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To disclose the turbulence features near a permeable spur dike, this paper measures the three-dimensional (3D) instantaneous velocity at different vertical lines and depths around the permeable spur dike through acoustic Doppler velocimetry (ADV). The relative turbulence intensity and Reynolds stress were calculated for each measuring point, and the distribution features of different turbulence structures were analyzed along the water depth. Experimental results show that: within the length of the dike, the turbulence intensity and Reynolds stress in the downstream of the dike are much greater than those in the upstream. In the downstream of the dike, the turbulence intensity in the root and body regions peaks in the dike crest layer, but that at other positions minimizes in that layer (but peaks on the water surface or river bottom). In the upstream, ejection and sweeping are the dominant turbulence structures; the two structures also dominate near the free layer at the bottom in the downstream; outward and inward interactions dominate near the dike crest layer in the downstream.

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The daily runoff is a complicated hydrological time-series, its extreme changes will affect not only the safety of the ships underway but also the dispatching of water transportation. Daily runoff forecast is a hot topic in hydrologic analysis and water transport planning. The fractional differenceautoregressive model based on wavelet analysis (WFIAR) is used to forecast the daily runoff. The daily runoff time series from 2002 to 2013 of Hankou Hydrologic Station are decomposed by the orthogonal db4 wavelet function into a series of stationary high-frequency sub-sequences and a non-stationary low frequency subsequence. According to the Hurst exponent of the low frequency subsequence, the appropriate difference order is determined and fractional difference is made. The differenced low-frequency part and high-frequency parts set up autoregressive models separately. These models are combined to forecast the daily runoff time series in 2014 and 2015 separately. The first-order difference autoregression (DIAR) model and the first-order autoregression (WDIAR) model based on wavelet analysis are also established to compare the forecasting accuracy of different models. The results show that the prediction accuracy of WFIAR is higher than the other two models that reveal the advantage of WDIAR model in daily runoff forecast. ARTICLE HISTORY