University of Twente Student Theses


Automated detection of river morphodynamics for large multithreaded rivers with satellite imagery : a case study on the Ayeyarwady river

Rawee, J. (2020) Automated detection of river morphodynamics for large multithreaded rivers with satellite imagery : a case study on the Ayeyarwady river.

[img] PDF
Abstract:Understanding planform dynamics is a difficult task as they are controlled by complex interactions between the discharge variability, sediment transport, floodplain characteristics and the valley geometry. The difficulties in understanding planform dynamics especially become clear in multithreaded river planforms, whose existence is still poorly understood. Multithreaded river planforms are characterized by a complex geometry with multiple channels separated by bars or islands. Satellite imagery combined with automated detection techniques might be key to generate a better understanding of planform dynamics, due to their ability to study large spatial scales. However, automated detection and quantification of planform dynamics is challenging, especially in complex multithreaded rivers. The main goal of this thesis is therefore to investigate the possibilities of automated detection techniques with satellite imagery to characterize, quantify and explain planform dynamics for large multithreaded rivers There exist several ways to consistently identify the river surface. The main challenge is to eliminate the effect of a varying water level, as the water level affects the extent of the water surface. To eliminate this effect two techniques are applied. The first is to automatically detect the vegetation boundary, which is assumed to be the river bankline. The second method uses water level measurements to select images with a similar water level and automatically detects the water surface. To study planform dynamics there is opted to use yearly intervals, in which images are selected in each dry season. This limits cloud cover in the study area and allows to study the effect of yearly occurring flood seasons on planform dynamics. The final step is to quantify yearly changes in river planform, which is done by differencing the detected river masks. This allows to quantify areas of change in metrics such as erosion and deposition. Next, the methods are applied at a case study of the multithreaded Ayeyarwady river (Myanmar). A roughly 250 km long river section located in the lower Ayeyarwady river is studied. Strong variability in planform dynamics over time is detected. Some years measure up to 3 times the amount of erosion as other years. The intensity of the planform dynamics is found to be strongly correlated to the average water level in the 4-month lasting flood season. Thus, yearly variations in average flood season intensity explain the large yearly variability in the measured intensity of the planform dynamics. Besides, the active surface area of the river, or the total area between the river banklines, is investigated. A decreasing trend is found in the study period of 1988-2019, indicating the abandonment of channels and a reduction in the overall river width. A plausible explanation that is found is a reduction in the long-term average intensity of flood seasons. The reduced intensity especially becomes clear between 1998 and 2010, in which relatively calm flood seasons are measured. This caused the abandonment of some of the active channels which resulted in a strong decrease in active channel area in the study period. The results of the case study show that even in complex multithreaded rivers, the usage of automatic detection on satellite imagery allows to quantify and characterize planform dynamics. The ability of automated detection techniques to quantify planform dynamics on large spatial scales, allowed to quantitatively study the controls of observed planform dynamics. In this way, the large impact of flood season intensity and its yearly variations could be identified. Some difficulties and limits remain, such as the uncertainty in detection, the spatial resolution of satellite images, and the remaining challenges to consistently derive river banklines. Nevertheless, this study shows the potential of automated detection techniques to better understand planform dynamics in rivers with complex multithreaded planforms. With ever-increasing pressure on river systems due to climate change or human interventions such as river dams, understanding the controls of planform dynamics is key to successfully manage rivers and their dynamics in the future.
Item Type:Essay (Master)
Faculty:ET: Engineering Technology
Programme:Civil Engineering and Management MSc (60026)
Link to this item:
Export this item as:BibTeX
HTML Citation
Reference Manager


Repository Staff Only: item control page