The quantification of evaporation is very important for water resource management, determination of water availability and environmental modeling. Evaporation (E) is a key component of the hydrological cycle, which becomes more relevant under a changing climate scenario, where increases in temperature and E are projected on a regional scale. This study evaluated the hourly applicability of 21 methods to estimate E in a mountain lake. Models were grouped as combination, solar radiation-temperature and mass transfer methods. Estimated E by all models were compared to three measurement campaigns with an eddy covariance system in Lake Laja during the month of January (22 to 28), March (17 to 23) and November (09 to 15) of 2016. The average evaporated water during the measurement sessions were 3.40, 3.38 and 1.89 mm d−1, respectively. Best model performance was obtained with models whose main E principles are heat flow and water vapor flow. The best performance in this group was the Penman model using a calibrated wind function with a determination coefficient (R2) of 0.91, Nash–Sutcliffe coefficient (NS) of 0.9, and index of agreement (W) of 0.98. Comparing daytime and nighttime hours, it was found that the daytime E in the lake is best explained by the product of the vapor pressure deficit and wind speed, while the nighttime E was explained by the flow of heat in the water. The results highlight the importance of the analysis of diurnal dynamics of water flux and energy stored in water to better understand the E in water bodies.

A surface energy balance model was conceived to estimate crop transpiration and soil evaporation in orchards and vineyards where the floor is partially wetted by micro-irrigation systems. The proposed surface energy balance model for partial wetting (SEB-PW) builds upon previous multiple-layer modelling approaches to estimate the latent, sensible, and soil heat fluxes, while partitioning the total evapotranspiration ( E T ) into dry and wet soil evaporation ( λ E s o i l ) and crop transpiration ( T ). The model estimates the energy balance and flux resistances for the evaporation from dry and wet soil areas below the canopy, evaporation from dry and wet soil areas between plant rows, crop transpiration, and total crop E T . This article describes the model development, sensitivity analysis and a preliminary model evaluation. The evaluation shows that simulated hourly E T values have a good correlation with field measurements conducted with the surface renewal method and micro-lysimeter measurements in a micro-irrigated winegrape vineyard of Northern California for a range of fractional crop canopy cover conditions. Evaluation showed that hourly L E estimates had root mean square error ( R M S E ) of 58.6 W m−2, mean absolute error ( M A E ) of 35.6 W m−2, Nash-Sutcliffe coefficient ( C N S ) of 0.85, and index of agreement ( d a ) of 0.94. Daily soil evaporation ( E s ) estimations had R M S E of 0.30 mm d−1, M A E of 0.24 mm d−1, C N S of 0.87, and d a of 0.94. E s estimation had a coefficient of determination ( r 2 ) of 0.95, when compared with the micro-lysimeter measurements, which showed that E s can reach values from 28% to 46% of the total E T after an irrigation event. The proposed SEB-PW model can be used to estimate the effect and significance of soil evaporation from wet and dry soil areas on the total E T , and to inform water balance studies for optimizing irrigation management. Further evaluation is needed to test the model in other partially wetted orchards and to test the model performance during all growing seasons and for different environmental conditions.

This article presents findings from a field research study conducted in the San Joaquin Valley of California in 2016-2018 to appraise the effects of soil salinity and sodicity on evapotranspiration and energy balance components of micro-irrigated pistachio orchards. Actual evapotranspiration (ET a ) and tree physiologic parameters were measured during consecutive growing seasons in mature orchards grown on non-saline and saline/sodic soils. Salinity and sodicity decreased pistachio water use by about 30%, with ET a reductions varying along the growing season. Accurate information on the dynamics of ET a and energy balance components along the growing season can improve water management for nut orchards exposed to long-term saline-sodic conditions. Results show that the main driver of ET a was the net radiation (Rn), which supplied most of the energy to vaporize water, irrespective of the growth period and level of salinity/sodicity. Field observations revealed that Rn was lower for salt-affected trees due to smaller canopies, which intercepted less light than non-saline trees. Secondarily, the exchange of sensible heat (H) between the ambient air and tree canopies was affected by the interaction between salinity-sodicity and seasonality. Early in the season, salinity and sodicity affected ET a mainly through the reduced canopy growth, which decreased the available energy (Rn-G) for ET a and reduced the water uptake as a result of the lower soil water potential. Late in the season, an increase in H and a decrease in the contribution of the aerodynamic component (β coefficient) to the latent heat flux (LE) occurred, which determined a further reduction of ET a due to a physiological response. The decrease in the β coefficient during the late season was associated with a direct impact of ion accumulation on leaf functionality. Collecting data on the contribution of the aerodynamic component to LE offers a low-cost method to detect and quantify physiological stress, while providing useful information for managing irrigation in salt-affected orchards. The results presented in this article provide insights to improve irrigation management of salt-affected pistachio through integration of weather measurements, energy balance components, and plant-based parameters.

A multi-layer surface energy balance model was previously developed to estimate crop transpiration (T) and soil evaporation (E) in orchards partially wet by micro-irrigation systems. The model, referred to as SEB-PW, estimates latent (λE), sensible (H), and soil heat fluxes (G) and separates actual evapotranspiration (ETa) into dry and wet soil E and crop T. The main goal of this work was to evaluate the ability of the SEB-PW model to estimate ETa and analyze the diurnal and seasonal dynamics of E and T in two hazelnut (Corylus avellana L.) orchards irrigated by drip or micro-sprinkler systems. The assessment showed that simulated hourly ET was highly correlated with estimates from nearby weather stations and with measurements from micro-lysimeters (MLs). Hourly ET estimates were evaluated by root-mean-square error (RMSE), mean absolute error (MAE), the Nash–Sutcliffe coefficient (NSE), and the index of agreement (da), which equaled 58.6 W m−2, 35.6 W m−2, 0.85, and 0.94, respectively. Daily E estimates were also evaluated and equaled 0.27 mm day−1, 0.21 mm day−1, 0.87, and 0.94, respectively, and obtained a coefficient of determination (r2) of 0.85 when compared to the measurements from the MLs. Within a day of irrigation, E accounted for 28 and 46% of ET. In accordance with the obtained results, the proposed SEB-PW model improves estimates of soil E by allowing the wetted and non-wetted areas to be estimated separately, which could be useful for optimizing irrigation methods and practices in hazelnut orchards.