The arctic is changing rapidly. Rivers integrate upstream processes, and are a key indicator of change. River monitoring is of vital importance, but data are scarce due to logistical constraints of…

This is a $409,679.64 research grant awarded by the National Aeronautics and Space Administration (NASA) to The Ohio State University (OSU) to support the development and validation of algorithms for estimating river discharge in the Arctic using data from the upcoming Surface Water and Ocean Topography (SWOT) mission and existing ArcticDEM elevation data. The grant will fund work to characterize the accuracy of river height, width, and slope measurements from ArcticDEM, evaluate flow law models for Arctic rivers, and assess the performance of Mass-Conserved Flow Law Inversion (MCFLI) algorithms in estimating discharge for ungaged basins, with a focus on braided rivers. This research directly supports the SWOT mission's objectives to monitor the hydrologic cycle and is vital for improving estimates of Arctic river discharge using both SWOT and ArcticDEM data. The grant does not have a set-aside designation.

The arctic is changing rapidly. Rivers integrate upstream processes, and are a key indicator of change. River monitoring is of vital importance, but data are scarce due to logistical constraints of operating stream gages and (in siberia) lack of data sharing. Remote sensing provides a way to address this data GAP, but remote sensing of discharge in ungaged basins is a grand challenge that has not yet been solved. The surface water & ocean topography (swot) mission (scheduled to launch in 2021) will measure river height, slope, and width globally for large rivers. The recently-released arcticdem provides the opportunity to begin working with swotlike measurements of arctic rivers now. The swot community has produced a family of algorithms known as mass-conserved flow law inversion (mcfli) applicable to ungaged basins, but these have not yet been successfully demonstrated on braided rivers. Mcfli approaches require river geometry measurements, a flow law that adequately resolves river hydraulic processes, and an inverse method. The full scientific impact of swot relies on achieving accurate discharge estimates, including the arctic; this requires adaptation of mcfli algorithms for braided rivers. We here propose to use arcticdem to retrieve swot-like estimates of river height, width, and slope, and to use this unique dataset to develop and validate mcfli discharge algorithms. Preliminary work on the tanana river shows that river height is measurable from arcticdem with ~40 CM accuracy at 100 m posting along flow direction. Slopes can be measured to approximately 2.5 CM/KM for river reaches on the order of 10 KM. Available lidar, airswot and intensive in situ measurements at two intensive sites will further be used to validate arcticdem slopes. We will investigate the potential for arctic DEM to map discharge in ungaged basins in three ways. First, we will characterize uncertainty of river height, width, and slope measurements from arctic DEM using all available in situ and airborne data. Second, we will evaluate flow law precision by i) computing unobserved flow law parameters for one arcticdem observation day, and evaluating them with another (essentially a simple model calibration-validation exercise). This will allow evaluation of the precision of several proposed flow law configurations. Third, we will evaluate arcticdem - mcfli discharge accuracy. This requires 6 or more arctic DEM observation days, which are available for five gages. Note that gage data are used only for validation, not for calibration of mcfli methods. This project will contribute to swot discharge algorithms, and in particular, will directly support swot algorithm theoretical basis documents (atbds), especially for braided rivers, a top-priority issue for the mission. This work is vital to ultimately achieve better estimates of river discharge across the arctic using both arcticdem and swot measurements, and thus supports NASA earth science objectives to monitor the hydrologic cycle in a changing climate.