Liu Rui-qiu

Dynamics of main nutrient input to Xiangxi Bay of the Three-Gorges Reservoir

Abstract Based on routine monitoring data in Xiangxi River and its main tributary Gaolan River from September 2000 to June 2005, this paper estimates the contribution of riverine nutrients, and analyzes the monthly dynamics of concentrations and fluxes of nutrients. The results show that Xiangxi Bay annually receives 1623.49 tons of total nitrogen (TN) and 331.85 tons of total phosphorus; Xiangxi River alone accounts for 68.50% of the total nitrogen fluxes and 91.74% of the total phosphorus fluxes. In these two rivers, dissolved inorganic nitrogen (DIN) is the dominating form of nitrogen; fluxes of DIN and TN are high during summer (July), mid-spring and autumn, and relatively low in winter; non-point source pollutants that flow into rivers are the most important pathway of nitrogen. Orthophosphate is the dominating form of phosphorus in Xiangxi River, relatively low in Gaolan River; fluxes of phosphorus are high during summer and late spring, relatively low during winter and late autumn in Gaolan River, but fluctuate irregularly in Xiangxi River; phosphorus in Gaolan River is mainly caused by non-point source pollutants, while point source pollutants of phosphorus play an important role in Xiangxi River. Soil erosion probably represents the major way of non-point source pollutants, while the drainages of phosphorus diggings and factory discharges play the most important role in the point source pollutants of phosphorus. This research suggests that measures must be taken to control the point source pollutants of phosphorus in Xiangxi River in order to protect Xiangxi Bay of the Three-Gorges Reservoir.

Spacial distributional pattern of macrozoobenthos and pollution evaluation in East Lake Dongting Reserve

Investigation of macrozoobenthos was carried out in East Lake Dongting Reserves in September, 2001. All total, 51 taxa were identified from thirty-two sampling sites, of which, 48 oligchaetes, 15 mollusks, 14 insects and 4 other forms. Mollusks constituted the most dominant group and accounted for more than 70% of the total abundance. Among which, four gastropods, Alocinma longicornis, Bellamya aeraginosa, Parafossarulus sinensis, P. striatulus and one oligochaete Branchiura sowerbyi were the dominant species. The richness and three biodiversity index values ((Margalef, Simpson and Shannon) per site were 6.3, 1.38, 4.05 and 1.47, respectively. Assemblages were composed mainly of scrapers (66.7%) and collector-gatherers (19.9%). and to a lesser extent to other functional feeding groups.The investigation data were compiled and a GIS database of macrozoobenthos was established. A vector boundary map of the lake was digitized and georeferenced, then used to introduce sampling sites. Under the support of GIS software Areview 3.2 and the relative extension modules (Spatial Analyst Extension 2.0 and Kringing Interpolator Extension 3.22 SA), the GIS database was employed to simulate spacial distribution patterns of parameters of macrozoobenthos and Hilsenhoff biotic index (BI). The simulation process was based on the principle of Kringing interpolation technique. The simulated results were stored as Areview Grid format with a grid precision of 20 m. The higher distributional pattern of main groups and five dominated species were overlapped based on the 2-4 times as mean abundance, and the 16 physical-chemical parameters were collected in these higher distributional regions.The simulated patterns of macrozoobenthos showed that these patterns were relatively high spatial heterogeneity, and distributions of most parameters of macrozoobenthos had usually 2-4 high value distributed zones in the whole lake. The oligochaete pattern showed basically no overlapping with two other groups, and mainly distributed in deeper region. ANOVA detected water depth was the key factor influencing the distribution patterns of macrozoobenthos, and SO42- mainly controlling the pattern of oligochaete, and hardness the maim factor affecting mollusks. The average of BI (8.18) revealed the Reserves endured higher organic pollution.