Abstract. Under the background of global climate change and local anthropogenic activities, multiple driving forces have introduced various nonstationary components into lowflow series. This has led to a high demand on low-flow frequency analysis that considers nonstationary conditions for modeling. In this study, through a nonstationary frequency analysis framework with the generalized linear model (GLM) to consider time-varying distribution parameters, the multiple explanatory variables were incorporated to explain the variation in low-flow distribution parameters. These variables are comprised of the three indices of human activities (HAs; i.e., population, POP; irrigation area, IAR; and gross domestic product, GDP) and the eight measuring indices of the climate and catchment conditions (i.e., total precipitation P , mean frequency of precipitation events λ, temperature T , potential evapotranspiration (EP), climate aridity index AI EP , base-flow index (BFI), recession constant K and the recession-related aridity index AI K ). This framework was applied to model the annual minimum flow series of both Huaxian and Xianyang gauging stations in the Weihe River, China (also known as the Wei He River). The results from stepwise regression for the optimal explanatory variables show that the variables related to irrigation, recession, temperature and precipitation play an important role in modeling. Specifically, analysis of annual minimum 30-day flow in Huaxian shows that the nonstationary distribution model with any one of all explanatory variables is better than the one without explanatory variables, the nonstationary gamma distribution model with four optimal variables is the best model and AI K is of the highest relative importance among these four variables, followed by IAR, BFI and AI EP . We conclude that the incorporation of multiple indices related to low-flow generation permits tracing various driving forces. The established link in nonstationary analysis will be beneficial to analyze future occurrences of low-flow extremes in similar areas.
The femtosecond laser micromachining of transparent optical materials offers a powerful and feasible solution to fabricate versatile photonic components towards diverse applications. In this work, we report on a new design and fabrication of ridge waveguides in LiNbO3 crystal operating at the mid-infrared (MIR) band by all-femtosecond-laser microfabrication. The ridges consist of laser-ablated sidewalls and laser-written bottom low-index cladding tracks, which are constructed for horizontal and longitudinal light confinement, respectively. The ridge waveguides are found to support good guidance at wavelength of 4 μm. By applying this configuration, Y-branch waveguiding structures (1 × 2 beam splitters) have been produced, which reach splitting ratios of ∼1:1 at 4 μm. This work paves a simple and feasible way to construct novel ridge waveguide devices in dielectrics through all-femtosecond-laser micro-processing.
The design of stormwater drainage infrastructure in urban areas in China is based on the statistical stationary assumption of probability distribution of extreme rainfall, which is being increasingly challenged by climate change. However, quantitative assessment of the performance of urban drainage systems in response to climate change with the latest emission scenarios of the Coupled Model Intercomparison Project Phase 5 in China is quite limited. This study aims to investigate potential changes of extreme rainfall and their influence on drainage infrastructure in a representative urban area in Wuhan city, China. The Storm Water Management Model is established to investigate the response of drainage infrastructure to future design rainfall. It is found that the probability distribution of extreme rainfall for two historical sub‐periods (1961–1985 and 1986–2005) has changed, especially in the head and tail of the frequency curves. Furthermore, the design rainfall with return periods of 2, 3, 4 and 5 years increases more significantly than those of 10 and 20 years. Consequently, the incapability of the current drainage infrastructure in the study area is aggravated. Moreover, the results of SWMM modelling provide detailed information about the performance of current drainage infrastructure, which can provide technical support for future modifications of the current drainage infrastructure of the study area. © 2018 John Wiley & Sons, Ltd.
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