青藏高原不同时段气候变化的研究综述

1 Introduction The annual mean world temperature increased by about 0.6℃ from the late 1800s to the 1980s (Wang, 1994). The global environmental change is marked with “global warming” and its possible effects on the ecosystem as well as the production …     

柴达木盆地盐尘暴及其资源生态环境影响

在干旱和半干旱地区,盐尘暴是一种常见的极端气象灾害。柴达木盆地频发的沙尘暴实质上就是盐尘暴。柴达木盆地盐尘暴已经对区域大气、土壤、植被、人类健康乃至全球气候变化都产生了不同程度的影响。由于柴达木盆地盐尘暴中可溶盐成分来源复杂,尽管目前对其形成过程和机制还缺乏深刻理解,但人类的资源开发活动对盐尘暴显然具有促进作用。有必要从系统的角度来考虑柴达木盆地盐尘暴对区域乃至全球的影响,这对于区域生态环境的正确评估和后期恢复治理具有重要意义。     

柴达木盆地尕斯库勒盐湖区盐生植物吸盐效应及其耐盐性评价<sub><sup> </sup></sub>

本项研究选取柴达木盆地尕斯库勒盐湖区作为研究区,筛选出了9种优势盐生植物,开展了盐生植物生长区土体颗粒、容重、含水量等物理性质指标,以及土体中HCO<sub>3</sub><sub><sup>-</sup></sub>、Cl<sub><sup>-</sup></sub>、SO<sub>4</sub><sub><sup>2-</sup></sub>、K<sub><sup>+</sup></sub>、Na<sub><sup>+</sup></sub>、Ca<sub><sup>2+</sup></sub>和Mg<sub><sup>2+ </sup></sub>7种易溶盐离子含量试验测试,分析了区内芦苇、海韭菜等9种盐生植物茎叶和根系部分HCO<sub>3</sub><sub><sup>-</sup></sub>、Cl<sub><sup>-</sup></sub>等7种易溶盐离子含量及其分布规律。在此基础上,探讨了区内9种盐生植物对易溶盐离子吸收作用及其差异性;采用盐生植物地上茎叶部分K<sub><sup>+</sup></sub>/Na<sub><sup>+</sup></sub>值结果,定量评价了区内9种盐生植物耐盐性及变化规律,结果表明,区内9种盐生植物茎叶部分K<sub><sup>+</sup></sub>/Na<sub><sup>+</sup></sub>比值,其由大至小依次为：小花棘豆0.84、羊齿天门冬0.58、白刺0.55、盐地风毛菊0.52、海韭菜0.50、无脉苔草0.47、洽草0.41、芦苇0.39和赖草0.34。本项研究结果,利用为尕斯库勒湖区及其周边地区,利用盐生植物有效改良土壤盐渍化方面提供理论支撑。     

察尔汗盐湖西北部典型采区地下卤水赋存状态的地面核磁探测与数值模拟研究

察尔汗盐湖地下晶间卤水蕴藏了宝贵的盐湖矿产资源,如何确定地下卤水的赋存规律以制定科学合理的卤水开采和补给方案,正成为盐湖资源大规模可持续利用亟需解决的重要问题。本文以察尔汗盐湖西北部的典型采卤区作为研究区域,1)利用新型的地面核磁共振找水仪,通过在研究区布设两条十字交叉的测线,探测并反演解译测区地下60米深度内的卤水静态赋存形式,2)结合OpenGeoSys(OGS)多物理场耦合地下水数值模拟软件,对测区地下卤水的动态运移形式进行数值模拟计算。地面核磁探测结果表明研究区含水量整体偏低,最大含水量约0.8%,平均含水量约0.4%。测点结果给出的含水层位分界面与邻近钻孔的地层层位分界面的一致性较高,浅部的层位误差在10%以下,达到了0.5米的精度。考虑到测区南北两边均有采卤渠正在汲取地下卤水,且在测区中心存在两条废弃的采卤渠,OGS地下水数值模拟研究结果表明采卤渠造成测区浅部卤水较大空缺,与研究区浅部含水量总体偏低的探测特征一致。研究结果表明地面核磁共振技术能准确探测卤水当前的赋存状态,地下水运移模拟技术可以深入认识采补活动引起卤水赋存状态的变化规律。探测和模拟结合的联合研究是确定卤水赋存规律的重要手段,研究成果可为盐湖资源合理开采高效利用提供基础资料和相关科学支撑。     

哈达贺休盐湖卤水氢氧同位素特征及成因分析

内蒙古哈达贺休盐湖蕴藏着较为丰富的地下卤水资源,但人们对其成因和演化机制尚缺乏充分的认识。本文采用稳定同位素方法,研究了哈达贺休盐湖地下卤水及其周边水体的氢氧同位素组成特征,并对卤水的成因进行了分析。结果表明：哈达贺休盐湖地下卤水的?D和?18O值平均值分别为-0.53 ‰和4.01 ‰,黑河河水的?D和?18O值平均值分别为-36.73 ‰和-5.51 ‰,居延海湖水的?D和?18O值平均值分别为1.26 ‰和2.73 ‰,当地大气降水的?D和?18O值平均值分别为-5.30 ‰和-1.20 ‰。研究区水体的蒸发趋势线方程为δD=5.32δ18O-20.08,该蒸发线偏离全球大气降水线。黑河河水的氘盈余值（d）最大,湖水和地下卤水的最小,而且湖水和卤水的d值与TDS呈负相关关系。偏正的?D和?18O值以及较小的d值,表明研究区卤水经历了强烈的蒸发,同时还存在与含氧类矿物的同位素交换反应。卤水和居延海湖水氢氧同位素值分布比较集中并且接近,二者都由黑河河水演化而来。     

A note on the lake level variations of Nam Co,south-central Tibetan Plateau from 2005 to 2019

Tibetan lake levels are sensitive to global change, and their variations have a large impact on the environment, local agriculture and animal husbandry practices. While many remote sensing data of Tibetan lake level changes have been reported, few are from in-situ measurements. This note presents the first in-situ lake level time series of the central Tibetan Plateau. Since 2005, daily lake level observations have been performed at Lake Nam Co, one of the largest on the Tibetan Plateau. The interannual lake level variations show an overall increasing trend from 2006 to 2014, a rapid decrease from 2014 to 2017, and a surge from 2017 to 2018. The annual average lake level of the hydrological year (May-April) rose 66 cm from 2006 to 2014, dropped 59 cm from 2014 to 2017, and increased 20 cm from 2017 to 2018, resulting in a net rise of 27 cm or an average rate of about 2 cm per year. Compared to the annual average lake level based on the calendar year, it is better to use the annual average lake level based on the hydrological year to determine the interannual lake level changes. As the lake level was stable in May, it is appropriate to compare May lake levels when examining interannual lake level changes with fewer data. Overall, remote sensing results agree well with the in-situ lake level observations; however, some significant deviations exist. In the comparable 2006-2009 period, the calendar-year average lake level observed in-situ rose by 10-11 cm per year, which is lower than the ICESat result of 18 cm per year.     

Integration of hyperspectral and LiDAR data for mapping small water bodies

Inland water bodies are globally threatened by environmental degradation and climate change. On the other hand, new water bodies can be designed during landscape restoration (e.g. after coal mining). Effective management of new water resources requires continuous monitoring; in situ surveys are, however, extremely time-demanding. Remote sensing has been widely used for identifying water bodies. However, the use of optical imagery is constrained by accuracy problems related to the difficulty in distinguishing water features from other surfaces with low albedo, such as tree shadows. This is especially true when mapping water bodies of different sizes. To address these problems, we evaluated the potential of integrating hyperspectral data with LiDAR (hereinafter “integrative approach”). The study area consisted of several spoil heaps containing heterogeneous water bodies with a high variability of shape and size. We utilized object-based classification (Support Vector Machine) based on: (i) hyperspectral data; (ii) LiDAR variables; (iii) integration of both datasets. Besides, we classified hyperspectral data using pixel-based approaches (K-mean, spectral angle mapper). Individual approaches (hyperspectral data, LiDAR data and integrative approach) resulted in 2–22.4 % underestimation of the water surface area (i.e, omission error) and 0.4–1.5 % overestimation (i.e., commission error).The integrative approach yielded an improved discrimination of open water surface compared to other approaches (omission error of 2 % and commission error of 0.4 %). We also evaluated the success of detecting individual ponds; the integrative approach was the only one capable of detecting the water bodies with both omission and commission errors below 10 %. Finally, the assessment of misclassification reasons showed a successful elimination of shadows in the integrative approach. Our findings demonstrate that the integration of hyperspectral and LiDAR data can greatly improve the identification of small water bodies and can be applied in practice to support mapping of restoration process.     

The 2019 Brumadinho tailings dam collapse: Possible cause and impacts of the worst human and environmental disaster in Brazil

On 25th January 2019, the tailings dam of the Brumadinho iron mine operated by Vale S/A failed catastrophically. The death toll stood at 259 and 11 people remained missing as of January 2020. This tragedy occurred three years after Mariana’s tailings dam rupture – the most significant tailing dam disaster in Brazilian history. Thus far, a systematic investigation on the cause and effect of the failure has yet to be conducted. Here, we use satellite-driven soil moisture index, multispectral high-resolution imagery and Interferometric Synthetic Aperture Radar (InSAR) products to assess pre-disaster scenarios and the direct causes of the tailings dam collapse. A decreasing trend in the moisture content at the surface and the full evanescence of pond water through time (2011–2019) suggest that the water was gradually penetrating the fill downwards and caused the seepage erosion, saturating the tailings dam. Large-scale slumping of the dam (extensional failure) upon the rupture indicates that the materials of the fill were already saturated. InSAR measurements reveal a dramatic, up to 30 cm subsidence in the dam (at the rear part) within the past 12 months before the dam collapse, signifying that the sediments had been removed from the fill. Although the information on the resistance level of the tailings dam to infiltrations is not available, these pieces of evidence collectively indicate that the seepage erosion (piping) is the primary cause for the chronic weakening of the structure and, hence, the internal “liquefaction” condition. Upon the collapse, the fully saturated mud tailings flowed down the gentle slope area (3.13 × 10⁶ m²), where 73 % were originally covered by tree, grass or agricultural tracts. The toxic mud eventually reached the Paraopeba River after travelling 10 km, abruptly increasing the suspended particulate matter (SPM) concentration and the toxic chemical elements in the river, immediately affecting the local livelihoods that depend on its water. The Paraopeba River is a major tributary of the San Francisco River, the second-longest river in Brazil reaching the Atlantic Ocean. We anticipate that the environmental repercussions of this toxic seepage will be felt throughout the entire basin, especially riverine communities located downstream.     

卫星测高数据监测青藏高原湖泊2010年—2018年水位变化

青藏高原湖泊水位变化是气候变化和生态环境变化研究的重要指标。随着Cryosat-2观测数据的日益丰富和处理技术的提升,可以有效监测更多湖泊的水位变化信息。本研究构建了基于噪声去除技术、改进的波形重跟踪处理算法（ImpMWaPP）和误差混合动态模型为一体的高精度湖泊水位序列提取方法,利用Cryosat-2 SARIn数据获取到133个青藏高原湖泊2010年—2018年的高精度水位序列,并分析了这些湖泊水位变化的时空变化特征。总体上,青藏高原湖泊的水位继续呈上升趋势,但上升速度较2003年—2009年趋缓,年均变化率0.159 m/a。从地域分布上,北部湖泊的水位上升最为显著,而南部湖泊的水位则趋于稳定。从时间上,2010年—2012年和2016年—2018年,大多数湖泊的水位呈现快速上涨,而其他时间水位相对稳定或略有下降。     

毛乌素沙地布寨淖尔下风向沙化湖滨地表沉积物理化特性

布寨淖尔湖是鄂尔多斯高原毛乌素沙地腹地的代表性盐湖,其东南部分布着平坦裸露的沙化湖滨\,湖岸沙丘及半固定沙丘,地表均沉积有大量沙物质与粉尘,这些松散富盐物质在风力侵蚀作用下常形成盐碱尘暴,威胁下风向区域的生态环境安全。研究了布寨淖尔湖东南部区域2.5 km范围内地表沉积物的土壤粒度与理化特性,旨在为盐碱尘暴源区的防治与生态治理提供基础科学参考。结果表明:布寨淖尔湖滨裸露地表沉积物以粗砂、中沙和细砂为主;从湖心沿东南方向等距离(0.5 km)采样,距湖心越远,粗砂和细砂含量逐渐减小,极细砂、粉砂和黏土含量逐渐增加,中砂含量无明显变化。地表沉积物含水率、容重随与湖心距离的增加逐渐增加,pH值、全盐量及电导率则呈逐渐减小趋势;沉积物阳离子以Na⁺为主,阴离子以Cl^-为主,其次为SO₄^2-、HCO^-₃。整体看,区内地表碱化较为严重,区域下风向土壤理化特征呈明显有规律变化趋势,湖滨地表土壤有明显风蚀迹象,可能是盐碱尘暴与湖岸沙丘形成的重要物源区。