Due to increasing competition for water resources by urban, industrial, and agricultural users, the proportion of agricultural water use is gradually decreasing. To maintain or increase agricultural production, new irrigation systems, such as surface or subsurface drip irrigation systems, will need to provide higher water use efficiency than those traditionally used. Several models have been developed to predict the dimensions of wetting patterns, which are important to design optimal drip irrigation system, using variables such as the emitter discharge, the volume of applied water, and the soil hydraulic properties. In this work, we evaluated the accuracy of several approaches used to estimate wetting zone dimensions by comparing their predictions with field and laboratory data, including the numerical HYDRUS-2D model, the analytical WetUp software, and selected empirical models. The soil hydraulic parameters for the HYDRUS-2D simulations were estimated using either Rosetta for the laboratory experiments and inverse analysis for the field experiments. The mean absolute error (MAE) was used to compare the model predictions and observations of wetting zone dimensions. MAE for different experiments and directions varied from 0.87 to 10.43 cm for HYDRUS-2D, from 1 to 58.1 cm for WetUp, and from 1.34 to 12.24 cm for other empirical models.

Leaching is an important aspect of irrigation water management, as it must be minimal to save available irrigation water resources, prevent shallow groundwater tables, and reduce nutrient loadings to the groundwater. However, at the same time, leaching should be sufficient to maintain root zone salinity levels below the threshold to prevent yield reduction. Therefore, monitoring leaching is the key component in evaluation and optimization of irrigation water management practices. Water balance (WB) is a common approach used to estimate leaching in agricultural fields and was applied in this study to assess field-scale leaching and the associated uncertainties for an almond orchard under drip and micro-sprinkler irrigation systems. In this study, we showed that change is soil water storage (ΔS) is highly influenced by the extent of monitoring depth, the location and number of monitoring points. Local measurement of WB parameters showed that leaching is highly variable across the field, thereby introducing considerable uncertainty on estimated leaching using WB approach. It was also shown that unknown input of water through fog interception added to the complexity of closing water balance at field scale.

The conventional tensiometer is among the most accurate devices for soil water matric potential measurements, as well as for estimations of soil water flux from soil water potential gradients. Uncertainties associated with conventional tensiometers such as caused by ambient temperature effects and the draining of the tensiometer tube, as well as their limitation for deep soil monitoring, has prevented their widespread use for vadose zone monitoring, despite their superior accuracy in general. We introduce an alternative tensiometer design that offers the accuracy of the conventional tensiometer, while minimizing the aforementioned uncertainties and limitations. The proposed alternative tensiometer largely eliminates temperature-induced diurnal fluctuations and uncertainties associated with draining of the tensiometer tube and removes the limitation in installation depth. In addition, the manufacturing costs of this alternative tensiometer design are close to those of the conventional tensiometer, while it is especially suited for monitoring of soil water potential gradients as required for soil water flux measurements.

California growers face challenges with water shortages and there is a strong need to use the least amount of water while optimizing yield. Timely information on evapotranspiration (ET), a dominant component of crop consumptive water use, is critical for growers to tailor irrigation management based on in-field spatial variability and in-season variations.We evaluated the performance of a remote sensing-based approach, Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC), in mapping ET over an almond orchard in California, driven by Landsat satellite observations. Reference ET from a network of weather stations over well-watered grass (ETo) was used for the internal calibration and for deriving ET at daily and extended time period, instead of alfalfa based reference evapotranspiration (ETr). Our study showed that METRIC daily ET estimates during Landsat overpass dates agreed well with the field measurements. During 2009-2012, a root mean square error (RMSE) of 0.53 mm/day and a coefficient of determination (R2) of 0.87 were found between METRIC versus observed daily ET. Monthly ET estimates had a higher accuracy, with a RMSE of 12.08 mm/month, a R2 of 0.90, and a relatively small relative mean difference (RMD) of 9.68% during 2009-2012 growing seasons. Net radiation and Normalized Difference Vegetation Index (NDVI) from remote sensing observations were highly correlated with spatial and temporal ET estimates. An empirical model was developed to estimate daily ET using NDVI, net radiation (Rn), and vapor pressure deficit (VPD). The validation showed that the accuracy of this easy-to-use empirical method was slightly lower than that of METRIC but still reasonable, with a RMSE of 0.71 mm/day when compared to ground measurements. The remote sensing based ET estimate will support a variety of State and local interests in water use and irrigation management, for both planning and regulatory/compliance purposes, and it provides the farmers observation-based guidance for site-specific and time-sensitive irrigation management.