Exploration of data requirements for adaptive control of irrigation scheduling

Abstract

Irrigation scheduling using physical and agronomic principles can improve both application and crop water use efficiencies. However, irrigation traditionally involves applying the same volume of water across an entire field, although not all plants in the field have the same water requirements. An adaptive control strategy is needed to locally control water applications in response to infield temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2008). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. This paper reports a 2008/09 field study which examined the utility of three sensed variables – weather (evaporative demand), soil moisture and plant height – for the determination of appropriate irrigation management strategies in a cotton crop. The relative significance of each sensed variable (either singly or in combination) as a control input was evaluated using VARIwise. The implications for sensed data requirements and the implementation of adaptive irrigation control strategies are discussed.