浅水湖泊水生植被恢复判别模型研究与应用

    Aquatic Macrophyte Restoration Differentiation Model and Application on Shallow Lakes

    • 摘要: 基于水生植物生长影响因子特征,综合考虑光照、营养盐、悬浮物、水动力、温度及底质等因素,初步提出了野外条件下水生植物恢复判别函数;通过对野外环境主要生境因子的耦合数值仿真,首次建立了基于投影寻踪原理的水生植物恢复判别模型;以苦草做为恢复目标种,选择长江中下游地区典型浅水湖泊——高淳固城湖为例,对模型进行了应用,结果表明:固城湖现状生境条件下,可能恢复苦草的水域面积约3.25 km2,占湖泊总面积的10.5%,其中北部湖区与湖心区恢复面积较大,南部湖区也有局部水域适合苦草恢复重建,但面积较小,约0.65 km2.

       

      Abstract: Based on the analysis of the environmental factors involved in the growth of aquatic macrophyte,the differentiation function for aquatic macrophyte restoration under field conditions is proposed,which considers the intergrated impacts of various environmental factors including the underwater light,nutrients,suspended sediment,water current,temperature,and deposited sediment.Through the numerical simulation of different influencing factors,an aquatic macrophyte restoration differentiation model (AMRDM) is established based on the projection pursuit theory.The model is applied to study on the restoration area of Vallisneria gigantean L. in Gucheng Lake,located in the middle and lower reaches of Yangtze River.Under the present living condition in Gucheng Lake,the restoration area of Vallisneria gigantean L. is found to reach 3.25 km2 approximately,which takes account for 10.5% of the total water surface area.Most of the restoration areas are concentrated in the north and the middle parts,and the restoration area in the south part,which is about 0.65 km2,is relatively small.

       

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