【作者】 李兴；

【导师】 李畅游；

【作者基本信息】 内蒙古农业大学 ， 农业水土工程， 2009， 博士

【摘要】 湖泊富营养化是当今国际上重大的水环境问题之一,已给湖泊水环境以及湖泊流域人们的生产生活造成了十分严重的危害。湖泊水环境是一个受多种不确定性因素限制、参数众多、机理十分复杂的系统,加之,湖泊水动力学方程的非线性性质,很难得出理论分析解。随着数值计算方法和数值模式的快速发展,计算机性能的不断提高,数值模拟在水环境科学中得到越来越广泛的研究和应用,已成为研究湖泊、河流、水库、港口等不同水域流场与水质的重要手段之一。本文以地处寒旱区的内蒙古乌梁素海为研究对象,针对其水浅、草多、藻多、同时又是河套灌区污水承泄体的特殊情况,首先选用灰色―随机风险率方法对入湖水质浓度风险性进行了分析和计算;其次应用地质统计学理论和ArcGIS软件的地统计分析模块对不同水质参数的时空分布特征及变化规律做了分析研究;最后,在深入理解乌梁素海污染成因及污染机理的基础上,选用EFDC模型和CE-QUAL-ICM模型联合模拟了乌梁素海流场和水质变化过程,得出了以下主要结论:⑴针对湖泊水环境受随机和灰色双重不确定性因素的影响,将灰色-随机风险率理论引入到湖泊水质分析中,对乌梁素海入湖断面有机污染超标风险率和各水质浓度超标的灰色概率区间进行了计算,并绘制了水质参数超过不同浓度值的风险率曲线。结果表明:乌梁素海入湖水质断面遭受着严重的富营养化污染和有机污染;灰色-随机风险率方法能够直观地反映出在不同水质浓度控制标准下,水质参数污染强度和污染历时的变异过程,对控制乌梁素海入湖水质浓度并合理制定富营养化治理措施具有一定的参考价值。⑵为揭示不同水质参数在乌梁素海的时空分布特征及变化规律,应用地质统计学理论和ArcGIS软件的地统计模块对乌梁素海水质参数进行了kriging空间插值。结果表明:受水生植物不同生长阶段、非冰冻期和冰冻期等因素的影响,乌梁素海水质参数呈现出不同的时空变异特征;乌梁素海湖区水体受富营养化污染、有机污染、盐化污染都十分严重。⑶针对乌梁素海生态系统中水体富营养化的现状和特征,选用EFDC模型和CE-QUAL-ICM模型联合模拟乌梁素海流场和水质。CE-QUAL-ICM模型以浮游植物生长动力学为主线,不仅考虑了不同形态营养盐的循环转化过程,还考虑了蓝藻、硅藻和绿藻的生长动力、新陈代谢、被捕食、沉降等过程,并且模拟了以上两方面的循环转换过程。⑷应用所建水动力富营养化模型,模拟乌梁素海水动力及水质变化情况,误差分析表明模拟结果与实测值拟合较好,误差基本在30%以内。模型不仅考虑了风速、蒸发、辐射等气象因素,更为重要的是考虑了水生植物的分布情况以及它们的密度、高度、直径等形态指标,结果表明:考虑水生植物分布的水质浓度模拟值与实测值变化趋势基本一致,未考虑水生植物分布的模拟值未能较好地反映实测值的变化趋势,可见,湖泊水生植物的分布情况对水质指标影响较大。⑸为进一步确定乌梁素海污染的主要原因,本文应用已建富营养化模型,锁定其它条件,改变模型边界条件(入湖水质浓度)进行模拟计算,结果表明:入湖水质浓度按Ⅴ类标准控制后,其模拟值较实际情况波动小,稳定性好;除溶解氧外,入湖水质浓度按Ⅴ类标准控制后的模拟值均小于实际情况模拟值,且后期模拟结果显示水质浓度降幅较大;富营养化主控因子氮磷浓度在整个模拟时段内降幅均较大,可见,入湖污染物质浓度的变化对湖区内污染物质浓度的变化影响显著,且模拟后期更为明显。因此,控制乌梁素海入湖污染负荷对治理和改善乌梁素海水质具有重要的意义。更多还原

【Abstract】 As one of the main global water environmental problems, Lake Eutrophication has been caused serious negative effects for biodiversity, wetland utilization, and human activities. Lake water environment is a well known complex system which is varied with so many related factors with complicated biological and chemical reaction mechanisms that usually deed to be getting better understanding through numerical modeling. There would hardly be able to obtain analytical solutions for the numerical models due to uncertainty parameters and nonlinear differential expressions. However, the latest development of IT technology could help to get numerical solutions for the water environment related models.Grey-Stochastic risk method was employed for environment risk analysis in Lake Wulangsuhai, which is located in a cold-dry region in Inner Mongolia. The lake has an average depth of about 1.5m with wide range species of aquatic plants and algae. It also acts as the receiver of agricultural drainage and sewage water collected from all over Hetao Irrigation District. Coupled Environmental Fluid Dynamics Code (EFDC) and CE-QUAL-ICM model were applied to analyze the concentration distribution and degradation processes of eutrophic contaminants, during which Geology statistics and ArcGIS were used to analyze the temporal and spatial distribution characteristics and variations of the parameters. The results could be concluded as:(1) Grey-Stochastic risk method could be used to get more accurate explanations on environment risk analysis for Lake Wulangsuhai as the lake water environment is influenced by both random and gray variables. The results shown that the area dear to the inlet is the heaviest polluted area in terms of both eutrophication and organic pollution. This method can better simulate the variation processes of eutrophication and sensitivity of the parameters under different concentrations of contaminants.(2) In order to get better understanding on the characteristics of parameters’temporal and spatial distribution and variation, geology statistics and ArcGIS were used to interpolate data based on the observed data. The results suggested that the parameters shown different variation characteristics within different growing periods of aquatic plants especially when the water body was covered by ice. (3) Water flow field and transport processes were simulated by using coupled EFDC and CE-QUAL-ICM. The use of CE-QUAL-ICM could involve the effects of phytoplankton such as its growing dynamics, metabolism, preyed, and receipted processes. It could also consider the effects of circulation and conversation processes between the species of nutrient salts.(4) Hydrodynamic eutrophication model was built and the errors were less than 30% between the modeled and observed data. It should be mentioned that the model involved the effects of as many as affected factors like meteorological factors (wind speed, evaporation, radiation) and aquatic plants factors (spatial distribution, density, height, diameter).(5) The major factors of eutrophication were modeled by means of only varying the inlet concentrations of eutrophic elements. The results shown that the water quality within the lake varied significantly with the change of the inlet concentrations of eutrophic elements. It implies that the degradation capability of the lake is far from the input load of eutrophic contaminants.更多还原