Throughout the world, many people have been affected by water related issues in the past, some more extreme than others. In this context, hydrological models have often been used to gain more insight into the situation and to limit negative impacts as much as possible. There are many different types of hydrological models with each their strengths and weaknesses, but all models need a certain amount of reliable data. However, many river basins throughout the globe are poorly gauged which means there are only limited reliable ground observations available. That is why satellite observations provide many interesting opportunities to fill this gap of which many are not yet explored. Therefore the goal of this research was to answer the following main research question: What is the added value of satellite-based observations for hydrological modelling in a semi-arid, data-scarce river basin? This research focused on the Luangwa River in Zambia which is a large tributary of the Zambezi River. This semi-arid river basin is poorly gauged, mostly unregulated and sparsely populated. A process-based distributed hydrological model with sub-grid heterogeneity was developed in this research and modified step-wise when exploring the added value of different satellite observations for different aspects within hydrological modelling. This included analysing the information content of satellite-based river water level, i.e. altimetry, for model calibration, as well as evaporation and total water storage for step-wise model structure improvement and spatial-temporal model calibration. Overall, satellite-based observations have been used successfully to improve our understanding of the hydrological processes in the data-scarce Luangwa river basin, to improve the hydrological model structure and to allow for more reliable parameter identifications in the absence of reliable discharge data. This research focused on a selection of satellite-based observations and hydrological model applications. In other words, there remain many opportunities yet to be explored!
|Qualification||Doctor of Philosophy|
|Award date||1 Mar 2021|
|Publication status||Published - 2021|
- hydrological modelling
- semi-arid regions
- poorly gauged
- satellite data