An integrated watershed-scale framework to model nitrogen transport and transformations

Unveiling Microbial Nitrogen Metabolism in Rivers using a Machine Learning Approach

Microbial nitrogen metabolism is a complicated and key process in mediating environmental pollution and greenhouse gas emissions in rivers. However, the interactive drivers of microbial nitrogen metabolism in rivers have not been identified. Here, we analyze the microbial nitrogen metabolism patterns in 105 rivers in China driven by 26 environmental and socioeconomic factors using an interpretable causal machine learning (ICML) framework. ICML better recognizes the complex relationships between factors and microbial nitrogen metabolism than traditional linear regression models. Furthermore, tipping points and concentration windows were proposed to precisely regulate microbial nitrogen metabolism. For example, concentrations of dissolved organic carbon (DOC) below tipping points of 6.2 and 4.2 mg/L easily reduce bacterial denitrification and nitrification, respectively. The concentration windows for NO3--N (15.9-18.0 mg/L) and DOC (9.1-10.8 mg/L) enabled the highest abundance of denitrifying bacteria on a national scale. The integration of ICML models and field data clarifies the important drivers of microbial nitrogen metabolism, supporting the precise regulation of nitrogen pollution and river ecological management.

Assessing transport timescales in Lake Huron's Hammond Bay: The crucial role of the Straits of Mackinac's exchange flows

The oscillating bidirectional exchange flows between Lakes Michigan and Huron in the Straits of Mackinac generate complex hydrodynamics and the exchange flows are known to alter hydrodynamics in regions as far down as 50-60 km from the Straits modulating physical, chemical, and biological processes in the region. Although previous research examined the effects of exchange flows on hydrodynamics, their impacts on transport time scales, including residence and flushing times, have not been quantified. We used observations and a three-dimensional hydrodynamic model to simulate bidirectional exchange flows in the Straits and their effects on hydrodynamics, temperature, and transport timescales in the Hammond Bay area, Lake Huron for the summers of 2018 and 2019. Comparisons with field observations showed that hydrodynamics can only be accurately described when the bidirectional flows are included in the modeling of the bays close to the Straits. Spectral analysis showed that the exchange flows play an important role in controlling conservative solute transport in bays close to the Straits. The residence time in the Hammond Bay area was calculated using a dye release approach with (without) the effects of bidirectional exchange flows producing estimates of 9.87 (16.00) and 13.75 (23.62) days for years 2018 and 2019 respectively based on a combined model of the two lakes and a model of Lake Huron only. Similarly, flushing times in the Hammond Bay area were estimated as 12.14 (14.38) and 8.96 (10.80) days for 2018 and 2019, respectively with (without) the exchange flows. Ignoring the exchange flows in the Straits was found to overestimate the residence time and flushing time in the Hammond Bay area by roughly 74 and 20 %, respectively. These results highlight the importance of including the bidirectional exchange flows in biophysical models of bays in Lake Huron closer to the Straits and in similar systems elsewhere.

Implications on freshwater lake-river ecosystem protection suggested by organic micropollutant (OMP) priority list

Lake-river complex systems represent interconnected ecosystems wherein inflow rivers significantly influence the migration of terrigenous contaminants, particularly organic micropollutants (OMPs), into lakes. Given the extensive array of OMPs, screening for those with the highest potential hazard is crucial for safeguarding freshwater lake-river ecosystems. In this study, an optimized multi-criteria scoring method was applied to prioritize OMPs. Flux estimation was then performed to identify the contamination load contributed by the Le'an River to Poyang Lake. Higher concentrations of phthalate esters (PAEs) were detected in the lake-river system, ranging from 1154.5 to 22,732.8 ng/L, followed by antibiotics and polycyclic aromatic hydrocarbons (PAHs), while historical pollutant residues were comparably lower. Based on the prioritization methodology, 27 compounds, encompassing eight PAEs, six organochlorine pesticides (OCPs), six polychlorinated biphenyls (PCBs), five PAHs and two antibiotics, emerged as priority pollutants. Multiple risk assessments revealed that priority PAEs posed relatively high ecological and human health risks; concurrently, the annual fluxes of individual priority PAEs into the lake all exceeded 1000 kg, with DBP, DEHP and BBP fluxes reaching 18,352, 10,429, and 7825 kg, respectively. This research offers valuable insights stemming from OMP prioritization to aid in the conservation of freshwater lake ecosystems, particularly concerning lake-river system integrity.