Nitrate Contamination Of Groundwater Research Articles

Identifying the spatial pattern and driving factors of nitrate in groundwater using a novel framework of interpretable stacking ensemble learning

Groundwater nitrate contamination poses a potential threat to human health and environmental safety globally. This study proposes an interpretable stacking ensemble learning (SEL) framework for enhancing and interpreting groundwater nitrate spatial predictions by integrating the two-level heterogeneous SEL model and SHapley Additive exPlanations (SHAP). In the SEL model, five commonly used machine learning models were utilized as base models (gradient boosting decision tree, extreme gradient boosting, random forest, extremely randomized trees, and k-nearest neighbor), whose outputs were taken as input data for the meta-model. When applied to the agricultural intensive area, the Eden Valley in the UK, the SEL model outperformed the individual models in predictive performance and generalization ability. It reveals a mean groundwater nitrate level of 2.22 mg/L-N, with 2.46% of sandstone aquifers exceeding the drinking standard of 11.3 mg/L-N. Alarmingly, 8.74% of areas with high groundwater nitrate remain outside the designated nitrate vulnerable zones. Moreover, SHAP identified that transmissivity, baseflow index, hydraulic conductivity, the percentage of arable land, and the C:N ratio in the soil were the top five key driving factors of groundwater nitrate. With nitrate threatening groundwater globally, this study presents a high-accuracy, interpretable, and flexible modeling framework that enhances our understanding of the mechanisms behind groundwater nitrate contamination. It implies that the interpretable SEL framework has great promise for providing valuable evidence for environmental management, water resource protection, and sustainable development, particularly in the data-scarce area.

Assessment of Nitrate Reduction by Microbes in Artificial Groundwater Medium

There are significant reasons for nitrate contamination in groundwater (Delhi, India): sewage, runoff from landfill sites, nitrogenous chemical fertilisers, and pesticides from agricultural lands. The highest recorded concentration of nitrate in Delhi’s groundwater is reported to be 1500 mg/l. Consumption of high nitrate through water may pose serious health problems in humans, especially children (below five years). The study’s primary objective was to isolate and identify nitrate-remediating microbes from the nitrate-contaminated site Okhla Barrage, located on the Yamuna River in Delhi, India. A total of 11 different strains were isolated from this site. Among these four strains exhibited 40%–50% remediation efficiency at a nitrate concentration of 1000 mg/l. Molecular characterisation revealed that these four strains, Enterobacter aerogenes, E. coli K12, <i>Klebsiella oxytoca</i> and <i>Lelliottia amnigena</i>, belong to the Enterobacteriaceae family. This study assessed the nitrate remediation potential of isolated microbes in groundwater with 1000 and 1500 mg/l nitrate concentrations. By using a 2% inoculum, the microbes were incubated anaerobically at room temperature for ten days. Nitrate concentrations were monitored every 48 hours. <i>Lelliottia</i>, <i>E. coli</i>, and <i>Enterobacter</i> reduced nitrate (1500 mg/l) by approximately 42%, 24%, and 29%, respectively, while <i>K. oxytoca</i> showed minimal reduction. <i>L. amnigena</i> exhibited superior nitrate removal efficiency compared to other strains. According to the reported data, these strains are known to reduce nitrate concentrations of 620 mg/l. However, our findings demonstrate a remarkable nitrate remediation capacity of 1500 mg/l, showcasing a novel contribution to this study. Further detailed analysis for condition optimisation and association of microbe-microbe could be more helpful.

Electrocatalytic Nitrate Reduction for Brackish Groundwater Treatment: From Engineering Aspects to Implementation

In recent years, nitrate has emerged as a significant groundwater pollutant due to its potential ecotoxicity. In particular, nitrate contamination of brackish groundwater poses a serious threat to both ecosystems and human health and remains difficult to treat. A promising, sustainable, and environmentally friendly solution when biological treatments are not applicable is the conversion of nitrate to harmless nitrogen (N2) or ammonia (NH3) as a nutrient by electrocatalytic nitrate reduction (eNO3R) using solar photovoltaic energy. This review provides a comprehensive overview of the current advances in eNO3R for the production of nitrogen and ammonia. The discussion begins with fundamental concepts, including a detailed examination of the mechanisms and pathways involved, supported by Density Functional Theory (DFT) to elucidate specific aspects of ammonium and nitrogen formation during the process. Furthermore, the integration of artificial intelligence (AI) and machine learning (ML) offers promising advancements in enhancing the predictive power of DFT, accelerating the discovery and optimization of novel catalysts. In this review, we also explore various electrode preparation methods and emphasize the importance of in situ characterization techniques to investigate surface phenomena during the reaction process. The review highlights numerous examples of copper-based catalysts and analyses their feasibility and effectiveness in ammonia production. It also explores strategies for the conversion of nitrate to N2, focusing on nanoscale zerovalent iron as a selective material and the subsequent oxidation of the produced ammonia. Finally, this review addresses the implementation of the eNO3R process for the treatment of brackish groundwater, discussing various challenges and providing reasonable opinions on how to overcome these obstacles. By synthesizing current research and practical examples, this review highlights the potential of eNO3R as a viable solution to mitigate nitrate pollution and improve water quality.

Chemical composition features of the Izhora groundwater field (Leningrad Region)

Drinking water quality is determined by the chemical composition of water and is regulated by sanitary legislation. Izhora field, located south of St. Petersburg on the Izhora Plateau, is the largest in the Leningrad region. The sediments contain fractured and karst limestones and dolomites (O1–3). The priority indicators of Ordovician aquifer quality in the Izhora groundwater field have been identified. Hardness, iron, manganese, barium, nitrates have been analyzed for assessing the Ordovician aquifer quality. A map of nitrate contamination of groundwater in the Izhora plateau has been constructed.

Study on the Remediation of Groundwater Nitrate Pollution by Pretreated Wheat Straw and Woodchips

Groundwater nitrate contamination poses a threat to both the ecological environment and human health. This study investigated the potential of using saturated Ca(OH)2 to pretreat wheat straw and woodchips, aiming to enhance their efficacy as carbon sources for denitrification. The optimization of pretreatment conditions, and the elucidation of underlying mechanisms were explored. The pretreatment process involved the dissolution of lignin and hemicellulose, exposure of the cellulose structure, reduction of hydrogen bonds within cellulose, hydrolysis of polymerized cellulose, and the formation of cracks and hierarchical structures on the surface of the carbon source. These alterations improved the attachment and utilization of microorganisms. The maximum enzymatic reducing sugar yields for wheat straw and woodchips were achieved at solid-liquid ratios of 1:40 and soaking times of 5 and 2 days, respectively. The response surface predicted the optimal pretreatment conditions for wheat straw to be a solid-liquid ratio of 1:88.1 and a soaking time of 8.2 hours. Alkaline treatment increased the denitrification rate of woodchips by fivefold and prevented the initial organic matter leaching rate of wheat straw, thereby reducing the risk of secondary pollution. The predominant microbial communities in all samples exhibited functions related to lignocellulose degradation and denitrification. The community composition of solid-phase carbon sources was found to be richer than that of liquid-phase carbon sources, and the pretreatment increased the abundance of lignocellulose degradation and denitrification functional microorganisms. The pretreatment liquid of wheat straw achieved the highest denitrification rate constant (0.43 h-1). Our result validated the feasibility of using the pretreatment liquid as a denitrification carbon source and presenting a novel approach for waste resource utilization.

Evaluating Health Risks Associated With Fluoride and Nitrate Contaminants in Drinking Water to Residents Living in the Chikkaballapur Taluk of Karnataka, India

ABSTRACTAddressing fluoride and nitrate contamination in groundwater is crucial for safeguarding public health. Fluoride contamination in groundwater can cause dental and skeletal fluorosis, along with potential neurotoxic effects. Nitrate contamination can lead to methemoglobinemia in infants and increase cancer risk due to the formation of nitrosamines. The major goal of this study was to examine groundwater quality in the Chickkaballapur urban (CBU) and Chikkaballapur rural (CBR) parts of the Chikkaballapur taluk (CBT), Karnataka, and to investigate the potential health hazards associated with the presence of fluoride and nitrate contaminants. Hazard quotient and total hazard index (THI) calculation methods, as suggested by the United States Environmental Protection Agency, were used in the present study to evaluate non‐carcinogenic risks for individuals of various age categories, including men, women, and children (MWC). A total of 112 samples from rural areas and 41 samples from urban areas of Chikkaballapur taluk were collected during the post‐monsoon season. According to the study's findings, groundwater samples from CBU and CBR surpassed acceptable fluoride concentration limits by 41% and 40%, respectively, while samples from CBR exceeded acceptable nitrate limits by 17%, set by the Bureau of Indian Standards (1 mg/L for fluoride and 45 mg/L for nitrate). All CBU samples remained within the acceptable nitrate limits. The total non‐carcinogenic health risks for MWC ranged from 0.34 to 2.18, 0.40 to 2.58, and 0.46 to 2.95, respectively, for CBU, and from 0.16 to 6.51, 0.19 to 7.69, and 0.21 to 8.80, respectively, for CBR. Furthermore, a significant percentage of the groundwater samples that were collected in CBU (60.98%, 68.29%, and 75.61%) and CBR (48.21%, 62.50%, and 73.21%) exceeded the THI limit for MWC (THI = 1). Hence, based on the health risk assessment, it is evident that children in the study area have greater health risks than men and women.

Groundwater nitrate contamination in China: Spatial distribution, temporal trend, and driver analysis

China's groundwater is facing a significant threat from nitrate pollution. Here we analyzed 2348 regional surveys of groundwater nitrate levels in China from 1990 to 2020, examining distribution, trends, and drivers. This study uncovers a concerning rise in nitrate pollution, with estimated median nitrate levels climbing from 3.84 mg/L in 1990 to 6.94 mg/L in 2020. A stark contrast is observed between regions: the northern areas have a median nitrate concentration of 8.54 mg/L, significantly higher than the southern regions, where the median is just 7.15 mg/L. From 1990 to 2020, agricultural activity consistently emerges as the dominant driver of changes in groundwater nitrate concentrations, while groundwater exploitation, domestic pollution, and industrial production also contribute to varying degrees. This analysis highlights the urgency for region-specific policies and interventions to address the escalating nitrate pollution in China's groundwater.

Occurrences of nitrate-contaminated groundwater in the piedmont aquifers: hydrogeochemical characteristics and health risks.

Groundwater nitrate (NO3-) contamination is a global concern. The distribution patterns, enrichment mechanisms, and human health risks of NO3- contaminated groundwater were investigated using 144 groundwater samples collected from domestic and irrigation wells in the piedmonts of the North China Plain (Beijing and Shijiazhuang areas). The results showed that the groundwater was neutral to weakly alkaline, and 47% of the groundwater samples had NO3- concentrations exceeding 50mg/L, a threshold proposed by world health organization to threaten infants up to 3months. Groundwater NO3- concentrations were generally higher in the Beijing piedmont than in the Shijiazhuang piedmont and decreased with depth in both piedmonts. High-NO3- (> 50mg/L) groundwater was distributed sporadically spatially and mainly was of Ca-Mg-HCO3 hydrochemical facies. Stable isotopes (D and 18O) compositions and NO3-/Cl- ratios indicated that NO3- accumulation in groundwater was primarily due to use of N-fertilizers under agricultural practices, and was associated with groundwater recharge sources such as septic tank leakage and re-infiltration of reclaimed irrigation water. Water quality evaluation showed that groundwater quality was highly dependent on NO3- concentration, with entropy-weighted water quality index values increasing linearly with increasing NO3- concentrations. The potential health risk of high-NO3- groundwater was the most serious for infants in both the piedmonts. Therefore, reducing NO3- input from sources and drinking water intake is recommended to minimize the human health risk.

Unveiling seasonal nitrate contamination dynamics in cropland sub-watersheds: A geo-morphological analysis of the bilate agricultural watershed

Cropland sub-watershed surface and groundwater contamination are pressing issues for water management. This study examines the impact of sediment transport indices (STI) on nitrate concentration in downstream water bodies. The research highlights rainfall's significant role in predicting seasonal nitrate levels. Employing GIS-SWPT tools and hydro-geomorphologic analysis, cropland sub-watersheds, particularly sub-watersheds one and three, are prioritized for their high contribution to downstream surface and groundwater nitrate contamination, with prioritization values of 105.58 and 180.63, respectively. Statistical analysis, conducted using Python's scikit-learn library, validated the findings of the study, with the model's F-statistic of 79.63 and a corresponding p-value of 0.0147 underscoring its overall significance. However, while STI alone showed a prioritization parametric correlation coefficient of 0.5077, suggesting other external factors also contribute to nitrate loading, a strong relationship between STI and nitrate concentration was revealed (R² of 0.993). This integrated approach enhances understanding of how geomorphologic parameters of cropland sub-watersheds influence water quality downstream. By clarifying the complex interactions between sediment transport and nitrate concentration, evidence-based strategies can be developed to mitigate surface and groundwater nitrate pollution. This research provides valuable insights into cropland sub-watershed pollution dynamics and informs targeted management interventions.

Integrated assessment of groundwater quality dynamics and Land use/land cover changes in rapidly urbanizing semi-arid region

Rapid urbanization worldwide, poses numerous environmental challenges between escalating land use land cover (LULC) changes and groundwater quality dynamics. The main objective of this study was to investigate the dynamics of groundwater quality and LULC changes in Sargodha district, Punjab, Pakistan. Groundwater hydrochemistry reveals acceptable pH levels (<8) but total dissolved solids (TDS), electrical conductivity (EC) and HCO3− showed dynamic fluctuations by exceeding WHO limits. Piper diagrams, indicated dominance by magnesium and bicarbonate types, underscoring the influence of natural processes and anthropogenic activities. Major ion relationships in 2010, 2015, and 2021 showed a high correlation (R2 > 0.85) between Na+ and Cl−, suggesting salinization. whereas, the poor correlation (<0.17) between Ca2+ and HCO3− does not support calcite dissolution as the primary process affecting groundwater composition. The examination of nitrate contamination in groundwater across the years 2010, 2015, and 2021 was found to be high in the municipal sewage zone, suggesting a prevailing issue of nitrate contamination attributed to urban activities. The Nitrate Pollution Index (NPI) reveals a concerning trend, with a higher proportion of samples classified under moderate to high pollution categories in 2015 and 2021 compared to 2010. The qualitative assessment of nitrate concentration on spatiotemporal scale showed lower values in 2010 while a consistent rise from 2015 to 2021 in north-east and western parts of district. Likewise, NPI was high in the north-eastern and south-western regions in 2010, then reduced in subsequent years, which may be attributed to effective waste management practices and alterations in agricultural practices. The health risk assessment of 2010 indicated Total Health Hazard Quotient (THQ) within the standard limit, while in 2015 and 2021, elevated health risk was observed. This study emphasizes the need to use multiple approaches to groundwater management for sustainable land use planning and regulations that prioritize groundwater quality conservation.

Assessment of spatiotemporal risks for nationwide groundwater nitrate contamination

National assessments of groundwater contamination risks are crucial for sustaining high-quality groundwater supplies. However, traditional methods often treat groundwater contamination risk as a steady-state indicator without considering spatiotemporal variation in risk, both geographically and over time, caused by anthropogenic and climatic factors. In this work, XGBoost, a tree-based algorithm, was applied to comprehensively analyze the drivers of groundwater contamination from nitrate, using data on 13 physical features (as used by the index-based ranking method DRASTIC) and 30 anthropogenic features from 1985 to 2010 in the contiguous United States (CONUS). The results indicate that physical features controlling the transport processes, particularly those affecting contaminant travel time from land surface to groundwater (depth to water table and transmissivity), were the dominant factors for nitrate contamination in groundwater. This was followed by features representing the potential nitrogen loading. Positive correlations between most features and the nitrogen loading time (year) were found, suggesting their growing influence on contamination risk. Based on the drivers identified for nitrate concentrations exceeding 10 mg/L in groundwater and their varying temporal contributions, this study proposes a reformulated index-based method for contamination risk assessment. With this method, an overall accuracy of around 70 % was achieved based on the validation data set. The predicted high-risk areas are mainly intensive irrigation regions, such as the High Plains, northern Midwest, and Central Valley. This new approach contributes to a more accurate and effective assessment of the contamination risks of groundwater on a regional and national scale under temporally varying environmental conditions.

Unveiling nitrate origins in semiarid aquifers: A comparative analysis of Bayesian isotope mixing models using nitrate and boron isotopes and a Positive Matrix Factorization model

Nitrate contamination of groundwater is a pressing global concern, affecting over 80 million people worldwide, with agricultural activities being the primary contributor to nitrogen inputs into aquifers. The primary objective of this study was to identify the predominant sources of nitrate pollution and biogeochemical transformations in the semiarid region of the Meoqui-Delicias aquifer, Mexico. In this region, the uncontrolled use of chemical fertilizers and manure leads to excessive nutrient input, which accelerates the deterioration of groundwater quality. This study introduces an innovative dual-model approach (δ15NNO3 vs. δ11B) to compare the Bayesian Isotope Mixing Model (BIMM) with Positive Matrix Factorization (PMF) for nuanced source apportionment. This approach enhanced the differentiation between manure and sewage as nitrate sources. Results from the δ15NNO3 vs. δ11B model revealed that manure (52.4%) was the most significant source of nitrate pollution in the aquifer, followed by soil (37.4%), chemical fertilizers (5.5%), and sewage (4.7%). The PMF model corroborated this finding and indicated that 60.2% of the NO3–-N pollution in the aquifer was attributed to manure and sewage, confirming the superior performance of the proposed BIMM in source differentiation. Our findings enhance the understanding of nitrate dynamics in semi-arid regions and can serve as a scientific evidence base for targeted interventions in nutrient management in the study area and elsewhere.

Multi-method characterization of groundwater nitrate and sulfate contamination by karst mines in southwest China

Groundwater contamination by nitrate and sulfate in mining areas is a significant challenge. Consequently, the inputs sources of these contaminants and their evolution have received considerable attention, with the knowledge gained critical for improved management of water quality. This study integrated data on multiple stable isotopes and water chemistry data and a Bayesian isotope mixing model to investigate the relative contributions of inputs sources of sulfate and nitrate sources to bodies of water in a karst mining area in southwest China. The outcomes indicated that hydrochemical component in the water bodies of the study area is mainly derived from the dissolution of silicate rocks, carbonate rocks and sulfate minerals as well as the oxidation of sulfides. The human and agricultural wastewater, soil nitrogen, and fertilizers were the predominant inputs sources of nitrate to the mine water environment; the predominant inputs sources of sulfide were mineral oxidation, evaporite dissolution, atmospheric deposition, and sewage. Groundwater is mainly recharged from atmospheric precipitation, and surface water is closely hydraulically connected to groundwater. Nitrogen and oxygen isotope composition and water chemistry indicative of nitrification dominate the nitrogen cycle in the study area. The oxidation of pyrite and bacterial sulfate reduction (SRB) had no significant impact on the stable isotopes of groundwater. The results of this study demonstrate the inputs of different sources to nitrate and sulfate in karst mines and associated transformation processes. The results of this study can assist in the conservation of groundwater quality in mining areas and can act as a reference for future related studies.

Precipitation, temperature, and landcovers drive spatiotemporal variability of groundwater nitrate concentration across the Continental United States

Groundwater nitrate contamination, especially in agriculturally active regions, is a well-recognized environmental concern. Understanding how this contamination evolves across the continental USA (CONUS) and through time is important to designing effective mitigation strategies. Despite extensive research on nitrate contamination, no existing studies can accurately predict changes in groundwater nitrate concentrations over time across the CONUS. To bridge this gap, we compiled a comprehensive dataset for a systematic evaluation of the potential influence of climate dynamics, landcover changes, and crucial soil and geological properties on groundwater contamination. We employed an interpretable machine learning approach, using 293,775 groundwater nitrate observations and 12 independent variables, to estimate annual groundwater nitrate concentrations at the county level from 2001 to 2020. Our model is the first one capable of accurately forecasting temporal changes in groundwater nitrate concentration across the entire CONUS. Our analysis reveals county level groundwater nitrate concentration changes occurred over the past two decades, particularly in regions initially with high concentrations in 2001, ranging from −16.2 mg/L-N to +6.5 mg/L-N between 2001 and 2020. 27 counties in the country appeared to have new concentrations greater than or equal to the maximum concentration level (MCL) at least once during this period. We revealed direct relationships between groundwater nitrate concentrations and climate factors, including that temperature and precipitation dominate the interannual variability in groundwater nitrate concentration in 75.2 % of counties. Notably, we have established a clear correlation between groundwater nitrate concentration and precipitation. Specifically, when annual precipitation falls below a threshold of about 748 mm, an increase of precipitation can directly result in elevated nitrate concentrations in groundwater, indicating heightened vulnerability to contamination due to climate change. This study forms a pivotal foundation for forecasting groundwater nitrate concentration changes across the continent and assessing the potential impact of climate change on future groundwater nitrate concentrations.

Enhanced Biological Nitrate Removal from Groundwater in Humid Tropical Regions Using Corn Cob-Based Permeable Reactive Barriers: A Case Study from Panama

Nitrate contamination in groundwater is a global concern due to its widespread presence and consequential social, environmental, and economic ramifications. This study investigates the efficacy of biological denitrification in a humid tropical setting, utilizing corn cob in batch and column tests to assess nitrate removal under varying conditions. Batch tests demonstrated the nitrate removal efficiencies of 93.14%, 91.58%, 90.77%, and 98.74% for initial concentrations of 22.18 ± 2.82 mg/L, 27.3 mg/L, 69.1 ± 1.2 mg/L and 115.08 ± 1.88 mg/L, respectively. In the column test, the removal efficiency was 99.86%, 87.13%, and 74%, and the denitrification rate was 32.82, 53.43, and 83.53 mg NO3−-N/L d, for a hydraulic retention time (HRT) of 24 h, 16 h, and 7 h, respectively. Predominantly, nitrate removal occurred via biological denitrification, particularly favoring a 24 h HRT. The corn cob effectively removed high nitrate concentrations of up to 115 mg NO3−-N/L. Scanning electron microscopy and Fourier transform infrared spectroscopy revealed surface characteristic changes of the carbon source pre- and post-denitrification. This research sheds light on the potential of biological denitrification using corn cob in humid tropical environments, offering a promising avenue for addressing nitrate contamination challenges in groundwater systems.

Research Advances of Groundwater Nitrate Pollution and Source Apportionment in China

Groundwater nitrate (NO3-) contamination in China has become a serious environmental problem, especially in agricultural production areas, which greatly affects the safety of drinking groundwater and requires urgent attention. In this study, the main sources of groundwater nitrate in China were reviewed, including atmospheric deposition, soil nitrogen, agricultural fertilization, and fecal sewage, among which fecal sewage and agricultural fertilization were the main reasons for the excessive groundwater nitrate. The application of hydrochemical analysis, multivariate statistical analysis, stable isotope tracer method, and microbial source tracking in the source apportionment of groundwater nitrate was summarized. All types of source apportionment methods had certain limitations. It is suggested that a variety of methods should be used to identify the source of groundwater nitrate, and the contribution rate of different pollution sources should be calculated using multivariate statistical analysis and isotope quantitative analysis models. The source apportionment of nitrate pollution has undergone a process from qualitative to quantitative research. At present, the SIAR and MixSIAR models based on δ15N-NO3-and δ18O-NO3- have been used widely to analyze the source of nitrate. However, due to the overlap of isotope characteristic values of different input end-members, the difference in δ15N-NO3-and δ18O-NO3- values under different spatial and temporal changes, and the influence of isotope fractionation in the process of nitrogen migration and transformation, the results calculated by the model remain uncertain. It is necessary to further optimize the analytical method of the model to obtain the source of nitrate pollution and its contribution rate more accurately to further aid in the scientific management of groundwater resources.

Impact of Agricultural Practices on Nitrate Pollution in Groundwater in India

Purpose: The aim of the study was to examine impact of agricultural practices on nitrate pollution in groundwater in India Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: a significant environmental concern with far-reaching implications for human health, ecosystem integrity, and water resource management. It is evident that agricultural activities such as fertilizer application, irrigation methods, and land management practices play a pivotal role in exacerbating nitrate contamination of groundwater. The studies highlighted the complex interactions between agricultural activities and hydrological processes, elucidating the pathways through which nitrates migrate from soil to groundwater. Unique Contribution to Theory, Practice and Policy: Diffuse Pollution Theory, Hydrological Connectivity Theory &amp; Sustainable Agriculture Theory may be used to anchor future studies on impact of agricultural practices on nitrate pollution in groundwater in India. Encourage the adoption of sustainable agricultural practices that minimize nitrate pollution while maintaining agricultural productivity. This includes promoting precision agriculture techniques, cover cropping, and integrated nutrient management systems to optimize fertilizer use and reduce nitrate leaching. Strengthen regulations and enforcement mechanisms to limit nitrate pollution from agricultural activities. This may include setting stringent water quality standards for nitrate concentrations in groundwater and implementing monitoring programs to assess compliance.

Nitrate and Ammonia Contamination in Groundwater and their Effect on Microbial Community in Apulia Region

Nitrate and Ammonia Contamination in Groundwater and their Effect on Microbial Community in Apulia Region

Evaluating the seasonal effects of whole orchard recycling on water movement and nitrogen retention for a newly established almond orchard: Simulation using HYDRUS-1D

Whole orchard recycling (WOR) is an emerging practice in perennial cropping systems and is an alternative to open or cogeneration burning. It is an orchard removal practice that incorporates large amounts of woody biomass back into the soil system. In this study, we utilized a soil hydrological model (HYDRUS-1D) to evaluate the seasonal effects of WOR on water movement and nitrogen (N) retention for a newly established almond orchard on a typical sandy loam soil in the Central Valley of California. Soil moisture and N content were monitored across the first five growing seasons from 2018 to 2022. The model was able to track seasonal moisture fluctuation nicely compared to observed data. Additionally, an increase in soil moisture was measured in the WOR treatments in surface soil (i.e., 0- to 15-cm depths) where biomass was incorporated, and N leaching was reduced when compared to the unamended control. Simulations suggest that with WOR, irrigation can be reduced by up to 20 % during the tree establishment stage with minimal effect on root water uptake. This reduction in applied water can increase farm water use efficiency and reduce operational expenses, e.g., cost of water and pumping. Likewise, the reduction in N leaching observed in both predicted results and laboratory analysis can further cut farm capital costs, e.g., fertilization, and lessen orchard environmental impacts. Overall, results from our simulation show a positive effect of WOR on soil ecosystem services and can potentially be a profitable strategy for orchard turnover. The results have important implications in reducing groundwater nitrate contamination in irrigated agriculture in the Central Valley of California and applicable to most parts of Southwestern United States.

Nitrate contamination in groundwater and its health risk assessment: a case study of Quanzhou, a typical coastal city in Southeast China

Nitrate contamination in groundwater and its health risk assessment: a case study of Quanzhou, a typical coastal city in Southeast China