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Temperature and water deficit stresses cause large year-to-year yield variability, and matching crop phenology with periods less prone to stresses can improve yield stability. We used 30 years of daily weather data from 69 stations in the U.S. Great Plains to quantify the risk of water deficit and temperature stresses for winter wheat (Triticum aestivum L.) cultivars differing in maturity, and to evaluate whether the selected variables explained variability in yield and area abandonment. Crop phenology was estimated using a simple temperature-based model based on 282 field observations. A difference between the 15-d running sums of reference evapotranspiration (ET o ) and precipitation greater than 40% of the soil's available water holding capacity (AWHC) determined atmospheric water deficit (AWD). Heat and freeze stresses occurred when maximum temperatures >27 • C and minimum temperatures <0 • C occurred around heading. Probabilities of AWD in the spring was greater in the west and in the south; however, latitudinal AWD gradients dissipated when crop maturity was considered.The day of year (DOY) for last freeze increased from south to north and from east to west; and the DOY for onset of heat stress increased from south to north but did not follow a longitudinal gradient. Early maturing varieties avoided heat and AWD stresses during heading but were more likely to experience freezing conditions. Regional yield decreased and area abandonment increased with early onset of spring AWD and heat stresses. This conceptual framework for evaluating the risk of environmental stresses can be applied to other regions and cropping systems. 2132wileyonlinelibrary.com/journal/agj2 Agronomy Journal. 2020;112:2132-2151.

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Surface water is the most readily accessible water resource and provides an array of ecosystem services, but its availability and access are stressed by changes in climate, land cover, and population size. Understanding drivers of surface water dynamics in space and time is key to better managing our water resources. However, few studies estimating changes in surface water account for climate and anthropogenic drivers both independently and together. We used 19 years (2000–2018) of the newly developed Dynamic Surface Water Extent Landsat Science Product in concert with time series of precipitation, temperature, land cover, and population size to statistically model maximum seasonal percent surface water area as a function of climate and anthropogenic drivers in the southeastern United States. We fitted three statistical models (linear mixed effects, random forests, and mixed effects random forests) and three groups of explanatory variables (climate, anthropogenic, and their combination) to assess the accuracy of estimating percent surface water area at the watershed scale with different drivers. We found that anthropogenic drivers accounted for approximately 37% more of the variance in the percent surface water area than the climate variables. The combination of variables in the mixed effects random forest model produced the smallest mean percent errors (mean −0.17%) and the highest explained variance (R2 0.99). Our results indicate that anthropogenic drivers have greater influence when estimating percent surface water area than climate drivers, suggesting that water management practices and land‐use policies can be highly effective tools in controlling surface water variations in the Southeast.

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Ammonia (NH 3) volatilization from broadcast urea may lead to significant N losses in winter wheat. We aimed to: (a) quantify N losses through NH 3 volatilization from fields fertilized with urea and urea amended with a urease inhibitor (NBPT) under cold weather months (February-April), and (b) investigate the impact of N losses through NH 3 volatilization on the winter wheat production. We employed the integrated horizontal flux (IHF) method with passive NH 3 samplers to quantify NH 3 volatilization at five sites in Kansas. Urea and urea + NBPT were broadcast at a rate of 60 kg N ha-1 over circular plots. We assessed the impact of NH 3 losses on wheat at three sites employing different rates of urea and urea + NBPT. NH 3 losses volatilization varied from 0.3 to 29.6% of total N applied. The largest N losses (>23% of applied N) occurred when urea was broadcasted to moist soils followed by a dry period. Amending urea with NBPT reduced NH 3 volatilization losses by more than 20% on the campaigns with the largest N losses (>23%). However, our results showed no significant differences for wheat yield, N-recovery and agronomic efficiency between urea and urea + NBPT treatments likely due to the reduced NH 3 volatilization (<17%) where the impact on winter wheat was measured. Our results suggest that winter wheat farmers should carefully evaluate the soil surface moisture conditions before broadcasting urea to avoid potential NH 3 volatilization losses even under cold conditions (average soil temperature ranging from 2.5 to 7.7 • C).

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