How Does the Unique Space‐Time Sampling of the SWOT Mission Influence River Discharge Series Characteristics?

The Surface Water and Ocean Topography (SWOT) satellite mission will, for the first time, provide simultaneous, high‐resolution measurements of water surface elevation and extent. Here we explore the applicability of SWOT's unique sampling to capture discharge frequency behavior throughout the Mississippi River Basin. Our findings suggest the mission may capture key variability in river discharge series. SWOT orbit specifications, US Geological Survey (USGS) discharge measurements, and potential uncertainty estimates are used to generate SWOT‐like river discharges. Frequency distributions and specific quantiles derived from synthetic SWOT discharge series are compared to those derived from daily USGS discharge series. Based on the Kolmogorov‐Smirnov test, SWOT temporal sampling has essentially no impact on derived frequency distributions. When including potential uncertainty, 78% of derived distributions are statistically identical. The combined effects of temporal sampling and discharge uncertainty mitigates the negative bias used for SWOT discharge uncertainty at larger discharge quantiles (i.e., ≥75% quantiles).

[1]  E. Shimizu Satellite Remote Sensing , 2019, Dictionary of Geotourism.

[2]  Emanuele Santi,et al.  Daily River Discharge Estimates by Merging Satellite Optical Sensors and Radar Altimetry Through Artificial Neural Network , 2019, IEEE Transactions on Geoscience and Remote Sensing.

[3]  N. Flipo,et al.  Retrieving river baseflow from SWOT spaceborne mission , 2018, Remote Sensing of Environment.

[4]  T. Pavelsky,et al.  Global extent of rivers and streams , 2018, Science.

[5]  Alessio Domeneghetti,et al.  Flow Duration Curve from Satellite: Potential of a Lifetime SWOT Mission , 2018, Remote. Sens..

[6]  John W. Jones,et al.  Satellite remote sensing estimation of river discharge: Application to the Yukon River Alaska , 2018, Journal of Hydrology.

[7]  Colin J. Gleason,et al.  BAM: Bayesian AMHG‐Manning Inference of Discharge Using Remotely Sensed Stream Width, Slope, and Height , 2017 .

[8]  Luca Brocca,et al.  Discharge estimation and forecasting by MODIS and altimetry data in Niger-Benue River , 2017 .

[9]  Zulkifli Yusop,et al.  Climate change impacts under CMIP5 RCP scenarios on water resources of the Kelantan River Basin, Malaysia , 2017 .

[10]  Claudia Klüppelberg,et al.  Combination of multi-mission altimetry data along the Mekong River with spatio-temporal kriging , 2017, Journal of Geodesy.

[11]  Faisal Hossain,et al.  An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope , 2016 .

[12]  Frédérique Seyler,et al.  Stage‐discharge rating curves based on satellite altimetry and modeled discharge in the Amazon basin , 2016 .

[13]  Faisal Hossain,et al.  Benchmarking wide swath altimetry‐based river discharge estimation algorithms for the Ganges river system , 2016 .

[14]  A. Kalra,et al.  Pacific Ocean SST and Z500 climate variability and western U.S. seasonal streamflow , 2016 .

[15]  D. Lettenmaier,et al.  The SWOT Mission and Its Capabilities for Land Hydrology , 2016, Surveys in Geophysics.

[16]  Nico Sneeuw,et al.  Spatiotemporal densification of river water level time series by multimission satellite altimetry , 2016 .

[17]  M. Vanclooster,et al.  Quantifying hydrological responses of small Mediterranean catchments under climate change projections. , 2016, The Science of the total environment.

[18]  J. Monnier,et al.  Inference of effective river properties from remotely sensed observations of water surface , 2015 .

[19]  J. Heo,et al.  Impacts of climate and land‐cover changes on water resources in a humid subtropical watershed: a case study from East Texas, USA , 2015 .

[20]  Enrique R. Vivoni,et al.  Hydrological assessment of proposed reservoirs in the Sonora River Basin, Mexico, under historical and future climate scenarios , 2015 .

[21]  C. Gleason,et al.  Retrieval of river discharge solely from satellite imagery and at‐many‐stations hydraulic geometry: Sensitivity to river form and optimization parameters , 2014 .

[22]  Michael Durand,et al.  Assessing the potential global extent of SWOT river discharge observations , 2014 .

[23]  C. Gleason,et al.  Toward global mapping of river discharge using satellite images and at-many-stations hydraulic geometry , 2014, Proceedings of the National Academy of Sciences.

[24]  Frédérique Seyler,et al.  Radar Altimetry Aids Managing Gauge Networks , 2014, Water Resources Management.

[25]  Xiufeng He,et al.  Estimating Total Discharge in the Yangtze River Basin Using Satellite-Based Observations , 2013, Remote. Sens..

[26]  J. McDonnell,et al.  A decade of Predictions in Ungauged Basins (PUB)—a review , 2013 .

[27]  Minghua Zhang,et al.  Assessment of climate change impacts on hydrology and water quality with a watershed modeling approach. , 2013, The Science of the total environment.

[28]  J. Freer,et al.  Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality , 2012 .

[29]  Manuel Gómez,et al.  Modelling impacts of climate change on water resources in ungauged and data-scarce watersheds. Application to the Siurana catchment (NE Spain). , 2012, The Science of the total environment.

[30]  S. Bastola,et al.  Calibration of hydrological models in ungauged basins based on satellite radar altimetry observations of river water level , 2012 .

[31]  Faisal Hossain,et al.  Forecasting transboundary river water elevations from space , 2011 .

[32]  Kyle Hilburn,et al.  Satellite-based global-ocean mass balance estimates of interannual variability and emerging trends in continental freshwater discharge , 2010, Proceedings of the National Academy of Sciences.

[33]  A. Hamlet Assessing water resources adaptive capacity to climate change impacts in the Pacific Northwest Region of North America , 2010 .

[34]  J. Famiglietti,et al.  Evaluation of global land-to-ocean fresh water discharge and evapotranspiration using space-based observations , 2009 .

[35]  T. Pavelsky,et al.  Estimation of river discharge, propagation speed, and hydraulic geometry from space: Lena River, Siberia , 2008 .

[36]  D. Chambers,et al.  GRACE-Based Estimates of Terrestrial Freshwater Discharge from Basin to Continental Scales , 2007 .

[37]  G. Brakenridge,et al.  Orbital microwave measurement of river discharge and ice status , 2007 .

[38]  Anny Cazenave,et al.  Ob' river discharge from TOPEX/Poseidon satellite altimetry (1992–2002) , 2004 .

[39]  Michael T. Coe,et al.  Calculation of river discharge and prediction of lake height from satellite radar altimetry: Example for the Lake Chad basin , 2004 .

[40]  Russell G. Congalton,et al.  Evaluating the potential for measuring river discharge from space , 2003 .

[41]  Petra Döll,et al.  Global water data: A newly endangered species , 2001 .

[42]  Luca Brocca,et al.  Coupling MODIS and Radar Altimetry Data for Discharge Estimation in Poorly Gauged River Basins , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[43]  P. Jones,et al.  Global warming and changes in drought , 2014 .