Using Inundation Extents to Predict Microbial Contamination in Private Wells after Flooding Events.

Disaster recovery poses unique challenges for residents reliant on private wells. Flooding events are drivers of microbial contamination in well water, but the relationship observed between flooding and contamination varies substantially. Here, we investigate the performance of different flood boundaries─the FEMA 100 year flood hazard boundary, height above nearest drainage-derived inundation extents, and satellite-derived extents from the Dartmouth Flood Observatory─in their ability to identify well water contamination following Hurricane Florence. Using these flood boundaries, we estimated about 2600 wells to 108,400 private wells may have been inundated─over 2 orders of magnitude difference based on boundary used. Using state-generated routine and post-Florence testing data, we observed that microbial contamination rates were 7.1-10.5 times higher within the three flood boundaries compared to routine conditions. However, the ability of the flood boundaries to identify contaminated samples varied spatially depending on the type of flooding (e.g., riverine, overbank, coastal). While participation in testing increased after Florence, rates were overall still low. With <1% of wells tested, there is a critical need for enhanced well water testing efforts. This work provides an understanding of the strengths and limitations of inundation mapping techniques, which are critical for guiding postdisaster well water response and recovery.

Village Settlements in Mountainous Tropical Areas, Hotspots of Fecal Contamination as Evidenced by Escherichia coli and Stanol Concentrations in Stormwater Pulses.

Fecal bacteria in surface water may indicate threats to human health. Our hypothesis is that village settlements in tropical rural areas are major hotspots of fecal contamination because of the number of domestic animals usually roaming in the alleys and the lack of fecal matter treatment before entering the river network. By jointly monitoring the dynamics of Escherichia coli and of seven stanol compounds during four flood events (July-August 2016) at the outlet of a ditch draining sewage and surface runoff out of a village of Northern Lao PDR, our objectives were (1) to assess the range of E. coli concentration in the surface runoff washing off from a village settlement and (2) to identify the major contributory sources of fecal contamination using stanol compounds during flood events. E. coli pulses ranged from 4.7 × 104 to 3.2 × 106 most probable number (MPN) 100 mL-1, with particle-attached E. coli ranging from 83 to 100%. Major contributory feces sources were chickens and humans (about 66 and 29%, respectively), with the highest percentage switching from the human pole to the chicken pole during flood events. Concentrations indicate a severe fecal contamination of surface water during flood events and suggest that villages may be considered as major hotspots of fecal contamination pulses into the river network and thus as point sources in hydrological models.

Study on agricultural water resource utilization efficiency under the constraint of carbon emission and water pollution.

Agricultural water resource utilization efficiency in China is facing significant challenges due to the dual constraints of carbon emissions and water pollution. The inefficiency in water usage in agriculture not only impacts the sustainability of water resources but also contributes to environmental degradation through increased carbon emissions and water pollution. Agricultural water resource utilization efficiency under the constraint of carbon emission and water pollution has been a critical issue in China from 2005 to 2022. This study employs the Quantile Autoregressive Distributed Lag (QARDL) method to comprehensively assess and analyze the complex relationship that exists between agricultural water usage, carbon emissions, and water pollution. By analyzing distinct quantiles of the data distribution, the research investigates how different levels of water resource utilization efficiency relate to carbon emissions and water pollution under various conditions. The findings reveal nuanced insights into the dynamic interactions among these components within the agricultural sector. This research project focuses on the efficiency of water resource utilization in agriculture while considering the constraints of carbon emission and water pollution. Given the dynamic and time-dependent character of these components, the QARDL methodology makes it possible to get a detailed knowledge of how they interact within the framework of agriculture. The study aims to give significant insights and policy suggestions to improve agricultural practices while minimizing environmental concerns linked to carbon emissions and water pollution.

Fluorescence fingerprint as an indicator to identify urban non-point sources in urban river during rainfall period.

Nowadays, the urban non-point source (NPS) pollution gradually evolved as the main contributor to urban water contamination since the point source pollution was effectively controlled. It was imperative to perform urban NPS identification in urban river to meet the requirements of precise source governance. In this study, the real-time detection about water quality parameters and fluorescence fingerprints (FFs) was performed for BX River and its outlets during rainfall period. EEM-PARAFAC and component similarity analyses discovered that the pollution encountered by BX River mainly came from road runoff and untreated municipal wastewater (UMWW) overflow. The C1 (tryptophan-like) and C3 (terrestrial humic-like) components located at Ex/Em = âˆ¼230(280)/340 and ∼275/430 nm were both detected in these two kinds of urban NPS. The C2 components of road runoff and UMWW overflow displayed remarkable differences, which located at Ex/Em = 250/385 and 245/365 nm, respectively, thus could be served as indicators for distinguishing them. During rainfall period, the outflow from rainwater outlets (RWOs) constantly showed similar FF features to road runoff, while the FFs of outflow from combined sewer outlets (CSOs) alternated between those of road runoff and UMWW overflow. The FF features of sections in BX River changed in response to the dynamic variations in FFs of the outlets, which revealed real-time pollution causes of BX River. This work not only realized the identification and differentiation of urban NPS, but also elucidated the dynamic variations of pollution characteristics throughout the entire process of "urban NPS-outlets-urban river", and demonstrated the feasibility of FF technique in quickly diagnosing the pollution causes of urban river during rainfall period, which provided important guidance for urban NPS governance.

Microplastics in aquatic ecosystems of Africa: A comprehensive review and meta-analysis.

Microplastic pollution is a global issue of great public concern. Africa is flagged to host some of the most polluted water bodies globally, but there is no enough information on the extent of microplastic contamination and the potential risks of microplastic pollution in African aquatic ecosystems. This meta-analysis has integrated data from published articles about microplastic pollution in African aquatic ecosystems. The data on the microplastic distribution and morphological characteristics in water, sediments and biota from African rivers, lakes, oceans and seas were extracted from 75 selected studies. Multivariate statistics were used to critically analyze the effects of sampling and detection methods, ecological risks, spatial distribution and similarity of microplastics in relation to the geographical distance between sampling sites. This study found that sampling methods have significant effect on abundance and morphological characteristics of microplastics and that African aquatic ecosystems are highly contaminated with microplastics compared to global data. The most prevalent colors were white, transparent and black, the most prevalent shapes were fibres and fragments, and the most available polymers were polypropylene (PP), polystyrene (PS) and polyethene terephthalate (PET). Microplastic polymers similarity decreased with an increase in geographical distance between sites. Risk levels of microplastics in African aquatic ecosystems were comparatively high, and more than 40 % of water and sediments showed highest level of ecological risk. This review provides recent information on the prevalence, distribution and risks of microplastics in African aquatic ecosystems.

A mechanistic approach to arsenic adsorption and immobilization in aqueous solution, groundwater, and contaminated paddy soil using pine-cone magnetic biochar.

Arsenic (As) poisoning in groundwater and rice paddy soil has increased globally, impacting human health and food security. There is an urgent need to deal with As-contaminated groundwater and soil. Biochar can be a useful remedy for toxic contaminants. This study explains the synthesis of pinecone-magnetic biochar (PC-MBC) by engineering the pinecone-pristine biochar with iron salts (FeCl3.6H2O and FeSO4.7H2O) to investigate its effects on As(V) adsorption and immobilization in water and soil, respectively. The results indicated that PC-MBC can remediate As(V)-contaminated water, with an adsorption capacity of 12.14 mg g-1 in water. Isotherm and kinetic modeling showed that the adsorption mechanism involved multilayer, monolayer, and diffusional processes, with chemisorption operating as the primary interface between As(V) and biochar. Post-adsorption analysis of PC-MBC, using FTIR and XRD, further revealed chemical fixing and outer-sphere complexation between As(V) and Fe, O, NH, and OH as the main reasons for As(V) adsorption onto PC-MBC. Recycling of PC-MBC also had excellent adsorption even after several regeneration cycles. Similarly, PC-MBC successfully immobilized As in paddy soil. Single and sequential extraction results showed the transformation of mobile forms of As to a more stable form, confirmed by non-destructive analysis using SEM, EDX, and elemental dot mapping. Thus, Fe-modified pine-cone biochar could be a suitable and cheap adsorbent for As-contaminated water and soil.

Microplastics increase the microbial functional potential of greenhouse gas emissions and water pollution in a freshwater lake: A metagenomic study.

Aquatic ecosystems are being increasingly polluted by microplastics (MPs), which calls for an understanding of how MPs affect microbially driven biogenic element cycling in water environments. A 28-day incubation experiment was conducted using freshwater lake water added with three polymer types of MPs (i.e., polyethylene, polypropylene, polystyrene) separately or in combination at a concentration of 1 items/L. The effects of various MPs on microbial communities and functional genes related to carbon, nitrogen, phosphorus, and sulfur cycling were analyzed using metagenomics. Results showed that Sphingomonas and Novosphingobium, which were indicator taxa (genus level) in the polyethylene treatment group, made the largest functional contribution to biogenic element cycling. Following the addition of MPs, the relative abundances of genes related to methane oxidation (e.g., hdrD, frhB, accAB) and denitrification (napABC, nirK, norB) increased. These changes were accompanied by increased relative abundances of genes involved in organic phosphorus mineralization (e.g., phoAD) and sulfate reduction (cysHIJ), as well as decreased relative abundances of genes involved in phosphate transport (phnCDE) and the SOX system. Findings of this study underscore that MPs, especially polyethylene, increase the potential of greenhouse gas emissions (CO2, N2O) and water pollution (PO43-, H2S) in freshwater lakes at the functional gene level.

Beachgoers' responses to beach health advisories.

Drawing on responses from 238 beachgoers who have visited a Georgia (U.S. state) beach in the past three years, this study asks respondents about their knowledge of beach water quality monitoring, awareness of beach health advisories, perception of water quality, and expected responses upon learning of a beach's water pollution advisory. Binomial logistic regression finds that the only demographic predictor of respondents who would completely stop visiting a beach with an advisory is whether the respondent is a visitor or resident (year-round or part-time). Nearly 40% of visitors would not come to a beach with an advisory compared to 13.4% of residents. Most respondents report they would continue to visit a beach but would stay out of the water and stop harvesting seafood from the beach's waters. More than a third (36.1%), however, are unaware Georgia regularly monitors beach water for water quality, and 41.2% have never read a beach sign warning of contaminated water or seafood. Alarmingly, just over half view aesthetic factors such as no litter, no odor, and clear water as criteria for defining whether beach water is safe.

Unraveling agricultural water pollution despite an ecological policy in the Ayeyarwady Basin.

BACKGROUND: The Ayeyarwady Basin in Myanmar, a critical economic zone, faces severe ecological degradation due to unsustainable agricultural practices. These practices pose significant threats to human health and marine biodiversity. Environmental threats persist despite the Myanmar government's efforts to implement biodiversity protection policies. This research explores the limited compliance with environmental protection policies among farmers in the Ayeyarwady Basin and its implications for sustainable agricultural practices and ecological conservation. METHODS: This research employs an exploratory phenomenological approach, utilizing semi-structured, in-depth interviews with government officials and farmers (N = 30). The data collected were subjected to thematic analysis using Atlas 23. RESULTS: Preliminary findings reveal a gap in farmers' awareness and understanding of these policies, hindered by insufficient financing, poor communication infrastructure, and uncoordinated policy monitoring. These factors and existing unrest contribute to a top-down policy approach that neglects frontline stakeholders. The study suggests the need for clear stakeholder roles, adequate policy financing, and diverse communication strategies to effectively implement environmental policies and protect human and marine life. CONCLUSIONS: Environmental policy shortcomings in Myanmar are attributable to governmental oversight and insufficient stakeholder engagement. To mitigate pollution and safeguard river basin ecosystems, the government must delineate stakeholder responsibilities, allocate appropriate policy funding, and adopt varied communication approaches with farmers.

Determinants and action paths of transboundary water pollution collaborative governance: A case study of the Yangtze River Basin, China.

With rapid economic growth, the issue of water pollution has become increasingly prominent, and there is a consensus that river basin management systems and cross-regional management coordination mechanisms need improving. In this study, 171 transboundary sections of the Yangtze River Basin were matched with the data of 57 cities to construct panel data from 2015 to 2021. Based on the four-dimensional framework of environment-determination-process-resources, the dynamic qualitative comparative analysis (QCA) method is used to identify the key influencing factors and action paths of water pollution collaborative governance effects. The results show that a single antecedent condition is not necessary to achieve efficient collaborative governance effects, and only the "number of collaborative governance" and "scale of collaboration" conditions played important roles. There are five paths that can achieve efficient collaborative governance effects: economy-oriented, ecology-oriented, technology-oriented, government-oriented, and all-oriented. Additionally, heterogeneous results show that the impact of the regional governance intention on efficient collaborative governance effect is limited in the middle and upstream sections of the Yangtze River Basin, while the downstream sections are more dependent on the basic condition of the basin. The results can help promote effective cross-regional collaboration in the Yangtze River Basin, provide scientific basis for regions to formulate targeted governance measures, and provide models for governance in other regions.

Balancing river water pollution and agricultural development: A tradeoff threshold approach.

Balancing environmental protection and social-economic development in agricultural land use management is a dilemma for decision-makers. Based on the modelling of the impacts of land use changes on river water pollution by SWAT model, the tradeoff between tea plantation expansion and river water quality was detected. SWAT model performs well in simulating the non-point source (NPS) pollution in agricultural watershed. The results showed that the tea plantation area expanded dramatically from 44 km2 in 2000 to 169 km2 in 2020 at the high cost of forest land. Consequently, the mean contents of NO3--N and TN have significantly increased by 100% and 91% respectively in the past 20 years. And the NO3--N in river water accounted for over 80% of TN in the tea plantation area. The NO3--N and TN concentrations were positively related with the proportions of tea plantation area (Tea%) at different periods. The high pollution levels of NO3--N and TN are priority control targets for river water quality management. The results indicated that the proportion of tea plantation thresholds lead to abrupt changes in river water quality. When the Tea% exceeded 3.0% in 2000, the probability of N pollution increased sharply. Whereas in 2020, it is suggested that the Tea% should not exceeds 18% to avoid sudden deterioration of water quality. The critical interval value of the Tea% for sudden change in N pollution showed an obvious increase tendency. The accelerating of nutrient pollution in rivers reduced the sensitivity of water quality to tea plantation expansion. Our results can provide new insights and empirical evidence for balancing the tradeoff between agricultural development and river water quality protection by demonstrating the carrying capacity threshold of river water environment for the expansion tea plantation.

Unlocking policy effects: Water resources management plans and urban water pollution.

Water resource management, as a foundation for supporting sustainable urban development, has garnered increasing attention from scholars. Developing effective water resource management plans is a major challenge faced by countries worldwide. This study uses the 2015 Water Pollution Control and Prevention Action Plan (WPCAP) in China as a natural experiment and employs a Difference-in-Differences (DID) model to estimate the relationship between WPCAP and urban water pollution from 2010 to 2021. The findings are as follows: 1) WPCAP reduces water pollution. 2) WPCAP decreases water pollution in high-policy-pressure cities but increases water pollution in low-policy-pressure cities within a 60 km radius, particularly having a significantly negative impact on water pollution in low-policy-pressure cities with low altitude. 3) optimizing industrial and domestic water use, as well as enhancing sewage treatment capabilities, are crucial pathways through which WPCAP reduces water pollution. Additionally, WPCAP significantly improves water pollution control capabilities in cities with abundant water resources, large cities, and industrialized cities. 4) although WPCAP's ability to control water pollution increases management costs, it also raises residential income and promotes population growth. These findings have important implications for the sustainable development of water resources in emerging countries, including China.

A "Prediction - Detection - Judgment" framework for sudden water contamination event detection with online monitoring.

The contamination detection technology helps in water quality management and protection in surface water. It is important to detect sudden contamination events timely from dynamic variations due to various interference factors in online water quality monitoring data. In this study, a framework named "Prediction - Detection - Judgment" is proposed with a method framework of "Time series increment - Hierarchical clustering - Bayes' theorem model". Time to detection is used as an evaluation index of contamination detection methods, along with the probability of detection and false alarm rate. The proposed method is tested with available public data and further applied in a monitoring site of a river. Results showed that the method could detect the contamination events with a 100% probability of detection, a 17% false alarm rate and a time to detection close to 4 monitoring intervals. The proposed index time to detection evaluates the timeliness of the method, and timely detection ensures that contamination events can be responded to and dealt with in time. The site application also demonstrates the feasibility and practicability of the framework proposed in this study and its potential for extensive implementation.

Gated graph neural networks for identifying contamination sources in water distribution systems.

Contamination events in water distribution networks (WDN) pose significant threats to water supply and public health. Rapid and accurate contamination source identification (CSI) can facilitate the development of remedial measures to reduce impacts. Though many machine learning (ML) methods have been proposed for fast detection, there is a critical need for approaches capturing complex spatial dynamics in WDNs to enhance prediction accuracy. This study proposes a gated graph neural network (GGNN) for CSI in the WDN, incorporating both spatiotemporal water quality data and flow directionality between network nodes. Evaluated across various contamination scenarios, the GGNN demonstrates high prediction accuracy even with limited sensor coverage. Notably, directional connections significantly enhance the GGNN CSI accuracy, underscoring the importance of network topology and flow dynamics in ML-based WDN CSI approaches. Specifically, the method achieves a 92.27% accuracy in narrowing the contamination source to 5 points using just 2 h of sensor data. The GGNN showcases resilience under model and measurement uncertainties, reaffirming its potential for real-time implementation in practice. Moreover, our findings highlight the impact of sensor sampling frequency and measurement accuracy on CSI accuracy, offering practical insights for ML methods in water network applications.

An approach to complex transboundary water management in Central Asia: Evolutionary cooperation in transboundary basins under the water-energy-food-ecosystem nexus.

Water-related issues in transboundary basins are generally complicated by the challenges of climate change, the historical evolution of the basin characteristics, and the different interests of the riparian countries. Therefore, dealing with water-sharing and water cooperation problems among basin countries needs to be based on multi-factor system analysis in the context of regional water, energy, food (land) resources, and ecosystems. In the present study, the Aral Sea basin in Central Asia, where transboundary water problems are extremely prominent and complex, was selected as the research area. Firstly, the characteristics of the water-energy-food-ecosystem nexus of the Aral Sea basin are analyzed. Then, based on the game theory, a multi-objective game model is constructed, and the multi-objective evolutionary game process and evolutionary stable strategies (ESSs) of both the upstream and downstream countries are explored. Finally, the evolutionary stable strategy under the intervention of the basin commission is simulated. The results show that there are obvious reciprocal feedbacks among water, land, energy, and ecosystem in the Aral Sea basin, and the uneven distribution of natural resources, fragile ecosystems, and conflicting demands of multiple actors lead to the unstable evolution of the nexus. Driven by the maximization of upstream and downstream countries' respective interests, the optimal stabilization strategy of the system cannot be realized. Whereas, the introduction of the basin commission intervention and its restraint mechanism is conducive to promoting cooperation and maximizing the overall benefits of the basin. The incentives and penalties of the basin commission have significant effects on whether the system can reach Pareto optimality, and higher incentive coefficient and penalty coefficient help the system converge to the ideal state more quickly. The evolution of the water-energy-food-ecosystem nexus based on the perspective of the whole basin can provide theoretical support for dealing with the transboundary water conflicts, and the cooperation strategy aiming at maximizing the overall benefits of the basin can provide decision-making basis for promoting transboundary water cooperation and synergistic development of the water-energy-food-ecosystem nexus.

Connecting blue-green infrastructure elements to reduce combined sewer overflows.

By infiltrating and retaining stormwater, Blue-Green Infrastructure (BGI) can help to reduce Combined Sewer Overflows (CSOs), one of the main causes of urban water pollution. Several studies have evaluated the ability of individual BGI types to reduce CSOs; however, the effect of combining these elements, likely to occur in reality, has not yet been thoroughly evaluated. Moreover, the CSO volume reduction potential of relevant components of the urban drainage system, such as detention ponds, has not been quantified using hydrological models. This study presents a systematic way to assess the potential of BGI combinations to mitigate CSO discharge in a catchment near Zurich (Switzerland). Sixty BGI combinations, including four BGI elements (bioretention cells, permeable pavement, green roofs, and detention ponds) and four different implementation rates (25%, 50%, 75%, and 100% of the available sewer catchment area) are evaluated for four runoff routing schemes. Results reveal that BGI combinations can provide substantial CSO volume reductions; however, combinations including detention ponds can potentially increase CSO frequency, due to runoff prolongation. When runoff from upstream areas is routed to the BGI, the CSO discharge reductions from combinations of BGI elements differ from the cumulative CSO discharge reductions achieved by individual BGI types, indicating that the sum of effects from individual BGI types cannot accurately predict CSO discharge in combined BGI scenarios. Moreover, larger BGI implementation areas are not consistently more cost-effective than small implementation areas, since the additional CSO volume reduction does not outweigh the additional costs. The best-performing BGI combination depends on the desired objective, being CSO volume reduction, CSO frequency reduction or cost-effectiveness. This study emphasizes the importance of BGI combinations and detention ponds in CSO mitigation plans, highlighting their critical factors-BGI types, implementation area, and runoff routing- and offering a novel and systematic approach to develop tailored BGI strategies for urban catchments facing CSO challenges.

Microplastic pollution calls for urgent investigations in stygobiont habitats: A case study from Classical karst.

Microplastic pollution in karst systems is still poorly studied, despite the presence of protected species and habitats, and important water reserves. Vulnerable key species hosted in these habitats could consume or assimilate microplastics, which can irreversibly damage management efforts, and thus ecosystems functionality. This can be particularly true for subterranean water habitats where microplastic pollution effects on wildlife management programs are not considered. The aim of this study is to provide a case study from the Classical Karst Region, which hosts peculiar habitats and key species protected at European level, such as the olm Proteus anguinus. As this area has been deeply exploited and modified over time, and is adjacent to highways, roads and railways, which could contribute to pollution within the karst system, threatening the ecosystems, it provides a perfect model system. In this study we collected and investigated water and sediment samples from aquatic environments of surface and subterranean habitats hosting several subterranean environment-adapted organisms. Examined particles were counted and characterized by size, color and shape via visual identification under a microscope, with and without UV light. Furthermore, spectroscopic analyses were carried out in order to identify microplastics typology. Microplastics were found in all examined habitats. In water, microplastics concentration ranged from 37 to 86 items/L, in sediments from 776 to 2064 items/kg. Fibre-shape was the main present, followed by fragments and beads, suggesting multiple sources of pollution, especially textile products. Most of the particles were fluorescent under UV light and were mainly transparent, while not-fluorescent ones were especially black, blue or brown. Samples contained especially polyesters and copolymers. These results highlight intense MP pollution in karst areas, with significant impacts on water quality, and potential effects on subterranean environment-dwelling species. We stress the importance of monitoring pollution in these critical environments for biodiversity and habitat conservation: monitoring in karst areas must become a priority for habitat and species protection, and water resources management, improving analyses on a larger number of aquatic surface and subterranean habitats.

A water quality assessment model involving novel fluorescence technology.

The reasonable utilization of water resources and real-time monitoring of water pollution are the core tasks of current world hydrological and water conservancy work. Novel technologies and methods for monitoring water pollution are important means to ensure water health. However, the absence of intuitive and simple analysis methods for the assessment of regional pollution in large-scale water bodies has prevented scientists from quickly grasping the overall situation of water pollution. In this study, we propose a strategy based on the unique combination of fluorescence technology and simple kriging (SK) interpolation (FL-SK) for the first time. This strategy could present the relative magnitude and distribution of the physicochemical indicators of a whole natural lake intuitively and accurately. The unique FL-SK model firstly offers a simple and effective water quality method that provides the pollution index of different sampling points in lakes. The macroscopic evaluation of large-scale water bodies by the FL-SK model primarily relies on the fluorescence response of the RDM-TPE to the comprehensive indicators of the water body, as experimental results have revealed a good correlation between fluorescent responses and six normalized physicochemical indicators. Multiple linear regression and fluorescence response experiments on RDM-TPE indicate that to some extent, the fluorescence signals of the FL-SK model may originate from a certain type of sulfide in the water body. Pattern discovery could enable the analysis of pollution levels in other ecosystems and promote early pollution assessment in the future.

Regulating greenhouse gas dynamics in tidal wetlands: Impacts of salinity gradients and water pollution.

Tidal wetlands play a critical role in emitting greenhouse gases (GHGs) into the atmosphere; our understanding of the intricate interplay between natural processes and human activities shaping their biogeochemistry and GHG emissions remains lacking. In this study, we delve into the spatiotemporal dynamics and key drivers of the GHG emissions from five tidal wetlands in the Scheldt Estuary by focusing on the interactive impacts of salinity and water pollution, two factors exhibiting contrasting gradients in this estuarine system: pollution escalates as salinity declines. Our findings reveal a marked escalation in GHG emissions when moving upstream, primarily attributed to increased concentrations of organic matter and nutrients, coupled with reduced levels of dissolved oxygen and pH. These low water quality conditions not only promote methanogenesis and denitrification to produce CH4 and N2O, respectively, but also shift the carbonate equilibria towards releasing more CO2. As a result, the most upstream freshwater wetland was the largest GHG emitter with a global warming potential around 35 to 70 times higher than the other wetlands. When moving seaward along a gradient of decreasing urbanization and increasing salinity, wetlands become less polluted and are characterized by lower concentrations of NO3-, TN and TOC, which induces stronger negative impact of elevated salinity on the GHG emissions from the saline wetlands. Consequently, these meso-to polyhaline wetlands released considerably smaller amounts of GHGs. These findings emphasize the importance of integrating management strategies, such as wetland restoration and pollution prevention, that address both natural salinity gradients and human-induced water pollution to effectively mitigate GHG emissions from tidal wetlands.

Applying water quality standards to pollution from diffuse sources.

Water quality standards are instrumental in evaluating the status of water bodies, and in providing protective and restorative endpoints. To date, much of the infrastructure used to implement water quality standards has been directed towards remediating and managing pollution from point source discharges. However, pollution from diffuse sources is the leading cause of water quality impairment, especially by nutrients. Although the effects of nutrient enrichment on streams is well studied, and ecological thresholds identified, those thresholds have not been widely adopted as standards primarily because they are not attainable by point sources. Clearly, a framework for adopting and applying standards to manage pollution from diffuse sources needs to be decoupled from those intended for point sources. This paper argues for a relatively unstructured distributional approach to predict how ecological responses might shift in response to management of diffuse sources. The approach calls for first developing a deterministic model of stressor and response variables, followed by a reformulation as a Bayesian model. In the case here, a structural equation model was developed that linked nutrient enrichment, habitat quality, and chloride and manganese concentrations to an index of macroinvertebrate quality. Results from the Bayesian representation suggest that in landscapes where the drainage network has been highly modified for agricultural production, reduction in total phosphorus alone is expected to have a modest (but non-trivial) effect on macroinvertebrate condition, shifting the distribution of scores up by 1 point. The addition of habitat restoration is likely to shift the distribution upwards by 4 points, an effect size observed in Ohio, USA from other large-scale restoration efforts.