Storm event impacts on in-stream nitrate concentration and discharge dynamics: A comparison of high resolution in-situ measured data with model simulations

Impact of typhoons on anthropogenic nitrogen sources in Lake Sihwa, South Korea

This study investigated the nitrate dual isotopic compositions (δ15NNO3 and δ18ONO3) of water samples to trace nitrate sources in Lake Sihwa, which encompasses various land-use types (e.g., urban, industry, wetland, and agriculture). The biogeochemical interactions of anthropogenic nitrogen sources (e.g., soil, road dust, and septic water) were also evaluated through multiple pathways from terrestrial boundaries to the water column. Based on increased concentrations of dissolved total nitrogen (DTN; 3.1 ± 1.6 mg/L) after typhoon, the variation of element stoichiometry (N:P:Si) in this system shifted to the relatively N-rich conditions (DIN/DIP; 14.1 ± 8.1, DIN/DSi; 1.4 ± 1.8), potentially triggering the occurrence of harmful algal blooms. Furthermore, discriminative isotopic compositions (δ15NNO3; 4.0 ± 2.1 ‰, δ18ONO3; 6.1 ± 4.3 ‰) after the typhoon suggested the increased DTN input of anthropogenic origins within Lake Sihwa would be mainly transported from urban sources (76 ± 9 %). Consequently, the isotopic-based approach may be useful for effective water quality management under increased anthropogenic activities near aquatic systems.

The effects of heavy rain on the fate of urban and agricultural pollutants in the riverside area around weirs using multi-isotope, microbial data and numerical simulation

The increase in extreme heavy rain due to climate change is a critical factor in the fate of urban and agricultural pollutants in aquatic system. Nutrients, including NO3- and PO43-, are transported with surface and seepage waters into rivers, lakes and aquifers and can eventually lead to algal blooms. δ15N-NO3-, δ18O-NO3-, and δ11B combined with hydrogeochemical and microbial data for groundwater and surface water samples were interpreted to evaluate the fate of nutrients in a riverside area around weirs in Daegu, South Korea. Most of the ions showed similar concentrations in the groundwater samples before and after heavy rain while concentrations of major ions in surface water samples were diluted after heavy rain. However, Si, PO43-, Zn, Ce, La, Pb, Cu and a number of waterborne pathogens increased in surface water after heavy rain. The interpretation of δ11B, δ15N-NO3-, and δ18O-NO3- values using a Bayesian mixing model revealed that sewage and synthetic fertilizers were the main sources of contaminants in the groundwater and surface water samples. δ18O and SiO2 interpreted using the Bayesian mixing model indicated that the groundwater component in the surface water increased from 4.4 % to 17.9 % during the wet season. This is consistent with numerical simulation results indicating that the direct surface runoff and the groundwater baseflow contributions to the river system had also increased 6.4 times during the wet season. The increase in proteobacteria and decrease of actinobacteria in the surface water samples after heavy rain were also consistent with an increase of surface runoff and an increased groundwater component in the surface water. This study suggests that source apportionment based on chemical and multi-isotope data combined with numerical modeling approaches can be useful for identifying main hydrological and geochemical processes in riverside areas around weirs and can inform suggestions of effective methods for water quality management.

Advances in Catchment Science, Hydrochemistry, and Aquatic Ecology Enabled by High-Frequency Water Quality Measurements

High-frequency water quality measurements in streams and rivers have expanded in scope and sophistication during the last two decades. Existing technology allows in situ automated measurements of water quality constituents, including both solutes and particulates, at unprecedented frequencies from seconds to subdaily sampling intervals. This detailed chemical information can be combined with measurements of hydrological and biogeochemical processes, bringing new insights into the sources, transport pathways, and transformation processes of solutes and particulates in complex catchments and along the aquatic continuum. Here, we summarize established and emerging high-frequency water quality technologies, outline key high-frequency hydrochemical data sets, and review scientific advances in key focus areas enabled by the rapid development of high-frequency water quality measurements in streams and rivers. Finally, we discuss future directions and challenges for using high-frequency water quality measurements to bridge scientific and management gaps by promoting a holistic understanding of freshwater systems and catchment status, health, and function.

Distinguishing and quantifying the fate of nitrate in irrigation water and nitrate produced by ammonium nitrification

When the sources of nitrogen include not only ammonium (NH₄⁺) fertilizer (ANF) but also nitrate (NO₃^-) from groundwater and rainfall (NRI), if the proportions of various types of NO₃^- are still based on the amount of ANF, the corresponding calculation method may be complicated. This paper established a water flow-nitrogen migration transformation model for the unsaturated zone in grain-planting and vegetable-planting areas, and studied the migration and transformation of NH₄⁺ and NO₃^- in the unsaturated zone when ANF and NRI coexist. This paper proposed for the first time the proportional coefficient method (PCM) and hypothetical assignment method (HAM) to distinguish and quantify the fate proportions of NO₃^- from NO₃^- produced by NH₄⁺ nitrification (NNR) and NRI. The results showed that the PCM was more practical than the HAM in quantifying the fate of NO₃^- from different sources. If only the root absorption ratio was used to evaluate the degree of nutrient supply to crops, the ratios of root absorption were as high as 40% (44.75-50.85%). NRI provided more nutrients in grain-growing areas than those in vegetable-growing areas. If the sum of the proportion of other fates was regarded as the degree of groundwater NO₃^- mitigation through irrigation in the unsaturated zone, except for the ratio of NO₃^- leaching to groundwater, the proportion of NO₃^- pollution mitigation was as high as 57.89% (57.89-92.99%), and the mitigation ability of groundwater NO₃^- pollution in grain-growing areas was higher than that in vegetable-growing areas.

Total and dissolved phosphorus losses from agricultural headwater streams during extreme runoff events

Eutrophication continues to be a concerning global water quality issue. Managing and mitigating harmful algal blooms demands clear information on the conditions promoting large phosphorus losses from contributing watersheds. Of particular concern is the amount and form of phosphorus loading to receiving water bodies during extreme runoff events, which are expected to increase in frequency due to climate change. Five years (2015 to 2020) of water quantity and quality data from 11 agricultural watersheds in the lower Great Lakes basin were analyzed and used to model total and dissolved phosphorus losses. This study aimed to assess temporal dynamics in phosphorus concentrations and losses over runoff events covering a wide range of hydrologic conditions and to quantify their relative importance on annual phosphorus losses. Event concentration-discharge relationships for total and dissolved phosphorus were hysteretic and had contrasting dominant patterns across watersheds. The proportion of annual phosphorus losses during events was highly variable between watersheds, accounting for 47-94 %. Extreme events were particularly impactful: as few as three events per year were found to be responsible for nearly half of total phosphorus (20-50 %) and total dissolved phosphorus (14-44 %) losses. Variability in total and dissolved phosphorus losses and concentrations over a wide range of flow conditions suggests that event magnitude is an important control on the relative mobility of particulate and dissolved phosphorus fractions. This study showed that insights into nutrient dynamics and phosphorus budgets in the lower Great Lakes basin and agriculture dominated environments more broadly can be gained by assessing event nutrient losses with respect to flow conditions and patterns in concentration-discharge relationships.

Identification of rainy season nitrogen export controls in a semi-arid mountainous watershed, North China

A comprehensive understanding of the nutrient export process and export controls is demanded effective pollution mitigation in fragile riverine ecosystems. In this study, behaviors of the full range of nitrogen (N) under stormflow (5-events) and baseflow (2-events; before and after the rainy season, multiple sites) were assessed to explore N export controlling mechanisms according to the identified main components causing the changes in N exports, N transport pathways, seasonal trends, and nutrient supply watershed regions through the 2020 rainy season in a semi-arid mountainous watershed, northern China. Results showed increments in riverine dissolved organic-N (DON) and particulate-N (PN) loadings as the leading cause of N flux and composition changes through the rainy season, although nitrate-N (NO₃-N) contributed 69.6% of total-N (TN). Storm runoff generated 3-fold and 4-fold average increments in DON and PN fluxes. DON and PN shared 1-66% (18.1%) and 1-44% (9.7%) of TN through storms, registered consistency in behavior, mainly originated from near-stream soil, and were primarily transported by shallower subsurface flow. Our results broaden the understanding of PN delivery in catchment wetting-up periods by highlighting the decoupling of primary origins/transport pathways of PN from sediments. Results suggested hydrological functioning parallel to the catchment wetting-up as the principal governor of storm N evolution; soil moisture levels build up in the early rainy season, soil water runoff dominance during peak discharge fluctuations, groundwater runoff dominance at the end of the rainy season. Cumulative rainfall and antecedent soil moisture exerted more significant control over storm N exports than individual rainfall features. The assessment of N behaviors through river network disclosed watershed regions responsible for excessive N delivery and influences of unsustainable agriculture, sewage treatment work, and damming on natural riverine N fluxes. These findings could be useful references for the formulation of water pollution control strategies in the future.

Novel predictors related to hysteresis and baseflow improve predictions of watershed nutrient loads: An example from Ontario's lower Great Lakes basin

Eutrophication has re-emerged in the lower Great Lakes basin resulting in critical water quality issues. Models that accurately predict nutrient loading from streams are needed to inform appropriate nutrient management decisions. Generalized additive models (GAMs) that use surrogate data from sensors to predict nutrient loads offer an alternative to commonly applied linear regression and may better handle relationship non-linearities and skewed water quality data. Five years (2015-2020) of water quantity and quality data from 11 agricultural watersheds in southern Ontario were used to develop GAMs to predict total phosphorus (TP) and nitrate (NO₃^-) loads. This study aimed to 1) use GAMs to predict nutrient loads using both common and novel predictors and 2) quantify and examine the variability in seasonal and annual nutrient loads. Along with routine surrogate model predictors (i.e., flow, turbidity, and seasonality), the addition of the baseflow proportion and the hydrograph position of flow observations improved model performance. Conversely, including the antecedent precipitation index minimally affected model performance, regardless of constituent. Seasonal and annual patterns in TP and NO₃^- load predictions mirrored that of the hydrologic regime. This study showed that parsimonious GAMs featuring novel model predictors can be used to predict nutrient loads while accounting for the partitioning of surface and subsurface flow paths and hysteresis between streamflow and water quality parameters that are frequently observed in a wide range of environments.

Detection of hidden model errors by combining single and multi-criteria calibration

Environmental models aim to reproduce landscape processes with mathematical equations. Observations are used for validation. The performance and uncertainties are quantified either by single or multi-criteria model assessment. In a case-study, we combine both approaches. We use a coupled hydro-biogeochemistry landscape-scale model to simulate 14 target values on discharge, stream nitrate as well as soil moisture, soil temperature and trace gas emissions (N₂O, CO₂) from different land uses. We reveal typical mistakes that happen during both, single and multi-criteria model assessment. Such as overestimated uncertainty in multi-criteria and ignored wrong model processes in single-criterion calibration. These mistakes can mislead the development of water quality and in general all environmental models. Only the combination of both approaches reveals the five types of posterior probability distributions for model parameters. Each type allocates a specific type of error. We identify and locate mismatched parameter values, obsolete parameters, flawed model structures and wrong process representations. The presented method can guide model users and developers to the so far hidden errors in their models. We emphasize to include observations from physical, chemical, biological and ecological processes in the model assessment, rather than the typical discipline specific assessments.