【摘要】：本文以太湖水域作為研究目標(biāo),采用MODIS和HJ-1A/B影像對(duì)其進(jìn)行監(jiān)測(cè)預(yù)警,監(jiān)測(cè)年份的區(qū)間段為2009年至2013年。通過(guò)太湖水域?qū)嵉夭蓸拥膶?shí)驗(yàn)數(shù)據(jù),建立正常湖泊水體、不同程度水華水體、水草區(qū)水體樣本的光譜曲線,探究正常湖泊水體與水華水體的光譜差異。利用地物光譜特征的差異選取日常水華監(jiān)測(cè)的識(shí)別模型,對(duì)太湖的藍(lán)藻水華暴發(fā)情況進(jìn)行長(zhǎng)時(shí)間監(jiān)測(cè)記錄,分別對(duì)空間分布、起始時(shí)間、暴發(fā)面積、暴發(fā)頻率、持續(xù)時(shí)間、多年演化特征等規(guī)律進(jìn)行分析。選取水溫、日照時(shí)間、風(fēng)速、降雨量四個(gè)因子,分析各氣象因子與藍(lán)藻水華暴發(fā)的關(guān)系。結(jié)合太湖的氣象數(shù)據(jù)及水質(zhì)數(shù)據(jù)建立藍(lán)藻水華預(yù)警模型,并進(jìn)行模型驗(yàn)證。研究結(jié)論如下:(1)MODIS以及HJ-1A/B數(shù)據(jù)能夠有效利用水華水體類似植被的光譜曲線特征對(duì)太湖區(qū)域的水華進(jìn)行遙感提取并且提取方法的識(shí)別準(zhǔn)確率在90%以上。(2)統(tǒng)計(jì)結(jié)果顯示,湖區(qū)水華在不同年份之間的空間分布趨勢(shì)大體一致。藍(lán)藻暴發(fā)的強(qiáng)度大體趨勢(shì)為從西南部沿岸、竺山湖、梅梁灣地區(qū)向東湖區(qū)呈遞減趨勢(shì);水華的起始時(shí)間分布呈由四周往湖心、由西部向東部的趨勢(shì)。(3)同一時(shí)刻的不同區(qū)域的水溫與葉綠素a濃度的相關(guān)性較高,與此同時(shí),太湖的平均水溫影響水華整體態(tài)勢(shì);日照時(shí)間為藍(lán)藻水華的適宜條件,夏季日照時(shí)間9h為適宜值,秋季日照時(shí)間8.69h為適宜值,冬季日照時(shí)間8.4h為適宜值;風(fēng)速的大小與藍(lán)藻的漂移擴(kuò)散有關(guān),藍(lán)藻在平均風(fēng)速約2m/s的狀態(tài)下,易發(fā)生向上漂浮和聚集過(guò)程,當(dāng)平均風(fēng)速大于4m/s時(shí)則抑制水華的形成;降雨量與水華呈現(xiàn)負(fù)相關(guān)趨勢(shì),前一天發(fā)生降雨過(guò)程會(huì)導(dǎo)致后一天的太湖水華面積相對(duì)減小。(4)太湖藍(lán)藻水華預(yù)警模型在48小時(shí)以內(nèi)的預(yù)測(cè)結(jié)果與太湖實(shí)際水華發(fā)生情況基本一致,精度滿足太湖水環(huán)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.
【學(xué)位授予單位】：中國(guó)地質(zhì)大學(xué)(北京)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：X524;X87

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