Surface renewal performance to independently estimate sensible and latent heat fluxes in heterogeneous crop surfaces

Abstract

Surface renewal (SR) analysis is an interesting alternative to eddy covariance (EC) flux measurements. We have applied two recent SR approaches, with different theoretical background, that from Castellví (2004), SRCas, and that from Shapland et al. (2012a, 2012b), SRShap. We have applied both models for sensible (H) and latent (LE) heat flux estimation over heterogeneous crop surfaces. For this, EC equipments, including a sonic anemometer CSAT3 and a krypton hygrometer KH20, were located in two zones of drip irrigated orchards of late and early maturing peaches. The measurement period was June to September 2009. The SRCas is based on similarity concepts for independent estimation of the calibration factor (, which varies with respect to the atmospheric stability. The SRShap is based on analysis of different ramp-dimensions, separating the ones that are flux-bearing from the others that are isotropic. According to the results obtained here, there was a high agreement between the 30-min turbulent fluxes independently derived by EC and SRCas. The SRShap agreement with EC was slightly lower. Estimation of fluxes determined by SRCas resulted in higher values (around 11% for LE) with respect to EC, similarly to previously published works over homogeneous canopies. In terms of evapotranspiration, the root mean square error (RMSE) between EC and SR was only 0.07 mm h-1 (for SRCas) and 0.11 mm h-1 (for SRshap) for both measuring spots. According to the energy balance closure, the SRCas method was as reliable as the EC in estimating the turbulent fluxes related to irrigated agriculture and watershed distribution management, even when applied in heterogeneous cropping systems.

Ground cover fraction (GCF) is defined as the fraction of ground beneath the canopy covered or shaded by a crop near solar noon as observed from directly overhead. GCF is a useful variable that can be determined in a variety of experimental procedures performed at a field plot scale. GCF is usually measured in experimental field plots using ceptometers or digital imagery. The use of these techniques in the field requires the presence in situ of qualified workers and do not permit the continuous recording of GCF. Thus, only a small number of measured values of GCF are available along the season. A network of pyranometers located at the ground level and above canopy can be connected to a datalogger so a continuous series of global radiation values can be recorded for long periods of time without the presence of any staff. Continuous values of daily GCF can be worked out from those readings. This approach could be particularly useful at remote, unattended sites. Nevertheless, the feasibility of such measures must be evaluated as the main constraint is that the pyranometers must be placed nearby the plant rows to avoid possible damage by the machinery used in the farm. This work presents the daily GCF estimates from pyranometer readings (‘pyranometer‐driven’ method, GCFpyr) at two experiments: a) Experiment I, at a table grape grown under a net, from February 2007 to November 2009; b) Experiment II, at a late peach orchard, from May to September 2011. In the Experiment II measurements were taken for one full irrigated, ‘control’ tree and for one ‘deficit irrigation’ tree.

The daily GCFpyr values were compared to measured values (‘reference’ method, GCFref) using either photographical techniques (table grape) or ceptometers (late peach). For computation of GCFpyr, solar radiation below and above the canopy was averaged for two time periods: a) two hours around solar noon; b) daytime period (8:00 to 18:00 Universal Time Coordinated, UTC). For both experiments, the results obtained with the ‘pyranometer‐driven’ method improved when the solar radiation was averaged for daytime periods. For the table grape vineyard (daytime averaging period), the ‘pyranometer‐driven’ method showed a good agreement with the GCFref values as shown by a mean estimation error (MEE) of 0.000, a root mean square error (RMSE) of 0.113, and an index of agreement (IA) of 0.967. For the peach orchard (daytime averaging period), the agreement of the ‘pyranometer‐driven’ method with the GCFref values was worse, particularly with the ‘deficit irrigation’ tree. MEE was 0.046 to 0.210, RMSE was 0.064 to 0.217, and IA was 0.863 to 0.232. The highest GCF attained, the larger measurement range for GCF (which involves a larger variability of sun angle above the horizon) and the presence of the net above the table grape, were the likely reasons for the better performance of GCFpyr in this crop. Further research is required to develop more appropriate calibration equations of GCFpyr taking into account the whole range of GCF variability.