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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.

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]

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.

Topography represented in the form of Digital Elevation Models (DEMs) has profound applications in hydrological modeling. DEMs can be generated from several sources including satellite products, contours, survey data, and LiDAR, each with their own merits and demerits. Where high resolution, accuracy, and spatial extent are concerned, it is often found that a DEM from one source alone is not able to represent the topography of the target area with full accuracy. Upon comparing different DEMs, it was found that most were able to successfully represent mountainous regions but failed to represent flat deltaic regions. Therefore, in this research with Bago River basin, Myanmar as a study area, a new methodology to combine multiple sources of data with different data types is developed. The inputs are: (a) a 10 m DEM, developed using contour data, point elevation data, and UTM topographic maps; (b) a 5 m Digital Surface Model (DSM) acquired by the Advanced Land Observation Satellite (ALOS); and (c) 168 sets of multiple-point elevation data representing a cross-sectional survey along the Bago River and the Bago-Sittaung canal. The output is a 10 m resolution Enhanced DEM (EnDEM) which is able to preserve the merits of all the input data, i.e., upper mountainous region, lower flat deltaic basin, and the river bathymetry. This paper provides a novel approach to DEM integration and burning of the river cross-section onto the DEM. [ABSTRACT FROM AUTHOR]

Accurate river bathymetry is required for applications including hydrodynamic flow modelling and understanding morphological processes. Bathymetric measurements are typically a set of depths at discrete points that must be reconstructed into a continuous surface. A number of algorithms exist for this reconstruction, including spline-based techniques and kriging methods. A novel and efficient method is introduced to produce a co-ordinate system fitted to the river path suitable for bathymetric reconstructions. The method is based on numerical conformal mapping and can handle topological features such as islands and branches in the river. Bathymetric surfaces generated using interpolation over a conformal map are compared to spline-based and kriging methods on a section of the Balonne River, Australia. The results show that the conformal mapping algorithm produces reconstructions comparable in quality to existing methods, preserves flow-wise features and is relatively insensitive to the number of sample points, enabling faster data collection in the field. • Introduction of a new method for rapidly reconstructing river bathymetry from a set of point depth measurements. • Unlike some existing techniques, the method can handle complex river morphologies such as islands and branches. • The method only requires a set of depth points and a mask of the land and water areas, making it suitable for automation. [ABSTRACT FROM AUTHOR]

Bathymetric measurements play an important role in assessing the sedimentation rate, deposition of pollutants, erosion rate, or monitoring of morphological changes in a river, lake, or accumulation basin. In order to create a coherent and continuous digital elevation model (DEM) of a river bed, various data interpolation methods are used, especially when single-beam bathymetric measurements do not cover the entire area and when there are areas which are not measured. Interpolation methods are based on numerical models applied to natural landscapes (e.g., meandering river) by taking into account various morphometric and morphologies and a wide range of scales. Obviously, each interpolation method, used in standard or customised form, yields different results. This study aims at testing four interpolation methods in order to determine the most appropriate method which will give an accurate description of the riverbed, based on single-beam bathymetric measurements. The four interpolation methods selected in the present research are: inverse distance weighting (IDW), radial basis function (RBF) with completely regularized spline (CRS) which uses deterministic interpolation, simple kriging (KRG) which is a geo-statistical method, and Topo to Raster (TopoR), a particular method specifically designed for creating continuous surfaces from various elevation points, contour, or polygon data, suitable for creating surfaces for hydrologic analysis. Digital elevation models (DEM’s) were statistically analyzed and precision and errors were evaluated. The single-beam bathymetric measurements were made on the Siret River, between 0 and 35 km. To check and validate the methods, the experiment was repeated for five randomly selected cross-sections in a 1500 m section of the river. The results were then compared with the data extracted from each elevation model generated with each of the four interpolation methods. Our results show that: 1) TopoR is the most accurate technique, and 2) the two deterministic methods give large errors in bank areas, for the entire river channel and for the particular cross-sections.

The main objective of this study was to quantify the error associated with input data, including various resolutions of elevation datasets and Manning’s roughness for travel time computation and floodplain mapping. This was accomplished on the test bed, the Grand River (Ohio, USA) using the HEC-RAS model. LiDAR data integrated with survey data provided conservative predictions, whereas coarser elevation datasets provided a positive difference in the travel time (11.03-15.01%) and inundation area (32.56-44.52%). The minimum differences in travel time and inundation area were 0.50-4.33% and 3.55-7.16%, respectively, when the result from LiDAR integrated with survey data was compared with a 10-m DEM integrated with survey data. The results suggest that a 10-m DEM in the channel and LiDAR data in the floodplain combined with survey data would be appropriate for a flood warning system. Additionally, Manning’s roughness of the channel section was found to be more sensitive than that of the floodplain. The decrease in inundation area was highest (8.97%) for the lower value of Manning’s roughness. [ABSTRACT FROM AUTHOR]

An appropriate digital elevation model (DEM) is required for purposes of hydrodynamic modelling of floods. Such a DEM describes a river’s bathymetry (bed topography) as well as its surrounding area. Extensive measurements for creating accurate bathymetry are time-consuming and expensive. Mathematical modelling can provide an alternative way for representing river bathymetry. This study explores new possibilities in mathematical depiction of river bathymetry. A new bathymetric model (Bathy-supp) is proposed, and the model’s ability to represent actual bathymetry is assessed. Three statistical methods for the determination of model parameters were evaluated. The best results were achieved by the random forest (RF) method. A two-dimensional (2D) hydrodynamic model was used to evaluate the influence of the Bathy-supp model on the hydrodynamic modelling results. Also presented is a comparison of the proposed model with another state-of-the-art bathymetric model. The study was carried out on a reach of the Otava River in the Czech Republic. The results show that the proposed model’s ability to represent river bathymetry exceeds that of his current competitor. Use of the bathymetric model may have a significant impact on improving the hydrodynamic model results.

The main purpose of the present research is to develop software for reconstruction of the river bed on the basis of sparse cross-section measurements. The tools prepared should support the process of hydrodynamic model preparation for simulation of river flow. Considering the formats of available data and the requirements of modern modeling techniques, the prepared software is fully integrated with the GIS environment. The scripting language Python 2.7 implemented in ArcGIS 10.5.1 was chosen for this purpose. Two study cases were selected to validate and test the prepared procedures. These are stream reaches in Poland. The first is located on the Warta river, and the second on the Ner river. The data necessary for the whole procedure are: a digital elevation model, measurements of the cross-sections in the form of points, and two polyline layers representing an arbitrary river centerline and river banks. In the presented research the concept of a channel-oriented coordinate system is applied. The elevations are linearly interpolated along the longitudinal and transversal directions. The interpolation along the channel is implemented in three computational schemes linking different tools available in ArcGIS and ArcToolbox. A simplified comparison of memory usage and computational time is presented. The scheme linking longitudinal and spatial interpolation algorithms seems to be the most advantageous.

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]

Bathymetric measurements play an important role in assessing the sedimentation rate, deposition of pollutants, erosion rate, or monitoring of morphological changes in a river, lake, or accumulation basin. In order to create a coherent and continuous digital elevation model (DEM) of a river bed, various data interpolation methods are used, especially when single-beam bathymetric measurements do not cover the entire area and when there are areas which are not measured. Interpolation methods are based on numerical models applied to natural landscapes (e.g., meandering river) by taking into account various morphometric and morphologies and a wide range of scales. Obviously, each interpolation method, used in standard or customised form, yields different results. This study aims at testing four interpolation methods in order to determine the most appropriate method which will give an accurate description of the riverbed, based on single-beam bathymetric measurements. The four interpolation methods selected in the present research are: inverse distance weighting (IDW), radial basis function (RBF) with completely regularized spline (CRS) which uses deterministic interpolation, simple kriging (KRG) which is a geo-statistical method, and Topo to Raster (TopoR), a particular method specifically designed for creating continuous surfaces from various elevation points, contour, or polygon data, suitable for creating surfaces for hydrologic analysis. Digital elevation models (DEM's) were statistically analyzed and precision and errors were evaluated. The single-beam bathymetric measurements were made on the Siret River, between 0 and 35 km. To check and validate the methods, the experiment was repeated for five randomly selected cross-sections in a 1500 m section of the river. The results were then compared with the data extracted from each elevation model generated with each of the four interpolation methods. Our results show that: 1) TopoR is the most accurate technique, and 2) the two deterministic methods give large errors in bank areas, for the entire river channel and for the particular cross-sections. [ABSTRACT FROM AUTHOR]

An appropriate digital elevation model (DEM) is required for purposes of hydrodynamic modelling of floods. Such a DEM describes a river's bathymetry (bed topography) as well as its surrounding area. Extensive measurements for creating accurate bathymetry are time-consuming and expensive. Mathematical modelling can provide an alternative way for representing river bathymetry. This study explores new possibilities in mathematical depiction of river bathymetry. A new bathymetric model (Bathy-supp) is proposed, and the model's ability to represent actual bathymetry is assessed. Three statistical methods for the determination of model parameters were evaluated. The best results were achieved by the random forest (RF) method. A two-dimensional (2D) hydrodynamic model was used to evaluate the influence of the Bathy-supp model on the hydrodynamic modelling results. Also presented is a comparison of the proposed model with another state-of-the-art bathymetric model. The study was carried out on a reach of the Otava River in the Czech Republic. The results show that the proposed model's ability to represent river bathymetry exceeds that of his current competitor. Use of the bathymetric model may have a significant impact on improving the hydrodynamic model results. [ABSTRACT FROM AUTHOR]

The main purpose of the present research is to develop software for reconstruction of the river bed on the basis of sparse cross-section measurements. The tools prepared should support the process of hydrodynamic model preparation for simulation of river flow. Considering the formats of available data and the requirements of modern modeling techniques, the prepared software is fully integrated with the GIS environment. The scripting language Python 2.7 implemented in ArcGIS 10.5.1 was chosen for this purpose. Two study cases were selected to validate and test the prepared procedures. These are stream reaches in Poland. The first is located on the Warta river, and the second on the Ner river. The data necessary for the whole procedure are: a digital elevation model, measurements of the cross-sections in the form of points, and two polyline layers representing an arbitrary river centerline and river banks. In the presented research the concept of a channel-oriented coordinate system is applied. The elevations are linearly interpolated along the longitudinal and transversal directions. The interpolation along the channel is implemented in three computational schemes linking different tools available in ArcGIS and ArcToolbox. A simplified comparison of memory usage and computational time is presented. The scheme linking longitudinal and spatial interpolation algorithms seems to be the most advantageous. [ABSTRACT FROM AUTHOR]