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Estimation of Future Water Requirement for Plantain (Musa spp.) in Ondo State, Nigeria using Statistically-Downscaled Climate Variables | OMICS International| Abstract
ISSN: 2157-7617

Journal of Earth Science & Climatic Change
Open Access

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  • Research Article   
  • J Earth Sci Clim Change,
  • DOI: 10.4172/2157-7617.1000499

Estimation of Future Water Requirement for Plantain (Musa spp.) in Ondo State, Nigeria using Statistically-Downscaled Climate Variables

Olotu Yahaya1*, Olufayo AA1, Oguntunde PG1 and Atanda EO2
1Department of Agricultural and Environmental Engineering, Federal University of Technology, Akure, Nigeria
2Department of Agricultural Engineering, Auchi Polytechnic College, Auchi, Nigeria
*Corresponding Author : Olotu Yahaya, Department of Agricultural and Environmental Engineering, Federal University of Technology, Akure, Nigeria, Tel: 348073135503, Email: realyahaya@yahoo.com

Received Date: Aug 05, 2018 / Accepted Date: Nov 28, 2018 / Published Date: Nov 30, 2018

Abstract

This study aims to determine the effects of potential climate change on crop water requirements (CWR) of plantain (Musa spp.) in three agro-ecological zones over Ondo State. Climate change scenario-Representative Concentration Pathways (RCP 4.5) derived from statistical downscaling of six global circulation model (GCM) outputs were applied as inputs to CROPWAT model. Statistically-downscaled climate parameters outputs were used as inputs to the CROPWAT to estimate irrigation water requirements (IWR) and CWR of plantain. Canadian Centre of Climate Model and Analysis (CCCMA) model predicted greatest annual maximum temperature (Tmax) increases of 1.3°C to 1.9°C and 0.8°C to 1.5°C at Ondo North and South Agro-Ecological Zones (ONAEZ and OSAEZ) for periods 2050s and 2080s respectively. The outputs of the simulation for Max Planck’s Institute of Meteorology (MPI) model at OSAEZ indicate highest minimum temperature changes of 2.5°C to 3.2°C for periods 2050s and 2080s. Changes in estimated monthly precipitation indicate reductions for most of the models, with the highest decreases in month of January with -95.8% and -96.8.6% for the future periods of 2050s and 2080s using CCCMA. Lowest decreases of -20.0% and -53.8% were predicted by Irish Centre for High End Computing (ICHEC) in ONAEZ. During the wet season (April to September), all the climate models indicated increase in monthly precipitation except CCCMA and MPI which estimated modest decrease of -18.4% and -19.4% in the months of June and July for period 2050s in OCAEZ. The outputs of CROPWAT model to estimate CWR and IWR showed that CCCMA consistently predicts seasonal highest increases of 26.7% (1085.4 mm) and 28.0% (1102.6 mm) for the periods of 2050s and 2080s in comparison to crop water requirement (CWR) of 879.9 mm in ONAEZ. This trend is similar to the predicted changes in CWR obtained in AEZ and OSAEZ respectively. Again, CCCMA model projected highest irrigation water requirements of 451.6 mm and 469.3 mm; 493.8 mm and 500.8 mm for Ondo Centre Agro-Ecological Zone (OCAEZ) and OSAEZ. These results correspond to IWR increase of 19.6% to 36.1% in ONAEZ, 20.3% to 39.9% in OCAEZ and 25.3% to 42.1% in OSAEZ for periods of 2050s and 2080s relative to the current period of 1975-2005. In conclusion, future CWR and IWR of plantain are likely to increase based on projected climate for the periods 2050s and 2080s in Ondo State.

Keywords: Climate change; General circulation models; Climate change scenario; Crop water requirements; Statistically-downscaling; CROPWAT; Plantain

Citation: Yahaya O, Olufayo AA, Oguntunde PG, Atanda EO (2018) Estimation of Future Water Requirement for Plantain (Musa spp.) in Ondo State, Nigeria using Statistically-Downscaled Climate Variables. J Earth Sci Clim Change 9: 499. Doi: 10.4172/2157-7617.1000499

Copyright: © 2018 Yahaya O, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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