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基于MIKE21和灰色模式识别模型的洪湖水质模拟与评价 被引量:12

Application of the MIKE21 and Grey-Mode Identification Model to Monitor and Assess Water Quality for Honghu Lake
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摘要 认识自然和人为因素驱动下湖泊水环境质量的响应和变化规律,有利于更精确地进行湖泊水质模拟和评价。运用二维水质模型和灰色模式识别模型评价了不同污染源削减方案对洪湖水质的影响。基于2012年实测地形、水文、气象、水质和污染源定量输入,建立了洪湖二维水动力和水质耦合模型。模拟结果显示:水位率定和验证的均方根误差分别为0. 10和0. 08 m,总氮、总磷、铵态氮和高锰酸盐指数的率定误差分别为0. 171、0. 009、0. 110和0. 627 mg/L,验证误差分别为0. 191、0. 020、0. 079和0. 689 mg/L,水动力模型和水质模型的模拟结果满足精度要求。不同管理措施方案下洪湖水质的恢复效果比较显示,洪湖蓝田和下新河入水口各污染物指标浓度减少50%方案下,水质的恢复效果最好,全湖总氮、总磷、铵态氮和高锰酸盐指数均值减少率分别为37. 2%、35. 1%、37. 3%和21. 3%,全湖Ⅴ类水质水域基本不存在,全湖90%的区域水体水质综合等级达到Ⅲ类。影响洪湖水质恶化的驱动因子中,关键因素是径流入湖所携带的四湖流域上游地区的非点源污染物。应大力控制上游地区的非点源污染,积极开展洪湖东北部和西北部的湿地水生植被生态修复工程,恢复水体的截污和自净能力。 Studying the change and response of lake water quality driven by natural and human factors can provide a scientific basis for water environmental management. This study accessed the effects of different scenarios of pollutions reduction on water quality using the combination methods of two-dimension water quality numerical modelling and grey-mode identification accessing. Based on measured topography, hydrological,meteorological data and water quality in 2012,as well as the quantitative results of pollution resources,a twodimensional hydrodynamic and water quality coupling model of Honghu Lake was established. The pollution resources were generalized to surface runoff, aquaculture activities and atmospheric deposition. The results showed that, during the model calibration and validation periods, the average water level RMSEs were respectively 0. 10 m and 0. 08 m,the concentration RMSEs of total nitrogen,total phosphorus,ammonia-nitrogen and permanganate index were respectively 0. 171 mg/L,0. 009 mg/L,0. 110 mg/L,0. 627 mg/L and 0. 191 mg/L,0. 020 mg/L,0. 079 mg/L,0. 689 mg/L. The simulation results meet the accuracy requirements of water quality model. The water quality change under different scenarios of load reduction revealed that under 50%reduction of inflow loads, the decreasing rates of total nitrogen, total phosphorus, ammonia-nitrogen and permanganate index concentration were largest,which were respectively 37. 2%,35. 1%,37. 3% and 37. 2%.The comprehensive water quality index were decreased from the baseline( 2. 84) to 2. 44. The areas of grade V water quality did not exist. The percentage in areas of grade IV water quality decreased from 15%( baseline) to 10%. The areas of grade III water quality accounted for 90% of the whole lake area. it concluded that the water quality deterioration primarily was owing to non-point pollution from upstream Sihu watershed brought by runoff.We should vigorously develop non-point source pollution control in the upstream and carry out the ecological restoration in the northeast and northwest of Honghu Lake.
作者 张婷 王学雷 耿军军 班璇 杨超 吕晓蓉 ZHANG Ting;WANG Xue-lei;GENG Jun-jun;BAN Xuan;YANG Chao;LU Xiao-rong(Hubei University of Science and Technology,School of Resources Environmental Science and Engineering,Xianning 437100,China;Institute of Geodesy and Geophysics,Chinese Academy of Sciences,Hubei Key Laboratory of Environment and Disaster Monitoring and Evaluation,Wuhan 430077,China;Wuhan University,School of Resource and Environmental Sciences,Wuhan 430072,China)
出处 《长江流域资源与环境》 CAS CSSCI CSCD 北大核心 2018年第9期2090-2100,共11页 Resources and Environment in the Yangtze Basin
基金 湖北省自然科学基金(2017CFB317) 湖北科技学院博士启动基金(2016-19XB005)
关键词 水质模拟 MIKE 21 灰色模式识别模型 水质评价 洪湖 water quality simulation MIKE21 Grey-mode identification model water quality assessment Honghu Lake
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