Superview-1 Remote Sensing for hydromorphological monitoring of shallow water streams within the Water Framework Directive

Abstract

Understanding change in river morphology is a crucial aspect to comprehend the complex and intertwined processes within a river ecosystem. The Dutch implementation of the Water Framework Directive (WFD) has established parameters that need to be monitored of river systems. One of those parameters included is hydromorphology. Although past studies emphasize the importance of measuring hydromorphology over time, this is not directly considered within this implementation of the WFD. Beyond the WFD parameters, the objective of this study was to monitor the hydromorphology shallow streams on high temporal basis with Superview-1 images. The research goal was to assess which waterbody extraction method gained the highest accuracy based on the Superview-1 satellite images. The AHN lidar scans of the Netherlands were used as validation reference, as lidar sources are substantiated for their classification accuracy. This research tested three waterbody extraction methods, including the Otsu threshold method, Supervised machine learning (Support Vector Machine) on a single training image, and Supervised machine learning (Support Vector Machine) on a multi-image training dataset. Accuracies for the threshold method, singleimage SVM, and multi-image SVM were assessed to be 90% (Kappa: 0.70), 76% (Kappa: 0.50) and 90% (Kappa:072), respectively. Going forward with hydromorphological monitoring of the shallow water streams, the Support vector machine trained on multiple images was used given its accuracy and kappa scores. By means of intersecting the extracted river polygons, with a pre-defined cross section, shift in riverbanks (left and right) and centre point was computed for an eroding and non-eroding section. This study revealed that a total shift of between 4.5 and 8.6 meters was recorded at the eroding section between the period of 2019 and 2023. At the noneroding section, the shift remained between 0.2 and 1.3 meter between 2019 and 2023. A maximum shift of 13.1 meters was recorded at one of the cross sections at the right riverbank (eroding section). This approach utilizing Superview-1 images has increased the temporal resolution of hydromorphology monitoring to approximately five yearly images. Towards monitoring the ecological status of shallow rivers, this research identified what the contribution of Superview-1 imagery could imply. Understanding trends in river (bank) shift is crucial for creating context for monitoring ecological status, within WFD.