Simulating Flood‐Induced Riverbed Transience Using Unmanned Aerial Vehicles, Physically Based Hydrological Modeling, and the Ensemble Kalman Filter

Abstract

Flood events can change the riverbed topography as well as the riverbed texture and structure, which in turn can influence the riverbed hydraulic conductivity (Krb) 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 Krb 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 Krb, 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 Krb and aquifer hydraulic conductivity (Kaq) were updated through DA after the flood, the RMSE (h) was reduced by 55%. We demonstrate how updating of Krb and Kaq based on EnKF and UAV‐based observations of riverbed topography transience after a major flood event strongly improve predictions of postflood hydraulic states.

Beyond Classical Observations in Hydrogeology: The Advantages of Including Exchange Flux, Temperature, Tracer Concentration, Residence Time, and Soil Moisture Observations in Groundwater Model Calibration

“…But with the capabilities of the current generation of flow models, one is no longer restricted to the simulation of such simple GW systems anymore or forced to oversimplify more complex GW systems—the current trend is toward the simulation of complex systems based on integrated surface water (SW)‐GW flow models (IFMs; Barthel & Banzhaf, ; Paniconi & Putti, ). Compared to numerical models that exclusively simulate GW flow, IFMs enable the simulation of GW and SW flow in a physically‐based and fully‐coupled way and allow the inclusion of many hydrologically relevant processes such as unsaturated flow through complex heterogeneous structures (e.g., Irvine et al, ; Schilling, Irvine, et al, ; Tang et al, , ), heat and mass transport (e.g., Carniato et al, ; Karan et al, ; Kurtz et al, ; Schilling et al, ), snow accumulation, melt and pore water freeze‐thaw (e.g., Cochand et al, ; Evans & Ge, ; Painter et al, ; Schilling et al, ; Shojae Ghias et al, ), and SW‐GW‐vegetation interactions (e.g., Banks et al, ; Maxwell & Condon, ; Schomburg et al, ). Compared to numerical flow models that exclusively simulate GW flow, IFMs require more parameters and boundary conditions to be defined and calibrated (the minimally required parameters and boundary conditions of different types of GW and SW simulations are listed in Table ).…”

Intra-catchment variability of surface saturation – insights from physically based simulations in comparison with biweekly thermal infrared image observations

“…Over the past years and decades, various field studies have mapped and analysed the spatial and temporal occurrence of surface saturation within different landscapes (e.g. Ambroise, 1986Ambroise, , 2016Dunne et al, 1975;Gburek and Sharpley, 1998;Latron and Gallart, 2007;Silasari et al, 2017;Tanaka et al, 1988). From these field studies it is well recognised that surface saturation varies in space and time and that this variability is affected by structural (e.g.…”

Intra-catchment variability of surface saturation – insights from longterm observations and simulations

“…HGS has been used in the past for addressing diverse questions at various temporal and spatial scales (e.g. Ala-aho et al, 2015;Davison et al, 2018;Erler et al, 2019;Frei et al, 2010;Munz et al, 2017;Nasta et al, 2019;Partington et al, 2013;Schilling et al, 2017;Tang et al, 2018). It also has already been applied for a 6 ha headwater region of the Weierbach catchment (Glaser et al, 2016.…”

“…This may sound trivial and several studies have already pointed out the importance of microtopography for the simulation of different hydrological aspects such as hydraulic heads, hyporheic surface-subsurface water exchange, bank storage and overbank flooding, water quality of shallow groundwater systems and runoff generation (e.g. Aleina et al, 2015;Frei et al, 2010;Käser et al, 2014;Van der Ploeg et al, 2012;Tang et al, 2018). Still, microtopography is not often considered in the 20 simulation of surface saturation patterns.…”