A tool for monitoring soil water using modelling, on-farm data, and mobile technology

Article


Freebairn, D. M., Ghahramani, A., Robinson, J. B. and McClymont, D. J.. 2018. "A tool for monitoring soil water using modelling, on-farm data, and mobile technology." Environmental Modelling and Software. 104, pp. 55-63. https://doi.org/10.1016/j.envsoft.2018.03.010
Article Title

A tool for monitoring soil water using modelling, on-farm data, and mobile technology

ERA Journal ID4673
Article CategoryArticle
AuthorsFreebairn, D. M. (Author), Ghahramani, A. (Author), Robinson, J. B. (Author) and McClymont, D. J. (Author)
Journal TitleEnvironmental Modelling and Software
Journal Citation104, pp. 55-63
Number of Pages9
Year2018
PublisherElsevier
Place of PublicationUnited Kingdom
ISSN1364-8152
1873-6726
Digital Object Identifier (DOI)https://doi.org/10.1016/j.envsoft.2018.03.010
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S1364815217312422
Abstract

Rainfall is low and unreliable in much of Australia's dryland cropping areas, requiring well-informed crop management for optimising yield and profit. Growing-season rainfall is usually supplemented by soil water during fallow periods preceding a crop. While rainfall is conveniently measured, the difficulty of measuring a soil's plant available water (PAW, mm) has led to using simulation models for estimating PAW. Here we developed a smartphone application (app) that simulates soil water balance by accessing weather, soil and crop data from databases and on-farm records. Predictions of PAW using the Howleaky modelling engine were compared with field measurements. Validation of the simulation engine across sites in Australian cropping areas showed good agreement between simulated and measured PAW. Errors in model estimates are compared with variability found within small fields. We conclude that estimating PAW for paddocks using a simulation model built in a smartphone app is a reliable and adaptable technology.

Keywordsdecision support; soil water; water balance; monitoring; modelling; app
ANZSRC Field of Research 2020300208. Farm management, rural management and agribusiness
300207. Agricultural systems analysis and modelling
410605. Soil physics
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File reproduced in accordance with the copyright policy of the publisher/author.

Byline AffiliationsNational Centre for Engineering in Agriculture
Institute for Agriculture and the Environment
DHM Environmental Software Engineering, Australia
Institution of OriginUniversity of Southern Queensland
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Modelling deep drainage rates of irrigation strategies under cropping sequence in subhumid, subtropical Australia
Kodur, S. and Robinson, J. B.. 2014. "Modelling deep drainage rates of irrigation strategies under cropping sequence in subhumid, subtropical Australia ." Irrigation and Drainage. 63 (3), pp. 365-372. https://doi.org/10.1002/ird.1813
Deep drainage estimates for irrigated crop rotations in subhumid, subtropical Australia
Kodur, S., Robinson, J. B., Foley, J. L. and Silburn, D. M.. 2014. "Deep drainage estimates for irrigated crop rotations in subhumid, subtropical Australia." Irrigation and Drainage. 63 (5), pp. 692-697. https://doi.org/10.1002/ird.1872
Soil-hydrological responses to rainfall variation in a subtropical Australian landscape
Kodur, S., Robinson, J. B., Foley, J. L. and Silburn, D. M.. 2015. "Soil-hydrological responses to rainfall variation in a subtropical Australian landscape." Irrigation and Drainage. 64 (5), pp. 694-702. https://doi.org/10.1002/ird.1946
Controlled traffic farming restores soil structure
McHugh, A. D., Tullberg, J. N. and Freebairn, D. M.. 2009. "Controlled traffic farming restores soil structure." Soil and Tillage Research. 104 (1), pp. 164-172. https://doi.org/10.1016/j.still.2008.10.010
Seasonal climate forecasting for better irrigation system management in Lombok, Indonesia
McClymont, David, Zhang, Xike, Dutta, Sunil, White, Simon, Yasin, Ismail, Idris, Husni, Yakin, Addinul, Ma'shum, Mansur, Suriadi, Ahmad and Surana, Ir.. 2009. Seasonal climate forecasting for better irrigation system management in Lombok, Indonesia. Canberra, Australia. Australian Centre for International Agricultural Research.
Developing ENSO-based irrigation water forecast system in a region with limited hydro-meteorological observations to mitigate the impacts of climate variability: a case study in Lombok, Indonesia
Zhang, X., Abawi, Yahya, Dutta, Sunil and McClymont, David. 2010. "Developing ENSO-based irrigation water forecast system in a region with limited hydro-meteorological observations to mitigate the impacts of climate variability: a case study in Lombok, Indonesia." Climate Adaptation Futures: Preparing for the Unavoidable Impacts of Climate Change (2010). Gold Coast, Australia 29 Jun - 01 Jul 2010 Brisbane, Australia.
Development of a decision support system for furrow and border irrigation
McClymont, David. 2007. Development of a decision support system for furrow and border irrigation. PhD Thesis Doctor of Philosophy. University of Southern Queensland.