Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2018WR023067 |
Simulating Flood-Induced Riverbed Transience Using Unmanned Aerial Vehicles, Physically Based Hydrological Modeling, and the Ensemble Kalman Filter | |
Tang, Qi1,2,3; Schilling, Oliver S.4,5; Kurtz, Wolfgang1,2,6; Brunner, Philip4; Vereecken, Harry1,2; Franssen, Harrie-Jan Hendricks1,2 | |
2018-11-01 | |
发表期刊 | WATER RESOURCES RESEARCH
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ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2018 |
卷号 | 54期号:11页码:9342-9363 |
文章类型 | Article |
语种 | 英语 |
国家 | Germany; Switzerland; Canada |
英文摘要 | Flood events can change the riverbed topography as well as the riverbed texture and structure, which in turn can influence the riverbed hydraulic conductivity (K-rb) and river-aquifer exchange fluxes. A major flood event occurred in the Emme River in Switzerland in 2014, with major implications for the riverbed structure. The event was simulated with the fully integrated hydrological model HydroGeoSphere. The aim was to investigate the effect of the spatial and temporal variability of riverbed topography and K-rb on predictions of hydraulic states and fluxes and to test whether data assimilation (DA) based on the ensemble Kalman filter (EnKF) can better reproduce flood-induced changes to hydraulic states and parameters with the help of riverbed topography changes recorded with an unmanned aerial vehicle (UAV) and through-water photogrammetry. The performance of DA was assessed by evaluating the reproduction of the hydraulic states for the year 2015. While the prediction of surface water discharge was not affected much by the changes in riverbed topography and in K-rb, using the UAV-derived postflood instead of the preflood riverbed topography reduced the root-mean-square error of predicted heads (RMSE [h]) by 24%. If, in addition to using the postflood riverbed topography, also K-rb and aquifer hydraulic conductivity (K-aq) were updated through DA after the flood, the RMSE (h) was reduced by 55%. We demonstrate how updating of K-rb and K-aq based on EnKF and UAV-based observations of riverbed topography transience after a major flood event strongly improve predictions of postflood hydraulic states. |
英文关键词 | data assimilation ensemble Kalman filter riverbed heterogeneity fully coupled surface water-groundwater interactions UAV HydroGeoSphere |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000453369400043 |
WOS关键词 | AQUIFER EXCHANGE FLUXES ; HYDRAULIC CONDUCTIVITY ; DATA ASSIMILATION ; HYPORHEIC EXCHANGE ; WATER EXCHANGE ; GROUNDWATER ; HETEROGENEITY ; STREAM ; TOPOGRAPHY ; SYSTEM |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/22054 |
专题 | 资源环境科学 |
作者单位 | 1.Forschungszentrum Julich, Inst Bio & Geosci Agrosphere IBG 3, Julich, Germany; 2.Geoverbund ABC J, HPSC TerrSys, Ctr High Performance Sci Comp Terr Syst, Julich, Germany; 3.Helmholtz Ctr Polar & Marine Res, Alfred Wegener Inst, Bremerhaven, Germany; 4.Univ Neuchatel, Ctr Hydrogeol & Geotherm, Neuchatel, Switzerland; 5.Univ Laval, Dept Geol & Geol Engn, Pavillon Adrien Pouliot, Quebec City, PQ, Canada; 6.Leibniz Supercomp Ctr, Environm Comp Grp, Garching, Germany |
推荐引用方式 GB/T 7714 | Tang, Qi,Schilling, Oliver S.,Kurtz, Wolfgang,et al. Simulating Flood-Induced Riverbed Transience Using Unmanned Aerial Vehicles, Physically Based Hydrological Modeling, and the Ensemble Kalman Filter[J]. WATER RESOURCES RESEARCH,2018,54(11):9342-9363. |
APA | Tang, Qi,Schilling, Oliver S.,Kurtz, Wolfgang,Brunner, Philip,Vereecken, Harry,&Franssen, Harrie-Jan Hendricks.(2018).Simulating Flood-Induced Riverbed Transience Using Unmanned Aerial Vehicles, Physically Based Hydrological Modeling, and the Ensemble Kalman Filter.WATER RESOURCES RESEARCH,54(11),9342-9363. |
MLA | Tang, Qi,et al."Simulating Flood-Induced Riverbed Transience Using Unmanned Aerial Vehicles, Physically Based Hydrological Modeling, and the Ensemble Kalman Filter".WATER RESOURCES RESEARCH 54.11(2018):9342-9363. |
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