nitrate-N Concentrations Research Articles

Discovering the role of fairy ring fungi in accelerating nitrogen cycling to promote plant productivity in grasslands

Soil microorganisms play a key role in the provision of plant-bioavailable nutrients, which is crucial for ecosystem functioning and plant productivity. Fairy rings are widespread features in grasslands accompanied by lush dark-green vegetation bands. This enigmatic feature is caused by increased soil bioavailable nitrogen (N) due to the expansion of fairy ring fungi (FRF). However, little is known about how FRF enhance soil bioavailable N concentrations. Here, we conducted a survey of 35 fairy rings in temperate grasslands to reveal the role of FRF in regulating soil microorganisms and N cycling using amplicon and metagenomic sequencing. The presence of FRF accelerated organic N mineralization via promoting extracellular enzyme (β-1,4-N-acetylglucosaminidase) activity, leading to a 455% increase in ammonium-N. This further stimulated nitrification to enhance nitrate-N concentration by favoring ammonia-oxidizing archaea. Concomitantly, the increased nitrate-N did not promote denitrification or affect the potential risk of N loss. Furthermore, the relative abundance of other saprotrophic and symbiotrophic fungi was significantly reduced by FRF but the changes in these fungi did not affect the activity of extracellular enzymes involved in N mineralization. Our results suggest that FRF can act as ecosystem engineer species shaping fairy rings by driving soil N cycling without the involvement of other microbial functional groups of saprotroph and symbiotroph to boost plant productivity. Thus, due to the stronger N mobilizing ability, FRF show great potential to be exploited as beneficial microorganisms in plant production and sustainable agricultural development.

Water deficit affects the nitrogen nutrition index of winter wheat under controlled water conditions

Nitrogen (N) uptake is regulated by water availability, and a water deficit can limit crop N responses by reducing N uptake and utilization. The complex and multifaceted interplay between water availability and the crop N response makes it difficult to predict and quantify the effect of water deficit on crop N status. The nitrogen nutrition index (NNI) has been widely used to accurately diagnose crop N status and to evaluate the effectiveness of N application. The decline of NNI under water-limiting conditions has been documented, although the underlying mechanism governing this decline is not fully understood. This study aimed to elucidate the reason for the decline of NNI under water-limiting conditions and to provide insights into the accurate utilization of NNI for assessing crop N status under different water-N interaction treatments. Rainout shelter experiments were conducted over three growing seasons from 2018 to 2021 under different N (75 and 225 kg N ha-1, low N and high N) and water (120 to 510 mm, W0 to W3) co-limitation treatments. Plant N accumulation, shoot biomass (SB), plant N concentration (%N), soil nitrate-N content, actual evapotranspiration (ETa), and yield were recorded at the stem elongation, booting, anthesis and grain filling stages. Compared to W0, the W1 to W3 treatments exhibited NNI values that were greater by 10.2 to 20.5%, 12.6 to 24.8%, 14 to 24.8%, and 16.8 to 24.8% at stem elongation, booting, anthesis, and grain filling, respectively, across the 2018-2021 seasons. This decline in NNI under water-limiting conditions stemmed from two main factors. First, reduced ETa and SB led to a greater critical N concentration (%Nc) under water-limiting conditions, which contributed to the decline in NNI primarily under high N conditions. Second, changes in plant %N played a more significant role under low N conditions. Plant N accumulation exhibited a positive allometric relationship with SB and a negative relationship with soil nitrate-N content under water-limiting conditions, indicating co-regulation by SB and the soil nitrate-N content. However, this regulation was influenced by water availability. Plant N accumulation sourced from the soil nitrate-N content reflects soil N availability. Greater soil water availability facilitated greater absorption of soil nitrate-N into the plants, leading to a positive correlation between plant N accumulation and ETa across the different water-N interaction treatments. Therefore, considering the impact of soil water availability is crucial when assessing soil N availability under water-limiting conditions. The findings of this study provide valuable insights into the factors contributing to the decline in NNI among different water-N interaction treatments and can contribute to the more accurate utilization of NNI for assessing winter wheat N status.

Effects of pellet inorganic nitrogen on nitrous oxide emissions from cattle manure compost pellets

ABSTRACT Manure compost pellets (MCPs) emit more nitrous oxide (N2O) when applied to soils than loose manure compost or inorganic fertilizer, but pellets of N-enriched manure compost (N+MCP), a by-product of deodorizing manure during composting, emit less N2O than MCPs. To investigate why N+MCPs emit less N2O than MCPs, I studied the effect of inorganic N content, which differs clearly between MCP (2 mg NO3 − g−1, 0.2 mg NH4 + g−1) and N+MCP (17 mg NO3 − g−1, 4 mg NH4 + g−1). MCPs made from cattle manure composts were incubated with various concentrations of nitrate-N (2, 3.5, 5, 10, 20 mg g−1) as KNO3 and ammonium-N (0, 2, 4 mg g−1) as (NH4)2SO4. N2O emissions and related chemical properties were measured during incubation for 14 days. N2O emission peaked at 1 day, and the peak height was significantly lower when nitrate (MCP-NO3_20) and nitrate plus ammonium (MCP-NO3+NH4) contents were raised to the same levels as in N+MCP than in MCP (no added N). Nitrite contents in pellets at 1 day were also lower in both treatments than in MCP. Total N2O emissions during incubation were significantly lower from MCP-NO3+NH4 than from MCP. Emission factors of MCP-NO3_20 and MCP-NO3+NH4 were significantly lower than that of MCP. Pellet nitrate content was negatively correlated with total N2O emission during incubation (p < 0.05). These results suggest that the inorganic N content is important in suppressing N2O emissions from N+MCP.

Sulfate-reducing consortium HQ23 stabilizes metal(loid)s and activates biological N-fixation in mixed heavy metal-contaminated soil

Sulfate-reducing bacteria (SRB) are used in the remediation of mine pollution; however, the mechanism of stabilizing multiple heavy metal(loid)s by the SRB consortium under low oxygen conditions needs further study. Indigenous microflora were extracted from non-ferrous metal-contaminated soil co-inoculated with enriched SRB consortium and assembled as the HQ23 consortium. The presence of Desulfovibrio (SRB) in HQ23 was confirmed by 16S rRNA sequencing and qPCR. The effects of culture media, dissolved oxygen (DO), SO42¯, and pH on the HQ23 growth rate, and the SO42¯-reducing activity were examined. Data indicates that the HQ23 sustained SRB function under low DO conditions (3.67 ± 0.1 mg/L), but the SRB activity was inhibited at high DO content (5.75 ± 0.39 mg/L). The HQ23 can grow from pH 5 to pH 9 and can decrease mobile or bioavailable Cr, Cu, and Zn concentrations in contaminated soil samples. FTIR revealed that Cu and Cr adsorbed to similar binding sites on bacteria, likely decreasing bacterial Cu toxicity. Increased abundances of DSV (marker for Desulfovibrio) and nifH (N-fixation) genes were observed, as well as an accumulation of nitrate-N content in soils suggesting that HQ23 stimulates the biological N-fixation in soils. This study strongly supports the future application of SRB for the bioremediation of heavy metal-polluted sites.

A regional examination of the footprint of agriculture and urban cover on stream water quality

Freshwater systems in cold regions, including the Laurentian Great Lakes, are threatened by both eutrophication and salinization, due to excess nitrogen (N), phosphorus (P) and chloride (Cl−) delivered in agricultural and urban runoff. However, identifying the relative contribution of urban vs. agricultural development to water quality impairment is challenging in watersheds with mixed land cover, which typify most developed regions. In this study, a self-organizing map (SOM) analysis was used to evaluate the contributions of various forms of land cover to water quality impairment in southern Ontario, a population-dense, yet highly agricultural region in the Laurentian Great Lakes basin where urban expansion and agricultural intensification have been associated with continued water quality impairment. Watersheds were classified into eight spatial clusters, representing four categories of agriculture, one urban, one natural, and two mixed land use clusters. All four agricultural clusters had high nitrate-N concentrations, but levels were especially high in watersheds with extensive corn and soybean cultivation, where exceedances of the 3 mg L−1 water quality objective dramatically increased above a threshold of ‍∼30 % watershed row crop cover. Maximum P concentrations also occurred in the most heavily tile-drained cash crop watersheds, but associations between P and land use were not as clear as for N. The most urbanized watersheds had the highest Cl− concentrations and expansions in urban area were mostly at the expense of surrounding agricultural land cover, which may drive intensification of remaining agricultural lands. Expansions in tile-drained corn and soybean area, often at the expense of mixed, lower intensity agriculture are not unique to this area and suggest that river nitrate-N levels will continue to increase in the future. The SOM approach provides a powerful means of simplifying heterogeneous land cover characteristics that can be associated with water quality patterns and identify problem areas to target management.

Implementation Of Water Quality Index For Measuring Groundwater Quality

Groundwater is one of the major sources of water consumption in developing countries. The aim of the study was to investigate the variations in physicochemical characteristics and metal content and to calculate the Water Quality Index (WQI) to assess the groundwater quality of seven districts (Central, East, West, South, Malir, Korangi, and Kemari) of Karachi City, Pakistan. A stratified sampling approach was used to collect groundwater samples and turbidity, pH, Electrical Conductivity (EC), Total Dissolved Solids (TDS), Total Suspended Solids (TSS), Nitrate-N, and arsenic concentrations were investigated to profile WQI. The physicochemical parameters from districts South, West, Korangi, and Kemari were as per APHA standards and found suitable for drinking purposes. EC and TDS were in ranges of (2660-3870μS/cm) and (1596-2322mg/L) exceeding the standard limits resulting in poor drinking water quality respectively in districts Central, Malir, and East. These districts fail to meet the APHA standards and become unfit for human consumption on the WQI scale. However, TSS and arsenic was not detected in any of the collected samples. The correlation matrix for the[1] correlation coefficient (R-value) of tested parameters with WQI indicated significant linear and high R-value among tested parameters. The statistical analysis showed that turbidity, pH, EC, TDS, and Nitrate-N have significant effects on WQI. EC and TDS showed a direct correlation with WQI (R=1.0) whereas turbidity significantly correlates with the presence of nitrate in drinking water (R=0.64). These findings help the decision makers to plan mitigation strategies for comprehensive water quality monitoring of the respective areas and ensure the availability of clean and safe drinking water to the public.

Screening protocol for freshwater filamentous macroalgae bioremediation of primary municipal wastewater

A screening protocol was developed and applied to isolate and select cultivars of freshwater filamentous macroalgae for year-round monoculture cultivation and nutrient bioremediation of primary municipal wastewater. The screening protocol is a step-by-step guide to identify robust cultivars which possess key attributes of competitive dominance, high biomass productivity and bioremediation performance under local seasonal and extreme conditions. Forty-four mixed samples of freshwater filamentous macroalgae were collected during summer and winter from a range of local aquatic environments. Eleven isolated cultivars were grown in primary treated municipal wastewater and their biomass productivity and bioremediation performance under local ambient (summer and winter), extreme summer (max. summer) and winter (min. winter) conditions were assessed. Extreme conditions proved to be an important determining factor for cultivar selection as biomass productivity and bioremediation performance significantly declined under min. winter conditions. However, biomass productivity was not directly related to bioremediation performance, as cultivars with low growth rates maintained high nutrient removal rates under min. winter conditions. Top performing cultivars were Klebsormidium sp. (KLEB B) which reduced total ammoniacal-N concentrations by 99.9% to 0.01 mg L-1 (± 0.01 SE), Oedogonium sp. (OEDO D) which reduced nitrate-N concentrations by 90.2% to 0.08 mg L-1 (± 0.7 SE) and Rhizoclonium sp. which reduced phosphate concentrations by 98.7% to 0.02 mg L-1 (± 0.01 SE). Based on overall biomass productivity and bioremediation performance across seasonal and extreme conditions Klebsormidium sp. (KLEB B), Stigeoclonium sp. (STIG A) and Ulothrix sp. were identified as top performing cultivars suitable for the nutrient bioremediation of primary municipal wastewater.

Toxicity threshold and ecological risk of nitrate in rivers based on endocrine-disrupting effects: A case study in the Luan River basin, China

Nitrate, as a crucial nutrient, is consistently targeted for controlling water eutrophication globally. However, there is considerable evidence suggesting that nitrate has endocrine-disrupting potential on aquatic organisms. In this study, the sensitivity of various adverse effects to nitrate nitrogen (nitrate-N) was compared, and a toxicity threshold based on endocrine-disrupting effects was derived. The spatiotemporal variations of nitrate-N concentrations in the Luan River basin were investigated, and the associated aquatic ecological risks were evaluated using a comprehensive approach. The results showed that reproduction and development were the most sensitive endpoints to nitrate, and their distribution exhibited significant differences compared to behavior. The derived threshold based on endocrine-disrupting effects was 0.65 mgL−1, providing adequate protection for the aquatic ecosystem. In the Luan River basin, the mean nitrate-N concentrations during winter (4.4 mgL−1) were significantly higher than those observed in spring (0.7 mgL−1) and summer (1.2 mgL−1). Tributary inputs had an important influence on the spatial characteristics of nitrate-N in the mainstream, primarily due to agricultural and population-related contamination. The risk quotients (RQ) during winter, summer, and spring were evaluated as 6.7, 1.8, and 1.1, respectively, and the frequency of exposure concentrations exceeding the threshold was 100 %, 64.3 %, and 42.5 %, respectively. At the ecosystem level, nitrate posed intermediate risks to aquatic organisms during winter and summer in the Luan River basin and at the national scale in China. We suggest that nitrate pollution control should not solely focus on water eutrophication but also consider the endocrine disruptive effect on aquatic animals.

The effect of four tillage systems on agronomic properties and soil health indicators in southern Manitoba

Soil health encompasses the collective functioning of chemical, physical, and biological properties in soil. The extent to which soil management affects soil health and the links with agronomic outcomes remain unclear. This project aimed to understand the interrelations of tillage systems, soil health, and agronomic properties in Portage la Prairie, MB, Canada. Tillage systems were cultivation, deep tillage, raised beds, and vertical tillage. Soybean ( Glycine max (L.) Merr), corn ( Zea mays L.), and canola ( Brassica napus L.) were all grown in 2020, 2021, and 2022. Crop yield, seed protein content, and seed oil content were measured each year. Soil samples were taken in spring 2021, fall 2021, and fall 2022 and analyzed for nitrate-N, ammonium-N, total N, ACE protein, water extractable organic N, water extractable total N, water extractable ammonium N, soil organic matter, soil organic carbon, calcium carbonate equivalent, CO2 burst, permanganate oxidizable carbon, water extractable organic C, pH, salts, Olsen P, K, S, sand, silt, and clay. Tillage system had a significant impact on agronomic properties in seven crop by sampling combinations. Tillage system effected soil nitrate-N concentration at five crop by sampling combinations, three more than any other soil property. Soybean agronomic properties correlated with soil health indicators more frequently than for corn and canola. This suggests that the utility of soil health indicators may be crop specific. Further research is needed to understand the mechanisms underpinning the ability of soil health indicators to predict agronomic outcomes and to benchmark soil health indicator values with time.

Pulp mill sludges as a solution for reducing the risk of mineral nitrogen leaching from agriculture

Nitrogen (N) from agricultural systems contributes to the eutrophication of waterbodies through leaching. Incorporating organic material with a high carbon-to-nitrogen (C/N) ratio, such as mixed pulp mill sludges (PMSs), into the soil in autumn could reduce the amount of leachable N. This study tested the potential of composted and lime-stabilised mixed PMSs (CPMS and LPMS) in reducing the concentration of mineral N in the soil, and thus the risk of N leaching from arable land in the boreal region using a two-year field experiment. To better understand the mechanisms of the PMSs for influencing mineral N concentration in soil, the impact of PMSs with different quality on the reactions of N in the soil was investigated in a laboratory incubation study. In the field experiment, nitrate-N (NO3--N) concentration was lower with PMSs compared to mineral fertilisation and the control during the first autumn and the following spring after PMS application. The undersowing of Italian ryegrass reduced the NO3--N concentration in the soil during the first autumn. In the incubation experiment, PMSs reduced the soil ammonium-N (NH4+-N) concentration at the beginning of the experiment and the soil NO3--N concentration throughout the experiment compared to a mineral fertiliser treatment and an organic fertiliser. Increased soil respiration in PMS-treated soils indicated increase in microbial activity, and thus immobilisation of soil NO3--N and NH4+-N due to PMSs addition. These results suggest that PMSs have the potential to reduce N leaching from agricultural soils. However, the immobilisation of N must be considered when planning the nutrient requirements of the following crops.

Comparison of manure application methods on nutrient and metal loss to snowmelt

Manure injection is well documented to reduce rain-driven nutrient losses, but the effect on snowmelt-driven losses is less studied. This study examined the surface application versus injection of liquid swine manure on phosphorus (P), nitrate‑nitrogen (nitrate-N), zinc (Zn), manganese (Mn), iron (Fe), magnesium (Mg), and calcium (Ca) release from soils to snowmelt. Manure was applied in the fall of 2021 to four replicated plots of surface-applied or injected treatments, and boxes were installed to collect snowmelt in each plot, including four unmanured (control) plots. In the spring of 2022, the snowmelt was collected from each box for 10 days, volume was recorded, and analyzed for dissolved reactive P (DRP), nitrate-N, Zn, Mn, Fe, Mg, and Ca concentrations, and pH. The mean daily snowmelt volume and snowmelt depth ranged from 2.9 to 25.2 L, and 2.7 to 23.3 mm, respectively. The mean snowmelt DRP concentrations for manure injected, surface-applied, and control treatments were 0.66 ± 0.07, 0.89 ± 0.07, and 0.65 ± 0.07 mg L−1, respectively. The mean DRP concentration did not vary among the manure application methods for the first 5 days of snowmelt. However, DRP was significantly higher in the manure surface-applied treatment, compared to both control and manure-injected treatments on days 7 and 8, compared to the control on day 6, and compared to the manure-injected on day 9. The effect of the manure application method on nitrate-N (3.27 to 3.60 mg L−1) and metal concentrations in the snowmelt was not significant. The cumulative loads (mean across application methods and sampling days in kg ha−1) of DRP (0.56), nitrate-N (4.03), and metals [Zn (0.11), Mn (0.01), Fe (0.18), Mg (8.03), Ca (21.70)] mobilized with snowmelt flooding did not significantly vary among the manure application methods. Results suggest that DRP, nitrate, and metal loads were primarily controlled by the snowmelt volume rather than their concentrations. Therefore, land management practices that reduce the volume of snowmelt discharge could be more effective for reducing the P, nitrate-N, and metal loss to snowmelt from manured soils.

Wastewater Nutrient Recovery via Fungal and Nitrifying Bacteria Treatment

In efforts to reduce the consumption of fossil fuels and promote recycling biowaste, there is an interest in the production of post-hydrothermal liquefaction wastewater (HTL-AP) from the hydrothermal liquefaction (HTL) process that converts wet biomass into biocrude oil. This study explores ways of transforming potentially toxic HTL-AP into a fertilizer source for hydroponic cropping systems. This study specifically investigates the integration of the white-rot fungus Trametes versicolor with nitrifying bacteria (Nitrosomonas and Nitrobacter) to convert the organic nitrogen compounds into inorganic nitrogen while also producing the enzyme laccase, which has been shown to remove toxic compounds. This study aims to increase the concentration of nitrate-N to valorize wastewater as a suitable fertilizer by measuring several parameters, including laccase activity, pH, nitrate-N, and ammonia/ammonium-N concentrations, and analyzes interactions to optimize the conversion process. The data support the claim that the simultaneous inoculation of T. versicolor and nitrifying bacteria significantly increases nitrate-N concentrations in HTL-AP, as it increased by 17 times, or an increase of 32.69 mg/L. In addition, HTL-AP treated with T. versicolor and nitrifying bacteria reduced the treatment time by 120 h, highlighting a reduction in personnel time and energy consumption. Therefore, this research accentuates sustainability through fungal and bacterial treatments to develop eco-friendly hydroponic fertilizers. Future research should explore the potential of utilizing the combination of T. versicolor and nitrifying bacteria for the treatment of other industrial wastewaters.

Integrated approach to understand the multiple natural and anthropogenic stresses on intensively irrigated coastal aquifer in the Mediterranean region

Understanding the major factors influencing groundwater chemistry and its evolution in irrigation areas is crucial for efficient irrigation management. Major ions and isotopes (δD-H2O together with δ18O–H2O) were used to identify the natural and anthropogenic factors contributing to groundwater salinization in the shallow aquifer of the Wadi Guenniche Plain (WGP) in the Mediterranean region of Tunisia. A comprehensive geochemical investigation of groundwater was conducted during both the low irrigation season (L-IR) and the high irrigation season (H-IR). The results show that the variation range and average concentrations of almost all the ions in both the L-IR and H-IR seasons are high. The groundwater in both seasons is characterized by high electrical conductivity and CaMgCl/SO4 and NaCl types. The dissolution of halite and gypsum, the precipitation of calcite and dolomite, and Na–Ca exchange are the main chemical reactions in the geochemical evolution of groundwater in the Wadi Guenniche Shallow Aquifer (WGSA). Stable isotopes of hydrogen and oxygen (δ18O–H2O and δD-H2O) indicate that groundwater in WGSA originated from local precipitation. In the H-IR season, the δ18O–H2O and δD-H2O values indicate that the groundwater experienced noticeable evaporation. The enriched isotopic signatures reveal that the WGSA's groundwater was influenced by irrigation return flow and seawater intrusion. The proportions of mixing with seawater were found to vary between 0.12% and 5.95%, and between 0.13% and 8.42% during the L-IR and H-IR seasons, respectively. Irrigation return flow and the associated evaporation increase the dissolved solids content in groundwater during the irrigation season. The long-term human activities (fertilization, irrigation, and septic waste infiltration) are the main drives of the high nitrate-N concentrations in groundwater. In coastal irrigation areas suffering from water scarcity, these results can help planners and policy makers understand the complexities of groundwater salinization to enable more sustainable management and development.

Extreme Learning Machine Predicts High-Frequency Stream flow and Nitrate-N Concentrations in a Karst Agricultural Watershed

Highlights A novel high-frequency dataset of streamflow, nitrate-N concentration, and soil moisture at depths throughout and below the root zone highlighted tight connectivity between soil moisture dynamics and nitrate-N concentrations spanning event to seasonal timescales. A TELM model successfully predicted both flow rate and nitrate exports from these complex systems because the time lag associated with the soil conditions was represented in model training. The inclusion of soil moisture and temperature data below the effective root zone was important to accurately capture the storm event hysteresis dynamics observed in the exported nitrate signals. Abstract. Efforts to reduce nitrogen contributions from karst agroecosystems have had variable success, in part due to an incomplete understanding of nitrogen source, fate, and transport dynamics in karst watersheds. Recent advancements in environmental sensors and data-driven artificial intelligence models may be useful in improving our understanding of system behavior and the linkages between soil hydrologic processes and karst nitrate loading dynamics. We collected 35 months of high-resolution streamflow, nitrate-N concentration, soil moisture and temperature (from 10-100 cm depths), and meteorological data in a karst agricultural watershed in the Inner-Bluegrass region of Central Kentucky. Two-layer extreme learning machine (TELM) models were developed to predict nitrate-N concentrations and flow rates as a function of meteorological and soil parameter inputs. Results suggest tight linkages between soil moisture gradients at different depths and nitrate-N concentrations at the watershed outlet. TELM modeling results supported visual observations from the high-frequency data and suggest that inclusion of both soil moisture and temperature parameters at all soil depths improved predictions of both flow rate and nitrate-N concentration (with optimal NSE values of 0.93 and 0.94, respectively, when all inputs were considered). Hysteresis analysis suggested that inclusion of the deepest soil layer (100 cm) was necessary to predict hysteresis observed during storm events. The findings of the study highlight the importance of variable activation of matrix waters in preferential flows throughout events and seasons and its subsequent impacts on nitrate-N concentrations. Results suggest that management models should incorporate vertical variability in soil hydrology to accurately characterize nitrate source and transport dynamics. Further, the results of hysteresis analysis underscore the importance of inclusion of hysteresis indices, in addition to typical model evaluation statistics, to ensure accurate representation of nutrient flow pathways. Keywords: Extreme learning machine, Karst agroecosystem, Nitrate, Water resources.

Dynamics and microbial characteristics of nitrogen and carbon in saline-alkali paddy soil under different fertilization

The expansion of saline-alkali paddy fields, coupled with the application of large amounts of nitrogen (N) fertilizers, has given rise to a host of environmental concerns. While N and carbon (C) are vital indicators for assessing soil fertility, their dynamic characteristics in saline-alkali paddy soil remain obscure. To address this knowledge gap, we established paddy mesocosms with five distinct N-fertilizer treatments: control without N-fertilizer (CK), urea (U), urea with inhibitors (UI), organic–inorganic compound fertilizer (OCF) and C-based slow-release fertilizer (CSF). The objective was to monitor the dynamic changes of various N and soil organic-C (SOC) during a 137-day rice growing season, and to clarify the microbiological characteristics. By the end of the rice growing season, soil ammonia-N (NH4+-N) concentrations were UI > OCF > CSF > U > CK, and UI had a significant difference (p < 0.05) with all the other four treatments. Soil nitrate-N (NO3−-N) concentrations in OCF and CSF treatments were 5.64 ± 1.25 mg kg−1 and 6.81 ± 0.29 mg kg−1, respectively, significantly (p < 0.05) higher than U and UI treatments. NH4+-N showed a negative correlation with NO3−-N regardless of the N-fertilizer types, and a significant (p < 0.01) positive relationship with alkali-hydrolyzable N (AHN). A significant (p < 0.01) positive relationship existed between total-N (TN) and Bacteria 16S rRNA gene. The SOC had a significant (p < 0.05) positive relationship with mcrA gene. During the entire rice growing season, CSF treatment had lower mean TN and SOC concentrations than all the other treatments, and exhibited the highest TN and total organic-C (TOC) content in rice. In summary, the UI can increase the residual NH4+-N in saline-alkali paddy fields, and the CSF is a better choice for growing rice.

Assessment of aquifer specific vulnerability to total nitrate contamination using ensemble learning and geochemical evidence

Henan Province's plain area is the granary of China, yet its regional aquifer is being polluted by industrial wastewater, agricultural pesticide, fertilizer and domestic wastewater. In order to safeguard the security of food and drinking water, and in response to the problem of low prediction accuracy caused by the lack of samples and unevenly distributed groundwater monitoring data, we propose a new way to predict the aquifer vulnerability in large areas by rich small-scale data, so as to identify the pollution risks and to address the issue of sample shortage. In small regions with abundant nitrate data, we employed a Random Forest model to screen key impact indicators, using them as features and nitrate-N concentration as the target variable. Consequently, we established six machine learning prediction models, and then selected the best bagging model (R2 = 0.86) to predict the vulnerability of aquifers in larger regions lacking nitrate data. The predicted results showed that highly vulnerable areas accounted for 20 %, which were mainly affected by aquifer thickness (65.91 %). High nitrate-N concentration implies serious aquifer contamination. Therefore, a long series of groundwater nitrate-N concentration monitoring data in a large scale, the trend and slope of nitrate-N concentration showed a significant correlation with the model prediction results (Spearman's correlation coefficients are 0.75 and 0.58). This study can help identify the risk of aquifer contamination, solve the problem of sample shortage in large areas, thus contributing to the security of food and drinking water.

Developing managed aquifer recharge (MAR) to augment irrigation water resources in the sand and gravel (Crag) aquifer of coastal Suffolk, UK

Managed aquifer recharge (MAR) offers a potential innovative solution for addressing groundwater resource issues, enabling excess surface water to be stored underground for later abstraction. Given its favourable hydrogeological properties, the Pliocene sand and gravel (Crag) aquifer in Suffolk, UK, was selected for a demonstration MAR scheme, with the goal of supplying additional summer irrigation water. The recharge source was a 4.6 km drainage channel that discharges to the River Deben estuary. Trialling the scheme in June 2022, 12,262 m3 of source water were recharged to the aquifer over 12 days via a lagoon and an array of 565 m of buried slotted pipes. Groundwater levels were raised by 0.3 m at the centre of the recharge mound with an approximate radius of 250 m, with no detrimental impact on local water features observed. The source water quality remained stable during the trial with a mean chloride concentration (133 mg L−1) below the regulatory requirement (165 mg L−1). The fraction of recharge water mixing with the groundwater ranged from 69% close to the centre and 5% at the boundary of the recharge mound, leading to a reduction in nitrate-N concentration of 23.6 mg L−1 at the centre of the mound. During July–September 2022, 12,301 m3 of recharge water were abstracted from two, 18 m boreholes to supplement surface irrigation reservoirs during drought conditions. However, the hydraulic conductivity of the Crag aquifer (∼10 m day−1) restricted the yield and thereby reduced the economic viability of the scheme. Construction costs for the MAR system were comparatively low but the high costs of data collection and securing regulatory permits brought the overall capital costs to within 18% of an equivalent surface storage reservoir, demonstrating that market-based mechanisms and more streamlined regulatory processes are required to incentivise similar MAR schemes.

Small villages and their sanitary infrastructure—an unnoticed influence on water quantity and a threat to water quality in headwater catchments

In rural catchments, villages often feature their own, separate urban water infrastructure, including combined sewer overflows (CSOs) or wastewater treatment plants (WWTPs). These point sources affect the water quantity and quality of the receiving low order streams. However, the extent of this impact is rarely monitored. We installed discharge and water quality measurements at the outlet of two small, neighbouring headwater catchments, one that includes a village, a WWTP, and two CSOs, while the other is predominantly influenced by agricultural activities. We also deployed electrical conductivity (EC) loggers at the CSOs to accurately detect discharge times. Discharge from the WWTP and CSOs led to higher peak flows and runoff coefficients during events. Less dilution of EC and increasing ammonium-N (NH4 − N) and ortho-phosphorus (oPO4 − P) concentrations indicate a significant contribution of poorly treated wastewater from the WWTP. During CSO events, water volumes and nutrient loads were clearly elevated, although concentrations were diluted, except for nitrite-N (NO2 − N) and particulate phosphorus (PP). Baseflow nitrate-N (NO3 − N) concentrations were diluted by the WWTP effluent, which led to considerably lower concentrations compared to the more agriculturally influenced stream. Concentrations of oPO4 − P, NH4 − N, and NO2 − N, which are most likely to originate from the WWTP, vary throughout the year but are always elevated. Our study shows the major and variable impact rural settlements can have on stream hydrology and water quality. Point sources should be monitored more closely to better understand the interaction of natural catchment responses and effects caused by sanitary infrastructure.

Water and soil quality respond to no-tillage and cover crops differently through 10 years of implementation

Addressing the global problem of eutrophication will require better management of inorganic nitrogen (N) on the agricultural landscape. This study investigates the impacts of no-tillage (NT), no tillage with winter cereal rye (NTr), and conventional tillage with rye (CTr), and a perennial (P) in comparison to a control system of conventional tillage without a cover crop (CT). All plots are individually drained and, except for P, in a corn/soybean rotation which dominates much of the Midwestern U.S. Drainage quantity and nitrate-N concentration were measured from individually drained plots 2011–2020. Treatments P, CT, and CTr began in 2004 and we report on years 7–11 (phase 1) and years 12–16 (phase 2). Treatments NT and NTr began in 2010 and we report on years 2–6 (phase 1) and 7–11 (phase 2). CTr and P functioned similarly throughout with consistent reductions in NO3-N concentration in leachate and loading. In contrast to initial expectations, when comparing NT to CT, there were consistent reductions in NO3-N concentration in leachate and loading in phase 1, but not in phase 2. Similarly, NTr did not reduce NO3-N concentration compared to NT in phase 1, but it did in phase 2. These results both indicate that there were possible changes to soil properties in the NT and NTr systems that influenced N cycling that could be unique to high carbon artificially drained environments. Soil quality improvements were detected in these mollisols after 15 years of cover crops in the conventional system, and after 10 years of NT and NTr. In this study, CTr was more consistent at improving water quality and maintaining cash crop yields than NTr. Both NTr and CTr had greater cover crop growth when the cover crop seeding method changed from drill-seeding after harvest in phase 1 to broadcast seeding in a standing crop in phase 2 due to a longer growth period. That water and soil quality responses changed over the years emphasizes the need for long-term studies.

Kinetic modelling for COD and nitrate-N removal from hatchery wastewater through biological approach

This study was conducted to determine the nutrient removal efficiency via the application of mixed cultures from the synthetic hatchery wastewater based on the first-order, second-order and Stover Kincannon models. The synthetic wastewater was prepared according to the characterization of the collected hatchery wastewater sample, and the collected mixed cultures from the pond sediment were acclimatized accordingly. The samples were tested for chemical oxygen demand (COD) and nitrate-N concentration using a Hach spectrophotometer to determine the removal value of the nutrients. The findings show that the highest removal percentage for COD was up to 31.35% on day 3. Meanwhile, the highest removal percentage for nitrate-N was obtained on day 4 at 43.48%. The obtained correlation coefficient, for COD through first-order, second-order, and Stover Kincannon models is 1, 0.6774, and 0.965, respectively, suggesting that the kinetics of COD removal can be described most properly by the first-order model. A similar model was also reported for nitrate-N with value of 1, 0.7563, and 0.8693 for the first-order, second-order, and Stover Kincannon models, respectively. Based on the findings, the acclimatized mixed culture used in this study could be a potent natural COD and nitrate-N removal in the hatchery wastewater.