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The stable isotopic composition of water vapour provides information about moisture sources and processes that is difficult to obtain with traditional measurement techniques. Recently, it has been proposed that the D-excess (dv = δ2H - 8 × δ18O) of water vapour can provide a diagnostic tracer of continental moisture recycling. However, D-excess exhibits a diurnal cycle that has been observed across a variety of ecosystems and may be influenced by a range of processes beyond regional scale moisture recycling, including local evaporation (ET) fluxes. There is a lack of measurements of D-excess in evaporation (ET) fluxes, which has made it difficult to assess how ET fluxes modify the D-excess in water vapour (dv). With this in mind, we employed a chamber based approach to directly measure D-excess in ET (dET) fluxes. We show that ET fluxes imposed a negative forcing on the ambient vapour and could not explain the higher daytime dv values. The low dET observed here was sourced from a soil water pool that had undergone an extended drying period, leading to low D-excess of the soil moisture. A strong correlation between daytime dv and locally measured relative humidity was consistent with an oceanic moisture source, suggesting that remote hydrological processes were the major contributor to daytime dv variability. During the early evening, ET fluxes into a shallow nocturnal inversion layer caused a lowering of the dv values near the surface. In addition, transient mixing of vapour with a higher D-excess from above the nocturnal inversion modified these values, causing large within night variability. These results indicate dET can generally be expected to show large spatial and temporal variability and to depend on the soil moisture state. For long periods between rain events, common in semi-arid environments, ET would be expected to impose negative forcing on the surface dv. The variability of D-excess in ET fluxes therefore needs to be considered when using dv to study moisture recycling and during extended dry periods may act as a tracer of the relative humidity of the oceanic moisture source. [ABSTRACT FROM AUTHOR]

Monitoring the development of vegetation height through time provides a key indicator of crop health and overall condition. Traditional manual approaches for monitoring crop height are generally time consuming, labor intensive and impractical for large-scale operations. Dynamic crop heights collected through the season allow for the identification of within-field problems at critical stages of the growth cycle, providing a mechanism for remedial action to be taken against end of season yield losses. With advances in unmanned aerial vehicle (UAV) technologies, routine monitoring of height is now feasible at any time throughout the growth cycle. To demonstrate this capability, five digital surface maps (DSM) were reconstructed from high-resolution RGB imagery collected over a field of maize during the course of a single growing season. The UAV retrievals were compared against LiDAR scans for the purpose of evaluating the derived point clouds capacity to capture ground surface variability and spatially variable crop height. A strong correlation was observed between structure-from-motion (SfM) derived heights and pixel-to-pixel comparison against LiDAR scan data for the intra-season bare-ground surface (R2 = 0.77 − 0.99, rRMSE = 0.44% − 0.85%), while there was reasonable agreement between canopy comparisons (R2 = 0.57 − 0.65, rRMSE = 37% − 50%). To examine the effect of resolution on retrieval accuracy and processing time, an evaluation of several ground sampling distances (GSD) was also performed. Our results indicate that a 10 cm resolution retrieval delivers a reliable product that provides a compromise between computational cost and spatial fidelity. Overall, UAV retrievals were able to accurately reproduce the observed spatial variability of crop heights within the maize field through the growing season and provide a valuable source of information with which to inform precision agricultural management in an operational context. [ABSTRACT FROM AUTHOR]