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.     

喜马拉雅中部甘达基河流域尼泊尔国鸟(棕尾虹雉)生境分布变化

甘达基河流域(Gandaki River Basin,GRB)是喜马拉雅中部地区的一部分,该地区栖息着许多珍稀的野生动物。由于气候和人类活动的影响,许多珍稀保护物种的生境处于危险之中。本研究基于最大熵(MaxEnt)模型,运用生物气候、土地覆被和DEM数据,分析各环境要素对棕尾虹雉(Lophophorusimpejanus)的生境适宜性的影响,评估棕尾虹雉现在状况和未来栖息地分布的变化。研究表明,目前棕尾虹雉的高度适宜栖息地面积约为749 km^2,主要分布在流域北部、东部和西部,尤其是郎塘国家公园、马纳斯卢峰自然保护区和安纳布尔纳峰自然保护区等保护区内。到2050年,棕尾虹雉的高度适宜栖息地面积将减少至561 km^2,主要在流域北部和西北部(即Chhyo,Tatopani,Humde和Chame地区)。未来环境变化的模拟表明,由于适宜栖息地面积的减少,棕尾虹雉面临的生存风险将增加。     

气候变化下基于物种与植物耦联机制的小白额雁(Anser erythropus)潜在生境及适宜性研究--以长江流域中下游为例

气候变化和人类活动通过改变物种生境而影响物种多样性。小白额雁是长江流域中下游的一种具有较高生态价值的食草型濒危候鸟,受气候变化和人类活动威胁。本文以小白额雁为代表性物种,定量分析了气候变化对长江流域中下游候鸟潜在生境及适宜性空间分布格局的影响。采用Maxent模型模拟了当前情景和全球环流模型(GCMs)气候场景下小白额雁潜在生境及其适宜性分布。研究结果表明,小白额雁分布特征与其栖息地周边植物分布呈显著相关关系;运用Maxent模型模拟小白额雁六种主要食源植物的分布特征,并将其结果作为环境变量,将显著改善小白额雁潜在生境及其适宜性模型的模拟性能;在两种典型浓度情景(RCP 2.6和RCP8.5)下,2070年小白额雁潜在生境适宜性面积将下降。为应对气候变化对小白额雁的影响,应采取更加合理的管理措施和保护政策,包括调整保护区的大小、形状和用途。     

Space Changes in the Rural Tourism Area of Mufu Town,Hubei Province,China

In a society dominated by tourism consumption, space changes occurring in rural areas can generally reflect their social changes. On the theoretical basis of flow, regeneration and adaptation of rural tourism space, this paper originally and creatively proposes that the spatial elements in a rural tourist area can be classified into three categories: Attractions (A), Towns (T) and Villages (V). By analyzing the spatial transformation characteristics of A, T and V, five types of rural spatial transition modes are found, the types of heritage, theme park, those serving as scenic spots, leisure industrial clusters and ecotourism areas. These different classes emerge due to their geographical differentiation. They show the same spatial evolution trend: The Attractions are distributed throughout the whole area and characterized by diversification; supporting services facilities gather in the Towns; and the Villages are landscape images. In this area the traditional rural benefit trends toward that of compound development. Mufu Town, Hubei province, is taken as a study case, and the changing characteristics of A, T and V from 2006 to 2016 are described. Problems in the process of establishing the new spatial order are considered. In order to realize the synergy between production space, living space and ecological space, the interactive development between Attractions, Towns and Villages is recommended. The perspective of Attraction-Town-Village (ATV) can lead to a better understanding of the situation of tourism space in rural areas and provide directions for thinking about the reconstruction path for the modernization of traditional societies.     

Integration of remote sensing,county-level census,and machine learning for century-long regional cropland distribution data reconstruction

The Lower Mississippi Alluvial Valley (LMAV) was home to about ten million hectare bottomland hardwood (BLH) forests in the Southern U.S. It experienced over 80 % area loss of the BLH forests in the past centuries and large-scale afforestation in recent decades. Due to the lack of a high-resolution cropland dataset, impacts of land use change (LUC) on the LMAV ecosystem services have not been fully understood. In this study, we developed a novel framework by integrating the machine learning algorithm, county-level agricultural census, and satellite-based cropland products to reconstruct the LMAV cropland distribution during 1850–2018 at a 30-m resolution. Results showed that the LMAV cropland area increased from 0.78 × 10⁴ km² in 1850 to 6.64 × 10⁴ km² in 1980 and then decreased to 6.16 × 10⁴ km² in 2018. Cropland expansion rate was the largest in the 1960s (749 km² yr⁻¹) but decreased rapidly thereafter, whereas cropland abandonment rate increased substantially in recent decades with the largest rate of 514 km² yr⁻¹ in the 2010s. Our dataset has three notable features: (1) the depiction of fine spatial details, (2) the integration of the county-level census, and (3) the inclusion of a machine-learning algorithm trained by satellite-based land cover product. Most importantly, our dataset well captured the continuous increasing trend in cropland area from 1930–1960, which was misrepresented by other cropland datasets reconstructed from the state-level census. Our dataset would be important to accurately evaluate the impacts of historical deforestation and recent afforestation efforts on regional ecosystem services, attribute the observed hydrological changes to anthropogenic and natural driving factors, and investigate how the socioeconomic factors control regional LUC pattern. Our framework and dataset are crucial to developing managerial and policy strategies for conserving natural resources and enhancing ecosystem services in the LMAV.     

Conjugate ruptures and seismotectonic implications of the 2019 Mindanao earthquake sequence inferred from Sentinel-1 InSAR data

In 2019, four strong earthquakes of Mw>6.4 occurred successively in Mindanao, Philippines. Based on the reports from the USGS and PHIVOLCS, these earthquakes were dominated by strike-slip ruptures. Whether these earthquakes are temporally and spatially related remained unknown. We characterized the coseismic displacement fields during the earthquake sequence using an InSAR technique with Sentinel-1 SAR data. The InSAR deformation measurements convincingly reveal that the four earthquakes produced distinct coseismic displacement patterns. We estimated the source parameters of the earthquakes with a two-step inversion strategy. The optimal model suggests that the earthquake sequence resulted from the reactivation of a conjugate fault structure that involves two nearly vertical left-lateral strike-slip faults and two high-angle right-lateral strike-slip faults. We calculated Coulomb stress changes from the earthquake sequence, suggesting that the previous strong earthquakes had significant stress-encouraging effects on the following events. The regional velocities based on the GPS analysis suggest that the formation of this conjugate structure is mainly due to the westward movement of the subducting Philippine Sea Plate. This earthquake sequence provides a seismotectonic background for subsequent strong earthquakes and helps to better understand the formation mechanisms and seismotectonic implications of conjugate structure rupturing.     

利用CEEMD分析中国沿海GNSS站高程时序变化

利用完备经验模态分解方法（CEEMD）对我国沿海地区6个GNSS基准站（2010—2018）的高程时序数据进行了处理分析。结果表明：CEEMD在高程时间序列分析中具有一定的优越性,可准确分解出各GNSS站高程时序中存在的周、月、季节、年等变化周期项,其中周年运动是主要贡献项,各站高程时间序列的短周期变化与潮汐变化周期具有密切关联性;沿海GNSS站的地面沉降既具有区域的一致性,又存在区域间差异性,其中D区DBJO、DZJJ站呈现先下降后上升的趋势,N区NZUH、NWZU站呈下降趋势,B区的BZMW呈上升趋势,而同海区的BLHT站则呈显著的下降趋势。     

高分三号SAR影像双阈值变化检测

双阈值合成孔径雷达SAR(Synthetic Aperture Radar)变化检测算法具有在发现变化区域的同时还能确定地表发生后向散射变化类型的优点。针对广义高斯双阈值最小误差法D-GKIT(Dual Generalized Kittler and Illingworth Thresholding)在进行阈值选取时直方图中不同类别像素灰度级重叠严重时,分割结果容易在尖峰单侧选取出双阈值而导致无法正确分割差异图的问题,本文提出一种结合归一化最大类间方差和广义高斯最小误差法GKIT(Generalized Kittler and Illingworth Thresholding)的双阈值SAR变化检测方法。首先,提出以归一化最大类间方差值作为灰度级重叠程度的判别参数,确定阈值的选取顺序及两个候选区间;然后,利用GKIT在候选区间内进行分割,获取单侧阈值及非变化类拟合函数;最后,提出利用非变化类拟合函数更新后的直方图作为另一侧阈值选取基础进行分割,得到对应分割阈值。以宁波地区高分三号(GF-3)SAR卫星影像作为试验研究数据,结果表明:本文方法能较好地解决灰度级重叠时D-GKIT无法进行正确分割的问题,具有良好的变化检测效果和更强的鲁棒性且达到了利用研究区数据验证利用GF-3号SAR卫星影像进行变化检测研究可行性的目的。     

泛北极地区多年冻土活动层厚度演变

深入理解泛北极地区多年冻土活动层厚度的演变, 对于全球碳通量模拟、气候变化预测及泛北极地区冻融风险评估具有重要意义。目前开展的泛北极地区多年冻土活动层厚度模拟与分析, 大多无法全覆盖或空间分辨率过低(25 km或是更大), 在景观尺度(公里级)上的多年冻土活动层厚度变化特征仍有待解析, 尤其是关键基础设施区的活动层厚度变化仍不清楚。本研究基于站点监测数据、MOD11B3地表温度数据、MCD12C1土地覆盖数据, 采用Stefan模型, 在公里级空间分辨率上模拟泛北极地区2001年—2017年多年冻土活动层厚度, 并解析泛北极地区及主要油气区多年冻土活动层厚度时空变化格局及主要原因。研究发现: 2001年—2017年泛北极地区约有78.4%的冻土区域多年冻土活动层厚度呈现增长趋势, 尽管全区多年平均的增长速率为0.22 cm/a (p<0.05), 但具有较强的时空差异性。显著增长区主要集中在加拿大西北部的落基山脉及劳伦琴高原一带以及俄罗斯中西伯利亚高原中部地区, 增加速率主要在0.5—1 cm/a;而减少区主要分布在加拿大的哈得孙湾沿岸平原、拉布拉多高原一带, 俄罗斯的东西伯利亚山地北部、中西伯利亚高原的北部、贝加尔湖以东区域和泰拉尔半岛一带。泛北极地区主要油气区多年冻土活动层厚度也以增加为主, 80%以上的油气区呈现增加趋势, 增长速率在0.1—0.7 cm/a。泛北极地区多年冻土活动层厚度变化与气温变化在空间上具有较好的一致性;积雪厚度与活动层厚度关系复杂;不同植被类型的多年冻土活动层厚度有所差异(林地>草地>稀树草原>灌丛), 且多年冻土活动层厚度变化与植被转化方向一致。该成果将有助于深入理解北半球高纬度多年冻土区冻融格局, 尤其可为冻土区的油气设施冻融风险识别与防控提供参考。     

毛乌素沙地东南缘全新世气候不稳定性

毛乌素沙地处于中国季风区的西北边缘,对气候变化敏感,是古气候演化和古环境变迁研究的理想场所。全新世气温回暖期,气候整体稳定但存在暖湿冷干的次级波动,不同类型沉积相组成的地层序列记录了全新世千年、百年尺度的气候不稳定性。对毛乌素沙地不同沉积序列的研究表明:(1)毛乌素沙地东南缘的沙漠/黄土边界带DLT、NB剖面粒度及Rb/Sr比值可作为气候变化的代用指标。>63 μm砂含量增加,Rb/Sr比值降低,揭示东亚冬季风增强,风成砂堆积,风沙活动加剧,气候干冷;反之,东亚夏季风增强,降水增多,风化成壤程度加大,气候暖湿。(2)毛乌素沙地东南缘沙漠/黄土边界带及低洼沟谷区年代概率密度函数的分析显示,全新世早期~8\^5 ka BP风成砂堆积,风沙活动加剧,气候表现为干冷;全新世中期8\^5 ka~3\^0 ka BP地势较高处古土壤广泛发育,地势低洼处发育湖沼相/泥炭层,但在6.0 ka BP左右存在气候转冷过程;全新世晚期3\^0 ka BP以来气候波动频繁。(3)毛乌素沙地气候变化与北大西洋冰筏冷事件、董哥洞石笋、季风边缘区湖泊、东部沙地等记录具有可对比性和相对一致性,反映出全新世千年和百年尺度上的气候变化主要受全球变化的影响,这对预测和模拟未来气候变化具有借鉴意义。