Long-term spatiotemporal variation analysis and probability prediction of algal blooms in Lake Chaohu (2009-2018) based on multi-source remote sensing data
نویسندگان
چکیده
湖泊富营养化导致的水华问题严重影响了淡水资源的利用和保护，快速、全面、准确的监测水华信息对于湖泊水环境的治理具有十分重要的意义.本文以巢湖为研究区域，利用多源光学遥感影像和时空融合技术，采用波段融合的方式将NDVI指数波段加入到遥感影像当中，并通过监督分类解译水华信息，以此揭示2009-2018年10年间巢湖水华的时空变化规律.结果表明：巢湖发生的水华以零星和局部水华为主，2012年巢湖水体首次出现区域蓝藻水华；巢湖水华的季节变化性强，夏、冬半年水华变化差异大，其中2018年季节间的差异最为显著；巢湖水华后五年发生频率明显高于前五年，西半湖水华较东半湖严重，且巢湖西北部是水华的高发区域，2011年水华开始向沿岸蔓延，2014年水华首次出现在西南湖区，2016年巢湖水华高发区域新增巢湖东部和中部地区.另外，本文根据巢湖的相关气象数据，构建了Logistic水华气象风险概率预测模型，模型平均预测准确率高达87.52%.探究巢湖水华长时序的时空变化规律有助于从宏观上把握其动态趋势，为后续湖区治理以及周边生态环境建设提供理论依据，水华气象风险概率预测模型可为巢湖水华的预警和防控提供决策支持.;The algal blooms problem caused by eutrophication of lakes has seriously affected the utilization and protection freshwater resources, hence rapid, comprehensive accurate monitoring information is great significance for governance water environment. Taking Lake Chaohu as research area, this article uses multi-source optical remote sensing images spatio-temporal fusion technology to reveal change trends from year 2009 2018, employing band method supervised classification-based extraction method. The results show that:The in are mainly sporadic localized. In 2012, regional cyanobacteria appeared first time. Algal a strong seasonal variation, there big difference between summer winter which most significant 2018; last five years, occurrence frequency was significantly higher than that previous years. west half lake were more serious east blooms, northwest part had high incidence blooms. 2011, began spread coast; 2014, southwest area; 2016, eastern central parts became high-occurrence area. Besides, based on relevant meteorological data Chaohu, paper constructs Logistic forecast model risk probability with an average prediction accuracy rate 87.52%. study variation can help us grasp its dynamic trend macro perspective, providing theoretical basis subsequent area ecological environment construction. provide decision support early warning prevention Chaohu's
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ژورنال
عنوان ژورنال: Journal of Lake Sciences
سال: 2021
ISSN: ['1003-5427']
DOI: https://doi.org/10.18307/2021.0204