湖泊水质模型SALMO在太湖梅梁湾的应用

改进了湖泊水质模型SALMO,针对太湖梅梁湾,利用2005年实测数据进行模型参数率定,并模拟了2006年水质.结果发现,绿藻、蓝藻、硅藻3种藻类的模拟结果与藻类的实测年变化格局一致,反应了3种藻类的季节性演替,其中,硅藻、绿藻在冬末春初占优势,蓝藻在夏秋季占优势;溶解氧模拟结果与实测数据非常一致,年平均相对误差为14.3%;NO-3-N和PO3-4-P的变化趋势与实测结果基本一致.研究结果表明,SALMO能很好地模拟藻类和营养盐的浓度动态,并在一定程度上揭示水华机制.

Application of lake model SALMO to the Meiliang Bay of Taihu Lake

The lake model SALMO (Simulation by Means of an Analytical Lake Model) was applied to simulate the water quality of the Meiliang Bay in Taihu Lake. The model includes 8 state variables: nitrate nitrogen, phosphate phosphorus, detritus, dissolved oxygen, biomass of three algae (Cyanophyta, Chlorophyta and Bacillariophyta) and zooplankton. Because SALMO was originally developed for non-shallow lakes (maximum depth>5 m), some improvements were made to SALMO before simulating the shallow Meiliang Bay. The data from the year 2005 were used for model calibration and the data from the year 2006 were used for model verification. The results showed that the modeled biomass of the three algae followed the observed seasonal patterns: Bacillariophyta and Chlorophyta were dominant from the end of winter to the beginning of spring, while Cyanophyta was dominant in summer and autumn. The modeled nutrient concentrations also showed a good agreement with the observations. This indicates that after improvement SALMO is applicable for Taihu Lake and can be used to study the mechanisms of algae bloom.