Fish inhabiting similar environments face space and resource constraints, develop diverse feeding strategies, and adjust their trophic niches during ontogeny to reduce competition. To investigate this process, we reconstructed the trophic trajectory of five species of the family Sciaenidae by analyzing δ13C and δ15N values in otolith organic matter along the growth axis of the otolith. We developed

The non-destructive, three-dimensional excitation-emission matrix (3D-EEM) based on fluorescence spectroscopy has been widely used in natural organic matter (NOM) monitoring in aquatic environments. However, the direct recognition of the species and concentration of NOM from 3D-EEM data remains challenging, especially under more complex scenarios such as in NOM mixtures and during ultrafiltration.

Agriculture is a major contributor to water pollution through nutrient runoff and excessive water use, exacerbating global water scarcity and ecosystem degradation. Water Quality Trading (WQT) has emerged as a market-based mechanism to address this issue by enabling cost-effective pollution control. However, this study critically evaluates WQT’s effectiveness, arguing that it often serves as a financial

Land permafrost thaw transfers increasing amounts of organic matter and nutrients to the Arctic Ocean. These nutrients could stimulate primary production directly, or indirectly following remineralization in sediments. Projections of this effect are limited by scarce observations and poor understanding of the underlying controls. Here, we focus on the Kara, Laptev, and East Siberian Sea shelves that

Endocrine disruptors have long half-life and wide distribution in surface water. The combination of ceramic membrane and advanced oxidation process is a high-efficient treatment technology for the removal of endocrine disruptors. Herein, a novel one-step co-sintering method using iron oxide and alumina for the fabrication of catalytic ceramic membranes was developed. The iron oxide facilitated the

Iron redox cycling governs the early diagenesis of organic matter (OM) and significantly influences phosphorus (P) dynamics in aquatic systems. The release of endogenous P during freezing periods carries significant ecological implications for these systems. However, it remains unclear whether microbial dissimilatory iron reduction maintains a dominant role under anoxic freezing conditions, and the

General Circulation Models (GCMs) can be considered the most accurate numerical models for simulating climate variables across past and future scenarios. The reliability of GCMs projections can vary markedly across different geographical regions but, despite the importance of selecting the most suitable GCM for a specific study area, there has been limited exploration into identifying the optimal model

Vegetation and associated ecosystem functions are critically dependent on soil moisture availability. As soil moisture declines below critical thresholds, vegetation may undergo regime shifts from energy to water limitation, and ultimately to systemic breakdown (i.e., vegetation no longer survives). However, the patterns, drivers, and trends of such full regime shifts remain unclear. In this study

Non-point source (NPS) pollution from stormwater runoff has become a major threat to urban water bodies. Rapid and reliable pollution profiling is essential for effective mitigation, yet early-stage stormwater management often lacks detailed drainage data and long-term monitoring, complicating model selection. This study evaluates the performance and practical utility of three widely used NPS modeling

Urban drainage systems (UDSs) are vital for managing stormwater and wastewater but face growing challenges due to urbanization, climate change and aging infrastructure. Real-time control (RTC) enhances UDSs’ performance and circumvents the need for system upgrades through adaptive management and repurposing existing systems. Meanwhile, deep reinforcement learning (DRL) has emerged as a promising tool

Ensuring water supply reliability as well as improving the quality of water environment is a challenging task, especially in cities with water shortage. Non-stationarity and variability in streamflow and water demand compound this challenge. This study first develops Non-stationary Transformer models to explore the stationarity in streamflow forecasting and, uncertainties of both water availability

Riverbed clogging by suspended sediments in turbid rivers can significantly alter the infiltration process. However, since it is difficult to quantitatively monitor the clogging process, the mechanism of riverbed infiltration-clogging is not yet clear. This study conducted a series of column experiments on intermittent riverbeds to simulate the infiltration-clogging process under different riverbed

Characterized by diverging and merging pathways, meandering-anabranching channels are prevalent in natural rivers. They usually have a significant impact on local bed topography, flow structure and sediment transport, thus influencing river segment stability. Despite their significance, the influence of emergent vegetation on the bed surface texture of these channels has not been adequately investigated

Forest transpiration (T) exhibits significant temporal and spatial patterns. A deeper understanding of this variability is necessary to more accurately predict future climate-carbon–water cycle feedbacks. Variations in T are driven by a wide range of biological and abiotic factors, primarily through changes in vegetation phenology and physiological processes. However, it is unclear that how plant phenology