The Lake-Catchment (LakeCat) Dataset: characterizing landscape features for lake basins within the conterminous USA

Expanding the Application of Sentinel-2 Chlorophyll Monitoring across United States Lakes

Eutrophication of inland lakes poses various societal and ecological threats, making water quality monitoring crucial. Satellites provide a comprehensive and cost-effective supplement to traditional in situ sampling. The Sentinel-2 MultiSpectral Instrument (S2 MSI) offers unique spectral bands positioned to quantify chlorophyll a, a water-quality and trophic-state indicator, along with fine spatial resolution, enabling the monitoring of small waterbodies. In this study, two algorithms-the Maximum Chlorophyll Index (MCI) and the Normalized Difference Chlorophyll Index (NDCI)-were applied to S2 MSI data. They were calibrated and validated using in situ chlorophyll a measurements for 103 lakes across the contiguous U.S. Both algorithms were tested using top-of-atmosphere reflectances (ρ t), Rayleigh-corrected reflectances (ρ s), and remote sensing reflectances (R rs ). MCI slightly outperformed NDCI across all reflectance products. MCI using ρ t showed the best overall performance, with a mean absolute error factor of 2.08 and a mean bias factor of 1.15. Conversion of derived chlorophyll a to trophic state improved the potential for management applications, with 82% accuracy using a binary classification. We report algorithm-to-chlorophyll-a conversions that show potential for application across the U.S., demonstrating that S2 can serve as a monitoring tool for inland lakes across broad spatial scales.

National hydrologic connectivity classification links wetlands with stream water quality

Wetland hydrologic connections to downstream waters influence stream water quality. However, no systematic approach for characterizing this connectivity exists. Here using physical principles, we categorized conterminous US freshwater wetlands into four hydrologic connectivity classes based on stream contact and flowpath depth to the nearest stream: riparian, non-riparian shallow, non-riparian mid-depth and non-riparian deep. These classes were heterogeneously distributed over the conterminous United States; for example, riparian dominated the south-eastern and Gulf coasts, while non-riparian deep dominated the Upper Midwest and High Plains. Analysis of a national stream dataset indicated acidification and organic matter brownification increased with connectivity. Eutrophication and sedimentation decreased with wetland area but did not respond to connectivity. This classification advances our mechanistic understanding of wetland influences on water quality nationally and could be applied globally.

Global hydro-environmental lake characteristics at high spatial resolution

Here we introduce the LakeATLAS dataset, which provides a broad range of hydro-environmental characteristics for more than 1.4 million lakes and reservoirs globally with an area of at least 10 ha. LakeATLAS forms part of the larger HydroATLAS data repository and expands the existing datasets of sub-basin and river reach descriptors by adding equivalent information for lakes and reservoirs in a compatible structure. Matching its HydroATLAS counterparts, version 1.0 of LakeATLAS contains data for 56 variables, partitioned into 281 individual attributes and organized in six categories: hydrology; physiography; climate; land cover & use; soils & geology; and anthropogenic influences. LakeATLAS derives these attributes by processing and reformatting original data from well-established global digital maps at 15 arc-second (~500 m) grid cell resolution and assigns the information spatially to each lake by aggregating it within the lake, in a 3-km vicinity buffer around the lake, and/or within the entire upstream drainage area of the lake. The standardized format of LakeATLAS ensures versatile applicability in hydro-ecological assessments from regional to global scales.

Measurement(s)	hydro-environmental characteristics • lake • water body • hydrographic feature
Technology Type(s)	digital curation
Sample Characteristic - Environment	freshwater environment • aquatic environment
Sample Characteristic - Location	Earth (planet)

Natural and anthropogenic controls on lake water-level decline and evaporation-to-inflow ratio in the conterminous United States

Lake water levels are integral to lake function, but hydrologic changes from land and water management may alter lake fluctuations beyond natural ranges. We constructed a conceptual model of multifaceted drivers of lake water-levels and evaporation-to-inflow ratio (Evap:Inflow). Using a structural equation modeling framework, we tested our model on 1) a national subset of lakes in the conterminous United States with minimal water management to describe natural drivers of lake hydrology and 2) five ecoregional subsets of lakes to explore regional variation in water management effects. Our model fit the national and ecoregional datasets and explained up to 47% of variation in Evap:Inflow, 38% of vertical water-level decline, and 79% of horizontal water-level decline (littoral exposure). For lakes with minimal water management, Evap:Inflow was related to lake depth (β = -0.31) and surface inflow (β = -0.44); vertical decline was related to annual climate (e.g., precipitation β = -0.18) and water management (β = -0.21); and horizontal decline was largely related to vertical decline (β = 0.73) and lake morphometry (e.g., depth β = -0.18). Anthropogenic effects varied by ecoregion and likely reflect differences in regional water management and climate. In the West, water management indicators were related to greater vertical decline (β = 0.38), whereas in the Midwest, these indicators were related to more stable and full lake levels (β = -0.22) even during drought conditions. National analyses show how human water use interacts with regional climate resulting in contrasting impacts to lake hydrologic variation in the US.

δ15N of Chironomidae: An index of nitrogen sources and processing within watersheds for national aquatic monitoring programs

Nitrogen (N) removal along flowpaths to aquatic ecosystems is an important regulating ecosystem service that can help reduce N pollution in the nation's waterways, but can be challenging to measure at large spatial scales. Measurements that integrate N processing within watersheds would be particularly useful for assessing the magnitude of this vital service. Because most N removal processes cause isotopic fractionation, δ¹⁵N from basal food-chain organisms in aquatic ecosystems can provide information on both N sources and the degree of watershed N processing. As part of EPA's National Aquatic Resource Surveys (NARS), we measured δ¹⁵N of Chironomidae collected from over 2000 lakes, rivers and streams across the continental USA. Using information on N inputs to watersheds and summer total N concentrations ([TN]) in the water column, we assessed where elevated chironomid δ¹⁵N would indicate N removal rather than possible enriched sources of N. Chironomid δ¹⁵N values ranged from -4 to +20‰, and were higher in rivers and streams than in lakes, indicating that N in rivers and streams underwent more processing and cycling that preferentially removes ¹⁴N than N in lakes. Chironomid δ¹⁵N increased with watershed size, N inputs, and water chemical components, and decreased as precipitation increased. In rivers and streams with high watershed N inputs, we found lower [TN] in streams with higher chironomid δ¹⁵N values, suggesting high rates of gaseous N loss such as denitrification. At low watershed N inputs, the pattern reversed; streams with elevated chironomid δ¹⁵N had higher [TN] than streams with lower chironomid δ¹⁵N, possibly indicating unknown sources elevated in δ¹⁵N such as legacy N, or waste from animals or humans. Chironomid δ¹⁵N values can be a valuable tool to assess integrated watershed-level N sources, input rates, and processing for water quality monitoring and assessment at large scales.

GLOBathy, the global lakes bathymetry dataset

Waterbodies (natural lakes and reservoirs) are a critical part of a watershed's ecological and hydrological balance, and in many cases dictate the downstream river flows either through natural attenuation or through managed controls. Investigating waterbody dynamics relies primarily on understanding their morphology and geophysical characteristics that are primarily defined by bathymetry. Bathymetric conditions define stage-storage relationships and circulation/transport processes in waterbodies. Yet many studies oversimplify these mechanisms due to unavailability of the bathymetric data. We developed a novel GLObal Bathymetric (GLOBathy) dataset of 1.4+ million waterbodies to align with the well-established global dataset, HydroLAKES. GLOBathy uses a GIS-based framework to generate bathymetric maps based on the waterbody maximum depth estimates and HydroLAKES geometric/geophysical attributes of the waterbodies. The maximum depth estimates are validated at 1,503 waterbodies, making use of several observed data sources. We also provide estimations for head-Area-Volume (h-A-V) relationships of the HydroLAKES waterbodies, driven from the bathymetric maps of the GLOBathy dataset. The h-A-V relationships provide essential information for water balance and hydrological studies of global waterbody systems.

Modeling Anthropogenic and Environmental Influences on Freshwater Harmful Algal Bloom Development Detected by MERIS Over the Central United States

Human and ecological health have been threatened by the increase of cyanobacteria harmful algal blooms (cyanoHABs) in freshwater systems. Successful mitigation of this risk requires understanding the factors driving cyanoHABs at a broad scale. To inform management priorities and decisions, we employed random forest modeling to identify major cyanoHAB drivers in 369 freshwater lakes distributed across 15 upper Midwest states during the 2011 bloom season (July-October). We used Cyanobacteria Index (CI_cyano)-A remotely sensed product derived from the MEdium Resolution Imaging Spectrometer (MERIS) aboard the European Space Agency's Envisat satellite-as the response variable to obtain variable importance metrics for 75 landscape and lake physiographic predictor variables. Lakes were stratified into high and low elevation categories to further focus CI_cyano variable importance identification by anthropogenic and natural influences. "High elevation" watershed land cover (LC) was primarily forest or natural vegetation, compared with "low elevation" watersheds LC dominated by anthropogenic landscapes (e.g., agriculture and municipalities). We used the top ranked 25 Random Forest variables to create a classification and regression tree (CART) for both low and high elevation lake designations to identify variable thresholds for possible management mitigation. Mean CI_cyano was 3 times larger for "low elevation" lakes than for "high elevation" lakes, with both mean values exceeding the "High" World Health Organization recreational guidance/action level threshold for cyanobacteria (100,000 cells/mL). Agrarian-related variables were prominent across all 369 lakes and low elevation lakes. High elevation lakes showed more influence of lakeside LC than for the low elevation lakes.

National framework for ranking lakes by potential for anthropogenic hydro-alteration

Lakes face multiple anthropogenic pressures that can substantially alter their hydrology. Dams and land use in the watershed (e.g., irrigated agriculture) can modify lake water regimes beyond natural ranges, and changing climate may exacerbate anthropogenic stresses on lake hydrology. However, we lack cost-effective indicators to quantify anthropogenic hydrologic alteration potential in lakes at regional and national extents. We developed a framework to rank lakes by the potential for dams and land use to alter lake hydrology (HydrAP) that can be applied at a national scale. The HydrAP framework principles are that 1) dams are primary drivers of lake hydro-alteration, 2) land use activities are secondary drivers that alter watershed hydrology, and 3) topographic relief limits where land use and dams are located on the landscape. We ranked lakes in the United States Environmental Protection Agency National Lakes Assessment (NLA) on a HydrAP scale from zero to seven, where a zero indicates lakes with no potential for anthropogenic hydro-alteration, and a seven indicates large dams and/or intensive land use with high potential to alter lake hydrology. We inferred HydrAP population distributions in the conterminous US (CONUS) using the NLA probabilistic weights. Half of CONUS lakes had moderate to high hydro-alteration potential (HydrAP ranks 3-7), the other half had minimal to no hydro-alteration potential (HydrAP ranks 0-2). HydrAP ranks generally corresponded with natural and man-made lake classes, but >15% of natural lakes had moderate to high HydrAP ranks and ~10% of man-made lakes had low HydrAP ranks. The Great Plains, Appalachians, and Coastal Plains had the largest percentages (>50%) of high HydrAP lakes, and the West and Midwest had the lowest percentages (~30%). Water residence time (τ) and water-level change were associated with HydrAP ranks, demonstrating the framework's intended ability to differentiate anthropogenic stressors that can alter lake hydrology. Consistently across ecoregions high HydrAP lakes had shorter τ. But HydrAP relationships with water-level change varied by ecoregion. In the West and Appalachians, high HydrAP lakes experienced excessive water-level declines compared to low-ranked lakes. In contrast, high HydrAP lakes in the Great Plains and Midwest showed stable water levels compared to low-ranked lakes. These differences imply that water management in western and eastern mountainous regions may result in large water-level fluctuations, but water management in central CONUS may promote water-level stabilization. The HydrAP framework using accessible, national datasets can support large-scale lake assessments and be adapted to specific locations where data are available.

Methane and Carbon Dioxide Emissions From Reservoirs: Controls and Upscaling

Estimating carbon dioxide (CO₂) and methane (CH₄) emission rates from reservoirs is important for regional and national greenhouse gas inventories. A lack of methodologically consistent data sets for many parts of the world, including agriculturally intensive areas of the United States, poses a major challenge to the development of models for predicting emission rates. In this study, we used a systematic approach to measure CO₂ and CH₄ diffusive and ebullitive emission rates from 32 reservoirs distributed across an agricultural to forested land use gradient in the United States. We found that all reservoirs were a source of CH₄ to the atmosphere, with ebullition being the dominant emission pathway in 75% of the systems. Ebullition was a negligible emission pathway for CO₂, and 65% of sampled reservoirs were a net CO₂ sink. Boosted regression trees (BRTs), a type of machine learning algorithm, identified reservoir morphology and watershed agricultural land use as important predictors of emission rates. We used the BRT to predict CH₄ emission rates for reservoirs in the U.S. state of Ohio and estimate they are the fourth largest anthropogenic CH₄ source in the state. Our work demonstrates that CH₄ emission rates for reservoirs in our study region can be predicted from information in readily available national geodatabases. Expanded sampling campaigns could generate the data needed to train models for upscaling in other U.S. regions or nationally.

Developing the hydrological dependency structure between streamgage and reservoir networks

Reliable operation of physical infrastructures such as reservoirs, dikes, nuclear power plants positioned along a river network depends on monitoring riverine conditions and infrastructure interdependency with the river network, especially during hydrologic extremes. Developing this cascading interdependency between the riverine conditions and infrastructures for a large watershed is challenging, as conventional tools (e.g., watershed delineation) do not provide the relative topographic information on infrastructures along the river network. Here, we present a generic geo-processing tool that systematically combines three geospatial layers: topographic information from the National Hydrographic Dataset (NHDPlusV2), streamgages from the USGS National Water Information System, and reservoirs from the National Inventory of Dams, to develop the interdependency between reservoirs and streamgages along the river network for upper and lower Colorado River Basin (CRB) resulting in River and Infrastructure Connectivity Network (RICON) that shows the said interdependency as a concise edge list for the CRB. Another contribution of this study is an algorithm for developing the cascading interdependency between infrastructure and riverine networks to support their management and operation.

Measurement(s)	network connectivity of streamgages and reservoirs
Technology Type(s)	geospatial analysis • computational modeling technique • digital curation
Factor Type(s)	location of USGS streamgages • location of NID reservoirs
Sample Characteristic - Environment	drainage basin • reservoir
Sample Characteristic - Location	Colorado River

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12757940

A bobber’s perspective on angler-driven vectors of invasive species transmission

Prevention of aquatic invasive species is a fundamental management challenge. With hundreds of millions of people participating in fishing trips each year, understanding angler movements that transmit invasive species can provide critical insight into the most effective locations and scales at which to apply preventative measures. Recent evidence suggests that mobile technologies provide new opportunities to understand different types of angler movement behaviour beyond what is possible with infrequently and sparsely conducted in-person boat surveys and mail questionnaires. Here we capitalise on data provided by ReelSonar’s iBobber, a sonar-enabled bobber with over 5 M recorded fishing locations, globally. By quantifying geographic patterns of fishing activities and assessing how these patterns change seasonally, we explore angler behaviour across the entire continental United States in terms of fishing frequency and distance travelled between sites and characterise the attributes of fished ecosystems. We found that iBobber users (anglers) undertook 66,918 trips to 20,049 different water-bodies over a two-year period. Anglers who use iBobber were more likely to visit larger, deeper and more urbanised water-bodies and these water-bodies were over five times more likely to be a reservoir compared to a lake. Inter-water-body travel road distances averaged 93 km (SD = 277 km; range < 1–300 km) and nearly half of these movements occurred over a timespan of two days or less, a timeframe that we show falls well within the desiccation tolerance window of many prevalent plant and animal invasive species. Our study offers novel insight into spatiotemporal patterns of angler behaviour well beyond the geographical and temporal extent of conventional ground-collected approaches and carries important implications for predicting and preventing future transmission of aquatic invasive species via recreational fishing.

Lake Water Levels and Associated Hydrologic Characteristics in the Conterminous U.S

Establishing baseline hydrologic characteristics for lakes in the U.S. is critical to evaluate changes to lake hydrology. We used the U.S. EPA National Lakes Assessment 2007 and 2012 surveys to assess hydrologic characteristics of a population of ~45,000 lakes in the conterminous U.S. based on probability samples of ~1,000 lakes/yr distributed across nine ecoregions. Lake hydrologic study variables include water-level drawdown (i.e., vertical decline and horizontal littoral exposure) and two water stable isotope-derived parameters: evaporation-to-inflow (E:I) and water residence time. We present 1) national and regional distributions of the study variables for both natural and man-made lakes and 2) differences in these characteristics between 2007 and 2012. In 2007, 59% of the population of U.S. lakes had Greater than normal or Excessive drawdown relative to water levels in ecoregional reference lakes with minimal human disturbances; while in 2012, only 20% of lakes were significantly drawn down beyond normal ranges. Water isotope-derived variables did not differ significantly between survey years in contrast to drawdown. Median E:I was 20% indicating that flow-through processes dominated lake water regimes. For 75% of U.S. lakes, water residence time was < 1 year and was longer in natural vs. man-made lakes. Our study provides baseline ranges to assess local and regional lake hydrologic status and inform management decisions in changing environmental conditions.