Characterising Spatiotemporal Pattern of Flow Regime in Large-Scale Arid-Zone Anastomosing Rivers

© 2019 Abbas MohammadiAbstract Anastomosing rivers are characterised by their low stream power (<10 Wm-2) in low-gradient floodplains (slope ~ 0.02%) and fine-grained cohesive sediments with minimal lateral activity. These rivers have a significant endemic and range-restricted biodiversity and the annual flood cycle is the basis of subsistence of the local population, providing water, arable land, and wetland resources. Consequently, they play a vital role in sustaining the cultural and environmental life of their basins. However, they are under increasing pressure on land use and water demands. In order to determine a sustainable level of water allocation for human purposes, their flow regime should be characterised first. Typically, hydrological modelling is employed to estimate how changes in climate and proposed water plans might affect surface and groundwater resources. However, hydrological modelling in the large-scale, sparsely gauged, spatially complex, low-gradient arid anastomosing floodplains with high annual flow variability is challenging. In Australia, previous attempts to characterise transmission loss in the wide anastomosing floodplains (width ~ 50 km) of Lake Eyre Basin were largely based on simplistic conceptual models, incorporating only gauged streamflow or coarse grid-based semi-distributed hydrological models. Consequently, they provided a poor representation of spatial patterns for flow paths and transmission loss. In this thesis, it was hypothesised that considering the volume and spatiotemporal features of direct floodplain rainfall and ungauged runoff from catchments surrounding floodplains significantly improves the accuracy of their water balance. In addition, accurate mapping of water extent and subsequent vegetation by remote sensing data is critical to model evapotranspiration dynamics over time and space. These two hypotheses will provide a more realistic conceptualisation of transmission loss patterns in the anastomosing rivers. After the introduction (Chapter 1) and literature review (Chapter 2), in the first part of the thesis (Chapter 3), an integrated framework for characterising floodplain response dynamics of water, vegetation and moisture was developed using optical remote-sensing. Daily time series of multispectral indices derived from MODIS images were utilised in the middle reaches of the Cooper Creek floodplain, the largest catchment of the Lake Eyre Basin in Australia. Findings indicated that in the extremely flat Cooper Creek floodplain, mapping inundation area by subsequent vegetation changes using NDVI provides more accurate results than surface water mapping area and the difference in their inundation mappings mainly occurs at the border of inundated edges, where the residence time of water is likely less than a day. Whereas, water and moisture indices (mNDWI and LSWI) outperform NDVI in detecting inundation extent in large water bodies (like Yamma Yamma Lake). In addition, by studying surface water and subsequent vegetation response together, it is possible to generate new information, such as the lag time between flooding and peak vegetation growth, and persistence time of surface water and green vegetation, which provide important hydroecological time scales in the arid zone floodplain. In the second part (Chapter 4), the significance of ungauged inflow and direct floodplain rainfall on the water balance of the Cooper Creek was investigated. Results indicated that ungauged streamflow mainly impacts the outflow volume of large flood events when the monsoon rainfall of tropical origin advances further south to inland Australia. In medium-size floods, ungauged flow is significant only when the ungauged catchments near the outlet receive considerable rainfall. In addition, local storms that are not captured by the sparse rainfall gauges of the ungauged catchments can impose high uncertainty on the water balance of flood events. Then, the proportion of rainfall contributing to the routing flow was estimated by means of remotely sensed inundation extent. In small and medium events, often