River Cross-section Research Articles

Effectiveness of an ecological flow regime to assure successful recruitment of anadromous Coregoninae populations in the Rupert River (northern Quebec, Canada)

AbstractObjectiveAs part of a large‐scale hydroelectric project, the mean annual flow of the Rupert River (northern Quebec, Canada) was reduced by 52% at its mouth in 2009. To protect fish habitat, an ecological flow regime that was modulated according to the biological seasons was implemented downstream from the diversion point. An 8‐year monitoring program, including 2 years before partial diversion, was carried out to verify the effectiveness of this mitigation measure on the total annual abundance of anadromous Coregoninae (Cisco Coregonus artedi and Lake Whitefish C. clupeaformis) larvae, which was used as biological indicator of recruitment success. The monitoring also aimed to determine the effects of flow modification on the timing of the larval drift and the spatial distribution of larvae in a river cross section.MethodsEach year, sampling consisted of installing drift nets during the entire downstream larval migration in a river cross section of the lower Rupert River. Drift nets were systematically placed to ensure representative sampling of the river section.ResultPrior to flow reduction, the estimated total number of larvae varied between 1.8 and 8.6 million. Over the following 6 years, the estimated larval population has remained steady at 3–4 million. Otherwise, larval drift characteristics have not changed since the flow reduction, as (1) the duration of the larval drift is the same as before, about 1 month in May and early June, with a peak period of about 8 days; (2) rise in water temperature in spring is a determining factor in the timing of larval drift; and (3) the larvae drift mainly near the surface of the water.ConclusionThe monitoring results indicate that the ecological flow regime implemented in the Rupert River was adequate to maintain anadromous coregonine populations.

Simulation of the Hydraulic Model HEC-RAS Coupled with GIS and Remote Sensing to Study the Effect of River Cross-section Width in Detecting Flood-prone Areas

Abstract Flooding is one of the extreme hydrological phenomena. It is a recurring natural disaster that causes loss of life and property in many parts of the world, particularly during the monsoon season. It is important to address such issues for local government and policymakers to manage the flood properly. One such flood management activity is to develop a flood-prone area that depicts the spatial and temporal extent of flood accurately. The integration of the Hydrologic Engineering Centre - River Analysis System (HEC-RAS) model and geospatial tools have emerged as a crucial approach for identifying and mapping flood-prone areas. The successful application of the HEC-RAS model generally depends on the topographical data, which represents the channel and floodplain geometry. In floodplain geometry, discrete cross-sections play a vital role to develop the floodplain map, particularly in the flat topographical region. To extract these data it needs a high-quality digital elevation model (DEM), such as light detection and ranging (LiDAR). However, due to a lack of high-resolution topographical data, flood hazard mapping in developing countries is rare. In common practice, the centerline of the river is considered the flow path for the channel. The orientation of the cross-sections is perpendicular to this line and extends to reach the limits of the floodplain. But, it is difficult to define the limits and it may depend on the magnitude of the flood. Hence, in this study, the HEC RAS model coupled with ArcGIS has been applied to the Ganga River, which traverses through the Bihar state of India to study the effect of cross-sectional width to define the floodplain. The Bihar state is facing substantial hardships from annual flooding events with approximately 16.5% of India’s flood-prone area. The extreme flood values for 5, 10, and 25 years of return period have been determined and the influence of the three different cross-sectional widths to mapping the floodplain has been investigated. This novel perspective adds dimension to the understanding of flood dynamics and its implications for flood risk assessment. In this analysis, it has been observed that, with an increase in the width of the cross-section, the floodplain area also getting increased. In this topographical region, keeping a fixed flow path will underestimate the flood-prone area. The width of the flow path depends on the topography of the region and the river flow. The outcomes of this analysis provide valuable insights into the flood-inundated areas for the specified return periods, enabling the identification and prioritization of flood-prone zones.

Channel cross-section heterogeneity of particulate organic carbon transport in the Huanghe

Abstract. The Huanghe (Yellow River), one of the largest turbid river systems in the world, has long been recognized as a major contributor of suspended particulate matter (SPM) to the ocean. However, over the last few decades, the SPM export flux of the Huanghe has decreased over 90 % due to the high management, impacting the global export of particulate organic carbon (POC). To better constrain sources and modes of transport of POC beyond the previously investigated transportation of POC near the channel surface, SPM samples were for the first time collected over a whole channel cross-section in the lower Huanghe. Riverine SPM samples were analyzed for particle size and major element contents, as well as for POC content and dual carbon isotopes (13C and 14C). Clear vertical and lateral heterogeneities of the physical and chemical properties of SPM are observed within the river cross-section. For instance, finer SPM carry more POC in general with higher 14C activity near the surface of the right bank. Notably, we discuss how bank erosion in the alluvial plain is likely to generate lateral heterogeneity in POC composition. The Huanghe POC is millennial-aged (4020 ± 500 radiocarbon years) and dominated by organic carbon (OC) from the biosphere, while the lithospheric fraction is ca. 12 %. The mobilization of aged and refractory OC, including radiocarbon-dead biospheric OC, from deeper soil horizons of the loess–paleosol sequence through erosion in the Chinese Loess Plateau is an important mechanism contributing to fluvial POC in the Huanghe drainage basin. Altogether, anthropogenic activities can drastically change the compositions and transport dynamics of fluvial POC, consequentially altering the feedback of the source-to-sink trajectory of a river system to regional and global carbon cycles.

Numerical simulation of velocity distribution and pollution transport in a two-stage channel with vegetation on a floodplain

Compound cross-sections are common forms of river cross-sections in nature. Due to their more complex structure, it is more difficult to study their hydrodynamic and pollutant transport characteristics. How to establish effective models to simulate such conditions has recently become a hot topic of attention. The work presented in this article establishes a numerical model to simulate the flow velocity and pollutant transport in a compound cross-section channel using the lattice Boltzmann method and random displacement method to study the hydrodynamic and pollutant transport characteristics under flexible vegetation cover. The model can effectively generalize the vegetation drag force on the floodplain of the compound cross-section and provide the distribution pattern of flow velocity under uneven vegetation cover. At the same time, the lateral diffusion coefficients of pollutants on the main channel and floodplain are provided separately. These have higher accuracy than those determined by traditional methods that rely on simple longitudinal diffusion coefficients. This study can provide a theoretical reference for optimizing vegetation planting in compound cross-section channels.

Optimization of passive acoustic bedload monitoring in rivers by signal inversion

Abstract. Recent studies have shown that hydrophone sensors can monitor bedload flux in rivers by measuring the self-generated noise (SGN) emitted by bedload particles when they impact the riverbed. However, experimental and theoretical studies have shown that the measured SGN depends not only on bedload flux intensity but also the propagation environment, which differs between rivers. Moreover, the SGN can propagate far from the acoustic source and be well measured at distant river positions without bedload transport. It has been shown that this dependency of the measured SGN data on the propagation environment can significantly affect the performance of monitoring bedload flux by hydrophone techniques. In this article, we propose an inversion model to solve the problem of the SGN propagation and integration effect. In this model, we assume that the riverbed acts as SGN source areas with intensity proportional to the local bedload flux. The inversion model locates the SGN sources and calculates their corresponding acoustic power by solving a system of linear algebraic equations, accounting for the actual measured cross-sectional acoustic power (acoustic mapping) and attenuation properties. We tested the model using data from measured bedload SGN profiles (acoustic mapping with a drift boat) and bedload flux profiles (direct sampling with an Elwha sampler) acquired during two field campaigns conducted in 2018 and 2021 on the Giffre river in the French Alps. Results confirm that the bedload flux measured at different verticals on the river cross-section correlates more with the inversed acoustic power than measured acoustic power. Moreover, it was possible to fit data from the two field campaigns with a common curve after inversion, which was not possible with the measured acoustic data. The results of the inversion model, compared to measured data, show the importance of considering the propagation effect when using the hydrophone technique and offer new perspectives for the calibration of bedload flux with SGN in rivers.

Estimations of surface velocity distributions from X-band radar images during floods observed at the mouth of Tenryu River, Japan

X-band radar observations with a transmitting frequency of 9.4 GHz were conducted for over 10 h at the mouth of Tenryu River, Japan, to estimate surface velocity distributions during floods in 2010 and 2020 and analyse changes in the flow field caused by dredging in 2014. X-band radar is an imaging radar that can collect backscatter of floating objects flowing downstream with the flood flow every 2 s. The observation area extends approximately 1000 m × 1000 m. Particle image velocimetry is applied to the image sequences to guess the surface flow pattern. Flow direction in the main river channel changed smoothly, while surface flow speeds ranged from 1 to 3 m s–1 depending on the discharge. Water levels were computed using the estimated surface flow velocities, river cross-section from survey data, and observed discharge for indirect validation: it agreed within an error of 0.3 m with the observed water level. This paper highlights radar’s potential for estimating surface velocity distribution during floods and harsh weather conditions.

Modified geomorphic flood index (GFI) using land use parameter and effective rainfall ratio at Cikapundung River

To determine the flood inundation area requires hydrological data and measurements of river cross sections. Those data are very limited and expensive. The Geomorphic Flood Index (GFI) can be used to identify the initial potential for inundation of an area. Until now, the GFI method only uses Digital Elevation Model (DEM) data and the return period cannot be known. GFI is then modified by using topographic, rainfall and land use maps to determine the potential flood inundation for each return period. Based on the results of the GFI analysis with an n value of 0.31, the result of flood inundation is quite close to the hydraulic approach with a return period of 100 years. To find out the inundation of floods in other periods (2 years to 50 years), it is necessary to modify the GFI by entering the weight in the analysis of the flow accumulation. The results of the modified GFI flood inundation show that the smaller the return period, the lower the flood height and the reduced flood inundation area in the affected areas. Thus, the GFI approach is still good enough for initial estimates in determining flood inundation with quick analysis and lower costs.

Progress and Prospects in River Cross Section Extraction Based on Multi-Source Remote Sensing

Progress and Prospects in River Cross Section Extraction Based on Multi-Source Remote Sensing

Risk analysis of debris and non-debris flow in the Cisokan river flood event

Cisokan River is one of the main inflow rivers of Cirata Reservoir aside from Citarum River. Cisokan River is the second largest contributor to Cirata inflow after Citarum River. In May of 2023 Cisokan River experienced instances of flash flood disasters that submerged houses in Cianjur Regency, one of the affected villages is Ciranjang Village. Several news outlets reported that this flood also left debris and mud in the affected areas, which indicated that the flood was debris flow. This study conducts the risk analysis resulting from debris and non-debris flow with the changes in river cross-section due to sedimentation. In this study, modeling was carried out employing a Digital Elevation Model (DEM) map and utilizing the Hec-RAS software. One focus of the modeling was on simulating the Newtonian (non-debris) and non-Newtonian (debris), comparing the results and analyzing the risk from both. The result showed that the non-Newtonian flow’s flood inundated area is larger than the Newtonian flow’s, which means the high flood risk area of debris flow is 12.5% larger than the non-debris flow’s high flood risk area.

Modeling the Effects of River Training Works on the Hydraulic Properties of Euphrates River Cross-Sections Using HEC-RAS

Modeling the Effects of River Training Works on the Hydraulic Properties of Euphrates River Cross-Sections Using HEC-RAS

Spatial distribution of the water exchange through river cross-section – measurements and the numerical model

Spatial distribution of the water exchange through river cross-section – measurements and the numerical model

PERBANDINGAN ELEVASI DASAR SUNGAI BERDASARKAN HASIL ANALISIS PADA DEM DRONE, DEMNAS dan DEM SRTM

Digital elevation models (DEMs) are essential to accurately predict river cross-section in the watershed. Technological developments of unmanned aerial vehicles (UAVs) or drone has received a lot of attention in various research field to get the latest information from the area, because of its mobility, high resolution, and low cost, so it can be a competitive alternative to produce maps with precise georeferences. However, this has not been tested so far. In this study, We evaluated the accuracy of the DEMs generated from UAV imagery by comparing it to DEMNAS, DEM SRTM, and direct topographic measurements. We performed regression analysis on the river bed elevation of the Kuranji River Padang, where the river bed elevation is the result of the analysis of each DEM. The result found that for river bed elevation of the DEM Drone performed competitively to DEMNAS with the correlation test value (r) were 0,992 and 0.954, respectively. The result of the DEM SRTM analysis has a wider range of data variations than the DEM Drone and DEMNAS.

Analisis Spasial Kenaikan Tinggi Permukaan Air Batang Sumani Menggunakan Model Permukaan Digital

The occurrence of flooding in the Batang Sumani area of ​​Solok Regency is caused by several things, including the low slope of the river, the river cross-section which is not wide enough, the topography of the plains, heavy bends along the river and silting due to sedimentation and the vulnerability to flood hazards which is quite high in the watershed area. The influence of the topography of the plains causes inundation on land managed and used by the community. In accordance with technological developments in digital mapping of the earth's surface, the earth's surface can be presented in the form of a three-dimensional map called a Digital Elevation Model (DEM). This DEM is used as a model, analysis and representation of conditions related to the earth's surface. The use of DEM in the process of analyzing inundation caused by surface runoff will help in identifying the coverage of inundation areas and water catchment areas. By using the Simulate water level rise / flooding analysis from the Global Mapper application it is possible to simulate water level rise / flooding which makes it possible to simulate the coverage or spread of water/flooding by increasing the water level to a certain depth and spatial analysis using the Geographic Information System can see the influence of the inundation area on land use managed by the community around the inundation area. So that the location and coverage of the inundation on land use can be obtained. Most of the inundation areas are in garden areas at 37.56%, rice fields at 23.83%, fields at 24.03% and residential areas at 13.67%. There was a significant increase in the water level rise of 2 meters.

Simulation of runoff process based on the 3-D river network

Many rivers originating from mountainous areas cannot be adequately measured in the field to obtain sufficient basic data due to the challenging terrain, which poses difficulties for conducting relevant research such as hydrodynamic and sediment transport simulations, fluvial material fluxes. This study utilized a combination of 71 river cross sections extracted from multisource remote sensing data and 34 cross sections measured by hydrological stations between 2010 and 2018 to generate generalized cross sections for all river orders in the middle reaches of the Yellow River. By integrating the generalized cross sections, river surfaces, and traditional DEM river network, a comprehensive 3-D river network has been established to provide a more accurate representation of the morphological changes along the river channel. To tackle the challenge of simulating runoff in data-deficient areas, the Digital Yellow River Integrated Model (DYRIM), a potent distributed hydrological model, was enhanced by incorporating geometric parameters derived from a 3-D river network into almost all input parameters that can be obtained from multi-source remote sensing. This enhancement enabled the model to accurately simulate runoff in representative data-deficient rivers of the Loess Plateau. The Nash Efficiency coefficients for the simulated runoff exhibited improvement of 23% compared to previous studies, surpassing 0.8 for the period between 2010 and 2018. Additionally, the simulated errors for flow velocity and water depth were 7% and 9% respectively. This approach can provide essential data for the simulation of hydrological processes and improving hydrological models, as well as technical methodologies for related research such as sediment transport simulations and river carbon emissions.

Modeling unsteady and steady 1D hydrodynamics under different hydraulic conceptualizations: Model/Software development and case studies

The stage-discharge relationship is affected by hysteresis, especially in 1D river cross-sections with very mild slopes, and/or where backwater effects occur. To model these cases, hydraulic property (HP) estimations (e.g., hydraulic radius and conveyance) are usually required as closed-form functions of stage. However, these are typically unavailable for complex cross-sections with overbanks. For no sediment-laden flows, we created the HydroHP - 1D tool to solve the 1D Saint Venant Equations aided by the cross-section HP stored in tables. It also simulates irregular and composite hydraulic cross-sections, allows hydrodynamic simulation using the single-channel method (SCM), and proposes the divided channel method (DCM) for steady and unsteady flow analysis. A wide range of applications in rivers such as the Little Washita River and the Upper Negro River, and comparisons with NOAA normal depth solver, HEC-RAS, and with an analytical solution shows a promising scenario of applying HydroHP - 1D to estimate 1D steady and unsteady hydrodynamics.

Automated streamflow measurements in high‐elevation Alpine catchments

AbstractSalt dilution is a well‐established streamflow measurement method in creeks, which works particularly well downstream of turbulent flow sections as the mixing of the salt tracer is enhanced. Usually, salt dilution measurements are performed manually, which considerably limits the observations of rare peak flow events. These events are particularly important for constructing robust rating curves and avoiding large uncertainties in the extrapolation of streamflow values. An additional challenge is the variability of the river cross section, especially after larger discharge events, leading to nonstationary rating curves. Therefore, discharge measurements well distributed over time are needed to construct a reliable streamflow–water level relationship and to detect changes caused by erosion and deposition processes. To overcome these two issues, we used an automated streamflow measuring systems at three different sites with contrasting hydrological and hydraulic characteristics in the Alps. This system allowed us to measure discharge at nearly maximum flow of the observation period (2020–2021) at all three sites and to detect abrupt changes in the rating curve by performing event‐based salt injections. The uncertainty in the measurements was quantified, and the streamflow was compared with official gauging stations in the same catchment. Based on a very large dataset of almost 300 measurements, we were able to evaluate the reliability of the system and identify the primary sources of uncertainty in the experimental setup. One key aspect was the site selection for the downstream electrical conductivity sensors, as measurement location strongly controls the signal‐to‐noise ratio in the recorded breakthrough curves.

A hybrid machine learning-based multi-DEM ensemble model of river cross-section extraction: Implications on streamflow routing

Accurate representation of river channel and floodplain geometries is of prime concern for streamflow routing and flood inundation modelling under inadequate surveyed river cross-section data-condition, in many rivers across the globe. Due to global coverage and easy accessibility, the public domain medium resolution (1-arc second) DEMs such as SRTM, ASTER, and ALOS-AW3D30, with a linear vertical bias-correction approach, are widely used for hydrodynamic modelling of upland river networks. In this context, this study, for the first time, developed a hybrid machine learning-based Multi-DEM Ensemble (MDE) approach to simulate bias-corrected cross-sections using open source DEMs-extracted river cross-sections. Additionally, the hydraulic suitability of the simulated cross-sections and associated uncertainties were analysed. For this, the routing of streamflow and water level was performed using MIKE11-HD for a low-gradient flood-prone deltaic river basin of Eastern India (∼9000 km2) consisting of 19 river distributary systems. A comprehensive evaluation of the developed hybrid machine learning-based MDE models revealed an excellent performance of the Random Forest-Particle Swarm Optimisation-MDE (RF-PSO-MDE) model (NSE: 0.89–0.95; RMSE: 1.75–2.23 m) and Deep Neural Network-Particle Swarm Optimisation-MDE (DNN-PSO-MDE) model (NSE: 0.89–0.93; RMSE: 2.09–2.27 m) followed by the Support Vector Machine-Particle Swarm Optimisation-MDE (SVM-PSO-MDE) model (NSE: 0.87–0.92 and RMSE: 2.22–2.50 m). The MIKE11-HD simulations using RF-PSO-MDE and DNN-PSO-MDE model-simulated cross-sections were in close agreement with the observed streamflow and water level hydrographs, together with excellent matching of the flood peak, time to flood peak, and streamflow regimes. Predictive uncertainties analysis by the quantile regression technique confirmed an acceptable range of the Mean Prediction Interval and Percentage Interval Coverage Probability for the MIKE11-HD-RFMDE and MIKE11-HD-DNNMDE model variants including the MIKE11-HD-S model. Conclusively, the developed MDE models have potential for generating river cross-sections under sparse bathymetric conditions for the accurate simulation of streamflow and water level estimates using public domain digital elevation models.

Attenuation of trace organic compounds along hyporheic flow paths in a lowland sandbed stream

Knowledge of flow paths in hyporheic zones of streams is essential for understanding different turnover processes of various chemicals, such as trace organic compounds (TrOCs). Due to the spatial heterogeneity of hyporheic zones, exact flow paths in situ are unknown and thus, pore water sampling along individual flow paths remains a major challenge. To this end, we developed and tested a novel method to enforce specific flow paths under field conditions. Therefore, U-shaped pipes of 40 cm total flow path length were installed in flow direction along a river cross section in the hyporheic zone of the urban lowland River Erpe (Germany). This allowed us to determine sediment properties and to collect pore water samples along the specific flow paths during 16 consecutive hours. The pore water was analyzed for electrical conductivity, redox parameters, and TrOCs. Diurnal electrical conductivity fluctuations in the surface water and their propagation to the end of the flow paths resulted in median residence times of 11.67 or 16.92 h for different specific flow paths. A clear redox zonation along the flow paths was found. Of the 18 TrOCs studied, five were strongly attenuated (i.e., relative attenuation to surface water > 75 %), three exhibited moderate attenuation (75 to 25 %), nine were only slightly or not attenuated (< 25 %), and one compound increased in concentration (relative formation > 25 %) along the entire flow paths. For TrOCs that showed strong or moderate attenuation, the attenuation occurred mainly within the first 5 to 15 cm. This work highlights (1) the importance of knowing the specific flow paths for a comprehensive understanding of TrOC turnover in the hyporheic zone and (2) the relevance of appropriate biogeochemical and hydrological conditions for the attenuation of TrOCs.

Are open-source hydrodynamic models efficient in quantifying flood risks over mountainous terrains? An exhaustive analysis over the Hindu-Kush-Himalayan region

The Hindu-Kush-Himalaya is abode to numerous severely flood-prone mountainous stretches that distress vulnerable communities and cause massive destruction to physical entities such as hydropower projects. Adopting commercial flood models for replicating the dynamics of flood wave propagation over such regions is a major constraint due to the financial economics threaded to flood management. For the first instance, the present study attempts to investigate whether advanced open-source models are skillful in quantifying flood hazards and population exposure over mountainous terrains. While doing so, the performance of 1D-2D coupled HEC-RAS v6.3 (the most recent version developed by the U.S. Army Corps of Engineers) is reconnoitred for the first time in flood management literature. The most flood-prone region in Bhutan, the Chamkhar Chhu River Basin, housing large groups of communities and airports near its floodplains, is considered. HEC-RAS v6.3 setups are corroborated by comparing them with 2010 flood imagery derived from MODIS through performance metrics. The results indicate a sizable portion of the central part of the basin experiences very-high flood hazards with depth and velocities exceeding 3 m, and 1.6 m/s, respectively, during 50, 100, and 200-year return periods of floods. To affirm HEC-RAS, the flood hazards are compared with TUFLOW at 1D and 1D-2D coupled levels. The hydrological similarity within the channel is reflected at river cross-sections (NSE and KGE > 0.98), while overland inundation and hazard statistics differ, however, very less significant (<10 %). Later, flood hazards extracted from HEC-RAS are fused with the World-Pop population to estimate the degree of population exposure. The study ascertains that HEC-RAS v6.3 is an efficacious option for flood risk mapping over geographically arduous regions and can be preferred in resource-constrained environments ensuring a minimal degree of anomaly.

Coastal acoustic tomography system for monitoring transect suspended sediment discharge of Yangtze river

Suspended sediment discharge (SSD) in the Yangtze River (YR) plays a crucial role in transporting nutrients and sediment to the YR estuaries and the East China Sea. In order to gather information on suspended sediment concentration (SSC) and SSD across an entire river cross-section, we investigated a novel method supported by Coastal Acoustic Tomography (CAT). Consequently, two CAT systems were employed to estimate the cross-section averaged SSC and SSD at the Datong (DT) station of the YR over approximately 2.5 years. Low (0.02 kg/m3), high (0.44 kg/m3), and mean (0.10 kg/m3) SSC values were successfully estimated. The SSD was primarily driven by water discharge, exhibiting low values (204 kg/s) during the dry season and a maximum of 36,299 kg/s during flood events, with the mean value of 3,903 kg/s throughout the observation period. The water sample and CAT results demonstrated high consistency, with correlation coefficients (R2) of 0.92 for SSC between the water sample and CAT results, and 0.96 for SSD between the DT result and CAT results. This study established the ability to monitor transect SSC and SSD in the YR using the CAT sound attenuation approach, offering the advantage of continuous real-time monitoring of transect river flow, SSC, and SSD, even during extreme flood events. For the success of this method, factors such as particle size, sound frequency selection, and the measurable distance between instruments must be meticulously considered. This work highlights the potential of CAT for monitoring riverine transect SSC and SSD.