Jordan S Read, PhD (Former Employee)
Science and Products
Quantifying the Impacts of Climate Change on Fish Growth and Production to Enable Sustainable Management of Diverse Inland Fisheries
Fisheries managers in Midwestern lakes and reservoirs are tasked with balancing multiple management objectives to help maintain healthy fish populations across a landscape of diverse lakes. As part of this, managers monitor fish growth and survival. Growth rates in particular are indicators of population health, and directly influence the effectiveness of regulations designed to protect...
Scoping the Feasibility of Incorporating Climate Change into Risk Assessments of Aquatic Invasive Species in the Upper Midwest
Aquatic invasive species threaten our lakes, streams, and wetlands. These species not only change the biology within the waterbody, but they can change the way we use those waterbodies and the resources they produce. Those changes may have large economic impacts, such as direct management costs and indirect costs to fisheries, tourism and commerce. These species can be small like zebra...
Water Data Visualizations
Water data visualizations are provocative visuals and captivating stories that inform, inspire, and empower people to address our Nation's most pressing water issues. USGS data science and visualization experts use visualizations to communicate water data in compelling and often interactive ways when static images or written narrative can’t effectively communicate the interconnectivity and...
Webinar: Variable Warming in Lakes of the Upper Midwest and Implications for Sport Fish
Check out this webinar to learn more about how warming temperatures are affecting lakes in the Midwest and the fish they support.
Fish Habitat Restoration to Promote Adaptation: Resilience of Sport Fish in Lakes of the Upper Midwest
Many Midwestern lakes are experiencing warming water temperatures as a result of climate change. In general, this change is causing coldwater fish species such as cisco and coolwater species such as walleye to decline. Meanwhile, warmer water species such as largemouth and smallmouth bass are increasing as temperatures warm. However, some fish populations are more vulnerable to these...
Developing Adaptation Strategies for Recreational and Tribal Fisheries in the Upper Midwest
Fisheries in the glacial lakes region of the upper Midwest are culturally, economically, and recreationally beneficial. Walleye, for instance, represent an important subsistence food source for some Wisconsin tribal nations and are also popular among recreational anglers. However, predicted ecological changes to these aquatic communities, such as an increase in invasive fish species, a...
Understanding Historical and Predicting Future Lake Temperatures in North and South Dakota
Lakes, reservoirs, and ponds are central and integral features of the North Central U.S. These water bodies provide aesthetic, cultural, and ecosystem services to surrounding wildlife and human communities. External impacts – such as climate change – can have significant impacts to these important parts of the region’s landscape. Understanding the responses of lakes to these drivers is...
“Hyperscale” Modeling to Understand and Predict Temperature Changes in Midwest Lakes
Many inland waters across the United States are experiencing warming water temperatures. The impacts of this warming on aquatic ecosystems are significant in many areas, causing problems for fisheries management, as many economically and ecologically important fish species are experiencing range shifts and population declines. Fisheries and natural resource managers need timely and...
sbtools: An R package for ScienceBase
Science is an increasingly collaborative endeavor. In an era of Web-enabled research, new tools reduce barriers to collaboration across traditional geographic and disciplinary divides and improve the quality and efficiency of science. Collaborative online code management has moved project collaboration from a manual process of email and thumb drives into a traceable, streamlined system...
An Assessment of Midwestern Lake and Stream Temperatures under Climate Change
Water temperatures are warming in lakes and streams, resulting in the loss of many native fish. Given clear passage, coldwater stream fishes can take refuge upstream when larger streams become too warm. Likewise, many Midwestern lakes “thermally stratify” resulting in warmer waters on top of deeper, cooler waters. Many of these lakes are connected to threatened streams. To date...
Continental-scale overview of stream primary productivity, its links to water quality, and consequences for aquatic carbon biogeochemistry
Streams and rivers have a limited spatial extent, but are increasingly recognized as key components of regional biogeochemical cycles. The collective metabolic processing of organisms, known as ecosystem metabolism, is centrally important to nutrient cycling and carbon fluxes in these environments, but is poorly integrated into emerging biogeochemical concepts. This line of inquiry lags...
Filter Total Items: 15
Compilation of multi-agency water temperature observations for U.S. streams, 1894-2022
This data release collates stream water temperature observations from across the United States from four data sources: The U.S. Geological Survey's National Water Information System (NWIS), Water Quality Portal (WQP), Spatial Hydro-Ecological Decision Systems temperature database (EcoSHEDS), and the U.S. Fish and Wildlife's NorWeST stream temperature database. These data were compiled...
Model predictions for heterogeneous stream-reservoir graph networks with data assimilation
This data release provides the predictions from stream temperature models described in Chen et al. 2021. Briefly, various deep learning and process-guided deep learning models were built to test improved performance of stream temperature predictions below reservoirs in the Delaware River Basin. The spatial extent of predictions was restricted to streams above the Delaware River at...
Predictions of lake water temperatures for eight reservoirs in Missouri US, 1980-2021
Lake temperature is an important environmental metric for understanding habitat suitability for many freshwater species and is especially useful when temperatures are predicted throughout the water column (known as temperature profiles). This dataset provides estimates of water temperature at half meter depths for eight reservoirs in Missouri, USA using version 3 of the General Lake...
Data release: Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning (Provisional Data Release)
These data are preliminary or provisional and are subject to revision. They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the...
Daily surface temperature predictions for 185,549 U.S. lakes with associated observations and meteorological conditions (1980-2020)
Daily lake surface temperatures estimates for 185,549 lakes across the contiguous United States from 1980 to 2020 generated using an entity-aware long short-term memory deep learning model. In-situ measurements used for model training and evaluation are from 12,227 lakes and are included as well as daily meteorological conditions and lake properties. Median per-lake estimated error found...
Multi-task Deep Learning for Water Temperature and Streamflow Prediction (ver. 1.1, June 2022)
This item contains data and code used in experiments that produced the results for Sadler et. al (2022) (see below for full reference). We ran five experiments for the analysis, Experiment A, Experiment B, Experiment C, Experiment D, and Experiment AuxIn. Experiment A tested multi-task learning for predicting streamflow with 25 years of training data and using a different model for each...
Lake Biogeochemical Model Output for One Retrospective and 12 Future Climate Runs in Northern Wisconsin & Michigan, USA
This dataset contains modeled daily lake area, volume, constituent mass, and biogeochemical rates for 3,692 lakes in the Northern Highlands Lake District (NHLD) for one retrospective model run (1986-2010) and 12 model runs under future climate scenarios. This dataset was created using published tools developed to simulate detailed hydrological and biogeochemical fluxes for thousands of...
Table and accompanying photographs for biogeomorphic classification of shorebird nesting sites on the U.S. Atlantic coast from March to September, 2016
Atlantic coast piping plover (Charadrius melodus) nest sites are typically found on low-lying beach and dune systems, which respond rapidly to coastal processes like sediment overwash, inlet formation, and island migration that are sensitive to climate-related changes in storminess and the rate of sea-level rise. Data were obtained to understand piping plover habitat distribution and use...
Predicting water temperature in the Delaware River Basin
Daily temperature predictions in the Delaware River Basin (DRB) can inform decision makers who can use cold-water reservoir releases to maintain thermal habitat for sensitive fish and mussel species. This data release supports a variety of flow and water temperature modeling efforts and provides the inputs and outputs of both machine learning and process-based modeling methods across 456...
Data release: Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes
Climate change and land use change have been shown to influence lake temperatures and water clarity in different ways. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we focused on improving prediction accuracy for daily water temperature profiles and optical habitat in 881 lakes in Minnesota during 1980-2018. The...
Data release: Process-based predictions of lake water temperature in the Midwest US
Climate change has been shown to influence lake temperatures in different ways. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we focused on improving prediction accuracy for daily water temperature profiles in 7,150 lakes in Minnesota and Wisconsin during 1980-2019. The data are organized into these items...
Data release: A large-scale database of modeled contemporary and future water temperature data for 10,774 Michigan, Minnesota and Wisconsin Lakes
Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate...
Filter Total Items: 58
Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations
Deep learning (DL) models are increasingly used to forecast water quality variables for use in decision making. Ingesting recent observations of the forecasted variable has been shown to greatly increase model performance at monitored locations; however, observations are not collected at all locations, and methods are not yet well developed for DL models for optimally ingesting recent...
Authors
Jacob Aaron Zwart, Jeremy Alejandro Diaz, Scott Douglas Hamshaw, Samantha K. Oliver, Jesse Cleveland Ross, Margaux Jeanne Sleckman, Alison P. Appling, Hayley R. Corson-Dosch, Xiaowei Jia, Jordan S Read, Jeffrey M Sadler, Theodore Paul Thompson, David Watkins, Elaheh (Ellie) White
Indicators of the effects of climate change on freshwater ecosystems
Freshwater ecosystems, including lakes, streams, and wetlands, are responsive to climate change and other natural and anthropogenic stresses. These ecosystems are frequently hydrologically and ecologically connected with one another and their surrounding landscapes, thereby integrating changes throughout their watersheds. The responses of any given freshwater ecosystem to climate change...
Authors
Kevin C. Rose, Britta Bierwagen, Scott D. Bridgham, Daren Carlisle, Charles P. Hawkins, N. LeRoy Poff, Jordan Read, Jason Rohr, Jasmine E. Saros, Craig E. Williamson
Connecting habitat to species abundance: The role of light and temperature on the abundance of walleye in lakes
Walleye (Sander vitreus) are an ecologically important species managed for recreational, tribal, and commercial harvest. Walleye prefer cool water and low light conditions, and therefore changing water temperature and clarity potentially impacts walleye habitat and populations across the landscape. Using survey data collected from 1993 to 2018 from 312 lakes in Minnesota, we evaluated...
Authors
Shad Mahlum, Kelsey Vitense, Hayley R. Corson-Dosch, Lindsay Platt, Jordan Read, Patrick J Schmalz, Melissa Treml, Gretchen J.A. Hansen
Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions
Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow...
Authors
Jacob Aaron Zwart, Samantha K. Oliver, William Watkins, Jeffrey Michael Sadler, Alison P. Appling, Hayley R. Corson-Dosch, Xiaowei Jia, Vipin Kumar, Jordan Read
Physics-guided architecture (PGA) of LSTM models for uncertainty quantification in lake temperature modeling
This chapter focuses on meeting the need to produce neural network outputs that are physically consistent and also express uncertainties, a rare combination to date. It explains the effectiveness of physics-guided architecture - long-short-term-memory (PGA-LSTM) in achieving better generalizability and physical consistency over data collected from Lake Mendota in Wisconsin and Falling...
Authors
Arka Daw, R. Quinn Thomas, Cayelan C. Carey, Jordan Read, Alison P. Appling, Anuj Karpatne
Physics-guided recurrent neural networks for predicting lake water temperature
This chapter presents a physics-guided recurrent neural network model (PGRNN) for predicting water temperature in lake systems. Standard machine learning (ML) methods, especially deep learning models, often require a large amount of labeled training samples, which are often not available in scientific problems due to the substantial human labor and material costs associated with data...
Authors
Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan Read, Jacob Aaron Zwart, Michael Steinbach, Vipin Kumar
Physics-guided neural networks (PGNN): An application in lake temperature modeling
This chapter introduces a framework for combining scientific knowledge of physics-based models with neural networks to advance scientific discovery. It explains termed physics-guided neural networks (PGNN), leverages the output of physics-based model simulations along with observational features in a hybrid modeling setup to generate predictions using a neural network architecture. Data...
Authors
Arka Daw, Anuj Karpatne, William Watkins, Jordan Read, Vipin Kumar
Heat budget of lakes
This article gives an overview of the heat fluxes between lakes and their environment. The heat budget of most lakes is dominated by heat fluxes at the lake surface, especially shortwave radiation, incoming and outgoing longwave radiation, and the latent heat flux. The seasonality of these fluxes is the most important driver for seasonal mixing processes in lakes. Changes in heat fluxes...
Authors
Martin Schmid, Jordan Read
Daily surface temperatures for 185,549 lakes in the conterminous United States estimated using deep learning (1980–2020)
The dataset described here includes estimates of historical (1980–2020) daily surface water temperature, lake metadata, and daily weather conditions for lakes bigger than 4 ha in the conterminous United States (n = 185,549), and also in situ temperature observations for a subset of lakes (n = 12,227). Estimates were generated using a long short-term memory deep learning model and...
Authors
Jared D. Willard, Jordan Read, Simon Nemer Topp, Gretchen J. A. Hansen, Vipin Kumar
Invertibility aware integration of static and time-series data: An application to lake temperature modeling
Accurate predictions of water temperature are the foundation for many decisions and regulations, with direct impacts on water quality, fishery yields, and power production. Building accurate broad-scale models for lake temperature prediction remains challenging in practice due to the variability in the data distribution across different lake systems monitored by static and time-series...
Authors
Kshitij Tayal, Xiaowei Jia, Rahul Ghosh, Jared Willard, Jordan Read, Vipin Kumar
Multi-task deep learning of daily streamflow and water temperature
Deep learning (DL) models can accurately predict many hydrologic variables including streamflow and water temperature; however, these models have typically predicted hydrologic variables independently. This study explored the benefits of modeling two interdependent variables, daily average streamflow and daily average stream water temperature, together using multi-task DL. A multi-task...
Authors
Jeffrey Michael Sadler, Alison P. Appling, Jordan Read, Samantha K. Oliver, Xiaowei Jia, Jacob Aaron Zwart, Vipin Kumar
Machine learning for understanding inland water quantity, quality, and ecology
This chapter provides an overview of machine learning models and their applications to the science of inland waters. Such models serve a wide range of purposes for science and management: predicting water quality, quantity, or ecological dynamics across space, time, or hypothetical scenarios; vetting and distilling raw data for further modeling or analysis; generating and exploring...
Authors
Alison P. Appling, Samantha K. Oliver, Jordan Read, Jeffrey Michael Sadler, Jacob Aaron Zwart
Non-USGS Publications**
Watras CJ, M Morrow, K Morrison, S Scannell, S Yaziciaglu, JS Read, YH Hu, PC Hanson, TK Kratz. 2013. Evaluation of wireless sensor networks (WSNs) for remote wetland monitoring: Design and initial results. Environmental Monitoring and Assessment. doi:10.1007/s10661-013-3424-8
Read JS, KC Rose. 2013. Physical responses of small temperate lakes to variation in dissolved organic carbon concentrations. Limnology and Oceanography. 58: 921-931. doi:10.4319/lo.2013.58.3.0921[Link]
Youngblut ND, A Shade, JS Read, KD McMahon, RJ Whitaker. 2013. Lineage-specific responses to environmental change in microbial communities. Applied and Environmental Microbiology. 79: 39-47. doi:10.1128/AEM.02226-12
Read JS. Physical processes in small temperate lakes. 2012. PhD Dissertation, University of Wisconsin-Madison
Samal NR, DC Pierson, E Schneiderman, Y Huang, JS Read, A Anandhi, EM Owens. 2012. Impact of climate change on Cannonsville reservoir thermal structure in the New York City Water Supply. Water Quality Research Journal of Canada. 47: 389-405
Staehr PA, JPA Christensen, RD Batt, JS Read. 2012. Ecosystem metabolism in a stratified lake. Limnology and Oceanography. 57: 1317-133
Shade A, JS Read, ND Youngblut, N Fierer, R Knight, TK Kratz, NR Lottig, EE Roden, EH Stanley, J Stombaugh, RJ Whitaker, CH Wu, KD McMahon. 2012. Microbial communities are resilient after a whole-ecosystem disturbance. The ISME Journal. 6: 2153-2167. doi:10.1038/ismej.2012.66
Read JS, DP Hamilton, AR Desai, KC Rose, S MacIntyre, JD Lenters, R Smyth, PC Hanson, JJ Cole, PA Staehr, JA Rusak, DC Pierson, JD Brookes, A Laas, CH Wu. 2012. Lake-size dependency of wind shear and convection as controls on gas exchange. Geophysical Research Letters. 39: L09405. doi:10.1029/2012GL051886
Gaeta JW, JS Read, JF Kitchell, SR Carpenter. 2012. Eradication via destratification: Whole-lake mixing to selectively remove rainbow smelt, a cold-water invasive species. Ecological Applications. 22: 817-827
Kara EL, PC Hanson, DP Hamilton, M Hipsey, KD McMahon, JS Read, LA Winslow, J Dedrick, KC Rose, CC Carey, S Bertilsson, D Motta-Marques, L Beversdorf, T Miller, CH Wu, YF Hsieh, E Gaiser, TK Kratz. 2012. Time-scale dependence in numerical simulations: Assessment of physical, chemical, and biological predictions in a stratified lake from scales of hours to months. Environmental Modelling and Software. 35: 104-121
Read JS, DP Hamilton, ID Jones, K Muraoka, LA Winslow, R Kroiss, CH Wu, E Gaiser. 2011. Derivation of lake mixing and stratification indices from high-resolution lake buoy data. Environmental Modelling and Software. 26: 1325-1336
Shade A, JS Read, D Welkie, TK Kratz, CH Wu, KD McMahon. 2011. Resistance, resilience, and recovery: Aquatic bacterial dynamics after water column disturbance. Environmental Microbiology. 13: 2752-2767
Read JS, A Shade, CH Wu, A Gorzalski, KD McMahon. 2011. "Gradual Entrainment Lake Inverter" (GELI): A novel device for experimental lake mixing. Limnology and Oceanography: Methods. 9:14-25
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Climate Change and Freshwater Fish
Lakes in Wisconsin are getting warmer, and fish communities are changing as a result. Understanding recent trends and anticipating future changes can help decision-makers protect resilient populations, adapt to new conditions, and effectively communicate realistic expectations.
Science and Products
Quantifying the Impacts of Climate Change on Fish Growth and Production to Enable Sustainable Management of Diverse Inland Fisheries
Fisheries managers in Midwestern lakes and reservoirs are tasked with balancing multiple management objectives to help maintain healthy fish populations across a landscape of diverse lakes. As part of this, managers monitor fish growth and survival. Growth rates in particular are indicators of population health, and directly influence the effectiveness of regulations designed to protect...
Scoping the Feasibility of Incorporating Climate Change into Risk Assessments of Aquatic Invasive Species in the Upper Midwest
Aquatic invasive species threaten our lakes, streams, and wetlands. These species not only change the biology within the waterbody, but they can change the way we use those waterbodies and the resources they produce. Those changes may have large economic impacts, such as direct management costs and indirect costs to fisheries, tourism and commerce. These species can be small like zebra...
Water Data Visualizations
Water data visualizations are provocative visuals and captivating stories that inform, inspire, and empower people to address our Nation's most pressing water issues. USGS data science and visualization experts use visualizations to communicate water data in compelling and often interactive ways when static images or written narrative can’t effectively communicate the interconnectivity and...
Webinar: Variable Warming in Lakes of the Upper Midwest and Implications for Sport Fish
Check out this webinar to learn more about how warming temperatures are affecting lakes in the Midwest and the fish they support.
Fish Habitat Restoration to Promote Adaptation: Resilience of Sport Fish in Lakes of the Upper Midwest
Many Midwestern lakes are experiencing warming water temperatures as a result of climate change. In general, this change is causing coldwater fish species such as cisco and coolwater species such as walleye to decline. Meanwhile, warmer water species such as largemouth and smallmouth bass are increasing as temperatures warm. However, some fish populations are more vulnerable to these...
Developing Adaptation Strategies for Recreational and Tribal Fisheries in the Upper Midwest
Fisheries in the glacial lakes region of the upper Midwest are culturally, economically, and recreationally beneficial. Walleye, for instance, represent an important subsistence food source for some Wisconsin tribal nations and are also popular among recreational anglers. However, predicted ecological changes to these aquatic communities, such as an increase in invasive fish species, a...
Understanding Historical and Predicting Future Lake Temperatures in North and South Dakota
Lakes, reservoirs, and ponds are central and integral features of the North Central U.S. These water bodies provide aesthetic, cultural, and ecosystem services to surrounding wildlife and human communities. External impacts – such as climate change – can have significant impacts to these important parts of the region’s landscape. Understanding the responses of lakes to these drivers is...
“Hyperscale” Modeling to Understand and Predict Temperature Changes in Midwest Lakes
Many inland waters across the United States are experiencing warming water temperatures. The impacts of this warming on aquatic ecosystems are significant in many areas, causing problems for fisheries management, as many economically and ecologically important fish species are experiencing range shifts and population declines. Fisheries and natural resource managers need timely and...
sbtools: An R package for ScienceBase
Science is an increasingly collaborative endeavor. In an era of Web-enabled research, new tools reduce barriers to collaboration across traditional geographic and disciplinary divides and improve the quality and efficiency of science. Collaborative online code management has moved project collaboration from a manual process of email and thumb drives into a traceable, streamlined system...
An Assessment of Midwestern Lake and Stream Temperatures under Climate Change
Water temperatures are warming in lakes and streams, resulting in the loss of many native fish. Given clear passage, coldwater stream fishes can take refuge upstream when larger streams become too warm. Likewise, many Midwestern lakes “thermally stratify” resulting in warmer waters on top of deeper, cooler waters. Many of these lakes are connected to threatened streams. To date...
Continental-scale overview of stream primary productivity, its links to water quality, and consequences for aquatic carbon biogeochemistry
Streams and rivers have a limited spatial extent, but are increasingly recognized as key components of regional biogeochemical cycles. The collective metabolic processing of organisms, known as ecosystem metabolism, is centrally important to nutrient cycling and carbon fluxes in these environments, but is poorly integrated into emerging biogeochemical concepts. This line of inquiry lags...
Filter Total Items: 15
Compilation of multi-agency water temperature observations for U.S. streams, 1894-2022
This data release collates stream water temperature observations from across the United States from four data sources: The U.S. Geological Survey's National Water Information System (NWIS), Water Quality Portal (WQP), Spatial Hydro-Ecological Decision Systems temperature database (EcoSHEDS), and the U.S. Fish and Wildlife's NorWeST stream temperature database. These data were compiled...
Model predictions for heterogeneous stream-reservoir graph networks with data assimilation
This data release provides the predictions from stream temperature models described in Chen et al. 2021. Briefly, various deep learning and process-guided deep learning models were built to test improved performance of stream temperature predictions below reservoirs in the Delaware River Basin. The spatial extent of predictions was restricted to streams above the Delaware River at...
Predictions of lake water temperatures for eight reservoirs in Missouri US, 1980-2021
Lake temperature is an important environmental metric for understanding habitat suitability for many freshwater species and is especially useful when temperatures are predicted throughout the water column (known as temperature profiles). This dataset provides estimates of water temperature at half meter depths for eight reservoirs in Missouri, USA using version 3 of the General Lake...
Data release: Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning (Provisional Data Release)
These data are preliminary or provisional and are subject to revision. They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the...
Daily surface temperature predictions for 185,549 U.S. lakes with associated observations and meteorological conditions (1980-2020)
Daily lake surface temperatures estimates for 185,549 lakes across the contiguous United States from 1980 to 2020 generated using an entity-aware long short-term memory deep learning model. In-situ measurements used for model training and evaluation are from 12,227 lakes and are included as well as daily meteorological conditions and lake properties. Median per-lake estimated error found...
Multi-task Deep Learning for Water Temperature and Streamflow Prediction (ver. 1.1, June 2022)
This item contains data and code used in experiments that produced the results for Sadler et. al (2022) (see below for full reference). We ran five experiments for the analysis, Experiment A, Experiment B, Experiment C, Experiment D, and Experiment AuxIn. Experiment A tested multi-task learning for predicting streamflow with 25 years of training data and using a different model for each...
Lake Biogeochemical Model Output for One Retrospective and 12 Future Climate Runs in Northern Wisconsin & Michigan, USA
This dataset contains modeled daily lake area, volume, constituent mass, and biogeochemical rates for 3,692 lakes in the Northern Highlands Lake District (NHLD) for one retrospective model run (1986-2010) and 12 model runs under future climate scenarios. This dataset was created using published tools developed to simulate detailed hydrological and biogeochemical fluxes for thousands of...
Table and accompanying photographs for biogeomorphic classification of shorebird nesting sites on the U.S. Atlantic coast from March to September, 2016
Atlantic coast piping plover (Charadrius melodus) nest sites are typically found on low-lying beach and dune systems, which respond rapidly to coastal processes like sediment overwash, inlet formation, and island migration that are sensitive to climate-related changes in storminess and the rate of sea-level rise. Data were obtained to understand piping plover habitat distribution and use...
Predicting water temperature in the Delaware River Basin
Daily temperature predictions in the Delaware River Basin (DRB) can inform decision makers who can use cold-water reservoir releases to maintain thermal habitat for sensitive fish and mussel species. This data release supports a variety of flow and water temperature modeling efforts and provides the inputs and outputs of both machine learning and process-based modeling methods across 456...
Data release: Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes
Climate change and land use change have been shown to influence lake temperatures and water clarity in different ways. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we focused on improving prediction accuracy for daily water temperature profiles and optical habitat in 881 lakes in Minnesota during 1980-2018. The...
Data release: Process-based predictions of lake water temperature in the Midwest US
Climate change has been shown to influence lake temperatures in different ways. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we focused on improving prediction accuracy for daily water temperature profiles in 7,150 lakes in Minnesota and Wisconsin during 1980-2019. The data are organized into these items...
Data release: A large-scale database of modeled contemporary and future water temperature data for 10,774 Michigan, Minnesota and Wisconsin Lakes
Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate...
Filter Total Items: 58
Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations
Deep learning (DL) models are increasingly used to forecast water quality variables for use in decision making. Ingesting recent observations of the forecasted variable has been shown to greatly increase model performance at monitored locations; however, observations are not collected at all locations, and methods are not yet well developed for DL models for optimally ingesting recent...
Authors
Jacob Aaron Zwart, Jeremy Alejandro Diaz, Scott Douglas Hamshaw, Samantha K. Oliver, Jesse Cleveland Ross, Margaux Jeanne Sleckman, Alison P. Appling, Hayley R. Corson-Dosch, Xiaowei Jia, Jordan S Read, Jeffrey M Sadler, Theodore Paul Thompson, David Watkins, Elaheh (Ellie) White
Indicators of the effects of climate change on freshwater ecosystems
Freshwater ecosystems, including lakes, streams, and wetlands, are responsive to climate change and other natural and anthropogenic stresses. These ecosystems are frequently hydrologically and ecologically connected with one another and their surrounding landscapes, thereby integrating changes throughout their watersheds. The responses of any given freshwater ecosystem to climate change...
Authors
Kevin C. Rose, Britta Bierwagen, Scott D. Bridgham, Daren Carlisle, Charles P. Hawkins, N. LeRoy Poff, Jordan Read, Jason Rohr, Jasmine E. Saros, Craig E. Williamson
Connecting habitat to species abundance: The role of light and temperature on the abundance of walleye in lakes
Walleye (Sander vitreus) are an ecologically important species managed for recreational, tribal, and commercial harvest. Walleye prefer cool water and low light conditions, and therefore changing water temperature and clarity potentially impacts walleye habitat and populations across the landscape. Using survey data collected from 1993 to 2018 from 312 lakes in Minnesota, we evaluated...
Authors
Shad Mahlum, Kelsey Vitense, Hayley R. Corson-Dosch, Lindsay Platt, Jordan Read, Patrick J Schmalz, Melissa Treml, Gretchen J.A. Hansen
Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions
Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow...
Authors
Jacob Aaron Zwart, Samantha K. Oliver, William Watkins, Jeffrey Michael Sadler, Alison P. Appling, Hayley R. Corson-Dosch, Xiaowei Jia, Vipin Kumar, Jordan Read
Physics-guided architecture (PGA) of LSTM models for uncertainty quantification in lake temperature modeling
This chapter focuses on meeting the need to produce neural network outputs that are physically consistent and also express uncertainties, a rare combination to date. It explains the effectiveness of physics-guided architecture - long-short-term-memory (PGA-LSTM) in achieving better generalizability and physical consistency over data collected from Lake Mendota in Wisconsin and Falling...
Authors
Arka Daw, R. Quinn Thomas, Cayelan C. Carey, Jordan Read, Alison P. Appling, Anuj Karpatne
Physics-guided recurrent neural networks for predicting lake water temperature
This chapter presents a physics-guided recurrent neural network model (PGRNN) for predicting water temperature in lake systems. Standard machine learning (ML) methods, especially deep learning models, often require a large amount of labeled training samples, which are often not available in scientific problems due to the substantial human labor and material costs associated with data...
Authors
Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan Read, Jacob Aaron Zwart, Michael Steinbach, Vipin Kumar
Physics-guided neural networks (PGNN): An application in lake temperature modeling
This chapter introduces a framework for combining scientific knowledge of physics-based models with neural networks to advance scientific discovery. It explains termed physics-guided neural networks (PGNN), leverages the output of physics-based model simulations along with observational features in a hybrid modeling setup to generate predictions using a neural network architecture. Data...
Authors
Arka Daw, Anuj Karpatne, William Watkins, Jordan Read, Vipin Kumar
Heat budget of lakes
This article gives an overview of the heat fluxes between lakes and their environment. The heat budget of most lakes is dominated by heat fluxes at the lake surface, especially shortwave radiation, incoming and outgoing longwave radiation, and the latent heat flux. The seasonality of these fluxes is the most important driver for seasonal mixing processes in lakes. Changes in heat fluxes...
Authors
Martin Schmid, Jordan Read
Daily surface temperatures for 185,549 lakes in the conterminous United States estimated using deep learning (1980–2020)
The dataset described here includes estimates of historical (1980–2020) daily surface water temperature, lake metadata, and daily weather conditions for lakes bigger than 4 ha in the conterminous United States (n = 185,549), and also in situ temperature observations for a subset of lakes (n = 12,227). Estimates were generated using a long short-term memory deep learning model and...
Authors
Jared D. Willard, Jordan Read, Simon Nemer Topp, Gretchen J. A. Hansen, Vipin Kumar
Invertibility aware integration of static and time-series data: An application to lake temperature modeling
Accurate predictions of water temperature are the foundation for many decisions and regulations, with direct impacts on water quality, fishery yields, and power production. Building accurate broad-scale models for lake temperature prediction remains challenging in practice due to the variability in the data distribution across different lake systems monitored by static and time-series...
Authors
Kshitij Tayal, Xiaowei Jia, Rahul Ghosh, Jared Willard, Jordan Read, Vipin Kumar
Multi-task deep learning of daily streamflow and water temperature
Deep learning (DL) models can accurately predict many hydrologic variables including streamflow and water temperature; however, these models have typically predicted hydrologic variables independently. This study explored the benefits of modeling two interdependent variables, daily average streamflow and daily average stream water temperature, together using multi-task DL. A multi-task...
Authors
Jeffrey Michael Sadler, Alison P. Appling, Jordan Read, Samantha K. Oliver, Xiaowei Jia, Jacob Aaron Zwart, Vipin Kumar
Machine learning for understanding inland water quantity, quality, and ecology
This chapter provides an overview of machine learning models and their applications to the science of inland waters. Such models serve a wide range of purposes for science and management: predicting water quality, quantity, or ecological dynamics across space, time, or hypothetical scenarios; vetting and distilling raw data for further modeling or analysis; generating and exploring...
Authors
Alison P. Appling, Samantha K. Oliver, Jordan Read, Jeffrey Michael Sadler, Jacob Aaron Zwart
Non-USGS Publications**
Watras CJ, M Morrow, K Morrison, S Scannell, S Yaziciaglu, JS Read, YH Hu, PC Hanson, TK Kratz. 2013. Evaluation of wireless sensor networks (WSNs) for remote wetland monitoring: Design and initial results. Environmental Monitoring and Assessment. doi:10.1007/s10661-013-3424-8
Read JS, KC Rose. 2013. Physical responses of small temperate lakes to variation in dissolved organic carbon concentrations. Limnology and Oceanography. 58: 921-931. doi:10.4319/lo.2013.58.3.0921[Link]
Youngblut ND, A Shade, JS Read, KD McMahon, RJ Whitaker. 2013. Lineage-specific responses to environmental change in microbial communities. Applied and Environmental Microbiology. 79: 39-47. doi:10.1128/AEM.02226-12
Read JS. Physical processes in small temperate lakes. 2012. PhD Dissertation, University of Wisconsin-Madison
Samal NR, DC Pierson, E Schneiderman, Y Huang, JS Read, A Anandhi, EM Owens. 2012. Impact of climate change on Cannonsville reservoir thermal structure in the New York City Water Supply. Water Quality Research Journal of Canada. 47: 389-405
Staehr PA, JPA Christensen, RD Batt, JS Read. 2012. Ecosystem metabolism in a stratified lake. Limnology and Oceanography. 57: 1317-133
Shade A, JS Read, ND Youngblut, N Fierer, R Knight, TK Kratz, NR Lottig, EE Roden, EH Stanley, J Stombaugh, RJ Whitaker, CH Wu, KD McMahon. 2012. Microbial communities are resilient after a whole-ecosystem disturbance. The ISME Journal. 6: 2153-2167. doi:10.1038/ismej.2012.66
Read JS, DP Hamilton, AR Desai, KC Rose, S MacIntyre, JD Lenters, R Smyth, PC Hanson, JJ Cole, PA Staehr, JA Rusak, DC Pierson, JD Brookes, A Laas, CH Wu. 2012. Lake-size dependency of wind shear and convection as controls on gas exchange. Geophysical Research Letters. 39: L09405. doi:10.1029/2012GL051886
Gaeta JW, JS Read, JF Kitchell, SR Carpenter. 2012. Eradication via destratification: Whole-lake mixing to selectively remove rainbow smelt, a cold-water invasive species. Ecological Applications. 22: 817-827
Kara EL, PC Hanson, DP Hamilton, M Hipsey, KD McMahon, JS Read, LA Winslow, J Dedrick, KC Rose, CC Carey, S Bertilsson, D Motta-Marques, L Beversdorf, T Miller, CH Wu, YF Hsieh, E Gaiser, TK Kratz. 2012. Time-scale dependence in numerical simulations: Assessment of physical, chemical, and biological predictions in a stratified lake from scales of hours to months. Environmental Modelling and Software. 35: 104-121
Read JS, DP Hamilton, ID Jones, K Muraoka, LA Winslow, R Kroiss, CH Wu, E Gaiser. 2011. Derivation of lake mixing and stratification indices from high-resolution lake buoy data. Environmental Modelling and Software. 26: 1325-1336
Shade A, JS Read, D Welkie, TK Kratz, CH Wu, KD McMahon. 2011. Resistance, resilience, and recovery: Aquatic bacterial dynamics after water column disturbance. Environmental Microbiology. 13: 2752-2767
Read JS, A Shade, CH Wu, A Gorzalski, KD McMahon. 2011. "Gradual Entrainment Lake Inverter" (GELI): A novel device for experimental lake mixing. Limnology and Oceanography: Methods. 9:14-25
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Climate Change and Freshwater Fish
Lakes in Wisconsin are getting warmer, and fish communities are changing as a result. Understanding recent trends and anticipating future changes can help decision-makers protect resilient populations, adapt to new conditions, and effectively communicate realistic expectations.