Satellite Altimetry-based Extension of global-scale in situ river discharge Measurements (SAEM)

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Saemian, Peyman; Elmi, Omid; Stroud, Molly; Riggs, Ryan; Kitambo, Benjamin M.; Papa, Fabrice; Allen, George H.; Tourian, Mohammad J., 2024, "Satellite Altimetry-based Extension of global-scale in situ river discharge Measurements (SAEM)", https://doi.org/10.18419/DARUS-4475, DaRUS, V1

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Description	The Satellite Altimetry-based Extension of global-scale in situ river discharge Measurements (SAEM) dataset provides a comprehensive solution for addressing gaps in river discharge measurements by leveraging satellite altimetry. This dataset offers enhanced coverage for river discharge estimations by utilizing data from multiple satellite missions and integrating it with existing river gauge networks. It supports sustainable development and helps address complex water-related challenges exacerbated by climate change. The first version of SAEM includes (1) height-based discharge estimates for 8,730 river gauges, covering approximately 88% of the total gauged discharge volume globally. These estimates demonstrate a median Kling-Gupta Efficiency (KGE) of 0.48, surpassing the performance of current global datasets. (2) Catalog of Virtual Stations (VSs): a catalog of VSs defined by specific criteria, including each station’s coordinates, associated satellite altimetry missions, distance to discharge gauges, and quality flags. (3) Altimetric Water Level Time Series: time series data of water levels from VSs that provide high-quality discharge estimates. The water level data are sourced from both existing Level-3 datasets and newly generated data within this study, including contributions from Hydroweb.Next, DAHITI, GRRATS, and HydroSat. Non-parametric quantile mapping functions: for VSs, which model the transformation of water level time series into discharge data using a Nonparametric Stochastic Quantile Mapping Function approach.
Subject	Earth and Environmental Sciences
Keyword	Discharge, River Discharge, Remote Sensing, Satellite Altimetry
Data Generation	Prediction
License/Data Use Agreement	CC BY 4.0

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	SAEM_Discharge_V01.nc Network Common Data Form - 75.7 MB Published Sep 18, 2024 26 Downloads MD5: 355d9e46423cc944605754c0b19315a1	Preview "SAEM_Discharge_V01.nc" Access File File Access Public Download Options Network Common Data Form Download Metadata Data File Citation EndNote XML RIS BibTeX Download Auxiliary Files XML from NetCDF/HDF5 (NcML) NcML (0.1)
	SAEM_NPQMfunctions_V01.nc Network Common Data Form - 34.8 MB Published Sep 18, 2024 14 Downloads MD5: e2670835d75c75a8d8260a788c34c60a	Preview "SAEM_NPQMfunctions_V01.nc" Access File File Access Public Download Options Network Common Data Form Download Metadata Data File Citation EndNote XML RIS BibTeX Download Auxiliary Files XML from NetCDF/HDF5 (NcML) NcML (0.1)
	SAEM_VS_Catalogue_V01_af.nc Network Common Data Form - 256.8 KB Published Sep 18, 2024 14 Downloads MD5: 5db5a9076b9483496713d10bf08d592f	Preview "SAEM_VS_Catalogue_V01_af.nc" Access File File Access Public Download Options Network Common Data Form Download Metadata Data File Citation EndNote XML RIS BibTeX Download Auxiliary Files XML from NetCDF/HDF5 (NcML) NcML (0.1)
	SAEM_VS_Catalogue_V01_as.nc Network Common Data Form - 592.7 KB Published Sep 18, 2024 18 Downloads MD5: 846d5489d7e860deb319f75a8847acb2	Preview "SAEM_VS_Catalogue_V01_as.nc" Access File File Access Public Download Options Network Common Data Form Download Metadata Data File Citation EndNote XML RIS BibTeX Download Auxiliary Files XML from NetCDF/HDF5 (NcML) NcML (0.1)
	SAEM_VS_Catalogue_V01_au.nc Network Common Data Form - 128.6 KB Published Sep 18, 2024 13 Downloads MD5: bf206aedecf4f4665928dc63a8684922	Preview "SAEM_VS_Catalogue_V01_au.nc" Access File File Access Public Download Options Network Common Data Form Download Metadata Data File Citation EndNote XML RIS BibTeX Download Auxiliary Files XML from NetCDF/HDF5 (NcML) NcML (0.1)
	SAEM_VS_Catalogue_V01_eu.nc Network Common Data Form - 265.1 KB Published Sep 18, 2024 14 Downloads MD5: b61e396f20c2d76bb83a2f1ea48ada70	Preview "SAEM_VS_Catalogue_V01_eu.nc" Access File File Access Public Download Options Network Common Data Form Download Metadata Data File Citation EndNote XML RIS BibTeX Download Auxiliary Files XML from NetCDF/HDF5 (NcML) NcML (0.1)
	SAEM_VS_Catalogue_V01_na.nc Network Common Data Form - 1.2 MB Published Sep 18, 2024 15 Downloads MD5: 9090bd28a9595eb9abf21a23b5699349	Preview "SAEM_VS_Catalogue_V01_na.nc" Access File File Access Public Download Options Network Common Data Form Download Metadata Data File Citation EndNote XML RIS BibTeX Download Auxiliary Files XML from NetCDF/HDF5 (NcML) NcML (0.1)
	SAEM_VS_Catalogue_V01_sa.nc Network Common Data Form - 1.6 MB Published Sep 18, 2024 14 Downloads MD5: 483b8dd1c1e6a5769e6bb030e3863dab	Preview "SAEM_VS_Catalogue_V01_sa.nc" Access File File Access Public Download Options Network Common Data Form Download Metadata Data File Citation EndNote XML RIS BibTeX Download Auxiliary Files XML from NetCDF/HDF5 (NcML) NcML (0.1)
	SAEM_WL_V01.nc Network Common Data Form - 9.5 MB Published Sep 18, 2024 17 Downloads MD5: c2da6a685d64710beef9824d1f0e1eb5	Preview "SAEM_WL_V01.nc" Access File File Access Public Download Options Network Common Data Form Download Metadata Data File Citation EndNote XML RIS BibTeX Download Auxiliary Files XML from NetCDF/HDF5 (NcML) NcML (0.1)

Citation Metadata

Persistent Identifier	doi:10.18419/DARUS-4475
Publication Date	2024-09-18
Title	Satellite Altimetry-based Extension of global-scale in situ river discharge Measurements (SAEM)
Author	Institute of Geodesy, University of Stuttgart0000-0003-2612-8718 Institute of Geodesy, University of Stuttgart0000-0003-2668-735X Department of Geosciences, Virginia Polytechnic Institute and State University, Virginia, USA0000-0001-7389-1586 Water Mission Area, U.S. Geological Survey, Conroe, TX, USA0000-0001-6834-9469 Laboratoire d’Etudes en Géophysique et Océanographie Spatiales (LEGOS), Université de Toulouse, CNES/CNRS/IRD/UT3, Toulouse, France0000-0001-9899-2842 Laboratoire d’Etudes en Géophysique et Océanographie Spatiales (LEGOS), Université de Toulouse, CNES/CNRS/IRD/UT3, Toulouse, France0000-0001-6305-6253 Department of Geosciences, Virginia Polytechnic Institute and State University, Virginia, USA0000-0001-8301-5301 Institute of Geodesy, University of Stuttgart0000-0002-4200-0848
Point of Contact	Use email button above to contact. Saemian, Peyman (Institute of Geodesy, University of Stuttgart) Tourian, Mohammad J. (Institute of Geodesy, University of Stuttgart)
Description	The Satellite Altimetry-based Extension of global-scale in situ river discharge Measurements (SAEM) dataset provides a comprehensive solution for addressing gaps in river discharge measurements by leveraging satellite altimetry. This dataset offers enhanced coverage for river discharge estimations by utilizing data from multiple satellite missions and integrating it with existing river gauge networks. It supports sustainable development and helps address complex water-related challenges exacerbated by climate change. The first version of SAEM includes (1) height-based discharge estimates for 8,730 river gauges, covering approximately 88% of the total gauged discharge volume globally. These estimates demonstrate a median Kling-Gupta Efficiency (KGE) of 0.48, surpassing the performance of current global datasets. (2) Catalog of Virtual Stations (VSs): a catalog of VSs defined by specific criteria, including each station’s coordinates, associated satellite altimetry missions, distance to discharge gauges, and quality flags. (3) Altimetric Water Level Time Series: time series data of water levels from VSs that provide high-quality discharge estimates. The water level data are sourced from both existing Level-3 datasets and newly generated data within this study, including contributions from Hydroweb.Next, DAHITI, GRRATS, and HydroSat. Non-parametric quantile mapping functions: for VSs, which model the transformation of water level time series into discharge data using a Nonparametric Stochastic Quantile Mapping Function approach.
Subject	Earth and Environmental Sciences
Keyword	Discharge https://www.wikidata.org/wiki/Q8737769 (Wikidata) River Discharge http://vocabs.lter-europe.net/EnvThes/21242 (EnvThes) Remote Sensing https://id.loc.gov/authorities/subjects/sh00007607.html (LCSH) Satellite Altimetry https://www.wikidata.org/wiki/Q1497312 (Wikidata)
Topic Classification	Geosciences (DFGFO) https://w3id.org/dfgfo/2024/34
Funding Information	DFG: 324641997
Depositor	Saemian, Peyman
Deposit Date	2024-09-10

Process Metadata

Processing Methods

Non-Parametric Quantile Mapping Function (First, for each gauge, we find the Virtual Stations (VSs) around the gauge at the intersection of the satellite track (from AVISO) and the river (from the SWORD dataset). Then we select VSs based on their distance to the gauge and with the condition of not having any dam or reservoir in between. Finally to have the best temporal coverage we put the VSs into four orbit families. Then we use the Nonparametric Stochastic Quantile Mapping approach to find the mapping functions. The algorithm performs the following steps to obtain the nonparametric stochastic quantile mapping function: (1) generating realizations of river discharge and river height time series using Monte Carlo simulation, (2) deriving a collection of quantile mapping functions by matching all possible permutations of the quantile functions of both variables, (3) estimating the mean quantile mapping function together with the uncertainty for each percentile, (4) evaluating the performance of the derived model by comparing the estimated and measured discharge of the evaluation sample performing a 3σ test, (5) updating the measurement uncertainties with respect to the result of step 4, (6) terminating the algorithm if the root mean square error (RMSE) from the previous step does not change significantly. Then we do a process to control the quality of the estimated discharge including some statistical tests and visual inspections.)

Method Parameters

River discharge [m^3/s]
River discharge uncertainty [m^3/s]
Water level time series [m]

Engineering Metadata

Data Generation	Prediction
Measured Variables	River discharge (Q) [[m^3/s]] : 0
Controlled Variables	River height (H) [[m]]

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Our Community Norms as well as good scientific practices expect that proper credit is given via citation. Please use the data citation shown on the dataset page.

Creative Commons Attribution 4.0 International License. CC BY 4.0

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