@article { ISI:000354901900010,
	title = {Classification of estuaries in China based on eutrophication susceptibility to nutrient load},
	journal = {SCIENCE CHINA-EARTH SCIENCES},
	volume = {58},
	number = {6},
	year = {2015},
	month = {JUN},
	pages = {949-961},
	abstract = {Recently, environmental pressures along coasts have increased substantially. Classification of estuaries according to their susceptibility to eutrophication nutrient load is a useful method to determine priority management objects and to enforce control measures. Using historical monitoring data from 2007 to 2012, from 65 estuaries, including 101 estuarine monitoring sections and 260 coastal monitoring stations, a nutrient-driven phytoplankton dynamic model was developed based on the relationship among phytoplankton biomass, Total Nitrogen (TN) load and physical features of estuaries. The ecological filter effect of estuaries was quantified by introducing conversion efficiency parameter values into the model. Markov Chain Monte Carlo algorithm of Bayesian inference was then employed to estimate parameters in the model. The developed model fitted well to the observed chlorophyll, primary production, grazing, and sinking rates. The analysis suggests that an estuary with Q/V (the ratio of river flow to estuarine volume) greater than 2.0 per year and E > (conversion efficiency ratio) less than 1.0 g C/g N can be classified as less susceptible to TN load, Q/V between 0.7 to 2.0 per year and E > between 1.0 to 3.0 g C/g N as moderately susceptible, and E > greater than 3.0 g C/g N as very susceptible. The estuaries with Q/V less than 0.7 per year vary greatly in their susceptibility. The estuaries with high and moderate susceptibility accounted for 67\% of all the analyzed estuaries. They have relatively high eutrophication risks and should be the focus of environmental supervision and pollution prevention.},
	issn = {1674-7313},
	doi = {10.1007/s11430-014-5030-1},
	author = {Li JunLong and Zheng BingHui and Liu Yong and Wu Zhen and Liu Fang and Shao JunBo and Hu XuPeng}
}
