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咸海湖盆盐/沙尘变化过程及其影响因素遥感研究
沈浩
Subtype博士
Thesis Advisor吉力力·阿不都外力
2018-06-05
Degree Grantor中国科学院大学
Place of Conferral新疆乌鲁木齐
Degree Discipline理学博士
Keyword盐/沙尘暴 土地覆被变化 沙尘监测指数 风蚀风险 咸海湖盆 Salt/dust storms Land surface dynamics Dust index Risk of deflation Aral Sea lake basin
Abstract咸海作为亚洲中部干旱区为数不多的超大型内陆湖泊之一,其生态功能在区域尺度上的重要性不言而喻。自上世纪 60 年代开始,在流域大规模开展灌溉农业生产以及气候变化的综合作用下,咸海水域发生灾难性萎缩,大面积湖床干涸暴露于地表,形成富含盐分的新型荒漠。这片荒漠由于积累了巨厚的湖相或海相沉积物,在强物理风化作用下,干裂破碎形成松散颗粒物质,受地带性强风的频繁侵蚀,极易形成裹挟大量盐类物质的沙尘暴,对咸海区域的生态安全和周边居民的生理健康构成巨大威胁。已经得到广泛研究证实风蚀盐/沙尘及形成的气溶胶通过多种形式,直接或间接影响地气能量交换及全球物质循环过程,在地球表观系统中起着至关重要的作用。针对咸海湖盆频发的盐/沙尘灾害现象,本文基于地面调查、遥感和 GIS 技术,从中亚五国所在区域大气气溶胶的大背景调查出发,首先对该地区气溶胶的时空分布特征及其主要来源作了探讨,并重点研究了气溶胶热点区——咸海湖盆的气溶胶变化。为查明与盐/沙起源密切相关的下垫面状况,借助多尺度遥感数据研究了咸海湖盆尺度地表覆被变化及演变趋势。在利用 MODIS 遥感影像监测盐/沙尘事件中,针对多种沙尘监测指数所存在的阈值不稳定的问题,提出指数改进方案,通过监测效果对比验证了改进指数的优异性,并由此获取自2000 年以来起源于咸海湖盆的盐/沙尘暴序列以及点源的空间分布。最后通过建立包括地表覆被类型、植被覆盖度、地形因子以及近地表风速等风蚀影响因素的综合评价体系,对湖盆尺度的风蚀风险进行评估和制图。同时结合 HYSPLIT模式,模拟咸海湖盆盐/沙尘的扩散传输路径和影响范围。主要研究结论如下:(1)气溶胶指数(AI)和气溶胶光学厚度(AOD)均显示 2005 年以来,中亚地区气溶胶整体水平呈明显上升趋势,气溶胶高值主要出现在春季和夏季,具体指 4、5、6、7 四个月份。其中咸海及其周边荒漠是中亚气溶胶的热点,表明气溶胶主要来源于沙尘和盐尘。咸海湖盆作为气溶胶高值中心,从1979 年开始 AI 水平一直在上升,增幅达 100%,AOD 从 2002 年至 2016 年的年均增幅也达到 3.12%。(2)基于 Landsat 数据的地表覆被变化结果表明,1977 年至 2015 年咸海水域面积减少 82.45%,形成大面积含盐表层(盐壳和盐土)和其它裸地,荒漠化面积达到 47566.45 km2(占湖盆面积的 70.28%),植被覆盖仅占 15.38%。根据 Markov-CA(马尔科夫-元胞自动机)模型的预测,若以过去 40 年来的地表覆被转化概率,2025 年咸海东南部将完全干涸。针对 MODIS 时序数据的集成学习分类实验表明相对于 AdaBoost、Bagging 和随机森林算法,旋转森林算法能显著提高分类精度。基于旋转森林方法的 2000~2015 年分类结果揭示了 16年间最显著的地表覆被变化是咸海东南部水体。覆被变化的驱动力分析表明,引水灌溉等人文因素占主导作用,区域气候变化,尤其是明显升温则在一定程度上加剧了咸海湖盆的荒漠化进程。(3)通过线性波谱分离方法,引入沙尘光学浓度(α)改进 NDDI 所形成的EDI,在与 BTD、NDDI、MEDI 和 BADI 几种通用沙尘监测指数对典型盐/沙尘事件监测效果的对比评估中, EDI 有效解决了监测阈值不稳定的问题,而且与AOD 的相关性最高,在识别沙尘空间分布和浓度方面的表现更好,适用于长距离传输的沙尘事件监测。由 EDI 监测并建立的 2000~2016 年的盐/沙尘暴事件序列表明咸海湖盆的盐/沙尘活动一直很活跃,年均出现频率达到 15.3 次,峰值出现在 2014 年达 25 次。由高值频率法分析 AI 和 AOD 产品的结果显示,东部早期干涸湖岸是盐/沙尘点源的集中分布地带。(4)根据 HYSPLIT 前向径迹模拟,起源于咸海湖盆的盐/沙尘传输扩散模式的季节变异较大,在盐/沙尘暴多发的春季和夏季,其中春季 41%向南部扩散,44%向东北方向扩散;夏季 53%向西南方向扩散,总体上看,咸海南部受盐/沙尘影响最为严重。综合地形、地表覆被类型、植被覆盖度和近地表风速等四种风蚀影响因素的风蚀风险评估模型及制图显示,咸海东部风蚀风险最为严重,风蚀可能性高达 93%,其次是中部(82%)和南部(67%)。
Other AbstractAral Sea, one of the largest inland lakes located in the Central Asian Arid Zone,plays a very important role in matainning the ecological functions on the regionalscale. However, dramatic desciccation has occurred on this huge sea-lake because ofoverexploitation of water resources for agricultural irrigation from the whole Aral Seadrainage basin since 1960s. Then the special saline desert Aralkum formed on the vastexposed dry lake bed. It has accumulated huge amounts of poisonous sediments andbecome a major source for salt and other chemical dust, which has generated frequentsalt or dust events and been posing great threat to the regional ecological environmentand human health in Central Asia. In addition, extensive studies have confirmed thataeolian salt, dust and aerosols are very important in the earth surface system throughvarious forms, directly or indirectly affecting the energy balance and material cycle ofthe earth.To this end, we organized this thesis to fully comprehend the salt or dust eventsorginated from the Aralkum desert. As mentioned above, dust activities would creatmuch atmospheric aerosols, therefore the temporal and spatial distributioncharacteristics of aerosol and its main sources in Central Asia were firstly analyzedbased on ground survey data, remote sensing methods as well as GIS technique. Sincethe outbreak of dust events are closely associated with the condition of land surface,then the land cover change and its evolution trend on the scale of Aral Sea lake basinwas obtained by analyzing multi-scale remotely-sensed imageries. In the salt/dustevent detection based on MODIS imageries an newly improved index was proposedto resolve the common problem of unfixed threshold. And its advantage wasconfirmed through comparisons of salt/dust events detection performance with severalwidely-used dust monitoring indexes, then built the sequence of salt/dust stormsoriginated from the Aral Sea basin since 2000. Finally, we established acomprehensive wind erosion risk evaluation model which involvs in land surface cover types, vegetation coverage, terrain factors and near surface wind regime, andperformed the evaluation and mapping of the deflation risk on the basin scale.Additionally, the salt/dust transport patterns was simulated via the HYSPLIT model.We could obtain the following major conclusions:(1) analysis of AI and AOD showed that the overall level of aerosol in CentralAsia increased significantly since 2005, and mainly took placed in late spring andsummer, specifically April, May, June and July. The Aral Sea and the surroundingdeserts were the hot spots of aerosols in Central Asia, indicating that the aerosolmainly comes from dust and salt dust. As an aerosol high value center, the AI level ofthe Aral Sea Lake Basin has been on the rise from the beginning of 1979, increasednearly by 100%, and the annual increase of AOD from 2002 to 2016 had reached3.1% as well.(2) Landsat data based land cover change results showed that the water body ofAral Sea decreased by 82.45% from 1977 to 2015, directly forming large area withsaline surface layer (namely salt crust and soil) and other bare land, hence thedesertification area reached up to 47566.45 km2(70.28% of the lake basin), whilevegetation covers only accounted 15.38%. And according to the simulation ofMarkov-CA model, the southeastern part of Aral Sea would be completely dry by2025. Experiments on ensemble learning for MODIS time series data showed thatrotation forest algorithm could significantly improve classification accuracy incontrast with AdaBoost, Bagging, and random forest ensemble learning methods. Theclassification results of 2000~2015 years based on rotation forest revealled the mostsignificant land cover change was the water body of Southeastern Aral Sea durng the16 years. As to the drivers of the LUCC, to some extent climate change did increasethe water incomings as well out-comings of the Aral Sea. But the most dramatic landuse changes were driven by the rapid and massive expansion of irrigation, waterdiversion and conversion of desert rangelands into irrigated croplands.(3) By comparisons of several common dust monitoring indexes like BTD,NDDI, MEDI and BADI on the detection performance of typical dust events, thenintroduced dust optical concentration (α) to improve NDDI and propose EDI, the results showed that EDI and AOD had the highest correlation, and EDI had the betterperformance in identifying the spatial distribution and concentration of dust, longdistance-transport dust events monitoring, numerical analysis of dust outbreaks,transport and deposition process. And salt/sand storm events sequence in 2000~2016years built by EDI monitoring showed that salt/dust activity had been very active inthe Aral Sea basin, and the peak value of frequency reached 25 in the year of 2014.High value frequency analysis based on AOD and AI revealed that the majority ofpoint sources for dust events were located in the eastern former lake shore.(4) The HYSPLIT trajectory mode revealled that the salt/dust diffusion modeltransported from the Aral Sea lake basin showed large seasonal variability. Focusedon the two seasons with high frequencies of salt/dust storms, in spring 41% of the dustspread to the south, 44% spread to the northeast, and 53% spread to the southwest insummer. Overall, the southern to the Aral Sea sufferred the most severe salt/dust. Theintegration of land cover types, vegetation coverage, terrain, and the near surfacewind speed of wind erosion risk assessment model and mapping showed that theeastern part of Aral Sea had the highest wind erosion risk, the possibility was of up to93%, followed by the central part (82%) and southern part (67%).
Subject Area自然地理学
Language中文
Document Type学位论文
Identifierhttp://ir.xjlas.org/handle/365004/14935
Collection研究系统_荒漠环境研究室
Affiliation中国科学院新疆生态与地理研究所
First Author Affilication中国科学院新疆生态与地理研究所
Recommended Citation
GB/T 7714
沈浩. 咸海湖盆盐/沙尘变化过程及其影响因素遥感研究[D]. 新疆乌鲁木齐. 中国科学院大学,2018.
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