Samuel Ortega-Farías

Erratum to: Estimation of actual evapotranspiration for a drip-irrigated Merlot vineyard using a three-source model

A study was performed in order to evaluate the three-source model (Clumped model) for direct estimation of actual evapotranspiration (ETa) and latent heat flux (LE) over a drip-irrigated Merlot vineyard trained on a vertical shoot positioned system (VSP) under semi-arid conditions. The vineyard, with an average fractional cover of 30%, is located in the Talca Valley, Region del Maule, Chile. The performance of the Clumped model was evaluated using an eddy covariance system during the 2006/2007 and 2007/2008 growing seasons. Results indicate that the Clumped model was able to predict ETa with a root mean square error (RMSE), mean bias error (MBE), and model efficiency (EF) of 0.33, −0.15 mm day−1 and 74%, respectively. Also, the Clumped model simulated the daytime variation of LE with a RMSE of 36 W m−2, MBE of −8 W m−2, and EF of 83%. Major disagreement (underestimated values) between observed and estimated values of ETa was found for clear days after rainfall or foggy days, but underestimated values were less than 10% of the data analysis. The results obtained in this study indicate that the Clumped model could be used to directly estimate vine water requirements for a drip-irrigated vineyard trained on a VSP. However, application of the Clumped model requires a good characterization of the drip-irrigated vineyard architecture.

Special issue on evapotranspiration measurement and modeling

Water availability for irrigation throughout the world has been reduced in recent years due to a combination of frequent droughts and competition for water resources among agricultural, industrial, and urban users. In addition, some major agricultural areas face moderate to significant reductions of rainfall, or changes in timing of stream flow due to changes in timing of snowmelt, as a result of global climate change. Under such conditions, sophisticated irrigation water management will be required to optimize water use efficiency and maintain sufficient levels of crop productivity and quality. A key factor to achieve these targets is the estimation of actual evapotranspiration (ET). Accurate determination of ET can be a viable tool in better utilization of water resources through well-designed irrigation management programs. Reliable estimates of ET are also vital to develop criteria for in-season irrigation management, water resource allocation, long-term estimates of water supply, demand and use, design and management of water resources infrastructure, and evaluation of the effect of land use and management changes on the water balance. ET is commonly calculated using grass or alfalfareference evapotranspiration (ETo) multiplied by grass or alfalfa-reference-based crop-specific coefficients (Kc). The Penman–Monteith combination equation is widely accepted as the best-performing method for reference evapotranspiration estimates from a well-watered hypothetical grass or alfalfa surface having a fixed crop height, albedo, and surface canopy resistance. The Kc is basically the ratio of ET to ETo where ET can be measured using a lysimeter, soil water balance approach, eddy covariance method, Bowen ratio energy balance system, or surface renewal method. Advances over the last two to three decades in instrumentation, data acquisition systems, remote data access, and the off-the-shelf availability of aforementioned ET measurement tools have significantly enhanced our understanding of ET and its relation to microclimatic conditions. Advances also enabled the availability and affordability of data for practitioners for use in irrigation management. While the reference ET and Kc approach provides a simple and convenient way to estimate crop water requirements for a variety of crops and climatic conditions, a major uncertainty in this approach is that many Kc values reported in the literature are empirical and often not adapted to local conditions. This is due to the fact that ratios of ET to ETo depend on nonlinear interactions of soil, crop and atmospheric conditions, and irrigation management practices. This consideration is especially Communicated by R. Evans.

Estimation of Energy Balance Components over a Drip-Irrigated Olive Orchard Using Thermal and Multispectral Cameras Placed on a Helicopter-Based Unmanned Aerial Vehicle (UAV)

A field experiment was carried out to implement a remote sensing energy balance (RSEB) algorithm for estimating the incoming solar radiation (Rsi), net radiation (Rn), sensible heat flux (H), soil heat flux (G) and latent heat flux (LE) over a drip-irrigated olive (cv. Arbequina) orchard located in the Pencahue Valley, Maule Region, Chile (35°25′S; 71°44′W; 90 m above sea level). For this study, a helicopter-based unmanned aerial vehicle (UAV) was equipped with multispectral and infrared thermal cameras to obtain simultaneously the normalized difference vegetation index (NDVI) and surface temperature (Tsurface) at very high resolution (6 cm × 6 cm). Meteorological variables and surface energy balance components were measured at the time of the UAV overpass (near solar noon). The performance of the RSEB algorithm was evaluated using measurements of H and LE obtained from an eddy correlation system. In addition, estimated values of Rsi and Rn were compared with ground-truth measurements from a four-way net radiometer while those of G were compared with soil heat flux based on flux plates. Results indicated that RSEB algorithm estimated LE and H with errors of 7% and 5%, respectively. Values of the root mean squared error (RMSE) and mean absolute error (MAE) for LE were 50 and 43 W m−2 while those for H were 56 and 46 W m−2, respectively. Finally, the RSEB algorithm computed Rsi, Rn and G with error less than 5% and with values of RMSE and MAE less than 38 W m−2. Results demonstrated that multispectral and thermal cameras placed on an UAV could provide an excellent tool to evaluate the intra-orchard spatial variability of Rn, G, H, LE, NDVI and Tsurface over the tree canopy and soil surface between rows.

Parameterization of the Satellite-Based Model (METRIC) for the Estimation of Instantaneous Surface Energy Balance Components over a Drip-Irrigated Vineyard

A study was carried out to parameterize the METRIC (Mapping EvapoTranspiration at high Resolution with Internalized Calibration) model for estimating instantaneous values of albedo (shortwave albedo) (αi), net radiation (Rni) and soil heat flux (Gi), sensible (Hi) and latent heat (LEi) over a drip-irrigated Merlot vineyard (location: 35°25′ LS; 71°32′ LW; 125 m.a.s. (l). The experiment was carried out in a plot of 4.25 ha, processing 15 Landsat images, which were acquired from 2006 to 2009. An automatic weather station was placed inside the experimental plot to measure αi, Rni and Gi. In the same tower an Eddy Covariance (EC) system was mounted to measure Hi and LEi. Specific sub-models to estimate Gi, leaf area index (LAI) and aerodynamic roughness length for momentum transfer (zom) were calibrated for the Merlot vineyard as an improvement to the original METRIC model. Results indicated that LAI, zom and Gi were estimated using the calibrated functions with errors of 4%, 2% and 17%, while those were computed using the original functions with errors of 58%, 81%, and 5%, respectively. At the time of satellite overpass, comparisons between measured and estimated values indicated that METRIC overestimated αi in 21% and Rni in 11%. Also, METRIC using the calibrated functions overestimated Hi and LEi with errors of 16% and 17%, respectively while it using the original functions overestimated Hi and LEi with errors of 13% and 15%, respectively. Finally, LEi was estimated with root mean square error (RMSE) between 43 and 60 W∙m−2 and mean absolute error (MAE) between 35 and 48 W∙m−2 for both calibrated and original functions, respectively. These results suggested that biases observed for instantaneous pixel-by-pixel values of Rni, Gi and other intermediate components of the algorithm were presumably absorbed into the computation of sensible heat flux as a result of the internal self-calibration of METRIC.

Estimating Evapotranspiration of an Apple Orchard Using a Remote Sensing-Based Soil Water Balance

The main goal of this research was to estimate the actual evapotranspiration (ETc) of a drip-irrigated apple orchard located in the semi-arid region of Talca Valley (Chile) using a remote sensing-based soil water balance model. The methodology to estimate ETc is a modified version of the Food and Agriculture Organization of the United Nations (FAO) dual crop coefficient approach, in which the basal crop coefficient (Kcb) was derived from the soil adjusted vegetation index (SAVI) calculated from satellite images and incorporated into a daily soil water balance in the root zone. A linear relationship between the Kcb and SAVI was developed for the apple orchard Kcb = 1.82·SAVI − 0.07 (R2 = 0.95). The methodology was applied during two growing seasons (2010–2011 and 2012–2013), and ETc was evaluated using latent heat fluxes (LE) from an eddy covariance system. The results indicate that the remote sensing-based soil water balance estimated ETc reasonably well over two growing seasons. The root mean square error (RMSE) between the measured and simulated ETc values during 2010–2011 and 2012–2013 were, respectively, 0.78 and 0.74 mm·day−1, which mean a relative error of 25%. The index of agreement (d) values were, respectively, 0.73 and 0.90. In addition, the weekly ETc showed better agreement. The proposed methodology could be considered as a useful tool for scheduling irrigation and driving the estimation of water requirements over large areas for apple orchards.

Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient

Leaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io) and transmitted radiation (I) through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAID), which was compared with LAI estimated by the proposed digital photography method (LAIM). Results showed that the LAIM was able to estimate LAID with an error of 25% using a constant light extinction coefficient (k = 0.68). However, when k was estimated using an exponential function based on the fraction of foliage cover (ff) derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic) were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions.

Special issue on water management in grapevines

Population growth, economic development, environmental demands, and climate change converge into a scenario of water scarcity worldwide (Fereres and Gonzalez-Dugo 2009). Water supply may therefore constraint grape production for quality wine. In this context, deficit irrigation (DI) strategies to stabilize yield and maintain or improve wine quality are critical. Recently, the use of regulated deficit irrigation (RDI) has expanded in vineyards to improve (sometimes to reduce) water application, yield per unit water supply, berry composition, and wine quality. The objective of RDI is to apply water deficits of predetermined levels during certain phenological stages when their effects on fruit growth and quality are neutral or positive, while keeping vineyard vigor in balance with potential production (Girona et al. 2006, 2009; Pellegrino et al. 2006; Greven et al. 2005). The short and long-term impact of deficit irrigation on production and quality vary with vineyard conditions, namely soil texture and depth, variety, atmospheric environment, and viticultural practices. These factors make it difficult to predict the best timing for imposing water deficits. Also, the desired intensity of deficit is not easy to impose uniformly over the whole vineyard, and the risks of excessive water deficits must be avoided through careful monitoring. Furthermore, there is a trade-off between regulated water deficit to improve yield per unit water supply and the need to maintain well-watered vines to reduce heat damage in warm and hot regions (Sadras and Soar 2009; Soar et al. 2009). Understanding the effects of timing and amount of irrigation on yield and berry composition is key to achieve the desired yield and berry quality. Thus, the correct determination of vineyard water requirements (or evapotranspiration, ET) and the monitoring of soil and vine water status are critical to apply the appropriate deficit irrigation strategies. The conventional crop coefficient (Kc) approach provides a simple and convenient way to estimate vineyard water requirements for a variety of soil and climatic conditions, but a major uncertainty in this approach is that the empirical nature of Kc which requires local calibration and monitoring of plant water status. Vine water status can be monitored with predawn, noon leaf, and stem water potentials, which integrate the effects of soil water status on both the environment (soil and atmosphere) and the vine (root and canopy size, stomatal conductance). However, there is no general agreement on which method is the most reliable to evaluate vine water status. This discrepancy may be explained by the combined effect of variety and rootstock, soil type and depth, range of soil water deficit, variability of weather conditions throughout the growing cycle, atmospheric evaporative demand, and source/sink ratio as affected by growing conditions and management practices shifting the balance between leaf area and fruit load. Midday stem water potential of horticultural trees, for example, is lower with high source/sink ratio (Sadras and Trentacoste 2011). Communicated by R. Evans.

Selecting Canopy Zones and Thresholding Approaches to Assess Grapevine Water Status by Using Aerial and Ground-Based Thermal Imaging

Aerial and terrestrial thermography has become a practical tool to determine water stress conditions in vineyards. However, for proper use of this technique it is necessary to consider vine architecture (canopy zone analysis) and image thresholding approaches (determination of the upper and lower baseline temperature values). During the 2014–2015 growing season, an experimental study under different water conditions (slight, mild, moderate, and severe water stress) was carried out in a commercial vineyard (Vitis vinifera L., cv. Carmene). In this study thermal images were obtained from different canopy zones by using both aerial (>60 m height) and ground-based (sunlit, shadow and nadir views) thermography. Using customized code that was written specifically for this research, three different thresholding approaches were applied to each image: (i) the standard deviation technique (SDT); (ii) the energy balance technique (EBT); and (iii) the field reference temperature technique (FRT). Results obtained from three different approaches showed that the EBT had the best performance. The EBT was able to discriminate over 95% of the leaf material, while SDT and FRT were able to detect around 70% and 40% of the leaf material, respectively. In the case of canopy zone analysis, ground-based nadir images presented the best correlations with stomatal conductance (gs) and stem water potential (Ψstem), reaching determination coefficients (r2) of 0.73 and 0.82, respectively. The best relationships between thermal indices and plant-based variables were registered during the period of maximum atmospheric demand (near veraison) with significant correlations for all methods.

EVALUATION OF A MODEL TO SIMULATE NET RADIATION OVER A VINEYARD CV. CABERNET SAUVIGNON

A B S T R A C T Net radiation (Rn) is the main energy balance component controlling evaporation and transpiration processes. In this regard, this study evaluated two models to estimate Rno above a commercial vineyard (Vitis vinifera cv. Cabernet Sauvignon) located in Pencahue Valley, Maule Region (35o22’ S; 71°47’ W; 75 m.a.s.l.). An automatic meteorological station (AMS) was installed in the central part of the vineyard and used to measure Rn, solar radiation (Rsi), air temperature (Ta), canopy temperature (Tf) and relative humidity (RH). On a 30 min interval, results indicated that model Rne1 (assuming Ta ≠ Tf) and model Rne2 (assuming Ta = Tf ) were able to estimate Rn with a mean absolute error (MAE) of less than 40 W m -2 and root mean square error (RMSE) of less than 61 W m -2 . On daily intervals, the two models estimated Rno with MAE and RMSE values of less than 1.68 and 1.75 MJ m -2 d -1 , respectively. In global terms, the models presented errors below 9 and 11% on 30 min and daily intervals, respectively. Furthermore, this study indicated that the incorporation of canopy temperature did not improve the Rno estimation substantially, in spite of having a temperature gradient (dT = Tf - Ta) between -3 and 4 o C. These results suggest that an Rne2 model could be used to estimate Rno using Rsi, Ta and RH measurements.

Evaluación de un modelo para estimar la radiación neta sobre un cultivo de tomate industrial

Se realizo un estudio para evaluar un modelo que estima el flujo de radiacion neta (Rn) sobre un cultivo de tomates (Licopersicon esculentum Mill.) variedad Heinz 2150, bajo condiciones de dia despejado y nublado. Para esto, una estacion meteorologica automatica (EMA) se instalo en la parte central del cultivo, localizado en la Estacion Experimental de Panguilemo perteneciente a la Facultad de Ciencias Agrarias de la Universidad de Talca (35°26? lat. Sur; 71°41? long. Oeste, 110,5 m.s.n.m.). La EMA fue usada para medir el flujo de radiacion neta, flujo de radiacion solar, temperatura del aire, humedad relativa y presion de vapor en intervalos de 20 min. Los resultados indicaron que el modelo fue capaz de estimar el flujo de radiacion neta en intervalos de 20 min, con una desviacion estandar del error (DEE) igual a 34 W m-2 y un error absoluto (Ea) menor a 3,2%. En terminos diarios, el modelo estimo el flujo de Rn con una DEE y Ea iguales a 0,6 MJ m-2 d-2 (0,24 mm d-1) y 4,1%, respectivamente.