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Irrigation Informatics IRRIGATION INFORMATICS Addressing poor irrigation decision support system uptake Nicholas John Car ORCID: 0000-0002-8742-7730 Philosophy Doctorate June, 2019 Melbourne School of Engineering The University of Melbourne This thesis is being submitted in total fulfilment of the degree Abstract Irrigation Decision Support Systems (DSS), in the first decade and a half of the 21st century, suffered from a lack of uptake by their target audience, namely farmers, according to a number of researchers in Australia and overseas. Reasons for this were proposed and solutions to overcome them explored. These included a “gap” between DSS research/development practice and on-farm practice with a solution being to involve irrigation practitioners in the planning and development of DSS; so-called participatory action research. The wider irrigation research community also undertook forms of social science investigation, such as surveys and networked interviewing, to better understand real-world irrigation decision making. That work did not evaluate, in any depth, the utility to farmers of new styles of DSS delivery based on the profound telecommunications and information technology changes in the early 2000s. Nor did that work much look to how decision-making in general may be better catered for via DSS. This thesis does these things by investigating approaches taken to assist irrigation DSS uptake in the field of informatics – the science of information. The fundamental hypothesis being tested is that it is supposed there are real gains to be made in both improving the technical delivery mechanics of irrigation DSS’ advice to farmers and the better staging of that advice through better technical handling of aspects of decision theory. Related here are several experiments conducted over the decade 2007 – 2017. They look at how: ¨ information has been, and could be, presented to irrigators to help them use it; ¨ more sources of knowledge used by irrigators, perhaps available but not currently used, could be incorporated into DSS to make them more relevant to real-world practice; ¨ the decisions that DSS hope to assist with can be modelled themselves, as distinct from biophysical irrigation modelling, in order to empirically determine irrigation best-practice and communicate decision norms. Additionally, work over time for this thesis has shed some insights into how changing technology availability, use and general acceptance on Australian farms has shifted the goalposts of DSS uptake. This thesis shows that: ¨ there have been, and are likely to continue to be, real gains to be made in the adoption of DSSs through technical system design such as user interface design; ¨ through both improving DSS design and growing data availability via technology change, the range of data sources available for and used by DSS is growing and this is likely to assist with their uptake. This is due to them being able to incorporate more data sources used in real-world decision making; ii ¨ some issues preventing DSS uptake have disappeared due to technology change on Australian farms, some remain and new ones have appeared; ¨ decision modelling, as opposed to biophysical or economic modelling, has not really been undertaken by irrigation DSS designers and yet there are both existing decision modelling systems that designers could use and the potential to create other, better, models which may help with uptake. Recommended future investigations from this work are: ¨ addressing the newly emergent issue of ‘data deluge’ which is beginning to plague DSS designers; which source of weather or commodity price should they use? A utility assessment of similar sources of data could be conducted; ¨ building of collections of real-world irrigation decisions made, modelled using approaches from this thesis, and the testing of automated approaches for assessing their outcome. This would test the practicality of empirical decision- modelling-based DSS; ¨ testing of the utility to irrigators of decision-modelling-enabled DSS. If current problems facing farmers can be matched to real-world best-practice, does this offer superior utility to calculated, theoretical best-practice? iii Declaration I, Nicholas John Car, declare that: ♦ This thesis comprises only my original work towards the PhD except where indicated in the preface. ♦ Due acknowledgement has Been made in the text to all other material used ♦ This thesis is fewer than the maximum word limit in length (100,000 words), exclusive of taBles, maps, BiBliographies and appendices. Signed: ____________________ Date: _________________ iv Preface Papers Here follows a description of work towards this thesis carried out in collaboration with others. Indicated are the portions of the work which I, Nicholas John Car, claim as original. Journal Articles The following journal articles are related to this PhD: 1. Car, N.J. (2018) Using decision models to enable better irrigation Decision Support Systems. In Computers & Electronics in Agriculture, September 2018, 152; 290- 301, ISSN 01681-699; DOI: 10.1016/j.compag.2018.07.024 ¨ 100% contribution: sole author 2. N.J. Car (2017) Tracking the value of an innovation through the new product development process: The IrriSat family of agricultural decision support system tools. In Australasian Agribusiness Perspectives, Volume 20, Paper 6, ISSN:1442- 6951, https://blog.une.edu.au/australasian-agribusiness-perspectives/ 2017/10/24/lessons-in-new-product-development-irrisat/ ¨ 100% contribution: sole author 3. Jonathan Yu, Benjamin Leighton, Nicholas Car, Shane Seaton, Jonathan Hodge (2016) The eReefs data brokering layer for hydrological and environmental data. In Journal of Hydroinformatics Mar 2016, 18 (2) 152-167; DOI: 10.2166/hydro.2015.165 ¨ 20% contribution: authorship proportion share equally between co- authors 4. Nicholas J. Car, Evan W. Christen, John W. Hornbuckle, Graham A. Moore (2012) Using a mobile phone Short Messaging Service (SMS) for irrigation scheduling in Australia – Farmers’ participation and utility evaluation. In Computers and Electronics in Agriculture, June 2012, 84, 132-143, ISSN 0168-1699, DOI: 10.1016/j.compag.2012.03.003 ¨ 75% contribution: primary author with editorial assistance from co- authors only v Conference Papers The following conference papers are related to this PhD: 1. Car, N.J. (2017). Modelling causes for actions with the Decision and PROV ontologies. In Syme, G., Hatton MacDonald, D., Fulton, B. and Piantadosi, J. (eds) MODSIM2017, 22nd International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2017, pp. 894–900. ISBN: 978-0-9872143-7-9. http://mssanz.org.au/modsim2017/C2/car.pdf ¨ 100% contribution: sole author 2. Car, N.J., Ip, A. and Druken, K. (2017) netCDF-LD SKOS: demonstrating Linked Data vocabulary use within netCDF-compliant files. In: Denzer R., Argent R.M., Schimak G., Hřebíček J. (eds) Environmental Software Systems. Infrastructures, Services and Applications. ISESS 2017. IFIP Advances in Information and Communication Technology, vol 448. Springer, Cham. http://www.isess2017.org/res/file/presentations/P04-Car.pdf ¨ 50% contribution: primary author with assistance from co-authors 3. Vleeshouwer J., Car N.J., Hornbuckle J. (2015) A Cotton Irrigator’s Decision Support System and Benchmarking Tool Using National, Regional and Local Data. In: Denzer R., Argent R.M., Schimak G., Hřebíček J. (eds) Environmental Software Systems. Infrastructures, Services and Applications. ISESS 2015. IFIP Advances in Information and Communication Technology, vol 448. Springer, Cham, DOI: 10.1007/978-3-319-15994-2_18 ¨ 33.3% contribution: authorship proportion shared equally 4. Yu J., Car N.J., Leadbetter A., Simons B.A., Cox S.J.D. (2015) Towards Linked Data Conventions for Delivery of Environmental Data Using netCDF. In: Denzer R., Argent R.M., Schimak G., Hřebíček J. (eds) Environmental Software Systems. Infrastructures, Services and Applications. ISESS 2015. IFIP Advances in Information and Communication Technology, vol 448. Springer, Cham, DOI: 10.1007/978-3-319-15994-2_9 ¨ 25% contribution: authorship proportion shared equally 5. Car N.J. and G.A. Moore (2011) Bridging the gap between modelling advice and irrigator solutions through empirical reasoning techniques. In Chan, F., Marinova, D. and Anderssen, R.S. (eds) MODSIM2011, 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2011, pp. 1652-1658. ISBN: 978-0-9872143-1-7. http://mssanz.org.au/modsim2011/B1/car.pdf ¨ 75% contribution: lead author, editorial assistance from co-author only 6. Car N.J. and G.A. Moore (2011) Towards standardising irrigation DSS inputs data formats through adaptation of the WDTF/WaterML. In Chan, F., Marinova, D. and Anderssen, R.S. (eds) MODSIM2011, 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, vi December 2011, pp. 1652-1658. ISBN: 978-0-9872143-1-7. http://mssanz.org.au/modsim2011/I1/car.pdf ¨ 75% contribution: lead author, editorial assistance from co-author only 7. Car, N.J., J.W. Hornbuckle, E.W. Christen and G.A. Moore (2009) Irrigation modelling language for decision support. In Anderssen, R.S., R.D. Braddock and L.T.H. Newham (eds) 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation,
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