HS1.2.2

The understanding of groundwater interactions with riverine systems is of utmost importance for ecosystem assessment and management. Diffuse groundwater born nutrients, such as N, P and C contribute significantly to an increase of algae growth in rivers and eventually in estuaries, leading to eutrophication with severe consequences for water quality and ecosystem health. Thus, knowledge of both location dynamics and temporal dynamics of diffuse groundwater discharge areas, as well as the discharging groundwater quantity are required.

Here we provide a multi-methodological approach to gain this information for a large river in Germany, i.e. the Elbe River. We applied complementary methods to a 450 km long stretch including: i) analysis of daily time series of hydraulic gradients between river- and groundwater levels, ii) a flux balance for river segments spanning between neighboring gauging stations, iii) inverse geochemical modeling of the river water composition for each segment, and iv) a Darcy approach as an additional tool based on the hydraulic conductivity of the upper aquifer. The results are manifold, including a spatiotemporal answer to the dynamics and orientation of groundwater interaction with the Elbe.

Groundwater inflow is variable but occurs along the entire river. Areas of high groundwater contribution are located in the upstream mountainous parts, where groundwater makes up to 11% of the total river flow. Further downstream, groundwater inflow decreases, while inversion of hydraulic gradients indicate an immense infiltration of river water into the river banks. Unexpectedly high input of groundwater-like fluids could be detected in the lowland, where geochemical modeling indicated a massive inflow of water in a magnitude of 10% of the total river flow. Given a missing surface and groundwater contribution, an unidentified but apparently large system of subsurface drainage ditches co-exists, which transports water to the Elbe River efficiently during and due to drought-related low flow conditions.

Gaining insight into such a large-scale setting with interfering surface water contributions, effluents of wastewater treatment plants, and diffuse groundwater in- and outflows was possible only by applying the combination of independent geochemical, hydraulic and balancing approaches. With a similar availability of river and well levels and the physical access to the latter, the presented multi-method approach may provide a blueprint for the assessment of other large river systems.

How to cite: Zill, J., Siebert, C., Rödiger, T., Weitere, M., and Mallast, U.: Revealing unexpected sources and quantities of groundwater discharge into major river systems during drought conditions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2218, https://doi.org/10.5194/egusphere-egu22-2218, 2022.

The annual monsoon inundations are vital in maintaining the fertility and productivity of the delta of the Mekong, Southeast Asia’s largest river. During the inundations, which traditionally last from July until November, nutrient-rich sediments are deposited on the floodplains, groundwater is recharged, and fish populations regenerate in the shallow waters. Consequently, local agriculture and fisheries are keyed to the timing of flood arrival and recession and reliant on overall flood duration. However, in recent years, the hydrological dynamics of the region have shifted. The Mekong’s hydrological regime has been impacted by shifts in land cover, the construction of hydropower infrastructure, and climate change. 

Yet the effects of these changes on the spatio-temporal patterns of inundations in the Mekong Delta remain largely unstudied, especially at local scales. Part of the reason for this is data sparsity: there is a lack of consistent long-term data on spatial inundation dynamics. No concerted in-situ monitoring efforts of flood extents existed until recently, while optical earth observation satellite missions such as Landsat often fail to provide data during the wet season due to cloud cover. Hydrological modelling approaches struggle with insufficiently precise elevation data - due to the flat topography of the Mekong Delta, even high-resolution Digital Elevation Models (DEMs) fail to capture small-scale dykes that determine whether large swaths of land become flooded. 

To cope with this data-scarce environment, we propose an innovative methodology harnessing recent satellite missions and long-term in-situ river water level measurements. This approach uses remote sensing data from the Sentinel-1 and 2 missions operated by the European Space Agency. Since 2017, these satellites provide optical and synthetic aperture radar (SAR) data at a spatial resolution of 10 m and a return frequency of 5-6 days. Furthermore, SAR provides data independent of cloud cover, which makes it particularly well-suited for operational flood monitoring purposes. After deriving inundation maps from available Sentinel images, we link these maps to water levels measured at a local hydrological station through a correlative approach to create a water-level flood link (WAFL). Using this link, we can describe the evolution of inundation patterns in the Mekong Delta since the 1990s. To quantify uncertainties, comparisons with historical inundation maps derived from available Landsat images,  and with a high- resolution DEM were carried out.  

The approach was tested in two study areas in the Cambodian Mekong Delta.  The results indicate that the accuracy of the WAFL for quantifying inundations on a per-pixel basis lies at 87%, reaching up to 93%. The spatio-temporal analysis shows that inundation incidence in the early wet season has declined by 21% since 1991 and that the average duration of inundations has decreased by 19 days. This illustrates that annual monsoon inundations have become an increasingly volatile resource, with significant impacts on agriculture, fisheries, and ecosystems. 

How to cite: Orieschnig, C., Belaud, G., Venot, J.-P., and Massuel, S.: Assessing long-term changes in annual monsoon inundations in the Mekong Delta (Cambodia): Testing an innovative approach linking remote sensing and in-situ measurements to overcome data scarcity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9619, https://doi.org/10.5194/egusphere-egu22-9619, 2022.

Since 2015, 13 agencies from all around the world (9 different countries in Europe, North and South America and Oceania) have been working together in an International Hydrometry Group, a loosely organized group of experts in instruments and methods for measuring discharge in rivers that meets virtually once a month to discuss scientific and technical issues relating to river flow measurements.

A main objective of the group is to lead the development and funding of an open-source software package, QRevInt, for postprocessing ADCP discharge measurements. The agencies participate in funding the software developer (Dave Mueller, Genesis HydroTech) or contribute scientific inputs. They define the annual development workplan and its funding, and monitor progress during monthly monitoring meetings.

In this presentation, the latest version of QRevInt is detailed and the main advantages of the software are explained, including processing of measurements from ADCP of different manufacturers (TRDI and SonTek) with the same calculation assumptions, objectification of the computation of unmeasured flow area (top, bottom, edges, invalid cells or ensembles), calculation of uncertainty and advanced graph options.

The workplan of the group for 2022 is presented, including the ongoing developments of QRevInt, and the new project for a software dedicated to mid- or mean-section ADCP measurement, QRevIntMS.

How to cite: Lennermark, M. and Hauet, A.: Developing a post-processing software for ADCP discharge measurement piloted by an international and inter-agency group: a unique, ambitious experience… and one that works!, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9379, https://doi.org/10.5194/egusphere-egu22-9379, 2022.

Acoustic Doppler Current Profilers (ADCP) are used a lot all around the world to measure discharge in rivers. These instruments measure most of the vertical velocity profile in rivers, but due to technical and physical limitations they cannot measure all the way to the surface or all the way to the bottom. To calculate discharge, the instruments (or software) need to extrapolate data into the un-measured regions. Previously there was no good and available tools to aid the operators in selecting proper extrapolation. In 2010 USGS released the software Extrap, which plots relative velocity versus relative depth for ADCP measurements, and this tool made it way easier to determine the correct extrapolation of data. (Extrap is now a part of Qrev/QrevInt). Before the introduction of Extrap, 80-90% of the ADCP-measurements at NVE used the default power law extrapolation in the ADCP’s standard software (WinRiver at the time), and around 5% used constant at top and no-slip at the bottom. The first if these assumes a velocity profile that is very similar to the logarithmic velocity profile that comes from classical boundary layer theory. The latter one is much steeper (constant) close to the surface.

After starting to use Extrap regularly, 60% of the measurements use the constant/no-slip extrapolation, while 40 % uses the power law extrapolation. This impacts the reported discharge from the measurements by reducing the reported discharge by on average 4% for the measurements using constant/no-slip extrapolation, and data users must be aware, because these measurements eventually form the foundation for the long time, continuous data series for discharge in our archives.

How will a climate researcher react to a 4% decrease in annual run-off from Norway?

How to cite: Florvaag-Dybvik, K.: Climate change or just new software? The impact of Extrap software on ADCP discharge measurements in Norway, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5037, https://doi.org/10.5194/egusphere-egu22-5037, 2022.

Stream networks are important flow pathways along which water transports solutes, sediments and affects living communities. Field observations in headwater catchments have shown that the networks of actively flowing channels are not static, but rather expand and contract over time, depending on the intensity and timing of hydro-climatic forcing. Until now, however, flowing stream networks (FSNs) have been mapped only sporadically and environmental tracer data to explore the varying stream-landscape connectivity are lacking. Thus, little is known about how and why these networks change and what the implications are for streamflow, water quality and biodiversity. 

To gain detailed insights into the mechanistic links between FSNs and catchment hydrological processes, we investigated two 4-ha head watersheds in the Alptal valley in central Switzerland. We deployed a wireless sensor network in the field to obtain spatially distributed continuous data of flow occurrence. In addition, we conducted multiple mapping surveys using a self-developed mobile phone application. Our data show that the total flowing stream length increased rapidly by more than a factor of 3 during individual rainfall events. This suggests that different water stores become dynamically connected to the stream network and disconnect again during subsequent dry periods. We test this hypothesis by linking short-term changes in FSN length to variations in subsurface water storage and water chemistry. The results help to broaden our understanding of flow intermittency in pre-Alpine headwater catchments, and thus aids in developing effective strategies to protect ecosystems dependent on temporary flow conditions.

How to cite: von Freyberg, J., Bujak, I., Rinaldo, A., and van Meerveld, I.: Monitoring changes in temporary stream networks during rainfall events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4435, https://doi.org/10.5194/egusphere-egu22-4435, 2022.

High mountain environments have shown substantial geomorphological changes forced by rising temperatures in recent decades. As such, paraglacial transition zones in catchments with rapidly retreating glaciers and abundant sediments are key elements in high alpine river systems and promise to be revealing, yet challenging, areas of investigation for the quantification of current and future sediment transport. In this study, we explore the potential of semi-automatic image analysis to detect the extent of the inundation area and corresponding inundation frequency in a proglacial outwash plain (Jamtal valley, Austria) from terrestrial time-lapse imagery. We cumulated all available records of the inundated area from 2018-2020 and analysed the spatial and temporal patterns of flood flows. The approach presented here allows semi-automated monitoring of fundamental hydrological/hydraulic processes in an environment of scarce data. The pixel classification based on greyscale values from oblique hourly recordings returned plausible results of the spatial and temporal variability of surface runoff in the investigated glacier forefield. The image sets, processed in ImageJ, allowed geo-rectification to produce inundation frequency maps. Meteorological and discharge data from downstream measuring stations was consulted to interpret our findings. Runoff events and their intensity were quantified and attributed to either pronounced ablation, heavy precipitation, or a combination of both. We also detected an increasing degree of channel concentration within the observation period. The maximum inundation from one event alone took up 35% of the analysed area. About 10% of the observed area presented inundation in 60-70% of the analysed images. In contrast, 60-70% of the observed area was inundated in fewer than 10% of the analysed period. Despite some limitations in terms of image classification, prevailing weather conditions and illumination, the derived inundation frequency maps provide novel insights into the evolution of the proglacial channel network.

How to cite: Hiller, C., Walter, L., Helfricht, K., Weisleitner, K., and Achleitner, S.: Flood flow in a proglacial outwash plain - quantifying spatial extent and frequency of inundation from time-lapse imagery, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7517, https://doi.org/10.5194/egusphere-egu22-7517, 2022.

A lot of different methods are used to estimate flood risk worldwide. The method that performs better depends on the catchment features and dimension, data time resolution and availability and uncertainty level required. Remote sensing approaches are more and more common, but because of the limited periods covered by time series derived by this new methodology, in-situ data integration is still required. A new methodology is proposed, based on a case-study of different reaches of Basento river, Basilicata (Southern Italy). Starting from hourly rainfall time series (covering not less than 20 years), for each pluviometric station taken into account into the catchment area, Intensity-Duration-Frequency (IDF) curves are computed (fitting a power law), in order to calculate the rainfall maximum at a certain percentile (typically 90° or 95° percentile are used) during the concentration time. Thiessen polygon method is used to divide the catchment area into smaller areas, each one corresponding to a pluviometric station, with the purpose of calculating weighted  rainfall values for each station area. A Digital Terrain Model is used to extract multiple cross sections of the river-bed, spanning different morphologies, from braided to meandering channels. For each cross section, starting from bankful level, it is possible to estimate diverse hydraulic parameters such as river stage, hydraulic radius, section’s surface area (using image analysis) and the mean velocity of the current, using the logarithmic law profile of the turbulent flow. Sediment size analysis is carried out as to estimate the river bed roughness for each cross section. The mean velocity value V can be used to estimate the concentration time t=L/V, where L is equal to the distance between the cross section and the hydraulically further point into the catchment area. The concentration time value t is used into the equation of the IDF curves, in order to link the corresponding rainfall height to the river stage reached at the cross section, eventually to estimate the rainfall value that, if exceeded, can cause flood. A FLO-2D model has been then used to run simulations with the aim to detect flood-prone areas, finding an overall good matching between the values of current mean velocity, discharge and river stage estimated in the cross sections.

How to cite: Roseto, R., Capolongo, D., and Dellino, P.: A new approach for flood risk estimation integrating remote sensing and in-situ data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7229, https://doi.org/10.5194/egusphere-egu22-7229, 2022.

The quantification of river bathymetry and its change through time is a primary challenge in fluvial geomorphology. Whilst there has been a very rapid development of methods for measuring exposed river morphology, inundated zones remain a problem. The development of cheap UAV platforms and SfM-MVS photogrammetry have been particularly important as these allow low cost, high resolution, and repeat surveys. Researches have now shown that provided that there is a signal of water depth then it is also possible to map inundated areas by adopting, for example, two media refraction correction if there is sufficient bed texture in the imagery. The main problem arises, however, when the water is so turbid that the river bed is not visible in imagery. This is the case for braided rivers in proglacial margins where high rates of glacial erosion create high suspended sediment concentrations and also morphodynamically active braided rivers. In this paper we test a new and simple hypothesis to predict water depth distribution based upon heuristic reasoning: that our experience of braided river environments allows us to make a series of qualitative statements about where water will be deeper and where it will be shallower; and that if we can quantify them, we can model the water depths associated with inundated zones.

The simplest statement is that water depth increases with distance away from the nearest river bank; and it is likely to do so more rapidly when the total wetted width is lower. A more rapid increase is also likely on the outer bank of curved sections; and conversely, a slower increase is likely on the inner bank. In a braided river, streamline convergence is likely to lead to deeper water; streamline divergence is likely to lead to shallow water. On this basis, we ought to be able to model water depths in a shallow braided river on the basis of: (1) distance from the nearest bank; (2) local channel width; (3) total inundated width (given a braided river is multi-channel); (4) local curvature magnitude and direction; and (5) planform streamline convergence/divergence. We measure these parameters for a shallow braided proglacial stream (Glacier d’Otemma, south-western Swiss Alps) with high suspended sediment concentrations. Over the summers of 2020 and 2021 we acquired high resolution UAV-based imagery, as well as spatially distributed GPS data of water depths. We used resultant ortho-imagery to extract these parameters and to calibrate predictive models of water-depth based upon multivariate statistical modelling. The independent validation data suggest that between 50% and 75% of the variance in water depths can be reconstructed and confidence in estimated depths are of the order of +/- 0.10m. Finally, we integrate these water depths and their uncertainty into elevation data derived using SfM-MVS photogrammetry for the exposed areas to produce digital elevation models with spatially dependent uncertainty. Comparison of these DEMs shows that they can be used to visualize quantitative geomorphological changes and that the associated uncertainties in volume of change estimates are sufficiently low to be used in sediment budget studies.

How to cite: Mancini, D., Roncoroni, M., Antoniazza, G., Ouvry, B., and Lane, S. N.: Heuristic measurement of river bathymetry in proglacial braided streams using SfM-MVS photogrammetry and statistical approaches, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7071, https://doi.org/10.5194/egusphere-egu22-7071, 2022.

Image-based monitoring of rivers is a growing field of research and is being popularized as a technical alternative for discharge, erosion and flood risk estimation applications. Surface velocimetry can also be a way to characterize the turbulence structure of shallow flows, making possible the remote determination of quantities of interest such as dissipation and integral length scales. To evaluate velocimetry methods and data processing workflows, a laboratory facility emulating a river reach was assembled at IST, and monitored using commercial grade cameras, in field-like conditions. In this work the results of estimates of turbulent dissipation and integral length scales using multiple methods are provided, along with a discussion on the differences among methods and possible applications of the derived data in hydrodynamic model parameter calibration and data assimilation. LSPIV and PTV display similar results with regard to velocity estimation and vortex detection. In the estimation of integral lengths, the longitudinal scales are most affected by limitations in the measurement setup, whereas for the dissipation and turbulent viscosity estimates, spectrum methods seem to be less reliable than simpler methods based on dimensional analysis and integral length scales.

How to cite: Zandonadi Moura, L., Ferreira, R., and Aleixo, R.: Turbulence Metrics from Surface Image Velocimetry, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3049, https://doi.org/10.5194/egusphere-egu22-3049, 2022.

A remote method of measuring surface and near-surface currents in wavy riverine environments
at high spatial and temporal resolution is presented. A two-dimensional power spectral density
technique (2D PSD), which is based on calculating the cross-spectrum between two images is
developed and compared with the established 3D PSD technique. In contrast to the 3D PSD
technique, the 2D PSD algorithm is capable of determining velocity time series and spectra,
thereby facilitating remote measurements of turbulence. Moreover, the 2D PSD algorithm can
accurately determine near-surface flows from fewer images. Results are presented from imagery
collected from an unmanned aerial vehicle and satellite imagery from a number of different
riverine locations.

How to cite: Johnson, E.: Measuring Instantaneous Velocity Fields Remotely using a Two-Dimensional Power Spectral Density Technique, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13487, https://doi.org/10.5194/egusphere-egu22-13487, 2022.

Debris flows and flash floods occur frequently in Chile due to geology, geomorphology and weather, costing human lives and impacting settlements, infrastructure and economic activities. One of the problems relates to the lack of adequate monitoring technology in remote areas with limited connectivity. We have developed a low cost system that processes acquired lidar and image data in-situ with a Raspberry Pi obtaining flow level and velocity and transmits near real time via satellite (or cellular network if available). The low implementation cost allows to replicate the system in the many hazardous sites, as well as advance towards early warning systems in locations with limited communication networks. The velocimetry method consists of two steps: first obtaining the images, and then a brightness filter and normalized cross correlation. To eliminate outliers a flow direction filter is used, and velocities are obtained by tracking of flow surface elements. Also the flow level is measured with a lidar also connected to the R-Pi. We will present both laboratory and field test results.

How to cite: Dussaillant, A., Sepúlveda, N., Aguilar, F., Valencia, J., Ancan, J., Cotroneo, J., Herrera, R., Leiva, N., Peña, C., Alfaro, A., Fernández, J., and Muñoz, A.: In-Situ, Near Real Time and Low Cost Image Velocimetry for Debris Flows and Flash Flood Monitoring in the Chilean Andes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10797, https://doi.org/10.5194/egusphere-egu22-10797, 2022.

The operator effect is a prominent error source in image-based velocimetry methods. Video sampling, ortho-rectification parameters, motion analysis parameters and filters can strongly impact velocity and discharge measurements. This has been reported in the literature (e.g. Detert, 2021) and highlighted by the Video Globe Challenge 2020, a video gauging intercomparison (Le Coz et al., 2021). The parameter choices made by the operator must be assisted to contain errors and to make image analysis methods accessible to non-specialists.

An investigation of the operator effect (or parameter effect) in various situations is proposed. The analysis focuses on the LSPIV measurements carried out during the Video Globe Challenge 2020. This contest involved around 15 participants with varying levels of experience, challenged over 8 videos. All the LSPIV measurements were replayed based on the data submitted by the participants. The objective was to identify the most sensitive parameter(s) for each video, based on an extensive analysis of the replayed velocity and discharge results.

The data retrieved were: video sampling rate, number of frames, ortho-rectification resolution, IA and SA sizes, correlation based and vector based filters, surface velocity coefficient (a.k.a. alpha) and transect interpolation parameters. To ensure valuable comparisons, grid points and video sequencing were fixed the same for all the participants. Replaying LSPIV measurements allowed to play with the parameters methodically and to quantify their impact on the measured discharge deviation from the reference.

Several lessons were learned from these analyses thanks to the variety of conditions offered by the 8 videos. A tendency to under-estimate the discharge in case of inappropriate parameters was observed. The influence of the video sampling rate has been noticed in many cases. It turns out to have more impact than the motion analysis parameters. The dataset was used to evaluate the benefit of automated parameters setting tools, e.g. ensemble correlation, automated time-interval, automated video sequencing.

Detert, M. (2021). How to avoid and correct biased riverine surface image velocimetry. Water Resources Research, 57, e2020WR027833. https://doi.org/10.1029/2020WR027833

Le Coz, J., Hauet, A., and Despax, A. (2021). The Video Globe Challenge 2020, a video streamgauging race during the Covid-19 lockdown, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2116, https://doi.org/10.5194/egusphere-egu21-2116, 2021

How to cite: Bodart, G., Le Coz, J., Jodeau, M., and Hauet, A.: Quantifying the operator effect in LSPIV image-based velocity and discharge measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4457, https://doi.org/10.5194/egusphere-egu22-4457, 2022.