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Residue removal from maize (Zea mays) fields offers an opportunity to increase farmer profits, but potential tradeoffs for water dynamics and crop performance merit further evaluation. This study, established in 2014, compared the effects of two tillage practices (no-till and conventional) and two residue management practices (harvested vs. kept in place) on maize grain yields, water infiltration, evapotranspiration, and soil physical attributes. On average, maize grain yields under limited irrigation increased with residue retention by 1.1 Mg ha−1 year−1 between 2016 and 2018, but tillage had no significant effect. Total infiltration (over 30 min) was higher with residue retention. Neither tillage nor residue management had a significant impact on evapotranspiration during the vegetative growth stage. However, there was a significant residue by tillage interaction where vegetative evapotranspiration was reduced by no-till and residue retention. Conversely, penetrometer resistance was significantly reduced by both tillage and residue retention. Volumetric water content in the soil profile at planting was higher with residue retention. These results suggest that plots with residue removal would on average require 60 mm year−1 of additional irrigation to attain the same yields as fields with residue retention. In summary, our findings suggest that high rates of crop residue removal under limited irrigation in a semiarid environment can negatively affect water conservation and yields, and that tradeoffs surrounding residue export need to be fully considered in land management and policy decisions.

Arctic coastal erosion damages infrastructure, threatens coastal communities, and releases organic carbon from permafrost. However, the magnitude, timing and sensitivity of coastal erosion increase to global warming remain unknown. Here, we project the Arctic-mean erosion rate to roughly double by 2100 and very likely exceed its historical range of variability by mid-21st century. The sensitivity of erosion to warming also doubles, reaching 0.4-0.5 m year-1 oC-1 and 2.3-2.8 TgC year-1 oC-1 by the end of the century under moderate and high-emission scenarios. Our first 21st-century pan-Arctic coastal erosion rate projections should inform policy makers on coastal conservation and socioeconomic planning. Our organic carbon flux projections also lay out the path for future work to investigate the impact of Arctic coastal erosion on the changing Arctic Ocean, on its role as a global carbon sink, and on the permafrost-carbon feedback.

Current state-of-the-art decadal ensemble prediction systems are run with an ensemble size of 10 to 40 members, their retrospective forecasts of the past are used to assess the system's prediction skill. Here, we present an attempt for a large ensemble decadal prediction system for the time period 1960-today, with an ensemble size of 80 members, based on the low resolution version of the Max Planck Institute Earth system model (MPI-ESM-LR). The ensemble is forced with CMIP6 conditions and initialized every year in November through a weakly coupled assimilation using atmospheric reanalyses via nudging and observed oceanic temperature and salinity profiles via a 16-member ensemble Kalman filter. To generate ensemble members beyond 16, we use additional physical perturbations at stratospheric height. The analysis of our large ensemble prediction system presented here aims for answering two questions: (1) How does the ensemble mean deterministic prediction skill for global and North Atlantic key climate indices change with ensemble size? (2) How well may the 80-member ensemble serve as a basis for a robust statistical analysis of probabilities of extremes in the North Atlantic sector? Preliminary results for global and regional air surface temperature show that in terms of ensemble mean ACC and full ensemble CPRSS with reference data, the 80-member ensemble leads to similar prediction skill as the 16-member ensemble. This indicates that the additional ensemble members may lead to a better sampling of the distribution of model trajectories, paving the way for a more robust statistical probabilistic analysis.

When unprotected by sea-ice and exposed to the warm air and ocean waves, the Arctic coast erodes and releases organic carbon from permafrost to the surrounding ocean and atmosphere. This release is estimated to deliver similar amounts of organic carbon to the Arctic Ocean as all Arctic rivers combined, at the present-day climate. Depending on the degradation pathway of the eroded material, the erosion of the Arctic coast could represent a positive feedback loop in the climate system, to an extent still unknown. In addition, the organic carbon flux from Arctic coastal erosion is expected to increase in the future, mainly due to surface warming and sea-ice loss. In this work, we aim at addressing the following questions: How is Arctic coastal erosion projected to change in the future? How sensitive is Arctic coastal erosion to climate change?To address these questions, we use a 10-member ensemble of climate change simulations performed with the Max Planck Institute Earth System Model (MPI-ESM) for the Coupled Model Intercomparison Project phase 6 (CMIP6) to make projections of coastal erosion at a pan-Arctic scale. We use a semi-empirical approach to model Arctic coastal erosion, assuming a linear contribution of its thermal and mechanical drivers. The pan-Arctic carbon release due to coastal erosion is projected to increase from 6.9 ± 5.4 TgC/year (mean estimate ± two standard deviations from the distribution of uncertainties) during the historical period (mean over 1850 -1950) to between 13.1 ± 6.7 TgC/year and 17.2 ± 8.2 TgC/year in the period 2081-2100 following an intermediate (SSP2.4-5) and a high-end (SSP5.8-5) climate change scenario, respectively. The sensitivity of the organic carbon release from Arctic coastal erosion to climate warming is estimated to range from 1.52 TgC/year/K to 2.79 TgC/year/K depending on the scenario. Our results present the first projections of Arctic coastal erosion, combining observations and Earth system model (ESM) simulations. This allows us to make first-order estimates of sensitivity and feedback magnitudes between Arctic coastal erosion and climate change, which can lay out pathways for future coupled ESM simulations.

The Arctic has warmed twice as fast as the globe and sea-ice extent has decreased, causing permafrost to thaw and the duration of the open-water period to extend. This combined effect increases the vulnerability of the Arctic coast to erosion, which in turn releases substantial amounts of carbon to both the ocean and the atmosphere, potentially contributing to further warming due to a positive climate-carbon cycle feedback. Therefore, Arctic coastal erosion is an important process of the global carbon cycle.Comprehensive modelling studies exploring Arctic coastal erosion within the Earth system are still in their infancy. Here, we describe the development of a semi-empirical Arctic coastal erosion model and its coupling with the Max Planck Institute Earth System Model (MPI-ESM). We also present preliminary results for historical and future climate projections of coastal erosion rates in the Arctic. The coupling consists on the exchange of a combination of driving forcings from the atmosphere and the ocean, such as surface air temperature, winds and sea-ice concentration, which result in annual coastal erosion rates. In a further setp, organic matter from the eroded permafrost is provided to the ocean biogeochemistry model and, consequently, to the global carbon cycle including atmospheric CO2.

Arctic coastal erosion experiences pronounced effects from ongoing climate change. The Laptev Sea figures among the Arctic regions with the most severe erosion rates. Here, we use unprecedentedly long records of almost 30 years of annual in-situ coastal erosion rate measurements from Bykovsky Peninsula and Muostakh Island to separate the main modes of variability, which we attribute to large-scale drivers. The first (lower-frequency) and second (higher-frequency) modes are associated with winter sea-ice cover in the Laptev Sea and with the Arctic Oscillation, respectively, which together account for (Formula presented.) of the total observed variance. Arctic coastal erosion has so far been neglected in Earth system models (ESMs). The proposed mechanisms set favorable conditions for coastal erosion at large scales (synoptic to planetary scales), compatible with those represented in modern ESMs. ©2020. American Geophysical Union. All Rights Reserved.

Dry edible bean (Phaseolus vulgaris L.) could be used to diversify dryland rotational cropping systems in the U.S. Central High Plains. Dryland production potential of dry bean is undocumented in this region. The objectives of this study were to determine dry bean yield and water use under a range of water availability conditions in order to produce a water use-yield production function and to use that production function in conjunction with long-term precipitation records to estimate average yields and probabilities of attaining given yields. Dry bean was grown over a six-yr period at Akron, CO under a line-source gradient irrigation system to impose a range of water availability conditions. Seed yield was linearly correlated with water use resulting in a production function defined as seed yield (kg ha−1) = 8.24 X (water use [mm] - 104). The slope was similar to another seed legume, field pea (Pisum sativum L.). This production function was used with the long-term precipitation record to determine an average dry bean yield of 1192 kg ha−1 (range 359–2514 kg ha−1). These yield estimates were used to create a cumulative probability exceedance graph of yield that can be used to assess production risk as farmers consider the possibility of including dry bean as a component of a dryland crop rotation.

Irrigated corn (L.) in the Great Plains will be increasingly grown under limited irrigation management and greater water stress. Hybrids with drought genetics may decrease the impacts of water stress on yield. The objective of this experiment was to evaluate the effect of drought genetics on corn water stress, water use, grain yield, yield components, and water use efficiency under varying water availability. A 3-yr (2009–2011) study was conducted at Akron, CO in which corn water use, yield, and yield components were measured for isolines of three corn hybrids with and without drought genetics grown under three water treatments (fully irrigated, no irrigation until just prior to tasseling followed by full irrigation, and limited irrigation throughout the growing season). There was no yield loss from the drought genetics under non-water-stressed conditions. There was no effect of drought genetics on water use, yield, or water use efficiency. However, there was a 7% increase in kernels per plant in 2011 and a 5% increase in 1000-kernel weight in 2010 due to the presence of the drought gene. It does not appear that the non-commercial, experimental drought genetics tested in this experiment produced any consistent effect on mitigating water stress in corn or on corn water use and yield under varying levels and timings of water stress. Further research is needed in which consistent levels of water stress are imposed during reproductive and grain-filling growth stages to verify the effects of drought genetics on corn yield.

Winter wheat (Triticum aestivum L.)-fallow (WF) remains a prominent cropping system throughout the Central Great Plains despite documentation confirming the inefficiency of precipitation storage during the summer fallow period. Wheat yield is greatly influenced by available soil water at planting, and that quantity is influenced by cropping intensity, tillage intensity, crop grown prior to winter wheat planting, and length of the non-crop period prior to winter wheat planting. The objective of this study was to determine the effect of cropping system intensity, tillage, and crop prior to wheat planting on available soil water at planting and the probabilities of having certain minimum amounts of available soil water at wheat planting. Available soil water was measured at wheat planting for nine cropping systems varying in fallow frequency, tillage intensity, and crop prior to wheat over a 25-yr period at Akron, CO. Available soil water at wheat planting was found to be greatest (average 218 mm) for no-tillage (NT) and reduced-tillage (RT) systems in which a fallow period of 12–14 months preceded wheat planting. The lowest amounts of available soil water at wheat planting were found for the continuously cropped rotations (average 100 mm). The cumulative probability exceedance graphs of available soil water at planting fell into three groupings: 1) the five rotations that had a NT or RT fallow period prior to the next wheat crop; 2) the WF (conventional till) rotation; 3) the three rotations with either pea (Pisum sativum L.) or proso millet (Panicum miliaceum L.) prior to the next wheat crop. These graphs provide a valuable decision support tool for helping farmers assess risk in moving from a WF cropping system to a system of greater cropping intensity and diversity.

Owing to differing degrees of reduction between substrates and products, biofuel production from carbohydrates inevitably releases a significant amount of CO2, reducing both overall carbon utilization efficiency and the sustainability of biofuel production processes. To address this fundamental and persistent challenge, recent studies have explored diverse metabolic engineering and synthetic biology approaches to either i) limit CO2 evolution by decreasing its generation or ii) recycle it through various biochemical mechanisms. Through these strategies, carbon that would have been wasted as CO2 is reduced, allowing carbon conversion efficiency to be significantly enhanced and greenhouse gas emission effectively mitigated, thus potentially leading to a more sustainable microbial process for biofuel production.

Microbial based biofuels represent a potential promising solution as an environmentally favorable transportation fuel. Cyanobacteria have many of the same advantages as microalgae: ability for rapid growth in otherwise non-arable regions, suitability for genetic engineering, and simple nutritional needs. Additionally, cyanobacteria can be engineered to secrete valuable co-products that can be harvested independent from the produced biomass. However, little work has been done to identify the processes and the economic and environmental impacts associated with a large-scale cyanobacteria-to-fuels facility. The present study is a concurrent techno-economic and life cycle assessment of a facility that generates fuels and methyl laurate, an oleochemical, from the cyanobacterial species Synechocystis sp. PCC 6803. The biorefinery model includes all aspects of cultivation, separation of the secreted methyl laurate, biomass harvesting and fuel processing via hydrothermal liquefaction (HTL) of the dewatered biomass. The assessments leverage Monte Carlo analysis (MCA) to address uncertainty and variability inherent in the most significant input parameters, replacing them with probabilistic functions. For the facility configuration producing both fuels and the oleochemical co-product, the MCA average minimum fuel selling price (MFSP) is $2.47 per decimeter (dm3) or $9.34 per gallon of gasoline equivalent (gge) with the corresponding average global warming potential determined to be 118 g CO2-eq-MJ−1. The case producing only fuels results in an MCA average MFSP of $2.01-(dm3)−1 ($7.60-gge−1) and an average environmental impact of 100 g CO2-eq-MJ−1. These results are compared to static optimistic and conservative scenario analysis estimates, illustrating the over- and under-estimation of outcomes associated with non-stochastic methods. Suggested facility improvements include increases in pond productivity of both the biomass and methyl laurate oil production, as well as improvements to carbon utilization and bio-crude yield from HTL processing.

Proso millet ( Panicum miliaceum L.) is a short-season, drought-tolerant C4 species capable of making use of limited available water supplies and is suitable for dryland crop rotations in the Central Great Plains. Previously published water use/yield production functions for proso millet have slopes lower than reported for other C4 species in this region. The objectives of this experiment were to determine the water-limited yield relationship for proso millet and to identify environmental factors that cause yields to be lower than predicted by the water-limited yield relationship. Water use and yield data were obtained from a long-term crop rotation experiment conducted under dryland conditions in northeast Colorado from 1995 to 2016. Stepwise linear regression analysis was used to determine important environmental factors influencing yield. The water-limited yield relationship had a slope consistent with other C4 species in this region (32.57 kg ha −1 per mm of water use). A relationship based on growing season water use, plant available soil water at planting, precipitation received from 12 to 18 August, number days in July and August with maximum temperature greater than 36°C, daily average wind run and maximum wind gust during the week before swathing explained 88% of yield variability. The results of this analysis suggest that closing the yield gap for proso millet production could likely result from efforts to breed for enhanced shattering resistance and heat tolerance and from production methods that improve precipitation storage efficiency during the non-crop period prior to millet planting and increase available soil water at millet planting.

Grain sorghum (Sorghum bicolor L. Moench) is a drought-tolerant C4 species capable of making use of limited available water supplies and is suitable for dryland crop rotations in the central Great Plains. In order for farmers to assess the production risk encountered when utilizing sorghum in rotations, a water use–yield production function would be useful. Previously published production functions vary widely in reported slope of the relationship between water use and grain yield, with many of those slopes being much less than expected for a C4 species. The objectives of this experiment were to determine a water use–yield production function applicable to grain sorghum grown in the central Great Plains and to use that production function with a long-term precipitation record to assess production risk. Sorghum water use and yield data were collected from 2006 to 2016 at Akron, CO, and a production function was determined by linear regression to be yield (kg ha–¹) = 30.2 × (water use [mm] – 259). A grain yield of at least 4000 kg ha–¹ would be expected to occur 16% of the time if plant available soil water at planting was 111 mm and 92% of the time if 259 mm was available. Both the production function and the probability exceedance graphs will be useful to farmers in assessing production risk as they consider incorporating grain sorghum into dryland crop rotations in the central Great Plains.

Increasing dryland cropping system intensity in the semi-arid central Great Plains by reducing frequency of fallow can add diversity to cropping systems and decrease erosion potential. However elimination of the periodic fallow phase has been shown to reduce yields of subsequent crops in this region. The objective of this experiment was to determine how productivity of a 4-yr WCMF rotation [wheat (W, Triticum aestivum L.); corn (C, Zea mays L.); proso millet (M, Panicum miliaceum L.); fallow (F)] was affected when the fallow phase was replaced with pea (P, Pisum sativum L.). The effect of this intensification of the WCMF rotation on the available soil water content at planting, the water use, and the yield of each crop, and on total system productivity and net income was quantified by analyzing data over a 20-yr period from a long-term crop rotation experiment at Akron, CO. Large year-to-year variations were found for available soil water at planting, water use, and yield for all four crops. Pea water use resulted in significant reductions in available soil water at planting, water use, and yield for wheat and corn, but had little effect on those quantities in the millet crop. Total production on a seed mass basis was not different between the WCMF and WCMP rotations, but system net income for the WCMP rotation was 32% lower than for WCMF. Intensification of the WCMF rotation by replacing the fallow phase with pea production could be recommended as an alternative production method if pea seed costs and nitrogen fertilizer applied to the subsequent wheat crop can be reduced.

The South Atlantic Convergence Zone (SACZ) plays a key role in the South American monsoon system (SAMS) precipitation regime, and accounts for around 25 of the rainfall volume over Southeast Brazil between October and April, on average, with peaks of 56 in March and 41 in January. Due to its often varying position and multi-variable structure, diagnosing or quantifying SACZ episodes may lie on subjective criteria. The present study provides a climatological characterization of different SACZ types, based on their position, and differences in dynamics analysed from 19 SAMS wet periods. A cycle in SACZ configurations is identified during the rainy season: northernmost (southernmost) episodes are more likely to occur during the onset/demise (peak) months of the SAMS. Objective SACZ indices are developed taking the principal components of the dynamics of the SACZ as explanatory variables, not including precipitation. The most sensitive threshold proposed for the identification of mean SACZ type yields simultaneous true positive rate of 86, false alarm rate of 28, true negative rate of 72 and false negative rate of 15, for example. The indices have potential to bring gains in predictability to SACZ-related precipitation in Southeast Brazil, apart from allowing the objective diagnosis of SACZ episodes. The indices are also correlated with the South American precipitation dipole and may be used to identify anomalous SAMS precipitation at longer time scales as well. © 2018, The Author(s).

Climate in the semiarid central Great Plains is expected to become warmer and drier in coming decades, with potentially greater variability in precipitation and temperature. Cropping systems that include forages and allow flexibility for determining if a crop should be planted and which crop to plant (based on available soil water at planting) may provide the opportunity to maintain economic viability in a changing climate environment. The objective of this study was to compare cropping system productivity and profitability of flexible rotations that incorporate forages against grain-based cropping systems that are set rotational sequences. Yield and net returns for five set rotations and three flexible rotations were compared at Akron, CO, over 5 yr. Winter wheat (Triticum aestivum L.) yields were reduced by 57% when the fallow period prior to wheat production was replaced with crop production. Average net income was greatest for the continuously cropped all-forage set 3-yr rotation followed by the flexible 3-yr rotations that included wheat and forage phases. The lowest net returns were seen for the set grain-based rotations and the flexible wheat–grain crop rotation. Incorporating forage production as a phase in dryland wheat rotational systems can add profitability and sustainability to the production system in the face of climate variability.

The South American monsoon system (SAMS) plays a fundamental role in the precipitation regime of the most populous and economically important regions in Brazil. The South Atlantic Convergence Zone (SACZ) is a main component of the SAMS, characterizing its active phase, and is often associated with intense rainfall events: Strong and persistent episodes cause severe floods and landslides, while weak and sparse episodes are associated with droughts. The variability of the convergence zone caused great natural disasters in Southeast Brazil, associated with extreme precipitation conditions: 3562 landslides killed 947 people in Rio de Janeiro state in 2011, while a shortage of water in Sao Paulo affected around 20 million people between 2014 and 2015. In the present study, we build SACZ configuration series for the period between January 2000 and June 2014 and use them as indicators for the SAMS to quantify its influence on several atmospheric variables. Based on a principal component analysis, we present indices that identify the configuration of the SACZ in a local scale. The indices reached strong accuracy rates, especially for identifying days of extreme rainfall events associated with the SAMS and may, thus, serve as decision-making tools to help prepare for their impacts. Furthermore, the indices are composed by common variables simulated by numerical weather and climate models, other than precipitation, which is often a not very reliable output. The applied methodology is easily reproducible and different variables may be used to compose indices for different regions—an advantage of this local-scale approach.

Cover crops can have beneficial effects on soil microbiology by increasing carbon (C) supply, but these beneficial effects can be modulated by precipitation conditions. The objective of this study was to compare a fallow-winter wheat (Triticum aestivum L.) rotation to several cover crop-winter wheat rotations under rainfed and irrigated conditions in the semiarid US High Plains. Experiments were carried out at two sites, Sidney in Nebraska, and Akron in Colorado, USA, with three times of soil sampling in 2012–2013 at cover crop termination, wheat planting, and wheat maturity. The experiments included four single-species cover crops, a 10-species mixture, and a fallow treatment. The variables measured were soil C and nitrogen (N), soil community structure by fatty acid methyl ester (FAME) profiles, and soil β-glucosidase, β-glucosaminidase, and phosphodiesterase activities. The fallow treatment, devoid of living plants, reduced the concentrations of most FAMEs at cover crop termination. The total FAME concentration was correlated with cover crop biomass (R = 0.62 at Sidney and 0.44 at Akron). By the time of wheat planting, there was a beneficial effect of irrigation, which caused an increase in mycorrhizal and protozoan markers. At wheat maturity, the cover crop and irrigation effects on soil FAMEs had subsided, but irrigation had a positive effect on the β-glucosidase and phosphodiesterase activities at Akron, which was the drier of the two sites. Cover crops and irrigation were slow to impact soil C concentration. Our results show that cover crops had a short-lived effect on soil microbial communities in semiarid wheat-based rotations and irrigation could enhance soil enzyme activity. In the semiarid environment, longer time spans may have been needed to see beneficial effects of cover crops on soil microbial community structure, soil enzyme activities, and soil C sequestration.

The water-limited environment of the semiarid Central Great Plains may not produce enough cover crop biomass to generate benefits associated with cover crop use in more humid regions. There have been reports that cover crops grown in mixtures produce more biomass with greater water use efficiency than single-species plantings. This study was conducted to determine differences in cover crop biomass production, water use effi- ciency, and residue cover between a mixture and single-species plantings. The study was conducted at Akron, CO, and Sidney, NE, during the 2012 and 2013 growing seasons under both rainfed and irrigated conditions. Water use, biomass, and resi - due cover were measured and water use efficiency was calculated for four single-species cover crops (flax ( Linum usitatissimum L.), oat (Avena sativa L.), pea (Pisum sativum ssp. arvense L. Poir), rapeseed ( Brassica napus L.)) and a 10-species mixture. The mixture did not produce greater biomass nor exhibit greater water use efficiency than the single-species plantings. The slope of the water-limited yield relationship was not significantly greater for the mixture than for single-species plantings. Water- limited yield relationship slopes were in the order of rapeseed < flax < pea < mixture < oat, which was the expected order based on previously published biomass productivity values generated from values of glucose conversion into carbohydrates, protein, or lipids. Residue cover was not generally greater from the mix

A correct simulation of crop responses to water stress is essential for a system model. In this study, we investigated three methods of quantifying water deficit stresses based on soil water measurements and their effects on simulating grain yield, biomass and canopy cover of corn ( Zea Mays L.). Experimental data were collected for six irrigation treatments designed to replace 40 to 100% of potential crop evapotranspiration (ETc) losses during the growing season, from 2008 to 2011 near Greeley, Colorado in a sandy loam soil (Limited Irrigation Research Farm, LIRF). Water available for plant uptake (PAW, plant available water) and the maximum PAW (MAW) in the soil were calculated for a constant 1 m soil profile from 45 days after planting till maturity. Water deficit stress factors were calculated as ratios of (1) PAW to alfalfa reference crop evapotranspiration (ETr) (WSF1), (2) PAW to MAW (WSF2), and (3) WSF2 to ETr (WSF3). Average WSF1, WSF2 and WSF3 over the growing season were related to end of the season grain yield, biomass, and fraction canopy cover measurements. These stress factors were implemented in the RZWQM2 cropping system model and the calibrated results compared with those obtained from using current stress factors in CERES-maize module in RZWQM2. The best simulation of the measured grain yields, biomass and LAI was obtained using WSF3. The modified model was also tested for simulating dryland and limited irrigation studies at Akron, CO, and irrigated corn in a sandy loam soil at Zaragoza, Spain and in a sandy soil at Gainesville, Florida, USA. In general, WSF3 gave slightly better simulations of grain yields, biomass and LAI than WSF2, WSF1 and the original stress factor.

a b s t r a c t Crop water production functions (CWPFs) are often expressed as crop yield vs. consumptive water use or irrigation water applied. CWPFs are helpful for optimizing management of limited water resources, but are site-specific and vary from year to year, especially when yield is expressed as a function of irrigation water applied. Designing limited irrigation practices requires deriving CWPFs from long-term field data to account for variation in precipitation and other climatic variables at a location. However, long-term field experimental data are seldom available. We developed location-specific (soil and climate) long-term averaged CWPFs for corn (Zea mays L.) using the Root Zone Water Quality Model (RZWQM2) and 20 years (1992-2011) of historical weather data from three counties of Colorado. Mean CWPFs as functions of crop evapotranspiration (ET), ET due to irrigation (ETa-d), irrigation (I), and plant water supply (PWS = effective rainfall + plant available water in the soil profile at planting + applied irrigation) were developed for three soil types at each location. Normalization of the developed CWPF across soils and climates was also developed. A Cobb-Douglas type response function was used to explain the mean yield responses to applied irrigations and extend the CWPFs for drip, sprinkler and surface irrigation methods, respectively, assuming irrigation application efficiencies of 95, 85 and 55%, respectively. The CWPFs developed for corn, and other crops, are being used in an optimizer program for decision support in limited irrigation water management in Colorado. © 2014 Elsevier B.V. All rights reserved.

Recent recommendations advocating the use of cover crop mixtures instead of single-species in semi-arid environments require rigorous scientific studies. One of those stated benefits is greatly reduced water use by cover crops grown in mixtures. The objec tives of this study were to characterize soil water extraction patterns and determine water use of cover crops grown in singlespecies plantings and in a 10-species mixture and to compare cover crop water use to evaporative water loss from no-till fallow. The study was conducted at Akron, CO, and Sidney, NE, during the 2012 and 2013 growing seasons on silt loam soils. At each location there were a dryland treatment and an irrigated treatment. Soil water contents were measured by neutron scattering and time-domain reflectometry at six depths (0.0–1.8 m, Akron) or four or five depths (to 1.2 m or 1.5 m, Sidney). There were no con sistent significant differences in soil water contents or growing season crop water use with the single-species plantings compared with the 10-species mixture. Cover crop water use (216 mm) averaged 1.78 times greater than evaporative water loss (122 mm) from the no-till fallow treatment with proso millet (Panicum miliaceum L.) residue. There appears to be no evidence from data collected in this semi-arid environment, even when irrigated to simulate higher rainfall environments, to support the conclusion that cover crops grown in multi-species mixtures use water differently than single species-plantings of cover crops.

Siberian wildrye (L.) is a perennial grass that is widely planted in semiarid northern China, but yield is often low due to insufficient soil water supply. Field experiments were conducted from 2009 to 2011 to study the effects of ridge and furrow planting (RFP) on yield, evapotranspiration, and water use efficiency (WUE) of Siberian wildrye grassland under rainfed conditions. The treatments included bare flat bed planting (FB), bare ridge with bare furrow (BRB), bare ridge with naked oat (L.) straw mulch in furrow (BRM), plastic mulch on ridge with bare furrow (MRB), and plastic mulch on ridge with straw mulch in furrow (MRM). In the RFP system, the ridge and furrow were each 30 cm wide. Total forage yield with MRB and MRM each year was 46 to 111% and 50 to 135% greater, respectively, than with FB (2580 kg ha yr). These two treatments also increased total WUE each year by 79 to 121% and 80 to 150%, respectively, compared with FB (10.8 kg ha mm yr). The BRB and BRM treatments increased total forage yield by 47 and 81% and total WUE by 51 and 81%, respectively, compared with FB only in 2010. The addition of straw mulch did not result in a further increase in total yield or WUE. Therefore, the MRB planting system will be recommended in Siberian wildrye production for achieving relatively high forage yield and WUE.

Rainfall, temperature, and solar radiation are important climate factors, which determine crop growth, development and yield from instantaneous to decadal scales. We propose to identify year patterns of climate impact on yield on the basis of rain and non-rain weather. There are inter-related impacts of climatic factors on crop production within a specific pattern. Historical wheat yield data in Queensland during 1889-2004 were used. The influence of meteorological conditions on wheat yields was derived from statistical yield data which were detrended by 9-year-smoothing averages to remove the effects of technological improvements on wheat yields over time. Climate affects crop growth and development differently over different growth stages. Therefore, we considered the climate effects at both vegetative and reproductive stages (before and after flowering date, respectively) on yield. Cluster analysis was employed to identify the year patterns of climate impact. Five patterns were significantly classified. Precipitation during the vegetative stage was the dominant and beneficial factor for wheat yields while increasing maximum temperature had a negative influence. Crop yields were strongly dependent on solar radiation under normal rainfall conditions. As the effect of rainfall on soil water is relatively long-lasting, its beneficial effect in vegetative stage was higher than its effect during the reproductive stage. The Agricultural Production Systems sIMulator (APSIM) was evaluated using long-term historical data to determine whether the model could reasonably simulate effects of climate factors for each year pattern. The model provided good estimates of wheat yield when conditions resulted in medium yield levels, however, in extremely low or high yield years, corresponding to extremely low or high precipitation in the vegetative stage, the model tended to underestimate or overestimate. Under high growing season precipitation, simulations responded more favourably to reproductive stage rainfall than measured yields. 2013 Royal Meteorological Society.

Throughout the years, many studies have evaluated changes in soil organic carbon (SOC) mass on a fixed-depth (FD) basis without considering changes in soil mass caused by changing bulk density (ρb). This study evaluates the temporal changes in SOC caused by two factors: 1) changing SOC concentration; and 2) changing equivalent soil mass (ESM) in comparison with FD. In addition, this study evaluates calculating changes in SOC stock over time using a minimum equivalent soil mass (ESMmin) basis from a single sampling event compared with the FD scenario. A tillage [no-tillage (NT) and chisel plow (CP)]-crop rotation (multiple crop and continuous corn), and irrigation (full and delayed)) study was initiated in 2001 on Weld silt loam soil. After seven years, SOC concentration in the 0 - 30 cm depth was 19.7% greater in 2008 compared with 2001. Standardizing the soil mass of 2001 to the ESM of 2008 for each individual treatment showed an average gain in SOC of 5.8 Mg C·ha −1 in 2008 compared with 2001. However, the increase in SOC using ESM was twice the SOC gained with the FD calculation, where some treatments lost SOC after seven years of management. Estimating SOC levels using the ESMmin and, thereby, eliminating the confounding effect of soil ρb indicated that SOC stock was influenced by crop species and their interaction with irrigation, but not by tillage practices. Over all, the ESM calculation appears to be more effective in evaluating SOC stock than the FD calculation.

a b s t r a c t Greater precipitation use efficiency (PUE) and economic returns by increasing cropping frequency through the addition of summer crops to the dryland winter wheat-fallow (WF) cropping system have been reported in the semiarid Central Great Plains of USA. However, due to the highly variable nature of precipitation and uncertain water availability, selection of a crop with assured positive net returns to add to the system to increase cropping frequency is a challenge in the absence of reliable seasonal precipitation forecasts. The objective of this study was to evaluate long-term yields and net returns of several potential summer crops at various soil water contents at planting to assess their potential use in increasing dryland cropping frequency. Three grain crops (corn (Zea mays L.), canola (Brassica napus), and proso millet (Panicum miliaceum L.)) and two forage crops (foxtail millet (Setaria italica L. Beauv.) and spring triticale (X Triticosecale rimpaui Wittm.)) for which the Root Zone Water Quality Model (RZWQM2) had been calibrated at Akron, CO and/or Sidney, NE, were selected for investigation through modeling. The calibrated model was used to simulate yield responses of the crops to 25, 50, 75 and 100% of plant available water (PAW) in the soil profile at planting using recorded weather data from Akron, CO and Sidney, NE (1948-2008). Average costs of production and 10-yr average commodity prices for northeast Colorado were used to calculate net returns for each of the crops at the varying PAW levels. All crops showed significant (p < 0.05) simulated yield increases in response to increasing initial PAW levels when those changes occurred in the entire 0-180 cm soil profile. The two forage crops gave greater net returns than the three grain crops for all initial PAW levels when calculated with 10-yr average prices received. Among the grain crops, proso millet was slightly more profitable than corn at Akron, while corn was the least profitable crop at Sidney. Using current commodity prices (13 September 2011) resulted in proso millet being the least profitable crop at Sidney, while corn was the most profitable grain crop at Akron and showed net returns that were similar to those found for the forage crops. The results of this study may guide the selection of a spring- or summer-planted crop and help farmers assess risk as they contemplate intensifying the WF system by using a measure or estimate of PAW at planting. Published by Elsevier B.V.

Parameterizing a system model for field research is a challenge and requires collaboration between modelers and experimentalists. In this study, the Root Zone Water Quality Model-DSSAT (RZWQM2) was used for simulating plant responses to water stresses in eastern Colorado. Experiments were conducted in 2008, 2009, and 2010 in which maize (Zea Mays L.) was irrigated to meet a certain percentage (100%, 85%, 70%, 55%, and 40%) of the estimated crop evapotranspiration (ETc) demand during a growing season. The model was calibrated with both laboratory-measured and field-estimated soil water retention curves (SWRC) and evaluated for yield, biomass, leaf area index (LAI), and soil water content under five irrigation treatments in all three years. Simulated results showed that field-estimated SWRC provided better model responses to irrigation than laboratory-measured SWRC. The results also showed that there were multiple sets of plant parameters that achieved acceptable simulations when only one irrigation treatment was used for calibration. Model parameterization can be improved when multiple treatments and multiple years of data are included. The parameterized RZWQM2 model was capable of simulating various irrigation treatments in all years and could be used to schedule irrigation based on ETc requirement.

No-till dryland winter wheat ( Triticum aestivum L.)-fallow systems in the central Great Plains have more water available for crop production than the traditional conventionally tilled winter wheat-fallow systems because of greater precipitation storage efficiency. That additional water is used most efficiently when a crop is present to transpire the water, and crop yields respond positively to increases in available soil water. The objective of this study was to evaluate yield, water use efficiency (WUE), precipitation use efficiency (PUE), and net returns of cropping systems where crop choice was based on established crop responses to water use while incorporating a grass/broadleaf rotation. Available soil water at planting was measured at several decision points each year and combined with three levels of expected growing season precipitation (70, 100, 130% of average) to provide input data for water use/yield production functions for seven grain crops and three forage crops. The predicted yields from those production functions were compared against established yield thresholds for each crop, and crops were retained for further consideration if the threshold yield was exceeded. Crop choice was then narrowed by following a rule which rotated summer crops (crops planted in the spring with most of their growth occurring during summer months) with winter crops (crops planted in the fall with most of their growth occurring during the next spring) and also rotating grasses with broadleaf crops. Yields, WUE, PUE, value-basis precipitation use efficiency ($PUE), gross receipts, and net returns from the four opportunity cropping (OC) selection schemes were compared with the same quantities from four set rotations [wheat-fallow (conventional till), (WF (CT)); wheat-fallow (no-till), (WF (NT)); wheat–corn ( Zea mays L.)-fallow (no-till), (WCF); wheat–millet ( Panicum miliaceum L.) (no-till), (WM)]. Water use efficiency was greater for three of the OC selection schemes than for any of the four set rotations. Precipitation was used more efficiently using two of the OC selection schemes than using any of the four set rotations. Of the four OC cropping decision methods, net returns were greatest for the method that assumed average growing season precipitation and allowed selection from all possible crop choices. The net returns from this system were not different from net returns from WF (CT) and WF (NT). Cropping frequency can be effectively increased in dryland cropping systems by use of crop selection rules based on water use/yield production functions, measured available soil water, and expected precipitation.

Currently, canola (Brassica napus L.) is gaining importance as a potential feedstock in biodiesel production industries, increasing the demand for canola production acreage. Agricultural system models that simulate canola growth and yield will help to assess the feasibility of canola production under various agroclimatic conditions. In this study, we adapted the CROPGRO model for simulation of spring canola in both Root Zone Water Quality Model (RZWQM2) and Decision Support System for Agrotechnology Transfer (DSSAT 4.0). Soil water, phenology, leaf area index (LAI) , biomass, plant height, and grain yield data from irrigation experiments conducted in 2005 on a Weld silt loam soil (fine, smectitic, mesic Aridic Argiustoll) in the semiarid climate at Akron, CO were used for model parameterization and calibration. Similar data from 1993, 1994, and 2006 were used for validation. Species and cultivar parameters for canola were developed using data from literature or by calibrating the existing CROPGRO-faba bean (Vicia faba L.) parameters. Grain yields across various irrigation levels and seasons were simulated reasonably well by RZWQM2 with root mean square error (RMSE) of215 kg ha -1 and index of agreement (d) of 0.98. Seasonal biomass development was simulated with RMSEs between 341 and 903 kg ha -1 , d between 0.55 and 0.99, and R 2 between 0.85 and 0.98. The CROPGRO-canola parameters developed were also tested within the DSSAT 4.0 cropping systems model and found to produce results with similar accuracy.

Long-term crop rotation effects on crop water use and yield have been investigated in the Central Great Plains since the 1990s. System models are needed to synthesize these long-term results for making management decisions and for transferring localized data to other conditions. The objectives of this study were to calibrate a cropping systems model (RZWQM2 with the DSSAT v4.0 crop modules) for dryland wheat (Triticum aestivum L.), corn (Zea mays L.), and proso millet (Panicum miliaceum L.) production in the wheat-corn-millet (WCM) rotation from 1995 to 2008, and then to evaluate the model from 1992-2008 for two additional rotations, wheat―fallow (WF) and wheat-corn-fallow (WCF) on a Weld silt loam soil under no-till conditions. Measured biomass and grain yield for the above three rotations were simulated reasonably well with root mean squared errors (RMSEs) ranging between 1147 and 2547 kg ha ―1 for biomass, and between 280 and 618 kg ha ―1 for grain yield. Corresponding index of agreement (d) ranged between 0.70 and 0.95 for biomass, and between 0.87 and 0.97 for grain yield. The validated model was further used to evaluate two additional crop rotations: wheat-millet-fallow (WMF) and wheat-corn-millet-fallow (WCMF) (1993-2008) without prior knowledge of the two rotations. We found that the model simulated the mean and range of yield and biomass of the three crops well. These results demonstrated that RZWQM2 can be used to synthesize long-term crop rotation data and to predict crop rotation effects on crop production under the semiarid conditions of eastern Colorado.

Grain yields for dryland maize (Zea mays L.) production in the semi-arid Great Plains of the United States can be unpredictable because of the erratic nature of growing season precipitation. Because of the high input costs for maize production, farmers need to have a tool that will help them assess the risk associated with dryland maize production. The objectives of this work were to determine the critical period for precipitation during the maize growing season and to develop a relationship between critical period precipitation and maize yield to use as a tool to quantify expected yield variability associated with dryland maize production in this region. Maize yield data were collected at Akron, CO from two dryland cropping systems experiments (1984–2009) in which maize was grown in a 3-year winter wheat (Triticum aestivum L.)–maize–fallow rotation. Yields were correlated with weekly precipitation amounts from planting to harvest in search of the period of time in which yield was most influenced by precipitation. Soil water contents at planting were measured either by gravimetric sampling or by neutron attenuation. Yields were found to be most closely correlated with precipitation occurring during the 6-week period between 16 July and 26 August. The data separated into two linear relationships defined by whether the sum of available soil water at planting and May precipitation was less than or greater than 250 mm. These two linear relationships between precipitation during this critical period and yield were used with long-term precipitation records to determine the probability of obtaining a maize yield of at least 2500 kg ha−1 (generally considered to be a break-even yield) at three locations across the central Great Plains precipitation gradient. This analysis quantified the production risk associated with the highly variable corn yields that result from erratic summer precipitation in this region.

Plant water status is a key factor impacting crop growth and agricultural water management. Crop water stress may alter canopy temperature, the energy balance, transpiration, photosynthesis, canopy water use efficiency, and crop yield. The objective of this study was to calculate the Crop Water Stress Index (CWSI) from canopy temperature and energy balance measurements and evaluate the utility of CWSI to quantify water stress by comparing CWSI to latent heat and carbon dioxide (CO(2)) flux measurements over canopies of winter wheat (Triticum aestivum L) and summer maize (Zea mays L.). The experiment was conducted at the Yucheng Integrated Agricultural Experimental Station of the Chinese Academy of Sciences from 2003 to 2005. Latent heat and CO(2) fluxes (by eddy covariance), canopy and air temperature, relative humidity, net radiation, wind speed, and soil heat flux were averaged at half-hour intervals. Leaf area index and crop height were measured every 7 days. CWSI was calculated from measured canopy-air temperature differences using the Jackson method. Under high net radiation conditions (greater than 500 W m(-2)), calculated values of minimum canopy-air temperature differences were similar to previously published empirically determined non-water-stressed baselines. Valid measures of CWSI were only obtained when canopy closure minimized the influence of viewed soil on infrared canopy temperature measurements (leaf area index was greater than 2.5 m(2) m(-2)). Wheat and maize latent heat flux and canopy CO(2) flux generally decreased linearly with increases in CWSI when net radiation levels were greater than 300 W m(-2). The responses of latent heat flux and CO(2) flux to CWSI did not demonstrate a consistent relationship in wheat that would recommend it as a reliable water stress quantification tool. The responses of latent heat flux and CO(2) flux to CWSI were more consistent in maize, suggesting that CWSI could be useful in identifying and quantifying water stress conditions when net radiation was greater than 300 W m(-2). The results suggest that CWSI calculated by the Jackson method under varying solar radiation and wind speed conditions may be used for irrigation scheduling and agricultural water management of maize in irrigated agricultural regions, such as the North China Plain. Published by Elsevier B.V.

Precipitation storage efficiency (PSE) is the fraction of precipitation received in a given time period that is stored in the soil. Average fallow PSE for Great Plains wheat (Triticum aestivum L.)-fallow (W-F) production systems have ranged widely (10-53%). Study objectives were to compare PSE in conventionally tilled (CT) and no-till (NT) W-F systems over 10 seasons at Akron, CO, against published values and to identify meteorological conditions that may influence PSE. Soil water measurements were made four times during each fallow period, dividing the fallow season into three periods (first summer, fall-winter-spring, second summer). Precipitation was measured in the plot area and other meteorological conditions were measured at a nearby weather station. The 14-mo fallow PSE averaged 20% (range 8-34%) for CT and 35% (range 20-51%) for NT, much lower than previously reported for NT at Akron. During the second summer period, PSE was not different between the two systems. The largest PSE difference between the two systems was seen during the fall—winter—spring period (32 vs. 81%). Fallow soil water increased an average of 111 mm under CT and 188 mm under NT. The PSE during the three fallow periods was related to tillage, precipitation, air temperature, vapor pressure deficit, and wind speed, but sometimes counter-intuitively. A simple linear regression using inputs of tillage system, percentage of fallow precipitation events with amounts between 5 and 15 mm, and percentage of fallow precipitation events with amounts > 25 mm can be used to estimate PSE and fallow period water storage.

Dryland farming strategies in the High Plains must make efficient use of limited and variable precipitation and stored water in the soil profile for stable and sustainable farm productivity. Current research efforts focus on replacing summer fallow in the region with more profitable and environmentally sustainable spring and summer crops. In the absence of reliable precipitation forecasts for the crop growing season, farmers rely mainly upon knowledge of plant available water (PAW) in the soil profile at planting for making crop choice decisions. To develop a decision support strategy for crop selection based on initial PAW, experiments were conducted with spring triticale (X Titicosecale Wittmack), proso millet (Panicum miliaceum L.), and foxtail millet (Setaria italica L. Beauv.) under artificially controlled Low, Medium, and High initial PAW levels during 2004 and 2005 at Akron, Colorado, and Sidney, Nebraska. The objectives of this study were to adapt an existing cropping systems model for the simulation of triticale and millet and to evaluate simulations from the adapted model by comparing results with field data collected under varying initial PAW conditions. The Root Zone Water Quality Model with DSSAT v4.0 crop growth modules (RZWQM2) was used. Specifically, the Cropping System Model (CSM)–CERES–Wheat module was adapted for simulating triticale, and CSM–CERES– Sorghum (v4.0) module was adapted for simulating proso millet and foxtail millet. Soil water, leaf area index, grain yield, and biomass data for the highest PAW treatment from one crop season for each of the three crops were used to adapt and calibrate the crop modules. The models were then evaluated with data from the remaining PAW treatments. The proso millet module was further tested with four years of data from a crop rotation experiment at Akron from 2003 to 2006. Simulation results indicated that the adapted and calibrated crop modules have the potential to simulate these new crops under a range of varying water availability conditions. Consequently, these models can aid in the development of decision support tools for the season-to-season management of these summer fallow replacement crops under dryland conditions in semi-arid environments. Published by Elsevier B.V.

Farmers in the central Great Plains want to diversify crop rotations from the traditional monoculture system of winter wheat-fallow. Corn (Zea mays L.) could work well as a rotation crop, but inputs are expensive and farmers would like to know the chances of producing a certain yield before investing in seed, fertilizer, herbicides, etc. Information on the yield response of corn to available soil water at planting could help guide the crop choice decision regarding corn. This study was conducted to determine if a predictive relationship exists between dryland corn yield and available soil water at planting time and, if such a relationship exists, to use it to assess the risk in obtaining profitable yields. Yield and soil water data from 10 years of a dryland crop rotation study at Akron, CO were analyzed by linear regression to determine predictive relationships. The yield-soil water content production function was highly variable, with values ranging from 0.0 to 67.3 kg ha � 1 per mm of available soil water in the 0 to 1.8 m soil profile at planting. The differences in yield response to soil water were related to the amount and timing of precipitation that fell during the corn growing season. Because dryland corn yield is highly dependent on precipitation during reproductive and grain-filling stages, soil water content at corn planting cannot be used alone to reliably determine whether corn should be planted in a flexible rotational system. The predictive relationships developed in this study indicate that under typical amounts of available soil water at corn planting, profitable corn production under dryland conditions is a risky and speculative activity in the central Great Plains of the United States.

Proso millet (Panicum miliaceum L.) (PM) is an important crop for dryland rotations in the central Great Plains. The crop is traditionally swathed before combining to promote uniform drying of the panicle and to minimize seed shattering losses. Direct harvesting of PM with a stripper-header would eliminate the swathing operation resulting in cost savings, and increased standing crop residues to enhance erosion protection, snow catch, and precipitation storage efficiency. This study was conducted to determine yield differences between conventionally swathed and stripper-header harvested PM and to compare PM residue mass and orientation following the two harvest techniques. The study was conducted over four growing seasons at Akron, CO. Proso millet was harvested either by swathing and then picking up the swath with a combine, or by direct harvesting with a stripper-header attached to the combine. Seed yields and moisture contents at harvest were not significantly different between treatments. About 20% more seed was found on the ground with the stripper-header harvest than with the conventionally swathed harvest, but the increased shattering resulted in only about 1% loss of the average final yield. Using a stripper-header resulted in both the standing residue mass and the silhouette area index following harvest to be four times greater than in conventionally swathed PM. A stripper-header can be used to successfully direct harvest PM thereby reducing harvest costs and increasing surface crop residues following harvest.

RZ-SHAW is a hybrid model, comprised of modules from the Simultaneous Heat and Water (SHAW) model integrated into the Root Zone Water Quality Model (RZWQM) that allows more detailed simulation of different residue types and architectures that affect heat and water transfer at the soil surface. RZ-SHAWallows different methods of surface energy flux evaluation to be used: (1) the SHAW module, where evapotranspiration (ET) and soil heat flux are computed in concert with a detailed surface energy balance; (2) the Shuttleworth‐Wallace (S‐W) module for ET in which soil surface temperature is assumed equal air temperature; and (3) the PENFLUX module, which uses a Penman transformation for a soil slabunder incomplete residue cover. The objective of this study was to compare the predictive accuracy of the three RZ-SHAW modules to simulate effects of residue architecture on net radiation, soil temperature, and water dynamics near the soil surface. The model was tested in Akron, Colorado in a wheat residuecovered (both standing and flat) no-till (NT) plot, and a reduced till (RT) plot where wheat residue was incorporated into the soil. Temperature difference between the soil surface and ambient air frequently exceeded 17 8C under RT and NT conditions, invalidating the isothermal assumption employed in the S‐W module. The S‐W module overestimated net radiation (Rn )b y an average of 69 Wm � 2 and underestimated the 3-cm soil temperature (Ts3) by 2.7 8C for the RT plot, attributedto consequences of the isothermal assumption. Both SHAWand PENFLUX modules overestimated midday Ts3 for RT conditions but underestimated Ts3 for NT conditions. Better performances of the SHAW and PENFLUX surface energy evaluations are to be expected as both approaches are more detailed and consider a more discretized domain than the S‐W module. PENFLUX simulated net radiation slightly better than the SHAW module for both plots, while Ts3 was simulated the best by SHAW, with a mean bias error of +0.1 8C for NTand +2.7 8C for RT. Simulation results for soil water content in the surface 30 cm (uv30) were mixed. The NT conditions were simulated best by SHAW, with mean bias error for uv30 within 0.006 m 3 m � 3 ; RT conditions were simulated best by the PENFLUX module, which was within 0.010 m 3 m � 3 .

No-till cropping systems in the semiarid West have the potential to improve soil physical properties by increasing cropping intensity and crop diversity. An investigation at Akron, CO, compared soil conditions in winter wheat (Triticum aestivum L.)-summer fallow (WF) plots with soil conditions in wheat-corn (Zea mays L.)-fallow (WCF), wheat-corn-sunflower (Helianthus annus L.)-fallow (WCSF), wheat-corn-millet (Panicum miliaceum L.) (WCM), and a perennial grass/legume mix. The study began in 1990. Bulk density, pore size distribution, and saturated hydraulic conductivity were measured 7, 11, and 15 yr after inception. Bulk density in the grass plots decreased from 1.39 to 1.25 Mg m -3 in 15 yr. Bulk density in the annually cropped plots decreased from 1.38 to 1.30 Mg m -3 during the same time period. The pore size distribution became more uniform among the cropped treatments 15 yr after the start of the experiment. Saturated hydraulic conductivity increased in the grass plots from 27 mm h -1 to 98 mm h -1 in 15 yr. Saturated hydraulic conductivity in the annually cropped plots increased from about 14 to about 35 mm h -1 during the same period. The results from this study show that improving soil physical properties by cropping system alone may take many years. Perennial vegetation may be more effective than annually cropped systems at improving soil physical conditions because of less surface compaction from planting operations and the apparent ability of perennial root systems to create a more stable, continuous pore network.

An agricultural system model can help optimize limited irrigation for higher grain yield and water use efficiency (WUE) across varied climatic conditions. In this study, the Root Zone Water Quality Model (RZWQM2) was first calibrated to simulate soil water, ET, and corn (Zea mays L.) yield under a range, 40 to 100% of crop ET under well-watered conditions (i.e., ETc, calculated by the reference ET and crop coefficient), of irrigation treatments from 2008 to 2011 in Colorado. The model was then used to explore grain yield responses to irrigation levels of 40, 60, 80, and 100% ETc (the Shuttleworth–Wallace ET, ETsw, was used as a surrogate for ETc in the model) under 300, 400, and 500 mm of total irrigation water and to provide guidelines to manage limited irrigation using weather data from 1992 to 2013. With 500 mm of irrigation water, high grain yield and WUE were obtained from the 100% ETsw for the vegetative stage and 80 to 100% ETsw for the reproductive stage. With 400 mm of irrigation water, high grain yield and WUE were simulated at 80 to 100% ETsw irrigation targets between the vegetative and reproductive stages. With 300 mm of irrigation water, however, meeting 100% ETsw at the reproductive and 60% ETsw at the vegetative stage achieved the highest grain yield and WUE. Simulations showed that meeting the crop water requirement during the reproductive stage is more important than during the vegetative stage to achieve high grain yield and WUE under water-limited conditions.

Forages, with greater water use efficiency (WUE) than grain and seed crops, could be used to diversify reduced and no-till dryland cropping systems from the traditional wheat (Triticum aestivum L.)– fallow system in the semiarid central Great Plains. However, farmers needasimpletooltoevaluateforageproductivity underwidelyvarying precipitation conditions. The objectives of this study were to (i) quantify the relationship betweencrop water use and dry matter (DM) yield for corn (Zea mays L.), foxtail millet (Setaria italica L. Beauv.), and winter triticale (X Triticosecale Wittmack); and (ii) determine the range and distribution of expected DM yields for these three crops in the central Great Plains based on historical precipitation records. The three crops were grown in a dryland no-till corn–millet–triticale sequence from 1998 through 2004 at Akron, CO. Dry matter production was linearly correlated with water use for all three crops, with regressionslopes ranging from24.2(corn) to 33.0kgha 21 mm 21 (millet). Water use efficiency varied widely from year to year (0–32.2 kg ha 21 mm 21 ) for the three crops, as influenced by growing season precipitation and time of year in which the crops were grown. Millet and triticale produced similar amounts of DM for a given water use, while corn produced less. Precipitation use efficiency for the millet–triticale– corn forage system was 8.7 kg ha 21 mm 21 , suggesting this as an efficient forage system for the region. P ROFITABLE agricultural operations in the semiarid central Great Plains must make efficient use of limited and highly variable precipitation. Additionally, cropping systems should be diversified, employing crop rotation systems that minimize disease, weed, and insect problems associatedwith monoculture. Further, thosesystems need toensurethatsufficientcropresiduesremainafterharvest to protect the soil surface from wind erosion and to maximize precipitation storage efficiency during the noncrop periods. A recent review of cropping systems across the Great Plains region of North America (Nielsen et al., 2005a) indicated that systems using forages generally had greater WUE and precipitation use efficiencies (based on both massproduced per unitof precipitationreceivedand gross value of product per unit of precipitation received) than systems that did not include forages. Three crops that may have potential to be grown for forage in dryland cropping systems in the central Great Plains region are corn, foxtail millet, and winter triticale. Corn is often grown for silage under rainfed conditions in the Corn Belt and under irrigation in the semiarid Great Plains, but a defined DM response to water

layers with both CT and NT in WF in western Nebraska and concluded that cropping intensification would be The Root Zone Water Quality Model (RZWQM) is a comprehennecessary to reverse the decline. Studies oriented toward sive agricultural system model with the capacity to predict crop–environmental response to varying soil and crop management systems. amelioration of adverse impacts of WF(CT) on soil qualOur objective was to evaluate RZWQM for its ability to simulate a ity and productivity increased substantially throughout 2-yr winter wheat (Triticum aestivum L.)–fallow (WF) rotation and a the Great Plains in recent years. Numerous research more complex wheat–corn (Zea mays L.)–fallow (WCF) rotation un- efforts emphasized developing better cropping and tillder tilled and no-till (NT) conditions on a Weld silt loam soil in semi- age practices for optimum use of available rainfall and arid northeastern Colorado. Measured data from all phases of both minimal environmental impact (Halvorson, 1990; Anrotations were compared with simulated values using root mean derson et al., 1999). To develop environmentally sound square error (RMSE) values to quantify the agreement. Soil water croppingsystemsasalternativestoWF(CT),fieldexperin different layers, total soil profile (180 cm) water contents, and grain iments were established in 1990 on a Weld silt loam soil yield were accurately predicted with RMSEs ranging between 0.055

state-of-the-science into their models. In this study, the CROPGRO plant growth model of Decision Support System for Agrotechnology chemical) in an agricultural system based on current Transfer (DSSAT v3.5) was linked to the Root Zone Water Quality theoreticalandexperimental knowledge,processdetails Model (RZWQM) to provide RZWQM users an option of using of the models vary widely depending on the objectives CROPGRO. In the hybrid model, RZWQM supplied CROPGRO and timeframe of the model developers (Ma and Shafwith daily soil water and N, soil temperature, and potential evapotranspi- fer, 2001; McGechan and Wu, 2001). Many agricultural ration (PET), whereas CROPGRO supplied RZWQM with daily water system models use components from other existing and N uptake and plant growth variables. The RZWQM-CROPGRO models to save development time. For example, the hybrid model was then evaluated against the original CROPGROoriginal soybean [Glycine max (L.) Merr.] crop growth soybean model using several data sets from the literature. These data model, SOYGRO, developed at the University of Florsets represented various drought conditions. Results showed that the ida, used the soil water and N balance component from RZWQM-CROPGRO hybrid model simulated higher water stress

Successful dryland crop production in the semiarid Great Plains of North America must make efficient use of precipitation that is often limited and erratic in spatial and temporal distribution. The purpose of this paper is to review research on water use efficiency and precipitation use efficiency (PUE) as affected by cropping system and management in the Great Plains. Water use efficiency and PUE increase with residue management practices that increase precipitation storage efficiency, soil surface alterations that reduce runoff, cropping sequences that minimize fallow periods, and use of appropriate management practices for the selected crop. Precipitation use efficiency on a mass-produced basis is highest for systems producing forage (14.5 kg ha - 1 mm - 1 ) and lowest for rotations with a high frequency of oilseed crops (4.2 kg ha - 1 mm - 1 ) or continuous small-grain production in the southern plains (2.8 kg ha - 1 mm - 1 ). Precipitation use efficiency when calculated on a price-received basis ranges from $1.20 ha - 1 mm - 1 (for an opportunity-cropped system with 4 of 5 yr in forage production in the southern plains) to $0.30 ha - 1 mm - 1 {for a wheat (Triticum aestivum L.)-grain sorghum [Sorghum bicolor (L.) Moench]-fallow system in the southern plains}. Throughout the Great Plains region, PUE decreases with more southern latitudes for rotations of similar makeup of cereals, pulses, oilseeds, and forages. Forage systems in the southern Great Plains appear to be highly efficient when PUE is computed on a price-received basis. In general across the Great Plains, increasing intensity of cropping increases PUE on both a mass-produced basis and on a price-received basis.

Corn (Zea mays L.) production in northeastern Colorado is constrained by a frost-free period averaging 11 May to 27 September. For optimization of yield, planting at the appropriate time to fit the hybrid maturity length and growing season is critical. Crop models could be used to determine optimum planting windows for a locality. We calibrated the plant parameters of the Root Zone Water Quality Model (RZWQM) and genetic coefficients for the CERES-Maize model and validated their performance against experimental data of three corn hybrids varying in days to maturity, planted on three planting dates in 2 yr at Akron, CO, under irrigation. Both models could be calibrated to predict leaf area index, soil water content, crop water use, and yield with similar levels of accuracy. Both models simulated the observed decline in yield with delayed planting date, but CERES-Maize simulated the yield from the latest planting date much more accurately for all three hybrids than did RZWQM (13% underpredicted by CERES-Maize; 50% overpredicted by RZWQM). Using the long-term Akron weather record, the latest planting dates for the short-, mid-, and long-season hybrids to have a 50% chance of achieving a break-even yield under irrigation were 13 May, 20 May, and 6 May, respectively. Long-term simulations also revealed that the longer maturity length hybrids lose yield faster than short maturity length hybrids with planting delay. The information generated by either RZWQM or CERES-Maize can be useful for making both planting and replanting decisions for corn hybrids of varying maturity length in northeastern Colorado.

Agricultural system models can provide an alternative, less time-consuming and inexpensive means of determining the optimum crop N requirement under varied soil and climatic conditions. In this context, we parameterized the Root Zone Water Quality Model (RZWQM) for winter wheat (Triticum aestivum L.) production and then evaluated it along with the CERES-Wheat model to assess their potential as N management tools at Akron, Co. Both models were evaluated with data from five N treatments (0, 28, 56, 84, and 112 kg N ha -1 ) and three crop seasons (1987-1988, 1988-1989, and 1989-1990). Data from 1987-1988 zero-N treatment were used for model calibration, and the rest of the data were used for model validation. Genetic coefficients for winter wheat (cv. TAM 107) were developed for the CERES-Wheat model. The crop parameters required for the generic crop model of RZWQM were parameterized using information from the literature or by calibration. Both models were calibrated first for soil moisture and then for biomass and grain yield. Grain yield predictions had a root mean square error (RMSE) of 500 and 363 kg ha -1 , respectively, for CERES-Wheat and RZWQM. Aboveground biomass was predicted with RMSEs of 1247 and 1441 kg ha -1 , respectively. Long-term simulations of both RZWQM and CERES for winter wheat growth using historical weather data (1912-2001) showed that 56 kg ha -1 N applied as broadcast incorporated is a viable N management option in eastern Colorado, taking into account the grain yield, crop N uptake, N leaching into groundwater, and residual soil N at harvest. Model simulations also showed that the wheat-fallow cropping system is less water use efficient than a continuous wheat system under rainfed agriculture in eastern Colorado.