Water-energy nexus has been a popular topic of rese arch in recent years. The relationships between the demand for water resources and energy are intense and closely connected in urban areas. The primary, secondary, and tertiary industry gross domestic product (GDP), the total population, the urban population, annual precipitation, agricultural and industrial water consumption, tap water supply, the total discharge of industrial wastewater, the daily sewage treatment capacity, total and domestic electricity consumption, and the consumption of coal in industrial enterprises above the designed size were chosen as input indicators. A feedforward artificial neural network model (ANN) based on a back-propagation algorithm with two hidden layers was constructed to combine urban water resources with energy demand. This model used historical data from 1991 to 2016 from Wuxi City, eastern China. Furthermore, a multiple linear regression model (MLR) was introduced for comparison with the ANN. The results show the following: (a) The mean relative error values of the forecast and historical urban water-energy demands are 1.58 % and 2.71%, respectively; (b) The predicted water-energy demand value for 2020 is 4.843 billion cubic meters and 47.561 million tons of standard coal equivalent; (c) The predicted water-energy demand value in the year 2030 is 5.887 billion cubic meters and 60.355 million tons of standard coal equivalent; (d) Compared with the MLR, the ANN performed better in fitting training data, which achieved a more satisfactory accuracy and may provide a reference for urban water-energy supply planning decisions.

To predict the effects of flood discharge atomization, a prediction method that combines physical and mathematical models is proposed. First, based on the physical modelling, splashing tests, and prototype observations we conclude that the large-scale physical models can be used to simulate the atomization when the Weber number is larger than 600. Then, based on the feedback analysis of model results and prototype data, a mathematical model is formulated. The model consists of the differential equations of the jet flow in air and accounts for the splashing of water drops as a result of the jet impact at the downstream water surface. The applicability of the proposed mathematical model is demonstrated by the verification analysis of the Ertan hydropower station. The prediction method that combines the large-scale physical model with the mathematical model is then used to quantify the atomization rainfall intensity and coverage area on the Baihetan hydropower station.

To reveal the effects of water diversion from the Yangtze River to Lake Taihu on the phytoplankton habitat of the main water transfer channel of the Wangyu River, we investigated the water’s physicochemical parameters and phytoplankton communities during the water diversion and non-diversion periods over the winters between 2014–2016, respectively. During the water diversion periods in the winter of 2014 and 2015, the nutrients and organic pollutant contents of the Wangyu River channel were significantly lower than those during the non-diversion period in 2016. Moreover, the phytoplankton diversities and relative proportions of Bacillariophyta during the diversion periods evidently increased during the water diversion periods in winter. The increase in the water turbidity content, the decrease in the contents of the permanganate index, and the total phosphorus explained only 21.4% of the variations in the phytoplankton communities between the diversion and non-diversion periods in winter, which revealed significant contributions of the allochthonous species from the Yangtze River and tributaries of the Wangyu River to phytoplankton communities in the Wangyu River. The increasing gradient in the contents of nutrients and organic pollutants from the Yangtze River to Lake Taihu indicated the potential allochthonous pollutant inputs along with the Wangyu River. Further controlling the pollutants from the tributaries of the Wangyu River is critical in order to improve the phytoplankton habitats in river channels and Lake Taihu.

Due to the impact of climate change and rapid urbanization, issues around global urban flood control and water environment security have emerged as major global concerns. As a practical way to address these issues, exploitation of urban rainwater resources has become a worldwide hotspot for research and application. This paper 1) briefly examined the evolution of rainwater utilization management modes in advanced countries, 2) classified urban rainwater utilization measures from the utilization stages into three categories—source control, medium transmission, and terminal treatment, 3) summarized the advantages, disadvantages, and scope of the application of these measures, 4) reviewed the benefits, drawbacks, and application areas of these measures, and 5) conducted a quantitative analysis of their impact on rainwater pollution and flood control.

Wind induced hydrodynamic circulations play significant roles in the transport and mixing process of pollutants and nutrients in large shallow lakes, but they have been usually overlooked, while environmental, biological, and ecological aspects of eutrophication problems get the most focus. Herein we use a three-dimensional model, driven by steady/unsteady wind, river discharge, rainfall, evaporation to investigate the spatially heterogeneous, large-scale hydrodynamic circulations and their role in transporting and mixing mechanisms in Taihu Lake. Wind direction and velocity determines the overall hydrodynamic circulation structure, i.e. direction, intensity, and position. A relative stable hydrodynamic circulation pattern has been formed shortly with steady wind (~2 days). Vertical profiles of horizontal velocities are linearly correlated to the relative shallowness of water depth. Volume exchange between subbasins, influenced by wind speed and initial water level, differs due to the complex topography and irregular shape. With unsteady wind, these findings are still valid to a high degree. Vertical variations in hydrodynamic circulation are important in explaining the surface accumulation of algae scums in Meiliang Bay in summers. Vorticity of velocity field, a key indicator of hydrodynamic circulation, is determined by wind direction, bathymetry gradient, and water depth. The maximum change of velocity vorticity happens when wind direction is perpendicular to bathymetry gradient. Furthermore, Lagrangian-based tracer transport is used to estimate emergency pollution leakage impacts, and also to evaluate operational management measurements, such as, the large-scale water transfer. The conclusion is that the large-scale water transfer does not affect the hydrodynamic circulation and volume exchanges between subbasins significantly, but succeeds to transport and then mix the fresh, clean Yangtze River water to a majority area of Taihu Lake.

Submerged vegetation changes the hydrodynamic characteristics of rivers, lakes, wetlands, and coastal zones. However, only a few studies have focused on the effect of flexible submerged vegetation on hydrodynamic characteristics under unidirectional flow. Therefore, laboratory experiments were conducted to study the effects of submerged vegetation with different flexibility on the flow structure and turbulence characteristics under unidirectional flow. The results showed that the reconfiguration and coordination of wave motion of flexible submerged vegetation redistribute flow velocity, Reynolds stress, and turbulent kinetic energy inside and outside of the vegetation canopy. With a gradual decrease in the deflection height of vegetation, the differences in dimensionless velocity, dimensionless mixed layer thickness, bulk drag coefficient, averaged turbulent kinetic energy, and the averaged contribution rate of its shear production term for the vegetation canopy also decrease; the trend of the penetration depth of Reynolds stress is opposite. Based on the turbulent kinetic energy budget equation, a turbulent kinetic energy model (TKE model) was established, which can be used to predict the turbulent kinetic energy and its shear production term within the vegetation canopy. Here, the scaling factor was determined by the vegetation canopy Cauchy number. The TKE model can be applied under unidirectional flow conditions for submerged vegetation with different flexibilities with high accuracy. It is a simple method to predict vegetation-induced turbulence and the characteristics of sediment and material transport under the influence of submerged vegetation with different flexibility.