Higher-density river discharge observation through integration of multiple satellite data: Midstream Yellow River, China
Silty Midstream Yellow River (MYR), characterized by its turbid waters, is currently underserved by a sparse network of gauging stations, which is insufficient for comprehensive flow monitoring. Establishing an extensive gauging network in this region is almost impractical. This study addresses the...
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Elsevier
2025-03-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843225000809 |
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| author | Qihang Liu Yun Chen João Paulo L.F. Brêda Handi Cui Hongtao Duan Chang Huang |
| author_facet | Qihang Liu Yun Chen João Paulo L.F. Brêda Handi Cui Hongtao Duan Chang Huang |
| author_sort | Qihang Liu |
| collection | DOAJ |
| description | Silty Midstream Yellow River (MYR), characterized by its turbid waters, is currently underserved by a sparse network of gauging stations, which is insufficient for comprehensive flow monitoring. Establishing an extensive gauging network in this region is almost impractical. This study addresses the challenge by estimating discharge at selected ungauged reaches of the MYR, leveraging multiple remote sensing datasets with high spatiotemporal resolutions, complemented by Manning’s Equation. Satellite observation reaches (SORs) were strategically positioned at each small river section between adjacent tributaries, chosen for their variable river width, stable channel terrain, and uniform flow, which are conducive to the application of Manning’s Equation. Hydraulic parameters for 16 SORs were calculated, integrating optical and Synthetic Aperture Radar data with a digital elevation model to derive river width, water surface level, and slope. River bathymetry and bed elevation, not directly observable by satellites, were simulated using an adapted altimetry-assimilated one-dimensional (1D) hydraulic model. The discharge time-series at the SOR locations was subsequently retrieved and validated against observed discharges at existing gauges, demonstrating high accuracy with Nash-Sutcliffe Efficiency values ranging from 0.704 to 0.779 and R2 values from 0.773 to 0.925. This study effectively expanded discharge observations at ungauged river reaches, increasing the number of observation sites from three to sixteen and achieving an average monitoring interval of 2.7 days per site. The enhanced river discharge observations facilitated by remote sensing provides more granular water and sediment flux data, which is instrumental for future hydrological research and soil conservation planning within large river basins. |
| format | Article |
| id | doaj-art-de23f485d9514d8d93598ec6ddf7f9b3 |
| institution | DOAJ |
| issn | 1569-8432 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj-art-de23f485d9514d8d93598ec6ddf7f9b32025-08-20T02:59:50ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322025-03-0113710443310.1016/j.jag.2025.104433Higher-density river discharge observation through integration of multiple satellite data: Midstream Yellow River, ChinaQihang Liu0Yun Chen1João Paulo L.F. Brêda2Handi Cui3Hongtao Duan4Chang Huang5Engineering Technology Research Center of Resources Environment and Geographic Information System of Anhui Province, School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China; Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China; CSIRO Environment, Canberra, ACT 2601, AustraliaCSIRO Environment, Canberra, ACT 2601, AustraliaWageningen University & Research, Wageningen 6700 AA, NetherlandsShaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, ChinaShaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China; Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, ChinaEngineering Technology Research Center of Resources Environment and Geographic Information System of Anhui Province, School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China; Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China; Corresponding author.Silty Midstream Yellow River (MYR), characterized by its turbid waters, is currently underserved by a sparse network of gauging stations, which is insufficient for comprehensive flow monitoring. Establishing an extensive gauging network in this region is almost impractical. This study addresses the challenge by estimating discharge at selected ungauged reaches of the MYR, leveraging multiple remote sensing datasets with high spatiotemporal resolutions, complemented by Manning’s Equation. Satellite observation reaches (SORs) were strategically positioned at each small river section between adjacent tributaries, chosen for their variable river width, stable channel terrain, and uniform flow, which are conducive to the application of Manning’s Equation. Hydraulic parameters for 16 SORs were calculated, integrating optical and Synthetic Aperture Radar data with a digital elevation model to derive river width, water surface level, and slope. River bathymetry and bed elevation, not directly observable by satellites, were simulated using an adapted altimetry-assimilated one-dimensional (1D) hydraulic model. The discharge time-series at the SOR locations was subsequently retrieved and validated against observed discharges at existing gauges, demonstrating high accuracy with Nash-Sutcliffe Efficiency values ranging from 0.704 to 0.779 and R2 values from 0.773 to 0.925. This study effectively expanded discharge observations at ungauged river reaches, increasing the number of observation sites from three to sixteen and achieving an average monitoring interval of 2.7 days per site. The enhanced river discharge observations facilitated by remote sensing provides more granular water and sediment flux data, which is instrumental for future hydrological research and soil conservation planning within large river basins.http://www.sciencedirect.com/science/article/pii/S1569843225000809River dischargeRemote sensingImage fusionData assimilationSediment flux |
| spellingShingle | Qihang Liu Yun Chen João Paulo L.F. Brêda Handi Cui Hongtao Duan Chang Huang Higher-density river discharge observation through integration of multiple satellite data: Midstream Yellow River, China International Journal of Applied Earth Observations and Geoinformation River discharge Remote sensing Image fusion Data assimilation Sediment flux |
| title | Higher-density river discharge observation through integration of multiple satellite data: Midstream Yellow River, China |
| title_full | Higher-density river discharge observation through integration of multiple satellite data: Midstream Yellow River, China |
| title_fullStr | Higher-density river discharge observation through integration of multiple satellite data: Midstream Yellow River, China |
| title_full_unstemmed | Higher-density river discharge observation through integration of multiple satellite data: Midstream Yellow River, China |
| title_short | Higher-density river discharge observation through integration of multiple satellite data: Midstream Yellow River, China |
| title_sort | higher density river discharge observation through integration of multiple satellite data midstream yellow river china |
| topic | River discharge Remote sensing Image fusion Data assimilation Sediment flux |
| url | http://www.sciencedirect.com/science/article/pii/S1569843225000809 |
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