Sexton, J., Everingham, Y., Skocaj, D., Biggs, J., Thorburn, P., and Schroeder, B. (2017) Identification of climatological sub-regions within the Tully mill area. In: Proceedings of the 39th Annual Conference of the Australian Society of Sugar Cane Technologists (39) pp. 342-350. From: ASSCT 2017: 39th Annual Conference of the Australian Society of Sugar Cane Technologists, 3-5 May 2017, Cairns, QLD, Australia.

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Abstract

Identifying optimal nitrogen application rates that reduce nitrogen loss without adversely reducing yields would benefit growers and the environment. In order to identify optimal nitrogen application rates throughout the Tully mill area, it is important to identify sub-regions that share similar topographical, soil, farm management, productivity or climatological attributes. While current SIX EASY STEPS nitrogen guidelines enable a hierarchy of district, soil, block and crop nitrogen requirements for sugarcane, it would be beneficial for management zones to also take spatial climate variability information into account. Unfortunately, spatial climate variability within a region, is generally not considered when developing nitrogen management practices. The objective of this paper was to identify sub-regions within the Tully mill area based on climatological attributes as a first step towards better informing nitrogen management decisions. Rainfall, radiation and temperature data were obtained on a 0.05 by 0.05˚ grid (approximately 5 km by 5 km) for sugarcane-growing areas within the Tully Mill region. A K-means clustering algorithm was then used to cluster these grid cells into distinct sub-regions based on seasonal or annual climate data. Two distinct sub-regions were identified based on total annual rainfall and annual average daily radiation data. These sub-regions were identified as a northern and southern sub-region, divided roughly along the Tully River. The northern sub-region was characterised by lower radiation, lower temperatures and higher rainfall than the southern sub-region. Crop simulation models will now be able to use this knowledge to assess if nitrogen management plans should vary between the two sub-regions in Tully.

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