Dual stable isotopes to rethink the watershed-scale spatiotemporal interaction between surface water and groundwater

The interaction between groundwater and surface water, including their recharge relationship and ratio, is crucial for water cycling, management, and pollution control. However, accurately estimating their spatiotemporal interaction at the watershed scale remains challenging. In this study, we used dual stable isotopes (δ18O, δ2H, d-excess, and lc-excess) and hydrochemistry methods to rethink spatiotemporal interaction at the Yiluo River watershed in central China. We collected 20 groundwater and 40 surface water samples over four periods in two seasons (dry and wet). Our results showed that in the downstream region, groundwater recharged surface water in the dry season while surface water recharged groundwater in the wet season, with average recharge ratios of 89.82% and 90.02%, respectively. In the midstream region, surface water recharged groundwater in both seasons with average ratios of 93.79% and 91.35%. In contrast, in the upstream region, groundwater recharged surface water in both seasons with ratios of 67.35% and 76.89%. Seasonal changes in the recharge relationship between surface water and groundwater in the downstream region also been found. Our findings provide valuable insights for watershed-scale water resource and pollution management.

Combining the multivariate statistics and dual stable isotopes methods for nitrogen source identification in coastal rivers of Hangzhou Bay, China

Coastal rivers contributed the majority of anthropogenic nitrogen (N) loads to coastal waters, often resulting in eutrophication and hypoxia zones. Accurate N source identification is critical for optimizing coastal river N pollution control strategies. Based on a 2-year seasonal record of dual stable isotopes ([Formula: see text] and [Formula: see text]) and water quality parameters, this study combined the dual stable isotope-based MixSIAR model and the absolute principal component score-multiple linear regression (APCS-MLR) model to elucidate N dynamics and sources in two coastal rivers of Hangzhou Bay. Water quality/trophic level indices indicated light-to-moderate eutrophication status for the studied rivers. Spatio-temporal variability of water quality was associated with seasonal agricultural, aquaculture, and domestic activities, as well as the seasonal precipitation pattern. The APCS-MLR model identified soil + domestic wastewater (69.5%) and aquaculture tailwater (22.2%) as the major nitrogen pollution sources. The dual stable isotope-based MixSIAR model identified soil N, aquaculture tailwater, domestic wastewater, and atmospheric deposition N contributions of 35.3 ±21.1%, 29.7 ±17.2%, 27.9 ±14.5%, and 7.2 ±11.4% to riverine [Formula: see text] in the Cao'e River (CER) and 34.4 ±21.3%, 29.5 ±17.2%, 27.4 ±14.7%, and 8.7 ±12.8% in the Jiantang River (JTR), respectively. The APCS-MLR model and the dual stable isotope-based MixSIAR model showed consistent results for riverine N source identification. Combining these two methods for riverine N source identifications effectively distinguished the mix-source components from the APCS-MLR method and alleviated the high cost of stable isotope analysis, thereby providing reliable N source apportionment results with low requirements for water quality sampling and isotope analysis costs. This study highlights the importance of soil N management and aquaculture tailwater treatment in coastal river N pollution control.

Effect of rainfall-runoff process on sources and transformations of nitrate using a combined approach of dual isotopes, hydrochemical and Bayesian model in the Dagang River basin

The control of agricultural nitrogen through inflow rivers is crucial for lake aquatic environment conservation, while nitrate is the main form of non-point source pollution of agricultural nitrogen in watersheds. Therefore, understanding the nitrate sources and transformation in the intensive-agricultural region was particularly concerned. Nitrate sources and transformation varied largely during some crucial periods or events. However, low-resolution sampling campaigns increased some uncertainties due to without considering the effect of key driving factors for identifying nitrate transformations and sources. In our study, high-frequency sampling and analysis of nitrogen and oxygen isotope, hydrochemical and Bayesian model was conducted at the Dagang River to capture nitrate sources and transformations and identify its response to rainfall-runoff process at the event scale. In addition, the N cycle process was refined by comparing the variation and relationship of water quality factors and isotopes before, during, and after rainfall. We found that nitrate and major ions derived from similar agricultural activities caused by anthropogenic factors, such as domestic sewage from rural residents and livestock waste, through field survey and principal component analysis. The δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- in Dagang River ranged from +0.05‰ to +9.94‰ and + 1.49‰ to +11.64‰, respectively. The spatio-temporal variations of nitrate isotopes and hydrochemical compositions of river water suggested that nitrification was the dominant nitrate transformation process although the mixing effect occurred in some periods, especially during, and after the rainfall. The relationship between NO₃^-/Cl^- and Cl^- ratios suggested the occurrence of denitrification in downstream of the river basin after the rainfall. The results of Bayesian model showed that livestock manure and groundwater contributed to the most (66.4 ± 31.9%) nitrate, which indicated the necessity to establish its regulatory policy to avoid the overuse of livestock manure and groundwater in Dagang River. This study benefit for developing concrete and legible management and conservation strategies for decreasing the effect of anthropogenic nitrogen loading on lake eutrophication.

Tracking nitrate sources in agricultural-urban watershed using dual stable isotope and Bayesian mixing model approach: Considering N transformation by Lagrangian sampling

A dual isotopes approach and the Bayesian isotope mixing model were applied to trace nitrogen pollution sources and to quantify their relative contribution to river water quality. We focused on two points to enhance the applicability of the method: 1) Direct measurement on the end-members to distinguish "sewage" and "manure" which used to be grouped in one pollution source as their isotope ranges overlap; 2) The Lagrangian sampling method was applied to consider the transport of nitrogen pollutants in a long river so that any fractionation process can be dealt with in the given Bayesian modeling framework. The results of the analysis confirmed the NO₃^- isotope composition in the river of interest to be within the range of NO₃^- with origins in "NH₄⁺ in fertilizer", "Soil N", and "Manure and sewage" pollution. This suggests that nitrogen pollution is mostly attributed to anthropogenic sources. The δ¹⁸O _NO3 value follows the range +2.5∼+15.0‰, implying that NO₃^- in the river is mainly derived from nitrification, and possible nitrification in groundwater or waterfront other than surface water. The ratio of the concentration of δ¹⁵N _NO3 to that of δ¹⁸O _NO3, and the corresponding regression equation indicates that the denitrification effect in surface water was insignificant during the study period. From the results of the contribution ratio of each source, improving the water quality of the discharge from the sewage treatment plants was proved to be the key factor to reduce nitrogen pollution in the river.

Coupling stable isotopes and water chemistry to assess the role of hydrological and biogeochemical processes on riverine nitrogen sources

Accurate source identification is critical for optimizing water pollution control strategies. Although the dual stable isotope (¹⁵N-NO₃^-/¹⁸O-NO₃^-) approach has been widely applied for differentiating riverine nitrogen (N) sources, the relatively short-term (<1 yr) ¹⁵N-NO₃^-/¹⁸O-NO₃^- records typically used in previous studies often hinders rigorous assessment due to high temporal variability associated with watershed N dynamics. Estimated contributions of legacy N sources in soils and groundwater to riverine N export by modeling approaches in many previous studies also lack validation from complementary information, such as multiple stable isotopes. This study integrated three years of multiple stable isotope (¹⁵N-NO₃^-/¹⁸O-NO₃^- and ²H-H₂O/¹⁸O-H₂O) and hydrochemistry measurements for river water, groundwater and rainfall to elucidate N dynamics and sources in the Yongan watershed (2474 km²) of eastern China. Nonpoint source N pollution dominated and displayed considerable seasonal and spatial variability in N forms and concentrations. Information from δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- indicated that riverine N dynamics were regulated by contributing sources, nitrification and denitrification, as well as hydrological processes. For the three examined catchments and entire watershed, slow subsurface and groundwater flows accounted for >75% of river discharge and were likely the major hydrological pathways for N delivery to the river. Riverine NO₃^- sources varied with dominant land use (p < 0.001), with the highest contributions of groundwater (60%), wastewater (35%), and soil (50%) occurring in agricultural, residential and forest catchments, respectively. For the entire watershed, groundwater (∼50%) and soil N (>30%) were the dominant riverine NO₃^- sources, implying considerable potential for N pollution legacy effects. Results were consistent with observed nitrous oxide dynamics and N sources identified in previous modeling studies. As the first attempt to apply multiple isotope tracers for exploring and quantifying N transformation and transport pathways, this study provides an integrated approach for verifying and understanding the N pollution legacy effects observed in many watersheds worldwide. This study highlights that river N pollution control in many watersheds requires particular attention to groundwater restoration and soil N management in addition to N input control strategies.

Seasonal variation in water uptake patterns of three plant species based on stable isotopes in the semi-arid Loess Plateau

Water is a limiting factor and significant driving force for ecosystem processes in arid and semi-arid areas. Knowledge of plant water uptake pattern is indispensable for understanding soil-plant interactions and species coexistence. The 'Grain for Green' project that started in 1999 in the Loess Plateau of China has led to large scale vegetation change. However, little is known about the water uptake patterns of the main plant species that inhabit in this region. In this study, the seasonal variations in water uptake patterns of three representative plant species, Stipa bungeana, Artemisia gmelinii and Vitex negundo, that are widely distributed in the semi-arid area of the Loess Plateau, were identified by using dual stable isotopes of δ²H and δ¹⁸O in plant and soil water coupled with a Bayesian mixing model MixSIAR. The soil water at the 0-120cm depth contributed 79.54±6.05% and 79.94±8.81% of the total water uptake of S. bungeana and A. gmelinii, respectively, in the growing season. The 0-40cm soil contributed the most water in July (74.20±15.20%), and the largest proportion of water (33.10±15.20%) was derived from 120-300cm soils in August for A. gmelinii. However, V. negundo obtained water predominantly from surface soil horizons (0-40cm) and then switched to deep soil layers (120-300cm) as the season progressed. This suggested that V. negundo has a greater degree of ecological plasticity as it could explore water sources from deeper soils as the water stress increased. This capacity can mainly be attributed to its functionally dimorphic root system. V. negundo may have a competitive advantage when encountering short-term drought. The ecological plasticity of plant water use needs to be considered in plant species selection and ecological management and restoration of the arid and semi-arid ecosystems in the Loess Plateau.

Using stable isotopes to determine seasonal variations in water uptake of summer maize under different fertilization treatments

Fertilization and water both affect root water uptake in the nutrient and water cycle of the Soil-Plant-Atmosphere-Continuum (SPAC). In this study, dual stable isotopes (D and (18)O) were used to determine seasonal variations in water uptake patterns of summer maize under different fertilization treatments in Beijing, China during 2013-2014. The contributions of soil water at different depths to water uptake were quantified by the MixSIAR Bayesian mixing model. Water uptake was mainly sourced from soil water in the 0-20cm depth at the seeding (67.7%), jointing (60.5%), tasseling (47.5%), dough (41.4%), and harvest (43.9%) stages, and the 20-50cm depth at the milk stage (32.8%). Different levels of fertilization application led to considerable differences in the proportional contribution of soil water at 0-20cm (6.0-58.5%) and 20-50cm (6.1-26.3%). There was little difference of contributions in the deep layers (50-200cm) among treatments in 2013, whereas differences were observed in 50-90cm at the milk stage and 50-200cm at the dough stage during 2014. The main water uptake depth was concentrated in the upper soil layers (0-50cm) during the wet season (2013), whereas a seasonal drought in 2014 promoted the contribution of soil water in deep layers. The contribution of soil water was significantly and positively correlated with the proportions of root length (r=0.753, p<0.01). The changes of soil water distribution were consistent with the seasonal variation in water uptake patterns. The present study identified water sources for summer maize under varying fertilization treatments and provided scientific implications for fertilization and irrigation management.