A tool for monitoring soil water using modelling, on-farm data, and mobile technology. (June 2018)

• Record Type: Journal Article
• Authors: Freebairn, D.M.; Ghahramani, A.; Robinson, J.B.; McClymont, D.J.
• Is Part Of: Environmental modelling & software. Volume 104(2018)
• Page Start: 55
• Page End: 63
• Publication Date: 2018-06
• Subjects: Decision support -- Soil water -- Water balance -- Monitoring -- Modelling -- App; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2018.03.010
• Languages: English
• ISSNs: 1364-8152

Abstract

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. Highlights: SoilWaterApp is reliable to predict PAW and total crop water supply. Uncertainty and cost of field observations makes virtual monitoring preferable. App-based estimate of PAW across paddocks and soil types is reliable and adaptable. SoilWaterApp is a practical approach for decision making of farmers & consultants.