The western region of the Qinghai-Tibet Plateau is characterized by an arid climate with minimal rainfall, making groundwater the primary water source for local towns. In recent years, levated concentrations of arsenic(As), fluoride(F-) and nitrate(NO3-) in groundwater have raised concerns about drinking water safety. This study, collected 52 groundwater samples from wells in seven towns across six basins in the Ali region. By employing methods such as mathematical statistics, major ion ratio analysis, the Entropy-Weighted Water Quality Index (EWQI), and Monte Carlo simulation, the characteristics of hydrogeochemical components, controlling factors, and potential risks of groundwater in this region were clarified. The groundwater chemistry type is dominated by HCO3-Ca, and its ion concentration from high to low is Ca2+ > Na+ > Mg2+ > K+ and HCO3- > SO42- > Cl- > NO3- >F-. The most severe As pollution (0-0.09 mg/L) occurred in Gaer(GR)and Geji(GJ) towns within the Shiquan River Basin in the western part of the study area, This is primarily attributed to high As hot spring discharge, ion exchange, and the weathering and dissolution of As-containing minerals in silicate rocks Elevated F- concentrations (0.01-1.41 mg/L) were observed in Gaize(GZ) of the Luoren River Basin and Ritu(RT) of the Maka River Basin, driven by evaporation and the dissolution of F--containing minerals in evaporitic salt rocks and silicate rocks. NO3- concentrations ranged from 1.44-30.2 mg/L, and were mainly influenced by human activities. Groundwater quality was evaluated using the EWQI method. Groundwater samples from Gaer(GR)and Geji(GJ) in the Shiquan River Basin exhibited poor to very poor quality, while samples from the other five towns ranged from excellent to good. Health risks were simulated using the Monte Carlo method, revealing that both carcinogenic and non-carcinogenic risks require attention, particularly in the Shiquan River Basin, where As pollution is significant. The effective exposure factor (EF) was the most critical parameter influencing health risks, followed by As concentration and body weight (BW), with BW showing a negative correlation and other parameters showing positive correlations with risk. This study offers new insights into groundwater pollution control mechanisms and associated health risks in the western urban area of the Qinghai-Tibet Plateau. It also provides valuable references for groundwater resource management and pollution prevention in the region and downstream South Asian countries.

Using unscientific agricultural methods can harm human health by increasing harmful nitrate (NO3-) levels in groundwater, as observed in the Yinchuan Plain. This research utilized hydrochemical data, dual isotopic data, the MixSIAR model, and the uncertainty index (UI90) to detect the potential sources of groundwater NO3-, track NO3- conversion processes, and calculate the apportionment of each groundwater NO3- source in the agricultural lands of the Yinchuan Plain. The results show that soil organic nitrogen accounted for 49.4 %, and N-fertilizers contributed 30.4 %, making them the two main contributors to NO3- contamination in groundwater. Long-term N-fertilization enhances soil organic nitrogen accumulation, resulting in NO3- leaching into groundwater during irrigation. The highest uncertainty regarding soil organic nitrogen and N-fertilizers may stem from changes in groundwater flow patterns, unbalanced N-fertilization, irrigation, and precipitation. Denitrification is the dominant process, resulting in lower NO3- concentrations in groundwater in most areas. As a result, most groundwater in the Yinchuan Plain is generally safe for human consumption, except the specific areas in Qingtongxia City and Wuzhong City. Flood irrigation can increase the leaching of NO3- into groundwater, and the repeated recharge of groundwater contaminated with high NO3- levels could also be a potential source of NO3- contamination in agricultural areas. This research provides scientific guidance for sustainable groundwater management in the Yinchuan Plain, mitigating the risk of groundwater NO3- pollution.

The wetlands of Qinghai-Tibet Plateau (QTP) have important ecological functions on biodiversity conservation and water resources protection, but the pollution and risk of microplastics in those wetlands remains elusive. Herein, the character, source, ecological risk of microplastics in two typical wetlands for 40 samples of QTP were investigated. The results demonstrated that the average abundances of microplastics in surface water of Nianchu river wetland and Maidika wetland were 1615 f 1505.8 items/m3 and 325 f 426.9 items/m3, respectively, while the sediment of them were 680.7 f 550.1 items/kg, 322.8 f 351.6 items/kg, respectively. Microplastics in surface water and sediments were predominantly fragments (Nianchu river wetland), film and sphere (Maidika wetland), transparency, and 100-500 mu m, respectively. Polypropylene was the main types in QTP wetlands based on the intelligently identified by a machine learning algorithm (accuracy of 0.977). Residents, resident's life, tourist flow, agricultural and fishery activities are the main sources of microplastics in the wetlands. In addition, the abundances of microplastics have positively correlation with total nitrogen in water samples, annual precipitation, and nighttime light index. Compared with the incomplete parameters of other algorithms, Potential Ecological Risk Index combined microplastics abundance and type to give a more reasonable assessment of the microplastics risk level of QTP wetlands. That is, 88.9% of surface water and all sediment microplastics pollution are at low risk. However, attention should be paid to the sources of microplastics brought by tourism and residential life. The study is beneficial to supplement the data of microplastics pollution in the wetland areas of Qinghai-Tibet Plateau.

The contamination issue of high Cr(VI) groundwater have become a widespread environmental issue globally. Nevertheless, the interaction between Cr(VI) and groundwater microbial communities in shallow aquifers remains insufficiently understood and requires further investigation. This study employs hydrogeochemistry, stable isotope analysis, and microbial molecular ecology techniques to reveal the genetic mechanisms of high Cr(VI) in shallow groundwater within the Jinghui Canal Irrigation District. The findings revealed that Cr(VI) contents in groundwater varied between 0.01 and 0.15 mg/L, with 20.8 % of samples exceeding the limits. The weathering and dissolution of silicate rocks, as the primary water-rock interaction in the groundwater, facilitates the release of chromium bound in unweathered silicate rocks and serves as the key contributor of Cr(III) in groundwater. Manganese-oxidizing genera such as Pseudomonas, Flavobacterium, and Sphingobium, recognized as key biomarkers distinguishing microbial communities in high and low Cr(VI) groundwater, play a pivotal role in the oxidation of Cr(III), and are the main factor contributing to the presence of high Cr(VI) groundwater. Nitrification reactions occur widely, and the resultant H+ acidification facilitates leaching of Cr-containing mineral phases and increases Cr(VI) enrichment. In conclusion, the formation of high Cr(VI) groundwater primarily results from microbially mediated Cr(III) oxidation, with secondary contributions from Cr(VI) desorption and nitrification processes that further influence its enrichment.

Groundwater nitrate pollution is a global environmental issue impacted by complex biogeochemical processes. The biogeochemical behavior of nitrogen in groundwater can significantly influence the hydrogeochemical processes and the carbon cycle. This study, taking the Jinghuiqu Irrigation District in China as an example, analyzed the biogeochemical processes of nitrate in groundwater, and discussed their effects on groundwater chemical weathering and the carbon cycle by using groundwater chemistry, multiple isotopes (515N-NO3-, 518ONO3-, and 518O-H2O), and microbial techniques. Results indicated that nitrification predominantly drives the biogeochemical processes of nitrogen in groundwater in this area. Anthropogenic nitrogen inputs enhanced the geochemical weathering of sediments in shallow groundwater systems through nitrification. As nitrification increased nitrate concentrations, the net CO2 sink gradually shifted to a net CO2 source. Under the influence of nitrification, the CO2 consumption decreases, leading to a reduction in the carbon sink. The average CO2 consumption rates of carbonate weathering and silicate weathering were 1.10 x 105 mol/km2/yr and 0.60 x 105 mol/km2/yr, respectively. Additionally, energy released during nitrification may promote microbial metabolic processes related to the carbon cycle. Correlation analysis of the nitrogen cycle and carbon cycle pathways revealed a significant association (p <= 0.05) between nitrification and both the reductive tricarboxylic acid cycle and the Calvin-Benson-Bassham cycle. Therefore, nitrification significantly influences the nitrogen cycle and may indirectly affect the carbon cycle. This research enhances our understanding of how the biogeochemical processes of groundwater nitrogen impact hydrochemistry and the carbon cycle, providing scientific insights for addressing climate change and ecosystem management.

Understanding the hydrochemical characteristics and interactions between surface water and groundwater is crucial for the development and protection of water resources in the watershed. This research employs mathematical statistics, hydrogen and oxygen isotopes, IsoSource model, and hydrogeochemical simulation to analyze the interactions between surface water and groundwater in the Hua County, Guanzhong Plain, China. The findings revealed that the surface water and groundwater are weakly alkaline and low-mineralization freshwater, and the primary hydrochemical types was HCO3SO4·Ca type. The absolute dominance of HCO3 - and Ca2+ in both surface and groundwater can be largely attributed to the dissolution of carbonate and silicate rocks. Evaporation led to δD and δ18O values enrichment in surface water samples from different tributaries, while groundwater samples, though less affected by evaporation, also displayed δD and δ18O enrichment due to river water infiltration recharge. Overall, the transformation relationship between surface water and groundwater is dominated by surface water infiltration recharge to the groundwater, with recharge contribution rates ranging from 4.7% to 64.5%. Additionally, some surface water samples from the Shidi River were characterized with high fluoride, which may be ascribed to human activities and evaporation. SUMMARY: Surface water and groundwater are weakly alkaline, dominated by HCO3SO4·Ca type. Hydrochemical components are primarily controlled by silicate rock dissolution. Surface-groundwater interaction mainly involves surface water infiltration. δ18O tracing reveals surface water infiltration recharge rates ranging from 4.7% to 64.5%.

The identification and quantification of high-risk hotspots for soils contaminated by heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) remains a challenge due to their various sources and heterogeneous sink properties in urban soil systems. In this study of 221 soil samples from Guangzhou, China, a novel framework combining Bivariate local Moran's I (BLMI), positive matrix factorization (PMF), human health risk (HHR) assessment, Monte Carlo simulation (MCS), and a newly developed spatial risk model were proposed to conduct probabilistic source-oriented HHR assessment, high-risk hotspot quantification, and risk formation mechanism elaboration. Study results indicate that traffic emissions are the largest contributor of HMs (47.6 %) and PAHs (40.2 %), but not always the largest contributor of HHR. Agricultural or urban green-space management activities of HM, and mixed source of PAH, are the largest contributors of non-carcinogenic risk (NCR, 48.7 % and 51.1 %, respectively), while mixed source of HM and traffic emissions of PAH are the largest contributors of carcinogenic risk (CR, 53.9 % and 71.2 %, respectively). The probability of risk exceeding safe threshold levels is < 5.0 % for NCR and > 90.0 % for CR. High-risk hotspots were identified in the mid-west and south of the city, making up 15.0 % of the total Guangzhou area. Risk mechanisms were deduced from the spatial heterogeneity and inter-dependence of emission sources and soil sink, based on source-sink theory. Our findings provide a new framework for precisely identifying risk sources and target areas, thereby alleviating HHR associated with co-occurring HMs and PAHs in urban soil systems.

With the rapid development of urbanization and agriculture, land use/land cover (LULC) types are directly and indirectly affected. Nitrate in groundwater, a pervasive pollutant, exhibits a close association with LULC changes. Employing Google Earth Engine, this study aims to elucidate the evolution characteristics of LULC type in northern piedmont of the Qinling Mountains, a region demarcating northern and southern China. By using analysis with multivariate statistics and Spearman correlation, the variation characteristics of groundwater nitrate under different LULC patterns were analyzed. Isotopic methods were used to identify nitrate sources, and the Bayesian stable isotope mixing model (MixSIAR) was used to determine the proportional contributions of potential sources under different land types. The results indicate that from 2015 to 2021, the distribution of high nitrate groundwater had been extended from the western region to the whole region. Groundwater nitrate levels are higher in farmland and rural land, contrasting with relatively lower concentrations in the forest/grassland types near the northern Qinling Mountains. Forest/grassland was negatively correlated with NO3−, indicating that plant roots may enhance nitrogen uptake. Soil nitrogen, manure/sewage, and chemical fertilizers were primary nitrogen sources. In addition, the average contribution of soil nitrogen in farmland, rural land, and forest/grassland to groundwater NO3− were 48.1, 50.2, and 44.8

Groundwater drought is a significant type of hydrological drought and manifests as abnormal groundwater shortages as a result of prolonged drought propagation. This type of drought typically exhibits a longer duration than meteorological and agricultural droughts and can be severe in arid and semiarid regions. Human activities like pumping can further complicate the detection and characterization of groundwater drought. This study used long-term groundwater level monitoring data from 1991 to 2018 for the Yinchuan region to calculate a standardized groundwater level index and applied hierarchical clustering and the run theory to assess groundwater drought. Additionally, the relationship between groundwater and meteorological/agricultural droughts were investigated, and the factors driving groundwater drought were analyzed. Based on the results, regional groundwater droughts are becoming increasingly severe. In this study, there are regional differences in the trends of the standardized groundwater level index, which could be divided into three clusters (C1, C2, and C3). Wells in C2 are located near the Yellow River and show a shorter groundwater drought duration (mean value: 3.16 months), which means that these wells can recover from drought more quickly than those in the other clusters. Meteorological and agricultural droughts show a weak correlation with groundwater drought (with average cross-correlation coefficients of 0.03 and 0.25, respectively), and human activities most likely were the causes of regional groundwater droughts. Thus, a comprehensive understanding of regional groundwater droughts should consider human activities, in addition to the geographical location and natural environments. This research establishes a scientific foundation for managing regional groundwater resources and offers novel insights for future groundwater drought studies in the context of human activities.

Water conservancy projects affect the migration, suspension, and deposition of microplastic (MP). However, its impact on MP pollution of river ecosystem remains elusive. Herein, we investigated the MP characteristics and the influence of water conservancy projects on MPs in the Lhasa River Basin of the Qinghai-Tibet Plateau, China. The results demonstrated that the MPs concentration in surface water decreased from upstream to downstream, as more MPs in surface water were settling down and stored in reservoir sediments in the midstream. It is postulated that reservoir sedimentation of MPs occurs at a greater rate due to the barrier effect of reservoirs, steady hydrodynamics, and weak salinity-induced buoyancy. To evaluate the ecological risk of the Lhasa River Basin, the pollution load index, the polymer hazard index, and the potential ecological risk index were analyzed. The upstream exhibits elevated polymer hazard index values (>100), and the potential ecological risk index values in the Lhasa River Basin showed ecological risk similar to those of pollution load index values. This research represents the initial exploration of MP distribution within the entire Lhasa River basin, providing a foundational framework for investigating the impact of water conservancy projects on MP migration.

The global public health concern of nitrate (NO3-) contamination in groundwater is particularly pronounced in irrigated agricultural regions. This paper aims to analyze the spatial distribution of groundwater NO3-, assess potential health risks for local residents, and quantitatively identify nitrate sources during different seasons and land use types in the Jinghuiqu Irrigation District, a region in northwestern China with a longstanding agricultural history. The investigation utilizes hydrochemical parameters, dual isotopic data, and the Bayesian stable isotope mixing model (MixSIAR). The findings underscore significant seasonal variations in the average concentrations of NO3-, with values of 87.72 mg/L and 101.87 mg/L during the wet and dry seasons, respectively. Furthermore, distinct fluctuations in nitrate concentration were observed across different land use types, whereby vegetable lands manifested the maximum concentration. Prolonged exposure to elevated nitrate concentrations may pose potential health risks to residents, especially in the dry season when the non-carcinogenic groundwater nitrate risk surges past its wet season counterpart. The MixSIAR analysis revealed that chemical fertilizers accounted for the majority of nitrate pollution in vegetable lands, both during the dry season (49.6%) and wet season (41.2%). In contrast, manure and sewage contributed significantly to NO3-concentrations in residential land during the wet (74.9%) and dry seasons (67.6%). For croplands, soil nitrogen emerged as a dominant source during the wet season (42.2%), while chemical fertilizers prevailed in the dry season (38.7%). In addition to source variations, the nitrate concentration of groundwater is further affected by hydrogeological conditions, with more permeable aquifers tending to display higher nitrate concentrations. Thus, targeted measures were proposed to modify or impede the nitrogen migration pathway, taking into consideration hydrogeological conditions and incorporating domestic sewage, organic fertilizer, and agricultural management practices.

Groundwater recharge from precipitation is a complex process that often exhibits strong nonlinearity. This process is influenced by multiple hydrogeological and topographical condi-tions. This study aims to assess the response of shallow groundwater table to precipitation in the northern piedmont of the Qinling Mountains in China from 2005 to 2015 using a combination of the Mann-Kendall (MK) test, continuous wavelet transform, and cross-wavelet transform. The MK test revealed a slight upward trend of precipitation from 2005 to 2015. In addition, 71% of the shallow groundwater monitoring wells exhibited increasing trends in the groundwater table depth. Continuous wavelet transform demonstrated periodic groundwater responses to precipi-tation. Both precipitation and groundwater table showed significant monthly oscillation of 9-15 months, while the highest wavelet power was detected at the temporal scale of 12 months. Ac-cording to the results of the cross wavelet transform, lag times between groundwater level re-sponses and precipitation events were 78, 73, and 99 days for P1-PF1, P2-FT1, and P3-ST1 in pluvial fans, first terraces, and second terraces, respectively. Moreover, the results suggested spatiotemporal variations in the lag time, which might be due to the variation in groundwater levels, aquifer lithology, precipitation intensity, and groundwater exploitation intensity. The current study revealed the spatiotemporal response mechanism of the shallow groundwater to precipitation, providing a scientific basis for assessing the regional water cycle processes and ensuring effective groundwater resource management.

Nitrate (NO3-) pollution of groundwater is a global concern in agricultural areas. To gain a comprehensive understanding of the sources and destiny of nitrate in soil and groundwater within intensive agricultural areas, this study employed a combination of chemical indicators, dual isotopes of nitrate (δ15N-NO3- and δ18O-NO3-), random forest model, and Bayesian stable isotope mixing model (MixSIAR). These approaches were utilized to examine the spatial distribution of NO3- in soil profiles and groundwater, identify key variables influencing groundwater nitrate concentration, and quantify the sources contribution at various depths of the vadose zone and groundwater with different nitrate concentrations. The results showed that the nitrate accumulation in the cropland and kiwifruit orchard at depths of 0-400 cm increased, leading to subsequent leaching of nitrate into deeper vadose zones and ultimately groundwater. The mean concentration of nitrate in groundwater was 91.89 mg/L, and 52.94% of the samples exceeded the recommended grade III value (88.57 mg/L) according to national standards. The results of the random forest model suggested that the main variables affecting the nitrate concentration in groundwater were well depth (16.6%), dissolved oxygen (11.6%), and soil nitrate (10.4%). The MixSIAR results revealed that nitrate sources vary at different soil depths, which was caused by the biogeochemical process of nitrate. In addition, the highest contribution of nitrate in groundwater, both with high and low concentrations, was found to be soil nitrogen (SN), accounting for 56.0% and 63.0%, respectively, followed by chemical fertilizer (CF) and manure and sewage (M&S). Through the identification of NO3- pollution sources, this study can take targeted measures to ensure the safety of groundwater in intensive agricultural areas.

Clarifying the biogeochemical mechanism of nitrate (NO3-) in the vadose zone-groundwater system, particularly in agricultural contexts, is crucial for mitigating groundwater NO3- pollution. However, comprehensive studies on the impacts of changes in chemical indicators and microbial communities on NO3- are still lacking. This paper aims to address this gap by employing hydrogeochemistry, stable isotopes, and microbial techniques to assess the NO3- biogeochemical processes in the vadose zone-groundwater system. The findings suggested that NO3- in upper soil layers was primarily influenced by plant root absorption, assimilation, and nitrification processes. The oxygen contents gradually decreased with the nitrification process, resulting in the occurrence of the denitrification. However, denitrification predominantly occurred in the 60-80 cm soil layer in the study area. The limited thickness of the denitrification layer results in less NO3- consumption, leading to increased NO3- leaching into groundwater. Hydrochemical and isotopic characteristics further indicated that groundwater NO3- concentrations were mainly controlled by nitrification, followed by denitrification and mixing processes. The 16S rRNA sequencing analysis revealed great influences of soil sampling depths and groundwater NO3- concentrations on the microbial community structure. Additionally, the PICRUSt2-based prediction results demonstrated a stronger potential for dissimilatory reduction of NO3- to ammonium (DNRA) in both soil and groundwater compared to the other processes, potentially due to the widespread presence of the nrfH functional genes. However, the chemical indicators and isotopes used in this study did not support the occurrence of DNRA process in the vadose zone-groundwater system. This finding highlights the importance of an integrated approach combining microbiological, isotopic, and hydrogeochemical data to comprehensive understanding biogeochemical processes. The study developed a conceptual model elucidating the NO3- biogeochemical processes in the vadose zone-groundwater system within an agricultural area, contributing to enhanced comprehension and advancement of sustainable management practices for groundwater nitrogen.

Fluoranthene (FLU) has gained much attention in recent years because of its continuous discharge in natural waters and toxicity to aquatic ecosystems. However, it is difficult to control and manage FLU pollution because of the lack of a rational and scientific water quality criteria (WQC) of FLU. To solve these data gaps, the US EPA established an interspecies correlation estimation (ICE) model, which can be utilized to develop the SSD and HC5 (hazardous concentration, 5th percentile). Moreover, an improved model was developed using a combination of North American ICE models supplemented with China-specific species. In this study, to verify the applicability of the two ICE models, measured acute toxicity data for FLU were obtained from 9 acute toxicity tests using indigenous Chinese aquatic species from different taxonomic levels. Original and improved ICE-based SSD curves, which were generated using 3 surrogate species (Daphnia magna, Oncorhynchus mykiss, and Lepomis macrochirus), were compared with SSD curves based on measured data. The results showed that HC5 was 1.838, 1.062, and 0.570 mg/L for the original ICE, improved ICE, and measured data, respectively. The improved ICE-based HC5 value for FLU was within twofold of the HC5 value based on measure data, while the original ICE-based HC5 value was threefold higher than the HC5 value based on measure data. This indicated that the improved ICE had better predictability in extrapolating data with acceptable deviation than the original ICE. Furthermore, their differences between HC5 derived from two SSD curves were not significant. Generally, the improved ICE model was verified as a valid approach for generating SSDs with limited toxicity data and for deriving WQC for FLU.

Groundwater quality in plains and basins of arid and semi-arid regions with increased agriculture and urbanization development faces severe nitrate pollution, which is affected by both climate and anthropogenic activities. Here, shallow groundwater nitrate concentrations in the Yinchuan Region in central Yinchuan Plain were modeled during 2000, 2005, 2010, and 2015 using random forest. Multiple spatial environment factors were taken as predictor variables. The relative importance of these factors was also calculated using the constructed model. Remote sensing and GIS methods were used to compile various environmental factors to generate training and test sets for training and validation of the random forest model. Mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) between the observed and predicted groundwater nitrate concentrations were used to measure the model performance. As indicated by these metrics, the random forest model for groundwater nitrate prediction was performed well. The relative importance of the predictor variables computed by the model indicated groundwater nitrate was mainly affected by the distance to the Yellow River, meteorological elements (precipitation, evaporation, and mean air temperature), and water level elevation. Additionally, urban and arable land were the two land use/land cover types that mainly influenced groundwater nitrate concentration in the Yinchuan Region, of which urban land was more influential than arable land as a result of intense expansion of urban land from 2000 to 2015. Overall, the current study provides an approach to integrate multiple environmental factors for groundwater quality study and is also significant for sustainable groundwater management in the Yinchuan Region.

Water resources are important in large basins which are important places for human habitation and industrial and agricultural development. The background of editing this thematic issue was introduced and the general water resources situation and water quality status in four major large river basins in the Asian and African continents were briefly summarized to give readers general pictures of water resources development and management in these basins, and these large river basins are the Yellow River Basin, the Yangtze River Basin, the Indus Basin, and the Nile Basin. The thematic issue papers were classified into four clustered topical categories, and the main points of the papers in this thematic issue were summarized. Finally, the perspectives of future sustainable water resources development and management in large river basins were proposed.

Microplastics (MPs) in the water environment pose a potential threat to aquatic organisms. The Species Sensitivity Distribution (SSD) method was used to assess the ecological risks of microplastics on aquatic organisms in this study. However, the limited toxicity data of aquatic organisms made it impossible to derive water quality criteria (WQC) for MPs and difficult to implement an accurately ecological risk assessment. To solve the data gaps, the USEPA established the interspecies correlation estimation (ICE) model, which could predict toxicity data to a wider range of aquatic organisms and could also be utilized to develop SSD and HC5 (hazardous concentration, 5th percentile). Herein, we collected the acute toxicity data of 11 aquatic species from 10 families in 5 phyla to fit the metrical-based SSDs, meanwhile generating the ICE-based-SSDs using three surrogate species (Oncorhynchus mykiss, Hyalella Azteca, and Daphnia magna), and finally compared the above SSDs, as well as the corresponding HC5. The results showed that the measured HC5 for acute MPs toxicity data was 112.3 μg/L, and ICE-based HC5 was 167.2 μg/L, which indicated there were no significant differences between HC5 derived from measured acute and ICE-based predicted values thus the ICE model was verified as a valid approach for generating SSDs with limited toxicity data and deriving WQC for MPs.

Irrigation and fertilizer application can lead to significant changes in groundwater quality. In this study, a field irrigation experiment was carried out from April 9 to 23, 2021 under irrigation and fertigation conditions to understand the mechanisms of moisture movement, soil salt migration, and nitrogen transformation in the soil profile. Continuous in-situ monitoring and sampling of soil and irrigation water, as well as stable isotopes, chemical parameters, and soluble salt analyses, were performed in this research. The results showed that the time cost by the irrigation water in the vadose zone was about 5 h. The infiltrated irrigation water was accompanied by high concentrations of soluble salts, leached from the soil layers of 20-80 cm and 100-150 cm, which is associated with the leaching of Na+, Cl-, SO42- , and Ca2+ and the dissolution of minerals such as gypsum and halite. Furthermore, the variations in nitrogen concentrations (NH4+ and NO3- ) in the soil profile suggested that fertilizer application was the main source of NO3- in the soil and groundwater, while irrigation was the biggest driving force for nitrogen transport and transformation in soil. The application of urea fertilizer can increase the content of ammonium nitrogen at the soil layer of 0-80 cm. This nitrogen form can be subsequently transformed to nitrate nitrogen during the water transport to the groundwater. The current study provides a strong scientific basis for the protection and management of groundwater and soil quality in agricultural areas.

Groundwater nitrate (NO3-) pollution is a worldwide environmental problem. Therefore, identification and partitioning of its potential sources are of great importance for effective control of groundwater quality. The current study was carried out to identify the potential sources of groundwater NO3- pollution and determine their apportionment in different land use/land cover (LULC) types in a traditional agricultural area, Weining Plain, in Northwest China. Multiple hydrochemical indices, as well as dual NO3- isotopes (δ15N-NO3 and δ18O-NO3), were used to investigate the groundwater quality and its influencing factors. LULC patterns of the study area were first determined by interpreting remote sensing image data collected from the Sentinel-2 satellite, then the Bayesian stable isotope mixing model (MixSIAR) was used to estimate proportional contributions of the potential sources to groundwater NO3- concentrations. Groundwater quality in the study area was influenced by both natural and anthropogenic factors, with anthropological impact being more important. The results of LULC revealed that the irrigated land is the dominant LULC type in the plain, covering an area of 576.6 km2 (57.18% of the total surface study area of the plain). On the other hand, the results of the NO3- isotopes suggested that manure and sewage (M&S), as well as soil nitrogen (SN), were the major contributors to groundwater NO3-. Moreover, the results obtained from the MixSIAR model showed that the mean proportional contributions of M&S to groundwater NO3- were 55.5, 43.4, 21.4, and 78.7% in the forest, irrigated, paddy, and urban lands, respectively. While SN showed mean proportional contributions of 29.9, 43.4, 61.5, and 12.7% in the forest, irrigated, paddy, and urban lands, respectively. The current study provides valuable information for local authorities to support sustainable groundwater management in the study region.