Y.M. Oliver

Improving water productivity in the Australian Grains industry—a nationally coordinated approach

Abstract. Improving the water-limited yield of dryland crops and farming systems has been an underpinning objective of research within the Australian grains industry since the concept was defined in the 1970s. Recent slowing in productivity growth has stimulated a search for new sources of improvement, but few previous research investments have been targeted on a national scale. In 2008, the Australian grains industry established the 5-year, AU

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

17.6 million, Water Use Efficiency (WUE) Initiative, which challenged growers and researchers to lift WUE of grain-based production systems by 10%. Sixteen regional grower research teams distributed across southern Australia (300–700 mm annual rainfall) proposed a range of agronomic management strategies to improve water-limited productivity. A coordinating project involving a team of agronomists, plant physiologists, soil scientists and system modellers was funded to provide consistent understanding and benchmarking of water-limited yield, experimental advice and assistance, integrating system science and modelling, and to play an integration and communication role. The 16 diverse regional project activities were organised into four themes related to the type of innovation pursued (integrating break-crops, managing summer fallows, managing in-season water-use, managing variable and constraining soils), and the important interactions between these at the farm-scale were explored and emphasised. At annual meetings, the teams compared the impacts of various management strategies across different regions, and the interactions from management combinations. Simulation studies provided predictions of both a priori outcomes that were tested experimentally and extrapolation of results across sites, seasons and up to the whole-farm scale. We demonstrated experimentally that potential exists to improve water productivity at paddock scale by levels well above the 10% target by better summer weed control (37–140%), inclusion of break crops (16–83%), earlier sowing of appropriate varieties (21–33%) and matching N supply to soil type (91% on deep sands). Capturing synergies from combinations of pre- and in-crop management could increase wheat yield at farm scale by 11–47%, and significant on-farm validation and adoption of some innovations has occurred during the Initiative. An ex post economic analysis of the Initiative estimated a benefit : cost ratio of 3.7 : 1, and an internal return on investment of 18.5%. We briefly review the structure and operation of the initiative and summarise some of the key strategies that emerged to improve WUE at paddock and farm-scale.

Quantifying the benefits of accounting for yield potential in spatially and seasonally responsive nutrient management in a Mediterranean climate

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) (FS 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 < 220 mm). Significant improvements to the F&S were achieved with a few simple adjustments. With the addition of a variable intercept (dependent upon GSR), accounting for stored soil water at the start of the season and placing a cap on GSR that is a function of the soil PAWC, the predictive performance (RMSE 624 kg/ha) was similar to that gained with the daily time-step model APSIM (RMSE 419 kg/ha). The improved method gave more realistic estimates of water-limited potential yield, particularly at low and high rainfall and on soils of low PAWC.

Mapping subsoil acidity and shallow soil across a field with information from yield maps, geophysical sensing and the grower

Crop yield potential is a chief determinant of nutrient requirements, but there is little objective information available on the gains in profitability that can be made by accounting for the influences of soil type and season on yield potential when making fertiliser decisions. We conducted such an assessment using crop growth simulation coupled to nutrient response curves for wheat-growing at 4 locations in the low-medium rainfall zone of Western Australia. At each location, the yield potential was simulated on 10 soil types with plant-available water capacity (PAWC) ranging from 34 to 134 mm, which represent the major soils types in Western Australia. Soil survey maps were available to quantify soil type variability and the historical climate record (1974–2005) for seasonal variability. The benefits possible for fertiliser (NPK) management that takes account of variation in crop yield potential due to season and soil type by having ‘perfect knowledge’ ranged from

Use of EM38 and Gamma Ray Spectrometry as Complementary Sensors for High-Resolution Soil Property Mapping

2 to 40/ha. Seasonal variation was more important than soil type for the better soils (high PAWC), providing two-thirds of the benefit of perfect knowledge. On low PAWC soils, knowledge of soils and seasonal influences on yield potential were similar contributors to profit gains. An assessment of one yield forecasting system showed that about 50% of the maximum gains could be captured if seasons could be categorised as below, at, or above average at the time the fertiliser decision is made. In each catchment, 30–40% of fields showed scope for benefits in accounting for within-field variation in soil type due to large variation in PAWC, and therefore yield. Maximum profit gains and reductions in nutrient excess were greater in the low rainfall locations and also on the low PAWC soil types.

Deep-drainage control and yield: the trade-off between trees and crops in agroforestry systems in the medium to low rainfall areas of Australia

Management decisions, such as subsoil liming or varying fertilizer inputs to take account of soil depth and anticipated yields require knowledge of where subsoil constraints to root growth occur across the field. We used selected yield maps based on criteria derived from crop simulation, apparent soil electrical conductivity (ECa), gamma-ray emission maps and a soil type map drawn by the grower to predict the spatial distribution of subsoil acidity and shallow soil across a field. Yield maps integrate the effects of variation in soil and climate, and it was only under specific seasonal conditions that subsoil constraints depressed yields. We used crop simulation modelling to select yield maps with a large information content on the spatial distribution of these constraints and to omit those with potentially misleading information. Yield and other spatial data layers were used alone or in combination to develop subsoil mapping options to accommodate differences in data availability, access to precision agriculture techniques and the grower’s aptitude and preference. One option used gamma-ray spectrometry and EM38 survey as a dual-sensing system to improve data interpretation. Gamma-ray spectrometry helped to overcome the inability of current ECa-based methods to sense soil depth in highly weathered sandy soil over cemented gravel. A feature of the approaches presented here is the use of grower and agronomist knowledge, and experience to help interpret the spatial data layers and to evaluate which approach is most suitable and likely to be adopted to suit an individual.

Capturing the in-field spatial-temporal dynamic of yield variation

Apparent soil electrical conductivity (ECa) is related to soil properties such as clay and water content, clay mineralogy, and depth to textural contrast – and hence to plant-available soil water storage capacity (PAWC). High spatial resolution sensing of ECa, coupled with local field calibration, has been used to map expensive-to-measure soil properties, interpret yield maps, locate leaky areas for water and nitrate, and manage the land. Multiple factors affecting ECa is a weakness of the method. Salinity interferes with data interpretation, and the method cannot distinguish between sandy soils and gravels which have similar and low ECa. Therefore soil depth and PAWC cannot be estimated in shallow soils over gravels. Gamma ray spectrometry is relatively new to soil sensing and has shown promise to estimate clay content, PAWC, soil depth, and other soil properties. It is insensitive to common salt, but again it is difficult to interpret gamma ray emission data alone, as clays and gravels result in similarly strong signals. This work provides an approach to overcoming the weaknesses of the single-sensor data by developing a rule-based method for dual EM38–gamma radiometric sensor interpretation to infer soil properties. Simple rules are developed and used to identify soil types (ranging from coarse-textured sands to clay and areas of shallow soils <40 cm deep) and soil acidification risks. The rules are guided by the grower’s soil map and validated with published maps of soil pH and depth. The dual-sensor method overcomes the weakness of the single-sensor data and has the potential to compensate sparsely sampled measurements and estimate their spatial distribution at high resolution in complex field situations without the need for expensive and extensive direct sampling and measurements.

Temporal and spatial patterns of salinity in a catchment of the central wheatbelt of Western Australia

In the dryland cropping areas of southern Australia, at risk from dryland salinity, tree belts can improve water management by taking up water unused by crops, with the risk that crop yield will be reduced through competition. As there are few direct markets for tree products grown in the medium to low rainfall areas, the design of agroforestry systems becomes important in reducing the trade-off in crop yield. This study examined some factors that influence the trade-off between crop yield and deep-drainage control in order to develop design guidelines for medium to low rainfall agroforestry. Twenty-one sites in the grain-growing region of Western Australia and southern New South Wales were surveyed over 2 years for crop yields, tree leaf area index, and estimated recharge, providing data from 32 tree-crop interfaces on the relative influence of environmental factors and farming system characteristics on the trade-off between water management and crop yield. The factors most strongly correlated with higher yields were water-gaining sites, orientation that provided shelter from southerly to north-westerly (S, SW, W, NW) winds, and tree age ( 10 years), lighter soil types, and low rainfall (<400 mm). Economic analysis of the trade-off required to produce a particular deep- drainage reduction target produced 3 groups of sites: (1) those where trees resulted in a gross margin increase of

Integrating farmer knowledge, precision agriculture tools, and crop simulation modelling to evaluate management options for poor-performing patches in cropping fields

15/ha and an estimated deep-drainage reduction of 52% (n = 3), (2) those with a gross margin loss of

Integrating the effects of climate and plant available soil water holding capacity on wheat yield

49/ha and estimated deep-drainage reduction of 47% (n = 11), and (3) those with a gross margin loss of