Prediction of Corn Yield based on Different Climate Scenarios using Aquacrop Model in Dangme East District of Ghana
2017
Twumasi, G.B., Kyungpook National University, Daegu, Republic of Korea | Junaid, A.M., Kyungpook National University, Daegu, Republic of Korea | Shin, Y., Kyungpook National University, Daegu, Republic of Korea | Choi, K.S., Kyungpook National University, Daegu, Republic of Korea
Climate change phenomenon is posing a serious threat to sustainable corn production in Ghana. This study investigated the impacts of climate change on the rain-fed corn yield in the Dangme East district, Ghana by using Aquacrop model with a daily weather data set of 22-year from 1992 to 2013. Analysis of the weather data showed that the area is facing a warming trend as the numbers of years hotter and drier than the normal seemed to be increasing. Aquacrop model was assessed using the limited observed data to verify model's sufficiency, and showed credible results of R2 and Nash-Sutcliffe efficiency (NSE). In order to simulate the corn yield response to climate variability four climate change scenarios were designed by varying long-term average temperature in the range of ±1℃ ~ ±3℃ and average annual rainfall to ±5 % ~ ±30 %, respectively. Generally, the corn yield was negatively correlated to temperature rise and rainfall reduction. Rainfall variations showed more prominent impacts on the corn yield than that of temperature variations. The reduction in average rainfall would instantly limit the crop growth rate and the corn yield irrespective of the temperature variations.
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