The objective of this study was to isolate a potent dye-degrading microbe that can be used to reduce the pollution caused by industrial dyes. Reactive red 198 is an extensively used textile dye and is a major environmental pollutant in water bodies. In this study, a bacterial strain was isolated from sea sediments and identified as Acinetobacter baumannii with 16S rRNA sequencing. The isolated bacteria were immobilized in calcium alginate and decolorization studies were carried out to determine the optimum pH, temperature, dye concentration, inoculum volume, and static/agitated condition using the one factor at a time (OFAT) approach. The Box-Behnken design, a type of response surface methodology, was adopted to improve the degradation efficiency. At 37ºC using an inoculum volume of six beads, 96.20% decolorization was observed in 500 mg/L of reactive red 198 after 72 hours. Dye degradation was confirmed with UV-visible spectroscopy and Fourier-transform infrared (FTIR) spectroscopy studies of the dye and degraded metabolites. Microbial toxicity studies using Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa and phytotoxicity studies using Vigna radiata proved that the toxicity of the dye was significantly reduced after degradation. We can conclude that the isolated Acinetobacter baumannii strain is an efficient dye-degrading microbe that can be used to reduce the pollution caused by industrial dyes.

In this study, the enclosure system exhibited perfect nitrogen removal performance with in situ oxygen-enhanced indigenous aerobic denitrifying bacteria in an enclosure experiment. We explored changes in the microbial community during the nitrogen removal process using the MiSeq high-throughput sequencing technology. The results revealed a total of 7974 and 33653 operational taxonomic units (OTUs) for water and sediment systems, respectively, with 97% similarity. The OTUs were found to be affiliated with eight main phyla (Proteobacteria, Actinobacteria, Cyanobacteria, Bacteroidetes, Planctomycetes, Chloroflexi, Firmicutes, and Actinobacteria). The diversity of the enhanced system was found to be higher than that of the control system. Principal component analysis (PCA) revealed that significant spatial and temporal differences were exhibited in the microbial community during nitrogen removal in the enclosure experiment. Redundancy analysis (RDA) indicated that physical parameters (temperature, dissolved oxygen, and pH), nitrogen (total nitrogen and nitrate), functional genes (nirK and nirS), and dissolved organic carbon (DOC) were the most important factors affecting bacterial community function and composition. Lastly, the results suggested that the variation in the microbial community could be analyzed through the MiSeq high-throughput sequencing technology, which may provide technical support for future field tests.

The 285.5 m-high Xiluodu Arch Dam is located in a seismic region along the Jinsha River in China, where the horizontal components of peak ground accelerations for design and checking earthquakes have been estimated to be 0.355g and 0.423g, respectively (g is the gravitational acceleration). The ground motion parameters of design and checking earthquakes are defined by exceedance probabilities of 2% over 100 years and 1% over 100 years, respectively. The dam shape was first selected and optimized through static analysis of the basic load combinations, and then adjusted after taking into account the seismic loads. The dam should be operational during and after the design earthquake with or without minor repairs, and maintain local and global stabilities during an extreme earthquake. Both standard linear elastic dynamic analysis and nonlinear dynamic analysis considering radiation damping, block joints, and material nonlinearity were conducted to assess the stress in the arch dam. The dynamic analysis shows that the maximum dynamic compressive stresses are less than the allowable levels, while the area with tensile stress over the limit is less than 15% of the dam surface and the maximum block openings range from 10 mm to 25 mm. The arch dam has sufficient earthquake-resistance capacity and meets the safety requirements. Nevertheless, steel reinforcement has been provided at the dam toe and in the zones of high tensile stress on the dam surface out of extra precaution.

Existing experimental results have shown that using a semi-log linear relationship between the permanent volumetric strain and cyclic number underestimates the volumetric deformation of rockfill materials with a large cyclic number, and that the error increases with the confining pressure. The existing permanent deformation models are not suitable for the seismic safety analysis of high dams during strong earthquakes. In this study, a series of large-scale triaxial cyclic loading tests of rockfill materials were performed, and a new permanent deformation model of rockfill materials was developed and validated with three kinds of rockfill materials. The results show that the proposed model can properly reflect the general features of the permanent deformation of rockfill materials. The main features of the model are as follows: (1) relations between the cyclic number and permanent volumetric/shear strain are described by hyperbolic functions, which can avoid underestimating the volumetric deformation occurring during strong earthquakes; (2) the model can capture the effect of the mean effective stress on the permanent volumetric strain, with greater confining pressure correlating to greater permanent volumetric deformation, and the permanent volumetric strain under low confining pressure near the dam crest can be well represented; and (3) the model can reflect the effect of the consolidation stress ratio on the permanent shear strain.

Many researchers have developed new calculation methods to analyze seismic slope stability problems, but the conventional pseudo-static method is still widely used in engineering design due to its simplicity. Based on the Technical Code for Building Slope Engineering (GB 50330―2013) of China and the Guidelines for Evaluating and Mitigating Seismic Hazards in California (SP117), a comparative study on the pseudo-static method was performed. The results indicate that the largest difference between these two design codes lies in determination of the seismic equivalence reduction factor (feq). The GB 50330―2013 code specifies a single value for feq of 0.25. In SP117, numerous factors, such as magnitude and distance, are considered in determining feq. Two case studies show that the types of slope stability status evaluated by SP117 are in agreement with those evaluated by the seismic time-history stability analysis and Newmark displacement analysis. The factors of safety evaluated by SP117 can be used in practice for safe design. However, the factors of safety evaluated by GB 50330―2013 are risky for slope seismic design.

Long-period waves pose a threat to coastal communities as they propagate from deep ocean to shallow coastal waters. At the coastline, such waves have a greater height and longer period in comparison with local storm waves, and can cause severe inundation and damage. In this study, we considered linear long waves in a two-dimensional (vertical-horizontal) domain propagating towards a shoreline over a shallowing shelf. New solutions to the linear shallow water equations were found, through the separation of variables, for two forms of transition shelf morphology: deep water and shallow coastal water horizontal shelves connected by linear and parabolic transition, respectively. Expressions for the transmission and reflection coefficients are presented for each case. The analytical solutions were used to test the results from a novel computational scheme, which was then applied to extending the existing results relating to the reflected and transmitted components of an incident wave. The solutions and computational package provide new tools for coastal managers to formulate improved defence and risk-mitigation strategies.

Developing regional models using physiographic, climatic, and hydrologic variables is an approach to estimating suspended load yield (SLY) in ungauged watersheds. However, using all the variables might reduce the applicability of these models. Therefore, data reduction techniques (DRTs), e.g., principal component analysis (PCA), Gamma test (GT), and stepwise regression (SR), have been used to select the most effective variables. The artificial neural network (ANN) and multiple linear regression (MLR) are also common tools for SLY modeling. We conducted this study (1) to obtain the most effective variables influencing SLY through DRTs including PCA, GT, and SR, and then, to use them as input data for ANN and MLR; and (2) to provide the best SLY models. Accordingly, we used 14 physiographic, climatic, and hydrologic parameters from 42 watersheds in the Hyrcanian forest region (in northern Iran). The most effective variables as determined through DRTs as well as the original data sets were used as the input data for ANN and MLR in order to provide an SLY model. The results indicated that the SLY models provided by ANN performed much better than the MLR models, and the GT-ANN model was the best. The determination of coefficient, relative error, root mean square error, and bias were 99.9%, 26%, 323 t/year, and 6 t/year in the calibration period, and 70%, 43%, 456 t/year, and 407 t/year in the validation period, respectively. Overall, selecting the main factors that influce SLY and using artificial intelligence tools can be useful for water resources managers to quickly determine the behavior of SLY in ungauged watersheds.

The flow pattern of supercritical flow in bend channels is complicated due to the shock wave phenomenon, which creates difficulties with regard to research and design of bend channels. Using the spillway of an actual project as an example, a three-dimensional numerical investigation was conducted to simulate the flow in a steep-slope bend based on the renormalization group (RNG) k-ε turbulence flow model and the volume of fluid (VOF) method. The validity of the numerical simulation was demonstrated by comparison between the results of numerical simulation and physical model tests. An optimal scheme of setting vertical vanes in the bend channel is presented. The results of numerical simulation and physical model tests are in agreement, which demonstrates the effectiveness of optimization of vertical vanes and the validity of the three-dimensional numerical simulation. Water depths along both bend walls were analyzed numerically and theoretically. The formula for calculating supercritical water depth along either bend wall was derived, and the critical condition of flow separation from the inner wall was determined.

Affected by external environmental factors and evolution of dam performance, dam seepage behavior shows nonlinear time-varying characteristics. In this study, to predict and evaluate the long-term development trend and short-term fluctuation of the dam seepage behavior, two monitoring models were developed, one for the base flow effect and one for daily variation of dam seepage elements. In the first model, to avoid the influence of the time lag effect on the evaluation of seepage variation with the time effect component of seepage elements, the base values of the seepage element and the reservoir water level were extracted using the wavelet multi-resolution analysis method, and the time effect component was separated by the established base flow effect monitoring model. For the development of the daily variation monitoring model for dam seepage elements, all the previous factors, of which the measured time series prior to the dam seepage element monitoring time may have certain influence on the monitored results, were considered. Those factors that were positively correlated with the analyzed seepage element were initially considered to be the support vector machine (SVM) model input factors, and then the SVM kernel function-based sensitivity analysis was performed to optimize the input factor set and establish the optimized daily variation SVM model. The efficiency and rationality of the two models were verified by case studies of the water level of two piezometric tubes buried under the slope of a concrete gravity dam. Sensitivity analysis of the optimized SVM model shows that the influences of the daily variation of the upstream reservoir water level and rainfall on the daily variation of piezometric tube water level are processes subject to normal distribution.