1,720,978 research outputs found
Hydrodynamic rainfall-runoff modelling for flash floods in small and steep catchments
No full textGlobal warming and climate change lead to more frequent and extreme weather events. These include sudden and intense rainfall and rising temperatures which cause flash floods. In steep terrains, flash floods with high-flow velocities lead to erosion and sedimentation with potential disastrous changes of flood path. Flash floods caused by heavy rainfall with snowmelt contribution due to sudden rise in temperature (rain-on-snow events) have become common in autumn and winter in snow-covered Nordic catchments. These events have caused widespread damage, closure of roads and bridges and landslides leading to evacuations in affected areas. Therefore, the analysis of such flood types becomes more important in terms of inundation area, water depths and flow-velocities to identify critical locations in a catchment.
Hydrological and hydraulic models are usually used to simulate flash floods. But most of the traditional hydrological models only give output as a hydrograph but do not represent the consequences such as velocity, water depth, sheer stress etc. at any point or region in the catchment. So, the flood hydrograph from a traditional hydrologic model must be combined with a hydraulic model for downstream consequences. In the traditional method of manual coupling, the output from the hydrologic model is used as input and set as input boundary condition in the hydraulic models. This method of manual coupling requires the separate calibration of two models which makes it a time-consuming process. Sometimes due to many tributaries, more than one boundary condition is required and it is difficult to decide where to set the input boundary conditions in the hydraulic model. In addition to this, there is always some residual flow along the river from the catchment or the water from small tributaries, which is difficult to estimate and add in the hydraulicmodel calculations. In small and steep catchments, the inflow contribution from every section of the water course can be important to determine where critical conditions may arise.
To overcome these challenges and the hassle of manual coupling of the two models, the direct rainfall method (DRM) also known as rain-on-grid (RoG) technique was tested in this research work. Primarily, TELEMAC-2D, a Hydrodynamic Rainfall-Runoff (HDRR) model, with Curve Number (CN) infiltration method, was used for this purpose in a study site of 10.5 km2 steep catchment located in western Norway. Spatially distributed precipitation data with a resolution of 1km by 1km was used as input instead of point precipitation data to reduce the uncertainties related to precipitation distribution over the catchment.
Since TELEMAC-2D is an open source toolbox, it was possible to make changes in the source code ourselves and implement spatially distributed precipitation as input. Since TELEMAC-2D doesn’t have a snow routine, initially only those peak flow events were simulated which were induced by rainfall without any contribution from snowmelt. Seven such events were simulated and a sensitivity analysis was conducted for the parameters such as the CN values, size of mesh elements, roughness and antecedent moisture conditions (AMC) in the catchment. In addition, a 200-year design flood was simulated to show the potential damages in the catchment. The study explored the benefits and limitations of the approach through a comprehensive description of model construction, calibration, and sensitivity analysis. The results showed that calibrated models can satisfactorily reproduce peak flows and produce relevant information about water velocities and inundation. Since, floods can reach even more extreme levels when snowmelt combines with the surface runoff generated by rainfall events. When rain falls on an existing snowpack in addition to the sudden increase in temperature, it is known as a rainon-snow (RoS) event. These events can result into destructive flash floods due to the sudden melting of snow combined with the extreme rainfall.
Hence, in the next part of the thesis work, the contribution and effect of snowmelt in flash floods were analysed. The hydrological model HBV was used to find out the portions of snow and rain from the raw precipitation data and to calculate the snowmelt. The sum of snowmelt and rain calculated from HBV, which eventually contributes to flash floods, was used as the input precipitation in TELEMAC-2D for HDRR modelling. The results showed the importance of including snowmelt for distributed runoff generation and how the combination of hydrological and hydraulic models allows to extract flow hydrographs anywhere in the catchment. It is also possible to extract the flow velocities and water depth at each time-step showing the critical points in the catchment in terms of flooding. The RoG technique works particularly good for single peak events, but not for floods with longduration sustained flow and which are generated by multiple rainfall storms. The results indicated a need for implementation of time-varying CN values or another infiltration model with a time-varying infiltration rate for such multi-storm floods.
Therefore, another HDRR model HEC-RAS 2D with the Green-Ampt Redistribution (GAR) infiltration method was tested and compared with TELEMAC-2D for its RoG technique. CN method was applied in both the models to simulate two single storm events up to 20 hours duration. NSE and R2 for the models ranged from 0.70 to 0.90 and from 0.93 to 0.95. Moreover, the two models were compared for the calibration process, computational time, mesh size and shape, model availability in general, as well as for the results including inundated areas, water depths and velocity of water after a flood event. In addition, The GAR method was applied in HEC-RAS 2D for a multi-peak flood event with sustained flow between the peaks, but the results showed that even this method was unable to reproduce all the peaks of the flood event. Therefore a sensitivity analysis of the GAR parameters was done to understand why GAR method could not reproduce the multi-storm flood. The sensitivity analysis showed that the results are not very sensitive to the two GAR parameters which are responsible to influence the flow of the later peaks.
Neither of the HDRR models could reproduce such multi-storm long duration floods because of the fact that both the HDRR models permanently lose the infiltrated water out of the model domain which usually contribute as the return flow to the river which is mainly the reason for the sustained flow between the multiple storms and for a gradual recession limb of a flow hydrograph. However, neither of the models incorporate a return flow algorithm. Hence, the HDRR models should only be used if it is sure that the infiltrated water goes to the deep base flow where there is no chance of subsurface return flow, or they should be used only for shortduration single storm floods.
Potential follow up to this research work can be to implement a subsurface flow module or the contribution of return flow in the fully integrated hydrologic- hydrodynamic RoG models. This enhancement would enable these models to effectively handle both short and long duration floods. Moreover, a snow routine can also be implemented in the HDRR models which eliminates the need of a separate model to calculate snow storage and snowmelt in the catchment
Ice and Ice Forces in Small Steep Rivers
No full textEnglish summary
Given the right circumstances ice can wreak havoc on riverine infrastructure. Ice runs pushing ice floes against bridge piers is frequently the governing design condition for bridges in cold regions. The physics of these interactions are complex and forces are hard to predict. Current standards and calculation methods for calculating these quasi-static ice forces disagree both on order of magnitude and underlying mechanics. While there reigns general agreement that ice thickness and ice strength are critical parameters, great difficulties remain for the accurate and reliable estimation of these parameters (Paper I). In small-steep rivers in particular these estimates are difficult. Anchor ice dams complicate things by encouraging the growth of highly complex and variable ice structures. Paper III provides a novel approach for quickly and accurately estimating ice thicknesses in generally inaccessible steep rivers using an unmanned aerial vehicle (UAV), structure for motion and automated GIS processing. Paper II provides new insights into how ice strength varies in steep rivers. Through statistical analysis it shows a novel and effective way of predicting anchor ice dam locations, proportion of river impacted by anchor ice dams as well as providing new data on how anchor ice dam strengths are distributed. As a whole, this thesis provides the river ice engineer with new and balanced guidance on how to go about predicting ice forces in small steep river.Norsk sammendrag
Is kan under visse omstendigheter påføre store skader på infrastruktur i elver. Istrykk på bropilarer er ofte dimensjonerende for bruer i kalde strøk. Fysikken bak disse interaksjonene er komplekse og kreftene vanskelige å forutsi. Nåværende design-koder og kalkulasjons metoder for disse kvasi-statiske iskreftene er uengie om både størrelses orden og underliggende mekanikk. Det regjerer en generel konsensus at is-tykkelse og is-styrke er kritiske parametre, men store vanskeligheter gjenstår før nøyaktige og påligelige estimater av disse er mulig (Paper I). Spesielt i små bratte elver så er disse estimatene vanskelige. Bunn-is dammer kompliserer ting ved å oppmuntre vekst av høyst komplekse og variable is strukturer. Paper III beskriver en ny tilnærming for raskt og effektiv estimering av is-tykkelse i generelt utilgjengelige bratte elver ved bruk av fjernstyrt drone, structure from motion (SfM) og automatisert GIS prosessering. Paper II gir ny innsikt i hvordan is-styrke varierer i bratte elver. Gjennomstatistisk analyse så viser den en ny og effektiv måte å forutsi bunn-is dam lokasjoner, brøk av elven påvirket av bunn-is dam formasjon, i tillegg til å gi nye data om hvordan bunn-is dam styrke er distribuert i disse elvene. Somen helhet så tilbyr denne avhandlingen elve-is ingeniøren med en ny og balansert veiledning på hvordan man best kan forutsi is-krefter i små bratte elver
Remotely sensed data for bathymetric mapping and ecohydraulics modelling in rivers
No full textRiver management decisions must be based on the best knowledge available. But acquiring information on river conditions and translating it into sufficient mitigation measures can be both time- and resource demanding. Remote sensing data can be an important source of information on the current state of rivers, and may also be used in scenario assessments of future river conditions. This PhD-study has focused on the use of remote sensing data as a source of information on bathymetry, seasonal mesohabitats for fish, scenarios of mitigation measures, and strategies on environmental eDNA sampling. Each of these four information elements are often central parts in river assessments. The results from the PhD-study are presented in four scientific papers and include remote sensing data from green and red LIDAR, multispectral satellite imagery and aerial photos collected and applied in four Norwegian rivers.
For the assessment of seasonal mesohabitats for fish, two remote sensing technologies were used: LIDAR and aerial photos. The LIDAR data enabled a 10x10 cm resolution bathymetry used as input to a 2D hydraulic model for the simulation of hydraulic heterogeneity. The aerial photos were used as both a source of calibration data and for assessing spatial heterogeneity along the river banks. The results show that both spatial heterogeneity and hydraulic heterogeneity are significant mesoscale habitat characteristics for European Grayling during its spawning period. No significant relationships were found on spatial and hydraulic heterogeneity for brown trout, emphasising the need for species-specific assessments in terms of mesoscale habitat characteristics.
While LIDAR data may be a source of high-resolution bathymetry, collecting and processing LIDAR data can be costly and time consuming. An alternative remote sensing data source for river assessments is multispectral imagery or (the previously mentioned) aerial photos. The application of multispectral imagery from two satellite platforms and aerial photos for mapping of bathymetry by linear models was tested in four rivers within the same geographical region. LIDAR and SONAR data was used in the study for establishing linear image-to-depth models and for verifying the modelled bathymetry. Platform-specific regional models were then established and tested by combining intercept and slope coefficients from the linear models in the four rivers.
The results showed that while the final quality of platform-specific regional model bathymetry did not fully match the quality of LIDAR-based bathymetry, overall model performance was adequate for depth calculations. For Worldview-2 images and aerial photos, coefficients of determination (R2) were in the 0.52-0.82 and 0.73-0.91 range, respectively. By adjusting the regional models with estimated local depth and a brightness factor, results on depth calculations improved slightly when compared to the LIDAR-based bathymetry, with coefficients of determination in the 0.47-0.84 and 0.71- 0.91 range, respectively.
Point cloud format LIDAR data can easily be modified e.g., for use in assessment of different mitigation measure scenarios. Modified LIDAR data was tested in a public preference study on scenarios for mitigation measures related to weir adjustments and changes in flow-dependent water covered areas in weir basins. The study was conducted in a bypass section (i.e., a river section with water withdrawal) with a 65-70% reduction in yearly discharge due to hydropower production. Findings from the study show that LIDAR data are highly useful for scenario-based adjustments and modelling of weirs. As the potential dry/wet interface at or around the weirs can be hydraulically complex, these locations may require high-density mapping using a combination of red and green LIDAR. Results from the study also include a structured and standardized framework for public preference assessments in rivers which includes the potential use of remote sensing data as input to mitigation measure scenarios.
A successful green LIDAR scan depends on a range of factors e.g., the technology applied in the scan process, signal pathway length and disturbances, river conditions and post-processing capabilities. Failure to address each of these factors when applying LIDAR may result in inadequate point cloud classification or coverage. In a study of strategic environmental eDNA sampling for biomonitoring in a river dominated by weirs and flow alteration, a regional adjusted image-to-depth model was applied on remote sensing imagery for river sections where two consecutive LIDAR scans returned inadequate coverage of bathymetry. Results on simulated depths and velocities adequately matched corresponding in-situ measurements of the same variables. Results from generalized mixed models testing the effect of spatial and abiotic variables on sample eDNA concentrations showed that sample location habitat type and season significantly affected eDNA concentrations of brown trout and minnow. Furthermore, weirs were found to be barriers for the dispersion of eDNA during autumn, while no significant effects of weirs were found during spring
Remotely sensed data for bathymetric mapping and ecohydraulics modelling in rivers
Full text linkRiver management decisions must be based on the best knowledge available. But acquiring information on river conditions and translating it into sufficient mitigation measures can be both time- and resource demanding. Remote sensing data can be an important source of information on the current state of rivers, and may also be used in scenario assessments of future river conditions. This PhD-study has focused on the use of remote sensing data as a source of information on bathymetry, seasonal mesohabitats for fish, scenarios of mitigation measures, and strategies on environmental eDNA sampling. Each of these four information elements are often central parts in river assessments. The results from the PhD-study are presented in four scientific papers and include remote sensing data from green and red LIDAR, multispectral satellite imagery and aerial photos collected and applied in four Norwegian rivers.
For the assessment of seasonal mesohabitats for fish, two remote sensing technologies were used: LIDAR and aerial photos. The LIDAR data enabled a 10x10 cm resolution bathymetry used as input to a 2D hydraulic model for the simulation of hydraulic heterogeneity. The aerial photos were used as both a source of calibration data and for assessing spatial heterogeneity along the river banks. The results show that both spatial heterogeneity and hydraulic heterogeneity are significant mesoscale habitat characteristics for European Grayling during its spawning period. No significant relationships were found on spatial and hydraulic heterogeneity for brown trout, emphasising the need for species-specific assessments in terms of mesoscale habitat characteristics.
While LIDAR data may be a source of high-resolution bathymetry, collecting and processing LIDAR data can be costly and time consuming. An alternative remote sensing data source for river assessments is multispectral imagery or (the previously mentioned) aerial photos. The application of multispectral imagery from two satellite platforms and aerial photos for mapping of bathymetry by linear models was tested in four rivers within the same geographical region. LIDAR and SONAR data was used in the study for establishing linear image-to-depth models and for verifying the modelled bathymetry. Platform-specific regional models were then established and tested by combining intercept and slope coefficients from the linear models in the four rivers.
The results showed that while the final quality of platform-specific regional model bathymetry did not fully match the quality of LIDAR-based bathymetry, overall model performance was adequate for depth calculations. For Worldview-2 images and aerial photos, coefficients of determination (R2) were in the 0.52-0.82 and 0.73-0.91 range, respectively. By adjusting the regional models with estimated local depth and a brightness factor, results on depth calculations improved slightly when compared to the LIDAR-based bathymetry, with coefficients of determination in the 0.47-0.84 and 0.71- 0.91 range, respectively.
Point cloud format LIDAR data can easily be modified e.g., for use in assessment of different mitigation measure scenarios. Modified LIDAR data was tested in a public preference study on scenarios for mitigation measures related to weir adjustments and changes in flow-dependent water covered areas in weir basins. The study was conducted in a bypass section (i.e., a river section with water withdrawal) with a 65-70% reduction in yearly discharge due to hydropower production. Findings from the study show that LIDAR data are highly useful for scenario-based adjustments and modelling of weirs. As the potential dry/wet interface at or around the weirs can be hydraulically complex, these locations may require high-density mapping using a combination of red and green LIDAR. Results from the study also include a structured and standardized framework for public preference assessments in rivers which includes the potential use of remote sensing data as input to mitigation measure scenarios.
A successful green LIDAR scan depends on a range of factors e.g., the technology applied in the scan process, signal pathway length and disturbances, river conditions and post-processing capabilities. Failure to address each of these factors when applying LIDAR may result in inadequate point cloud classification or coverage. In a study of strategic environmental eDNA sampling for biomonitoring in a river dominated by weirs and flow alteration, a regional adjusted image-to-depth model was applied on remote sensing imagery for river sections where two consecutive LIDAR scans returned inadequate coverage of bathymetry. Results on simulated depths and velocities adequately matched corresponding in-situ measurements of the same variables. Results from generalized mixed models testing the effect of spatial and abiotic variables on sample eDNA concentrations showed that sample location habitat type and season significantly affected eDNA concentrations of brown trout and minnow. Furthermore, weirs were found to be barriers for the dispersion of eDNA during autumn, while no significant effects of weirs were found during spring
Climate-Informed Planning and Design of Urban Water Systems
Full text linkGlobal warming is expected to cause alterations of the climate with potential impacts on urban water systems. As the knowledge base on climate change expands, and regional climate projections become increasingly available to local water managers, the need for climate-informed tools and decision-support systems rises.
This thesis seeks to address local stakeholders needs for novel tools and frameworks for facilitating climate adaptation and to investigate how climate projections can inform the analyses. The work of this thesis has been conducted as part of the H2020 project BINGO
- Bringing INnovation to onGOing water management - a better future under climate change (Grant Agreement number 641739), where the principal goal has been to provide end-users in the water sector with practical tools and knowledge on climate change.
The thesis specifically attends to three main applications of urban water systems: 1) drinking water availability planning, 2) storm water infrastructure design, and 3) urban drainage systems planning. To support the overall aims of the thesis, the following objectives were defined:
1. Investigate local climate projections and their potential to provide decision-support in local climate adaptation
2. Evaluate climate projections’ applicability for design in current stormwater management practice in Norway
3. Develop climate-informed adaptation frameworks for Norwegian urban water systems
To pursue these objectives, a collection of regional climate projections for the city of Bergen, Norway, was produced, processed and assessed through various tools and techniques. This resulted in a rich ensemble of climate projections for the city, covering a range of emissions scenarios, parent global climate models, and downscaling methods. These projections have further been used as input to hydrologic and hydraulic models embraced by the three defined water sector applications. Through this, the application of climate projections in planning and design of urban water systems was demonstrated and assessed, and frameworks providing decision-support were proposed.
The assessment of the resulting climate projection ensemble emphasizes the general consensus in research that ensemble approaches are necessary to gain a holistic and reliable indication of future local climates, as choices of emissions scenario, parent GCM, predictor, and downscaling techniques all introduce their own range of uncertainty. This implies that climate projections should not be further applied in a traditional predict-then-act manner, but rather treated as what they are: possible scenarios of future climate, sooner than predictions, and ensembles rather than singular best-guess estimates.
To emerge at climate-informed design practices in Norway, the results of this thesis strongly suggest that existing tools and methods should be adjusted to handle a range of input scenarios rather than single event or time series inputs. This would allow a shift from prediction-based design, to a risk-oriented design of urban water systems and system components.
Finally, three main decision-support frameworks are proposed for climate adaptation in the water sector. The three frameworks incorporate a new dimension of climate change information into traditional tools known to the water sector. In addition to addressing the third, and last objective of this thesis, they also contribute to the principle goal of the BINGO project: to provide end-users in the water sector with practical tools and knowledge on climate change. Although the results are site specific, linking frameworks to existing tools ensures scalability and transferability of methodologies
Climate-Informed Planning and Design of Urban Water Systems
No full textGlobal warming is expected to cause alterations of the climate with potential impacts on urban water systems. As the knowledge base on climate change expands, and regional climate projections become increasingly available to local water managers, the need for climate-informed tools and decision-support systems rises.
This thesis seeks to address local stakeholders needs for novel tools and frameworks for facilitating climate adaptation and to investigate how climate projections can inform the analyses. The work of this thesis has been conducted as part of the H2020 project BINGO
- Bringing INnovation to onGOing water management - a better future under climate change (Grant Agreement number 641739), where the principal goal has been to provide end-users in the water sector with practical tools and knowledge on climate change.
The thesis specifically attends to three main applications of urban water systems: 1) drinking water availability planning, 2) storm water infrastructure design, and 3) urban drainage systems planning. To support the overall aims of the thesis, the following objectives were defined:
1. Investigate local climate projections and their potential to provide decision-support in local climate adaptation
2. Evaluate climate projections’ applicability for design in current stormwater management practice in Norway
3. Develop climate-informed adaptation frameworks for Norwegian urban water systems
To pursue these objectives, a collection of regional climate projections for the city of Bergen, Norway, was produced, processed and assessed through various tools and techniques. This resulted in a rich ensemble of climate projections for the city, covering a range of emissions scenarios, parent global climate models, and downscaling methods. These projections have further been used as input to hydrologic and hydraulic models embraced by the three defined water sector applications. Through this, the application of climate projections in planning and design of urban water systems was demonstrated and assessed, and frameworks providing decision-support were proposed.
The assessment of the resulting climate projection ensemble emphasizes the general consensus in research that ensemble approaches are necessary to gain a holistic and reliable indication of future local climates, as choices of emissions scenario, parent GCM, predictor, and downscaling techniques all introduce their own range of uncertainty. This implies that climate projections should not be further applied in a traditional predict-then-act manner, but rather treated as what they are: possible scenarios of future climate, sooner than predictions, and ensembles rather than singular best-guess estimates.
To emerge at climate-informed design practices in Norway, the results of this thesis strongly suggest that existing tools and methods should be adjusted to handle a range of input scenarios rather than single event or time series inputs. This would allow a shift from prediction-based design, to a risk-oriented design of urban water systems and system components.
Finally, three main decision-support frameworks are proposed for climate adaptation in the water sector. The three frameworks incorporate a new dimension of climate change information into traditional tools known to the water sector. In addition to addressing the third, and last objective of this thesis, they also contribute to the principle goal of the BINGO project: to provide end-users in the water sector with practical tools and knowledge on climate change. Although the results are site specific, linking frameworks to existing tools ensures scalability and transferability of methodologies
Optimization of hydraulic models for the visualization of flash floods in steep rivers
No full textThe research explores the use of advanced visualization techniques and hydraulic models to enhance communication and management of flash flood hazards.
Specifically, on how digital twins and Virtual Reality (VR) can transform traditional flood communication methods by making hydrodynamic simulations more interactive, immersive, and accessible to a wider audience.
A VR-based framework that visualizes flood models efficiently was developed, tested through case studies, and its impact on user engagement and hazard awareness was investigated.
This research aims to offer innovative tools for improving flood management and communication, helping river managers, vulnerable communities, and other stakeholders make informed decisions during extreme event
Exploring hydrological response to land use/land cover change using the swat plus model in the İznik lake watershed, Türkiye
No full textLand use/land cover (LULC) changes significantly affect hydrological processes in watersheds. In this study, the Soil and Water Assessment Tool (SWAT+) model was employed to investigate the hydrological response to LULC changes in the & Idot;znik Lake Watershed, a region of significant environmental and social importance in the Marmara Region of T & uuml;rkiye. This study provides a novel understanding of water balance dynamics of the & Idot;znik Lake Watershed through hydrological modeling. The SWAT+ model was calibrated and validated against observed monthly flow data from two gauging stations using three objective functions: Nash-Sutcliffe efficiency (NSE), Kling-Gupta efficiency (KGE), and the percent bias (PBIAS). The model was utilized to evaluate the impacts of LULC change on water balance components such as surface runoff, percolation, lateral flow, water yield, and evapotranspiration. The results revealed that the expansion of urban areas and reduction in forest land have led to an increase in surface runoff and a decrease in lateral flow and percolation, which in turn have impacted the overall water yield of the watershed. The findings of this study can inform land use planning and management decisions to mitigate the negative impacts of LULC changes on water resources in the & Idot;znik Lake Watershed and similar regions
Effect of flow ramping on stranding potential related to river morphology—Developing hydraulic indices for peaking severity
Full text linkStranding can be an important negative effect downstream of peaking power plants. Much work is put into computing indices of peaking operation based on flow data from power plant outlets or in reaches downstream of power plants. Such indices give good measures of the frequency and magnitude of hydropeaking and indirectly the potential severity of the operation. To address stranding potential local studies are needed to find measures that relate river geometry to dewatered areas and dewatering speeds and the length of river downstream that is affected by the power plant operation. In recent years, high-precision laser scans have become available for some Norwegian rivers making it possible to do hydraulic modeling on a scale that can describe the dewatering process in detail. The new data also provides details on the river valley and areas adjacent to the rivers. Using these data, we have carried out simulations for peaking operations in several rivers and computed indices of hydraulic effects of potential shutdown hydrographs. The results show a dampening effect in all rivers and a significant relationship between river features like distance from outlet and cross section geometry and the hydraulic dependent indices ramping rate and dewatering rate. These relations could be a method for initial assessment of the effect of hydropeaking on rivers and a foundation for deciding on where more detailed studies will be needed.publishedVersio
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