Water Use and Soil Water Balance of Mediterranean Vineyards under Rainfed and Drip Irrigation Management: Evapotranspiration Partition and Soil Management Modelling for Resource Conservation

Seasonal Mapping of Irrigated Winter Wheat Traits in Argentina with a Hybrid Retrieval Workflow Using Sentinel-2 Imagery

Earth observation offers an unprecedented opportunity to monitor intensively cultivated areas providing key support to assess fertilizer needs and crop water uptake. Routinely, vegetation traits mapping can help farmers to monitor plant development along the crop's phenological cycle, which is particularly relevant for irrigated agricultural areas. The high spatial and temporal resolution of the Sentinel-2 (S2) multispectral instrument leverages the possibility to estimate leaf area index (LAI), canopy chlorophyll content (CCC), and vegetation water content (VWC) from space. Therefore, our study presents a hybrid retrieval workflow combining a physically-based strategy with a machine learning regression algorithm, i.e., Gaussian processes regression, and an active learning technique to estimate LAI, CCC and VWC of irrigated winter wheat. The established hybrid models of the three traits were validated against in-situ data of a wheat campaign in the Bonaerense valley, South of the Buenos Aires Province, Argentina, in the year 2020. We obtained good to highly accurate validation results with LAI: R² = 0.92, RMSE = 0.43 m² m^-2, CCC: R² = 0.80, RMSE = 0.27 g m^-2 and VWC: R² = 0.75, RMSE = 416 g m^-2. The retrieval models were also applied to a series of S2 images, producing time series along the seasonal cycle, which reflected the effects of fertilizer and irrigation on crop growth. The associated uncertainties along with the obtained maps underlined the robustness of the hybrid retrieval workflow. We conclude that processing S2 imagery with optimised hybrid models allows accurate space-based crop traits mapping over large irrigated areas and thus can support agricultural management decisions.

Searching for Sustainable-Irrigation Issues of Clementine Orchards in the Syrian Akkar Plain: Effects of Irrigation Method and Canopy Size on Crop Coefficients, Transpiration, and Water Use with SIMDualKc Model

Citrus is one of the most valuable crops in Syria, with the largest production areas in the Tartus and Latakia provinces. Water-saving policies have been adopted to modernize the irrigation systems and increase water productivity. Following dedicated research, this study aimed to evaluate the water balance in clementine trees irrigated with diverse methods and schedules using the SIMDualKc software model. Two experiments are reported: one with 10–14 years old trees irrigated with different methods (2007−2011) and the other with the same trees but now 18−20 years old, irrigated with different schedules (2015−2019). The SIMDualKc model successfully simulated the soil water contents measured in the various field plots, with root mean square error values lower than 0.004 m3 m−3 and modeling efficiencies up to 0.83. The model-calibrated standard basal crop coefficients (Kcb) were approximately constant throughout all growing stages, assuming values of 0.54−0.55 for the mature trees having smaller height (h) and fraction of ground cover (fc), and 0.64 for older trees with larger canopies, i.e., larger h and fc. With drip irrigation, single Kc had a higher value (1.14) at the end, non-growing, and initial stages, and a lower value (0.75–0.76) during mid-season (Kc mid), because precipitation was lesser then, contributing less to soil evaporation. On the other hand, Kc values were nearly constant with micro-sprinkler and surface irrigation techniques because the ground was fully wetted. The Kcb values derived from the fraction of ground cover and height (A&P approach) were similar to those obtained from the model, thus showing that the A&P approach represents a practical alternative to estimate Kcb in the practice of irrigation management. The soil water balance further revealed a large weight of the terms corresponding to the non-beneficial water consumption and non-consumptive water use when the fraction wetted was large and the application efficiencies were low. These terms were reduced, namely, evaporation losses when drip irrigation was used. This study, thus, provides a valuable tool for improving the irrigation management, water saving, and water productivity of Syrian citrus production systems.

Advances in Ecohydrology for Water Resources Optimization in Arid and Semi-Arid Areas

Conserving water resources is a current challenge that will become increasingly urgent in future due to climate change. The arid and semi-arid areas of the globe are expected to be particularly affected by changes in water availability. Consequently, advances in ecohydrology sciences, i.e., the interplay between ecological and hydrological processes, are necessary to enhance the understanding of the critical zone, optimize water resources’ usage in arid and semi-arid areas, and mitigate climate change. This Special Issue (SI) collected 10 original contributions on sustainable land management and the optimization of water resources in fragile environments that are at elevated risk due to climate change. In this context, the topics mainly concern transpiration, evapotranspiration, groundwater recharge, deep percolation, and related issues. The collection of manuscripts presented in this SI represents knowledge of ecohydrology. It is expected that ecohydrology will have increasing applications in the future. Therefore, it is realistic to assume that efforts to increase environmental sustainability and socio-economic development, with water as a central theme, will have a greater chance of success.

Probabilistic Approach to Determine the Spatial Distribution of the Antecedent Moisture Conditions for Different Return Periods in the Atlántico Region, Colombia

Previous soil moisture conditions play an important role in the design of hydraulic structures because they are directly related to the runoff threshold associated with a return period. These represent one of the main determinants of the runoff response of a drainage basin. One of the main difficulties facing hydrologists in Colombia lies in the time spent gathering and analyzing information related to the selection of antecedent moisture conditions. In this study, complete records from 19 rainfall stations located in the Atlántico region, Colombia, were used to analyze the cumulative precipitation during the 5 days prior to the annual maximum daily precipitation associated with different return periods using the Gev, Gumbel, Pearson Type III and Log Pearson Type III probability distributions. Different interpolation methods (IDW, kriging and spline) were applied to evaluate the spatial distribution of the antecedent moisture conditions. The main contribution of this research is establishing, using a probabilistic approach, the behavior of antecedent moisture conditions in a particular region, which can be used by engineers and designers to plan water infrastructure. This probabilistic approach was applied to a case study of the Atlántico region, Colombia, where the spatial distribution of antecedent moisture conditions was calculated for several return periods. The results indicate that the better results were obtained with the IDW interpolation method, and the Pearson Type III and Gumbel distributions also showed the best fits based on the Akaike criterion.