Search

In the broad field of sensors and 3D information retrieval, bathymetric reconstruction from side-scan sonar imaging is associated with unique technical hurdles. Neural Networks have recently led to promising new solutions in this field, but the available methods tend to be complex and data-intensive in a way typically making their use in a riverine environment impossible. Throughout our work, we have focused on simplifying the problem-handling and treating compatibility with a riverine environment as priority. In our work, Long Short-Term Memory proved to be effective in a surprisingly simple form. Combined with traditional post-processing techniques in the GIS environment, like median filtered focal statistics, our workflow ultimately results in ∼0.259 m median of error on the evaluation dataset of the Dráva River.

River bathymetry (RB) is a fundamental dataset in the field of river research. However, mountainous regions often lack comprehensive data due to topographical and transportation challenges. Remote sensing technology provides an innovative method for estimating RB. In this study, the theoretical relationship between the water level and the river width is established by generalizing the channel cross-section shape. A novel RB estimation method was proposed, integrating the Hydroweb dataset and Sentinel-1 images. The impacts of exposure, reach-average length, and remote sensing observation errors on estimation accuracy were systematically analyzed. The method was applied to the Upper Yangtze River to evaluate its potential for estimating river discharge. Results reveal that: ① The estimation error of the riverbed elevation ranges from 4.00 m to 4.06 m, with the estimated cross-section representing 73.69% to 80.29% of the actual area, indicating precise RB estimation. ② Exposure rate emerges as a primary factor, significantly enhancing estimation accuracy. An appropriate reach-average length improves the estimation precision and optimal length of 10km is advised for the Upper Yangtze River. Furthermore, the accuracy of RB estimation is more susceptible to water level errors in remote sensing than to river width. ③ The method demonstrates the potential to estimate river discharge achieving a Nash efficiency coefficient of 0.92. The research outcome can provide a novel approach to RB monitoring in data-scarce regions. [ABSTRACT FROM AUTHOR]

Digital Elevation Models (DEMs) act as an essential input to hydraulic models for the simulation of flood hazard maps. Coarser resolution DEMs are subject to higher levels of uncertainty, particularly in capturing river‐bed bathymetry. The principal aim of the present study was to assess the potential use of freely available DEMs and the 1D and 2D HEC‐RAS modeling approaches for flood mapping in four different types of river morphology. The DEM created from direct river survey (Surveyed DEM) was used as a benchmark to assess three remote sensing‐based DEMs (i.e., ALOS, SRTM, and ASTER). The results indicated that ALOS is more accurate. However, the regeneration of main‐channel bathymetry was poor for floodplain‐meandering and braided river reaches. The DEMs were then corrected by optimizing the number and layout of representative sections. A total of 144 tests were carried out. The results indicated that the flood‐mapping index F of ALOS increased from 86% to 91%. The flood mapping with a 1D model was sufficient in straight reaches (F‐index 84%). In floodplain‐meandering rivers, a 2D model had to be used to reach an F‐index up to 81%. The responses of both 1D and 2D models were almost identical in the case of wide‐braided rivers. [ABSTRACT FROM AUTHOR]

The development of bathymetric LiDAR technology has contributed significantly to both the quality and quantity of river bathymetry data. Although several bathymetric LiDAR sensors are available today, studies that evaluate the performance of the different bathymetric LiDAR sensors comparatively are still lacking. This study evaluates the performance of three bathymetric LiDAR sensors, CZMIL Supernova, Riegl VQ880-G, and Riegl VQ840-G, used with different acquisition approaches, in mapping Lærdal River bathymetry in Norway. The performance was evaluated based on comparing the sensors against a multibeam echosounder (MBES), a terrestrial laser scanner (TLS), and by an intercomparison between the individual sensors. The comparison was completed by comparing point clouds from the instruments and through the comparison of DEMs created from the point clouds. For the comparison against the MBES, the results show that the median residuals range between 3 to 13 cm, while against the TLS the median residuals range between 0 to 5 cm. The comparison of the CZMIL sensor against the two Riegl sensors shows median residuals of around 12 cm where the CZMIL map is shallower against the VQ880-G and deeper against the VQ840-G sensor. For the two Riegl sensors, the results show a median difference of 2 cm with the VQ880-G map deeper. We do observe that areas with high residuals are linked to river features such as large substrate variability, steep banks, and whitewater/turbulent flow. The study shows that all the LiDAR instruments provide high-quality representations of the river geometry and create a solid foundation for planning, modelling, or other work in rivers where detailed bathymetry is needed. [ABSTRACT FROM AUTHOR]

Abstract Digital Elevation Models (DEMs) act as an essential input to hydraulic models for the simulation of flood hazard maps. Coarser resolution DEMs are subject to higher levels of uncertainty, particularly in capturing river‐bed bathymetry. The principal aim of the present study was to assess the potential use of freely available DEMs and the 1D and 2D HEC‐RAS modeling approaches for flood mapping in four different types of river morphology. The DEM created from direct river survey (Surveyed DEM) was used as a benchmark to assess three remote sensing‐based DEMs (i.e., ALOS, SRTM, and ASTER). The results indicated that ALOS is more accurate. However, the regeneration of main‐channel bathymetry was poor for floodplain‐meandering and braided river reaches. The DEMs were then corrected by optimizing the number and layout of representative sections. A total of 144 tests were carried out. The results indicated that the flood‐mapping index F of ALOS increased from 86% to 91%. The flood mapping with a 1D model was sufficient in straight reaches (F‐index 84%). In floodplain‐meandering rivers, a 2D model had to be used to reach an F‐index up to 81%. The responses of both 1D and 2D models were almost identical in the case of wide‐braided rivers.

Unmanned aerial vehicles (UAVs), affordable precise Global Navigation Satellite System hardware, echo sounders, open-source 3D hydrodynamic modelling software, and freely available satellite data have opened up opportunities for a robust, affordable, physics-based approach to monitor river flows. In short, the hardware can be used to produce the geometry. 3D hydrodynamic modelling offers a framework to establish relationships between river flow and state variables such as width and depth, while satellite images with surface water detection methods or altimetry records can be used to operationally monitor flows through the established rating curve. Uncertainties in the data acquisition may propagate into uncertainties in the relationships found between discharge and state variables. Variations in acquired geometry emanate from the different ground control point (GCP) densities and distributions which are used during photogrammetry-based terrain reconstruction. In this study, we develop a rating curve using affordable data collection methods and basic principles of physics. The specific objectives were to: determine how the rating curve based on a 3D hydraulic model compares with conventional methods; investigate the impact of geometry uncertainty on estimated discharge when applied in a hydraulic model; and investigate how uncertainties in continuous observations of depth and width from satellite platforms propagate into uncertainties in river flow estimates using the rating curves obtained. The study shows comparable results between the 3D and traditional river rating discharge estimations. The rating curve derived on the basis of 3D hydraulic modelling was within a 95 % confidence interval of the traditional gauging based rating curve. The physics- based estimation requires determination of the roughness coefficient within the permanent bed and the floodplain using field observation as both the end of dry and wet season. Furthermore, the study demonstrates that variations in the density of GCPs beyond an optimal number (9) has no significant influence on the resultant rating relationships. Finally, the study observes that it depends on the magnitude of the flow which state variable approximation (water level & river width) is most promising to use. Combining stage appropriate proxies (water level when the floodplain is entirely filled, and width when the floodplain is filling) in data limited environments yields more accurate discharge estimations. The study was able to successfully apply low cost technologies for accurate river monitoring through bhydraulic modelling. In future studies, a larger amount of in-situ gauge readings may be considered so as to optimise the validation process. [ABSTRACT FROM AUTHOR]

Several studies have focused on the importance of river bathymetry (channel geometry) in hydrodynamic routing along individual reaches. However, its effect on other watershed processes such as infiltration and surface water (SW)‐groundwater (GW) interactions has not been explored across large river networks. Surface and sbsurface processes are interdependent, therefore, errors due to inaccurate representation of one watershed process can cascade across other hydraulic or hydrologic processes. This study hypothesizes that accurate bathymetric representation is not only essential for simulating channel hydrodynamics but also affects subsurface processes by impacting SW‐GW interactions. Moreover, quantifying the effect of bathymetry on surface and subsurface hydrological processes across a river network can facilitate an improved understanding of how bathymetric characteristics affect these processes across large spatial domains. The study tests this hypothesis by developing physically based distributed models capable of bidirectional coupling (SW‐GW) with four configurations with progressively reduced levels of bathymetric representation. A comparison of hydrologic and hydrodynamic outputs shows that changes in channel geometry across the four configurations has a considerable effect on infiltration, lateral seepage, and location of water table across the entire river network. For example, when using bathymetry with inaccurate channel conveyance capacity but accurate channel depth, peak lateral seepage rate exhibited 58% error. The results from this study provide insights into the level of bathymetric detail required for accurately simulating flooding‐related physical processes while also highlighting potential issues with ignoring bathymetry across lower order streams such as spurious backwater flow, inaccurate water table elevations, and incorrect inundation extents. Key Points: The effect of river geometry on subsurface processes, such as infiltration and lateral seepage in large‐scale fluvial modeling is highlightedSubsurface processes in the floodplain are controlled by overall channel characteristics, rather than channel shapeChannel conveyance capacity and longitudinal slope are critical bathymetric controls of subsurface processes in floodplains of river network [ABSTRACT FROM AUTHOR]

River bathymetry is an important parameter for hydrodynamic modeling; however, it is associated with large bias because direct large‐scale measurements are impractical. Recent studies adjusted river bathymetry data based on assessment of the difference between modeled and observed water surface elevation (WSE); however, model uncertainties in river discharge can lead to unintended errors in correcting river bathymetry. In this study, we propose a simple but robust and rational correction method of river bathymetry using the bias between stage–discharge rating curves rather than WSE time series data. The rating curve represents the internal characteristics of the river section, and is not sensitive to the instantaneous simulated discharge errors. Our results showed that the corrected river bathymetry are robust to bias in runoff as they converged among experiments driven by noise‐corrupted or multimodel runoff forcing. Evaluation with the corrected river bathymetry against virtual truth demonstrated that the new method reduced 0.85–1.12 m of the absolute bias than the result from the conventional method. The deviation among the results reduced by more than 70% particularly in river sections with no backwater effects. Evaluation of the corrected river model output also showed the advantage of rating‐curve bias correction, as the simulated WSE is reasonably better only with better runoff and it does not conceal errors in runoff inputs. Given the difficulty of eliminating discharge errors and bias in runoff, a method for correcting river bathymetry that is free from discharge and runoff errors is important for improving hydrodynamic modeling. Plain Language Summary: We propose a simple method for correcting river bathymetry in river models using bias between stage–discharge rating curves rather than direct bias of water surface elevation as used in conventional methods. The rating‐curve bias is insensitive to runoff and discharge and the corrected river bathymetry are robust to biases in runoff or discharge modeling errors. The performance of corrected river model is also more reasonable than that of conventional method as it does not conceal the errors in runoff or discharge. Accurately modeling discharge is challenging due to climate forcing, model complexity, inhomogeneity of model parameters, and the difficulty of representing human interventions. Therefore, a robust method for correcting river bathymetry in hydrodynamic models, which is independent of river discharge bias, is required. Key Points: Empirical river bathymetry approximation equations introduce bias into local water surface elevation (WSE) simulationsWSE bias between the rating curves for simulations and observations reflects only river bathymetry biasRiver bathymetry corrections based on the rating curve are robust, regardless of runoff uncertainties and discharge errors [ABSTRACT FROM AUTHOR]

The development of bathymetric LiDAR technology has contributed significantly to both the quality and quantity of river bathymetry data. Although several bathymetric LiDAR sensors are available today, studies that evaluate the performance of the different bathymetric LiDAR sensors comparatively are still lacking. This study evaluates the performance of three bathymetric LiDAR sensors, CZMIL Supernova, Riegl VQ880-G, and Riegl VQ840-G, used with different acquisition approaches, in mapping Lærdal River bathymetry in Norway. The performance was evaluated based on comparing the sensors against a multibeam echosounder (MBES), a terrestrial laser scanner (TLS), and by an intercomparison between the individual sensors. The comparison was completed by comparing point clouds from the instruments and through the comparison of DEMs created from the point clouds. For the comparison against the MBES, the results show that the median residuals range between 3 to 13 cm, while against the TLS the median residuals range between 0 to 5 cm. The comparison of the CZMIL sensor against the two Riegl sensors shows median residuals of around 12 cm where the CZMIL map is shallower against the VQ880-G and deeper against the VQ840-G sensor. For the two Riegl sensors, the results show a median difference of 2 cm with the VQ880-G map deeper. We do observe that areas with high residuals are linked to river features such as large substrate variability, steep banks, and whitewater/turbulent flow. The study shows that all the LiDAR instruments provide high-quality representations of the river geometry and create a solid foundation for planning, modelling, or other work in rivers where detailed bathymetry is needed.

The Ohashi River is a narrow water stream that connects two brackish lakes in Japan. Intermittent saline water intrusion often occurs in Lake Shinji from Lake Nakaumi through Ohashi River. In this study, two approaches were discussed to reproduce the hydrodynamic conditions of a morphologically complex river. In the first approach, the river sinuosity was straightened. The straightening of the river resulted in a higher flow velocity and water flux coefficient due to the reduction in the flow path and the resistance, and this approach was found to be appropriate for the reproduction of the flow velocity. However, the river shape was visually quite different from the actual river morphology. In the second approach, the prime focus was given to the shape and bathymetry to quantitively reproduce the flowrate of the saline water intrusion. This approach resulted in an underestimation of the flow velocity, which was compensated by increasing the cross-sectional area of the river. A slower flow velocity causes up to a 3-h time lag for the water mass to pass through the Ohashi River, which in principle should affect the temporal variations of the water temperature and salinity. Fortunately, as the typical time scale for water temperature and salinity fluctuations in the Ohashi River is a few days, a 3-h time lag did not cause any problems.

• Estimated river bathymetry using the satellites data on river width and water level. • Derived nonlinear z-w relationship from generalized channel cross section. • Investigated the influences of channel exposure on river bathymetry estimation. • Studied the effects of reach-averaging length and remote sensing data on bathymetry. River bathymetry is a key variable in estimating river discharge by remote sensing. However, traditional methods of mapping river bathymetry are expensive and time-consuming, which hinders the estimation of river discharge. In this study, we propose and test a method for estimating river bathymetry by combining remotely sensed observations of water level (z) and river width (w) with a nonlinear z - w relationship derived from a generalized channel cross-sectional shape. The results from five reaches of the upper Yangtze River show that the absolute relative error for the estimate is between 1.25% and 6.18%, indicating the ability of this method to provide accurate estimates. The channel exposure (e) is the main limitation of the proposed method, and the river bathymetry estimates improve significantly with increasing e. For the upper Yangtze River, averaging reaches over an appropriate length can reduce variability in river bathymetry estimate, especially when data are reach-averaged over a length of 10 km. Considering that a priori bathymetric information is not required and its computational process is relatively simple, the proposed method could open up the possibility of bathymetry modeling of global rivers. [ABSTRACT FROM AUTHOR]

The Ohashi River is a narrow water stream that connects two brackish lakes in Japan. Intermittent saline water intrusion often occurs in Lake Shinji from Lake Nakaumi through Ohashi River. In this study, two approaches were discussed to reproduce the hydrodynamic conditions of a morphologically complex river. In the first approach, the river sinuosity was straightened. The straightening of the river resulted in a higher flow velocity and water flux coefficient due to the reduction in the flow path and the resistance, and this approach was found to be appropriate for the reproduction of the flow velocity. However, the river shape was visually quite different from the actual river morphology. In the second approach, the prime focus was given to the shape and bathymetry to quantitively reproduce the flowrate of the saline water intrusion. This approach resulted in an underestimation of the flow velocity, which was compensated by increasing the cross-sectional area of the river. A slower flow velocity causes up to a 3-h time lag for the water mass to pass through the Ohashi River, which in principle should affect the temporal variations of the water temperature and salinity. Fortunately, as the typical time scale for water temperature and salinity fluctuations in the Ohashi River is a few days, a 3-h time lag did not cause any problems. [ABSTRACT FROM AUTHOR]