**6. Conclusions**

Irrigation areas have a complex history (spatially and temporally) with respect to the timing of irrigation development, water use e fficiency, drainage, climate, and crop type, among other factors. This complexity can lead to a lack of transparency, obscure interpretation, and require additional resources and skills to represent it appropriated within a modelling framework. Any new methodology has to ensure that it does not add to the complexity of prior approaches and it must be widely applicable. Our development of the transfer function and integrated modelling was cognisant of these considerations. It attempted to simulate the transmission of the unsaturated zone with as few parameters as possible. It implemented a flexible method that can be applied in other semi-arid environments where there is a deep vadose zone. It makes use of existing datasets and attempts to use all of these datasets more thoroughly to calibrate and constrain the model outputs.

This paper described an integrated methodology for the estimation of groundwater returns to streams from irrigation areas with deep vadose zones and perched water tables. This methodology was implemented for an irrigation district in south-eastern Australia, adjacent to the lower reaches of the River Murray. An existing surface water balance model and the spatial distribution of the historical irrigation development were used to assess irrigation accessions to the unsaturated zone. A recently developed unsaturated zone model [22,23] estimated the groundwater recharge from the irrigation accession. Two di fferent implementations of a groundwater model using these data were compared to a pre-existing groundwater model by using recharge calibrated using groundwater responses. In the first implementation, the newly estimated recharge values replaced the recharge values in the pre-existing model, that is, the saturated zone properties were the same. In the second implementation, a new set ofsaturatedzoneparameterswerecalibrated.

 The study has shown that


Further work is required to optimize the calibration methodology, standardise scripting approaches, and test the method in other vadose zone settings.

**Author Contributions:** Conceptualization, G.W.; data curation, D.C., T.L., and K.B.; formal analysis, D.C., T.L., G.W., and T.S.; funding acquisition, D.C. and J.W.; investigation, D.C., T.L., G.W., and T.S.; methodology, D.C., T.L., and G.W.; project administration, D.C.; software, T.L., G.W., and T.S.; supervision, G.W. and J.W.; writing—original draft, D.C.; writing—review and editing, G.W. and J.W. All authors have read and agreed to the published version of the manuscript.

**Funding:** The authors would like to thank the Murray-Darling Basin Authority (MDBA) and the Department of Environment and Water, South Australia (DEW), for funding support.

**Acknowledgments:** The authors would like to thank and acknowledge Emmanuel Xevi for his support throughout this work program, and Hugh Middlemis, Ray Evans, and Prathapur for technical advice.

**Conflicts of Interest:** The authors declare no conflict of interest.
