Appropriate stoichiometric ratios of dissolved organic carbon and nitrate can trigger a transition in nitrate removal in groundwater around plateau lakes, Southwest China.

Increasing dissolved organic carbon (DOC) in groundwater as a carbon source for microorganisms that stimulate nitrate attenuation is considered a sustainable strategy to mitigate nitrate pollution in groundwater. However, little is known on the stoichiometric ratio of DOC and nitrate required in groundwater nitrate reduction processes, which has become an obstacle for evaluating the current status of DOC limitations on nitrate reduction. Here, the NO3--N and DOC concentrations in groundwater around 8 plateau lakes were investigated, and a microcosm experiment was performed to elucidate the effects of different DOC:NO3--N levels in groundwater on NO3--N reduction, and the current status of DOC limitations on groundwater NO3--N reduction around 8 lakes was further evaluated. The results indicated that nearly 41 % of the groundwater NO3--N concentrations exceeded the WHO threshold for drinking water (11.3 mg L-1) and 79 % of the groundwater DOC concentrations exceeded 5 mg L-1. The differences in groundwater NO3--N and DOC concentrations among the 8 lakes were controlled by the intensity of agricultural and human activities and hydrogeological background. The stoichiometric ratio of DOC:NO3--N regulated the NO3--N reduction process, and groundwater NO3--N accumulation rate appeared to become limited and sharply decreased when the DOC concentration was approximately 10 mg L-1 or when the DOC:NO3--N ratio was close to 1:1, and the DOC:NO3--N ratio threshold for limiting the NO3--N reduction process was approximately 2.25. Based on this threshold, >33 %-86 % of the groundwater samples around the 8 plateau lakes were strongly limited in the reduction of groundwater NO3--N due to a lack of sufficient DOC provides energy for heterotrophic microorganisms. Additionally, we highlight that the sustainable strategy of increasing DOC to stimulate groundwater NO3- attenuation should be combined with short-term strategies to jointly coordinate and control groundwater NO3- pollution.

[Identification of Nitrate Source and Transformation Process in Shallow Groundwater Around Dianchi Lake].

Elucidating the main sources and transformation process of nitrate for the prevention and control of groundwater nitrogen pollution and the development and utilization of groundwater resources has great significance. To explore the current situation and source of nitrate pollution in shallow groundwater around the Dianchi Lake, 73 shallow groundwater samples were collected in the rainy season in 2020(October) and dry season in 2021(April). Using the hydrochemistry and nitrogen and oxygen isotopes(δ15N-NO3- and δ18O-NO3-), the spatial distribution, source, and transformation process of nitrate in shallow groundwater were identified. The contribution of nitrogen from different sources to nitrate in shallow groundwater was quantitatively evaluated using the isotope mixing model(SIAR). The results showed that in nearly 40.5% of sampling points in the shallow groundwater in the dry season, ρ(NO3--N) exceeded the 20 mg·L-1 specified in the Class Ⅲ water quality standard for groundwater(GB/T 14848), and in more than 47.2% of sampling points in the rainy season, ρ (NO3--N) exceeded 20 mg·L-1. The analysis results of nitrogen and oxygen isotopes and SIAR model showed that soil organic nitrogen, chemical fertilizer nitrogen, and manure and sewage nitrogen were the main sources of nitrate in shallow groundwater; these nitrogen sources contributed 13.9%, 11.8%, and 66.5% to nitrate in shallow groundwater in the dry season and 33.7%, 31.1%, and 25.9% in the rainy season, respectively. However, the contribution rate of atmospheric nitrogen deposition was only 8.5%, which contributed little to the source of nitrate in shallow groundwater in the study area. Nitrification was the leading process of nitrate transformation in shallow groundwater in the dry season, denitrification was the dominant process in the rainy season, and denitrification was more noticeable in the rainy season than that in the dry season.

Prediction of phosphorus concentrations in shallow groundwater in intensive agricultural regions based on machine learning.

Excessive accumulation of phosphorus in soil profiles has become the main source of phosphorus in groundwater due to the application of phosphorus fertilizers in intensive agricultural regions (IARs). Elevated phosphorus concentrations in groundwater have become a global phenomenon, which places enormous pressure on the safe use of water resources and the safety of the aquatic environment. Currently, the prediction of pollutant concentrations in groundwater mainly focuses on nitrate nitrogen, while research on phosphorus prediction is limited. Taking the IARs approximately 8 plateau lakes in the Yunnan-Guizhou Plateau as an example, 570 shallow groundwater samples and 28 predictor variables were collected and measured, and a machine learning approach was used to predict phosphorus concentrations in groundwater. The performance of three machine learning algorithms and different sets of variables for predicting phosphorus concentrations in shallow groundwater was evaluated. The results showed that after all variables were introduced into the model, the R2, RMSE and MAE of support vector machine (SVM), random forest (RF) and neural network (NN) were 0.52-0.60, 0.101-0.108 and 0.074-0.081, respectively. Among them, the SVM model had the best prediction effect. The clay content and water-soluble phosphorus in soil and soluble organic carbon in groundwater had a high contribution to the prediction accuracy of the model. The prediction accuracy of the model with reduced number of variables showed that when the number of variables was equal to 6, the RF model had R2, RMSE and MAE values of 0.53, 0.108 and 0.074, respectively, and the number of variables increased again; there were small changes in R2, RMSE and MAE. Compared with the SVM and NN models, the RF model can achieve higher accuracy by inputting fewer variables.

[Shallow Groundwater Around Plateau Lakes: Spatiotemporal Distribution of Phosphorus and Its Driving Factors].

The extensive application of phosphorus fertilizers to croplands and the aggregation of towns and villages around plateau lakes has resulted in the continuous accumulation of phosphorus in the soil profile and the discharge of phosphorus pollutants, which causes phosphorus pollution in shallow groundwater around the lakes. The phosphorus entering the lake with shallow underground runoff in the region around the lake also affects the water quality safety of plateau lakes. The spatiotemporal differences in phosphorus concentrations in 452 shallow groundwater samples and the driving factors were analyzed by monitoring wells in croplands and residential areas around the eight lakes in Yunnan province during the rainy and dry seasons from 2019 to 2021. The results showed that seasonal changes and land use influenced phosphorus concentrations and their composition in shallow groundwater. The concentration of phosphorus in shallow groundwater in the rainy season was higher than that in the dry season, and it was also greater in cropland than that in residential areas. DTP was the dominant form of TP, accounting for 75%-81%, and DIP was the dominant form of DTP, accounting for 74%-80%. Nearly 30% of the samples around the eight lakes had TP concentrations exceeding the surface water Class Ⅲ standard (GB 3838); the exceeded rates of phosphorus in groundwater around the Erhai Lake (52%), Qiluhu Lake (45%), Xingyun Lake (42%), and Dianchi Lake (29%) were far higher than those of Yangzonghai Lake (16%), Fuxianhu Lake (13%), Chenghai Lake (6%), and Yilonghu Lake (5%). The key driving factors of phosphorus concentrations in shallow groundwater were water-soluble phosphorus (WEP), water content (MWC), soil organic matter (SOM), total nitrogen (TN), pH in the soil profile, and pH and groundwater level in the shallow groundwater (P<0.05). The increases in WEP, SOM, TN, and MWC in the soil and pH in groundwater significantly increased the concentrations of DIP and DTP in shallow groundwater, whereas the decrease in groundwater level significantly reduced the concentrations of DTP and DIP in the groundwater.

[Shallow Groundwater Around Plateau Lakes: Spatiotemporal Distribution of Nitrogen and Its Driving Factors].

Shallow groundwater around plateau lakes is one of the important sources of production and potable water. Shallow groundwater NO3--N pollution driven by factors such as surface nitrogen input load, rainfall, and irrigation is serious and threatens the water quality of plateau lakes. In order to identify the characteristics of nitrogen pollution and its driving factors in shallow groundwater, 463 shallow groundwater samples were collected from wells in farmland and residential areas around eight plateau lakes of Yunnan in the rainy and dry seasons in 2020 and 2021. The results showed that the average values of ρ(TN), ρ(NO3--N), ρ(ON), and ρ(NH4+-N) in shallow groundwater were 24.35, 15.15, 8.41, and 0.79 mg·L-1, respectively. Nearly 32% of the shallow groundwater samples around the eight lakes failed to meet the groundwater Class Ⅲ water quality requirements (GB/T 14848) of 20 mg·L-1 for NO3--N. Among them, the NO3--N concentration in the shallow groundwater around Erhai Lake, Qiluhu Lake, and Dianchi Lake had the highest rate of exceeding the standard, followed by that around Xingyunhu Lake, Yangzonghai Lake, Yilonghu Lake, Fuxianhu Lake, and Chenghai Lake as the smallest. Land use and seasonal changes affected the concentration and composition of various forms of nitrogen in shallow groundwater. The concentration of various forms of nitrogen in shallow groundwater in the farmland area was higher than that in the residential area. The nitrogen concentration in shallow groundwater in farmland was higher than that in residential areas. Except for NH4+-N, the concentration of various forms of nitrogen in shallow groundwater in the rainy season was higher than that in the dry season. NO3--N was the main nitrogen form in shallow groundwater; the fraction of TN was 57%-68%, and the fraction of ON was 27%-38%. The EC, DO, ORP, and T in shallow groundwater were the key factors reflecting or affecting the concentration of various forms of nitrogen in shallow groundwater, whereas soil factors had a weak impact on the concentration of various forms of nitrogen in shallow groundwater.

Shallow groundwater fluctuation: An ignored soil N loss pathway from cropland.

Nitrogen (N) pollution originating from agricultural land is among the major threats to shallow groundwater (SG). Soil N losses due to the SG table fluctuation are neglected, although a large number of studies have been conducted to evaluate N losses through leaching and runoff. Herein, the characteristics of N losses driven by SG table fluctuation were investigated using the microcosm experiment and surveyed data from the croplands around Erhai Lake. According to the results achieved, the total N (TN) loss mainly occurred during the initial 12 days when the soil was flooded, then presented N immobilized by soil and finally, basically balanced between influent and effluent after 50 days. The results demonstrated that 1.7% of the original soil TN storage (0-100 cm) was lost. The alternation of drying and flooding could greatly increase TN loss up to 1086 kg hm-2, which was 2.72 times as much as that of continuous flooding flow. The amount of soil N losses to groundwater was closely related to the soil profile biochemical characteristics (water content, soil microbial immobilization, mineralization, nitrification, and denitrification processes). Soil N loss from crop fields driven by SG table fluctuation is 26 and 6 times of the runoff and leaching losses, respectively, while the soil N loss from the vegetable fields is 33 and 4 times of the runoff and leaching losses. The total amount of N losses from the croplands around the Erhai Lake caused by flooding of shallow groundwater (SG) in 2016 was estimated at 3506 Mg. The estimations showed that N losses would decrease by 16% if vegetables are replaced with staple food crops. These results imply that the adjustment of the planting structure was the key measure to reduce soil N storage and mitigate groundwater contamination.

Electrical conductivity and dissolved oxygen as predictors of nitrate concentrations in shallow groundwater in Erhai Lake region.

Elevated nitrogen (N) concentration in shallow groundwater is becoming increasingly problematic, putting water resources under pressure. For more effective management of such a resource, more precise predictors of N level in groundwater using smart monitoring networks are needed. However, external factors such as land use type, rainfall, and N loads from multiple sources (residential and agricultural) make it difficult to accurately predict the spatial and temporal variations of N concentration. In order to identify the key factors affecting spatial and temporal N concentration in shallow groundwater and develop a predictive model, 635 groundwater samples from drinking wells in residential areas and agricultural wells in croplands of a typical agricultural watershed in the Erhai Lake Basin, southwest China, in the period from 2018 to 2020, were collected and analyzed. The results showed that the type of land use and seasonal variations significantly affected the N forms and their concentrations in the shallow groundwater, as the ratios of ON and NO3--N to TN were 30%-39% and 52%-59% for the two land uses and 25%-44% and 46%-66% for seasonal changes. Their variations were reflected by electrical conductivity (EC) and redox environment. EC and dissolved oxygen (DO) had a positive non-linear relationship with the concentrations of total nitrogen (TN) and nitrate (NO3--N). The fitted non-linear quantitative models were established separately to predict TN and NO3--N concentrations in groundwater using easily available indictors (EC and DO). The high accuracy and performance of the models were investigated and approved by rRMSE, MAE, and 1:1 line. These findings can provide technical support for the rapid prediction and evaluation of N pollution in shallow groundwater through easily available indicators.

Shift of lakeshore cropland to buffer zones greatly reduced nitrogen loss from the soil profile caused by the interaction of lake water and shallow groundwater.

The interaction of lake water (LW) and shallow groundwater (SGW) accelerates nitrogen (N) loss from the soil profile in the lakeshore cropland, and cropland buffer zone (CBZ) significantly inhibits N loss in this area. Here, characteristics of N loss and transformations driven by SGW and LW interactions were explored using microcosmic experiments, and N loss was estimated using in situ monitoring data before and after the construction of the CBZ along the west bank of Erhai Lake. The results indicated that NO3--N, dissolved organic N and total dissolved N sustained the main N losses in the soil, and the organic N was responsible for the main N loss in the effluent. The lower total nitrogen (TN) concentrations of SGW in this area, the greater the soil N loss. Moreover, N total loss from the 100 cm soil profile in the control check was 1.8 times that in the simulated SGW treatment. We found that nitrification, denitrification and anammox driven by the microbial community and N functional genes were the key processes leading to N loss. The effluent N (3.64%) and gaseous N (0.32%) loss ratios in the cropland for continuously growing vegetables (CGV) were much higher than that in the CBZ (1.07% of effluent N and 0.25% of gaseous N loss ratios). If a 100 m wide and 48 km long area of lakeshore cropland is CGV, an increase by 47% is projected by 2030 compared with the N loss in 2020. But this region was built as a 100 m wide CBZ or 50 m wide CBZ + 50 m wide CGV after 2019, N loss will be reduced by 87% and 44% in 2030 compared with the N loss in CGV. The results implied that restoring a suitable width of CBZ can significantly reduce N loss.

Identification of the sources and fate of NO3--N in shallow groundwater around a plateau lake in southwest China using NO3- isotopes (δ15N and δ18O) and a Bayesian model.

Pollution by NO3--N seriously threatens the quality of shallow groundwater (SG) around Erhai Lake, which is the 2nd largest source of freshwater in the plateau area in southwest China; further, NO3--N affects the lake water quality and human health. We collected SG samples during the dry and wet seasons in 2018 and 2019, and the potential NO3--N sources and their fates were identified in SG by NO3- isotopes and hydrochemical methods. Our results showed that the NO3--N concentrations in the SG in the wet season in farmland were far higher than those in the dry season in residential areas. The high variation in δ15N-NO3- and δ18O-NO3- (from -12.78‰ to +18.10‰ and -27.62‰ to +23.07‰, respectively, in the farmland and from -5.34‰ to +34.54‰ and -20.04‰ to +17.47‰, respectively, in the residential area) indicated multiple NO3--N sources in the SG. The NO3--N in the farmland mainly originated from chemical nitrogen fertilizer (NF, 36%), soil nitrogen (SN, 33%) and manure and sewage (M&S, 24%) in the dry season and from SN (61%) and NF (33%) in the wet season. The NO3--N in the residential area mainly originated from M&S (57%), SN (23%) and NF (14%) in the dry season and from SN (50%), NF (25%) and M&S (24%) in the wet season. Nitrogen transformation was dominated by denitrification in the SG. The most polluted SG area was observed on the east bank of Erhai Lake, NO3--N mainly originated from NF. But the NO3--N pollution slowed down from high altitude to lakeside and had multiple NO3--N sources on the west bank of Erhai Lake. The SG was contaminated by nitrogen from NF, SN and M&S along the flow path and flowed into Erhai Lake. Therefore, reducing soil nitrogen concentrations and chemical nitrogen fertilizer applications and improving sewage facilities are significant ways to mitigate nitrate pollution in the SG.