太湖蓝藻水华的遥感监测预警研究
发布时间：2019-05-24 01:36
【摘要】：本文以太湖水域作为研究目标,采用MODIS和HJ-1A/B影像对其进行监测预警,监测年份的区间段为2009年至2013年。通过太湖水域实地采样的实验数据,建立正常湖泊水体、不同程度水华水体、水草区水体样本的光谱曲线,探究正常湖泊水体与水华水体的光谱差异。利用地物光谱特征的差异选取日常水华监测的识别模型,对太湖的蓝藻水华暴发情况进行长时间监测记录,分别对空间分布、起始时间、暴发面积、暴发频率、持续时间、多年演化特征等规律进行分析。选取水温、日照时间、风速、降雨量四个因子,分析各气象因子与蓝藻水华暴发的关系。结合太湖的气象数据及水质数据建立蓝藻水华预警模型,并进行模型验证。研究结论如下:(1)MODIS以及HJ-1A/B数据能够有效利用水华水体类似植被的光谱曲线特征对太湖区域的水华进行遥感提取并且提取方法的识别准确率在90%以上。(2)统计结果显示,湖区水华在不同年份之间的空间分布趋势大体一致。蓝藻暴发的强度大体趋势为从西南部沿岸、竺山湖、梅梁湾地区向东湖区呈递减趋势;水华的起始时间分布呈由四周往湖心、由西部向东部的趋势。(3)同一时刻的不同区域的水温与叶绿素a浓度的相关性较高,与此同时,太湖的平均水温影响水华整体态势;日照时间为蓝藻水华的适宜条件,夏季日照时间9h为适宜值,秋季日照时间8.69h为适宜值,冬季日照时间8.4h为适宜值;风速的大小与蓝藻的漂移扩散有关,蓝藻在平均风速约2m/s的状态下,易发生向上漂浮和聚集过程,当平均风速大于4m/s时则抑制水华的形成;降雨量与水华呈现负相关趋势,前一天发生降雨过程会导致后一天的太湖水华面积相对减小。(4)太湖蓝藻水华预警模型在48小时以内的预测结果与太湖实际水华发生情况基本一致,精度满足太湖水环境污染防治的要求。
[Abstract]:In this paper, Taihu Lake waters are taken as the research goal, and MODIS and HJ-1A/B images are used to monitor and warn them. The interval of the monitoring year is from 2009 to 2013. Based on the experimental data of field sampling in Taihu Lake, the spectral curves of normal lake water body, Shui Hua water body and water grass area were established, and the spectral difference between normal lake water body and Shui Hua water body was explored. Based on the difference of spectral characteristics of ground objects, the identification model of daily Shui Hua monitoring was selected to monitor and record the outbreak of blue algae Shui Hua in Taihu Lake for a long time, and the spatial distribution, initial time, outbreak area, outbreak frequency and duration were recorded respectively. The characteristics of evolution for many years are analyzed. Four factors, water temperature, sunshine time, wind speed and rainfall, were selected to analyze the relationship between each meteorological factor and the outbreak of blue algae Shui Hua. Based on the meteorological data and water quality data of Taihu Lake, the early warning model of cyanobacteria Shui Hua was established and verified. The conclusions are as follows: (1) MODIS and HJ-1A/B data can effectively use the spectral curve characteristics of Shui Hua water body similar to vegetation to extract Shui Hua from Taihu Lake area by remote sensing, and the recognition accuracy of the extraction method is 90%. (2) the statistical results show that, The spatial distribution trend of Shui Hua in lake area is basically the same among different years. The intensity of blue algae outbreaks decreased from the southwest coast, Zhushan Lake and Meiliang Bay area to the East Lake area. The initial time distribution of Shui Hua is from all around to the center of the lake and from the west to the east. (3) the correlation between water temperature and chlorophyll a concentration is high in different regions at the same time. At the same time, the average water temperature of Taihu Lake affects the overall situation of Shui Hua; The sunshine time was the suitable condition for blue algae Shui Hua, the summer sunshine time was 9 h, the autumn sunshine time was 8.69 h, and the winter sunshine time was 8.4 h. The size of wind speed is related to the drift and diffusion of blue algae. When the average wind speed is about 2m/s, the process of upward floating and accumulation is easy to occur, and when the average wind speed is greater than 4m/s, the formation of Shui Hua is restrained. There is a negative correlation between rainfall and Shui Hua. The rainfall process the day before yesterday will lead to the relative decrease of Shui Hua area in Taihu Lake the following day. (4) the prediction results of Shui Hua early warning model of Taihu Lake within 48 hours are basically consistent with the actual Shui Hua occurrence in Taihu Lake. The accuracy meets the requirements of water environmental pollution prevention and control in Taihu Lake.
【学位授予单位】：中国地质大学(北京)
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X524;X87
本文编号：2484433
[Abstract]:In this paper, Taihu Lake waters are taken as the research goal, and MODIS and HJ-1A/B images are used to monitor and warn them. The interval of the monitoring year is from 2009 to 2013. Based on the experimental data of field sampling in Taihu Lake, the spectral curves of normal lake water body, Shui Hua water body and water grass area were established, and the spectral difference between normal lake water body and Shui Hua water body was explored. Based on the difference of spectral characteristics of ground objects, the identification model of daily Shui Hua monitoring was selected to monitor and record the outbreak of blue algae Shui Hua in Taihu Lake for a long time, and the spatial distribution, initial time, outbreak area, outbreak frequency and duration were recorded respectively. The characteristics of evolution for many years are analyzed. Four factors, water temperature, sunshine time, wind speed and rainfall, were selected to analyze the relationship between each meteorological factor and the outbreak of blue algae Shui Hua. Based on the meteorological data and water quality data of Taihu Lake, the early warning model of cyanobacteria Shui Hua was established and verified. The conclusions are as follows: (1) MODIS and HJ-1A/B data can effectively use the spectral curve characteristics of Shui Hua water body similar to vegetation to extract Shui Hua from Taihu Lake area by remote sensing, and the recognition accuracy of the extraction method is 90%. (2) the statistical results show that, The spatial distribution trend of Shui Hua in lake area is basically the same among different years. The intensity of blue algae outbreaks decreased from the southwest coast, Zhushan Lake and Meiliang Bay area to the East Lake area. The initial time distribution of Shui Hua is from all around to the center of the lake and from the west to the east. (3) the correlation between water temperature and chlorophyll a concentration is high in different regions at the same time. At the same time, the average water temperature of Taihu Lake affects the overall situation of Shui Hua; The sunshine time was the suitable condition for blue algae Shui Hua, the summer sunshine time was 9 h, the autumn sunshine time was 8.69 h, and the winter sunshine time was 8.4 h. The size of wind speed is related to the drift and diffusion of blue algae. When the average wind speed is about 2m/s, the process of upward floating and accumulation is easy to occur, and when the average wind speed is greater than 4m/s, the formation of Shui Hua is restrained. There is a negative correlation between rainfall and Shui Hua. The rainfall process the day before yesterday will lead to the relative decrease of Shui Hua area in Taihu Lake the following day. (4) the prediction results of Shui Hua early warning model of Taihu Lake within 48 hours are basically consistent with the actual Shui Hua occurrence in Taihu Lake. The accuracy meets the requirements of water environmental pollution prevention and control in Taihu Lake.
【学位授予单位】：中国地质大学(北京)
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X524;X87
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