Irrigation Performance Assessment in Table Grape Using the Reflectance-Based Crop Coefficient

Effect of Shading Nets on Yield, Leaf Biomass and Petiole Nutrients of a Muscat of Alexandria Vineyard Growing under Hyper-Arid Conditions

Background: Currently, viticulture is exposed to extreme weather fluctuations and global warming, thus the implementation of short-term adaptation strategies to mitigate climate change impacts will be of a wide importance for the sustainability and competitiveness of wine industry. This research aimed to study the effect of shading nets on the viticultural performance of a Muscat of Alexandria vineyard growing under hyper-arid conditions. Methods: Three treatments were randomly arranged in the vineyard: (i) a control (without shading), (ii) a white shading net (25% of shading), and (iii) a black shading net (40% of shading). Subsequently, yield, vine vigor, berry composition, leaf biomass and petiole nutrient content were assessed. Results: Both shading nets decreased the incidence of solar radiation in vines. The application of white shading nets induced a high bunch weight and a higher number of berries per bunch than the black shading nets. Black shading nets increased pruning weight, decreased Ravaz index and induced a considerably accumulation of soluble solids in grapes. This treatment also decreased bunch weight and the number of berries per bunch, and increased rachis length compared to control. Black shading nets decreased Mg petiole content, leaf dry weight and leaf biomass at flowering compared to uncovered vines. Conclusions: Shading considerably affected the viticultural performance of Muscat of Alexandria vines growing under hyper-arid conditions, modifying yield, leaf biomass and petiole nutrients.

Evaluation of Penman-Monteith Model Based on Sentinel-2 Data for the Estimation of Actual Evapotranspiration in Vineyards

Water scarcity is one of the most important problems of agroecosystems in Mediterranean and semiarid areas, especially for species such as vineyards that largely depend on irrigation. Actual evapotranspiration (ET) is a variable that represents water consumption of a crop, integrating climate and biophysical variables. Actual evapotranspiration models based on remote sensing data from visible bands of Sentinel-2, including Penman-Monteith–Stewart (RS-PMS) and Penman-Monteith–Leuning (RS-PML), were evaluated at different temporal scales in a Cabernet Sauvignon vineyard (Vitis vinifera L.) located in central Chile, and their performance compared with independent ET measurements from an eddy covariance system (EC) and outputs from models based on thermal infrared data from Landsat 7 and Landsat 8, such as Mapping EvapoTranspiration with high Resolution and Internalized Calibration (METRIC) and Priestley–Taylor Two-Source Model (TSEB-PT). The RS-PMS model showed the best goodness of fit for all temporal scales evaluated, especially at instantaneous and daily ET, with root mean squared error (RMSE) of 28.9 Wm−2 and 0.52 mm day−1, respectively, and Willmott agreement index (d1) values of 0.77 at instantaneous scale and 0.7 at daily scale. Additionally, both approaches of RS-PM model were evaluated incorporating a soil evaporation estimation method, one considering the soil water content (fSWC) and the other hand, using the ratio of accumulated precipitation and equivalent evaporation (fZhang), achieving the best fit at instantaneous scale for RS-PMS fSWC method with relative root mean squared error (%RMSE) of 15.2% in comparison to 58.8% of fZhang. Finally, the relevance of the RS-PMS model was highlighted in the assessment and monitoring of vineyard drip irrigation in terms of crop coefficient (Kc) estimation, which is one of the methods commonly used in irrigation planning, yielding a comparable Kc to the one obtained by the EC tower with a bias around 9%.

Evaluation of Remote Sensing-Based Irrigation Water Accounting at River Basin District Management Scale

The Water Framework Directive in Europe requires extending metering and water abstraction controls to accurately satisfy the necessary water resource requirements. However, in situ measurement instruments are inappropriate for large irrigation surface areas, considering the high investment and maintenance service costs. In this study, Remote Sensing-based Irrigation Water Accounting (RS-IWA) (previously evaluated for commercial plots, water user associations, and groundwater water management scales) was applied to over 11 Spanish river basin districts during the period of 2014–2018. Using the FAO56 methodology and incorporating remote sensing basal crop coefficient time series to simulate the Remote Sensing-based Soil Water Balance (RS-SWB), we were able to provide spatially and temporally distributed net irrigation requirements. The results were evaluated against the irrigation water demands estimated by the Hydrological Planning Offices and published in the River Basin Management Plans applying the same spatial (Agricultural Demand Units and Exploitation Systems) and temporal (annual and monthly) water management scales used by these public water managers, ultimately returning ranges of agreement (r2 and dr) (Willmott refined index) of 0.79 and 0.99, respectively. Thus, this paper presents an operational tool for providing updated spatio-temporal maps of RS-IWA over large and diverse irrigation surface areas, which is ready to serve as a complementary irrigation water monitoring and management tool.