The seasonal Chindwin river (Myanmar) forms the central artery for transportation in the region. However, the dynamic river behaviour, archaic boat equipment and limited monitoring, yearly results in large numbers of grounding ships, causing injuries and economic losses. A pilot
...
The seasonal Chindwin river (Myanmar) forms the central artery for transportation in the region. However, the dynamic river behaviour, archaic boat equipment and limited monitoring, yearly results in large numbers of grounding ships, causing injuries and economic losses. A pilot project involving CoVadem technology was initiated in the beginning of 2019 to benefit safer navigation on the Chindwin. CoVadem technology can chart the most up to date water depths by collecting under keel clearance measurements from the commercial fleet. The pilot project aims to increase safety on the Chindwin through sharing information about safe routes and forecasted water depths with captains sailing the river.
The added value of using CoVadem technology, however, is vulnerable to the number of participating vessels. A combination of morphological changes and the typical spatial spread of CoVadem data limits the extent of the navigation channel that can be derived from the data. With only a small part of the navigation channel known it is unclear where passing of other vessels is possible, where speeds should be adjusted due to e.g., bottlenecks and where shorter routes are present.
The objective of this research is to provide more information about the navigable area around CoVadem data in order to assist captains with navigation. During this research, two physics-based models have been developed, able to carry out this task. The ‘soil-model’ combines CoVadem data with assumptions about the maximum slope in the bed.
The ‘axi-symmetric model’ utilises CoVadem data, the axi-symmetric solution and assumptions about sand dunes and river banks in a model to estimate a navigable area.
Two ‘reliability indicators’ have been developed that can indicate areas of the river where the output of the axi-symmetric model is reliable in its estimate. One indicator is related to the channel stability, it is calculated from many years of satellite imagery. The other indicator is related to channel curvature.
To measure the performance of the models and the reliability indicators, two dimensionless performance indicators have been developed: the safety score and the channel coverage score. The models and the reliability indicators were consecutively tested and evaluated for four study cases located along the Chindwin river.
The results are promising. It follows from this research that navigation channel estimates around scarce CoVadem ship track data can substantially benefit from application of a physics-based model. The soil-model is very robust, but has limited added value for navigation. The axi-symmetric model increases the navigable width estimate around a single CoVadem trackline significantly O(100 m). The performance indicators can improve the reliability of the axi-symmetric model significantly.
This research combines Big Data, physics-based models and remote sensing in a not early demonstrated way: with models tailored for navigable area estimates and with measured data as the starting point. The correlation between axi-symmetric model reliability and remote sensing/curvature is, moreover, something that has not been demonstrated before. Finally, the two developed performance indicators show great promise for the evaluation of navigable area estimates. As such, this research adds to current advancements in (open-access) cross-platform data accumulation and utilisation.
