A parametric bio-economic model of monthly irrigation water demands in the Murray-Darling Basin
Irrigation water demands in hydrologic models are typically simulated using bio-physical crop water balances, ignoring the economic behaviour of farmers and their responses to water and crop prices. This study develops a bio-economic model of monthly irrigation water demand that integrates bio-physical crop water requirements with an economic profit maximisation framework, yielding simple parametric equations for annual crop areas and monthly water use as a function of weather and prices. Parameters are estimated via structural estimation, solving a joint system of physical and behavioural regression equations by non-linear least squares. Applied to the Australian Murray-Darling Basin, the model explains 94% of annual variation in southern basin water use (cross-validated NSE- R² 0.90). The model is applied to measure long-term adjustment in the irrigation sector, revealing a 40% increase in peak summer water demand in the lower-Murray since 2007 due to an expansion of almond plantings. This bio-economic framework provides an empirical foundation for new integrated hydro-economic models capable of simulating irrigation sector responses to long-term changes in water availability and climate. • Our bio-economic model combines crop water processes and profit maximisation • Structural estimation yields parametric equations for crop water use and area • Monthly irrigation demand estimated for the Murray-Darling Basin, 2004–2022 • Cross-validated R² of 0.90 for annual water use in the southern basin • Almond expansion drove a 40% rise in peak summer demand in the lower Murray
Authors
- Rhys Downham
- Maruge Zhao (ORCID: https://orcid.org/0000-0002-4538-8630)
- Neal Hughes
Institutions
- Australian Bureau of Agricultural and Resource Economics and Sciences (AU)
Publication Details
- Journal
- Agricultural Water Management
- Published
- 2026-05-08
- DOI
- https://doi.org/10.1016/j.agwat.2026.110411
- Primary Topic
- Water resources management and optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Department of Climate Change, Energy, the Environment and Water