Search

Underground aquifers that took millions of years to fill are being depleted due to unsustainable water withdrawals for crop irrigation. Concurrently, atmospheric warming due to anthropogenic greenhouse gases is enhancing demands for water inputs in agriculture. Accurate information on crop-ecosystem water use efficiencies [EWUE, amount of CO2 removed from the soil-crop-air system per unit of water used in evapotranspiration (ET)] is essential for developing environmentally and economically sustainable water management practices that also help account for CO2, the most abundant of the greenhouse gases, exchange rates from cropping systems. We quantified EWUE of corn (a C4 crop) and soybean and cotton (C3 crops) in a predominantly clay soil under humid climate in the Lower Mississippi (MS) Delta, USA. Crop-ecosystem level exchanges of CO2 and water from these three cropping systems were measured in 2017 using the eddy covariance method. Ancillary micrometeorological data were also collected. On a seasonal basis, all three crops were net sinks for CO2 in the atmosphere: corn, soybean, and cotton fixed −31,331, −23,563, and −8856 kg ha−1 of CO2 in exchange for 483, 552, and 367 mm of ET, respectively (negative values show that CO2 is fixed in the plant or removed from the air). The seasonal NEE estimated for cotton was 72% less than corn and 62% less than soybean. Half-hourly averaged maximum net ecosystem exchange (NEE) from these cropping systems were −33.6, −27.2, and −14.2 kg CO2 ha−1, respectively. Average daily NEE were −258, −169, and −65 kg CO2 ha−1, respectively. The EWUE in these three cropping systems were 53, 43, and 24 kg CO2 ha−1 mm−1 of water. Results of this investigation can help in adopting crop mixtures that are environmentally and economically sustainable, conserving limited water resources in the region.

Quantification of evapotranspiration (ETc) from crops is critical in irrigation scheduling in agriculture. In a pioneering study, in the Mississippi (MS) Delta region, we quantified ETc from soybean (Glycine max L.) using the eddy covariance (EC) approach (ETe). We also monitored ETc using a residual energy balance (EB) approach (ETb) and compared the fluxes. The unclosed energy fluxes in the EC were post-analysis closed using the Bowen ratio (BR) and latent heat (LH) methods. The measurements were conducted in a 35-ha clay soil planted to irrigated soybean in the lower MS Delta in 2016. The crop reached physiological maturity in 126 days after emergence (DAE). Maximum LAI was 5.7 and average grain yield was 4900 kg ha−1. The EC showed an energy balance closure of about 88% on a 30 min and 90% on a daily flux accumulation. The ETe was 18.2, 6.8, and 15.9% lower than ETb, and ETe corrected using BR (ETebr) and LH (ETele) approaches, respectively. Average soybean seasonal ETe, ETb, ETebr, and ETele were 422, 499, 451, and 490 mm, respectively. Seasonal reference-crop evapotranspiration for alfalfa (ETo) and grass (ETr) were 470 and 547 mm, respectively. Daily ETe, ETb, ETebr, ETele, ETo, and ETr averaged across the whole season were 4.4, 5.2, 4.7, 5.1, 4.9, and 5.7 mm, respectively. For scheduling irrigations, based on grass and alfalfa reference crop ET calculated from weather data, averages of the ETe, ETb, ETebr, and ETele daily estimates were used in deriving crop coefficients (Kc). The Kc for grass reference varied between 0.56 and 1.29 and for alfalfa reference varied between 0.56 and 1.02. The information developed will be useful for scheduling irrigations in the MS Delta region, and the methodology developed can be adapted for generating similar information elsewhere.

Accurate quantification of crop evapotranspiration (ET) is critical to optimizing irrigation water productivity, especially, in the semiarid regions of the world where limited rainfall is supplemented by irrigation for crop production. In this context, cropping system models are potential tools for predicting ET or crop water requirements in agriculture across soils and climates and assist in developing decision support tools for irrigation. The objective of this study was to evaluate the accuracy of RZWQM2 simulated ET for fully irrigated silage (2006 and 2007) and grain corn (1990) against measured crop water use and soil evaporation with large weighing lysimeters in the Texas High Plains. An extended Shuttleworth and Wallace method was used to estimate potential crop ET (E and T) demand in RZWQM2. The Nimah and Hanks approach was used for crop water uptake and Richard’s Equation for soil water redistribution modeling. Simulations of biomass, leaf area index, soil water storage, and ET were reasonably close to the measured data. Root Mean Squared Deviation (RMSD) for corn biomass was between 1 and 2.1 MT ha−1, LAI between 0.33 and 0.88, water in the soil between 2 and 2.9 cm for a 190 cm soil profile, and actual daily crop ET between 1.0 to 1.5 mm across the three years of measured data. Arithmetic mean deviation (MD) for ET ranged from −0.10 to 0.40 mm. Fallow soil evaporation before and after corn planting was simulated within MD of −0.03–0.003 mm. The crop coefficients (Kc) calculated with measured ET and the short grass or alfalfa crop reference ET methods varied from year to year. The Kc values obtained by using the simulated ET and alfalfa reference ET were close to Kc values using measured ET, within RMSD of 0.17, and could be used to obtain long-term average Kc values for scheduling irrigation.

Accurate quantification of consumptive water requirements (ETc, evapotranspiration) of cropping systems is a critical prerequisite for sustainable irrigation water management applications. For applying the ETc for irrigation scheduling across soils and climates other than the location in which it was measured, it is also critical to develop crop coefficients (Kc) that link a reference crop evapotranspiration computed from local weather data to ETc. A systematic study for deriving Kc for cotton (Gossypium hirsutum L.) - representing its growth stages from planting to harvest - in humid climates is lacking in the literature. In this study, we used an eddy covariance (EC) method to quantify ETc from irrigated cotton (Gossypium hirsutum L.) in a 250 ha field with a Tunica clay soil, in 2017 and 2018. In the EC experiment, an open-path infrared gas analyzer and a sonic 3-D anemometer were deployed in the constant flux layer above the cotton canopy for collecting crop-canopy water flux data. Using the measured ETc, Kc were derived for alfalfa (Kcr) and grass (Kco) reference crop ET computed from weather data. Cotton cv. Delta Pine Land 1522 was planted in the first week of May and harvested in the second week of September in both the years. Lint yield was 1269 kg ha−1 in 2017 and 1569 kg ha−1 in 2018. Measured monthly averaged daily ETc ranged between 2.5 mm in May/September to 4 mm in July in 2017, and between 2.9 mm in May and 4.4 mm in August in 2018. Maximum daily ETc in 2017 and 2018 crop seasons were 5.6 and 6.7 mm, respectively. Seasonal total ETc was 367 mm and 439 mm (on average 402 mm), respectively. Alfalfa (ETr) and grass reference crop ET (ETo) computed were 664 and 546 mm, respectively. Averaged across the two years, average daily Kcr ranged between 0.45 in May to 0.80 in August, and Kco ranged from 0.54 in May and 0.99 in August. On average, seasonal ETr was 18 % more than ETo. Seasonal ETr and ETo were, respectively, 39 % and 22 % more than ETc. The Kc data developed will be useful for irrigation scheduling in cotton grown in similar climates and soils.

Agricultural management practices control soil organic carbon (SOC) content in croplands. Long-term cropping system experiments offer a great opportunity to understand the magnitude and direction of SOC change in response to management practices. Such information is very limited from the southeastern US, a region with warm and humid climatic conditions that typically favor SOC decomposition over accumulation. Therefore, this study was conducted to assess the effect of 39 years of chisel plow (CP), disc plow (DP), moldboard plow (MP), no-tillage (NT), NT with winter wheat (Triticum aestivum L.) cover crop (NTW), and NT with wheat-soybean (Glycine max L.) double crop (NTWD) on total SOC and SOC fractions including permanganate oxidizable C (POXC), water extractable C (WEC), resistant C (RC), and aggregate-associated SOC in a continuous soybean system. Additionally, aggregate size distribution, mean weight diameter (MWD), and wet aggregate stability (WAS) were determined. Results showed that NTW and NTWD significantly increased SOC and POXC compared to MP with mean SOC (g kg⁻¹ soil) of 12.2 (NTW) ≥10.9 (NTWD) >7.2 (MP) and mean POXC (mg kg⁻¹ soil) of 465 (NTWD) ≥418 (NTW) >252 (MP). The WEC and RC fractions did not differ among treatments. Across the treatments, the greatest aggregate-associated SOC concentration was found in microaggregates (0.053–0.25 mm) and the lowest in clay- and silt-size particles ( 0.6, p

Agricultural system simulation models are key tools for assessment of possible impacts of climate change on crop production and environmental quality. In this study, the CERES-Wheat 4.0 module in the RZWQM2 model was calibrated and validated for simulating spring wheat grown under elevated CO2 conditions in the FACE (Free Air CO2 Enrichment) experiments conducted at Maricopa, Arizona, USA from 1992 to 1997. The validated model was then used to simulate the possible impacts of climate change on the crop for a 16-year period centered on 2050 with a projected atmospheric CO2 concentration of 550 ppm. Sixteen General Circulation Model (GCM) projections of climate in response to this CO2 concentration were used for this purpose. In the FACE experiment, the crops were grown under ambient (365–370 ppm) and elevated (∼550 ppm) CO2 concentrations with two irrigation treatments (wet and dry) in 1992–1993 and 1993–1994, and two nitrogen (N) treatments (high and low N) in 1995–1996 and 1996–1997 crop seasons. The model simulated crop growth and grain yield, and soil water responses to CO2 reasonably well, reproducing variations due to the treatments. Under ambient CO2 in 1992–1993 and 1995–1996, biomass was simulated better in the dry and low N treatments with root mean square difference (RMSD) of 181 and 161 kg ha−1, respectively, compared to the wet and high N treatments with RMSD of 259 and 268 kg ha −1 , respectively. The effects of water and N treatments were higher than those of CO2, and the model reproduced these effects well. Elevated CO2 effects on crop growth were counterbalanced by temperature effects, and projected precipitation had little effect on the simulated crop. The model results provide reasonable confidence for simulations of possible impacts of projected climate change on wheat crop growth in the region, within normal field data uncertainties.