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The angular resolution of current near-eye display devices is still far below humaneye acuity. How to achieve retina-level resolution while keeping wide field-of-view (FOV) remains a great challenge. In this work, we demonstrate a multi-resolution foveated display with two display panels and an optical combiner. The first display panel provides a wide FOV but relatively low resolution for the surrounding region, while the second one offers an ultrahigh resolution for the central fovea region, by an optical minifying system which enhances the effective resolution by 5 ×. In addition, a switchable Pancharatnam-Berry phase deflector is employed to shift the high-resolution region. The proposed design effectively reduces the pixelation and screen-door effect in near-eye displays.

Rainfall-runoff models play an important role in urban water resource management. The storm water management model (SWMM) developed by the US Environmental Protection Agency (EPA) is a widely used dynamic rainfall-runoff model for analyzing quantity and quality problems associated with urban drainage systems. In an ideal situation, the SWMM model would be designed and analyzed using a collection of catchment modeling systems. Traditionally, catchment discretization for rainfall-runoff modeling is performed manually on watershed maps, a time-consuming job with less-than-accurate results. An alternative approach to catchment discretization based on geographic information system (GIS) is proposed in this paper. The automatic discretization approach was successfully applied to rainfall-runoff modeling in Macau using a SWMM model. The results showed that the proposed approach outperformed the conventional catchmentdiscretization method in terms of producing meaningful parameters and avoiding most of the tedious preliminary tasks.

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Statistical analysis of stormwater runoff data enables general identification of runoff characteristics. Six catchments with different urban surface type including roofs, roadway, park, and residential/commercial in Macau were selected for sampling and study during the period from June 2005 to September 2006. Based on univariate statistical analysis of data sampled, major pollutants discharged from different urban surface type were identified. As for iron roof runoff, Zn is the most significant pollutant. The major pollutants from urban roadway runoff are TSS and COD. Stormwater runoff from commercial/residential and Park catchments show high level of COD, TN, and TP concentration. Principal component analysis was further done for identification of linkages between stormwater quality and urban surface types. Two potential pollution sources were identified for study catchments with different urban surface types. The first one is referred as nutrients losses, soil losses and organic pollutants discharges, the second is related to heavy metals losses. PCA was proved to be a viable tool to explain the type of pollution sources and its mechanism for different urban surface type catchments.

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