Digital soil mapping of available water content using proximal and remotely sensed data

Abstract

Two‐thirds of all irrigated agriculture in Australia is undertaken within the Murray–Darling Basin. However, climate change predictions for this region suggest rainfall will decrease. To maintain profitability, more will need to be done by irrigators with less water. In this regard, irrigators need to be aware of the spatial distribution of the available water content (AWC) in the root‐zone (i.e. 0.0–0.90 m). To reduce the cost, digital soil mapping (DSM) techniques are being used to map soil properties related to AWC (e.g. soil texture). The purpose of this study was to create a DSM of the AWC at the district scale. This is achieved by determining AWC by the difference between laboratory measured permanent wilting point (PWP) and field capacity (FC) and using pressure plate apparatus. The PWP and FC data are coupled to remote (i.e. gamma‐ray spectrometry) and proximal (i.e. EM38 and EM34) sensed data and two trend surface parameters. Using a hierarchical spatial regression (HSR), we predict PWP and FC across the areas of Warren and Trangie in the lower Macquarie valley, Australia. The reliability of the DSM of PWP and FC were compared using prediction precision (RMSE – root mean square error) and bias (ME – mean error). The best results were achieved using EM38‐v, EM34‐20, eU and eTh. The DSM map of AWC is consistent with known Pedoderms and provides a basis for agricultural water management.

Digital soil assessment for regional agricultural land evaluation

“…DSM has become the preferred method for many soil mapping applications (e.g. Mansuy et al, 2014;Gooley et al, 2014) and is the technique being adopted to deliver a soil map of the world (Arrouays et al, 2014).…”

terraGIS – a web GIS for delivery of digital soil maps in cotton‐growing areas of Australia

“…This was the approach used by Gooley et al . () and in the lower Macquarie valley, when they estimated the AWC using measured PWP and FC, it was made more efficient by developing hierarchical spatial regression models that were applicable in both areas.…”

“…In addition, and owing to the proximity of some areas to each other it may be possible that calibration equations could be developed and which could be used across more than one area. This was the approach used by Gooley et al (2014) and in the lower Macquarie valley, when they estimated the AWC using measured PWP and FC, it was made more efficient by developing hierarchical spatial regression models that were applicable in both areas.…”

A Cloud Computing-Enabled Spatio-Temporal Cyber-Physical Information Infrastructure for Efficient Soil Moisture Monitoring

“…The monitoring of SM with sensors, commonly aboard satellites, is an active research area [10,11]. In addition to the use of in situ sensors in SM monitoring [12,13], Earth Observation data (EOD) are also widely applied in SM monitoring [14,15]. The Open Geospatial Consortium (OGC)'s Sensor Web Enablement initiative defines a sensor web as an infrastructure enabling access to sensor networks and archived sensor data that can be discovered and accessed using standard protocols and interfaces [16].…”