Dispersion in the Ayeyarwady

Abstract

The 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.