Streamflow and fluvial sediment load are inter-connected and through river networks contribute to the dynamic stability of river/coast systems. Robust assessment of catchment responses under changing climate and human activities is essential for understanding future status of the system. This study was undertaken to explore how different modelling approaches and input data sources may influence projections of streamflow and fluvial sediment loads accounting for climate change and human activities, particularly in data-poor river basins. In order to achieve this overarching objective, two case study sites were selected: the Irrawaddy River Basin in Myanmar and the Kalu River Basin in Sri Lanka. Results show that while not all global precipitation products are equally good, application of carefully selected precipitation products and remote sensing-based evapotranspiration data have viable potential for simulating hydrological response in data-poor basins. Model projections indicate that, at the two selected study sites, streamflow and fluvial sediment supply to coasts would increase by 2100. In the Irrawaddy River Basin, significant alterations in seasonal streamflow and sediment loads are projected under climate change scenario combined with the effects of planned reservoirs. Comparison of annual fluvial sediment loads projected using the process-based SWAT model and the empirical BQART model indicates that the BQART model might be better suited for large basins (such as the Irrawaddy).
|Qualification||Doctor of Philosophy|
|Award date||10 Dec 2020|
|Place of Publication||Enschede|
|Publication status||Published - 10 Dec 2020|