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While many watershed models estimate overland flow-related soil loss, streambank erosion is often overlooked even though it can be the dominant source of sediment in a catchment. We used the enhanced generalized watershed loading functions (GWLF-E) model to simulate the water budget, field erosion from the landscape, and streambank erosion along a gradient of agricultural to urban land cover from 1997 to 2015 in the Indian Mill Creek watershed of Michigan, USA. We evaluated discharge simulations using in-streamflow measurements and evaluated streambank erosion simulations using field-collected erosion pin measurements from a previous study. Annual water budget results suggest the creek is primarily groundwater fed, but that a per-subbasin average of 6–15% of precipitation becomes runoff. Field erosion contributed a per-subbasin average of 0.5–2.5 Mg ha−1 year−1 of sediment, while streambank erosion accounted for 0.2–50.1% of the subbasins’ total sediment yields. Average lateral erosion rate of streambanks in subbasins ranged from 0.04 to 7.37 cm year−1, with four subbasins exceeding 1.0 cm year−1. Evaluation with field-collected discharge data suggest that GWLF-E may have been overestimating discharge in the subbasins. Evaluation with streambank erosion data found that GWLF-E may have difficulty capturing the complexity of erosion rates, including instances where sediment is deposited on streambanks from upstream sources, and that it underestimates streambank erosion in headwater catchments sometimes over an order of magnitude. Our findings are important for watershed managers to evaluate modeling approaches and highlight the importance of modeling both field and streambank erosion.

Explaining spatiotemporal variability in metacommunities is challenging because conducting empirical studies that link mechanisms across scales is difficult. We developed a stochastic model of epilithic algal succession in streams to better understand the underlying interactions that drive patch dynamics at three levels of spatial hierarchy: patch, channel habitat, and reach. The state of an algal patch is specified by one of nine community types, which are defined by growth form. Ninety‐two empirical data sets of epilithic succession were used to estimate Markov transition probabilities among patch types as functions of inputs for light, nutrients, and current. Two additional probability matrices determine the effects of herbivory and disturbance based on user inputs. Testing model predictions of patch composition against independent empirical data indicated good correspondence based on resemblance metrics. Early in succession, most patches were occupied by prostrate and erect diatoms. These persisted under low light and nutrient conditions. Motile and stalked diatom patches characterized later stages when resources were moderate. Succession proceeded to mostly filamentous green algal patches under high resource levels. Sensitivity simulations indicated light most affected succession. Herbivory and disturbance increased the probability of prostrate diatom patches. We then used the model to examine how changes in abiotic and biotic parameters affect patch dynamics at different scales. Changes in nutrients or light affected patch diversity differently at the habitat vs. reach scale. Interactions with local resource levels within a channel habitat determined its alpha diversity. The proportion of channel habitat types within a reach, and their collective response to changes, determined beta diversity. Patch diversity within channel habitats generated by herbivory followed the predation hypothesis only when nutrients were low. At the reach scale, herbivory always increased patch similarity among channel habitats, lowering beta diversity. Diversity within channel habitats followed the intermediate disturbance hypothesis for a variety of habitats. Effects of disturbance on beta diversity at the reach scale depended on channel habitat heterogeneity. The stability of patches at the reach scale was highest when disturbance created high patch diversity, supporting the insurance hypothesis. The ideas generated can improve stream bioassessment methods and provide insight into mechanisms underlying patch dynamics in other ecosystems.

Background Urban areas are often built along large rivers and surrounded by agricultural land. This may lead to small tributary streams that have agricultural headwaters and urbanized lower reaches. Our study objectives assessed are as follows: (1) landscape, geomorphic, and water quality variables that best explained variation in aquatic communities and their integrity in a stream system following this agricultural-to-urban land use gradient; (2) ways this land use gradient caused aquatic communities to differ from what would be expected for an idealized natural stream or other longitudinal gradients; and (3) whether the impacts of this land use gradient on aquatic communities would grow larger in a downstream direction through the agricultural and urban developments. Our study area was an impaired coldwater stream in Michigan, USA. Results Many factors structured the biological communities along the agricultural-to-urban land use gradient. Instream woody debris had the strongest relationship with EPT (Ephemeroptera, Plecoptera, and Trichoptera) abundance and richness and were most common in the lower, urbanized watershed. Fine streambed substrate had the strongest relationship with Diptera taxa and surface air breather macroinvertebrates and was dominant in agricultural headwaters. Fish community assemblage was influenced largely by stream flow and temperature regimes, while poor fish community integrity in lower urban reaches could be impacted by geomorphology and episodic urban pollution events. Scraping macroinvertebrates were most abundant in deforested, first-order agricultural headwaters, while EPT macroinvertebrate richness was the highest downstream of agricultural areas within the urban zone that had extensive forest buffers. Conclusion Environmental variables and aquatic communities would often not conform with what we would expect from an idealized natural stream. EPT richness improved downstream of agricultural areas. This shows promise for the recovery of aquatic systems using well-planned management in watersheds with this agricultural-to-urban land use pattern. Small patches of forest can be the key to conserving aquatic biodiversity in urbanized landscapes. These findings are valuable to an international audience of researchers and water resource managers who study stream systems following this common agricultural-to-urban land use gradient, the ecological communities of which may not conform with what is generally known about land use impacts to streams.

We evaluated data from 10 laboratories that analyzed water samples from 82 recreational water sites across the state of Michigan between 2016 and 2018. Water sample replicates were analyzed by experienced U.S. Environmental Protection Agency (EPA) analysts and Michigan laboratories personnel, many of whom were newly trained, using EPA Draft Method C—a rapid quantitative polymerase chain reaction (qPCR) technique that provides same day Escherichia coli (E. coli) concentration results. Beach management decisions (i.e. remain open or issue an advisory or closure) based on E. coli concentration estimates obtained by Michigan labs and by the EPA were compared; the beach management decision agreed in 94% of the samples analyzed. We used the Wilcoxon one-sample signed rank test and nonparametric quantile regression to assess (1) the degree of agreement between E. coli concentrations quantified by Michigan labs versus the EPA and (2) Michigan lab E. coli measurement precision, relative to EPA results, in different years and water body types. The median quantile regression curve for Michigan labs versus EPA approximated the 1:1 line of perfect agreement more closely as years progressed. Similarly, Michigan lab E. coli estimates precision also demonstrated yearly improvements. No meaningful difference was observed in the degree of association between Michigan lab and EPA E. coli concentration estimates for inland lake and Great Lakes samples (median regression curve average slopes 0.93 and 0.95, respectively). Overall, our study shows that properly trained laboratory personnel can perform Draft Method C to a degree comparable with experienced EPA analysts. This allows health departments that oversee recreational water quality monitoring to be confident in qPCR results generated by the local laboratories responsible for analyzing the water samples.

Streambank erosion is difficult to quantify, models and field methods are needed to assess this important sediment source to streams. Our objectives were to (1) evaluate and compare three techniques for quantifying streambank erosion: erosion pins, total station, and laser scanning, (2) spatially assess streambank erosion rates in the Indian Mill Creek watershed of Michigan, USA, and (3) relate results with modeling of nonpoint source pollution. We found large absolute and relative errors between the different measurement techniques. However, we were unable to determine any statistically significant differences between techniques and only observed a correlation between total station and laser scanner. This suggests that the three methods have limited comparability and differences between measurements were largely not systemic. Further, the application of each technique should be dependent on site conditions, project goals, desired resolution, and resources. The laser scanner collected high-resolution data on clear, barren streambanks, but the erosion pin and total station were more representative of complex vegetated banks. Streambank erosion rates varied throughout the watershed and were influenced by fluvial processes. We estimate that streambank erosion contributed 28.5% of the creek&rsquo, s total sediment load. These findings are important to address sources of watershed impairments related to sedimentation, as choosing an applicable technique for individual purposes can help reduce the challenges and costs of a streambank erosion study.

The 2-sample mark-recapture method with Chapman’s estimator is often used by inland fishery managers to estimate the reach-scale abundance of stream fish. An important assumption of this method is that no dispersal into or out of the study reach occurs between the two samples. Violations of this assumption are probably common in practice, but their effect on bias (systematic error) of abundance estimates is poorly understood, especially in small populations. Estimation methods permitting dispersal exist but, for logistical reasons, often are infeasible for routine assessments in streams. The purpose of this paper is to extend available results regarding effects of dispersal on the bias of Chapman’s estimator as applied to reach-scale studies of stream fish abundance. We examine for the first time the joint effects of dispersal and sampling variation on the bias of this estimator. To reduce the bias effects of dispersal, we propose a modified sampling scheme in which the original study reach is expanded, a central subreach is sampled during the mark session (sample 1), and the entire reach is sampled during the recapture session (sample 2). This modified sampling scheme can substantially reduce bias effects of dispersal without requiring unique marking of individual fish or additional site visits. Analytical and simulation results show that sampling variation tends to create negative bias with respect to study-reach abundance, while dispersal tends to create positive bias; the net effect can be positive, negative, or zero, depending on the true abundance, capture probabilities, and amount and nature of dispersal. In most cases, simply expanding the study reach is an effective way to reduce dispersal-related bias of Chapman’s estimator, but expanding the study reach and employing the modified sampling scheme we propose is a better alternative for accurately estimating abundance with the same level of sampling effort.

Exchange of carbon between the biosphere and atmosphere is dominated by rates of photosynthetic CO2 uptake and respiratory CO2 release by aquatic and terrestrial ecosystems worldwide. Obtaining accurate estimates of these rates is therefore important. In lakes, the most common estimation method is based on a model of dissolved-oxygen (DO) dynamics and a corresponding time series of DO concentrations measured in freely moving lake water. O2 production and consumption are inferred from changes in DO concentration, then converted to estimates of carbon uptake and release using photosynthetic and respiratory quotients. The traditional method of this type uses a simple accounting procedure to estimate daily gross primary production (GPP), total respiration (R), and net production (NP). Assuming that measured DO concentrations contain no error, it attempts to back-calculate GPP, R, and NP from an observed time series without using statistical techniques. This method produces valid estimates of GPP and the nighttime component of R, but it is unable to estimate the daytime component of R and hence cannot estimate R or NP for a complete dark–light cycle. To obtain estimates of these quantities, one must subjectively assume a value for daytime respiration. We present three new methods for estimating GPP, R, and NP that resolve this problem and also facilitate assessment of model adequacy. We illustrate use of the methods and compare their parameter estimates by applying them to monitoring data from Muskegon Lake, Michigan (USA).

A field study assessing the sustainability and efficacy of 55 biosand filters installed during 1999–2010 was conducted in the Artibonite Valley, Haiti during 2011. Twenty-nine filters were still in use. Duration of filter use ranged from < 1 to 12 years. Water quality, microbial analysis, and flow rate were evaluated for each functioning filter. Kaplan-Meier analysis of filter lifespans showed that filter use remained high (> 85%) up to seven years after installation. Several filters were still in use after 12 years, which is longer than documented in any previous study. Filtered water from 25 filters (86%) contained Escherichia coli concentrations of < 10 most probable number of coliforms/100 mL. Recontamination of stored filtered water was negligible. Bacterial removal efficiency was 1.1 log10. Comparable results from previous studies in the same region and elsewhere show that biosand filter technology continues to be an effective and sustainable water treatment method in developing countries worldwide.

Effective landuse planning to protect stream ecosystems requires quantitative tools that link catchment landuse to stream biotic integrity. This study explores two practical catchment-scale modeling approaches to this problem. Both predict levels of sediment or nutrient stressors in stream reaches based on landcover and other geospatial data, then predict impacts of these stressor levels on metrics of stream biotic integrity using fitted stressor-response functions (SRFs). Both approaches can be applied to large numbers of catchments using only readily available geospatial data and types of biological data commonly collected by state environmental agencies. The two approaches differ in the types of stressors they address and in details of how stressor loads of catchments are predicted. Stressor variables include total sediment and dissolved, particulate, and total nitrogen and phosphorus. Biological response variables include various metrics of community structure and pollution tolerance or sens...

Summary 1. The restoration of native, forested riparian habitats is a widely accepted method for improving degraded streams. Little is known, however, about how the width, extent and continuity of forested vegetation along stream networks affect stream ecosystems. 2. To increase the likelihood of achieving restoration goals, restoration practitioners require quantitative tools to guide the development of restoration strategies in different catchment settings. We present an empirically based model that establishes a relationship between a ‘stress’ imposed at different locations along a stream by the spatial pattern of land cover within catchments, and the response of biologically determined ecosystem characteristics to this stress. The model provides a spatially explicit, quantitative framework for predicting the effects of changes in catchment land cover composition and spatial configuration on specific characteristics of stream ecosystems. 3. We used geospatial datasets and biological data for attached algae and benthic macroinvertebrates in streams to estimate model parameters for 40 sites in 33 distinct catchments within the mid-Atlantic Piedmont region of the eastern U.S. Model parameters were estimated using a genetic optimisation algorithm. R2 values for the resulting relationships between catchment land cover and biological characteristics of streams were substantially improved over R2 values for spatially aggregated regression models based on whole-catchment land cover. 4. Using model parameters estimated for the mid-Atlantic Piedmont, we show how the model can be used to guide restoration planning in a case study of a small catchment. The model predicts the quantitative change in biological characteristics of the stream, such as indices of species diversity and species composition, that would occur with the implementation of a hypothetical restoration project.

The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash-Sutcliffe coefficient of efficiency (E) and coefficient of determination (R2) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R2 were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were −0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds.

Turbulence plays an important role in the transport of particles in many aquatic systems. In addition to various types of inorganic sediment (silt, sand, etc.), these particles typically include bacteria, algae, invertebrates, and fine organic debris. In this paper, we focus on one aspect of turbulent particle transport; namely, the average time required for a suspended particle to reach the bottom of a waterbody from a specified initial elevation. This is the mean hitting-time problem, and it is important in determining, for example, the effect of turbulence on downstream transport of organic particles, dispersal times and dispersal propagules. We approach this problem by developing a stochastic diffusion model of particle transport called the Local Exchange Model, which is an extension of a model posed by Denny & Shibata (1989) in an earlier study of the same problem. We show how the mean hitting-time of the Local Exchange Model varies with factors such as a particle's fall velocity an the shape of the vertical profile in turbulent mixing. We also show how the mean hitting-time is related to both the vertical profile in current velocity and the vertical profile in concentration of suspended particles, and how these relationships can be exploited in testing the model. Among other things, our results predict that, with the sole exception of neutrally buoyant particles that do not swim downward, there is always a region of the water-column in which turbulence increases rather than decreases the mean hitting-time. We discuss the significance of this and other results for dispersal by benthic organisms.

The Local Exchange Model (LEM) is a stochastic diffusion model of particle transport in turbulent flowing water. It was developed mainly for application to particles of near-neutral buoyancy that are strongly influenced by turbulent eddies. Turbulence can rapidly transfer such particles to the bed, where settlement can then occur by, for example, sticking to biofilms (e.g., fine particulate organic matter, or FPOM) or attaching to the substrate behaviorally (e.g., benthic invertebrates). Previous papers on the LEM have addressed the problems of how long (time) and far (distance) a suspended particle will be transported before hitting the bed for the first time. These are the hitting-time and hitting-distance problems, respectively. Hitting distances predicted by the LEM for FPOM in natural streams tend to be much shorter than the distances at which most particles actually settle, suggesting that particles usually do not settle the first time they hit the bed. The present paper extends the LEM so it can address probabilistic settling, where a particle encountering the bed can either remain there for a positive length of time (i.e., settle) or immediately reflect back into the water column, each with positive probability. Previous results for the LEM are generalized by deducing a single set of equations governing the probability distribution and moments of a broad class of quantities that accumulate during particle trajectories terminated by hitting or settling on the bed (e.g., transport time, transport distance, cumulative energy expenditure during transport). Key properties of the settling-time and settling-distance distributions are studied numerically and compared with the observed FPOM settling-distance distribution for a natural stream. Some remaining limitations of the LEM and possible means of overcoming them are discussed.

Synopsis. Previous empirical and theoretical work has focused on how feeding territory size is governed by average levels of food availability and intrusion pressure; the potentially important effects of variability have not yet been studied in detail. Here I incorporate variation in food availability and intrusion pressure in some simple optimality models of territory size. The results show that the possible effects of variability are diverse, including both increase and decrease in territory size. And in some cases, variation in food availability produces qualitatively different effects than variation in intrusion pressure.