Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation
<p>This paper presents an innovative approach, STREAM – SaTellite-based Runoff Evaluation And Mapping – to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and total water storage anomalies (TWSAs). Within a very simple model struct...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2022-09-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/15/6935/2022/gmd-15-6935-2022.pdf |
| _version_ | 1811261820247212032 |
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| author | S. Camici G. Giuliani L. Brocca C. Massari A. Tarpanelli H. H. Farahani N. Sneeuw M. Restano J. Benveniste |
| author_facet | S. Camici G. Giuliani L. Brocca C. Massari A. Tarpanelli H. H. Farahani N. Sneeuw M. Restano J. Benveniste |
| author_sort | S. Camici |
| collection | DOAJ |
| description | <p>This paper presents an innovative approach, STREAM – SaTellite-based Runoff Evaluation And Mapping – to derive daily river discharge and runoff
estimates from satellite observations of soil moisture, precipitation, and total water storage anomalies (TWSAs). Within a very simple model structure, precipitation and soil moisture data are used to estimate the <i>quick-flow</i> river discharge component while TWSAs are used for obtaining its complementary part, i.e., the <i>slow-flow</i> river discharge component. The two are then added together to obtain river discharge estimates.</p>
<p>The method is tested over the Mississippi River basin for the period
2003–2016 by using precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), soil moisture data from the European Space Agency's Climate Change Initiative (ESA CCI), and total water storage data from the Gravity Recovery and Climate Experiment (GRACE). Despite the model simplicity, relatively high-performance scores are
obtained in river discharge estimates, with a Kling–Gupta efficiency (KGE) index greater than 0.64 both at the basin outlet and over several inner stations used for model calibration, highlighting the high information content of satellite observations on surface processes. Potentially useful for multiple operational and scientific applications, from flood warning systems to the understanding of water cycle, the added value of the STREAM approach is twofold: (1) a simple modeling framework, potentially suitable for global runoff monitoring, at daily timescale when forced with satellite
observations only, and (2) increased knowledge of natural processes and human activities as well as their interactions on the land.</p> |
| first_indexed | 2024-04-12T19:12:47Z |
| format | Article |
| id | doaj.art-9a8e46cf795f4bf68dba0d8c5ef1ffeb |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-04-12T19:12:47Z |
| publishDate | 2022-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-9a8e46cf795f4bf68dba0d8c5ef1ffeb2022-12-22T03:19:50ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032022-09-01156935695610.5194/gmd-15-6935-2022Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimationS. Camici0G. Giuliani1L. Brocca2C. Massari3A. Tarpanelli4H. H. Farahani5N. Sneeuw6M. Restano7J. Benveniste8National Research Council, Research Institute for Geo-Hydrological Protection, Perugia, ItalyNational Research Council, Research Institute for Geo-Hydrological Protection, Perugia, ItalyNational Research Council, Research Institute for Geo-Hydrological Protection, Perugia, ItalyNational Research Council, Research Institute for Geo-Hydrological Protection, Perugia, ItalyNational Research Council, Research Institute for Geo-Hydrological Protection, Perugia, ItalyInstitute of Geodesy, University of Stuttgart, Geschwister-Scholl-Straße 24D, 70174 Stuttgart, GermanyInstitute of Geodesy, University of Stuttgart, Geschwister-Scholl-Straße 24D, 70174 Stuttgart, GermanySERCO c/o ESA-ESRIN, Largo Galileo Galilei, Frascati, 00044, ItalyEuropean Space Agency, ESA-ESRIN, Largo Galileo Galilei, Frascati, 00044, Italy<p>This paper presents an innovative approach, STREAM – SaTellite-based Runoff Evaluation And Mapping – to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and total water storage anomalies (TWSAs). Within a very simple model structure, precipitation and soil moisture data are used to estimate the <i>quick-flow</i> river discharge component while TWSAs are used for obtaining its complementary part, i.e., the <i>slow-flow</i> river discharge component. The two are then added together to obtain river discharge estimates.</p> <p>The method is tested over the Mississippi River basin for the period 2003–2016 by using precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), soil moisture data from the European Space Agency's Climate Change Initiative (ESA CCI), and total water storage data from the Gravity Recovery and Climate Experiment (GRACE). Despite the model simplicity, relatively high-performance scores are obtained in river discharge estimates, with a Kling–Gupta efficiency (KGE) index greater than 0.64 both at the basin outlet and over several inner stations used for model calibration, highlighting the high information content of satellite observations on surface processes. Potentially useful for multiple operational and scientific applications, from flood warning systems to the understanding of water cycle, the added value of the STREAM approach is twofold: (1) a simple modeling framework, potentially suitable for global runoff monitoring, at daily timescale when forced with satellite observations only, and (2) increased knowledge of natural processes and human activities as well as their interactions on the land.</p>https://gmd.copernicus.org/articles/15/6935/2022/gmd-15-6935-2022.pdf |
| spellingShingle | S. Camici G. Giuliani L. Brocca C. Massari A. Tarpanelli H. H. Farahani N. Sneeuw M. Restano J. Benveniste Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation Geoscientific Model Development |
| title | Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation |
| title_full | Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation |
| title_fullStr | Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation |
| title_full_unstemmed | Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation |
| title_short | Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation |
| title_sort | synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation |
| url | https://gmd.copernicus.org/articles/15/6935/2022/gmd-15-6935-2022.pdf |
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