184 research outputs found
Dispersion in the Ayeyarwady: A description of the mixing of tracers in the area of the Ayeyarwady River- Chindwin River confluence
No full textThe Ayeyarwady River (also called Irrawaddy River) is the most important river of Myanmar and due to the country’s rapid development it is expected to become even more important. The river flows roughly from north to south through Myanmar and is very dynamic and mostly unregulated. With a length of 2170 km and an over the year average (highly seasonally varying) discharge of 13’000 m3/s into the Andaman Sea (Bhardwaj, Owen, & Leinbach, 2012), the Ayeyarwady is one of the bigger rivers in Asia. To more than before take into account the interests of different stakeholders, as well as ecological aspects, sustainable management of the river is needed. Understanding the key aspects of the river flow can be a first step to sustainable river management (Richter et al., 2003). Pollution due to a large variety of activities of different nature make that water quality monitoring is of high importance (Thanda Thatoe Nwe Win, Bogaard, & Van de Giesen, 2015). For monitoring and modelling the water quality, information about the mixing of tracers trough the river is needed, which can be quantified with the use of dispersion coefficients. Little research has been done about the Ayeyarwady River in general considered its size and importance. Very limited data about the mixing of tracers and the parameters needed to estimate the mixing of tracers was available. This research focuses on the situation around the Ayeyarwady-Chindwin confluence in the first week of February 2017 (dry season). Hence, there is a very different situation during for example wet season. For the water quality, mainly the mixing in the longitudinal direction (direction of the main river flow) is of interest, which can be quantified by a longitudinal dispersion coefficient (Kx). First relevant parameters for estimating Kx were identified based on the theory. This appeared to be the discharge, roughness and bathymetry. Besides, Kx has to be calibrated by floater experiments. To get better insight into the magnitude of these parameters, flow velocity and depth measurements (needed for estimating the discharge, roughness and bathymetry) and floater experiments have been done during a week of fieldwork in the area. Due to loss, theft and destruction of floaters, less data was collected than planed. To get further insight in the mixing of tracers, a numerical model was made in the software Delft3D based on data collected during the fieldwork. Based on the combined results of the theory, measurements done during the fieldwork and the Delft3D model, it is expected that the magnitude of Kx in the Ayeyarwady River is somewhere in between 50-500 m2/s (best estimate: Kx~300 m2/s), although this has to be confirmed by further research. When the found value is compared with values found for other bigger rivers this value for Kx appears to be somewhat on the low side. From the Delft3D model runs follows that the longitudinal dispersion coefficient in the Chindwin River is higher than in the Ayeyarwady, possibly even a factor 10. Besides, insight in the effect of the different parameters on the dispersion was obtained, contributing to a better understanding of processes causing the mixing of tracers in the Ayeyarwady and Chindwin rivers. Estimating the highly sensitive longitudinal dispersion coefficient (Kx) appeared to be challenging, mostly due to the remote and highly dynamic character of the area. To make a better estimate of Kx, the uncertainty in the parameters needed (discharge, roughness, bathymetry and spreading of floaters for calibration) has to be reduced. Although some modelling options in Delft3D could be tried to narrow the range of these parameters, the best option to reduce this uncertainty is collecting more (high quality) data in the field
Validate results of river bends modelled by Delft3D 4 Suite and D-Flow FM
No full textThe use of rivers for navigation and the increased human activity along their banks generally requires river control and improvement measures. Most rivers have a natural tendency for continuous change of alignment, e.g. meandering and braiding rivers. Construction of bridges, towns, berths, etc. have required fixation of the river alignment at many places, changing the natural morphology of the rivers. This might lead to bank erosion, erosion around bridge pillars, sedimentation of navigation channels, etc. Adequate measures against this requires a reliable prediction of the morphological changes.For simulating the morphological effects in bends there are two different major factors involved that have been described by several scientists: bed slope effects and spiral flow. For modelling morphological development of a river bend several tests have been done on two different cases that have been researched in a laboratory flume (Delft Hydraulics Laboratory (DHL) and Laboratory of Fluid Mechanics (LFM)) in the 80s. In this research the effects of the major characteristics on the bed development of the bend are examined. This has been done by varying the different input parameters that have influence on the secondary flow and the bed slope effects. Subsequently the varied input files are used to model the same bend with Delft3D 4 Suite, D-Flow FM with an unstructured grid and D-Flow FM with a structured grid. In this way the differences are shown between the different kinds of modelling of the same input parameters.The parameters that have been tuned are Ash, Bsh and Csh for the bedload transport factor that is influencing the bed slope effect. The other parameter is Espir that influence the amount of spiral flow in a bend. The last is αcal that is a multiplication factor in the sediment transport formula from Engelund-Hansen in Delft3D 4 Suite. After optimising these parameters it was not possible to reproduce the flume experiments. Reason for this is probably a simplification in the numerical calculation because with similar parameters of Struiksmas modulation [6] in 1985, which reproduce the flume well, it was still not possible.To improve the reliability of the model it is recommended to study the following aspects:• Improvement of the inflow boundary conditions, to improve the way in which water and sediment flows into the system.• Improvement of the numerical modelling, to create a model that can simulate the characteristics of the river bed in a better way.• Look for test cases which are close to reality to see if the updates in the model are truly simulating the reality.By improving these points, the morphological changes might be predicted in a better way than it is in the current situation. Also it will be possible to have less crashes during the run of simulations.Additional master thesi
The effects of vegetation on riverbank stability in the Ayeyarwady River: The use of the Normalised Difference Vegetation Index as indicator for stabilising effects of vegetation by measuring bank retreat rates
No full textThe Ayeyarwady River is the most important river in Myanmar, connecting the cities Mandalay and Yangon, making inland water transport economically attractive. The Ayeyarwady River has a dynamic character, caused by the significant discharge difference between the dry and rainy season, and the related suspended sediment transport. Point bar formation in inner bends causes flow deflection towards the opposite riverbank. This causes local instability with as a result the banks to retreat. Vegetation contributes to the strength of riverbanks, by increasing the shear strength of the soil through roots and increasing hydraulic resistance, reducing flow velocities near the bank. However, to what extent the vegetation on the Ayeyarwady riverbanks contributes to this stability is debatable. Therefore it was the objective of this thesis to obtain a better understanding of the effects of vegetation on riverbank stability. By means of a fieldwork photo material of the river reach between Mandalay and Pakokku was collected, which was used for the NDVI validation. NDVI is the Normalised Difference Vegetation Index and is a remote sensing indicator for the ‘greenness’ of vegetation on satellite imagery. More vegetation means a higher NDVI value, hence it provides information about the livelihood of the vegetation present on the subsoil. In combination with determined bank retreat rates from a yearly comparison of satellite images in Google Earth, it was examined whether higher NDVI values, obtained with the Google Earth Engine, resulted in reduced bank retreat rates and therefore if NDVI can be used as a bank stability parameter. Nine regions of bank retreat were both altogether and separately examined, but the graphs showed no definite answer of retreat rates being dependent on NDVI. Therefore, the results of the riverbank retreat analysis were categorised based on location, erosion mechanism, the slope, and vegetation classes. The areas where fluvial entrainment was the primary erosion mechanism showed a clear trend. When NDVI was smaller than 0.2, maximum bank retreat rates appeared to be 200 meters per year. When NDVI was higher than 0.2, bank retreat rates did not exceed 80 meters per year. On satellite images, vegetation was not observed in these areas, so the influence of vegetation remained questionable. In areas where mass failure caused bank retreat, no reduction in bank retreat was found. The results showed considerable scatter, although much more vegetation was present on these banks. Water level variability played a crucial role in the evaluation of the net effects of vegetation on riverbank stability. During low water, vegetation cannot provide the positive impacts, especially on steep river banks. It is not possible to identify vegetation types from NDVI records only. NDVI also does not show which erosion mechanism takes place. This makes riverbank stability difficult to predict by using NDVI only, and therefore, NDVI does not seem to be an appropriate estimator for the additional effects of vegetation on riverbank stability. However, it can be used in combination with other remote sensing techniques to identify healthy vegetation areas and to make roughness estimations in river planform analyses
Comparing one and two-dimensional hydraulic modelling of flow on varying spatial scales: Identifying the physical processes that are of influence to the modelling choice of a stream system
No full textIn the past years, climate change has caused an increasing number of extreme weather events. In the Netherlands this is, for instance, reflected by the growing amount of extreme rainfall events. This creates big issues for water management authorities like water boards. Water boards are often responsible for local streams, that cannot handle the peak discharges caused by extreme rainfall. This raises the question whether measures have to be taken, for instance by creating additional storage areas to decrease discharge peaks. For questions like these computational model studies can be used to gain insight in the distribution of discharges and water levels.During these model studies often one-dimensional models are used. Recent developments made two-dimensional modelling, including for instance the simulation of inundation, possible for regular users like water boards. Two-dimensional modelling is proved to be more accurate for rivers, compared to one-dimensional modelling. Water boards, however, often deal with water systems of smaller scale. This raises the question whether it is worth for authorities like water boards to invest their resources in this new modelling approach. Several physical system properties are of influence on the answer to this question. Therefore, the main question of this research is:Which physical processes are of influence to the choice of a modelling approach, one or two dimensional, for the modelling of stream systems in particular situations?The methodology of answering this question consists of three major parts:1) identify possible differences in the model properties of 1D versus 2D modelling;2) analyze the output of test models to see whether the differences in model properties actually influence the effects of physical processes; and3) analyze a case area to see whether these processes are important in practice.The research scope consists of the hydrodynamics of systems with a length scale of 10^3 – 10^5 m and a temporal scale of hours to a few days. This range corresponds with a range in discharges of a few cubic meters per second up to a few thousands of cubic meters per second. The choice for this range has been made to be able to analyze the effects between the scales of streams and rivers, as until now mostly rivers have been modelled using 2D modelling approaches.The starting point of this research has been the analysis of differences in model properties. The used flow equations, numerical methods, computational grids and bathymetry implementation are analyzed and the differences are discussed. Concluding, it can be stated that there are differences, which may be of influence to the model output. The main differences are the number of dimensions on which the flow equations are calculated and the way the bathymetry is schematized by the computational grid.Using these differences, physical parameters have been specified that were varied in a range of test models. These are mainly the parameters that cause 2D effects, like meandering and varying roughness coefficients. The modelling of flood waves could also cause differences due to the fact that the 1D model is not able to model storage with the used default settings. Lastly, the way the bathymetry is used in the simulations is of great importance, due to the way the bathymetry is discretized in 2D models. The goal of varying these physical properties is to analyze whether these variations would influence the quantity of the effects the differences in model properties are causing. Comparing the output of both a 1D and 2D model, it appeared that there are significant differences in the observed water levels. Generally speaking, the following observations were made:1. The smaller the simulated spatial scale, the larger the 1D-2D differences are2. The higher the meandering intensity, the larger the 1D-2D differences are3. The lower the summer bed roughness, the larger the 1D-2D differences are4. The larger the 2D grid cell size, the larger the 1D-2D differences are5. The smaller the flood wave duration, the larger the 1D-2D differences areThe underlying physical processes have been analyzed to see how their influence varies in different situations and for different spatial scales. In the end, six processes were found to be influencing the 1D-2D differences:1. The effects of grid size on bathymetry discretization2. The water level and velocity difference in cross-sectional direction for varying roughness3. The water level and velocity difference in cross-sectional direction for varying meandering intensities4. The interaction between summer bed and floodplains5. The Boussinesq approach and consequences for the summer bed – floodplain flow area ratio6. The effects of storageWhen combining the findings of the test models and the analysis of a small scale stream system, it was found that the above processes are of the most influence on the following situations:1. In situations with a complex bathymetry the process of grid discretization is having the most influence.2. In situations with a high meandering intensity two physical processes are playing a role: high water level and velocity gradients in lateral direction, and a high summer bed – floodplain interaction.3. In situations with a very low roughness compared to the surrounding area two physical processes are playing a role: high water level and velocity gradients in lateral direction, and a high summer bed – floodplain interaction.4. In situations with a lot of elevation changes and open water bodies, a lot of potential storage is present.In these four situations a 2D approach is preferred, as the physical processes that are present in these situations are all processes that are poorly implemented or represented by a 1D model. Of course, there are also some more practical considerations to be made about the modelling choice. The most important one is the research goal; whether inundation modelling is desired and what the required model output is. Another important consideration is the available time for running the simulations; 2D models have a significantly longer simulation time compared to 1D models.All things considered, this research provides an overview of the differences in model properties between 1D and 2D modelling approaches, an analysis of the important physical processes that determine the choice of a modelling approach and some recommendations about practical issues one could encounter when performing a modelling study
Long-term bed level change in the Dutch Rhine branches and its impacts to water availability
No full textGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Rivers, Ports, Waterways and Dredging Engineerin
Morphological Impacts of Porcupine River Training Structures
No full textGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Rivers, Ports, Waterways and Dredging Engineerin
Combining microwave and optical remote sensing to monitor rivers in monsoon affected regions
No full textUnderstanding the river dynamics is very important to be able to make use of all river functions and to protect ourselves against floods. Hydrodynamic models are used to predict river behaviour and one of the input parameters is the river geometry. In-situ measuring of river geometry can be very expensive and time consuming. Remote sensing offers a more efficient method to monitor rivers, because it has the ability to continuously monitor the Earth surface at multiple scales. Rivers in monsoon dominated regions show a strong seasonal variation in discharge and have a high variability in morphodynamics. Therefore it is very important to have a high spatial-temporal resolution of river geometry data as input for hydrodynamic models to keep up with the changes in the river. Both optical and microwave images can be used in providing information about the river geometry. The microwave images need a lot of processing to deal with noise, but they are not limited by clouds, whereas optical sensors are troubled by clouds but produce less noise. The benefit of combining these methods is because the microwave images could fill the gap of cloud covered optical images during the monsoon. The main result from this thesis is that more investigation is needed on how to deal with the noise produced by the microwave images before the methods can be combined. Nevertheless it is shown that using the Canny Edge detector and Otsu thresholding improves the results. With this research we are a small step further in global river monitoring. This is important in particular for parts of the world where rivers are not continuously monitored because they are situated in hard to reach terrain and because the country will not invest in local gauge stations. Having more knowledge about river behaviour will help to get a better understanding of water losses along the river course, habitat change and flood risks.Geoscience and Remote Sensin
DVR toolbox for sediment management in the Rhine delta
No full textThe DVR Toolbox is a modeling system developed to be used as an operational model for long-term morphological assessment of the Rhine branches in the Netherlands (10 to 50 years). The Toolbox consists of a 2D computational core (containing the Delft3D modeling system), a shell that controls input- and output, and a system for time/simulation management. The effects of different processes, e.g. helical flow and sediment sorting, on time-dependent bed topography and dredging-operations can be simulated. It has been designed and optimized to allow for relative short computation times: 40 year simulations for the full delta can be run in less than 1 week. The Toolbox is mostly used to calculate morphological impacts that affect the navigability of the Rhine, and the impact of measures to affect them. It is now also widely used as an official tool to study the impacts of flood-lowering measures in the Room for the River program. Also for future studies in the Rhine River this Toolbox will be widely used.Hydraulic EngineeringCivil Engineering and Geoscience
Reservoir sedimentation; a literature survey
No full textA survey of literature is made on reservoir sedimentation, one of the most threatening processes for world-wide reservoir performance. The sedimentation processes, their impacts, and their controlling factors are assessed from a hydraulic engineering point of view with special emphasis on mathematical modelling. The objective of this study is to find the remaining gaps in the understanding of the relevant features, and the needs for further research. The physics of sediment distribution (such as delta formation and density currents) and the present modelling techniques are identified for various types of reservoirs. Attention is also paid to the operational aspects and the environmental impacts of the reservoir on the river-system morphology. Finally the methods to reduce the sediment inflow, to reduce the accumulation, or to remove the deposits are described. Evaluating the state of knowledge it is clear that a large number of physical processes are involved which are not well understood or hard to simulate. Recommended is to develop more comprehensive mathematical models and to do more specific laboratory research.Civil Engineering and Geoscience
The influence of hydropower developments on the Mekong delta
No full textRapid hydropower development is taking place in the Mekong river, which is expected to change the natural river regime. Because of the ecological and economical importance of the Mekong delta, the effects of these changes could have large consequences in the delta area. This research focuses on the hydrodynamical processes and assesses potential risks of changes to these processes, caused by hydropower development, could have on the ecology and socio-economy. Furthermore, a number of mitigation measures in the delta have been proposed to reduce the potential risks.Initiative for sustainable hydropower, Mekong River Commissio
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