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Identifying sources and fate of nutrients and pollutants in lake waters is often difficult when key analytes (e.g., dissolved phosphate) are frequently below analytical detection limits (non-detects). One way of dealing with this problem in water quality data is to replace non-detects with "fill-in" values using imputation methods (IMs). While their performance for estimating descriptive statistics (e.g., mean and variance) has been evaluated comprehensively for many environmental variables, whether IMs can reconstruct overall patterns of long-term water quality data with non-detects and different magnitudes of spatial variation remains under-studied. We developed an integrative framework, combining numerical simulations with univariate and multivariate approaches, to compare performance of nine IMs in recovering patterns of water quality data with different degrees of spatial heterogeneity. We applied this framework to a 12-year water quality dataset sampled from the nearshore region of Lake Ontario near Pickering and Ajax to show the usefulness of IMs in estimating water quality spatial variation. Firstly, in the simplest modeling scenario, we found that most IMs reproduced spatial patterns of univariate data well with ≤30 % non-detects in the dataset. Secondly, when spatial patterns were heterogeneous (e.g., when weak water mixing in nearshore regions limited nutrient transport from input sources to offshore regions), most IMs also performed well by recovering spatial variation in multivariate data with ≤80 % non-detects. Thirdly, when spatial distributions were homogeneous (e.g., when strong water mixing increased transport of nutrients from input sources to other lake areas), only weighted quantile sum regression (WQSR) performed well in reconstructing multivariate data trends with ≤10 % non-detects. Our study highlighted that IMs (especially WQSR) are useful for reconstructing spatial trends of water quality in large lakes. However, potential interactions between spatial heterogeneity and non-detect frequency must be considered when using IMs to accurately model spatial patterns in water quality.

Eutrophication of freshwaters is already a problem in many regions globally and will probably worsen as human populations grow and consume more resources. The ability of researchers and gov...

In nearshore regions of large freshwater ecosystems, complex biophysical processes across large geographic regions, combined with the common logistical challenges of data collection by multiple research agencies and shifting monitoring survey designs over time, present challenges for detecting and managing the influence of multiple sources of nutrients and pollution. We present a statistical framework using linear mixed models (LMMs) to test impact of multiple drivers on nearshore water quality of large lakes. Under this framework, we analyzed a 12-year dataset of water quality variables that were measured from a nearshore region along the Canadian shoreline of Lake Ontario (~86 km

Lechaion's inner harbour basin was constructed in the 7th-6th c. BCE and served as Corinth's principal port for over a millennium. The harbour decline and abandonment in the 6th c. CE has been attributed to several causes: natural siltation, co-seismic uplift, coastal subsidence, and damage by tsunami impacts. A multi-proxy palaeoenvironmental study was conducted on seven cores from Lechaion's inner harbour to determine changes in the coastal environments and timing and cause of harbour abandonment. Palaeoenvironments were reconstructed using high-resolution micro-XRF core scanning of sedimentary facies, isotopic (δ18O, δ13C), and micropalaeontological analyses (foraminifera, palynomorphs). The harbour lithostratigraphy consists of an uppermost (∼1 m) sequence of laminated mud and marl overlying interbedded pebbly sand and mud containing abundant marine microfossils and Roman pottery refuse. A thin (

Phosphorus distribution in the nearshore of Lake Erie near the mouth of the Grand River, Ontario, reflects the extent of the mixing area between the river and the lake, with elevated concentrations observed directly within the river plume decreasing as the plume is mixed with the nearshore waters. Easterly alongshore currents were dominant within the area and affected the spatial distribution of phosphorus (P). Suspended solids concentration declined by an order of magnitude between the river and lake, and particulate P (PP) transitioned from being largely organic phosphorus and non-apatite inorganic phosphorus (NAIP) to predominantly NAIP only. Dominant processes transitioned from PP transport in suspension or resuspension in the river below Dunnville Dam to consumption and sedimentation in the lower reaches of the river and the nearshore. Higher dreissenid mussel density and mussel phosphorus content were at times associated with the mixing area of the Grand River, suggesting that river P influences the local ecology (e.g., Cladophora and mussel growth). Mussels and Cladophora in the study area are estimated to contain 8.6 and up to 4.9 tons of phosphorus in the standing biomass, respectively, which can be supplied by the Grand River in approximately 16–25 days.

Spatially detailed surveys were conducted in 2008 over 97 km of the Canadian coastline of Lake Ontario to describe patterns in water quality correlated with natural and anthropogenic features. Features of variability were used to infer lake-wide, regional, and location specific influences on nearshore water quality. Levels of solids, nutrients, major ions, Escherichia coli , and dissolved organic carbon were higher and more variable among tributary, embayment, and shoreside (0 to 1.2 m depth) areas compared with the open nearshore (~3 m depth to 5 km offshore). A recurring pattern was a sharp drop in these features away from the shoreline with little or subtle decline beyond 1 to 3 km into the nearshore. Conductivity and UV-induced fluorescence of organic material were used to detect discharges to the nearshore. Land-based influence on water quality was greatest in the urbanized Greater Toronto Area and the least over the less developed areas. Nearshore regions received inputs from the adjacent shoreline affecting water quality, the spatial extent of which was difficult to generalize, ranging from 10s of metres to several kilometres in breadth. Despite this, concentrations of total phosphorus, soluble reactive phosphorus, dissolved inorganic nitrogen, and silicate, when averaged over the entire nearshore, were typically similar to the open lake reflecting the broad distribution of the nearshore relative to the areas most influenced by adjacent lands. The development of environmental management to address water resource problems in the nearshore should proceed with awareness of the strong spatial dimensions that define nearshore water quality.

A combination of data from shipboard and deployed sensors, nutrient and major ion concentration data, and tributary discharge and current data was used to assess water quality patterns on the Canadian nearshore of Lake Ontario in 2008 and the factors that impact these patterns. Mixing areas at tributary mouths were characterized by high spatial and temporal variability in water quality. Conductivity at sensors offshore from tributaries was variably correlated with discharge, with the correspondence most evident during high spring flow. Tracers of land runoff were positively correlated with tributary discharge at three of five study locations. The spatial distribution of water quality was strongly influenced by the predominating alongshore circulations, with gradients frequently observed parallel to the shoreline away from tributary mouths. Upwelling, evident from temperature bands along the coastline, periodically created onshore–offshore gradients in chlorophyll a and dissolved inorganic nitrogen. Lake whiting, starting in July, further enhanced the effect of upwelling by accentuating differences in water clarity, suspended solids, and ionic composition between surface and bottom strata. In general, turbidity decreased and water clarity increased with lake depth. Gradients in water clarity and chlorophyll a suggestive of dreissenid mussel feeding were uncommon. Interacting land- and lake-based factors contributed to heterogeneous water quality over the coastline of Lake Ontario highlighting needs for water resource assessment methods sensitive to the temporal and spatial scales of problems as well as the connectivity between the land and the lake.

Passive samplers (SPMDs, semi-permeable membrane devices; POCIS, polar organic chemical integrative samplers) were deployed in Lake Ontario near Pickering, Ajax, and Port Hope, Ontario in 2008 and complemented with detailed water quality indicator and water current measurements. The intent was to examine the influences of source inputs and limnological features on the distribution and dilution patterns of several organic wastewater-associated chemicals (OWCs) in dynamic nearshore waters. Generally, concentrations ranged from 0.1 to 11 ng/L for most pharmaceuticals and up to 25 ng/L for gemfibrozil and 28 ng/L for caffeine based on previously determined POCIS sampling rates. Musk (HHCB and AHTN) and triclosan (TCS) concentrations were estimated using laboratory-derived sampling rates as part of this study (4.3–7.9 L/d) and ranged up to 10 ng/L for musks and 1.5 ng/L for TCS near Pickering–Ajax. Nitrate and conductivity maps indicated that alongshore currents were primary drivers of distribution and transport for tributary discharges and wastewater treatment plant (WWTP) effluents parallel to shore. Organic wastewater chemicals like HHCB, AHTN, TCS, gemfibrozil, and venlafaxine were greatest in the vicinity of the Pickering–Ajax WWTP and then dramatically declined. Ibuprofen, carbamazepine, and especially caffeine concentrations exhibited more uniform distributions both within and between the Pickering–Ajax and Port Hope study areas suggesting that transport via alongshore currents may contribute to a regional background of the relatively more persistent OWCs that may not be captured in onshore–offshore gradient studies.