Modelling the effect of changing precipitation inputs on deep soil water utilization

Forests in the Southeastern United States are predicted to experience future changes in seasonal patterns of precipitation inputs as well as more variable precipitation events. These climate change‐induced alterations could increase drought and lower soil water availability. Drought could alter rooting patterns and increase the importance of deep roots that access subsurface water resources. To address plant response to drought in both deep rooting and soil water utilization as well as soil drainage, we utilize a throughfall reduction experiment in a loblolly pine plantation of the Southeastern United States to calibrate and validate a hydrological model. The model was accurately calibrated against field measured soil moisture data under ambient rainfall and validated using 30% throughfall reduction data. Using this model, we then tested these scenarios: (a) evenly reduced precipitation; (b) less precipitation in summer, more in winter; (c) same total amount of precipitation with less frequent but heavier storms; and (d) shallower rooting depth under the above 3 scenarios. When less precipitation was received, drainage decreased proportionally much faster than evapotranspiration implying plants will acquire water first to the detriment of drainage. When precipitation was reduced by more than 30%, plants relied on stored soil water to satisfy evapotranspiration suggesting 30% may be a threshold that if sustained over the long term would deplete plant available soil water. Under the third scenario, evapotranspiration and drainage decreased, whereas surface run‐off increased. Changes in root biomass measured before and 4 years after the throughfall reduction experiment were not detected among treatments. Model simulations, however, indicated gains in evapotranspiration with deeper roots under evenly reduced precipitation and seasonal precipitation redistribution scenarios but not when precipitation frequency was adjusted. Deep soil and deep rooting can provide an important buffer capacity when precipitation alone cannot satisfy the evapotranspirational demand of forests. How this buffering capacity will persist in the face of changing precipitation inputs, however, will depend less on seasonal redistribution than on the magnitude of reductions and changes in rainfall frequency.     

Spatial patch structure and adaptive strategy for desert shrub of Reaumuria soongorica in arid ecosystem of the Heihe River Basin

In many arid ecosystems, vegetation frequently occurs in high-cover patches interspersed in a matrix of low plant cover. However, theoretical explanations for shrub patch pattern dynamics along climate gradients remain unclear on a large scale. This context aimed to assess the variance of the Reaumuria soongorica patch structure along the precipitation gradient and the factors that affect patch structure formation in the middle and lower Heihe River Basin (HRB). Field investigations on vegetation patterns and heterogeneity in soil properties were conducted during 2014 and 2015. The results showed that patch height, size and plant-to-patch distance were smaller in high precipitation habitats than in low precipitation sites. Climate, soil and vegetation explained 82.5% of the variance in patch structure. Spatially, R. soongorica shifted from a clumped to a random pattern on the landscape towards the MAP gradient, and heterogeneity in the surface soil properties (the ratio of biological soil crust (BSC) to bare gravels (BG)) determined the R. soongorica population distribution pattern in the middle and lower HRB. A conceptual model, which integrated water availability and plant facilitation and competition effects, was revealed that R. soongorica changed from a flexible water use strategy in high precipitation regions to a consistent water use strategy in low precipitation areas. Our study provides a comprehensive quantification of the variance in shrub patch structure along a precipitation gradient and may improve our understanding of vegetation pattern dynamics in the Gobi Desert under future climate change.

     

基于SPEI的渭河流域干旱时空变化特征分析

以标准化降水蒸散指数（SPEI）作为评估指标，基于渭河流域28个气象站点1961—2017年实测降水量和气温数据，采用Mann-Kendall（M-K）趋势检验、经验正交函数以及小波变换等方法分析渭河流域干旱时空变化特征，并研究渭河流域干旱与6种大尺度气候因子之间的相关关系，进一步探讨主要气候因子对流域干旱时空分布特征的潜在影响。研究表明：渭河流域在1961—2017年间整体呈现出变旱的趋势。通过经验正交函数分解，渭河流域干旱分布场主要有3种典型模态类型，分别为全局型、西北—东南反向分布型以及东—西反向分布型；同时，大尺度气候因子南方涛动指数SOI与流域干旱分布场具有更好的相关关系，对该区域内干旱变化有较强的影响。     

大同—阳高Ms6.1地震前兆综合加权信息熵的变化

利用“地震预报计算机专家系统”的思想对大同 -阳高 Ms6 .1地震前每一前兆异常事件进行综合评估 ,以每一异常的最可能发震时间来计算发震概率 ,利用地震前兆综合加权信息熵研究了系统熵值与地震的关系。对华北地区的地震前兆综合加权信息熵研究表明 ,在大同 -阳高 Ms6 .1地震前 ,信息熵出现了明显的减熵有序变化     

Precipitation patterns in flood season over China associated with the El Niño/Southern Osciliation

The precipitation patterns in flood season over China associated with the El Niño/Southern Oscillation (ENSO) are investigated, especially in the eastern China, using the rather long period rainfall data in this century. The results show that there were remarkable differences between the precipitation patterns in flood seasons of ENSO warm phase (El Niño year) and cold phase (La Niña year), as well as between the patterns in El Niño years and their following years. The most parts of China received below normal rainfall in flood season of the onset years of El Niño events, but the coastal area of Southeast China received above normal amounts. Comparatively, the most parts of China received above normal rainfall in flood season of the following years of El Niño events, but the eastern part of the reaches among the Huanghe (Yellow) River, the Huaihe River and the Haihe River, and the Northeast China received less. During ENSO cold phase, the reaches of the Changjiang (Yangtze) River and the North China received more amounts than normal rainfall in flood season of the onset years of La Niña events, and the other regions of China received less. In the following years of La Niña events, the coastal area of the Southeast China, the most part of the Northeast China and the regions between the Huanghe River and the Huaihe River received more precipitation during flood seasons, but the other parts received below normal precipitation.     

模糊划分矩阵在岩土参数概率分布中的应用

讨论如何在小样本条件下用已有的过程经验与试验资料确定岩土参数概率分布,用模糊划分矩阵与BAYES方法相结合,给出由小样本试验数据确定岩土参数的概率分布。     

雅砻江流域主汛期降水长期预报的一种方法

本文使用天气学方法，从影响雅砻江区域主汛期降水量的长期预报有关因子出发，再运用数理统计方法反复筛选，仅取３个主要因子：西部青藏高原８个站冬春积温，北部冬季极涡面积指数，南部冬季印缅槽平均强度，建立逐步回归预报方程。结果显示：对主汛期６～９月降水量预报拟合准确率为１６／１７即约９４％。回归分析中发现：尽管西太平洋副热带高压对盆地西部降水有很大影响，盛夏且与高原积温有较密切相关，但由放大范围长时段的青藏高原积温，对于雅砻江区域主汛期降水量的影响超过西太平洋副热高压，因而在逐步回归过程中，副高因子仍被剔除．     

Is Precipitation the Dominant Controlling Factor of High Inorganic Nitrogen Content in the Changjiang River and Its Mouth？

The main reasons for the high content of inorganic N and its increase by several times in the Changjiang River and its mouth during the last 40 years were analysed in this work. The inorganic N in precipitation in the Changjiang River catchment mainly comes from gaseous loss of fertilizer N, N resulting from the increases of population and livestock, and from high temperature combustions of fossil fuels. N from precipitation is the first N source in the Changjiang River water and the only direct cause of high content of inorganic N in the Changjiang River and its mouth. The lost N in gaseous form and from agriculture non-point sources fertilizer comprised about 60% of annual consumption of fertilizer N in the Changjiang River catchment and were key factors controlling the high content of inorganic N in the Changjiang River mouth. The fate of the N in precipitation and other N sources in the Changjiang River catchment are also discussed in this paper.     

疏散星团NGC6530天区的恒星自行和成员概率

利用上海天文台的照相底片资料,确定了疏散星团NGC6530天区364颗恒星的自行和成员概率,并对有关自行测定的方法、结果和精度等问题作了较为详细的介绍和讨论。使用的底片历元差为87年,全部恒星自行中误差的均方根值为1．09mas/a。     

概率图解法软件研制及其在东升庙矿床研究中的应用

文章根据概率图解法原理,利用VB可视化编程技术,完成了概率图筛分软件的研制.并通过该软件对东升庙矿床矿石品位混合总体进行筛分处理,探究其成矿期次信息.已有研究结果表明:一次成矿作用形成的矿床,其矿石品位的累积概率图是一条直线.而东升庙矿床的8条代表性勘探线中4种主要成矿元素TS、An、Pb、Cu品位的累积概率图均为曲线且出现明显拐点,经多次作图检验证实有效拐点数为1,由此得到新的成矿期次信息,揭示该矿床经历了两期成矿作用,即中元古代同沉积-海底喷气矿化期和后生改造矿化期,这对于研究其成矿物质来源和成矿机理具有重要的意义.