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- Title
Waterlogging in Australian agricultural landscapes: a review of plant responses and crop models.
- Authors
Shaw, Ruth E.; Meyer, Wayne S.; McNeill, Ann; Tyerman, Stephen D.
- Abstract
This review summarises reported observations of the effects of waterlogging on agricultural production in Australia and briefly discusses potential remediation strategies. Inconsistencies are demonstrated in the current indicators used for assessment of waterlogging potential across agricultural landscapes as well as in parameters measured in waterlogging studies. It is suggested that predictions of waterlogging potential for landscapes should be based on a minimum dataset that includes pedological, topographical, and climate data for the defined area, as well as observations of plant morphological appearance and visible surface water. The review also summarises the effects of low oxygen concentration in soil on rhizosphere processes, and discusses evidence for direct effects on plant physiology of reductions in soil oxygen caused by waterlogging. Finally, the review describes current crop growth, water use, and yield simulation models used in Australia (SWAGMAN, DRAINMOD, and APSIM) that incorporate waterlogging stress. It is suggested that there is scope for modifications to these models based on recent improved understanding of plant physiological responses to waterlogging and on further research. The review concludes that improvements in modelling waterlogging outcomes to assist growth and yield predictions should ultimately enhance management capacity for growers. This review of waterlogging in the Australian landscape examines potential for occurrence of waterlogging, soil and plant response, and reduction in crop yield and economics due to waterlogging. The review highlights enormous scope to include recent improved understanding of plant physiological processes involved in waterlogging, along with a standardised minimum dataset, into crop growth, water use, and yield simulation models. This is suggested to result in better biological process models as well as improved capacity to predict likelihood of waterlogging, yield effects, and economic consequences, thus enhancing information available to farmers.
- Publication
Crop & Pasture Science, 2013, Vol 64, Issue 6, p4
- ISSN
1836-0947
- Publication type
Article
- DOI
10.1071/CP13080