Analysis of trends in annual streamflow to the Arctic Ocean

There is increasing interest in the magnitude of the flow of freshwater to the Arctic Ocean due to its impacts on the biogeophysical and socio‐economic systems in the north and its influence on global climate. This study examines freshwater flow based on a dataset of 72 rivers that either directly or indirectly contribute flow to the Arctic Ocean or reflect the hydrologic regime of areas contributing flow to the Arctic Ocean. Annual streamflow for the 72 rivers is categorized as to the nature and location of the contribution to the Arctic Ocean, and composite series of annual flows are determined for each category for the period 1975 to 2015. A trend analysis is then conducted for the annual discharge series assembled for each category. The results reveal a general increase in freshwater flow to the Arctic Ocean with this increase being more prominent from the Eurasian rivers than from the North American rivers. A comparison with trends obtained from an earlier study ending in 2000 indicates similar trend response from the Eurasian rivers, but dramatic differences from some of the North American rivers. A total annual discharge increase of 8.7 km³/y/y is found, with an annual discharge increase of 5.8 km³/y/y observed for the rivers directly flowing to the Arctic Ocean. The influence of annual or seasonal climate oscillation indices on annual discharge series is also assessed. Several river categories are found to have significant correlations with the Arctic Oscillation, the North Atlantic Oscillation, or the Pacific Decadal Oscillation. However, no significant association with climate indices is found for the river categories leading to the largest freshwater contribution to the Arctic Ocean.     

时空大数据背景下并行数据处理分析挖掘的进展及趋势

随着互联网、物联网和云计算的高速发展,与时间、空间相关的数据呈现出“爆炸式”增长的趋势,时空大数据时代已经来临。时空大数据除具备大数据典型的“4V”特性外,还具备丰富的语义特征和时空动态关联特性,已经成为地理学者分析自然地理环境、感知人类社会活动规律的重要资源。然而在具体研究应用中,传统数据处理和分析方法已无法满足时空大数据高效存取、实时处理、智能挖掘的性能需求。因此,时空大数据与高性能计算/云计算融合是必然的发展趋势。在此背景下,本文首先从大数据的起源出发,回顾了大数据概念的发展历程,以及时空大数据的特有特征;然后分析了时空大数据研究应用产生的性能需求,总结了底层平台软硬件的发展现状;进而重点从时空大数据的存储管理、时空分析和领域挖掘3个角度对并行化现状进行了总结,阐述了其中存在的问题;最后指出了时空大数据研究发展趋势。     

从若干典型地区的研究对近十余年来中国土地沙漠化演变趋势的分析

土地沙漠化是当前世界上一个重要的生态环境问题,在我国也存在着严重的土地沙漠化问题。50年代末至70年代中期,我国沙漠化土地以每年1560km~2的速度扩大。近10余年来其总的趋势仍在发展,平均每年以2100km~2的速度蔓延。目前,全国已经沙漠化了的土地面积达19.70×10~4km~2以上,其中以沙质草原农垦区和能源基地附近的情况最为严重。实例说明,沙漠化土地在采取必要的措施之后,不仅可以防止其蔓延,而且还可以重新恢复其生产潜力成为农牧业用地。     

未来百年夏季青藏高原臭氧变化趋势及可能机制

利用全大气气候通用模式(WACCM3)对政府间气候变化专门委员会排放情景特别报告中2001年到2099年A1B、A2、B1三种排放情景进行了模拟,分析了三种排放情景下青藏高原地区未来百年臭氧总量在夏季(6—8月)的变化趋势及引起该变化的可能机制。结果表明:在三种排放情景下未来百年夏季高原区臭氧总量均呈现增长趋势,其中A2情景下臭氧增长最快,B1情景下增长最慢,但相对于同纬度其他地区,高原区的臭氧总量增长较慢,即高原区臭氧谷加深。高原区高空污染物的减少以及局域Hadley环流的减弱是未来高原区臭氧总量增加的原因;而南亚高压的增强,以及与之相对应的辐散增强则可能是高原区臭氧谷继续加深的原因。     

Water quality in New Zealand rivers: current state and trends

River water quality, particularly in lowland catchments, is a matter of concern to the New Zealand public. We assessed river water quality and biological state and trends using data from more than 900 monitoring sites. Parallel state and trend analyses were carried out using all sites and a subset of lowland river sites. Median water-quality state in urban and pastoral land-cover classes was poorer than in exotic forest and natural land-cover classes, and lowland sites in the urban and pastoral classes had the poorest water quality. Nutrient and Escherichia coli concentrations increased and visual clarity and Macroinvertebrate Community Index scores decreased as proportions of catchments in high-intensity agricultural and urban land cover increased. Ten-year trends (2004–2013) indicated recent improvements in ammoniacal nitrogen, dissolved reactive phosphorus and total phosphorus in the pastoral and urban classes, possibly reflecting improved land management. In contrast, trends in nitrate-nitrogen in the exotic forest and cool-dry/pastoral classes indicated worsening conditions.     

Land change attribution based on Landsat time series and integration of ancillary disturbance data in the Athabasca oil sands region of Canada

The Alberta Oil Sands (AOS) is a unique area in Canada undergoing significant disturbance and recovery due to a variety of anthropogenic and natural factors. Accurately quantifying these changes in space and time is important for assessing ecosystem status and trends. In this research, we implemented an approach to combine Landsat time series for the period 1984–2012 with ancillary change datasets to derive detailed change attribution in the AOS. Detected changes were attributed to causes including fire, forest harvest, surface mining, insect damage, flooding, regeneration, and several generic change classes (abrupt/gradual, with/without regeneration) with accuracies ranging from 74% to 100% for classes that occurred frequently. Lower accuracies were found for the generic gradual change classes which accounted for less than 3% of the affected area. Timing of abrupt change events were generally well captured to within ±1 year. For gradual changes timing was less accurate and variable by change type. A land-cover time series was also created to provide information on “from-to” change. A basic accuracy assessment of the land cover showed it to be of moderate accuracy, approximately 69%. Results show that fire was the major cause of change in the region. As expected, surface mine development and related activities have increased since 2000. Insect damage has become a more significant agent of change in the region. Further investigation is required to determine if insect damage is greater than past historical events and to determine if industrial development is linked to the increasing trend observed.     

Spatial and Temporal Patterns in Structure of Macrobenthic Assemblages. A Three-Year Study in the Northern Adriatic Sea in Front of the Po River Delta

Abstract. Coastal benthic communities in soft-bottom deposits of a restricted area were studied by seasonal sampling at nine stations. Faunal assemblages at three different depths were consistently different and exhibited a seasonal pattern of abundance and diversity. Multivariate statistical analyses suggest that each community structure is very similar during the three summer samplings; in autumn and winter many causes of disturbance can disrupt this structure, which is reconstituted the following summer. The stability of benthic communities in this physically variable environment is discussed and a "cyclic" adjustment mechanism of stability is proposed to explain the dynamics of the benthos in this area.