Determination of Onset and End of Growing Season in Nigeria using the Modified Dynamic (Optimal) Threshold Method and Satellite data
DOI:
https://doi.org/10.62292/njtep.v1i1.2023.15Keywords:
Vegetation phenology, SOS & EOS, climate change, modified dynamic (optimal) threshold method, Koppen climate zonesAbstract
Understanding and accurately determining the onset and end of the growing season is essential for crop management, forecasting yields, and assessing the impacts of climate change, which are crucial for various sectors such as agriculture, ecology, and climate science. The study investigates the start and end of seasons using the optimal threshold method in different climate zones from 2001 to 2022. The climate zones include Tropical Rainforest (Af), Tropical Monsoon (Am), Tropical Wet (Aw), Hot Semi-Arid (BSh), Hot Arid (BWh), and Hot Summer Mediterranean climates. The relationship between climate parameters (temperature and precipitation) and phenology was examined using cross-correlation analysis. Furthermore, the research explores the annual distribution of precipitation and temperature, highlighting the variable nature of precipitation compared to temperature. Climate zone-specific analyses reveal trends in precipitation and temperature changes, indicating potential impacts on vegetation growth. The results show that the Af (BWh) climate zone indicated the longest (shortest) season length, and longer zones with a larger Length of Season (LOS) experienced delayed End of Season (EOS) and/or an early onset of the season. Moreover, Af climate seasons start earlier and finish later than those in the other climate zones. The findings have shown that season length (LOS) in Af, Aw, BSh, BWh, and Csb increased at 1.2, 0.4, 0.2, 0.9, and 0.5 days/yr, respectively. However, it is noteworthy that Am experiences a contraction at -0.6 days/yr. The study found that climatic fluctuation has an impact on vegetation phenology throughout all climate zones of Nigeria. Changes in agricultural growing seasons should be studied to maximize agricultural output.
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