics: Descriptive (Mean), Least     climate change.
  Square Difference (LSD) and T test.       Planting should be done between July
                                            and October; to reduce impacts of
                                            climate change on yield.

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Simulating the impact of climate change on yield reduction of vegetable crop propagation using CROPWAT-8 - Ewemoje, T. A. and Ashaolu, P. O., Lecturer in Soil and Water Conservation Engineering, University of Ibadan, Nigeria

  • 1. SIMULATING THE IMPACT OF CLIMATE CHANGE ON YIELD REDUCTION OF VEGETABLE CROP PROPAGATION USING CROPWAT-8 by EWEMOJE, T. A. and ASHAOLU, P. O. Agricultural and Environmental Engineering Department, University of Ibadan, Ibadan, Nigeria. Introduction Results • Man’s activity such as deforestation Inconsistent variability in climate has lead to climate change. change under CD, NI and DI. • Climate change has both negative and Yield reduction was low under CD positive impact on agriculture. and high for both DI and NI. • This impact can be determined using No significant difference (p<0.05) sensitivity analysis. between CD and NI. • A simulation model is needed to carry Significant differences existed, at p < out sensitivity analysis. 0.05 between DI and CD, also • CROPWAT model was used. between at DI and NI. Coefficient of determination (R2) is Objectives close to 1 therefore model is valid. • Simulation of climate change impact Yield reduction was low between July on vegetable propagation using and October, depicting better yield CROPWAT-8. during rainy season. • Analyse weather forecasting for a 9- year period for vegetable crop yield in response to climate change. • Model crop yield sensitivity to changes in weather data in a tropical environment. Methods Source: www.fao.org/nr/water • Study area: Ibadan, Nigeria. Conclusion • Data: Climatic, Soil and Crop. Climate change is not constant • Irrigation Schedule: No Irrigation, phenomenon, its ever changing. irrigation (NI) and Critical Depletion Critical depletion is most preferred (CD) with Definite Interval (DI). under uncertainty in variability of • Statistics: Descriptive (Mean), Least climate change. Square Difference (LSD) and T test. Planting should be done between July and October; to reduce impacts of climate change on yield.