Surface Water Nutrient Concentrations Research Articles

Subsurface influences on watershed nutrient concentrations and loading in a clay dominated agricultural system

Water quality issues in the Great Lakes Basin persist despite management and monitoring efforts. With changing land use and climatic conditions, the need for improved understanding of nutrient loss from agricultural field to surface water is imperative to reduce consequences on human and aquatic life, such as perpetual algal blooms and contaminated drinking water. There remains a gap in holistic rural water management studies that investigate the understanding of the water cycle in rural settings and the interconnections between different components of the water cycle, including artificial drainage. In the current study, a year-round paired investigation of subsurface and nutrient dynamics was conducted in a small, intensively managed agricultural watershed within southwestern Ontario, Canada. Nutrients (Nitrate and Phosphorus) and stable isotopes of water (δ2H and δ18O) were sampled at varying scales (i.e., field and watershed), from multiple hydrologic components (e.g., groundwater, surface water, tile flow, and soil water), from 2020 to 2022. Results indicate that nutrient concentrations in surface water were elevated during the growing season, while nutrient loading was greater during the non-growing season in surface water. Monthly nitrate loads were found to be significantly (p < 0.01) related to groundwater elevation, soil moisture and tile flow, whereas total phosphorus loading was found to be significantly (p < 0.01) related to soil moisture and tile flow. δ2H and δ18O signatures revealed that during the growing season nutrient movement was predominantly through interflow pathways (including tile drainage) comprised of event-water. In the non-growing season, there was an increased subsurface influence on nutrient transport. This study highlights the importance of including subsurface characterization in nutrient management studies. A comprehensive understanding of varying seasonal hydrologic mechanisms that control nutrient movement within an agricultural watershed is essential to sustain growing rural communities.

Azolla cultivation enables phosphate extraction from inundated former agricultural soils

To combat the global loss of wetlands and their essential functions, the restoration and creation of wetlands is imperative. However, wetland development is challenging when soils have been in prolonged agricultural use, often resulting in a substantial nutrient legacy, especially of phosphorous (P). Inundating these soils typically leads to P mobilization, resulting in poor water quality and low biodiversity recovery. As a potential novel means to overcome this challenge, we tested whether cultivation of the floating fern Azolla filiculoides could simultaneously extract and recycle P, and provide a commercial product. Azolla has high growth rates due to the nitrogen fixing capacity of its microbiome and is capable of luxury consumption of P. Azolla cultivation may also accelerate soil P mobilization and subsequent extraction by causing surface water anoxia and the release of iron-bound P. To test this approach, we cultivated Azolla on 15 P-rich former agricultural soils in an indoor mesocosm experiment. Soils were inundated and either left unvegetated or inoculated with A. filiculoides during two 8-week cultivation periods. Biomass was harvested at different intervals (weekly/monthly/bimonthly) to investigate the effect of harvesting frequency on oxygen (O2) and nutrient dynamics. We found that Azolla attained high growth rates only on soils with high mobilization of labile P, as plant cover did not reduce surface water O2 concentrations in the first phase after inundation. This concurred with low porewater iron to P ratios (<10) and high porewater P concentrations. A. filiculoides cultivation substantially reduced surface water nutrient concentrations and extracted P at rates up to 122 kg ha−1 yr−1. We conclude that rapid P extraction by A. filiculoides cultivation is possible on soils rich in labile P, offering new perspectives for wetland rehabilitation. Additional field trials are recommended to investigate long-term feasibility, seasonal variations, and the influence of potential grazers and pathogens.

Prioritizing river basins for nutrient studies

Increases in fluxes of nitrogen (N) and phosphorus (P) in the environment have led to negative impacts affecting drinking water, eutrophication, harmful algal blooms, climate change, and biodiversity loss. Because of the importance, scale, and complexity of these issues, it may be useful to consider methods for prioritizing nutrient research in representative drainage basins within a regional or national context. Two systematic, quantitative approaches were developed to (1) identify basins that geospatial data suggest are most impacted by nutrients and (2) identify basins that have the most variability in factors affecting nutrient sources and transport in order to prioritize basins for studies that seek to understand the key drivers of nutrient impacts. The “impact” approach relied on geospatial variables representing surface-water and groundwater nutrient concentrations, sources of N and P, and potential impacts on receptors (i.e., ecosystems and human health). The “variability” approach relied on geospatial variables representing surface-water nutrient concentrations, factors affecting sources and transport of nutrients, model accuracy, and potential receptor impacts. One hundred and sixty-three drainage basins throughout the contiguous United States were ranked nationally and within 18 hydrologic regions. Nationally, the top-ranked basins from the impact approach were concentrated in the Midwest, while those from the variability approach were dispersed across the nation. Regionally, the top-ranked basin selected by the two approaches differed in 15 of the 18 regions, with top-ranked basins selected by the variability approach having lower minimum concentrations and larger ranges in concentrations than top-ranked basins selected by the impact approach. The highest ranked basins identified using the variability approach may have advantages for exploring how landscape factors affect surface-water quality and how surface-water quality may affect ecosystems. In contrast, the impact approach prioritized basins in terms of human development and nutrient concentrations in both surface water and groundwater, thereby targeting areas where actions to reduce nutrient concentrations could have the largest effect on improving water availability and reducing ecosystem impacts.

Before and after mink fur farming: water chemistry and sedimentary diatom assemblages in lakes from southwestern Nova Scotia, Canada

Libera N, Rühland KM, Kurek J, Smol JP. 2024. Before and after mink fur farming: water chemistry and sedimentary diatom assemblages in lakes from southwestern Nova Scotia, Canada. Lake Reserv Manage. 40:18–35. Since the 1930s, farmed mink pelts have been an important contributor to the economy of rural Nova Scotia (NS, Canada). However, these farms are a potential source of pollutants to nearby ecosystems. To determine how regional lakes have been affected by fur farms, we compared modern water chemistry and sedimentary diatom assemblages in 14 lakes in southwestern Nova Scotia. We categorized lakes into 3 groups: (a) 5 lakes with fur farms in the catchment or near inlets; (b) 4 lakes downstream from or near fur farms; and (c) 5 reference lakes without hydrological connection to fur farms. To assess whether lake conditions have changed since the establishment of fur farms, we conducted a “before-and-after” paleolimnological analysis comparing surface sediments (representing modern environments) to dated sediments deposited prior to fur farm operations. Diatom assemblages registered distinct responses to eutrophication in several hypereutrophic lakes with farms within their catchment boundaries. In lakes ∼25 km downstream from fur farms, diatom assemblage changes were more characteristic of climate warming and acidification than of eutrophication, despite surface water nutrient concentrations well above levels in reference lakes. We found no association between the presence of fur farms and surface water trace metals that could potentially bioaccumulate and/or biomagnify. Our data indicate that decades of nutrient inputs from fur farms have caused eutrophication at several lakes where fur farms are close to the shoreline or to inlet streams.

Sediment records from Lake Nipissing (ON, Canada) register a lake-wide multi-trophic response to climate change and reveal its possible role for increased cyanobacterial blooms

Recurring cyanobacterial blooms have been reported in Lake Nipissing (Ontario, Canada) since at least 2000. However, monitoring data indicate that surface water nutrient concentrations have not increased over the past ∼45 years in this large, shallow, mesotrophic lake. Applying paleolimnological methods, we establish baseline environmental conditions and extend the Lake Nipissing water quality data to pre-industrial times. Lake-wide assessment of changes in nutrient status, algal production, and effects of climate warming are provided by examining: 1) modern and pre-industrial sedimentary diatom assemblages from nine locations; 2) temporal trends in sedimentary photosynthetic pigments over ∼200 years from five locations; and 3) detailed sedimentary profiles of diatom and chironomid assemblage composition from Callander Bay, spanning the past ∼200 years. A pronounced shift in diatom assemblage composition was registered at all sites with pre-industrial sediments dominated by Aulacoseira spp. and modern samples dominated by Discostella stelligera. The detailed diatom analysis for Callander Bay indicated that this shift occurred ca. 1990. Since ca. 1975, cyanobacterial production (spectrally inferred from sediments) exceeded the ∼200-year mean and matches the observed increase in bloom reports. Twentieth century shifts in chironomid assemblages in Callander Bay from Procladius to Chironomus spp. dominance indicate lower hypolimnetic oxygen in recent decades. Collectively, these changes suggest that previously polymictic Lake Nipissing is now experiencing periods of thermal stratification and development of transient anoxia in bottom waters. These conditions are more prevalent and widespread in modern Lake Nipissing, consistent with a response to recent warming, decreased wind speed, and a longer ice-free period.

Nutrient explorer: An analytical framework to visualize and investigate drivers of surface water quality

Excess nutrients (nitrogen and phosphorus) in lakes can lead to eutrophication, hypoxia, and algal blooms that may harm aquatic life and people. Some U.S. states have established numeric water quality criteria for nutrients to protect surface waters. However, monitoring to determine if criteria are being met is limited by resources and time. Using R code and publicly available lake data, we introduce a downloadable interactive user interface for modeling relationships between watershed land use, climate, and other variables and surface water nutrient concentrations. Random Forest modeling identified watershed agricultural and forest land coverage, fertilizer inputs, and lake depth as the most important predictors of total phosphorus. The analytical framework implemented in this application can be applied to different locations and other surface water types to be leveraged by decision makers to identify the most influential drivers of excess nutrient concentrations and to prioritize watersheds for restoration.

Application of classification machine learning algorithms for characterizing nutrient transport in a clay plain agricultural watershed

Excess nutrients in surface water and groundwater can lead to water quality deterioration in available water resources. Thus, the classification of nutrient concentrations in water resources has gained significant attention during recent decades. Machine learning (ML) algorithms are considered an efficient tool to describe nutrient loss from agricultural land to surface water and groundwater. Previous studies have applied regression and classification ML algorithms to predict nutrient concentrations in surface water and/or groundwater, or to categorize an output variable using a limited number of input variables. However, there have been no studies that examined the application of different ML classification algorithms in agricultural settings to classify various output variables using a wide range of input variables. In this study, twenty-four ML classification algorithms were implemented on a dataset from three locations within the Upper Parkhill watershed, an agricultural watershed in southern Ontario, Canada. Nutrient concentrations in surface water were classified using geochemical and physical water parameters of surface water and groundwater (e.g., pH), climate and field conditions as the input variables. The performance of these algorithms was evaluated using four evaluation metrics (e.g., classification accuracy) to identify the optimal algorithm for classifying the output variables. Ensemble bagged trees was found to be the optimal ML algorithm for classifying nitrate concentration in surface water (accuracy of 90.9%), while the weighted KNN was the most appropriate algorithm for categorizing the total phosphorus concentration (accuracy of 87%). The ensemble subspace discriminant algorithm gave the highest overall classification accuracy for the concentration of soluble reactive phosphorus and total dissolved phosphorus in surface water with an accuracy of 79.2% and 77.9%, respectively. This study exemplifies that ML algorithms can be used to signify exceedance of recommended concentrations of nutrients in surface waters in agricultural watersheds. Results are useful for decision makers to develop nutrient management strategies.

Impacts of Basal Melting of the Totten Ice Shelf and Biological Productivity on Marine Biogeochemical Components in Sabrina Coast, East Antarctica

AbstractTo clarify the impacts of basal melting of the Antarctic ice sheet and biological productivity on biogeochemical processes in Antarctic coastal waters, concentrations of dissolved inorganic carbon (DIC), total alkalinity (TA), inorganic nutrients, chlorophyll a, and stable oxygen isotopic ratios (δ18O) were measured from the offshore slope to the ice front of the Totten Ice Shelf (TIS) during the spring/summer of 2018, 2019, and 2020. Modified Circumpolar Deep Water (mCDW) intruded onto the continental shelf off the TIS and flowed along bathymetric troughs into the TIS cavity, where it formed a buoyant mixture with glacial meltwater from the ice shelf base. Physical oceanographic processes mostly determined the distributions of DIC, TA, and nutrient concentrations. However, photosynthesis and dilution by meltwater from sea ice and the ice shelf base decreased DIC, TA, and nutrient concentrations in surface water near the ice front. These causes also reduced the partial pressure of CO2 (pCO2) in surface water by more than 100 μatm with respect to mCDW in austral summer of 2018 and 2020, and the surface water became a strong CO2 sink for the atmosphere. Phytoplankton photosynthesis changed DIC and TA in a molar ratio of 106:16. Thus, pCO2 decreased mostly as a result of photosynthesis while dilution by glacial and sea ice meltwater had a small effect. The nutrient consumption ratio suggested that photosynthesis was stimulated by iron in the water column, supplied to the surface layer via buoyancy‐driven upwelling and basal ice shelf meltwater in addition to sea ice meltwater.

Novel insight into ammonium, phosphate, and iron(II) dynamics in the sediment porewater of a constructed wetland under artificial aeration through the diffusive equilibrium in thin films technique

The analysis of porewater concentrations in constructed wetland sediments could help to understand biogeochemical processes, the sources and sinks of nutrients, and their effect on overlying water quality. In this study, we measured high-resolution porewater concentration profiles of ammonium (NH4+-N), nitrate (NO3N), phosphate (PO43--P), and ferrous iron (Fe(II)) in-situ in the Laratinga constructed wetland in Mount Barker (South Australia) using diffusive equilibration in thin films (DET) techniques. Measurements were taken under light and dark conditions, and non-aerated and aerated conditions to determine the effect on sediment porewater nutrient concentrations. Baseline surface water nutrient concentrations (NH4+-N > 36 mg L-1, PO43--P > 0.43 mg L-1) greatly exceeded water quality guideline criteria. Aeration of the water column alleviated night-time hypoxic conditions (i.e. dissolved oxygen increased from a minimum of 0.7 mg L-1 to a minimum of 4 mg L-1), and increased the redox potential in the sediment. Significant differences were present for NH4+-N, PO43--P, and Fe(II) concentrations with depth in the sediment. Ammonium concentrations in the sediment reduced under aerated conditions, presumably due to enhanced nitrification. However it was observed that PO43--P and Fe(II) concentrations increased significantly with aeration, especially under dark conditions, and were strongly correlated (R2>0.8). This was not what was hypothesised and points to complex interactions between Fe and P in the sediment. Nitrate concentrations in the sediment were below the detection limit (<0.9 mg L-1) which suggests limited nitrification-denitrification is occurring. Overall the results suggest that DET techniques are useful tools for quantifying porewater concentrations of nutrients in constructed wetlands under various environmental conditions.

Investigating relationships between climate controls and nutrient flux in surface waters, sediments, and subsurface pathways in an agricultural clay catchment of the Great Lakes Basin

Water quality within agricultural catchments is governed by management practices and climate conditions that control the transport, storage, and exchange of nutrients between components of the hydrologic cycle. This study aims to improve knowledge of nitrogen (N) and phosphorus (P) transport in low permeability agricultural watersheds by considering spatial and temporal trends of surface water nutrient concentrations in relation to hydroclimatic drivers, sediment quality, shallow hyporheic exchange, groundwater quality, and tile drain discharge over a 14-month field study in a clay hydrosystem of the Lake Huron basin, one of the five Great Lakes. Results found that events of varying magnitude and intensity enhanced nutrient release from overland flow and subsurface pathways. Tile drain discharge was found to be a consistent and elevated source of P and N to surface waters when flowing, mobilizing both diffuse nutrients from fertilizer application and legacy stores in the vadose zone. Surface water quality was temporally variable at the seasonal and event scale. Targeted sampling following fertilization periods, snowmelt, and moderate precipitation events revealed catchment wide elevated nutrient concentrations, emphasizing the need for targeted sampling regimes. Controls other than discharge magnitude and overland flow were found to contribute to peak nutrient concentrations, including internal nitrate loading, soil-snowmelt interaction, catchment wetness, and freeze thaw cycles. Sediments were found to store P in calcium minerals and have a high P storage capacity. Instream mechanisms such as sediment P fixation and hyporheic exchange may play a role in mediating surface water quality, but currently have no discernable benefit to year-round surface water nutrient concentrations. Best management practices need to focus on reducing sources of agricultural nutrients (e.g., field phosphorus concentrations and tile drain discharge loading) at the watershed scale to reduce nutrient concentrations and export in flashy clay catchments.

The interaction of physical structure and nutrient loading drives ecosystem change in a large tropical lake over 40 years

Many lakes across the world are entering novel states and experiencing altered biogeochemical cycling due to local anthropogenic stressors. In the tropics, understanding the drivers of these changes can be difficult due to a lack of documented historic conditions or an absence of continuous monitoring that can distinguish between intra- and inter-annual variation. Over the last forty years (1980–2020), Lake Yojoa (Honduras) has experienced increased watershed development as well as the introduction of a large net-pen Tilapia farm, resulting in a dramatic reduction in seasonal water clarity, increased trophic state and altered nutrient dynamics, shifting Lake Yojoa from an oligotrophic (low productivity) to mesotrophic (moderate productivity) ecosystem. To assess the changes that have occurred in Lake Yojoa as well as putative drivers for those changes, we compared Secchi depth (water clarity), dissolved inorganic nitrogen (DIN), and total phosphorus (TP) concentrations at continuous semi-monthly intervals for the three years between 1979 and 1983 and again at continuous 16-day intervals for 2018–2020. Between those two periods we observed the loss of a clear water phase that previously occurred in the months when the water column was fully mixed. Seasonal peaks in DIN coincident with mixing suggest that an enhanced accumulation of ammonium in the hypolimnion (the bottom layer of a stratified lake) during stratification, and release to the epilimnion (the top layer of a stratified lake) with mixing maintains high algal abundance and subsequently low Secchi depth during what was previously the clear water phase. This interaction of nutrient loading and Lake Yojoa's monomictic stratification regime illustrates a key phenomenon in how physical water column structure and nutrients interact in tropical monomictic lakes. This work highlights the need to consider nutrient dynamics of warm anoxic hypolimnions, not just surface water nutrient concentrations, to understand environmental change in these societally important but understudied ecosystems.

Ultraviolet‐visual spectroscopy estimation of nitrate concentrations in surface waters via machine learning

AbstractHigh‐frequency acquisition of nutrient concentrations in rivers is needed to generate nutrient loading estimates commensurate with flow and discharge data. Although the combination of field sampling and laboratory analysis is the standard approach to riverine water quality analysis, this strategy is expensive and can miss important storm‐related events. Ultraviolet‐visual (UV–Vis) spectroscopy is widely used in drinking water and wastewater systems for high‐frequency concentration estimates. However, surface waters present a unique challenge as co‐occurring constituents in environmental samples cause spectral interference at the wavelengths used to measure concentrations of dissolved nutrients. Partial least squares regression (PLSR), Lasso regression (Lasso), and stepwise multivariate linear regression (Stepwise) models can be effective predictors of nitrate concentrations using UV–Vis absorbance and are used in many available in‐situ nitrate sensors; however, the proliferation of user‐friendly open‐source machine learning (ML) algorithms offers an opportunity to use sophisticated big‐data techniques to predict nutrient concentrations in surface waters. We collected samples from four rivers across southern Ontario with a variety of nitrate concentrations, flow regimes, and interfering co‐contaminants. We demonstrated that ML applications of random forest and gradient boosting models significantly outperformed PLSR, Lasso, and Stepwise methodologies to estimate nitrate concentrations in complex environmental samples via UV–Vis absorbance. Importantly, ML applications outcompete current models at low concentrations. This new predictive methodology provides regulators and stakeholders an opportunity to establish low cost, continuous monitoring environmental programs using UV–Vis approaches.

A quarter-century of nutrient load reduction leads to halving river nutrient fluxes and increasing nutrient limitation in coastal waters of central Japan.

Nutrient load reduction is widely used to improve coastal water quality, but it can lead to oligotrophication. This paper evaluates the current status of river water origin and the water recharge system based on isotope values and dissolved compositions recorded in 2018, and it also assesses the impact of nutrient load reduction efforts on river nutrient fluxes and coastal water quality using 25years of monitoring data. This study focuses on the coast of Toyama Bay as a model area because (1) up to 20% of terrestrially derived nutrient support the growth of coastal primary productivity, and (2) the adjacent land is a typical city in a population-dense area (~ 500 persons/km2), a demographic characteristic that exists in 88% of Japan's total land area and 96% of the total length of the country's coastline. Since the government adopted new wastewater treatment systems in 1993, river nutrient supplies in the study area have been halved, while the total river flow and annual precipitation have remained almost unchanged. The reduction in riverine nutrient supply has increased phosphorus deficiencies in the coastal waters. Most notably, the decline in nutrient concentrations in coastal surface waters and the enlarged nutrient-restricted areas are facing most parts of Japan, suggesting a resulting 25-50% decrease in CO2 uptake by primary production. This study is in agreement with previous studies from various countries in emphasizing the importance of setting appropriate nutrient-management goals for maintaining a sustainable marine environment. This paper recommends the need to accumulate various case studies of different areas and to share in a timely manner scientific evidence on a regional and global scale.

Ongoing anthropogenic eutrophication of the catchment area threatens the Doñana World Heritage Site (South-west Spain)

Eutrophication is a major cause of wetland degradation worldwide. In recent decades, reductions in nutrient inputs have led to improvements in water quality in many rivers and lakes in central and northern Europe, but long-term trends are less clear in southern Europe. We conducted the first comprehensive study of water quality in Doñana (SW Spain), one of the most important wetland complexes in Europe and the Mediterranean region. The core area of Doñana is a large shallow, seasonal marsh (UNESCO World Heritage Site—WHS) that floods during rainy, cool winter months, then dries out during the summer. The marsh is fed by three main streams whose catchments are within a Biosphere Reserve but are impacted by greenhouses (for cultivating fruit, irrigated with groundwater), poorly treated urban wastewaters and tourism. From 2013 to 2016, we monitored nutrient (Total P, Total N, PO4−3, NH4+, NO3−, NO2−) and phytoplankton chlorophyll-a (chla) concentrations in surface waters of the Doñana marsh and the three main streams. We quantified changes in greenhouse cover since 1995 using satellite images. Nutrient concentrations in streams were consistently higher than in the marsh, particularly in the Partido and Rocina streams that regularly reached concentrations equivalent to a “bad physico-chemical status” under the EU Water Framework Directive (WFD), and whose catchments suffered a fivefold expansion of greenhouses from 1995 to 2016. The Partido was the most polluted stream, and the most affected by wastewater effluents, and had particularly high concentrations of NH4+ (Geometric Mean = 0.3 mg L−1) and NO2− (GM = 0.52 mg L−1) across seasons. Patterns in chla concentrations were less consistent, but streams (GM = 6.78 µg L−1) generally had higher concentrations than the marsh (GM = 4.27 µg L−1). Nutrient concentrations in spot samples within the marsh largely depended on a combination of evaporation (as revealed by higher stable isotope δ2H values in the water column) and spatial processes (concentrations increase close to stream entry points, where conductivity is lower). Anthropogenic nutrient pollution in entry streams is a serious problem in Doñana, with extensive stretches too toxic for fish. Reinforcement of policies aimed at reducing nutrient inputs to Doñana are urgently required to meet the biodiversity conservation and environmental objectives for the WHS and WFD, respectively. Paradoxically, the marsh is currently relied upon to purify the water entering from streams.

ML-SWAN-v1: a hybrid machine learning framework for the concentration prediction and discovery of transport pathways of surface water nutrients

Abstract. Nutrient data from catchments discharging to receiving waters are monitored for catchment management. However, nutrient data are often sparse in time and space and have non-linear responses to environmental factors, making it difficult to systematically analyse long- and short-term trends and undertake nutrient budgets. To address these challenges, we developed a hybrid machine learning (ML) framework that first separated baseflow and quickflow from total flow, generated data for missing nutrient species, and then utilised the pre-generated nutrient data as additional variables in a final simulation of tributary water quality. Hybrid random forest (RF) and gradient boosting machine (GBM) models were employed and their performance compared with a linear model, a multivariate weighted regression model, and stand-alone RF and GBM models that did not pre-generate nutrient data. The six models were used to predict six different nutrients discharged from two study sites in Western Australia: Ellen Brook (small and ephemeral) and the Murray River (large and perennial). Our results showed that the hybrid RF and GBM models had significantly higher accuracy and lower prediction uncertainty for almost all nutrient species across the two sites. The pre-generated nutrient and hydrological data were highlighted as the most important components of the hybrid model. The model results also indicated different hydrological transport pathways for total nitrogen (TN) export from two tributary catchments. We demonstrated that the hybrid model provides a flexible method to combine data of varied resolution and quality and is accurate for the prediction of responses of surface water nutrient concentrations to hydrologic variability.

Saltwater intrusion affects nutrient concentrations in soil porewater and surface waters of coastal habitats

AbstractCoastal ecosystems are undergoing major biogeochemical shifts due to climate change and sea level rise. At the same time, agricultural fertilizer applications are increasing coastal nutrient inputs. In this study, we examine the potential impact of saltwater intrusion (SWI) on nitrogen (N) and phosphorus (P) concentrations in soil porewater and surface water of different habitats within the Chesapeake Bay estuary. Study sites are located along Maryland's Lower Eastern Shore and were monitored over three summers from 2016 to 2018. These sites encompass various habitats on the land–sea interface, consisting of healthy forests, intruded forests, abandoned fields, intruded fields, agricultural ditches, tidal creeks, and tidal salt marshes. Intruded fields were being actively farmed at the time of the study. Soil porewater and surface water grab samples were collected from the habitats and analyzed for electrical conductivity, pH, dissolved organic P (DOP), dissolved inorganic P in the form of soluble reactive P (SRP), dissolved inorganic N as ammonium‐N (NH4‐N), and total dissolved iron (TDFe). Electrical conductivity was greatest in the marshes (16.58 mS/cm averaged across all years) and did not significantly differ among intruded forests, intruded fields, and agricultural ditches. As a legacy of heavy fertilizer use, DOP concentrations exceeded 0.45 mg P/L in all habitats. Concentrations of inorganic N and P differed significantly by habitat. Concentrations of NH4‐N were significantly higher in salt marsh soil porewater than in any other habitat measured. Overall, SRP concentrations were the highest in the soil porewater of intruded fields and marshes and in the surface water of agricultural ditches (0.30, 0.29, and 0.33 mg P/L averaged across all years, respectively). These concentrations greatly exceeded recommended U.S. Environmental Protection Agency nutrient pollution thresholds for the region. In its oxidized state, dissolved iron can bind to SRP and prevent it from becoming bioavailable. However, TDFe concentrations in the ditches, tidal creeks, and marshes were too low to adequately buffer against SRP loss to downstream areas. As SWI moves salts inland and increases hydrologic connectivity across coastal landscapes, it is important to consider the mechanisms through which nutrients may be released from coastal soils and their potential to impact downstream water quality.

Distinct responses of planktonic and sedimentary bacterial communities to anthropogenic activities: Case study of a tributary of the Three Gorges Reservoir, China

Anthropogenic activities can cause serious negative effects on ecosystems. Despite the ecological significance of bacterial communities, the integrated biogeography of planktonic and sedimentary bacterial communities in response to anthropogenic activities is not adequately understood. Here, we examined environmental parameters and the composition of planktonic and sedimentary bacteria in the Yulin River, a tributary of Three Gorges Reservoir, in response to changes in land use and dam construction. The results revealed that human-induced land use changes enhanced the nutrient concentrations in surface water and dam construction reduced the content of carbon and nitrogen in immediately downstream sediments. Intensified human-dominated land use showed a slight impact on sedimentary bacterial communities but largely reduced the diversity of planktonic bacterial communities. Moreover, human-induced land use changes increased the abundance of genes associated with denitrification, nitrification, and anammox in planktonic bacterial communities by 19.04%, 32.40% and 30.45%, respectively. In dam construction regions, the diversity and nutrient-related metabolic activity of sedimentary bacterial communities immediately downstream of the dam were decreased, whereas these changes were not observed in planktonic bacterial communities. Additionally, bacterial community composition was significantly related to nutrient concentrations variability and followed a distance-decay pattern. Furthermore, environmental effects explained more of the variation in planktonic bacterial community composition as compared with spatial effects did, whereas, sedimentary bacterial communities were more closely related to spatial effects. Our results demonstrated the distinct responses of planktonic and sedimentary bacterial communities to anthropogenic activities, and offered new insight for understanding their potential ecological influence on rivers.

Quantifying the effects of surface conveyance of treated wastewater effluent on groundwater, surface water, and nutrient dynamics in a large river floodplain

Restoration and reconnection of floodplain systems provide multiple societal and ecosystem benefits, while providing municipalities the opportunity to attempt alternative approaches to maintain infrastructure protection and function. In some restored floodplains, treated wastewater effluent discharge is redirected over land instead of directly into rivers to allow natural flow and infiltration, to facilitate restoration designs such as levee setback, and to provide additional freshwater to floodplain ecosystems. However, indirect discharge of treated effluent over land may pose risks to surface and groundwater when pollutants like excess nutrients enter the floodplain and undergo transformation. We investigated the consequences for groundwater and surface water quality when effluent was redirected as open water channels over a floodplain surface. In this study, seasonal floodplain nutrient concentrations in groundwater and surface water were observed for more than 5 years as a floodplain and wastewater treatment plant underwent a major restoration project that included river-floodplain reconnection with levee setback and redirection of effluent discharge from a river channel to open flow across the restored floodplain. Nutrient loading to the surrounding floodplain groundwater and surface water was observed, but based on measures of hydrological connectivity, groundwater flow paths, and biogeochemistry, nutrients from the effluent moved within the floodplain with minimal effect to the surrounding floodplain water quality. We did not find evidence of substantial additional processing that could replace advanced nutrient treatment in this system, however we did observe evidence of diverse nutrient processes that may support enhanced retention if treatment channels were designed to enhance these processes. We suggest that indirect discharge of high quality treated effluent in a restored floodplain is a viable alternative to direct discharge into a river when groundwater flow directs that discharge to habitats where minimal nutrient sensitivity is expected.

Ispitivanje uticaja najboljih upravljanja poljoprivrednim projektima na kvalitet površinske vode

Water is an essential component of the Earth's ecosystem; each freshwater body has its specific physical and chemical characteristics. High contents of nutrients in the water, such as nitrogen and phosphorus are the major issues in terms of water quality. Notably, excessive nutrient concentrations in surface waters cause eutrophication. This research examines some pollution parameters to determine the current pollution level of the Goksu River. The river passes through the Goksu Delta, which is the most important natural habitat of the Mediterranean region of Turkey. Agricultural best management practices were an important phase of this study. The main goal was to examine the effects of agricultural best management practices on water quality of the Goksu River. Soil and Water Assessment Tool (SWAT) was used for modeling the water quality of the Goksu River considering the agricultural best management practices. Water quality is the lowest in the watershed outlet. For this reason, agricultural best management practices have been evaluated by using SWAT program by considering watershed outlet water quality values. Results confirmed that agricultural best management practices retain large amounts of nutrient load in the Goksu River Watershed. SWAT simulation shows that in case agricultural best management practices were used, there could be a high decrease in BOD5, NO2 - and Total P loads. Which means a higher water quality class according to the Surface Water Quality Management Regulations (SWQMR) of Turkey.

Diatoms Si uptake capacity drives carbon export in coastal upwelling systems

Abstract. Coastal upwelling systems account for approximately half of global ocean primary production and contribute disproportionately to biologically driven carbon sequestration. Diatoms, silica-precipitating microalgae, constitute the dominant phytoplankton in these productive regions, and their abundance and assemblage composition in the sedimentary record is considered one of the best proxies for primary production. The study of the sedimentary diatom abundance (SDA) and total organic carbon content (TOC) in the five most important coastal upwelling systems of the modern ocean (Iberia–Canary, Benguela, Peru–Humboldt, California, and Somalia–Oman) reveals a global-scale positive relationship between diatom production and organic carbon burial. The analysis of SDA in conjunction with environmental variables of coastal upwelling systems such as upwelling strength, satellite-derived net primary production, and surface water nutrient concentrations shows different relations between SDA and primary production on the regional scale. On the global scale, SDA appears modulated by the capacity of diatoms to take up silicic acid, which ultimately sets an upper limit to global export production in these ocean regions.