Three braided rivers of different scales and different hydrologic/geomorphologic characteristics (the Aichilik and Hulahula in Alaska and the Brahmaputra in Bangladesh) are analyzed for spatial scaling using a logarithmic correlation integral method developed earlier by the authors. It is shown that the rivers exhibit anisotropic scaling (self‐affinity) with fractal exponents vx = 0.72–0.74 and vy = 0.51‐0.52, the x axis being oriented along the river and the y axis in the perpendicular direction. The fact that despite large differences in scales (0.5–15 km in braid plain width), slopes (7 × 10−3 to 8 × 10−5), and types of bed material (gravel to sand), the analyzed braided rivers show similar spatial scaling deserves special attention. It might indicate the presence of universal features in the underlying mechanisms responsible for the formation of the spatial structure of braided rivers. Also, comparison of fractal characteristics of braided rivers with those of single‐channel rivers and river networks suggests that braided rivers form a class of fractal objects lying between the classes of single‐channel rivers and river networks.

Abstract. As in any evolving process, including rainfall, variability in space and time are not independent of each other but depend in a way particular to the process at hand. Understanding and quantifying the space-time dependences in a process over a range of scales is not always easy because these dependences may be hidden under complex patterns with pronounced statistical variability at all scales. In this paper, we report our efforts to understand the spatiotemporal organization of rainfall at a range of scales (2 km to 20 km in space and 10 min to several hours in time) and explore the existence of simple relationships which might connect the rate of rainfall pattern evolution at small space and time scales to that at larger scales. Specifically, we seek to understand whether there exist space-time transformations under which these relationships can be parameterized in a simple scale-invariant framework. On the basis of analysis of several tropical convective storms in Darwin, Australia, we found that the rate of evolution of rainfall remains invariant under space-time transformations of the form t • L z (dynamic scaling). In other words, the dependence of the statistical structure of rainfall on space (L) and time (t) can be reduced to a single parameter t/L •, where z is called the dynamic scaling exponent. The space-time organization in rainfall, apart from being interesting in its own right, permits the development of simple rainfall downscaling schemes which incorporate both spatial and temporal persistence.

Enhancement of current for solutions, containing Ni+2, Fe+2, and H+ ions, has been observed by linear sweep voltammetry and chronoamperometry when a magnetic field of 0.1 T was applied parallel to the cathode. The current enhancement in a magnetic field was attributed to the convection near the electrode surface induced by the Lorentz force. There is a decrease of the Fe content in NiFe films by approximately 4% obtained with applied magnetic field. It was also demonstrated that the applied magnetic field affects the magnetic properties, crystalline structure and/or texture, stress, and surface roughness of NiFe films. © 2003 The Electrochemical Society. All rights reserved.

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Abstract.Interpretation of the impact of climate change or climate variability on water resources management requires information at scales much smaller than the current resolution of regional climate models. Subgrid-scale variability of precipitation is typically resolved by running nested or variable resolution models or by statistical downscaling, the latter being especially attractive in ensemble predictions due to its computational efficiency. Most existing precipitation downscaling schemes are based on spatial disaggregation of rainfall patterns, independently at different times, and do not properly account for the temporal persistence of rainfall at the subgrid spatial scales. Such a temporal persistence in rainfall directly relates to the spatial variability of accumulated local soil moisture and might be important if the downscaled values were to be used in a coupled atmospheric-hydrologic model. In this paper we propose a rainfall downscaling model which utilizes the presence of dynamic scaling in rainfall [Venugopal et al., 1999] and which in conjunction with a spatial disaggregation scheme preserves both the temporal and spatial correlation structure of rainfall at the subgrid scales.