【作者】 王卫红；

【导师】 罗学刚；

【作者基本信息】 西南科技大学 ， 环境科学与工程， 2020， 博士

【摘要】 随着国防和核电工业对铀资源需求的不断增加,在铀矿资源的开采和利用过程中,大量铀废石和铀尾矿的产生不可避免。铀尾矿及周边污染土壤平均含铀量比天然本底值高4~10倍,其表面辐射剂量比一般土壤平均高5~70倍。铀尾矿渣还常含有超标的伴生重金属。因此,铀尾矿库已成为一个不容忽视的放射性和重金属污染源。快速、安全地监测铀尾矿及周边土壤的放射性和重金属污染是推进生态环境保护、改善生态环境质量的现实需求。研究植物叶片反射光谱、土壤铀及伴生重金属含量、植物的富集与耐性特征之间的关联机制,特别是探索如何利用植物叶片反射光谱进行土壤和植物叶片的铀及伴生重金属含量反演,为最终实现利用遥感方法进行铀尾矿及周边土壤铀及伴生重金属污染程度和修复效果的大面积高效监测提供理论与技术创新,成为本论文提出和诠释的关键科学问题。本文采用五种植物苎麻(Boehmeria nivea)(湘苎7号)、印度芥菜(Brassica juncea)、酸模(Rumex acetosa L.)、甘蓝型油菜(Brassica napus L.)、玉米(Zea mays L.),分别在不同浓度的铀及伴生重金属镉、铅污染土壤中进行盆栽实验。作者分析了实验植物的铀及伴生重金属富集与耐性特征;从光谱角变异、敏感波长、光谱特征参数的角度分析了铀及伴生重金属污染下实验植物叶片的反射光谱特征;尝试根据富集与耐性特征解释叶片反射光谱特征对铀及伴生重金属的响应;分析了叶片与土壤铀及伴生重金属含量之间的关系;以叶片反射光谱特征为基础,用统计方法反演了土壤铀及伴生重金属含量;分别用统计方法、植被指数方法和物理方法反演了叶片的铀及伴生重金属含量。本文揭示了叶片反射光谱特征与土壤和叶片中铀及伴生重金属的定量关系,探索了土壤铀及伴生重金属污染在叶片反射光谱的响应机制,基于叶片反射光谱特征实现了土壤中铀及伴生重金属含量的直接和间接反演,为利用遥感手段进行铀矿山、铀尾矿等铀及伴生重金属污染程度和修复效果的大面积快速监测提供了理论依据和技术支撑。主要研究结果和创新点表现在:(1)通过测量5种实验植物累积32个生长期的叶片反射光谱进行分析,发现铀、镉、铅污染下,植物的光谱角、敏感波长、光谱特征参数均可能产生相应的变化,其中光谱角变异反映了光谱的宏观变异情况,可直接用于土壤铀及伴生重金属含量的反演。有16个生长期由光谱角变异成功反演了土壤铀及伴生重金属含量。从光谱角变异直接反演土壤铀及伴生重金属含量的角度衡量,油菜可以看作是土壤铀、镉、铅污染的指示植物。湘苎7号的光谱角变异对土壤的铀和铅污染也有较好的指示作用。统计方法、植被指数方法和物理方法各具特点,三种方法相互补充,在32个生长期均成功实现了叶片铀及伴生重金属含量的反演。土壤和叶片铀及伴生重金属含量的回归模型表明,叶片铀及伴生重金属含量能定量反映土壤铀及伴生重金属含量的高低。从叶片与土壤重金属含量的关系来衡量,印度芥菜、酸模可以作为铀污染的指示植物和监视器,油菜对铀、镉、铅在大多数生长期也具有指示和监视的作用。以叶片铀及伴生重金属含量为中介,扩大了由叶片反射光谱特征反演土壤铀及伴生重金属含量的适用范围。(2)原始光谱敏感波长较集中分布在370、600、775和980nm附近,但双子叶和单子叶植物、不同重金属污染下的原始光谱敏感波长之间均有较大的区别。一阶导数光谱敏感波长比较集中地分布在380、550、800和950nm附近,双子叶和单子叶植物、不同重金属污染下的一阶导数光谱敏感波长一致性比原始光谱高。与原始光谱相比,一阶导数光谱对铀及伴生重金属更敏感。一般情况下,以一阶导数光谱敏感波长为自变量的回归方程比以原始光谱敏感波长为自变量的质量好。(3)在本文选择的51个光谱特征参数中,5种实验植物、3种重金属污染的累积29个生长期找到了与叶片的铀及伴生重金属含量显著强相关的光谱特征参数。比值参数SDnir/SDre在苗期即能敏感地响应3种植物的铀和铅污染,而且与叶片的铀和铅含量呈现非常一致的显著强负相关关系,具有成为监测铀及伴生重金属含量的理想光谱特征参数的潜质。绿峰、红谷、近红外平台等参数与叶片铀与伴生重金属含量关系密切,而以往研究比较多的红边参数表现平淡。从响应时间、回归方程的决定系数、个数等方面比较,基于光谱参数比基于敏感波长的反演综合效果更好,证明光谱参数确实综合了多个敏感波长的特征,对信息有较强的提取能力。(4)确定了植被指数的52个具体形式用于叶片铀及伴生重金属含量的反演;对部分植被指数原始形式中的某些参数进行了替换,其中替换式RBRI3、PRI22、TVI3、CARI12和MCARI2比对应的原始形式更适合进行铀及伴生重金属含量的反演。(5)利用敏感波长进行了PROSPECT模型中叶片结构参数N的反演,大幅度地提高了其与叶片铀及伴生重金属含量的相关性。测量了叶片的解剖结构参数,发现在铀及重金属污染胁迫下,叶片整体厚度和表皮厚度、下表皮厚度、表皮细胞、维管束、栅栏组织、泡状细胞等指标发生了明显变化。建立了叶片结构参数N与叶片解剖结构参数的回归方程,创新了确定叶片结构参数N的方法;并且完成了物理方法反演叶片铀及伴生重金属含量。(6)如果从成功反演的生长期期数和回归方程最大决定系数R2来衡量,统计方法和植被指数方法的效果比物理方法效果更好。无论是富集植物还是非富集植物,都有可能得到质量高的回归方程。统计方法反演的结果表明:对铀具有富集作用的植物苎麻和印度芥菜整体上更有利于通过其生长早期的叶片光谱进行铀含量的监测;植物耐性强则很可能对反演叶片铀及伴生重金属含量起反作用,尤其在生长晚期。但根据植被指数方法和物理方法反演时,该规律不明显。更多还原

【Abstract】 With the increasing demand of national defense and nuclear power industry for uranium resources,a large number of uranium waste rocks and uranium tailings are inevitable in the process of uranium mining and utilization.The average uranium content of uranium tailing and surrounding contaminated soil is 4-10 times higher than the natural background value,and its surface radiation dose is 5-70 times higher than that of general soil.Uranium tailings have become a radioactive pollution source that can not be ignored.How to determine the radioactive and heavy metal pollution risk of uranium tailings and surrounding soil and repair them when necessary,study the correlation mechanism or mechanism between plant leaf reflectance spectrum and soil uranium and associated heavy metal content,especially explore how to use plant leaf reflectance spectrum to retrieve uranium and associated heavy metal content in soil and plant leaves,and finally realize the remote sensing method Large area and efficient monitoring of uranium and associated heavy metals pollution and remediation effect of uranium tailings and surrounding soil provides theoretical and technical innovation,which has become the key scientific problem proposed and interpreted in this dissertation.The author carried out five plants ramie(Boehmeria nivea),Indian mustard(Brassica juncea),sorrel(Rumex acetosa L.),rape(Brassica napus L.)and corn(Zea mays L.)pot experiment under different concentrations of uranium,cadmium and lead pollution.The characteristics of enrichment and tolerance of experimental plants were analyzed.The reflectance spectra of plants at different growth stages were measured.The reflectance spectra of leaves were analyzed according to spectral angle,sensitive wavelength and spectral characteristic parameters.Based on the reflectance spectra of leaves,the contents of heavy metals in soil were retrieved by statistical method.While the contents of heavy metals in leaves were retrieved by statistical method,vegetation index method and physical method,respectively.This dissertation reveals the quantitative relationship between leaf reflectance spectrum characteristics and uranium and associated heavy metals in soil and leaves,realizes direct and indirect inversion of uranium and associated heavy metals in soil,and explores the response mechanism of soil heavy metal pollution in leaf reflectance spectrum,which provides theoretical basis and technical support for monitoring the pollution degree and remediation effect of heavy metals by remote sensing.The main research results and innovations are as follows:(1)By measuring and analyzing the leaf reflectance spectra of 32 growing periods of experimental plants,it is found that the spectral angle,sensitive wavelength and spectral characteristic parameters of plants may change under the pollution of uranium,cadmium and lead.The spectral angle reflects the macroscopic variation of the spectrum,which can be directly used for the inversion of soil heavy metal content.In most of the experimental conditions,the spectral variation of leaves under heavy metal pollution was significant.The contents of heavy metals in soil were successfully retrieved from spectral angle in 16 growing periods.From the perspective of leaf scale remote sensing detection,rape can be regarded as an indicator plant of uranium,cadmium and lead pollution in soil.The spectral angle of Xiangzhu No.7 also indicated the pollution of uranium and lead in soil.According to the sensitive wavelength,spectral characteristic parameters,vegetation index and leaf radiation transfer model prospect based on spectral characteristics,the retrieval of heavy metal content in leaves was successfully achieved in all 32 growing periods when effective sprctral data were gathered.Judging from the relationship of heavy metal contents between leaf and soil,Indian mustard and rape can be used as index plants and monitors for uranium pollution,and rape can also be used as monitor for uranium,cadmium and lead in most growth periods.The regression equation of heavy metal content in soil and leaves showed that heavy metal content in leaves could reflect the content of heavy metals in soil.In other words,taking the leaf heavy metal content as the intermediary,the application range of soil heavy metal content retrieval from leaf reflectance spectrum characteristics was expanded.(2)Basically,the relationship between the reflectance and the original spectra was positive.The sensitive wavelengths of dicotyledons and monocotyledons were different,and the sensitive wavelengths of original spectra of experimental plants under different heavy metal pollution were significantly different,too,which mainly distributed around 370,600,770 and 980 nm.Compared with the original spectral sensitive wavelength,the first derivative spectrum is more sensitive to heavy metals.The results showed that the derivative values corresponding to the sensitive wavelengths of the first derivative spectra at different growth stages had the same correlation with the heavy metal content in leaves,which were mainly distributed around 380,550,800 and 950 nm.In general,the determination coefficient of the regression equation with the first derivative spectral sensitive wavelength as the independent variable is larger than that of the regression equation with the original spectral sensitive wavelength as the independent variable or the two are equal.(3)The results showed that the spectral characteristic parameters were significantly correlated with the heavy metal content in leaves of all the five plants and three heavy metal pollution accumulation periods,and the ratio parameter SDnir/SDre had the potential to be an ideal spectral characteristic parameter for monitoring heavy metal content.Comparing the inversion based on sensitive wavelength and spectral parameters from response time,determination coefficient and number of regression equations,the inversion based on spectral parameters is slightly better than that based on spectral parameters.It is proved that spectral parameters have integrated the characteristics of multiple sensitive wavelengths,which can avoid the contingency of a single band and have strong ability to extract information.(4)52 specific forms of vegetation index were determined for the retrieval of heavy metal content in leaves,and some parameters in the original form of vegetation index were replaced.Among them,RBRI3、PRI22、TVI3、CARI12 and MCARI2 were more suitable for heavy metal content inversion than the corresponding original forms.(5)The inversion of leaf structure parameter N in the radiative transfer model of leaf PROSPECT was carried out by using sensitive wavelength.Compared with N determined by two empirical formula,the correlation between N and heavy metals was greatly improved.The anatomical structure parameters of leaves were measured.It was found that under heavy metal pollution stress,the whole leaf thickness and epidermis thickness,lower epidermis thickness,epidermal cells,vascular bundles,palisade tissue,vesicular cells and other indicators changed significantly.N was calculated from the anatomical structure parameters of leaves,which provided a way to determine N.The regression equations of leaf structure parameters N and leaf anatomical structure parameters were obtained by multiple linear successive regression,and the physical method was used to retrieve the heavy metal content in leaves.(6)Due to the comprehensive selection of spectral characteristic parameters and vegetation index,the statistical method and vegetation index method are better than the physical method in terms of the number of growth periods retrieved successfully and the maximum determinant coefficient R2.The results of statistical inversion show that uranium enriched plants are more conducive to monitoring uranium content through their leaf spectra in the early growth stage,and the strong tolerance of plants is likely to have a negative effect on the inversion of uranium and associated heavy metal content in leaves,especially in the late growth stage.But according to the vegetation index method and physical method,the law is not obvious.On the whole,it is possible to obtain high quality regression equations for both enriched and non enriched plants.更多还原