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In recent decades, increasing frequency and intensity of saltwater intrusion in the Modaomen Channel has threatened the freshwater supply in the surrounding cities of the Pearl River Estuary, and ulteriorly changed the environmental conditions of the estuarine waters. Phytoplankton biomass, primary production (PP) and species composition, as well as hydrological and chemical parameters were examined along a downstream transect in the Modaomen Channel during neap tide (NT) and spring tide (ST), when a strong saltwater intrusion event occurred in late September, 2011. A total of 46 species phytoplankton were identified, including Bacillariophyta (25 species), Dinoflagellate (14 species), Chlorophyta (4 species), Cyanophyta (2 species) and Euglenozoa (1 species). The dominant species were shifted from freshwater diatoms (e.g., Melosira granulata and Melosira granulata var. angustissima) in the upper reaches to saline water diatoms (e.g., Skeletonema costatum and Coscinodiscus sp.) in the river mouth. Generally, phytoplankton density, biomass (chl-a) and PP decreased from the upper to lower reaches along the channel, and were significantly higher in NT than those of ST. There was a shift from large-sized phytoplankton (>20 μm) in the upper reaches to relative small-sized cells (5-20 μm) in the lower reaches. Compared to NT, low discharge and flow velocity, coupled with strong easterly winds during ST specially aggravated saltwater intrusion further to the upstream (~50 km from the estuary). The intruded saltwater diluted nutrients, N/P ratios, chl-a, and phytoplankton abundances, and thereby led to a decline in PP during ST.

In a vehicular ad hoc network (VANET), the periodic exchange of single-hop status information broadcasts (beacon frames) produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network.