[1] Previous studies have shown significant dependence of annual maximum floods in eastern Australia on the Interdecadal Pacific Oscillation (IPO), a low-frequency mode of natural climatic variability. However, the causative factors behind differences in flood risk observed during contrasting phases of the IPO remain poorly understood. In particular, an important question that stems from a practical flood hydrology perspective is: Does maximum precipitation exhibit a similar level of dependence on the IPO as that observed in the floods? If not, then what are the factors responsible for this disparity, and are there significant ramifications for the conventional approach of estimating design floods through a predefined design rainfall? This paper investigates the possible reasons for the disparate relationship of IPO on rainfall and streamflow design events; that is, why do flood characteristics for contrasting IPO phases differ significantly compared to less notable changes in the corresponding rainfall intensities? We hypothesize that this difference in flood characteristics as a function of the IPO is a result of catchment antecedent or wetness conditions prior to the design storm. This hypothesis is tested using data from 166 high-quality daily rainfall stations across Australia along with catchment-averaged rainfall and resulting flows across an additional 128 catchments from the same region. In addition, 35 subdaily rainfall stations with long records in east Australia were also used to support our arguments. The results of these tests suggest that catchment antecedent conditions prior to design storm events were found to vary significantly across the two IPO phases, leading to the significant differences in flood characteristics across the two phases.
Results of this study are valuable as a methods to determine optimum space and time discretizations of future modeling applications when the maximum allowable numerical error and the dimensions of the flow features to be simulated are known. Results can also be used to understand the magnitudes of numerical errors in existing modeling applications.
River ice processes are complex phenomena that are affected by many factors, including meteorological conditions, thermal inputs, hydraulic conditions and channel geometry. In this study a one-dimensional model called RICE is developed for simulating ice processes in rivers. In the river hydraulics component, the flow condition is determined by an implicit finite-difference solution of onedimensional unsteady flow equations. In the thermal component, distributions of water temperature and ice concentration are determined by a LagrangianEulerian solution scheme for equations of transport of thermal energy and ice. A two-layer formulation is introduced to model the ice transport. In this formulation the total ice discharge is considered to consist of the surface ice discharge of suspended ice distributed over the depth of the flow. The effect of surface ice on ice production, as well as the formation of skim ice and border ice, is included. The dynamic formation and stability of the ice cover is formulated according to existing equilibrium ice jam theories with due consideration to the interaction between the ice cover and the flow. The undercover ice accumulation is formulated according to the critical velocity criterion. The growth and decay of the ice cover is simulated using a finite-difference formulation applicable to composite ice covers consisting of snow, ice and frazil layers. The model has been applied to the St. Lawrence River and the Ohio River system, with simulated results comparing favorably with field observations. Future improvements on the mathematical model as well as theoretical formulations on various ice processes are discussed.
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