Many studies have examined individual water-saving management practices for corn (Zea mays L.), but few studies have looked at how combinations of practices might further enhance water optimization. The research objectives of this paper were to evaluate the impact of irrigation technology, irrigation rate, and crop genetics, as well as their interactions, on silage corn yield and forage quality. Trials were conducted in three Utah locations from 2019 through 2021. The results from five site-years indicated that the best water optimization practices varied by site-year. Low-elevation sprinklers commonly applied water more efficiently, with four of the five site-years having improved or equivalent yield compared to mid-elevation sprinklers. Irrigation rate reductions and yield losses were not proportional, as a 25% irrigation reduction resulted in better silage quality and a 7% average yield loss across site-years. Further, targeted deficit irrigation (less water during vegetation and more during maturation) was inferior to a uniform deficit during all growth stages. Drought-tolerant genetics often maintained but did not improve yield in extreme water stress environments compared to non-DT genetics. No cumulative benefits were observed when combining irrigation technology, rate, and DT genetics. Irrigation technology had the greatest potential of the three factors to optimize water use in silage corn production in the Western U.S. region.

Soil sodicity degrades soil structure and restricts water movement by promoting clay swelling, dispersion, and surface sealing, thereby reducing infiltration and hydraulic conductivity. This study aims to evaluate the effects of four soil amendments (elemental sulfur, gypsum, compost, and humate) on the hydraulic conductivity of sodic soils, both in the field and in the laboratory, across six farm sites in Utah and Wyoming. Field‐saturated hydraulic conductivity ( K _fs ) was measured using a dual‐head infiltrometer, while lab‐saturated ( K _s ) was measured using a falling head test, and unsaturated hydraulic conductivity was measured using the HYPROP 2 system during controlled drying. Across sites, field K _fs values ranged widely from 1.5 to 38.9 cm h ⁻¹ , reflecting high spatial variability with measurements made 6–8 or 17–20 months after amendment application, depending on site establishment year. Laboratory measurements were conducted only for a subset of sites and treatments. At the sites evaluated, compost increased K _s by 215% (3.04   vs. 0.96 cm h ⁻¹ ), while gypsum increased it by 70% (1.63 cm h ⁻¹ ). Lab measurements align with field measurements but vary in the magnitude of conductivity, potentially due to the presence of macropores in the field measurements and root biomass. Unsaturated hydraulic conductivity results revealed increased water permeability in gypsum and compost‐treated soil, with an increase in plant‐available water by 5%–7%, indicating enhanced soil permeability. Limited laboratory measurements showed higher hydraulic conductivity under gypsum and compost treatment than the control, but the results should be interpreted with caution due to restricted site and treatments in the lab, and field variability may have masked short‐term amendment effects.

The escalating pressure on water resources in agricultural regions has become a catalyst for water conflicts. The adoption of innovative approaches to estimate actual evapotranspiration (ETa) offers potential solutions to mitigate conflicts related to water usage. This research presents the application of a remote sensing-based methodology for estimating actual evapotranspiration (ETa) based on a two-source energy balance model (TSEB) for riparian vegetation in Nebraska, US using the Spatial EvapoTranspiration Modeling Interface (SETMI). Estimated results through SETMI and field data using the eddy covariance system (EC) considering the period 2008–2013 were used to validate the energy balance components and ETa. Modeled energy balance components showed a strong correlation to the ground data from EC, with ET presenting R2 equal to 0.96 and RMSE of 0.73 mm.d⁻¹. In 2012, the lowest adjusted crop coefficient (Kcadj) values were observed across all land covers, with a mean value of 0.49. The years 2013 and 2012, due to the dry conditions, recorded the highest accumulated ETa values (706 mm and 664 mm, respectively). Soybeans and corn exhibited the highest ETa values, recording 699 mm and 773 mm, respectively. Corn and soybeans, together accounting for a substantial portion of the land cover at 15% and 3%, respectively, play a significant role. Given that most fields cultivating these crops are irrigated, both pumped groundwater and surface water directly impact the water source of the Republican River. The SETMI model has generated appropriate estimated daily ETa values, thereby affirming the model’s utility as a tool for assisting water management and decision-makers in riparian zones.

Irrigation organizations (IOs) in the arid US West manage water supply, own water rights, and deliver water shares to their users. In delivering most of the water used for irrigated agriculture, the influence of the water managers who run them on water futures cannot be overstated. Yet, the perspectives of both water managers and IOs regarding nimble strategies for water management under scarcity remain understudied. One water management strategy, water banking, was introduced in Utah in 2020, but formal uptake has been slow. Using data collected from individual agricultural water managers within IOs in Utah, we show that water managers are familiar with water markets, but that they do not believe their IOs are interested in increasing the number they engage in. Further, we find that most IOs would have little to no water to place in a future water bank, and that over half of the water managers surveyed believe none of their shareholders would be interested in participating. Finally, government meddling, fear of forfeiture, and economic impacts are all barriers to banking, but water infrastructure improvements might act as bridges to finding more “wet” water for banking and other transactions. This study helps clarify whether and how water markets might be integrated into a more secure water future for Utah and the arid West. While water banking remains one tool for flexible and adaptive water management, we underscore that barriers to banking may limit its uptake in Utah.

Tart cherry is an important fruit crop in Utah, where irrigation is essential due to arid conditions. Precision irrigation requires reliable indicators of plant water status, and stem water potential (Ψ_stem), is among the most sensitive though labor-intensive and spatially limited. This study develops Ψ_stem estimation models using high-resolution multispectral Unmanned Aerial Vehicle (UAV) imagery combined with meteorological and soil moisture data, applying Symbolic Regression (SR). Results show a stronger correlation between optical bands and Ψ_stem during the pre-harvest period. Among 85 vegetation indices, the Red Chromatic Coordinate (RCC) index performed best (R² = 0.67). Six equations were generated for different data-availability scenarios and validated using a leave-one-tree-out (modified k-fold) approach, resulting in Ψ_stem estimates with R² values ranging from 0.67 to 0.80 and root mean square errors (RMSE) ranging from 0.11 to 0.08 MPa. Notably, SR was able to produce interpretable equations that enhance model transparency and transferability. Model robustness was further confirmed using an independent dataset from a different location. To our knowledge, this is the first application of SR for Ψ_stem estimation, offering a scalable and interpretable tool to support irrigation management in tart cherry orchards.