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Visitor crowding issues caused by over-tourism at World Heritage Sites (WHS) are increasingly prominent. However, related studies and management give less consideration to the uneven tourist spatial-temporal distribution within micro-attractions, ignoring the detrimental impacts of local crowding on WHS' sustainable development. Aimed at exploring local crowding within heritage attractions from a perspective of time-space, this study used video-based computer vision technology to analyze tourist spatial-temporal distribution, density, and carrying capacity at stationary points (spatial locations where visitors stay and gather), taking a case study of the Master-of-Nets Garden, a World Cultural Heritage Site. The results indicated that although the total visitor number was below the attraction's carrying capacity, visitors repeatedly and quickly crowded at stationary points and formed high-density clusters, exceeding stationary points' space capacity and causing spatial local crowding. When visitors' dwell time was 5, 12, and 20 seconds, the crowding index K of stationary points was 3.4∼108.5, 1.7∼42.9, and 0.5∼33, indicating the spatial local crowding effect was negatively correlated with the length of visitors' dwell time at stationary points. Our contribution provides an accurate understanding of local crowding in WHS by highlighting the impact of tourist spatial-temporal distribution on carrying capacity and spatial crowding and suggests visitor management recommendations. [ABSTRACT FROM AUTHOR]

This paper presents the results of an experimental study on the mean and turbulence structures of flow in a vertical slot fishway with slopes of 5.06 and 10.52%. Two flow patterns existed in the fishway and for each one, two flow regions were formed in the pools: a jet flow region and a recirculating flow region. The mean kinetic energy decays rapidly in the jet region and the dissipation rate in most of the areas in the pool is less than 200 W/[m.sup.3]. For the jet flow, the nondimensional mean velocity profile across the jet agrees very well with that of a plane turbulent jet in the central part of the jet with some scatter near its boundaries. Its maximum velocity decays faster compared to a plane turbulent jet in a large stagnant ambient. The jet presents different turbulence structure for the two flow patterns and for each pattern, the turbulence characteristics appear different between the left and right halves of the jet. However, the turbulence characteristics show some similarity for each case. The normalized energy dissipation rate shows some similarity and has a maximum value on the center of the jet. The results are believed to provide useful insight on the turbulence characteristics of flow in vertical slot fishways and can be used to verify numerical models and also for guidance in the design of fishways in the future. CE Database subject headings: Fish habitats; Turbulence; Energy dissipation; Hydraulic structures; Water flow.

Turbulence characteristics of hydraulic jumps with Froude numbers of 2.0, 2.5, and 3.32 are presented. A Micro Acoustic Doppler velocimeter was used to obtain measurements of the velocities, turbulence intensities, Reynolds stresses, and power spectra. The maximum turbulence intensities and Reynolds stress at any section were found to decrease rapidly from the toe of the jump towards downstream within the jump and then gradually level off in the transition region from the end of the jump to the friction dominated open channel flow downstream. The maximum turbulence kinetic energy at each section decreases linearly with the longitudinal distance within the jump and gradually levels off in the transition region. The Reynolds stress and turbulence intensities within the jump show some degree of similarity. The dissipative eddy size was estimated to vary from 0.04 mm within the jump to 0.15 mm at the end of the transition region. The dominant frequency is in the range from 0 to 4 Hz for both horizontal and vertical velocity components. CE Database subject headings: Hydraulic jump; Turbulence; Energy dissipation; Froude number.

Floods occur frequently and cause considerable damage to local environments. Effectively assessing the flood risk contributes to reducing loss caused by such disasters. In this study, the weighted naïve Bayes (WNB) method was selected to evaluate flood risk, and the entropy weight method was employed to compute the weights. A sampling and verifying model was employed to generate the most accurate conditional probability table (MACPT) to calculate the probability of flooding. When using the framework integrating WNB with the sampling and verifying model, previous studies could not obtain a WNB‐based MACPT and the WNB classification accuracy, for lacking WNB functions that could be called directly. Facing this issue, in this study we developed WNB functions with the MATLAB platform to directly integrate with the sampling and verifying model to generate a WNB‐based MACPT, contributing to the greater interpretability and extensibility of the model. Shantou and Jieyang cities in China were selected as the study area. The results demonstrate that: (1) a WNB‐based MACPT can reflect the real spatial distribution of flood risk and (2) the WNB outperform the NB when integrated with the sampling and verifying model. The resulting gridded estimation reveal a detailed spatial pattern of flood risk, which can serve as a realistic reference for decision making related to floods. Furthermore, the proposed method uses less data, which would be helpful in developing countries where long‐term intensive hydrologic monitoring is limited. [ABSTRACT FROM AUTHOR]

Bubble characteristics in free hydraulic jumps for inflow Froude numbers ranging from 2.0 to 6.7 were measured using a single-tip optical probe, with a focus on mean and turbulent bubble velocities. It was found that the mean bubble velocity , to a large extent, is able to reflect the water-phase flow structure in a jump. In the boundary layer of the channel bed, follows the th power law in the vertical direction, and it follows a Gaussian distribution beyond that up to the water surface. Dimensionless maximum bubble velocity was found to be smaller than that for the classical wall jet up to a characteristic distance in the longitudinal direction; beyond that, however, they agree well with each other. Turbulence intensity of bubble velocity was found to first increase and then decrease with the vertical distance from the bed. The maximum value of turbulence intensity is 33% of the inflow velocity, which is comparable to that of the water-phase. Exponential relations are proposed to describe the variation of the maximum bubble velocity and maximum turbulence intensity of bubbles, in the longitudinal direction. [ABSTRACT FROM AUTHOR]

• The Random Naïve Bayes (RNB) was developed to evaluate the flood susceptibility. • A repeatedly random sampling method was adopted to select negative samples for RNB. • The RNB-based most accurate classifier can achieve better classification performance. • The framework can generate stable flood susceptibility maps. • RNB is a feasible approach for natural susceptibility assessment study. Random Naïve Bayes (RNB) is a machine learning method that uses the Random Forest (RF) structure to optimize Naïve Bayes (NB). It is interesting to see whether RNB could optimize NB and achieve satisfied assessment results like RF in the flood susceptibility assessment study. RNB has rarely been used in study of using machine learning methods to spatially analyze natural disasters, and thus it was selected as the analysis method. Based on the data feasibility, 12 spatial factors that affect the occurrence and spatial distribution of floods were selected. To avoid the influence of subjective equal-interval classification method, natural breaks and quantile method were used to discretize factors with continuous values, respectively. Here, a recently proposed repeatedly random sampling method was adopted to select negative samples for RNB to generate a most accurate classifier (MAC) that was employed to compute the probability of flood occurrence in the study area. Consequently, this paper adopted the integrated framework of GIS and RNB to spatially assess the flood susceptibility using the Wanan County in China as an instance. The results demonstrated that when integrated with the repeatedly random sampling method, the MAC-based flood susceptibility maps corresponding to different factor discretization methods were similar, meaning this framework can effectively avoid the effects caused by different factor discretization methods. Also, to testify the classification performance of RNB, RF and NB were chosen to compare the classification performance with it. The results indicated the classification performance in the order of RF > RNB > NB. This means RNB is able to achieve better classification performance than NB, but it exists limitations when compared with traditional strong classifiers like RF. The findings of this paper proved that RNB is a feasible approach for natural hazard susceptibility assessment. [ABSTRACT FROM AUTHOR]

Floods occur frequently and cause considerable damage to local environments. Effectively assessing the flood risk contributes to reducing loss caused by such disasters. In this study, the weighted naïve Bayes (WNB) method was selected to evaluate flood risk, and the entropy weight method was employed to compute the weights. A sampling and verifying model was employed to generate the most accurate conditional probability table (MACPT) to calculate the probability of flooding. When using the framework integrating WNB with the sampling and verifying model, previous studies could not obtain a WNB-based MACPT and the WNB classification accuracy, for lacking WNB functions that could be called directly. Facing this issue, in this study we developed WNB functions with the MATLAB platform to directly integrate with the sampling and verifying model to generate a WNB-based MACPT, contributing to the greater interpretability and extensibility of the model. Shantou and Jieyang cities in China were selected as the study area. The results demonstrate that: (1) a WNB-based MACPT can reflect the real spatial distribution of flood risk and (2) the WNB outperform the NB when integrated with the sampling and verifying model. The resulting gridded estimation reveal a detailed spatial pattern of flood risk, which can serve as a realistic reference for decision making related to floods. Furthermore, the proposed method uses less data, which would be helpful in developing countries where long-term intensive hydrologic monitoring is limited., (© 2021 Society for Risk Analysis.)