Irrigation benchmarking in the Murray-Darling Basin
Abstract
This project built on the framework and success of a similar project that was developed by the South Australian Research and Development Institute in the late 1990s. It reviewed the irrigation practices, yield and quality targets of over 40 selected grape growers across the Riverland, Sunraysia and Riverina regions. Information about potential drivers of irrigation practices such as irrigation infrastructure type (drip, overhead etc.) and age, diversion method, scheduling methods and production targets were compared with measured performance.
Performance against the range of indicators varied widely. For example, yield ranged from 9 to 53 t/ha, water use efficiency from 1.15 to 6.91 t/ML, cost of water per tonne of fruit from $17 to $163 /t and return per dollar of water input from $4.3 to $28.9 /$.
Comparison of potential drivers of performance indicated that water delivery method (river, pipeline or channel), irrigation scheduling method, region and system age had little impact on performance against any of the indicators. Key determinants of performance included varietal class, yield and percentage of water sourced from permanent entitlement versus the volume leased annually.
The results will inform better targeted research and extension to support the adoption of management targets and practices that improve the efficiency of irrigation use and grower profitability.
Summary
A standard set of data was collected from 43 vineyard patches (contiguous management units) across the Riverland, Sunraysia and Riverina regions. The primary data set included information about the water delivery to each site, irrigation system details, a detailed record of the irrigation schedule applied to the site over the 2021/22 season and information about grape variety, yield and quality.
These data were used to benchmark irrigation performance at these sites against six indicators; yield per hectare, yield per megalitre of water applied (also referred to as water use efficiency), gross return per megalitre, cost of water per tonne of fruit, return per dollar of water cost and irrigation efficiency. Results were sorted and graphed for each indicator, demonstrating the range in performance between the best and worst sites. The performance of individual sites varied between the performance indicators.
Additional data from each site were used to group the sites into a range of categories based on irrigation water diversion method, water source, irrigation scheduling method, target market, grape variety class and irrigation system age. Performance of the sites within each grouping was compared in order to identify which of these groupings had the greatest influence on performance.
The strongest relationships were in response to grape variety class, with white grape varieties performing better than red grape varieties. This appeared to be due to a combination of higher yields in the white varieties and higher returns per tonne for white varieties in the 2021/22 season.
The proportion of water owned as entitlement versus leased annually also contributed to variation in indicators, especially those that incorporate the cost of water. Estimated water costs were significantly increased by the additional cost of leasing water.
Other designators such as water delivery method, irrigation scheduling method, target market and irrigation system age gave much weaker responses.
Six of the sites evaluated in this study also took part in a previous benchmarking exercise (Skewes and Meissner, 1997b). Comparison of data from this study with the previous study revealed large changes in the cost structures for the viticulture industry over the past 25 years. The cost of water delivery and pumping more than tripled on average across this period, while the returns per tonne of grapes declined by 36% on average, from all-time highs at the time of the previous investigations. Both of these changes were outside the control of irrigators, but directly impacted on their performance against a number of the benchmarking indicators.