Field studies on factors affecting very fine and ultra fine particulate organic matter deposition in low‐gradient sand‐bed streams

The knowledge on particle deposition in streams is mainly based on investigations in mountain streams. No data exist from low‐gradient sand‐bed streams that largely differ in the morphological and hydraulic factors proposed to affect deposition. To identify physical control on particle deposition in low‐gradient streams, we assessed deposition of very fine and ultra fine organic particulate matter in 18 sand‐bed stream reaches. We added particles derived from lake sediment and assessed the mean transport distance S_P and the deposition velocity v_dep. Additionally, reach hydraulics were estimated by injections of a conservative solute tracer (NaCl). Among the low‐gradient streams, particle deposition kinetics were variable but similar to deposition in mountain streams. S_P was solely related to the flow velocity. This relation was confirmed when comprising published data on deposition of fine organic particles. An association between particle deposition and transient storage factors was insignificant. We found significance of the transient storage to S_P only for repeated measures within a single reach, when flow velocity and benthic conditions were nearly constant. Measured v_dep/v_fall ratios were much larger than unity in most reaches. Evidence from this relation suggests that the vertical transport of very fine and ultra fine organic particulate matter through the water column was caused mainly by vertical mixing. Copyright © 2006 John Wiley & Sons, Ltd.     

Uncertainties in real‐time flood forecasting with neural networks

Although artificial neural networks (ANNs) have been applied in rainfall runoff modelling for many years, there are still many important issues unsolved that have prevented this powerful non‐linear tool from wide applications in operational flood forecasting activities. This paper describes three ANN configurations and it is found that a dedicated ANN for each lead‐time step has the best performance and a multiple output form has the worst result. The most popular form with multiple inputs and single output has the average performance. In comparison with a linear transfer function (TF) model, it is found that ANN models are uncompetitive against the TF model in short‐range predictions and should not be used in operational flood forecasting owing to their complicated calibration process. For longer range predictions, ANN models have an improved chance to perform better than the TF model; however, this is highly dependent on the training data arrangement and there are undesirable uncertainties involved, as demonstrated by bootstrap analysis in the study. To tackle the uncertainty issue, two novel approaches are proposed: distance analysis and response analysis. Instead of discarding the training data after the model's calibration, the data should be retained as an integral part of the model during its prediction stage and the uncertainty for each prediction could be judged in real time by measuring the distances against the training data. The response analysis is based on an extension of the traditional unit hydrograph concept and has a very useful potential to reveal the hydrological characteristics of ANN models, hence improving user confidence in using them in real time. Copyright © 2006 John Wiley & Sons, Ltd.     

按运动学方法确定疏散星团M11的距离

在合理假设星团成员星的内部随机运动为各向同性的基础上,提出一种利用纯运动学资料确定星团距离的方法,并依此方法估算出疏散星团M11的速度距离为(1．89±0．52)kpc。这一结果与其他作者给出的星团M11的光度距离符合得相当好。     

Harmonizing the RR Lyrae and clump distance scales – stretching the short distance scale to intermediate ranges?

I explore the consequences of making the RR Lyrae and clump giant distance scales consistent in the solar neighbourhood, Galactic bulge and Large Magellanic Cloud (LMC). I employ two major assumptions: (i) that the absolute magnitude–metallicity, M _V (RR)–[Fe/H], relation for RR Lyrae stars is universal, and (ii) that absolute I magnitudes of clump giants, M _I (RC), in Baade's Window are known (e.g. can be inferred from the local Hipparcos -based calibration or theoretical modelling). A comparison between the solar neighbourhood and Baade's Window sets M _V (RR) at [Fe/H]=−1.6 in the range (0.59±0.05, 0.70±0.05), somewhat brighter than the statistical parallax solution. More luminous RR Lyrae stars imply younger globular clusters, which would be in better agreement with the conclusions from the currently favoured stellar evolution and cosmological models. A comparison between Baade's Window and the LMC sets M ^LMC(RC) _I in the range (−0.33±0.09,−0.53±0.09). The distance modulus to the LMC is μ ^LMC∈(18.24±0.08,18.44±0.07). Unlike M ^LMC(RC) _I , this range in μ ^LMC does not depend on the adopted value of the dereddened LMC clump magnitude, I ^LMC(RC)₀. I argue that the currently available information is insufficient to select the correct distance scale with high confidence.     

WARPED SPACE: A GEOGRAPHY OF DISTANCE DECAY*

Distance decay is one of geography's core concepts, yet its own spatial properties have been largely neglected. We illustrate the use of the expansion method in assessing the spatial variation of distance-decay parameters within the general context of gravity models. The approach enables the portrayal of “space warping,” said to occur when equivalent distances have spatially uneven effects on interaction. The concepts are examined empirically through the estimation of a competing destination model for out-migration from five State Economic Areas over the 1965–70 period. Four of the five origins are found to have spatially unstable frictions of distance. We conclude by suggesting that distance decay is a contextual, rather than a universal, effect.