Abstract
This paper describes the development of an intelligent irrigation management system that can be used by farmers to manage water allocation in the farms. Each farm is represented as a single agent that can work out the actual water required for each crop in the farm based on the crop’s drought sensitivity, growth stage, the crop coefficient value and the soil type. During water scarcity, this system can prioritise irrigation allocation to different crops on a farm. Our initial experiment showed that using the irrigation management system, the farm can achieve a consistent water reduction which is more than the required reduction. The results showed that the agent consistently recorded water reduction higher than the actual reduction required by the water authority. This significant reduction means that more water can be conserved in the farm and reallocated for other purposes.
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References
Akhbari, M., & Grigg, N. S.: A framework for an agent-based model to manage water resources conflicts. Water resources management, 27(11), 4039-4052 (2013).
Anthony, P., & Birendra, K. C.: Improving irrigation water management using agent technology. New Zealand Journal of Agricultural Research, 1-15 (2017).
Barreteau, O., Bousquet, F., Millier, C., & Weber, J.: Suitability of Multi-Agent Simulations to study irrigated system viability: application to case studies in the Senegal River Valley. Agricultural Systems, 80(3), 255-275 (2004).
Berger, T., Birner, R., Mccarthy, N., DíAz, J., & Wittmer, H.: Capturing the complexity of water uses and water users within a multi-agent framework. Water Resources Manage-ment, 21(1), 129-148 (2007).
Bellifemine, F. L., Caire, G., & Greenwood, D.: Developing multi-agent systems with JADE. Vol. 7. John Wiley & Sons (2007).
Bright, J. C.: Prepared for Irrigation New Zealand. Aqualinc Research Limited, New Zea-land (2009).
New Zealand statistics Homepage, https://www.dairynz.co.nz/, last accessed 2017/7/9.
Ding, N., Erfani, R., Mokhtar, H., & Erfani, T.: Agent Based Modelling for Water Resource Allocation in the Transboundary Nile River. Water 8(4), 139-151 (2016).
Doorenbos, Jan, Willian O. Pruitt, and A. Aboukhaled.: Crop water requirements. Food and Agriculture Organization, Rome, Italy (1997).
Foundation for Arable Research (FAR).: Irrigation management for cropping – a grower’s guide, Australia (2010).
Giuliani, M., Castelletti, A., Amigoni, F., & Cai, X.: Multiagent systems and distributed constraint reasoning for regulatory mechanism design in water management. Journal of Water Resources Planning and Management 141(4), 04014068 (2014).
Holtz, G., & Pahl-Wostl, C.: An agent-based model of groundwater over-exploitation in the Upper Guadiana, Spain. Regional Environmental Change 12(1), 95-121 (2012).
Ministry for the Environment Homepage, https://www.mfe.govt.nz/sites/default/files/media/Fresh%20water/water-allocation-use-jun04.pdf last accessed 2018/3/20.
New Zealand Parliament Homepage, https://www.parliament.nz/resource/en-NZ/00PlibCIP151/431c33c3cf20b98103fa36e28a1dee1185801174 , last accessed 2018/3/9.
Williams, J. M., & Richardson, P.: Williams, J. Morgan, and Philippa Richardson. Growing for Good, Intensive Farming, Sustainability and New Zealand’s Environment. Wellington, New Zealand (2004).
Wheeler, D.M. and Bright, J.: Comparison of OVERSEER and IrriCalc predicted irrigation and drainage depths. AgResearch. Report prepared for Overseer Management Services Limited, New Zealand (2015).
Wooldridge, M.: Agent-Based Computing. Interoperable Communication Networks 1, 71-97 (1997).
Zhao, J., Cai, X., & Wang, Z.: Comparing administered and market-based water allocation systems through a consistent agent-based modeling framework. Journal of environmental management, 123, 120-130 (2013).
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Chiewchan, K., Anthony, P., Samarasinghe, S. (2019). Agent Based Irrigation Management for Mixed-Cropping Farms. In: Alfred, R., Lim, Y., Ibrahim, A., Anthony, P. (eds) Computational Science and Technology. Lecture Notes in Electrical Engineering, vol 481. Springer, Singapore. https://doi.org/10.1007/978-981-13-2622-6_46
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DOI: https://doi.org/10.1007/978-981-13-2622-6_46
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