Predicting space-time variability of hourly streamflow and the role of climate seasonality: Mahurangi Catchment, New Zealand

We present a systematic approach to achieving accurate hourly streamflow predictions at locations internal to a catchment, potentially with minimal calibration. Each step in this approach is meant to provide insight into the relative importance of catchment and climatic properties (rainfall, soil, vegetation, topography), their spatial variability, and their influence on the spatial and temporal variability of streamflows. This has been made possible through the use of a simple conceptual model design requiring minimal calibration and with physically meaningful catchment parameters estimated mostly a priori from landscape data, and climatic variables. Eight model types originating from this simple conceptual model design, with complexity ranging from lumped to fully distributed, were tested over summer and winter periods at the Mahurangi Catchment, New Zealand, and the preferred model identified using statistical assessment criteria. Results of the simulations suggest that, although the required model complexity was found to be a function of the season (summer versus winter), a fully distributed representation is most appropriate for accurate predictions under all seasonal climate conditions. Using this model, the success of hourly flow predictions in space-time was assessed and sensitivity analysis used to identify the dominant controls on the timing and magnitude of hourly flow predictions and to investigate the adequacy of the assumption of homogeneity for a number of catchment properties. Copyright (C) 2003 John Wiley Sons, Ltd.