Improving estimates of water-limited yield of wheat by accounting for soil type and within-season rainfall

Rainfall is the main driver of potential yield in the dryland cropping environment of Australia. Rainfall-based empirically derived models such as that proposed by French and Schultz (1984) (F&S) can be used to determine an upper limit of water-limited potential yield, but F&S often overesti...

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Veröffentlicht in:Crop and pasture science 2009-01, Vol.60 (12), p.1137-1146
Hauptverfasser: OLIVER, Y. M, ROBERTSON, M. J, STONE, P. J, WHITBREAD, A
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Sprache:eng
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Zusammenfassung:Rainfall is the main driver of potential yield in the dryland cropping environment of Australia. Rainfall-based empirically derived models such as that proposed by French and Schultz (1984) (F&S) can be used to determine an upper limit of water-limited potential yield, but F&S often overestimates actual yield as it does not account for rainfall distribution, runoff, drainage, or stored soil water. More complex models are available to predict potential yield more accurately; however, farmers and advisors favour easy-to-use-methods to estimate potential yield. To derive a simple yet accurate method for estimating potential yield, several adjustments to F&S were evaluated: ( 1 ) accounting for stored soil water at sowing, ( 2 ) varying the value of the intercept between yield and growing-season rainfall (GSR), ( 3 ) varying the water-use efficiency of the crops (WUE) according to soil type, and ( 4 ) adjustments to GSR depending on soil plant-available water capacity (PAWC). The water-limited potential yields predicted from these methods were compared with simulations from the daily time-step simulation model APSIM and observed wheat yields from 146 dryland wheat crops, managed to water-limited potential yield, covering the 1996–2006 seasons in the Mediterranean-type growing environments of Australia. The original F&S method overestimated actual yields, particularly at high rainfall (GSR > 220 mm) when PAWC was low, and underestimated yields at low rainfall (GSR 
ISSN:1836-0947
1836-5795
DOI:10.1071/CP09122