No abstract

Subsurface drip irrigation (SDI) systems are increasingly being used in agriculture in attempts to use the available water more efficiently. The proper design and management of SDI systems requires knowledge of precise distribution of water around emitters. We conducted both field and numerical experiments to evaluate the soil water content distributions between two neighboring emitters when their wetting patterns started to overlap. The experiments involved SDI systems with emitters installed at different depths and with different spacings along the drip lateral. The HYDRUS software package was used to analyze the field data, assuming modeling approaches in which emitters were represented as (i) a point source in an axisymmetrical two‐dimensional domain, (ii) a line source in a planar two‐dimensional domain, or (iii) a point source in a fully three‐dimensional domain. Results indicated that SDI systems can be accurately described using an axisymmetrical two‐dimensional model only before wetting patterns start to overlap, and a planar two‐dimensional model only after full merging of the wetting fronts from neighboring emitters. A fully three‐dimensional model appears to be required for describing subsurface drip irrigation processes in their entirety.

Large spatial and temporal variability in water flow and N transport dynamics poses significant challenges to accurately estimating N losses form orchards. A 2-yr study was conducted to explore nitrate (NO 3 − ) leaching below the root zone of an almond [Prunus dulcis (Mill.) D. A. Webb] orchard. Temporal changes in water content, pore water NO 3 − concentrations and soil water potential were monitored within and below the root zone to a soil depth of 3 m at eight sites, which represented spatial variations in soil profiles within an almond orchard in California. Orchard monthly average NO 3 − concentrations below the root zone ranged from 225 to 710 mg L −1 with mean annual concentration of 468 and 333 mg L −1 for the 2014 and 2015 growing seasons, respectively. Despite the huge variability in pore water NO 3 − concentration between sites, the larger spatiotemporal scale N losses estimated at the annual orchard scale from surface N mass balance, vadose zone based water and N mass balance, flow calculations, and HYDRUS modeling were all on the same order of magnitude (80-240 kg N ha −1 yr −1 ). All methods indicated that most of the N losses occur early in the growing season (February-May) when fertilizer is applied to wet soil profiles. Simple mass balance (i.e., N load applied minus N load removed) provided a good proxy of the annual N accumulation in the soil profile at the orchard scale. Reduction of N losses at the orchard scale would require alternative fertigation and irrigation practices to decrease the difference between the N load removed and the N load applied to orchards.

No abstract

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. Communicated by J. Ayars.

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 (ET o ) was used for the internal calibration and for deriving ET at daily and extended time period, instead of alfalfa based reference evapotranspiration (ET r ). 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 (R 2 ) 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 R 2 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 (R n ), 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.

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.

It has recently been proposed to couple the Beerkan method with the Beerkan \ud Estimation of Soil Transfer parameters (BEST) algorithm to facilitate the estima-\ud tion of soil hydraulic parameters from an infiltration experiment. Although this \ud simplified field procedure is relatively rapid and inexpensive, it has been doubt -\ud ed if the Beerkan method can represent a valid and reliable alternative to other \ud conventional methods. This study explored the impact of the tortuosity param-\ud eter (p) and two infiltration constants included in the BEST algorithm \ud using a sensitivity analysis applied to three experimental soils. The analysis that \ud was validated using the numerical model HYDRUS 2D/3D indicates that the \ud tortuosity is relatively insignificant compared to parameters b and g that have a \ud large impact on the estimation procedure