Publications by authors named "Donald Scavia"

29 Publications

  • Page 1 of 1

Advancing estuarine ecological forecasts: seasonal hypoxia in Chesapeake Bay.

Ecol Appl 2021 Sep 21;31(6):e02384. Epub 2021 Jul 21.

U.S. Geological Survey Chesapeake Bay Program Office, Annapolis, Maryland, 21403, USA.

Ecological forecasts are quantitative tools that can guide ecosystem management. The coemergence of extensive environmental monitoring and quantitative frameworks allows for widespread development and continued improvement of ecological forecasting systems. We use a relatively simple estuarine hypoxia model to demonstrate advances in addressing some of the most critical challenges and opportunities of contemporary ecological forecasting, including predictive accuracy, uncertainty characterization, and management relevance. We explore the impacts of different combinations of forecast metrics, drivers, and driver time windows on predictive performance. We also incorporate multiple sets of state-variable observations from different sources and separately quantify model prediction error and measurement uncertainty through a flexible Bayesian hierarchical framework. Results illustrate the benefits of (1) adopting forecast metrics and drivers that strike an optimal balance between predictability and relevance to management, (2) incorporating multiple data sources in the calibration data set to separate and propagate different sources of uncertainty, and (3) using the model in scenario mode to probabilistically evaluate the effects of alternative management decisions on future ecosystem state. In the Chesapeake Bay, the subject of this case study, we find that average summer or total annual hypoxia metrics are more predictable than monthly metrics and that measurement error represents an important source of uncertainty. Application of the model in scenario mode suggests that absent watershed management actions over the past decades, long-term average hypoxia would have increased by 7% compared to 1985. Conversely, the model projects that if management goals currently in place to restore the Bay are met, long-term average hypoxia would eventually decrease by 32% with respect to the mid-1980s.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/eap.2384DOI Listing
September 2021

Simulating internal watershed processes using multiple SWAT models.

Sci Total Environ 2021 Mar 3;759:143920. Epub 2020 Dec 3.

School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA.

The need for effective water quality models to help guide management and policy, and extend monitoring information, is at the forefront of recent discussions related to watershed management. These models are often calibrated and validated at the basin outlet, which ensures that models are capable of evaluating basin scale hydrology and water quality. However, there is a need to understand where these models succeed or fail with respect to internal process representation, as these watershed-scale models are used to inform management practices and mitigation strategies upstream. We evaluated an ensemble of models-each calibrated to in-stream observations at the basin outlet-against discharge and nutrient observations at the farm field scale to determine the extent to which these models capture field-scale dynamics. While all models performed well at the watershed outlet, upstream performance varied. Models tended to over-predict discharge through surface runoff and subsurface drainage, while under-predicting phosphorus loading through subsurface drainage and nitrogen loading through surface runoff. Our study suggests that while models may be applied to predict impacts of management at the basin scale, care should be taken in applying the models to evaluate field-scale management and processes in the absence of data that can be incorporated at that scale, even with the use of multiple models.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.scitotenv.2020.143920DOI Listing
March 2021

Evaluating management options to reduce Lake Erie algal blooms using an ensemble of watershed models.

J Environ Manage 2021 Feb 9;280:111710. Epub 2020 Dec 9.

Water Center, Graham Sustainability Institute, University of Michigan, Ann Arbor, MI, 48104, United States.

Reducing harmful algal blooms in Lake Erie, situated between the United States and Canada, requires implementing best management practices to decrease nutrient loading from upstream sources. Bi-national water quality targets have been set for total and dissolved phosphorus loads, with the ultimate goal of reaching these targets in 9-out-of-10 years. Row crop agriculture dominates the land use in the Western Lake Erie Basin thus requiring efforts to mitigate nutrient loads from agricultural systems. To determine the types and extent of agricultural management practices needed to reach the water quality goals, we used five independently developed Soil and Water Assessment Tool models to evaluate the effects of 18 management scenarios over a 10-year period on nutrient export. Guidance from a stakeholder group was provided throughout the project, and resulted in improved data, development of realistic scenarios, and expanded outreach. Subsurface placement of phosphorus fertilizers, cover crops, riparian buffers, and wetlands were among the most effective management options. But, only in one realistic scenario did a majority (3/5) of the models predict that the total phosphorus loading target would be met in 9-out-of-10 years. Further, the dissolved phosphorus loading target was predicted to meet the 9-out-of-10-year goal by only one model and only in three scenarios. In all scenarios evaluated, the 9-out-of-10-year goal was not met based on the average of model predictions. Ensemble modeling revealed general agreement about the effects of several practices although some scenarios resulted in a wide range of uncertainty. Overall, our results demonstrate that there are multiple pathways to approach the established water quality goals, but greater adoption rates of practices than those tested here will likely be needed to attain the management targets.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jenvman.2020.111710DOI Listing
February 2021

Quantifying uncertainty cascading from climate, watershed, and lake models in harmful algal bloom predictions.

Sci Total Environ 2021 Mar 11;759:143487. Epub 2020 Nov 11.

Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI 48109, USA.

In response to increased harmful algal blooms (HABs), hypoxia, and nearshore algae growth in Lake Erie, the United States and Canada agreed to phosphorus load reduction targets. While the load targets were guided by an ensemble of models, none of them considered the effects of climate change. Some watershed models developed to guide load reduction strategies have simulated climate effects, but without extending the resulting loads or their uncertainties to HAB projections. In this study, we integrated an ensemble of four climate models, three watershed models, and four HAB models. Nutrient loads and HAB predictions were generated for historical (1985-1999), current (2002-2017), and mid-21st-century (2051-2065) periods. For the current and historical periods, modeled loads and HABs are comparable to observations but exhibit less interannual variability. Our results show that climate impacts on watershed processes are likely to lead to reductions in future loading, assuming land use and watershed management practices are unchanged. This reduction in load should help reduce the magnitude of future HABs, although increases in lake temperature could mitigate that decrease. Using Monte-Carlo analysis to attribute sources of uncertainty from this cascade of models, we show that the uncertainty associated with each model is significant, and that improvements in all three are needed to build confidence in future projections.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.scitotenv.2020.143487DOI Listing
March 2021

Uncertainty in critical source area predictions from watershed-scale hydrologic models.

J Environ Manage 2021 Feb 7;279:111506. Epub 2020 Nov 7.

LimnoTech, Ann Arbor, MI, USA.

Watershed-scale hydrologic models are frequently used to inform conservation and restoration efforts by identifying critical source areas (CSAs; alternatively 'hotspots'), defined as areas that export relatively greater quantities of nutrients and sediment. The CSAs can then be prioritized or 'targeted' for conservation and restoration to ensure efficient use of limited resources. However, CSA simulations from watershed-scale hydrologic models may be uncertain and it is critical that the extent and implications of this uncertainty be conveyed to stakeholders and decision makers. We used an ensemble of four independently developed Soil and Water Assessment Tool (SWAT) models and a SPAtially Referenced Regression On Watershed attributes (SPARROW) model to simulate CSA locations for flow, phosphorus, nitrogen, and sediment within the ~17,000-km Maumee River watershed at the HUC-12 scale. We then assessed uncertainty in CSA simulations determined as the variation in CSA locations across the models. Our application of an ensemble of models - differing with respect to inputs, structure, and parameterization - facilitated an improved accounting of CSA prediction uncertainty. We found that the models agreed on the location of a subset of CSAs, and that these locations may be targeted with relative confidence. However, models more often disagreed on CSA locations. On average, only 16%-46% of HUC-12 subwatersheds simulated as a CSA by one model were also simulated as a CSA by a different model. Our work shows that simulated CSA locations are highly uncertain and may vary substantially across models. Hence, while models may be useful in informing conservation and restoration planning, their application to identify CSA locations would benefit from comprehensive uncertainty analyses to avoid inefficient use of limited resources.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jenvman.2020.111506DOI Listing
February 2021

Bias correction of climate model outputs influences watershed model nutrient load predictions.

Sci Total Environ 2021 Mar 16;759:143039. Epub 2020 Oct 16.

Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT 06269, USA.

Waterbodies around the world experience problems associated with elevated phosphorus (P) and nitrogen (N) loads. While vital for ecosystem functioning, when present in excess amounts these nutrients can impair water quality and create symptoms of eutrophication, including harmful algal blooms. Under a changing climate, nutrient loads are likely to change. While climate models can serve as inputs to watershed models, the climate models often do not adequately represent the distribution of observed data, generating uncertainties that can be addressed to some degree with bias correction. However, the impacts of bias correction on nutrient models are not well understood. This study compares 4 univariate and 3 multivariate bias correction methods, which correct precipitation and temperature variables from 4 climate models in the historical (1980-1999) and mid-century future (2046-2065) time periods. These variables served as inputs to a calibrated Soil and Water Assessment Tool (SWAT) model of Lake Erie's Maumee River watershed. We compared the performance of SWAT outputs driven with climate model outputs that were bias-corrected (BC) and not bias-corrected (no-BC) for dissolved reactive P, total P, and total N. Results based on graphical comparisons and goodness of fit metrics showed that the choice of BC method impacts both the direction of change and magnitude of nutrient loads and hydrological processes. While the Delta method performed best, it should be used with caution since it considers historical variable relationships as the basis for predictions, which may not hold true under future climate. Quantile Delta Mapping (QDM) and Multivariate Bias Correction N-dimensional probability density function transform (MBCn) BC methods also performed well and work well for non-stationary climate scenarios. Furthermore, results suggest that February-July cumulative load in the Maumee basin is likely to decrease in the mid-century as runoff and snowfall decrease, and evapotranspiration increases with warming temperatures.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.scitotenv.2020.143039DOI Listing
March 2021

Elucidating controls on cyanobacteria bloom timing and intensity via Bayesian mechanistic modeling.

Sci Total Environ 2021 Feb 24;755(Pt 1):142487. Epub 2020 Sep 24.

Department of Civil, Construction & Environmental Engineering, NC State University, Raleigh, NC 27695, USA; Center for Geospatial Analytics, NC State University, Raleigh, NC 27695, USA.

The adverse impacts of harmful algal blooms (HABs) are increasing worldwide. Lake Erie is a North American Great Lake highly affected by cultural eutrophication and summer cyanobacterial HABs. While phosphorus loading is a known driver of bloom size, more nuanced yet crucial questions remain. For example, it is unclear what mechanisms are primarily responsible for initiating cyanobacterial dominance and subsequent biomass accumulation. To address these questions, we develop a mechanistic model describing June-October dynamics of chlorophyll a, nitrogen, and phosphorus near the Maumee River outlet, where blooms typically initiate and are most severe. We calibrate the model to a new, geostatistically-derived dataset of daily water quality spanning 2008-2017. A Bayesian framework enables us to embed prior knowledge on system characteristics and test alternative model formulations. Overall, the best model formulation explains 42% of the variability in chlorophyll a and 83% of nitrogen, and better captures bloom timing than previous models. Our results, supported by cross validation, show that onset of the major midsummer bloom is associated with about a month of water temperatures above 20 °C (occurring 19 July to 6 August), consistent with when cyanobacteria dominance is usually reported. Decreased phytoplankton loss rate is the main factor enabling biomass accumulation, consistent with reduced zooplankton grazing on cyanobacteria. The model also shows that phosphorus limitation is most severe in August, and nitrogen limitation tends to occur in early autumn. Our results highlight the role of temperature in regulating bloom initiation and subsequent loss rates, and suggest that a 2 °C increase could lead to blooms that start about 10 days earlier and grow 23% more intense.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.scitotenv.2020.142487DOI Listing
February 2021

The hydrologic model as a source of nutrient loading uncertainty in a future climate.

Sci Total Environ 2020 Jul 16;724:138004. Epub 2020 Mar 16.

School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA.

Hydrologic models are applied increasingly with climate projections to provide insights into future hydrologic conditions. However, both hydrologic models and climate models can produce a wide range of predictions based on model inputs, assumptions, and structure. To characterize a range of future predictions, it is common to use multiple climate models to drive hydrologic models, yet it is less common to also use a suite of hydrologic models. It is also common for hydrologic models to report riverine discharge and assume that nutrient loading will follow similar patterns, but this may not be the case. In this study, we characterized uncertainty from both climate models and hydrologic models in predicting riverine discharge and nutrient loading. Six climate models drawn from the Coupled Model Intercomparison Project Phase 5 ensemble were used to drive five independently developed and calibrated Soil and Water Assessment Tool models to assess hydrology and nutrient loadings for mid-century (2046-2065) in the Maumee River Watershed,the largest watershedsdraining to the Laurentian Great Lakes. Under those conditions, there was no clear agreement on the direction of change in future nutrient loadings or discharge. Analysis of variance demonstrated that variation among climate models was the dominant source of uncertainty in predicting future total discharge, tile discharge (i.e. subsurface drainage), evapotranspiration, and total nitrogen loading, while hydrologic models were the main source of uncertainty in predicted surface runoff and phosphorus loadings. This innovative study quantifies the importance of hydrologic model in the prediction of riverine nutrient loadings under a future climate.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.scitotenv.2020.138004DOI Listing
July 2020

Lake Huron's Phosphorus Contributions to the St. Clair-Detroit River Great Lakes Connecting Channel.

Environ Sci Technol 2020 05 22;54(9):5550-5559. Epub 2020 Apr 22.

School for Environment and Sustainability, University of Michigan, 440 Church St., Ann Arbor, Michigan 48109, United States.

The United States and Canada called for a 40% load reduction of total phosphorus from 2008 levels entering the western and central basins of Lake Erie to achieve a 6000 MTA target and help reduce its central basin hypoxia. The Detroit River is a significant source of total phosphorus to Lake Erie; it in turn has been reported to receive up to 58% of its load from Lake Huron when accounting for resuspended sediment loads previously unmonitored at the lake outlet. Key open questions are where does this additional load originate, what drives its variability, and how often does it occur. We used a hydrodynamic model, satellite images of resuspension events and ice cover, wave hindcasts, and continuous turbidity measurements at the outlet of Lake Huron to determine where in Lake Huron the undetected load originates and what drives its variability. We show that the additional sediment load, and likely phosphorus, is from wave-induced Lake Huron sediment resuspension, primarily within 30 km of the southeastern shore. When the flow is from southwest or down the center of the lake, the resuspended sediment is not detected at Canada's sampling station at the head of the St. Clair River.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/acs.est.0c00383DOI Listing
May 2020

A space-time geostatistical model for probabilistic estimation of harmful algal bloom biomass and areal extent.

Sci Total Environ 2019 Dec 8;695:133776. Epub 2019 Aug 8.

Department of Civil, Construction, & Environmental Engineering, North Carolina State University, Campus Box 7908, Raleigh, NC 27695, USA; Center for Geospatial Analytics, North Carolina State University, Campus Box 7106, Raleigh, NC 27695, USA.

Harmful algal blooms (HABs) have been increasing in intensity worldwide, including the western basin of Lake Erie. Substantial efforts have been made to track these blooms using in situ sampling and remote sensing. However, such measurements do not fully capture HAB spatial and temporal dynamics due to the limitations of discrete shipboard sampling over large areas and the effects of clouds and winds on remote sensing estimates. To address these limitations, we develop a space-time geostatistical modeling framework for estimating HAB intensity and extent using chlorophyll a data sampled during the HAB season (June-October) from 2008 to 2017 by five independent monitoring programs. Based on the Bayesian information criterion for model selection, trend variables explain bloom northerly and easterly expansion from Maumee Bay, wind effects over depth, and variability among sampling methods. Cross validation results demonstrate that space-time kriging explains over half of the variability in daily, location-specific chlorophyll observations, on average. Conditional simulations provide, for the first time, comprehensive estimates of overall bloom biomass (based on depth-integrated concentrations) and surface areal extent with quantified uncertainties. These new estimates are contrasted with previous Lake Erie HAB monitoring studies, and deviations among estimates are explored and discussed. Overall, results highlight the importance of maintaining sufficient monitoring coverage to capture bloom dynamics, as well as the benefits of the proposed approach for synthesizing data from multiple monitoring programs to improve estimation accuracy while reducing uncertainty.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.scitotenv.2019.133776DOI Listing
December 2019

Climate Change and Nutrient Loading in the Western Lake Erie Basin: Warming Can Counteract a Wetter Future.

Environ Sci Technol 2019 07 18;53(13):7543-7550. Epub 2019 Jun 18.

School for Environment and Sustainability , University of Michigan , 440 Church St. , Ann Arbor , Michigan 48104 , United States.

In the past 20 years, Lake Erie has experienced a resurgence of harmful algal blooms and hypoxia driven by increased nutrient loading from its agriculturally dominated watersheds. The increase in phosphorus loading, specifically the dissolved reactive portion, has been attributed to a combination of changing climate and agricultural management. While many management practices and strategies have been identified to reduce phosphorus loads, the impacts of future climate remain uncertain. This is particularly the case for the Great Lakes region because many global climate models do not accurately represent the land-lake interactions that govern regional climate. For this study, we used midcentury (2046-2065) climate projections from one global model and four regional dynamically downscaled models as drivers for the Soil and Water Assessment Tool configured for the Maumee River watershed, the source of almost 50% of Lake Erie's Western Basin phosphorus load. Our findings suggest that future warming may lead to less nutrient runoff due to increased evapotranspiration and decreased snowfall, despite projected moderate increases in intensity and overall amount of precipitation. Results highlight the benefits of considering multiple environmental drivers in determining the fate of nutrients in the environment and demonstrate a need to improve approaches for climate change assessment using watershed models.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/acs.est.9b01274DOI Listing
July 2019

Are all data useful? Inferring causality to predict flows across sewer and drainage systems using directed information and boosted regression trees.

Water Res 2018 11 4;145:697-706. Epub 2018 Sep 4.

Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, United States. Electronic address:

As more sensor data become available across urban water systems, it is often unclear which of these new measurements are actually useful and how they can be efficiently ingested to improve predictions. We present a data-driven approach for modeling and predicting flows across combined sewer and drainage systems, which fuses sensor measurements with output of a large numerical simulation model. Rather than adjusting the structure and parameters of the numerical model, as is commonly done when new data become available, our approach instead learns causal relationships between the numerically-modeled outputs, distributed rainfall measurements, and measured flows. By treating an existing numerical model - even one that may be outdated - as just another data stream, we illustrate how to automatically select and combine features that best explain flows for any given location. This allows for new sensor measurements to be rapidly fused with existing knowledge of the system without requiring recalibration of the underlying physics. Our approach, based on Directed Information (DI) and Boosted Regression Trees (BRT), is evaluated by fusing measurements across nearly 30 rain gages, 15 flow locations, and the outputs of a numerical sewer model in the city of Detroit, Michigan: one of the largest combined sewer systems in the world. The results illustrate that the Boosted Regression Trees provide skillful predictions of flow, especially when compared to an existing numerical model. The innovation of this paper is the use of the Directed Information step, which selects only those inputs that are causal with measurements at locations of interest. Better predictions are achieved when the Directed Information step is used because it reduces overfitting during the training phase of the predictive algorithm. In the age of "big water data", this finding highlights the importance of screening all available data sources before using them as inputs to data-driven models, since more may not always be better. We discuss the generalizability of the case study and the requirements of transferring the approach to other systems.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.watres.2018.09.009DOI Listing
November 2018

Ensemble modeling informs hypoxia management in the northern Gulf of Mexico.

Proc Natl Acad Sci U S A 2017 08 31;114(33):8823-8828. Epub 2017 Jul 31.

Department of Civil, Construction, and Environmental Engineering, North Carolina State University, Raleigh, NC 27695.

A large region of low-dissolved-oxygen bottom waters (hypoxia) forms nearly every summer in the northern Gulf of Mexico because of nutrient inputs from the Mississippi River Basin and water column stratification. Policymakers developed goals to reduce the area of hypoxic extent because of its ecological, economic, and commercial fisheries impacts. However, the goals remain elusive after 30 y of research and monitoring and 15 y of goal-setting and assessment because there has been little change in river nitrogen concentrations. An intergovernmental Task Force recently extended to 2035 the deadline for achieving the goal of a 5,000-km 5-y average hypoxic zone and set an interim load target of a 20% reduction of the spring nitrogen loading from the Mississippi River by 2025 as part of their adaptive management process. The Task Force has asked modelers to reassess the loading reduction required to achieve the 2035 goal and to determine the effect of the 20% interim load reduction. Here, we address both questions using a probabilistic ensemble of four substantially different hypoxia models. Our results indicate that, under typical weather conditions, a 59% reduction in Mississippi River nitrogen load is required to reduce hypoxic area to 5,000 km The interim goal of a 20% load reduction is expected to produce an 18% reduction in hypoxic area over the long term. However, due to substantial interannual variability, a 25% load reduction is required before there is 95% certainty of observing any hypoxic area reduction between consecutive 5-y assessment periods.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1073/pnas.1705293114DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5565443PMC
August 2017

Tracking cyanobacteria blooms: Do different monitoring approaches tell the same story?

Sci Total Environ 2017 Jan 13;575:294-308. Epub 2016 Oct 13.

Water Center, Graham Sustainability Institute, University of Michigan, 625 E. Liberty St., Suite 300, Ann Arbor, MI 48104, USA.

Cyanobacteria blooms are a major environmental issue worldwide. Our understanding of the biophysical processes driving cyanobacterial proliferation and the ability to develop predictive models that inform resource managers and policy makers rely upon the accurate characterization of bloom dynamics. Models quantifying relationships between bloom severity and environmental drivers are often calibrated to an individual set of bloom observations, and few studies have assessed whether differences among observing platforms could lead to contrasting results in terms of relevant bloom predictors and their estimated influence on bloom severity. The aim of this study was to assess the degree of coherence of different monitoring methods in (1) capturing short- and long-term cyanobacteria bloom dynamics and (2) identifying environmental drivers associated with bloom variability. Using western Lake Erie as a case study, we applied boosted regression tree (BRT) models to long-term time series of cyanobacteria bloom estimates from multiple in-situ and remote sensing approaches to quantify the relative influence of physico-chemical and meteorological drivers on bloom variability. Results of BRT models showed remarkable consistency with known ecological requirements of cyanobacteria (e.g., nutrient loading, water temperature, and tributary discharge). However, discrepancies in inter-annual and intra-seasonal bloom dynamics across monitoring approaches led to some inconsistencies in the relative importance, shape, and sign of the modeled relationships between select environmental drivers and bloom severity. This was especially true for variables characterized by high short-term variability, such as wind forcing. These discrepancies might have implications for our understanding of the role of different environmental drivers in regulating bloom dynamics, and subsequently for the development of models capable of informing management and decision making. Our results highlight the need to develop methods to integrate multiple data sources to better characterize bloom spatio-temporal variability and improve our ability to understand and predict cyanobacteria blooms.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.scitotenv.2016.10.023DOI Listing
January 2017

Engaging Stakeholders To Define Feasible and Desirable Agricultural Conservation in Western Lake Erie Watersheds.

Environ Sci Technol 2016 08 14;50(15):8135-45. Epub 2016 Jul 14.

Graham Sustainability Institute, University of Michigan , 625 E. Liberty Street, Suite #300, Ann Arbor, Michigan 48104, United States.

Widespread adoption of agricultural conservation measures in Lake Erie's Maumee River watershed may be required to reduce phosphorus loading that drives harmful algal blooms and hypoxia. We engaged agricultural and conservation stakeholders through a survey and workshops to determine which conservation practices to evaluate. We investigated feasible and desirable conservation practices using the Soil and Water Assessment Tool calibrated for streamflow, sediment, and nutrient loading near the Maumee River outlet. We found subsurface placement of phosphorus applications to be the individual practice most influential on March-July dissolved reactive phosphorus (DRP) loading from row croplands. Perennial cover crops and vegetated filter strips were most effective for reducing seasonal total phosphorus (TP) loading. We found that practices effective for reducing TP and DRP load were not always mutually beneficial, culminating in trade-offs among multiple Lake Erie phosphorus management goals. Adoption of practices at levels considered feasible to stakeholders led to nearly reaching TP targets for western Lake Erie on average years; however, adoption of practices at a rate that goes beyond what is currently considered feasible will likely be required to reach the DRP target.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/acs.est.6b01420DOI Listing
August 2016

Evaluating the Impact of Legacy P and Agricultural Conservation Practices on Nutrient Loads from the Maumee River Watershed.

Environ Sci Technol 2016 08 6;50(15):8146-54. Epub 2016 Jul 6.

Graham Sustainability Institute, University of Michigan , 625 East Liberty Street, Suite 300, Ann Arbor, Michigan 48104, United States.

The recent resurgence of hypoxia and harmful algal blooms in Lake Erie, driven substantially by phosphorus loads from agriculture, have led the United States and Canada to begin developing plans to meet new phosphorus load targets. To provide insight into which agricultural management options could help reach these targets, we tested alternative agricultural-land-use and land-management scenarios on phosphorus loads to Lake Erie. These scenarios highlight certain constraints on phosphorus load reductions from changes in the Maumee River Watershed (MRW), which contributes roughly half of the phosphorus load to the lake's western basin. We evaluate the effects on phosphorus loads under nutrient management strategies, reduction of fertilizer applications, employing vegetative buffers, and implementing widespread cover crops and alternative cropping changes. Results indicate that even if fertilizer application ceased, it may take years to see desired decreases in phosphorus loads, especially if we experience greater spring precipitation or snowmelt. Scenarios also indicate that widespread conversions to perennial crops that may be used for biofuel production are capable of substantially reducing phosphorus loads. This work demonstrates that a combination of legacy phosphorus, land management, land use, and climate should all be considered when seeking phosphorus-loading solutions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/acs.est.6b01421DOI Listing
August 2016

Assessing biophysical controls on Gulf of Mexico hypoxia through probabilistic modeling.

Ecol Appl 2015 Mar;25(2):492-505

A mechanistic model was developed to predict midsummer bottom-water dissolved oxygen (BWDO) concentration and hypoxic area on the Louisiana shelf of the northern Gulf of Mexico, USA (1985-2011). Because of its parsimonious formulation, the model possesses many of the benefits of simpler, more empirical models, in that it is computationally efficient and can rigorously account for uncertainty through Bayesian inference. At the same time, the model incorporates important biophysical processes such that its parameterization can be informed by field-measured biological and physical rates. The model is used to explore how freshwater flow, nutrient load, benthic oxygen demand, and wind velocity affect hypoxia on the western and eastern sections of the shelf, delineated by the Atchafalaya River outfall. The model explains over 70% of the variability in BWDO on both shelf sections, and outperforms linear regression models developed from the same input variables. Model results suggest that physical factors (i.e., wind and flow) control a larger portion of the year-to-year variability in hypoxia than previously thought, especially on the western shelf, though seasonal nutrient loads remain an important driver of hypoxia, as well. Unlike several previous Gulf hypoxia modeling studies, results do not indicate a temporal shift in the system's propensity for hypoxia formation (i.e., no regime change). Results do indicate that benthic oxygen demand is a substantial BWDO sink, and a better understanding of the long-term dynamics of this sink is required to better predict how the size of the hypoxic zone will respond to proposed reductions in nutrient loading.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1890/13-2257.1DOI Listing
March 2015

A scenario and forecast model for Gulf of Mexico hypoxic area and volume.

Environ Sci Technol 2013 Sep 4;47(18):10423-8. Epub 2013 Sep 4.

Graham Sustainability Institute, University of Michigan , Ann Arbor, Michigan 48104, United States.

For almost three decades, the relative size of the hypoxic region on the Louisiana-Texas continental shelf has drawn scientific and policy attention. During that time, both simple and complex models have been used to explore hypoxia dynamics and to provide management guidance relating the size of the hypoxic zone to key drivers. Throughout much of that development, analyses had to accommodate an apparent change in hypoxic sensitivity to loads and often cull observations due to anomalous meteorological conditions. Here, we describe an adaptation of our earlier, simple biophysical model, calibrated to revised hypoxic area estimates and new hypoxic volume estimates through Bayesian estimation. This application eliminates the need to cull observations and provides revised hypoxic extent estimates with uncertainties corresponding to different nutrient loading reduction scenarios. We compare guidance from this model application, suggesting an approximately 62% nutrient loading reduction is required to reduce Gulf hypoxia to the Action Plan goal of 5000 km(2), to that of previous applications. In addition, we describe for the first time, the corresponding response of hypoxic volume. We also analyze model results to test for increasing system sensitivity to hypoxia formation, but find no strong evidence of such change.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/es4025035DOI Listing
September 2013

Retrospective analysis of midsummer hypoxic area and volume in the northern Gulf of Mexico, 1985-2011.

Environ Sci Technol 2013 Sep 14;47(17):9808-15. Epub 2013 Aug 14.

School of Natural Resources & Environment, University of Michigan , Ann Arbor, Michigan 48109-1041, United States.

Robust estimates of hypoxic extent (both area and volume) are important for assessing the impacts of low dissolved oxygen on aquatic ecosystems at large spatial scales. Such estimates are also important for calibrating models linking hypoxia to causal factors, such as nutrient loading and stratification, and for informing management decisions. In this study, we develop a rigorous geostatistical modeling framework to estimate the hypoxic extent in the northern Gulf of Mexico from data collected during midsummer, quasi-synoptic monitoring cruises (1985-2011). Instead of a traditional interpolation-based approach, we use a simulation-based approach that yields more robust extent estimates and quantified uncertainty. The modeling framework also makes use of covariate information (i.e., trend variables such as depth and spatial position), to reduce estimation uncertainty. Furthermore, adjustments are made to account for observational bias resulting from the use of different sampling instruments in different years. Our results suggest an increasing trend in hypoxic layer thickness (p = 0.05) from 1985 to 2011, but less than significant increases in volume (p = 0.12) and area (p = 0.42). The uncertainties in the extent estimates vary with sampling network coverage and instrument type, and generally decrease over the study period.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/es400983gDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3823027PMC
September 2013

Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions.

Proc Natl Acad Sci U S A 2013 Apr 1;110(16):6448-52. Epub 2013 Apr 1.

Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA.

In 2011, Lake Erie experienced the largest harmful algal bloom in its recorded history, with a peak intensity over three times greater than any previously observed bloom. Here we show that long-term trends in agricultural practices are consistent with increasing phosphorus loading to the western basin of the lake, and that these trends, coupled with meteorological conditions in spring 2011, produced record-breaking nutrient loads. An extended period of weak lake circulation then led to abnormally long residence times that incubated the bloom, and warm and quiescent conditions after bloom onset allowed algae to remain near the top of the water column and prevented flushing of nutrients from the system. We further find that all of these factors are consistent with expected future conditions. If a scientifically guided management plan to mitigate these impacts is not implemented, we can therefore expect this bloom to be a harbinger of future blooms in Lake Erie.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1073/pnas.1216006110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3631662PMC
April 2013

Spatial and temporal trends in Lake Erie hypoxia, 1987-2007.

Environ Sci Technol 2013 Jan 3;47(2):899-905. Epub 2013 Jan 3.

Department of Global Ecology, Carnegie Institution for Science, Stanford, California 94305, USA.

Hypoxic conditions, defined as dissolved oxygen (DO) concentrations below 2 mg/L, are a regular summertime occurrence in Lake Erie, but the spatial extent has been poorly understood due to sparse sampling. We use geostatistical kriging and conditional realizations to provide quantitative estimates of the extent of hypoxia in the central basin of Lake Erie for August and September of 1987 to 2007, along with their associated uncertainties. The applied geostatistical approach combines the limited in situ DO measurements with auxiliary data selected using the Bayesian Information Criterion. Bathymetry and longitude are found to be highly significant in explaining the spatial distribution of DO, while satellite observations of sea surface temperature and satellite chlorophyll are not. The hypoxic extent was generally lowest in the mid-1990s, with the late 1980s (1987, 1988) and the 2000s (2003, 2005) experiencing the largest hypoxic zones. A simple exponential relationship based on the squared average measured bottom DO explains 97% of the estimated variability in the hypoxic extent. The change in the observed maximum extent between August and September is found to be sensitive to the corresponding variability in the hypolimnion thickness.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/es303401bDOI Listing
January 2013

Evaluating causes of trends in long-term dissolved reactive phosphorus loads to Lake Erie.

Environ Sci Technol 2012 Oct 21;46(19):10660-6. Epub 2012 Sep 21.

School of Natural Resources & Environment, University of Michigan, Ann Arbor, Michigan 48109, United States.

Renewed harmful algal blooms and hypoxia in Lake Erie have drawn significant attention to phosphorus loads, particularly increased dissolved reactive phosphorus (DRP) from highly agricultural watersheds. We use the Soil and Water Assessment Tool (SWAT) to model DRP in the agriculture-dominated Sandusky watershed for 1970-2010 to explore potential reasons for the recent increased DRP load from Lake Erie watersheds. We demonstrate that recent increased storm events, interacting with changes in fertilizer application timing and rate, as well as management practices that increase soil stratification and phosphorus accumulation at the soil surface, appear to drive the increasing DRP trend after the mid-1990s. This study is the first long-term, detailed analysis of DRP load estimation using SWAT.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/es302315dDOI Listing
October 2012

Quantifying the impacts of stratification and nutrient loading on hypoxia in the northern Gulf of Mexico.

Environ Sci Technol 2012 May 1;46(10):5489-96. Epub 2012 May 1.

School of Natural Resources & Environment, University of Michigan, Ann Arbor, Michigan 48109-1041, United States.

Stratification and nutrient loading are two primary factors leading to hypoxia in coastal systems. However, where these factors are temporally correlated, it can be difficult to isolate and quantify their individual impacts. This study provides a novel solution to this problem by determining the effect of stratification based on its spatial relationship with bottom-water dissolved oxygen (BWDO) concentration using a geostatistical regression. Ten years (1998-2007) of midsummer Gulf of Mexico BWDO measurements are modeled using stratification metrics along with trends based on spatial coordinates and bathymetry, which together explain 27-61% of the spatial variability in BWDO for individual years. Because stratification effects explain only a portion of the year-to-year variability in mean BWDO; the remaining variability is explained by other factors, with May nitrate plus nitrite river concentration the most important. Overall, 82% of the year-to-year variability in mean BWDO is explained. The results suggest that while both stratification and nutrients play important roles in determining the annual extent of midsummer hypoxia, reducing nutrient inputs alone will substantially reduce the average extent.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/es204481aDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3823025PMC
May 2012

Incidental oligotrophication of North American Great Lakes.

Environ Sci Technol 2011 Apr 21;45(8):3297-303. Epub 2011 Mar 21.

School of Natural Resources and Environment, University of Michigan , 440 Church St., Ann Arbor, Michigan 48109, United States.

Phytoplankton production is an important factor in determining both ecosystem stability and the provision of ecosystem goods and services. The expansive and economically important North American Great Lakes are subjected to multiple stressors and understanding their responses to those stresses is important for understanding system-wide ecological controls. Here we show gradual increases in spring silica concentration (an indicator of decreasing growth of the dominant diatoms) in all basins of Lakes Michigan and Huron (USA and Canadian waters) between 1983 and 2008. These changes indicate the lakes have undergone gradual oligotrophication coincident with and anticipated by nutrient management implementation. Slow declines in seasonal drawdown of silica (proxy for seasonal phytoplankton production) also occurred, until recent years, when lake-wide responses were punctuated by abrupt decreases, putting them in the range of oligotrophic Lake Superior. The timing of these dramatic production drops is coincident with expansion of populations of invasive dreissenid mussels, particularly quagga mussels, in each basin. The combined effect of nutrient mitigation and invasive species expansion demonstrates the challenges facing large-scale ecosystems and suggest the need for new management regimes for large ecosystems.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/es103892wDOI Listing
April 2011

Cattle, clean water, and climate change: policy choices for the Brazilian Agricultural Frontier.

Environ Sci Technol 2010 Nov 20;44(22):8377-84. Epub 2010 Oct 20.

School of Natural Resources and Environment, University of Michigan, Ann Arbor, Michigan 48103, USA.

In the Amazonian agricultural frontier, pasture for cattle ranching is an important and potentially hazardous form of land use because of sediment erosion as pastures degrade. This relationship between ranching, sediment load, and water quality is likely to further exacerbate environmental impacts, particularly in the context of climate change. We examine the role that river basin councils (RBCs) - a water governance option of Brazil's 1997 National Water Act - might play in managing this nonpoint-source pollution in the Amazônian state of Rondônia. We implement a simple coupled rancher-water system model to compare two potential governance options: a bulk water cleanup charge (BWC) implemented by RBCs and a land-use fine (LUF) for failing to maintain riparian buffers. We find no significant advantage of BWC over LUF in reducing sediment loading while keeping ranching profitable, under a changing climate. We also fail to find in Rondônia the important stake in water issues that has driven water reform elsewhere in Brazil. Moreover, the comparative success of reforestation programs suggests these programs may, in fact, have the potential to manage nonpoint-source agricultural pollution in the region.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/es1034014DOI Listing
November 2010

Gulf of Mexico hypoxia: exploring increasing sensitivity to nitrogen loads.

Environ Sci Technol 2010 Aug;44(15):5836-41

College of Environmental Science and Engineering, Peking University, The Key Laboratory of Water and Sediment Sciences, Ministry of Education, Beijing 100871, China.

Hypoxia is a critical issue in the Gulf of Mexico that has challenged management efforts in recent years by an increase in hypoxia sensitivity to nitrogen loads. Several mechanisms have been proposed to explain the recent increase in sensitivity. Two commonly cited mechanisms are bottom-water reducing conditions preventing nitrification and thus denitrification, leading to more N recycling and production of oxygen-consuming organic matter, and carryover of organic matter from previous years increasing oxygen demand, making the system more sensitive. We use models informed by these mechanisms and fit with Bayesian inference to explore changes in Gulf of Mexico hypoxia sensitivity. We show that a model including an annually fit parameter representing variation in the fraction of nutrient loading and recycling contributing to bottom water oxygen demand provides a good fit to observations and is not improved by explicit inclusion of organic matter carryover to subsequent years. Both models support two stepwise increases in system sensitivity during the period of record. This change in sensitivity has greatly increased the nutrient reduction needed to achieve the established hypoxia goal. If the Gulf remains at the current state of sensitivity, our analysis suggests a roughly 70% reduction of spring TN loads from the 1988-1996 average of 6083 ton/day may be required.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/es903521nDOI Listing
August 2010

Exploring estuarine nutrient susceptibility.

Environ Sci Technol 2009 May;43(10):3474-9

School of Natural Resources & Environment, University of Michigan, Ann Arbor, Michigan 48109, USA.

The susceptibility of estuaries to nutrient loading is an important issue that cuts across a range of management needs. We used a theory-driven but data-tested simple model to assist classifying estuaries according to their susceptibility to nutrients. This simple nutrient-driven phytoplankton model is based on fundamental principles of mass balance and empirical response functions for a wide variety of estuaries in the United States. Phytoplankton production was assumed to be stoichiometrically proportional to nitrogen load and an introduced "efficiency factor" intended to capture the myriad processes involved in converting nitrogen load to algal production. A Markov Chain Monte Carlo algorithm of Bayesian inference was then employed for parameter estimation. The model performed remarkably well for chlorophyll estimates, and the predicted estimates of primary production, grazing, and sinking losses are consistent with measurements reported in the literature from a wide array of systems. Analysis of the efficiency factor suggests that estuaries with the ratio of river inflow to estuarine volume (Q/V) greater than 2.0 per year are less susceptible to nutrient loads, and those with Q/V between 0.3 and 2.0 per year are moderately susceptible. This simple model analysis provides a first-order screening tool for estuarine susceptibility classification.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/es803401yDOI Listing
May 2009

Influence of climate and human activities on the relationship between watershed nitrogen input and river export.

Environ Sci Technol 2009 Mar;43(6):1916-22

University of Michigan, School of Natural Resources and Environment Dana Building, 440 Church Street, Ann Arbor, Michigan 48109-1041, USA.

River export of nitrogen (N) is influenced strongly by spatial variation in anthropogenic N inputs and climatic variation. We developed a model of riverine N export for 18 Lake Michigan Basin watersheds based on N budgets at 5-year intervals from 1974 to 1992. N inputs explained a high proportion of the spatial variation in river export but virtually none of the temporal variation, whereas between year N export was related to variation in discharge for over one-half of the rivers. A regression model of riverine N exports as an exponential function of N inputs and a powerfunction of annual water discharge accounted for 87% of the variation in annual total nitrogen fluxes over space and time. Application of this model to three scenarios of future land use, including business as usual, greater reliance on organic farming methods, and expanded corn-based ethanol production, and two climate scenarios, including increases in water discharge by 5% and 10%, suggests that riverine N export is likely to increase by as much as 24% in response to heavierfertilizer use for expanded corn production and a 10% increase in annual discharge. However, N export by rivers could decrease below present-day export through reduced reliance on commercial fertilizer use.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/es801985xDOI Listing
March 2009

Reassessing hypoxia forecasts for the Gulf of Mexico.

Environ Sci Technol 2007 Dec;41(23):8111-7

School of Natural Resources and Environment, University of Michigan, Ann Arbor 48109, USA.

Gulf of Mexico hypoxia has received considerable scientific and policy attention because of its potential ecological and economic impacts and implications for agriculture within its massive watershed. A 2000 assessment concluded that increased nitrate load to the Gulf since the 1950s was the primary cause of large-scale hypoxia areas. More recently, models have suggested that large-scale hypoxia did not start untilthe mid-1970s, and that a 40-45% nitrogen load reduction may be needed to reach the hypoxia area goal of the Hypoxia Action Plan. Recently, USGS revised nutrient load estimates to the Gulf, and the Action Plan reassessment has questioned the role of phosphorus versus nitrogen in controlling hypoxia. In this paper, we re-evaluate model simulations, hindcasts, and forecasts using revised nitrogen loads, and testthe ability of a phosphorus-driven version of the model to reproduce hypoxia trends. Our analysis suggests that, if phosphorus is limiting now, it became so because of relative increases in nitrogen loads during the 1970s and 1980s. While our model suggests nitrogen load reductions of 37-45% or phosphorus load reductions of 40-50% below the 1980-1996 average are needed, we caution that a phosphorus-only strategy is potentially dangerous, and suggest it would be prudent to reduce both.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/es0714235DOI Listing
December 2007
-->