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Part 1: Document Description
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Citation |
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Title: |
Remote Sensing-Based Extension of GRDC River Discharge Time Series |
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Identification Number: |
doi:10.18419/darus-3558 |
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Distributor: |
DaRUS |
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Date of Distribution: |
2023-07-24 |
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Version: |
4 |
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Bibliographic Citation: |
Elmi, Omid; Tourian, Mohammad J.; Saemian, Peyman; Sneeuw, Nico, 2023, "Remote Sensing-Based Extension of GRDC River Discharge Time Series", https://doi.org/10.18419/darus-3558, DaRUS, V4 |
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Citation |
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Title: |
Remote Sensing-Based Extension of GRDC River Discharge Time Series |
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Identification Number: |
doi:10.18419/darus-3558 |
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Authoring Entity: |
Elmi, Omid (Universität Stuttgart) |
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Tourian, Mohammad J. (Universität Stuttgart) |
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Saemian, Peyman (Universität Stuttgart) |
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Sneeuw, Nico (Universität Stuttgart) |
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Distributor: |
DaRUS |
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Access Authority: |
Tourian, Mohammad J. |
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Access Authority: |
Elmi, Omid |
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Depositor: |
Saemian, Peyman |
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Date of Deposit: |
2023-06-19 |
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Holdings Information: |
https://doi.org/10.18419/darus-3558 |
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Study Scope |
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Keywords: |
Earth and Environmental Sciences, River Discharge, GRDC, Remote Sensing, Satellite Altimetry, Satellite Imagery |
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Abstract: |
The quantification of river discharge is essential for understanding global freshwater dynamics. However, the Global Runoff Data Center (GRDC) dataset has faced a decline in the number of active gauges since the 1980s, leaving only 14% of gauges active as of 2020. We develop the Remote Sensing-based Extension for the GRDC (RSEG) dataset that can ingest legacy gauge discharge and remote sensing observations. We employ a stochastic nonparametric mapping algorithm to extend the monthly discharge time series for inactive GRDC stations, benefiting from satellite imagery- and altimetry-derived river width and water height observations. After a rigorous quality assessment of our estimated discharge, involving statistical validation, tests and visual inspection, results in the salvation of discharge records for 3377 out of 6015 GRDC stations with an average monthly discharge exceeding 10 m³/s. The RSEG dataset regains monitoring capability for 83% of global river discharge measured by GRDC stations, equivalent to 7895 km³/month, providing valuable insight into Earth's river systems with comprehensive and up-to-date information. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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Maps_Of_Statistical_Indices.pdf |
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Notes: |
application/pdf |
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QuantileLookUpFunctionRivDischWidth.m |
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Notes: |
text/plain |
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QuantileLookUpFunctionRivDischWidthSimData.m |
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Notes: |
text/plain |
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RSEG_Summary_Table.pdf |
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Notes: |
application/pdf |
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RSEG_V01.nc |
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Notes: |
application/netcdf |