Potato (Solanum tuberosum L.), the fourth important global food crop, is sensitive to stress of soil water and temperature, especially in arid regions. To mitigate the stress, plastic film mulch combined with drip irrigation has been widely adopted to improve thermal and moisture conditions and potato growth which depend on the film color. Critically, it is challenging to predict soil water and temperature and potato growth under different colored film mulches. Process-based simulation models offer a powerful tool to address this complexity. However, the capability of the modified RZ-SHAW model to accurately simulate the soil hydrothermal conditions and the drip irrigated potato growth under different colored plastic films has not been adequately evaluated. In this research, the simulation ability of the modified RZ-SHAW model on soil moisture, soil temperature, yield, water consumption, leaf area index, and dry matter under transparent mulch (TM), no mulch (NM), and black mulch (BM) treatments was evaluated using two years of field potato experimental data. The simulation results showed that the modified RZ-SHAW model effectively captured soil water and temperature variations during the entire potato growth stage. The average root means squared error (RMSE) for soil water content was 0.029, 0.038, and 0.037 cm3 cm-3, and for soil temperature was 3.0, 2.0, and 3.0 degrees C with TM, NM, and BM, respectively. The relative RMSEs (RRMSE) were 15.3%, 22.0%, and 19.9% for soil water content and 17.0%, 11.7%, and 17.6% for soil temperature with TM, NM, and BM, respectively. The modified RZ-SHAW model had an advantage in the simulation of crop evapotranspiration and tuber yield. Overall, this model can simulate soil water and heat condition and potato growth under colored film mulches, which can provide guidelines for high yield potato cultivation.

Bermudagrass (Cynodon dactylon, L.) is widely used as a forage in ruminant diets owing to its nutritional value and its capacity to grow under various agroecological conditions. For the southeastern United States climate conditions, previous research on bermudagrass recommended the cultivar Tifton 85 for forage production and a monthly frequency for forage-cutting. Even though bermudagrass cultivars are known to positively respond to nitrogen (N) fertilization, the interplay of the forage-cutting and N fertilization rates is not well understood. As a result, there is not sufficient guidance for adequate harvesting schedules and fertilization management to optimize bermudagrass forage production. Hence, this study aims to clarify the interplay of biomass-cutting events and N fertilization rates on forage quality and quantity, and N footprint. The study used experimental data of bermudagrass Tifton 85 forage production under three N fertilization rates (i.e., high = 504 kg N ha(-1), medium = 336 kg N ha(-1), and low = 168 kg N ha(-1)), to calibrate and validate Root Zone Water Quality Model 2 (RZWQM2) for biomass weight and biomass N content. For each N fertilization rate, multiyear simulations of four biomass-cutting scenarios were used to investigate the joint effects of harvesting schedules and N fertilization rates on biomass weight, biomass N content, N use efficiency (NUE), and N leaching. Results show statistically significant effects of the biomass-cutting scenarios on biomass weight and biomass N content for both high and medium N fertilization rates. The interplay of biomass-cutting and N fertilization reflected differently on forage quality and quantity, and N footprint. The low N fertilization did not show any statistically significant effect except for the biomass weight. NUE values were higher with both medium and low N fertilization rates compared to the high N fertilization which showed a relatively high N leaching. The outcomes of this study can be used to inform bermudagrass cutting and fertilization options to achieve forage yield goals with an understanding of the potential environmental consequence of N leaching and low NUE.

Advances in biological degradation of per- and polyfluoroalkyl substances (PFAS) have shown that bioremediation is a promising method of PFAS mineralization; however, most of these studies focus on remediation of more reactive polyfluorinated compounds. This review focuses on the defluorination of the more recalcitrant perfluorinated alkyl acids (PFAAs) by bacteria. We highlight key studies that report PFAA degradation products, specific bacteria, and relevant genes. Among these studies, we discuss trends in anaerobic versus aerobic conditions with specific bacterial species or consortia. This holistic review seeks to elucidate the state of PFAA biodegradation research and discuss the need for future research for environmental application.

Acidimicrobium sp. strain A6 is a recently discovered autotrophic bacterium that is capable of oxidizing ammonium while reducing ferric iron and is relatively common in acidic iron-rich soils. The genome of Acidimicrobium sp. strain A6 contains sequences for several reductive dehalogenases, including a gene for a previously unreported reductive dehalogenase, rdhA. Incubations of Acidimicrobium sp. strain A6 in the presence of perfluorinated substances, such as PFOA (perfluorooctanoic acid, C8HF15O2) or PFOS (perfluorooctane sulfonic acid, C8HF17O3S), have shown that fluoride, as well as shorter carbon chain PFAAs (perfluoroalkyl acids), are being produced, and the rdhA gene is expressed during these incubations. Results from initial gene knockout experiments indicate that the enzyme associated with the rdhA gene plays a key role in the PFAS defluorination by Acidimicrobium sp. strain A6. Experiments focusing on the defluorination kinetics by Acidimicrobium sp. strain A6 show that the defluorination kinetics are proportional to the amount of ammonium oxidized. To explore potential applications for PFAS bioremediation, PFAS-contaminated biosolids were augmented with Fe(III) and Acidimicrobium sp. strain A6, resulting in PFAS degradation. Since the high demand of Fe(III) makes growing Acidimicrobium sp. strain A6 in conventional rectors challenging, and since Acidimicrobium sp. strain A6 was shown to be electrogenic, it was grown in the absence of Fe(III) in microbial electrolysis cells, where it did oxidize ammonium and degraded PFAS.

Per- and polyfluoroalkyl substances (PFAS) are emerging contaminants of concern due to their health effects and persistence in the environment. Although perfluoroalkyl acids (PFAAs), such as perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) are very difficult to biodegrade because they are completely saturated with fluorine, it has recently been shown that Acidimicrobium sp. A6 (A6), which oxidizes ammonium under iron reducing conditions (Feammox process), can defluorinate PFAAs. A kinetic model was developed and tested in this study using results from previously published laboratory experiments, augmented with results from additional incubations, to couple the Feammox process to PFAS defluorination. The experimental results show higher Feammox activity and PFAS degradation in the A6 enrichment cultures than in the highly enriched A6 cultures. The coupled experimental and modeling results show that the PFAS defluorination rate is proportional to the rate of ammonium oxidation. The ammonium oxidation rate and the defluorination rate increase monotonically, but not linearly, with increasing A6 biomass. Given that different experiments had different level of Feammox activity, the parameters required to simulate the Feammox varied between A6 cultures. Nonetheless, the kinetic model was able to simulate an anaerobic incubation system and show that PFAS defluorination is proportional to the Feammox activity.

Highlights The macropore component of RZWQM2 was evaluated using hourly drainage and rainfall data. Activating macropore components improved hourly drainage peak simulation. Macropore flow simulated by RZWQM2 was insensitive to the macroporosity and pore radius. Abstract. Understanding preferential flow through soil macropores is critical to effectively managing subsurface drainage water quantity and quality. This study aims to assess the macropore component of the Root Zone Water Quality Model (RZWQM2) in simulating subsurface tile flow with a high time resolution. Observed hourly tile flow rates from two experimental sites in Ontario, Canada (2008-2011) and Iowa, USA (2007-2008) were used to evaluate the importance of including a macropore flow component in subsurface drainage simulation. Activating the macropore component in the model improved the simulation of hourly drainage peaks, especially peak amplitude. Still, it did not improve the simulation of the total drainage amount for each rainfall event. Simulation of the drainage peak recession varied from peak to peak, suggesting that further studies are warranted for drainage flow in the model. In general, the macropore component in the RZWQM2 model improved subsurface peak subsurface simulation at the hourly resolution. However, further investigation and model modifications are needed to improve the drainage simulation’s timing and quality for RZWQM2’s hydrologic simulation of macropore flow and subsurface drainage. Keywords: Macropores, RZWQM2, Subsurface drainage modelling, Preferential flow simulation.

Anaerobic incubations were performed with biosolids obtained from an industrial wastewater treatment plant (WWTP) that contained perfluorooctanoic acid (PFOA), and with per- and polyfluoroalkyl substances- (PFAS) free, laboratory-generated, biosolids that were spiked with PFOA. Biosolid slurries were incubated for 150 days as is, after augmenting with either Acidimicrobium sp. Strain A6 or ferrihydrite, or with both, Acidimicrobium sp. Strain A6 and ferrihydrite. Autoclaved controls were run in parallel. Only the biosolids augmented with both, Acidimicrobium sp. Strain A6 and ferrihydrite showed a decrease in the PFOA concentration, in excess of 50% (total, dissolved, and solid associated). Higher concentrations of PFOA in the biosolids spiked with PFOA and no previous PFAS exposure allowed to track the production of fluoride to verify PFOA defluorination. The buildup of fluoride over the incubation time was observed in these biosolid incubations spiked with PFOA. A significant increase in the concentration of perfluoroheptanoic acid (PFHpA) over the incubations of the filter cake samples from the industrial WWTP was observed, indicating the presence of a non-identified precursor in these biosolids. Results show that anaerobic incubation of PFAS contaminated biosolids, after augmentation with Fe(III) and Acidimicrobium sp. Strain A6 can result in PFAS defluorination.

The increasing contamination of heavy metals in agricultural soils and its impact on the nitrogen (N) cycle and N use efficiency have attracted considerable attention in recent years. In this study, agricultural soils neighboring the Dabaoshan copper mining area (DBS) and Qingyuan electronic-waste recycling area (QY), in Guangdong, China, were sampled to study the interaction between heavy metals and nitrification/denitrification processes, especially the related microbial functional profiles. Results showed that the contamination of heavy metals affected nitrifiers and denitrifiers differently. The potential nitrification activity was about four times lower in metal-polluted soils compared with the unpolluted ones, with a significant decrease in the abundance of amoA and nxrB (p < 0.05) in the polluted samples. On the other hand, the potential denitrification activity was more metal-resistant, which attributed to its complex species composition as shown by a slightly higher α-diversity index, and was slightly higher (p > 0.05) in the polluted samples. Among the five denitrifying genes tested, nosZ gene had the highest increase and the nirK gene the most decrease in numbers and in the polluted soils. The metal-polluted soils had fewer correlations among N functional genes based on the co-occurrence network analysis. In addition, the core taxa of the whole bacterial community changed from copiotrophic to oligotrophic bacteria in the presence of heavy metals. Mantel test indicated that heavy metals were the dominant factors determining N-related genes while the bacterial community composition was due to a combination of heavy metal presence and soil properties such as TOC, NO2-, and pH. It is concluded that long-term heavy metals pollution potentially affected nitrifiers and denitrifiers differently as indicated by the shift in N functional genes and the change in nitrification/denitrification processes.

Irrigated cotton (Gossypium hirsutum L.) is produced mainly in Northwest China, where groundwater is heavily used. To alleviate water scarcity and increase regional economic benefits, a four-year (2016–2019) field experiment was conducted in Qira Oasis, Xingjiang Province, to evaluate irrigation water use efficiency (IWUE) in cotton production using the Root Zone Water Quality Model (RZWQM2), that was calibrated and validated using volumetric soil water content (θ), soil temperature (Tsoil°) and plant transpiration (T), along with cotton growth and yield data collected from full and deficit irrigation experimental plots managed with a newly developed Decision Support System for Irrigation Scheduling (DSSIS). In the validation phase, RZWQM2 adequately simulated (S) topsoil θ and Tsoil°, as well as cotton growth (average index of agreement (IOA) > 0.76). Relative root mean squared error (RRMSE) and percent bias (PBIAS) of cotton seed yield were 8% and 2.5%, respectively, during calibration, and 20% and −10.3% during validation. The cotton crop’s (M) T was well S (−18% < PBIAS < 14% and IOA > 0.95) for both full and deficit irrigation fields. The validated RZWQM2 model was subsequently run with seven irrigation scenarios with 850 to 350 mm water (Irr850, Irr750, Irr700, Irr650, Irr550, Irr450, and Irr350) and long-term (1990–2019) weather data to determine the best IWUE. Simulation results showed that the Irr650 treatment generated the greatest cotton seed yield (4.09 Mg ha−1) and net income (US $3165 ha−1), while the Irr550 treatment achieved the greatest IWUE (6.53 kg ha−1 mm−1) and net water production (0.94 $ m−3). These results provided farmers guidelines to adopt deficit irrigation strategies.

Sunflower (Helianthus annuus L.) has been used as an alternative summer crop in the traditional wheat (Triticum aestivum L.)-fallow rotation in the Great Plains of the USA. However, few studies have been conducted to quantify sunflower productivity and water productivity (WP) under semi-arid conditions and projected climate change. Experiments were conducted in 2008, 2010, and 2011 on sunflowers under deficit irrigation to meet a fraction of crop evapotranspiration (ETc) as estimated by FAO-56 in eastern Colorado. The field data was used to calibrate and validate the CSM-CROPGRO-Sunflower model that is incorporated in the Root Zone Water Qualify Model (RZWQM2). The calibrated model was then used to simulate sunflower production under projected climate conditions with four Representative Concentration Pathways (RCP) scenarios (2.6, 4.5, 6.0, and 8.5) and four irrigation levels (100%, 60%, 40% ETc and rainfed) in the late 21st century. The results showed that the model was able to adequately simulate sunflower biomass, yield, and soil water storage under the different irrigation treatments in all three years. The corresponding relative root mean square deviation (RRMSD) values were between 0.05 and 0.15 for the simulations of soil water storage, yield, and biomass. Under future climate change conditions, the model simulated greater impact of irrigation treatments than RCP scenarios on sunflower production. For example, yield was 3251.3, 2638.85 and 1937.17 kg ha(-1) with 100%, 60% and 40% ETc irrigation under baseline (1992-2013) and was 2932.47, 2360.53 and 1810.65 kg ha(-1) with these irrigation treatments under RCP8.5 (2070-2091). Simulation results also showed that scheduling irrigations based on 60% of ETc was the best choice for sunflower WP in eastern Colorado. Climate change did not affect sunflower biomass, yield, and WP. There was an increasing trend of irrigation amount was simulated from the baseline to RCP8.5 scenario to maintain a certain percent of ETc due to high temperature projected. For instance, the irrigation amount for 100%, 60% and 40% of ETc irrigation treatment was 16.4%, 17.3%, and 20.0% higher under RCP8.5 than those under baseline conditions with CO2 fertilization. Finally, our results demonstrated that RZWQM2 can be used to effectively schedule sunflower irrigations based on crop evapotranspiration requirement.

Ecological multi-pond constructed wetlands (CWs) are an alternative wastewater treatment technology for nitrogen removal from non-point source pollution. As an important component of nitrogen cycles in the field-scale CWs, microorganisms are affected by design parameters. Nevertheless, the mechanism of design parameters affecting the distribution of microbial community and removal performance remains largely unexplored. In this study, satisfactory nitrogen removal performance was obtained in three multi-pond CWs. The highest mass removal rate per square meter (1104.0 mg/m2/day) and mass removal rate per cubic meter (590.2 mg/m3/day) for total nitrogen removal were obtained in the XY CW system during the wet season. The changes in seasonal parameters accounted for different removal performances and distributions of the microbial community. The combination of wastewater treatment technologies in the XY CW system consisting of ponds, CWs, and eco-floating treatment wetlands enriched the abundances of nitrogen-related functional genera. Correlation network analysis further demonstrated that longer hydraulic residence time and higher nitrogen concentration could intensify the enrichment of nitrogen-related functional genera. Regulating the combination of wastewater treatment technologies, the nitrogen concentration of influent, hydraulic loading rate, and water depth might promote the accumulation of microbial communities and enhance nitrogen removal. Macroscopical spatial/temporal regulation were proposed to enhance the treatment of non-point source pollution. The clarification of driving mechanism on design parameters, microbial community, and removal performance provided a novel perspective on the long-term maintenance of purification performance, practically sustainable applications, and scientific management of field-scale multi-pond CWs.

Due to their health effects and the recalcitrant nature of their CF bonds, Poly- and Perfluoroalkyl Substances (PFAS) are widely investigated for their distribution, remediation, and toxicology in ecosystems. However, very few studies have focused on modeling PFAS in the soil-water environment. In this review, we summarized the recent development in PFAS modeling for various chemical, physical, and biological processes, including sorption, volatilization, degradation, bioaccumulation, and transport. PFAS sorption is kinetic in nature with sorption equilibrium commonly quantified by either a linear, the Freundlich, or the Langmuir isotherms. Volatilization of PFAS depends on carbon chain length and ionization status and has been simulated by a two-layer diffusion process across the air water interface. First-order kinetics is commonly used for physical, chemical, and biological degradation processes. Uptake by plants and other biota can be passive and/or active. As surfactants, PFAS have a tendency to be sorbed or concentrated on air-water or non-aqueous phase liquid (NAPL)-water interfaces, where the same three isotherms for soil sorption are adopted. PFAS transport in the soil-water environment is simulated by solving the convection-dispersion equation (CDE) that is coupled to PFAS sorption, phase transfer, as well as physical, chemical, and biological transformations. As the physicochemical properties and concentration vary greatly among the potentially thousands of PFAS species in the environment, systematic efforts are needed to identify models and model parameters to simulate their fate, transport, and response to remediation techniques. Since many process formulations are empirical in nature, mechanistic approaches are needed to further the understanding of PFAS-soil-water-plant interactions so that the model parameters are less site dependent and more predictive in simulating PFAS remediation efficiency.

The black-odor phenomenon in polluted urban rivers is a serious environmental problem that has received increasing attention in the recent years. The low redox potential (less than − 100 mV) in the sediment is considered to be the key factor causing the occurrence of black-odor phenomenon. Here, we studied the structure and function of the microbial community during the remediation of urban rivers. Results showed a clear improvement in water quality after undergoing river remediation processes. The on-site treatments showed a succession in the microbial composition and their predicted functions. The primary iron- and sulfur-reducing bacteria (Thiobacillus, Sulfuricurvum, and Sulfursoma) and the related reactions rapidly decreased after the dredging treatment but reappeared after a year. The structure and abundance of nitrogen and methane participants were also affected by river remediation process. These results indicated that although the water quality temporarily improved shortly after a dredging process, a recurrence of the black-odor phenomenon may occur as a result of the rebound in the microbial communities.

Hydrogen peroxide (H 2 O 2 ) is a major reactive oxygen species in unicellular and multicellular organisms, and is produced extracellularly in response to external stresses and internal cues 1 – 4 . H 2 O 2 enters cells through aquaporin membrane proteins and covalently modifies cytoplasmic proteins to regulate signalling and cellular processes. However, whether sensors for H 2 O 2 also exist on the cell surface remains unknown. In plant cells, H 2 O 2 triggers an influx of Ca 2+ ions, which is thought to be involved in H 2 O 2 sensing and signalling. Here, by using forward genetic screens based on Ca 2+ imaging, we isolated hydrogen-peroxide-induced Ca 2+ increases ( hpca ) mutants in Arabidopsis , and identified HPCA1 as a leucine-rich-repeat receptor kinase belonging to a previously uncharacterized subfamily that features two extra pairs of cysteine residues in the extracellular domain. HPCA1 is localized to the plasma membrane and is activated by H 2 O 2 via covalent modification of extracellular cysteine residues, which leads to autophosphorylation of HPCA1. HPCA1 mediates H 2 O 2 -induced activation of Ca 2+ channels in guard cells and is required for stomatal closure. Our findings help to identify how the perception of extracellular H 2 O 2 is integrated with responses to various external stresses and internal cues in plants, and have implications for the design of crops with enhanced fitness.

To help reduce future N loads entering the Gulf of Mexico from the Mississippi River 45%, Iowa set the goal of reducing non-point source N loads 41%. Studies show that implementing winter rye cover crops into agricultural systems reduces N loads from subsurface drainage, but its effectiveness in the Mississippi River Basin under expected climate change is uncertain. We used the field-tested Root Zone Water Quality Model (RZWQM) to estimate drainage N loads, crop yield, and rye growth in central Iowa corn-soybean rotations. RZWQM scenarios included baseline (BL) observed weather (1991–2011) and ambient CO2 with cover crop and no cover crop treatments (BL_CC and BL_NCC). Scenarios also included projected future temperature and precipitation change (2065–2085) from six general circulation models (GCMs) and elevated CO2 with cover crop and no cover crop treatments (CC and NCC). Average annual drainage N loads under NCC, BL_NCC, CC and BL_CC were 63.6, 47.5, 17.0, and 18.9 kg N ha−1. Winter rye cover crop was more effective at reducing drainage N losses under climate change than under baseline conditions (73 and 60% for future and baseline climate), mostly because the projected temperatures and atmospheric CO2 resulted in greater rye growth and crop N uptake. Annual CC drainage N loads were reduced compared with BL_NCC more than the targeted 41% for 18 to 20 years of the 21-year simulation, depending on the GCM. Under projected climate change, average annual simulated crop yield differences between scenarios with and without winter rye were approximately 0.1 Mg ha−1. These results suggest that implementing winter rye cover crop in a corn-soybean rotation effectively addresses the goal of drainage N load reduction under climate change in a northern Mississippi River Basin agricultural system without affecting cash crop production.

Optimizing irrigation scheduling through a Decision Support System has shown promise to improve crop yield and water productivity in irrigated agriculture in an arid climate. The effects of an irrigation scheduling method on cotton (Gossypium hirsutum L.) yield and water productivity were investigated in Qira Oasis, China from 2016-2018. The Decision Support System for Irrigation Scheduling (DSSIS) was based on forecasted rainfall and water stress index simulated by the Root Zone Water Quality Model (RZWQM2). A field experiment was conducted to test the viability of the DSSIS in 2016. The design of the experiment was a randomized complete that included two factors and two levels for each factor: (i) irrigation scheduling method-DSSIS-based (DSS) and soil moisture sensor-based (SMS), and (ii) irrigation level-full irrigation (FI) and deficit irrigation (DI, 75 % of FI). Implementation of the DSS led to significant increases in seed cotton yield [1.05 Mg ha(-1) (32 %)] and water productivity [1.64 kg ha(-1) mm(-1) (20 %)] compared to the SMS. Compared to DI, FI significantly increased cotton yield [0.69 Mg ha(-1) (20 %)] but had no significant effect on water productivity. In general, the higher water productivity under DSS (vs. SMS) was attributed to the reduced water stress and increased seed cotton yield. While the DSS-FI treatment provided the greatest seed cotton yield (4.55 Mg ha(-1)) and net income (US $3427 ha(-1)), the highest water productivity (10.09 kg ha(-1) mm(-1)) was achieved under the DSS-DI treatment. Water use under DSS-DI treatment significantly decreased by 51 mm (10 %) and 23 mm (5 %), respectively, compared to DSS-FI and SMS-FI treatments. Therefore, our results demonstrated that the DSS with deficit irrigation could maintain cotton yield and improve water productivity under an arid desert climate.

Photodegradation of perfluorooctane sulfonate (PFOS) by UV irradiation could remove this environmentally persistent chemical from aqueous solution, but its efficiency needs to be further optimized. This study introduced foam fractionation technique, which utilizing the surface activity of PFOS, to promote the removal efficiency of PFOS during photodegradation. Under the favorable conditions of foam fractionation (pH = 11.0; the height to diameter ratio of the reaction solution = 3:1; gas flow rate = 1.0 L/min) in a cylindrical glass reactor, PFOS photodegradation rate (20 mg/L initial concentration) was 8.76 times higher than that without foam fractionation, over a 3-hour reaction. While under neutral condition, PFOS photodegradation rate also experienced an increase of 7.43, 6.20 and 2.66 times compared to that without foam fractionation for initial concentrations of 20 mg/L, 5 mg/L and 1 mg/L, respectively. This combination of foam fractionation and photodegradation process will hopefully be used for treatment of PFOS and other per- and polyfluoroalkyl substances with surface activity and photodegradability.