Lake trophic state is a key ecosystem property that integrates a lake’s physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used Landsat surface reflectance data to create the first compendium of annual lake trophic state for 55,662 lakes of at least 10 ha in area throughout the contiguous United States from 1984 through 2020. The dataset was constructed with FAIR data principles (Findable, Accessible, Interoperable, and Reproducible) in mind, where data are publicly available, relational keys from parent datasets are retained, and all data wrangling and modeling routines are scripted for future reuse. Together, this resource offers critical data to address basic and applied research questions about lake water quality at a suite of spatial and temporal scales.

Near-field remote sensing of surface velocity and river discharge (discharge) were measured using coherent, continuous wave Doppler and pulsed radars. Traditional streamgaging requires sensors be deployed in the water column; however, near-field remote sensing has the potential to transform streamgaging operations through non-contact methods in the U.S. Geological Survey (USGS) and other agencies around the world. To differentiate from satellite or high-altitude platforms, near-field remote sensing is conducted from fixed platforms such as bridges and cable stays. Radar gages were collocated with 10 USGS streamgages in river reaches of varying hydrologic and hydraulic characteristics, where basin size ranged from 381 to 66,200 square kilometers. Radar-derived mean-channel (mean) velocity and discharge were computed using the probability concept and were compared to conventional instantaneous measurements and time series. To test the efficacy of near-field methods, radars were deployed for extended periods of time to capture a range of hydraulic conditions and environmental factors. During the operational phase, continuous time series of surface velocity, radar-derived discharge, and stage-discharge were recorded, computed, and transmitted contemporaneously and continuously in real time every 5 to 15 min. Minimum and maximum surface velocities ranged from 0.30 to 3.84 m per second (m/s); minimum and maximum radar-derived discharges ranged from 0.17 to 4890 cubic meters per second (m³/s); and minimum and maximum stage-discharge ranged from 0.12 to 4950 m³/s. Comparisons between radar and stage-discharge time series were evaluated using goodness-of-fit statistics, which provided a measure of the utility of the probability concept to compute discharge from a singular surface velocity and cross-sectional area relative to conventional methods. Mean velocity and discharge data indicate that velocity radars are highly correlated with conventional methods and are a viable near-field remote sensing technology that can be operationalized to deliver real-time surface velocity, mean velocity, and discharge.

The U.S. Geological Survey monitors water level (water surface elevation relative to an arbitrary datum) and measures streamflow in Alaska rivers to compute and compile river flow records for use by water resource planners, engineers, and land managers to design infrastructure, manage floodplains, and protect life, property, and aquatic resources. Alaska has over 800,000 miles of rivers including the Yukon River, the third longest river in the United States. These rivers are home to rare and important ecosystems and are used for recreation, hydropower generation, commercial fishing, and transportation. River flow measurements are essential for wise and safe development and use of Alaska rivers.

With growing global capability for satellite measurement of river discharge (flow) comes a need to understand and reduce error in satellite‐based discharge measurements. Satellite‐based discharge estimates are based on measurements of water surface width, elevation, slope, and potentially velocity. Site selection is important for reducing error and uncertainty in both conventional and satellite‐based discharge measurements because geomorphic river characteristics have strong control over the relationships between discharge and width, water surface elevation (or depth), slope, and velocity. A large ground‐truth data set of 8,445 conventional hydraulic measurements, collected by acoustic Doppler current profilers at 503 stations in the United States, was developed and quality assured to examine correlation between river discharge and water surface width, depth, velocity, and cross‐sectional area. A separate database of river surface slope and discharge time‐series was developed from paired continuous monitoring stations to examine slope‐discharge correlations. Results show that discharge correlates most strongly with velocity, cross‐sectional area, depth, width, and slope, in that order. Uncertainty of satellite discharge estimates is affected by observed hydraulic variable and reach‐specific variability in observed variable(s) characteristics including range of variability, georegistration accuracy, and stability over time of relationships between discharge and observed hydraulic variable.

The U.S. Geological Survey (USGS), in cooperation with the U.S Fish and Wildlife Service, has investigated the hydrology of the Great Dismal Swamp (Swamp) National Wildlife Refuge (Refuge) in Virginia and North Carolina and developed a three-dimensional numerical model to simulate groundwater and surface-water hydrology. The model was developed with MODFLOW-NWT, a USGS numerical groundwater flow modeling program, in combination with the Surface-Water Routing Process, a software package that simulates dynamic surface-water flows, water control structure management, and groundwater/surface-water interactions.The steady-state model was calibrated to average spring conditions by using automated parameter estimation software (PEST) to reduce simulation errors and assess model parameter sensitivity. The model was then used to simulate wet and dry climatic conditions and a variety of hypothetical scenarios in which water levels in the Swamp were raised and lowered by simulated management of water control structures. Results of the model simulations indicate that, under average spring conditions, precipitation is the primary water input (92%); surface-water (5%) and groundwater (3%) inflows make up the remainder. The primary outflow (or loss) is evapotranspiration (55%), with surface outflows (about 41%) and groundwater outflow (about 4%) making up the remainder.Simulated adjustment of water control structure weir levels demonstrates that groundwater levels are affected by water levels in adjacent ditches and that surface-water and groundwater levels can be controlled through management of water control structures, allowing the Refuge to better manage fire risks and preserve forested-wetland ecosystems in the Refuge. The 13 water control structures proposed in the simulated scenario representing possible future conditions effectively raised simulated water levels in the northeastern corner of the study area, a goal of the Refuge management.Results of this study demonstrate use of MODFLOW with the Surface-Water Routing Process for simulating water management options in peat wetlands and will help Refuge managers to better understand existing hydrologic conditions, assess the hydrologic effects of planned changes to water control structures, and apply the new simulation tool to guide water management on the Refuge.