In plant breeding, unmanned aerial vehicles (UAVs) carrying multispectral cameras have demonstrated increasing utility for high-throughput phenotyping (HTP) to aid the interpretation of genotype and environment effects on morphological, biochemical, and physiological traits. A key constraint remains the reduced resolution and quality extracted from stitched mosaics generated from UAV missions across large areas. This can be addressed by generating high-quality reflectance data from a single nadir image per plot. In this study, a pipeline was developed to derive reflectance data from raw multispectral UAV images that preserve the original high spatial and spectral resolutions and to use these for phenotyping applications. Sequential steps involved (i) imagery calibration, (ii) spectral band alignment, (iii) backward calculation, (iv) plot segmentation, and (v) application. Each step was designed and optimised to estimate the number of plants and count sorghum heads within each breeding plot. Using a derived nadir image of each plot, the coefficients of determination were 0.90 and 0.86 for estimates of the number of sorghum plants and heads, respectively. Furthermore, the reflectance information acquired from the different spectral bands showed appreciably high discriminative ability for sorghum head colours (i.e., red and white). Deployment of this pipeline allowed accurate segmentation of crop organs at the canopy level across many diverse field plots with minimal training needed from machine learning approaches.

Precipitation (P) and evapotranspiration (ET) are the key factors determining water availability for water resource management activities in river basins. While global P and ET data products have become more accessible, their performances in river basins with a diverse climate and landscape remain less discussed. This paper evaluated the performance of four representative global P (CHIRPS_P, GLDAS_P, TRMM_P and Persiann_P) and ET products (CSIRO_ET, GLDAS_ET, MOD_ET and TerraClimate_ET) against the reference data provided by the Australian Water Availability Project (AWAP) in the Murray Darling Basin (MDB) of Australia. The disparities among the data products both in the period from 2001 to 2016 and across the 22 catchments of MDB were related to a set of catchment characteristics (climate, terrain, etc.) to explore any possible contributors. The results show that the four global P products presented overall high consistency with AWAP_P across the MDB catchments except in southeastern catchments with abundant rainfalls and large terrain variations. The Penman–Monteith algorithm based MOD_ET underestimated ET in the MDB, especially in the arid, less vegetation covered catchments. While the CSIRO_ET, which also estimated with the Penman–Monteith method, presented overall better estimations, which can be attributed to the better parameterization of the landscape in the simulation processes. The hydrological model based TerraClimate_ET showed overall good consistency with AWAP_ET except in the arid catchments, which might be attributed to the simplified water balance model it applied, however it did not adequately reflect the intensive ground water uses in these catchments. The findings indicated that basin and catchment characteristics had impacts on the accuracy of global products and therefore provided important implications for choosing appropriate product and/or conducting field calibrations for potential users in large basins characterized with diverse rainfall, terrain variations and land use patterns.

Evapotranspiration (ET) is a critical component of the water and energy balance of climate–soil–vegetation interactions and can account for a water loss of about 90% in arid regions. It is recognized that there are differences among different ET products, but it is not known what the range of this difference is and to what extent it impacts on water resources and ecosystem management. In this study, we assess the effects of value differences of five representative ET products on water resources and ecosystem management in the Murrumbidgee River catchment in Australia. The results show there are obvious differences in the annual and monthly ET values among these five ET products, which lead to huge differences on the estimations of mean annual runoff, soil water storage changes, and yearly irrigation water per area. Meanwhile, they result in different relationships between the annual gross primary productivity and ET and different water-use efficiency values for both forest and grassland, but the influence of ET variations on forest is less obvious than on grassland. The effects of the variations among the ET products on water resources and ecosystem management are remarkable and need to be the subject of more attention.