Waterlogging in Australian agricultural landscapes: a review of plant responses and crop models

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.

Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States

“…While currently very few models include complete representation of these excessive soil water processes (Shaw, Meyer, McNeill, & Tyerman, ), there have been studies demonstrating that the crop yield response to excess water can be effectively improved by implementing empirical relationship of varying complexities, such as the stress‐day approach (Kanwar, ), damage function of root growth (Rosenzweig et al, ), or the three‐stage empirical representation of waterlogging (Shaw & Meyer, ). The continuous development of field‐level agronomic crop models against experimental data also paves the way for modeling these new processes, and the recent efforts to combine the strengths of agronomic crop models and global‐scale ecosystem/land surface models under a unified model framework could potentially benefit simulation of excessive rainfall impact through improved soil hydrology and photosynthesis processes (Peng et al, ).…”

Membrane transporters mediating root signalling and adaptive responses to oxygen deprivation and soil flooding

“…Tomato leaves wilt when waterlogged for 4–6 h (Jackson ), and tobacco plants undergo leaf yellowing and wilting when waterlogged for as little as 2 h (Shaw et al . ). The estimated yield reduction due to soil flooding ranges from 40 to 80% (MacEwan et al .…”

“…; Rao & Li ; Shaw et al . ). In Australia alone, ∼20% of all soils are duplex, so prone to waterlogging (Setter & Waters ; Shaw et al .…”

Waterlogging and submergence stress: affects and acclimation

“…Whether genus or species, approximately 16% of the fertile areas of the world are affected by soil waterlogging and the average yield loss due to spring floods or excess rainfall is estimated to be 40-80%, which can vary depending on the stage of plant development (Ahsan et al, 2007;Setter et al, 1999;Shaw et al, 2013). The estimated annual damage from crop loss is estimated to be in excess of billions of dollars, which empathizes the need to take waterlogging stress very seriously (Voesenek and Bailey-Serres, 2013;Pucciariello et al, 2014;Voesenek & Sasidharan, 2013).…”