Book of Extended Abstracts. Webinar on Methods for Ecohydraulics: Remote Sensing, 17-20 May 2022

Abstract:

The present work aims to summarize the outcomes of the webinar on Remote Sensing in Ecohydraulics, co-organized by the Institute of Geophysics of the Polish Academy of Sciences, the IAHR Committee on Ecohydraulics, the IAHR Poland Young Professional Network and ECoENet.
    During the webinar, four keynote lectures and twelve technical notes, mainly coming from young researchers, provided the framework of the state-of-the-art of new tools, methods, equip-ment and methodologies for monitoring water habitats, and they aimed to share knowledge and address data survey needs.
    In terms of the geographical distribution of the abstracts, more than 10 countries were rep-resented, showing the worldwide importance of the topic, and the willingness for developing international and transdisciplinary connections.

Abstract:

The growing availability of remote sensed data provides new opportunities for analysis of conditions in lakes and rivers. Scanned terrain and bathymetry from LiDAR, various kind of satellite and aerial imagery and climatic data from satellite and combined products provide both a spatial and temporal resolution that is unavailable in traditional measurement approaches. Examples of use is drones and structure from motion to map ice formation and remnants in rivers. Effects of river ice is important for instream habitat in cold climate rivers and notoriously difficult to measure. Topographic and bathymetric LiDAR is used to build terrain models as a foundation for hydraulic modelling, providing highly detailed and accurate models. Finally, machine learning is used to classify historical aerial imagery providing a basis for the evaluation of the development of rivers.

Abstract:

The camera has a storied history, with the oldest recorded camera, the camera obscura, linked to Han Chinese philosopher Mozi c. 470–390 BC. Today, cameras (or sensors) are omnipresent, floating around the Earth acquiring data, gazing into space as we seek to explain our universe, and rest in your hand as you photograph a stream. In Earth science sensors are providing deep insights into hydrologic, geologic, ecologic, and hydraulic processes. In this talk I will provide an overview of the physics that underlies sensors, followed by a suite of remote sensing case studies relevant to ecohydraulic researchers, practitioners, and resource managers. These studies illustrate the utility of remote sensing for ecohydraulic studies at the catchment to patch scale, and from a snap shot in time to 10-minute resolution data collected throughout a summer.

Abstract:

Climate change is increasing river temperature globally, with potentially serious consequences for iconic cold water fish species. As a result, the past 20 years have seen a consid-erable growth in the use of thermal and optical remote sensing (thermal infrared and otherwise) to characterise stream temperature patterns across multiple spatio-temporal scales. In this keynote, I review how remote sensing has generated new insights into our understanding of the processes driving stream temperature and explain how knowledge stemming from this research is advancing the management of rivers and streams threatened by climate change. I then examine recent advances and knowledge gaps in the field. Finally, I outline how and where progress is still needed in order to improve management of the thermal regimes of rivers, with a view to ensuring the continued survival of threatened river ecosystems.

Abstract:

Telemetry is an ever-evolving field with a suite of technologies for wildlife and fisheries researchers. Over the past 100 years many advancements in telemetry equipment have transpired. These developments allow for numerous options when deciding on equipment and methods for telemetry related studies. As such, this talk will cover the four major divisions of telemetry including radio, acoustic, GPS, and radio frequency identification (RFID). An overview of telemetry technologies and their applications will be covered, to further education and bolster the tools that researchers and managers have at their disposal. It is the purpose of this presentation to provide guidelines and suggestions to researchers to identify when the appropriate technology should be utilized, and what combinations of these technologies are best suited for answering research questions.

Abstract:

Climate change is increasing the severity of numerous natural hazard processes: rising global air temperatures have, over the past decades, led to an acceleration of glacial retreat in many places around the world, causing increases in volume at many existing glacial lakes and the development of new ones. The increased risk of glacial lake outburst floods (GLOFs) endangers human infrastructure downstream. Hydraulic modeling is a vital tool in the process of GLOF risk assessment. The affected areas are usually difficult to access, hence the model inputs are often derived from remote sensing. The present study simulates a major scale GLOF event at the River Biya in the Siberian Altai Mountains. The propagation of possible hydrographs was modeled alongside mobilized grain sizes. Results like these can be used to antic-ipate the extent of a flood event of a certain magnitude and to evaluate whether any infrastructure is endangered.

Abstract:

Integration of remote sensing and 2D hydraulic modelling offers the potential for broader applicability of habitat modelling at the meso-scale, extending applications to larger non-wadeable streams, and allowing to survey longer river stretches. We present an example of the application of a methodological framework for meso-scale habitat suitability modelling, on a reach of the gravel-bed Aurino River (NE Italy). The framework implements the following main steps: remote sensing-based acquisition of the topo-bathymetry and a high-resolution orthophoto; 2D hydraulic modelling coupled with an unsupervised algorithm to map hydro-morphologically defined units; semi-automated mapping of substrate and refugia; and finally, the estimation of meso-scale habitat suitabilities for a target species or community.

Abstract:

The knowledge of the hydro-morphological evolution of lowland rivers is essential to develop integrated river management plans. Multispectral and Synthetic Aperture Radar (SAR) Satellite data can be helpful in continuous and efficient monitoring of wet channel evolutions. On the one part, multispectral images are easily interpreted but affected by the presence of cloud cover. Instead, although the SAR images have more complex interpretation, they can provide information in all weather conditions. In this work, a supervised deep learning segmentation method was proposed to analyse the hydro-morphological changes along a reach of the Italian Po River using Sentinel-1 SAR data.

Abstract:

Water temperature maps based on Unmanned Aerial Vehicles (UAVs)-thermal camera data have a significant role to study freshwater systems and inform for the potential thermal effects of any alteration. Nevertheless, the estimation of water absolute temperature (Tk) can still represent a problem when the accuracy needed must be < 1 °C. The vignetting effect and the thermal shift are two sources of bias in the estimation of water temperature. We present here a procedure that implement already developed methodologies with new techniques to produce thermal map with errors below 1 °C.

Abstract:

Geoprocessing techniques in GIS allow extraction of the river basin and its drainage networks, thus facilitating the computation of morphometric parameters of the basin. Multi Error Removed Improved Terrain (MERIT) DEM based delineation of the watershed of the Dibang River Basin and its sub-basins in the north-eastern Indian state of Arunachal Pradesh along with its drainage networks was attempted in this study using geospatial tools. Also, various morphometric parameters that describe the basin characteristics and morphotectonic parameters were derived. According to the Strahler’s scheme, the Dibang River is a seventh order stream with a catchment area of 11823.9 km². Dri, Mathun, Emra, Ithun, Ahul, and Tangon are the major tributaries of the Dibang River. Various morphometric parameters show the dominant tectonic influence in the drainage development in the area. The morphometric pa-rameters indicative of tectonic influences correlates well with the regional tectonics when compared with the lineament map and lithotectonic map.

Abstract:

Sustainable management of riparian zones requires detailed spatial information about vegetation and hydromorphological properties. Uncrewed aerial systems (UAS) or gyrocopters equipped with multispectral cameras yield imagery of small to intermediate scale areas. Machine learning classification workflows (object based, random forest) including additional geodata and trained with in-situ data allow to map classes of vegetation and hydromorphological substrate types with different level of detail. A case study was carried out in a floodplain area along the River Rhine, Germany, resulting in overall accuracies for UAS data of 89% for basic surface types, 88% for vegetation units, 75% for dominant stand, and 62% for substrate types. Classification probability maps helped to identify areas of lower classification performance, as e.g. vegetation within the transition zone, thus allowing for a subsequent, more focused and effective site inspection. In combination, this workflow provides a valuable tool for monitoring and ecologically integrated water management.

Abstract:

Environmental water is delivered to floodplains to maintain environmental health in terms of vegetation health and animal populations in arid and semi-arid areas. When and how much environmental water is required to restore or maintain vegetation health requires robust predictions of vegetation response. We used Normalized Differences Vegetation Index (NDVI) derived from 30-year Landsat dataset to represent vegetation condition. A lake water balance model and long short-term memory networks (LSTMs) were coupled to model NDVI. The predictor variables included in the LSTMs are the outputs of the water balance model, climate factors, day of year and previous NDVI values. The model is expected to generate more precise predictions of ecological outcomes under different watering scenarios, and thus has the potential to help environmental water management in the changing climate.

Abstract:

We developed a method to provide a relatively simple, quick and inexpensive assessment of restoration success in relation to fish fauna. Using a UAV, high-resolution orthomosaics of three restored and three channelized river sections were created under low, medium, and high flow situations. These served as the basis for remote mapping of fish habitats, focusing on riffle and shallow water areas as potential spawning and juvenile and hence key habitats for rheophilic fish species. It was found that by interpreting high-resolution orthomosaics, it was possible to map these habitats, whose actual suitability was validated with field observations. Together with an analysis of discharge time series (17 years), the mapped habitat situations were related to the probability of their occurrence. By combining morphological and hydrological analyses of the restoration projects, it was possible to assess whether the newly created habitats were usable all year round or only at certain flow situations.

Abstract:

Various forms of obstacle structures in water are common in the natural environment. The flow through these obstructions causes mutual interference, and changes in hydraulic conditions result in changes in fish swimming behaviour around the column. In this study, the behaviour of carp is evaluated when interacting with wake currents caused by three types of columns: shuttled, D-shaped, and rectangular. The hydraulic properties of the natural fish passage are simulated and analysed in coupling with the swimming behaviour of the fish. Based on two-dimensional threshold segmentation (OTSU) and video recognition, the probability of fish occurrence in different locations and the tail swing frequency can be identified. The probability of fish occurrence can be predicted by BP model when the parameters of hydrodynamic characteristics under unknown flow are known. The results show it is reliable in all three types of channels and provides a reference for finding swimming paths of fish.

Abstract:

The fish passage is an effective way for fish to pass through dams and obstacles, but most fish passes are currently not used, and the energy used by fish to pass through them is too great to meet the conditions for passage. This paper focuses on the factors that affect the fish swimming energy expenditure. The factors include the hydraulic conditions of the fish passage, the fish swimming speed, and the fish tail swing frequency. A baffle is set up in a U-shaped channel with different barriers on either side of the baffle, making the hydrodynamic conditions different on each side of the channel. HD cameras were set up to observe and record the fish swimming behaviors in the channel, and deep learning YOLOV5 algorithm was used to identify the fish swimming speed and the frequency of the tail swing. The data was analyzed to derive an equation for calculating the fish swimming energy consumption. FLUENT was used to simulate the fish energy consumption in the channel during high flows and to obtain the route with the lowest energy consumption of the fish, which will provide suggestions for the subsequent construction of fish passage and fish crossing facilities.

Abstract:

Fluvial remote sensing of river bathymetry is crucial for characterizing the topography of the riverbed and monitor changes in habitat at large scales. Hyperspectral data enables bathymetric retrieval through optical models. On the Ain River (France), multiple hyperspectral aerial campaigns with different sensors were conducted and processed to create bathymetric maps of the river for different flow conditions. In particular, a continuous bathymetric map was produced for a 20 km reach of the river with a median error of 20 cm for depths up to 2.5 m. Despite the uncertainties of the models tested, the result are more robust spatially and over a wider range of depth and flow conditions than optical models based on traditional colour imagery.