Space-time streamflow: A theoretical and practical approach

Streamflow in a river basin is a space-time object, with a value at every time and every point in the river network. Several important theoretical and practical questions in surface water hydrology depend on an understanding of the structure of this object. The purpose of this dissertation is to build a theoretical and practical framework for characterizing space-time streamflow by: (1) investigating the possibility of measurement extension, preparing data and building the spatial structure for space-time streamflow by calibrating a quasi-distributed rainfall-runoff model in a moderately-sized river basin; (2) proposing a general theoretical framework for space-time streamflow in a river basin with applications to the structure of second order statistics of space-time streamflow; and (3) applying the general theoretical framework to an area of practical importance, proposing a space-time flood peak theory with practical applications.; A distributed rainfall-runoff model which uses the TOPMODEL construct at the sub-basin scale is developed and calibrated for the St. Francis River basin by taking into account spatially distributed rainfall, land use/land cover, soil and geologic information. This model is used to provide basic data and structure for the space-time streamflow theory, and an approximate extension of streamflow to sub-basin scale.; The general space-time streamflow theory is built on a pixel and grid description of the river basin under simple runoff production and linear routing assumptions. The theory is demonstrated by special cases and simplifications with application of second order statistics of space-time streamflow. Results in real basins validate the theory.; The space-time flood peak theory is a practical application of the general space-time streamflow theory and focuses on the physical structure of spatial flood peaks (annual flood peak especially). The space-time flood peak theory starts from very simple assumptions on flood peak distribution scale exponent analysis and then modifies the assumptions to bring them close to reality. Some straightforward physical structures, especially the correlation structure of flood peaks, are modeled and analyzed with practical applications such as regional flood probability.