富营养化浅水湖泊藻源性湖泛的短期数值预报方法-以太湖为例
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J.LakeSci.(湖泊科学),2016,28(4):701-709DOI10.18307/2016.04022016byJournalofLakeSciences富营养化浅水湖泊藻源性湖泛的短期数值预报方法———以太湖为例*李未,秦伯强,张运林,朱广伟(中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室,南京210008)摘要:本文建立了一种富营养化浅水湖泊藻源性湖泛的短期数值预报方法.选取表征藻源性湖泛的代表性指标叶绿素a和溶解氧浓度作为预测变量,以天气预报中的风场为驱动力,求解浅水湖泊三维水动力水质耦合数值模型,计算未来3d浅水湖泊叶绿素a和溶解氧浓度的时空分布,然后结合未来3d的气象因子信息建立经验公式,计算湖泛易发水域发生湖泛的概率,并进一步确定湖泛发生位置和面积.以太湖为例,采用构建的方法于20132014年夏、秋季对太湖7段湖泛易发水域的湖泛发生概率及发生面积进行未来3d的预测预报,预报正确率在80%以上.关键词:藻源性湖泛;数值模型;短期预报;浅水湖泊;太湖Numericalforecastingofshort-termalgae-inducedblackbloomineutrophicshallowlake:AcasestudyofLakeTaihuLIWei,QINBoqiang,ZHANGYunlin&ZHUGuangwei(StateKeyLaboratoryofLakeScienceandEnvironment,NanjingInstituteofGeographyandLimnology,ChineseAcademyofSciences,Nanjing210008,P.R.China)Abstract:Inthispaper,anattempttoforecastthealgae-inducedblackbloomineutrophicshallowlakewasdocumented.Takenchlorophyll-aconcentrationanddissolvedoxygenconcentrationastherepresentativevariables,athree-dimensional,coupledhydro-dynamic-waterqualitynumericalmodelwasbuilt.Bycombiningcalculationandpredictionofthehydrologicalandmeteorologicalscenariosovertheensuing3days,thedynamicdistributionsofalgaeconcentrationanddissolvedoxygenconcentrationscenariosinLakeTaihuweresimulated.BlackBloomprobabilitieswerethenpredictedbyaforecastempiricalmodelthatincludedtheweightofalgalbiomass,dissolvedoxygenconcentration,windvelocity,andweathercondition.Iftheprobabilitieswerelargerthan50%,theareaofblackbloomshouldbecalculated.Themodelwasappliedtopredicttheoccurrencesoftheblackbloomofthenext3daysinLakeTaihufromApriltoSeptemberin2013and2014.Independentevaluationsfromboatsurveydatashowedthattheaccuracyofthesebloomforecastswasmorethan80%.Keywords:Algae-inducedblackbloom;numericalmodel;short-termforecast;shallowlake;LakeTaihu近20年来,我国长江中下游地区浅水湖泊水环境问题日趋严重,在夏、秋季由湖水富营养化引发的蓝藻水华暴发时有发生,严重影响水质景观,甚至危及供水安全.由蓝藻水华引发的“湖泛”是指湖泊富营养化水体在藻类大量暴发、积聚和死亡后,在适宜的气象、水文条件下,与底泥中的有机物在缺氧和厌氧条件下产生生化反应,释放金属类和硫醚类等硫化物,形成褐黑色伴有恶臭的“黑水团”,从而导致水体水质迅速恶化,生态系统受到严重破坏的现象[1].以太湖为例,1990s以来,太湖西部湖区、北部湖区曾多次发生湖泛[2].20092014年春、夏季,每年发生的湖泛次数分
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