The effects of spatial resolution and dimensionality on modeling regional-scale hydraulics in a multichannel river

As modeling capabilities at regional and global scales improve, questions remain regarding the appropriate process representation required to accurately simulate multichannel river hydraulics. This study uses the hydrodynamic model LISFLOOD-FP to simulate patterns of water surface elevation (WSE), depth, and inundation extent across a ∼90 km, anabranching reach of the Tanana River, Alaska. To provide boundary conditions, we collected field observations of bathymetry and WSE during a 2 week field campaign in summer 2013. For the first time at this scale, we test a simple, raster-based model's capabilities to simulate 2-D, in-channel patterns of WSE and inundation extent. Additionally, we compare finer resolution (≤25 m) 2-D models to four other models of lower dimensionality and coarser resolution (100–500 m) to determine the effects of simplifying process representation. Results indicate that simple, raster-based models can accurately simulate 2-D, in-channel hydraulics in the Tanana. Also, the fine-resolution, 2-D models produce lower errors in spatiotemporal outputs of WSE and inundation extent compared to coarse-resolution, 1-D models: 22.6 cm versus 56.4 cm RMSE for WSE, and 90% versus 41% Critical Success Index values for simulating inundation extent. Incorporating the anabranching channel network using subgrid representations for smaller channels is important for simulating accurate hydraulics and lowers RMSE in spatially distributed WSE by at least 16%. As a result, better representation of the converging and diverging multichannel network by using subgrid solvers or downscaling techniques in multichannel rivers is needed to improve errors in regional to global-scale models

Estimating River Surface Elevation From ArcticDEM

ArcticDEM is a collection of 2-m resolution, repeat digital surface models created from stereoscopic satellite imagery. To demonstrate the potential of ArcticDEM for measuring river stages and discharges, we estimate river surface heights along a reach of Tanana River near Fairbanks, Alaska, by the precise detection of river shorelines and mapping of shorelines to land surface elevation. The river height profiles over a 15-km reach agree with in situ measurements to a standard deviation less than 30 cm. The time series of ArcticDEM-derived river heights agree with the U.S. Geological Survey gage measurements with a standard deviation of 32 cm. Using the rating curve for that gage, we obtain discharges with a validation accuracy (root-mean-square error) of 234 m3/s (23% of the mean discharge). Our results demonstrate that ArcticDEM can accurately measure spatial and temporal variations of river surfaces, providing a new and powerful data set for hydrologic analysis

The Surface Water and Ocean Topography (SWOT) Mission River Database (SWORD): A Global River Network for Satellite Data Products

The upcoming Surface Water and Ocean Topography (SWOT) satellite mission, planned to launch in 2022, is the first mission to focus on measuring hydrological processes in Earth's surface water. As such, SWOT will vastly expand observations of global rivers ≥100 m wide. SWOT will provide a variety of data products, including a global vector river product containing water surface elevation (WSE), width, slope, and estimated discharge. Practical application and consistency of the SWOT vector products requires a prior global river network database divided into reaches. Here, we introduce the SWOT River Database (SWORD). SWORD will serve as the framework for the SWOT river vector products consisting of river reaches (∼10 km long) and nodes (∼200 m spacing). We generate SWORD by combining several global river- and satellite-related data sets into one congruent product. When defining river reaches, we incorporate natural and human-created river obstructions, basin boundaries, tributary junctions, and SWOT orbit track information. SWORD contains a total of 213,485 reaches and 10.7 million nodes. Globally, 77.3% of river reach lengths are between 10 and 20 km with a median reach length of 10.5 km. 95% of river reaches ≥10 km will have sufficient SWOT observations to provide discharge estimates at least once per orbit cycle. SWORD also contains many useful hydrologic and morphological attributes and is designed to be expandable in the future. Even before the launch of SWOT, it can serve as a framework for global hydrologic analyses using models, in situ measurements, and additional satellite observations

The Color of Rivers

Rivers are among the most imperiled ecosystems globally, yet we do not have broad-scale understanding of their changing ecology because most are rarely sampled. Water color, as perceived by the human eye, is an integrative measure of water quality directly observed by satellites. We examined patterns in river color between 1984 and 2018 by building a remote sensing database of surface reflectance, RiverSR, extracted from 234,727 Landsat images covering 108,000 kilometers of rivers > 60 m wide in the contiguous USA. We found 1) broad regional patterns in river color, with 56% of observations dominantly yellow and 38% dominantly green; 2) river color has three distinct seasonal patterns that were synchronous with flow regimes; 3) one third of rivers had significant color shifts over the last 35 years. RiverSR provides the first map of river color and new insights into macrosystems ecology of rivers

Anticipated improvements to river surface elevation profiles from the surface water and ocean topography mission

Existing publicly available digital elevation models (DEMs) provide global-scale data but are often not precise enough for studying processes that depend on small-scale topographic features in rivers. For example, slope breaks and knickpoints in rivers can be important in understanding tectonic processes, and riffle-pool structures are important drivers of riverine ecology. More precise data (e.g., lidar) are available in some areas, but their spatial extent limits large-scale research. The upcoming Surface Water and Ocean Topography (SWOT) satellite mission is planned to launch in 2021 and will provide measurements of elevation and inundation extent of surface waters between 78° north and south latitude on average twice every 21 days. We present a novel noise reduction method for multitemporal river water surface elevation (WSE) profiles from SWOT that combines a truncated singular value decomposition and a slope-constrained least-squares estimator. We use simulated SWOT data of 85–145 km sections of the Po, Sacramento, and Tanana Rivers to show that 3–12 months of simulated SWOT data can produce elevation profiles with mean absolute errors (MAEs) of 5.38–12.55 cm at 100–200 m along-stream resolution. MAEs can be reduced further to 4–11 cm by averaging all observations. The average profiles have errors much lower than existing DEMs, allowing new advances in riverine research globally. We consider two case studies in geomorphology and ecology that highlight the scientific value of the more accurate in-river DEMs expected from SWOT. Simulated SWOT elevation profiles for the Po reveal convexities in the river longitudinal profile that are spatially coincident with the upward projection of blind thrust faults that are buried beneath the Po Plain at the northern termination of the Apennine Mountains. Meanwhile, simulated SWOT data for the Sacramento River reveals locally steep sections of the river profile that represent important habitat for benthic invertebrates at a spatial scale previously unrecognizable in large-scale DEMs presently available for this river

AirSWOT measurements of river water surface elevation and slope: Tanana River, AK

Fluctuations in water surface elevation (WSE) along rivers have important implications for water resources, flood hazards, and biogeochemical cycling. However, current in situ and remote sensing methods exhibit key limitations in characterizing spatiotemporal hydraulics of many of the world's river systems. Here we analyze new measurements of river WSE and slope from AirSWOT, an airborne analogue to the Surface Water and Ocean Topography (SWOT) mission aimed at addressing limitations in current remotely sensed observations of surface water. To evaluate its capabilities, we compare AirSWOT WSEs and slopes to in situ measurements along the Tanana River, Alaska. Root-mean-square error is 9.0 cm for WSEs averaged over 1 km2 areas and 1.0 cm/km for slopes along 10 km reaches. Results indicate that AirSWOT can accurately reproduce the spatial variations in slope critical for characterizing reach-scale hydraulics. AirSWOT's high-precision measurements are valuable for hydrologic analysis, flood modeling studies, and for validating future SWOT measurements

AirSWOT InSAR Mapping of Surface Water Elevations and Hydraulic Gradients Across the Yukon Flats Basin, Alaska

AirSWOT, an experimental airborne Ka-band interferometric synthetic aperture radar, was developed for hydrologic research and validation of the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission (to be launched in 2021). AirSWOT and SWOT aim to improve understanding of surface water processes by mapping water surface elevation (WSE) and water surface slope (WSS) in rivers, lakes, and wetlands. However, the utility of AirSWOT for these purposes remains largely unexamined. We present the first investigation of AirSWOT WSE and WSS surveys over complex, low-relief, wetland-river hydrologic environments, including (1) a field-validated assessment of AirSWOT WSE and WSS precisions for lakes and rivers in the Yukon Flats Basin, an Arctic-Boreal wetland complex in eastern interior Alaska; (2) improved scientific understanding of surface water flow gradients and the influence of subsurface permafrost; and (3) recommendations for improving AirSWOT precisions in future scientific and SWOT validation campaigns. AirSWOT quantifies WSE with an RMSE of 8 and 15 cm in 1 and 0.0625 km2 river reaches, respectively, and 21 cm in lakes. This indicates good utility for studying hydrologic flux, WSS, geomorphic processes, and coupled surface/subsurface hydrology in permafrost environments. This also suggests that AirSWOT supplies sufficient precision for validating SWOT WSE and WSS over rivers, but not lakes. However, improvements in sensor calibration and flight experiment design may improve precisions in future deployments as may modifications to data processing. We conclude that AirSWOT is a useful tool for bridging the gap between field observations and forthcoming global SWOT satellite products

Mapping Flow-Obstructing Structures on Global Rivers

To help store water, facilitate navigation, generate energy, mitigate floods, and support industrial and agricultural production, people have built and continue to build obstructions to natural flow in rivers. However, due to the long and complex history of constructing and removing such obstructions, we lack a globally consistent record of their locations and types. Here, we used a consistent method to visually locate and classify obstructions on 2.1 million km of large rivers (width ≥30 m) globally. We based our mapping on Google Earth Engine’s high resolution images, which for many places have meter-scale resolution. The resulting Global River Obstruction Database (GROD) consists of 30,549 unique obstructions, covering six different obstruction types: dam, lock, low head dam, channel dam, and two types of partial dams. By classifying a subset of the obstructions multiple times, we are able to show high classification consistency (87% mean balanced accuracy) for the three types of obstructions that fully intersect rivers: dams, low head dams, and locks. The classification of the three types of partial obstructions are somewhat less consistent (61% mean balanced accuracy). Overall, by comparing GROD to similar datasets, we estimate GROD likely captured >90% of the obstructions on large rivers. We anticipate that GROD will be of wide interest to the hydrological modeling, aquatic ecology, geomorphology, and water resource management communities

Discharge Estimation From Dense Arrays of Pressure Transducers

In situ river discharge estimation is a critical component of studying rivers. A dominant method for establishing discharge monitoring in situ is a temporary gauge, which uses a rating curve to relate stage to discharge. However, this approach is constrained by cost and the time to develop the stage-discharge rating curve, as rating curves rely on numerous flow measurements at high and low stages. Here, we offer a novel alternative approach to traditional temporary gauges: estimating Discharge via Arrays of Pressure Transducers (DAPT). DAPT uses a Bayesian discharge algorithm developed for the upcoming Surface Water Ocean Topography satellite (SWOT) to estimate in situ discharge from automated water surface elevation measurements. We conducted sensitivity tests over 4,954 model runs on five gauged rivers and conclude that the DAPT method can robustly reproduce discharge with an average Nash-Sutcliffe Efficiency (NSE) of 0.79 and Kling-Gupta Efficiency of 0.78. Further, we find that the DAPT method estimates discharge similarly to an idealized temporary gauge created from the same input data (NSE differences of less than 0.1), and that results improve significantly with accurate priors. Finally, we test the DAPT method in nine poorly gauged rivers in a realistic and complex field setting in the Peace-Athabasca Delta, and show that the DAPT method largely outperforms a temporary gauge in this time and budget constrained setting. We therefore recommend DAPT as an effective tool for in situ discharge estimation in cases where there is not enough time or resources to develop a temporary gauge

Estimating River Surface Elevation From ArcticDEM

ArcticDEM is a collection of 2-m resolution, repeat digital surface models created from stereoscopic satellite imagery. To demonstrate the potential of ArcticDEM for measuring river stages and discharges, we estimate river surface heights along a reach of Tanana River near Fairbanks, Alaska, by the precise detection of river shorelines and mapping of shorelines to land surface elevation. The river height profiles over a 15-km reach agree with in situ measurements to a standard deviation less than 30 cm. The time series of ArcticDEM-derived river heights agree with the U.S. Geological Survey gage measurements with a standard deviation of 32 cm. Using the rating curve for that gage, we obtain discharges with a validation accuracy (root-mean-square error) of 234 m3/s (23% of the mean discharge). Our results demonstrate that ArcticDEM can accurately measure spatial and temporal variations of river surfaces, providing a new and powerful data set for hydrologic analysis