Water Research X最新文献_第3页

Comparing different Physics-Informed Neural Network models for chlorine modeling in EPANET under varying initial and boundary conditions 比较不同初始和边界条件下EPANET中氯建模的不同物理信息神经网络模型

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2025.100471

Shimon Komarovsky , Raghad Shamaly , Gopinathan R. Abhijith , Andrea Cominola , Avi Ostfeld

Accurate water quality modeling in water distribution systems (WDS) is essential for ensuring safe and reliable drinking water. While numerical solvers such as EPANET provide robust simulations, their computational cost increases substantially for real-time or large-scale applications, particularly when boundary and initial conditions vary over time. Existing Physics-Informed Neural Network (PINN) approaches face limitations in handling such changing conditions, despite their prevalence in real WDS operations. This study focuses on enhancing the adaptability of PINNs for chlorine modeling under diverse and dynamic scenarios. The proposed framework embeds the governing Advection–Reaction (AR) equation into a deep learning architecture and introduces targeted modifications to the formulation of boundary and initial condition losses. Training data are generated using EPANET simulations, and the framework is evaluated under multiple scenarios, including constant and time-varying velocities as well as fixed and dynamic boundary and initial conditions. Results demonstrate that a PINN model explicitly designed for boundary-condition adaptability can accurately reproduce EPANET water quality simulations while reducing computational demands. Key factors influencing performance, such as proper PDE specification, loss balancing, and data preprocessing, are identified. Although the analysis is conducted on a single-pipe testbed to isolate these effects, the findings establish an essential foundation for extending adaptive PINNs to full WDS networks. The primary contribution of this work is the development and demonstration of a PINN architecture capable of reliably adapting to varying boundary and initial conditions, addressing a critical gap in current PINN-based water quality modeling research.

准确的配水系统水质建模是保证饮用水安全可靠的关键。虽然数值求解器如EPANET提供了强大的模拟，但它们的计算成本在实时或大规模应用中大幅增加，特别是当边界和初始条件随时间变化时。现有的物理信息神经网络（PINN）方法在处理这种变化的条件时面临局限性，尽管它们在实际的WDS操作中很普遍。本研究的重点是增强pinn在多种动态场景下对氯模拟的适应性。所提出的框架将控制平流反应（AR）方程嵌入到深度学习架构中，并对边界和初始条件损失的公式进行了有针对性的修改。使用EPANET模拟生成训练数据，并在多种场景下对框架进行评估，包括恒定和时变速度以及固定和动态边界和初始条件。结果表明，明确设计的边界条件自适应的PINN模型可以准确地再现EPANET水质模拟，同时减少计算量。确定了影响性能的关键因素，如适当的PDE规格、损失平衡和数据预处理。虽然分析是在单管测试台上进行的，以隔离这些影响，但研究结果为将自适应pin扩展到整个WDS网络奠定了重要基础。这项工作的主要贡献是开发和演示了一个能够可靠地适应不同边界和初始条件的PINN架构，解决了当前基于ppin的水质建模研究中的一个关键空白。

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引用次数: 0

Chain-length-dependent adsorption of extracellular DNA on biochar: Behaviors, mechanisms, and structural Stability 细胞外DNA在生物炭上的链长依赖性吸附：行为、机制和结构稳定性

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2026.100496

Xiao Sun , Lin Shi , Huang Zhang , Fangfang Li , Yanjin Long , Di Zhang

The environmental fate of extracellular DNA is significantly influenced by its interaction with widely used biochar. However, a systematic understanding of how DNA chain length and biochar properties jointly govern the adsorption process, mechanism, and subsequent DNA stability remains limited. This study systematically investigated the adsorption behaviors and mechanisms of short-stranded (sDNA) and long-stranded DNA (LDNA) on biochars produced at 300 – 600°C under neutral pH conditions. sDNA exhibited a higher adsorption capacity (5.91 mg g^-1 on BC600) by accessing internal mesopores on biochar, whereas LDNA showed a lower adsorption (2.22 mg g^-1 on BC600) and a stronger desorption hysteresis, resulting from multisite anchoring with biochars. The release rate values of sDNA and LDNA were 5 – 20% and 4 – 13% respectively on BC300. Correlation studies and desorption experiments revealed that π-π interactions and hydrophobic forces were the primary adsorption mechanisms. Spectroscopic analyses and molecular dynamic simulation confirmed conformational changes in the adsorbed DNA but showed no chain fragmentation. These findings underscore that DNA chain length and biochar properties jointly govern the sequestration and stability of DNA, providing essential mechanistic insights for assessing the role of biochar in the persistence and mobility of genetic material in the environment.

胞外DNA的环境命运受到其与广泛使用的生物炭相互作用的显著影响。然而，对DNA链长度和生物炭性质如何共同影响吸附过程、机制和随后的DNA稳定性的系统理解仍然有限。本研究系统地研究了短链DNA （sDNA）和长链DNA （LDNA）在中性pH条件下在300 ~ 600℃生产的生物炭上的吸附行为和机理。sDNA通过进入生物炭内部介孔，对BC600表现出较高的吸附量（5.91 mg g-1），而LDNA通过生物炭的多位点锚定，对BC600表现出较低的吸附量（2.22 mg g-1）和较强的解吸滞后性。sDNA和LDNA在BC300上的释放率分别为5 ~ 20%和4 ~ 13%。相关研究和解吸实验表明，π-π相互作用和疏水力是主要的吸附机制。光谱分析和分子动力学模拟证实了吸附DNA的构象变化，但没有显示链断裂。这些发现强调了DNA链长度和生物炭特性共同控制着DNA的固存和稳定性，为评估生物炭在遗传物质在环境中的持久性和流动性中的作用提供了重要的机制见解。

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引用次数: 0

Pivotal role of oxidation processes in rainwater dissolved organic matter: A three-year study 氧化过程在雨水溶解有机物中的关键作用：一项为期三年的研究

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2026.100494

Kaidi Li , Junjun Deng , Hao Ma , Ziye Huang , Zanfang Jin , Wei Hu , Libin Wu , Pingqing Fu

Understanding the composition, sources, and transformation of rainwater dissolved organic matter (DOM) is critical for elucidating surface-atmosphere material transport and associated ecosystem impacts. This three-year (2020–2022) Hangzhou study characterized anthropogenically influenced rainwater DOM via integrated spectroscopic and modeling approaches. Results revealed strong anthropogenic imprints, with mean dissolved organic carbon (DOC) of 2.9 mg C L^–1 and secondary ions dominating rainwater chemistry. Post-pandemic economic recovery in 2022 amplified fossil-fuel-combustion signatures and sulfate dominance, alongside a doubled DOC deposition flux (1.0 g C m⁻ (Iavorivska et al., 2016)). Summer DOC flux peaked at 0.32 g C m^–2, driven by increased rainfall and secondary processes. Rainwater DOM featured optical indices FI, BIX, and HIX of 1.75 ± 0.17, 1.09 ± 0.31, and 1.32 ± 0.80, indicating low humification and aging degrees with anthropogenic and biological contributions. Parallel Factor Analysis (PARAFAC) identified two humic-like substances (HULIS) and two protein-like substances (PRLIS) with distinct oxidation states. Intense oxidation drove summer peaks of highly oxidized HULIS/PRLIS, with the contribution of oxidized PRLIS increasing from 10% (2020–2021) to 26% (2022). Principal Component Analysis (PCA) emphasized strengthened fossil-fuel emissions and ozone oxidation impacts in 2022, while Positive Matrix Factorization (PMF) modeling confirmed secondary processes as dominant DOM sources, with ozone oxidation accounting for 60.7% in 2022, inducing molecular condensation and fluorescence spectrum redshift. These findings advance understanding of wet-deposition DOM in megacities, clarify the dual influences of anthropogenic activities and environmental processes, and provide quantitative constraints to inform air quality management strategies in anthropogenically perturbed regions.

了解雨水溶解有机质（DOM）的组成、来源和转化对阐明地表-大气物质运移及其对生态系统的影响至关重要。这项为期三年（2020-2022）的杭州研究通过综合光谱和建模方法表征了人为影响的雨水DOM。结果表明，雨水化学成分中存在明显的人为影响，平均溶解有机碳（DOC）为2.9 mg cl - 1，次生离子占主导地位。2022年大流行后的经济复苏放大了化石燃料燃烧特征和硫酸盐的主导地位，同时DOC沉积通量增加了一倍（1.0克立方米毒血症（Iavorivska et al., 2016））。夏季DOC通量峰值为0.32 g C m-2，受降雨增加和二次过程的驱动。雨水DOM的光学指数FI、BIX和HIX分别为1.75±0.17、1.09±0.31和1.32±0.80，表明雨水DOM的腐殖化和老化程度较低，受人为和生物因素的影响。平行因子分析（PARAFAC）鉴定出两种腐殖质样物质（HULIS）和两种蛋白样物质（PRLIS）具有不同的氧化态。强烈氧化驱动了夏季高氧化的HULIS/PRLIS峰值，氧化PRLIS的贡献从10%（2020-2021）增加到26%（2022）。主成分分析（PCA）强调2022年化石燃料排放和臭氧氧化的影响增强，而正矩阵分解（PMF）模型证实次级过程是主要的DOM源，臭氧氧化在2022年占60.7%，引起分子缩聚和荧光光谱红移。这些发现促进了对特大城市湿沉降DOM的理解，阐明了人为活动和环境过程的双重影响，并为人为扰动地区的空气质量管理策略提供了定量约束。

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引用次数: 0

Domestic wastewater treatment in a 40 L photobioreactor without sludge inoculum: Process performance and insights into nitrous oxide dynamics 无污泥接种的40 L光生物反应器处理生活废水：工艺性能和对氧化亚氮动力学的见解

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2026.100483

Talita Marinho , Stephan Berzio , Salahaldeen Dababat , Josivaldo Satiro , Alfredo Quirino , Konrad Koch , Mario T. Kato , Tito Gehring , Lourdinha Florencio , Marc Wichern

This study investigated the performance and nitrous oxide (N₂O) emission dynamics of algal-bacterial granular sludge (ABGS) cultivated in a 40 L sequencing batch photobioreactor (SBPBR) treating real domestic wastewater, without initial external inoculum. ABGS formation was successfully achieved and remained stable over 180 days, with stable granule structure (> 1000 µm), good settling properties (SVI₃₀ of 42 mL· g_VSS⁻¹), and chlorophyll-a content of 1.2 ± 0.1 mg· g_VSS⁻¹. The system remained resilient to disturbances, including tubifex proliferation, confirming the structural viability of ABGS under non-sterile conditions. Regarding treatment performance, the reactor achieved consistent COD removal (> 80 %) and efficient ammonium removal (> 97 %) after microbial community adaptation. However, phosphorus removal was moderate (52 %), limited by the lack of anaerobic cycling and absence of excess sludge removal. N₂O dynamics were monitored under four operational scenarios: low/high dissolved oxygen (DO) (2–3 and 6–7 mg· L⁻¹) and with/without light. N₂O production on liquid phase was mainly influenced by DO concentration, as lower DO levels resulted in higher N₂O emissions, while light had only a minor effect on its dynamics. However, under high DO conditions (10 L· min⁻¹, k_La = 283 h⁻¹), N₂O in the gas phase (emission factor, EF) reached 3.4 %, which was considerably higher than under low DO (3 L· min⁻¹, k_La = 100 h⁻¹), where EF remained below 1 %. This outcome indicates that oxygen availability is the dominant driver of N₂O formation, with light exerting only a secondary influence. These results emphasize the dual control of N₂O by microbial pathways and physical mass transfer, underscoring the need to optimize aeration strategies in ABGS reactors to balance nitrogen removal and greenhouse gas mitigation.

研究了40 L顺序间歇式光生物反应器（SBPBR）培养的藻-细菌颗粒污泥（ABGS）处理实际生活废水的性能和氧化亚氮（N₂O）排放动态，无需初始外部接种。ABGS的形成成功，并在180天内保持稳定，具有稳定的颗粒结构（> 1000µm），良好的沉降性能（SVI₃₀为42 mL·gVSS⁻¹），并具有1.2±0.1 mg·gVSS⁻¹的含量。该系统对包括输卵管增生在内的干扰保持弹性，证实了ABGS在非无菌条件下的结构活力。处理性能方面，反应器经过微生物群落适应后，COD去除率达到80%，铵态氮去除率达到97%。然而，磷的去除率是中等的（52%），由于缺乏厌氧循环和没有多余的污泥去除。在四种操作场景下监测N2O动态：低/高溶解氧（2-3和6-7 mg·L毒血症）和有光/无光。液相的N₂O生成主要受DO浓度的影响，DO浓度越低，N₂O排放量越大，而光对其动态影响较小。然而，在高DO条件下（10 L·min⁻¹，kLa = 283 h⁻¹），气相中的N₂O（释放因子，EF）达到3.4%，这比在低DO条件下（3 L·min⁻¹，kLa = 100 h⁻¹）要高得多，在低DO条件下，EF仍然低于1%。这一结果表明，氧可用性是N₂O形成的主要驱动因素，光仅发挥次要影响。这些结果强调了微生物途径和物理传质对N₂O的双重控制，强调了优化ABGS反应器曝气策略以平衡氮去除和温室气体减排的必要性。

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引用次数: 0

Dual-phase nitrogen transport from swine farms in a volcanic watershed of Jeju Island, South Korea: Insights from hydrochemical, isotopic and microbial analyses 韩国济州岛火山流域养猪场的双相氮运输：来自水化学、同位素和微生物分析的见解

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2026.100500

Hyun-Ji Kang , Kyoung-Ho Kim , Kanghyun Park , Junseop Oh , Frankline Enow Arrey , Jeong-Woo Kim , Seong-Taek Yun

Intensive livestock farming in volcanic watersheds creates complex nitrogen pollution pathways that remain poorly understood. This study investigated nitrogen transport mechanisms in an ephemeral creek system on Jeju Island, South Korea, using an integrated approach combining hydrochemical analysis, dual isotope tracing, and microbial community profiling of 52 water samples from groundwater, springs, and surface runoff.

Results revealed a two-stage nitrogen pollution mechanism: during dry periods, manure-derived nitrogen underwent volatilization, creating accumulated nitrogen reservoirs with enriched δ¹⁵N signatures. Rainfall events subsequently triggered rapid mobilization of stored nitrogen through ephemeral creeks and subsurface pathways. Nitrate concentrations in spring water consistently exceeded Korean drinking water standard (44.4 mg/L NO₃), with isotopic signatures confirming manure as the primary source. Dual isotope analysis demonstrated that microbial nitrification was the dominant transformation process, supported by key nitrifying bacteria (Acinetobacter, Comamonadaceae) along flow paths. Bayesian mixing models confirmed that runoff became the primary contributor to spring water nitrate during precipitation events. Advanced compositional data analysis validated the mixing of surface-derived nitrogen with groundwater. These findings highlight the vulnerability of spring water systems to delayed nitrogen inputs in fractured volcanic aquifers, emphasizing the need for management strategies that address both immediate and rainfall-triggered transport pathways in agricultural watersheds.

火山流域的集约化畜牧业产生了复杂的氮污染途径，但人们对这一途径仍知之甚少。本研究采用水化学分析、双同位素示踪和微生物群落分析相结合的综合方法，研究了韩国济州岛一个短暂溪流系统的氮转运机制，该系统来自地下水、泉水和地表径流的52个水样。结果表明，氮素污染机制分为两个阶段：在干旱期，粪便衍生的氮素挥发，形成具有丰富δ15N特征的累积氮素库；降雨事件随后通过短暂的溪流和地下通道触发了储存氮的快速动员。泉水中的硝酸盐浓度一直超过韩国饮用水标准（44.4 mg/L NO3），同位素特征证实粪便是主要来源。双同位素分析表明，微生物硝化作用是主要的转化过程，主要的硝化细菌（不动杆菌，共生菌科）沿着流动路径支持。贝叶斯混合模型证实，在降水事件中，径流成为泉水硝酸盐的主要贡献者。先进的成分数据分析证实了地表衍生氮与地下水的混合。这些发现突出了断裂的火山含水层中泉水系统对延迟氮输入的脆弱性，强调了解决农业流域即时和降雨触发的运输途径的管理策略的必要性。

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引用次数: 0

Neural network-informed Optimal Water Flow problem: Modeling, algorithm, and benchmarking 神经网络信息的最优水流问题：建模、算法和基准

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2025.100479

A. Belmondo Bianchi, H.H.M. Rijnaarts, S. Shariat Torbaghan

Water distribution networks comprise interconnected components such as pipes, tanks, and pumps, whose hydraulic behavior is inherently nonlinear and nonconvex. Modeling head loss in pipes and pump performance curves is a major challenge for optimization-based planning and operations. These challenges arise, for instance, when solving the Optimal Water Flow (OWF) problem, which aims to determine pump schedules that minimize energy costs while satisfying hydraulic and operational constraints. While various approximation techniques exist, they often lack sufficient accuracy, raising concerns about their reliability in practice. To address this, we propose a hybrid approach that integrates deep learning with mathematical optimization to solve the OWF problem. We design a modified Input Convex Neural Network (ICNN) capable of capturing complex nonlinear relationships, focusing on pipe friction losses and pump hydraulics. To ensure tractable optimization, we introduce a novel regularization that enforces input convexity, enabling neural network inference to be reformulated as a linear program. This convex approximation is embedded into the OWF formulation, enabling end-to-end optimization with standard solvers. Empirical results demonstrate significant improvements in accuracy and scalability over existing OWF approximations, offering a practical tool for cost-effective, energy-efficient water distribution management.

配水网络由管道、水箱和泵等相互连接的部件组成，其水力特性本质上是非线性和非凸的。管道和泵性能曲线的水头损失建模是基于优化规划和操作的主要挑战。例如，在解决最优水流量（OWF）问题时，这些挑战就会出现，该问题旨在确定泵的时间表，以最大限度地降低能源成本，同时满足水力和操作限制。虽然存在各种近似技术，但它们往往缺乏足够的准确性，这引起了人们对其在实践中的可靠性的担忧。为了解决这个问题，我们提出了一种将深度学习与数学优化相结合的混合方法来解决OWF问题。我们设计了一个改进的输入凸神经网络（ICNN），能够捕捉复杂的非线性关系，重点关注管道摩擦损失和泵液压。为了确保可处理的优化，我们引入了一种新的正则化，强制输入凸性，使神经网络推理能够被重新表述为线性程序。这个凸近似嵌入到OWF公式中，支持使用标准求解器进行端到端优化。实证结果表明，与现有的OWF近似相比，该方法的准确性和可扩展性有了显著提高，为具有成本效益、节能的配水管理提供了实用工具。

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引用次数: 0

Habitat partitioning shapes divergent bacterial community assembly and carbon–nitrogen functional responses under cascade-dam fragmentation and seasonality 在梯级坝破碎化和季节性条件下，生境分区形成了不同的细菌群落组合和碳氮功能响应

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2026.100495

Rongchao He, Shasha Chen, Zhenxin Chen, Weisong Ma, Mei Fu, Hongjian Lü, Weizhi Yao

Cascade-dam systems impose repeated hydrological discontinuities that convert a river continuum into alternating reservoir–river segments, enhancing environmental heterogeneity and longitudinal gradients beyond the influence of a single dam. Seasonal shifts in temperature and hydrologic conditions also modulate connectivity along the cascade, yet how these drivers jointly shape bacterial community assembly remains poorly understood. This study investigated 10 cascade-dammed reaches of the Qijiang River, collecting paired sediment and water samples in summer and winter. Using an integrated approach of 16S rRNA gene amplicon sequencing, functional gene quantification, and potential process assays, we analyzed the impacts of spatial fragmentation and seasonality on bacterial community structure, assembly mechanisms, and carbon-nitrogen functions. The results revealed a habitat partitioning phenomenon characterized by two divergent assembly mechanisms. The sediment community, predominantly shaped by stable spatial gradients, followed a deterministic track where assembly was consistently dominated by selection. Conversely, the highly sensitive water community followed a season-responsive track, with its assembly shifting from mixed assembly with elevated stochasticity in summer to deterministic control in winter. This functional partitioning was also evident: sediment functions were more strongly associated with community structure, while the water community exhibited high functional redundancy, maintaining relatively stable functional potential despite marked seasonal compositional shifts. Together, these results provide a mechanistic explanation for why dam cascades matter by demonstrating that repeated, season-modulated fragmentation generates habitat-specific assembly pathways and may buffer functional stability in regulated river landscapes.

级联坝系统造成了重复的水文不连续，将河流连续体转化为交替的水库-河流段，增强了环境异质性和纵向梯度，超出了单个大坝的影响。温度和水文条件的季节性变化也调节了级联的连通性，但这些驱动因素如何共同塑造细菌群落组装仍然知之甚少。本研究对綦江10个梯级坝河段进行了夏季和冬季的成对泥沙和水样采集。采用16S rRNA基因扩增子测序、功能基因定量和潜在过程分析等综合方法，分析了空间破碎化和季节性对细菌群落结构、组装机制和碳氮功能的影响。研究结果揭示了一种以两种不同的装配机制为特征的生境分区现象。沉积物群落主要由稳定的空间梯度形成，遵循一个确定性的轨迹，即组合始终以选择为主。相反，高度敏感的水群落遵循季节响应的轨迹，其组合从夏季随机性较高的混合组合转变为冬季确定性控制。这种功能划分也很明显：沉积物功能与群落结构的关联更强，而水群落则表现出高度的功能冗余，尽管季节组成发生明显变化，但仍保持相对稳定的功能潜力。总之，这些结果通过证明重复的、季节调节的破碎化产生了栖息地特定的组装路径，并可能缓冲受调节的河流景观的功能稳定性，为大坝级联为什么重要提供了机制解释。

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引用次数: 0

Seasonal and depth-dependent dynamics of molecular properties of lake dissolved organic matter during chlorophyll-a production and depletion 叶绿素-a产生和耗竭过程中湖泊溶解有机质分子特性的季节和深度依赖动态

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2026.100504

Qi Zhang , Mingqi Ruan , Weiying Feng , Tingting Li , Xiaofei Chen , Yuhan Cao , Xiaowei Jin , Fazhi Xie , Fanhao Song , Fengchang Wu

The molecular properties of dissolved organic matter (DOM) are closely tied to diverse biogeochemical processes and are fundamental to aquatic ecosystem function. However, how changes in lake DOM molecular composition relate to chlorophyll a (Chl‑a) dynamics remains poorly understood. Here, we examine the seasonal and depth-dependent dynamics of DOM molecular properties during Chl-a production and depletion and propose a dynamic response mechanism linking DOM molecules to Chl-a variability using Fourier-transform ion cyclotron resonance mass spectrometry and machine-learning analysis. During the Chl‑a production stage (June‒August), molecular formulas positively correlated with Chl‑a (+MFs*) accumulated, and these +MFs* were characterized by high saturation, low aromaticity, low carbon content, and small molecular weight. +MFs* were most abundance in surface waters (0‒5 m) and progressively increase at shallow (10‒20 m) and deep (30‒70 m) depths as the season advanced. During the Chl-a depletion stage (October‒March), depletion of +MFs* exceeded their production rate, and the abundance of –MFs* negatively correlated with Chl‑a increased. Thermal inversion and mixing homogenized +MFs*/–MFs* while retaining depth-specific signatures and facilitating the downward redistribution of surface +MFs*. Seasonal shifts and depth gradients drove changes in Chl-a, which modulated the diversity and complexity of DOM molecules. These findings provide a process-based framework linking DOM molecular properties to Chl-a dynamics and inform predictive lake assessment and management.

溶解有机物（DOM）的分子性质与多种生物地球化学过程密切相关，是水生生态系统功能的基础。然而，湖泊DOM分子组成的变化与叶绿素a （Chl - a）动力学的关系仍然知之甚少。在这里，我们研究了在Chl-a产生和消耗过程中DOM分子特性的季节性和深度依赖动态，并利用傅里叶变换离子回旋共振质谱和机器学习分析提出了将DOM分子与Chl-a变化联系起来的动态响应机制。在Chl - a生产阶段（6 - 8月），积累了与Chl - a正相关的分子式（+MFs*），这些+MFs*具有高饱和度、低芳构性、低含碳量和小分子量的特点。+MFs*在表层（0-5 m）最丰富，随着季节的推进，在浅层（10-20 m）和深层（30-70 m）逐渐增加。在Chl-a耗竭期（10 ~ 3月），+MFs*耗竭量超过其产量，与Chl-a负相关的-MFs *丰度增加。热反演和混合均质化+MFs*/ -MFs *，同时保留深度特征，促进表面+MFs*向下再分布。季节变化和深度梯度驱动Chl-a的变化，从而调节DOM分子的多样性和复杂性。这些发现提供了一个基于过程的框架，将DOM分子特性与Chl-a动态联系起来，并为预测性湖泊评估和管理提供信息。

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引用次数: 0

Unveiling the illusion of successful water quality governance using deep learning 揭开利用深度学习成功治理水质的假象

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2025.100476

Yueyi Liu , Hang Zheng , Jianshi Zhao

Observable improvements in surface water quality are often interpreted as evidence of effective governance. However, such conclusions may be misleading when hydrological variability and socio-economic activities obscure inconsistencies in policy implementation. This study develops a deep learning prediction-error framework that combines Convolutional Neural Networks and Long Short-Term Memory networks to predict multiple water quality indicators across China’s Pearl River Basin and to retrospectively assess governance performance. By comparing predicted and observed water quality, the approach identifies temporal and spatial patterns where regulatory signals are strong or weak. The analysis reveals that prediction errors serve as sensitive markers of governance inconsistency, particularly in economically underdeveloped regions where seemingly good water quality does not necessarily reflect robust pollution control. Occasional anomalies, such as short-term degradation coinciding with major public holidays, are presented as examples of governance-related temporal irregularities detectable through this method. Overall, the results demonstrate that deep learning models can serve not only as predictive tools but also as diagnostic instruments for uncovering hidden governance issues, offering a more nuanced evaluation of environmental management than water quality observations alone.

可观察到的地表水质量的改善常常被解释为有效治理的证据。然而，当水文变化和社会经济活动掩盖了政策执行的不一致性时，这种结论可能会产生误导。本研究开发了一个深度学习预测误差框架，该框架结合了卷积神经网络和长短期记忆网络来预测中国珠江流域的多个水质指标，并对治理绩效进行回顾性评估。通过比较预测和观察到的水质，该方法确定了调节信号强弱的时空模式。分析表明，预测误差是治理不一致的敏感标志，特别是在经济不发达地区，在这些地区，看似良好的水质不一定反映出强有力的污染控制。偶尔出现的异常情况，例如与主要公共假日同时发生的短期退化，作为通过这种方法可检测到的与治理有关的时间异常的例子。总体而言，研究结果表明，深度学习模型不仅可以作为预测工具，还可以作为发现隐藏治理问题的诊断工具，提供比单独的水质观察更细致的环境管理评估。

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引用次数: 0

Enhancing carbon sequestration through flocculation of harmful algal blooms by modified clay technology 改性粘土絮凝对有害藻华的固碳作用

IF 8.2 2区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research X

Pub Date : 2026-01-01 DOI: 10.1016/j.wroa.2026.100493

Lianbao Chi , Jing Chen , Tianhao Zheng , Wentao Wang , Xiuxian Song , Zhiming Yu

Global efforts to mitigate climate change emphasize the critical need to enhance carbon sinks. Harmful algal blooms (HABs) areas represent hot spots for labile organic carbon production, yet their carbon sequestration capacity is diminished by rapid microbial mineralization. Modified clay (MC) technology, used for HABs mitigation, could enhance the sedimentation and influence the transformation dynamics of algal-derived organic carbon. Nevertheless, the impacts of MC on the mineralization of algal-derived organic carbon and the mechanisms involved remain inadequately understood. In this study, employing ¹³C-labeled batch incubation experiments, we demonstrated that algal-derived organic carbon undergoes rapid mineralization, with 46%–59% of the total organic carbon (TOC) being mineralized within 30 days. MC substantially reduced the mineralization rate of algal-derived organic carbon from 0.68–0.80 mg/(L·d) to 0.09 mg/(L·d), thereby boosting organic carbon sequestration potential by approximately 55-70% compared to the control group. Multiple lines of evidence, including microscopic imaging, fluorescence spectroscopy, and microbial analysis, revealed that MC promoted organic carbon downward export, reduced bioavailability through flocculation and encapsulation, and suppressed heterotrophic bacteria. Notably, the MC treatment group exhibited a significant reduction, with the abundance of heterotrophic bacteria decreasing by approximately 60% and the functional genes associated with microbial mineralization dropping by 50%. Overall, this study presents direct evidence and mechanistic insights that demonstrate the feasibility of employing MC to enhance carbon sequestration in mitigating HABs.

减缓气候变化的全球努力强调了加强碳汇的迫切需要。有害藻华（HABs）地区是产生不稳定有机碳的热点，但其固碳能力因微生物的快速矿化而减弱。改性粘土（MC）技术用于减缓赤潮，可以增强沉积，影响藻源有机碳的转化动态。然而，MC对藻源有机碳矿化的影响及其机制尚不清楚。在本研究中，我们采用¹³c标记的批量培养实验，证明了藻类衍生的有机碳经历了快速矿化，在30天内矿化了总有机碳（TOC）的46%-59%。MC显著降低了藻源有机碳的矿化率，从0.68-0.80 mg/（L·d）降至0.09 mg/(L·d)，从而使有机碳固存潜力比对照组提高了约55-70%。显微成像、荧光光谱和微生物分析等多种证据表明，MC促进有机碳向下输出，通过絮凝和包封降低生物利用度，抑制异养细菌。值得注意的是，MC处理组表现出明显的减少，异养细菌的丰度下降了大约60%，与微生物矿化相关的功能基因下降了50%。总体而言，本研究提供了直接证据和机制见解，证明了采用MC来增强碳固存以减轻有害藻华的可行性。

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