A nonstationary extreme value distribution for analysing the cessation of karst spring discharge

The effects of climate change and population growth in recent decades are leading us to consider their combined and potentially extreme consequences, particularly regarding hydrological processes, which can be modeled using a generalized extreme value (GEV) distribution. Most of the GEV models were based on a stationary assumption for hydrological processes, in contrast to the nonstationary reality due to climate change and human activities. In this paper, we present the nonstationary generalized extreme value (NSGEV) distribution and use it to investigate the risk of Niangziguan Springs discharge decreasing to zero. Rather than assuming the location, scale, and shape parameters to be constant as one might do for a stationary GEV distribution analysis, the NSGEV approach can reflect the dynamic processes by defining the GEV parameters as functions of time. Because most of the GEV model is designed to evaluate maxima (e.g. flooding, represented by positive numbers), and spring discharge cessation is a ?minima’, we deduced an NSGEV model for minima by applying opposite numbers, i.e. negative instead of positive numbers. The results of the model application to Niangziguan Springs showed that the probability of zero discharge at Niangziguan Springs will be 1/80 in 2025, and 1/10 in 2030. After 2025, the rate of decrease in spring discharge will accelerate, and the probability that Niangziguan Springs will cease flowing will dramatically increase. The NSGEV model is a robust method for analysing karst spring discharge. Copyright © 2013 John Wiley & Sons, Ltd.     

Spatiotemporal variability in hydrochemistry of shallow groundwater in a small pre‐alpine catchment: The importance of landscape elements

Topography and landscape characteristics affect the storage and release of water and, thus, groundwater dynamics and chemistry. Quantification of catchment scale variability in groundwater chemistry and groundwater dynamics may therefore help to delineate different groundwater types and improve our understanding of which parts of the catchment contribute to streamflow. We sampled shallow groundwater from 34 to 47 wells and streamflow at seven locations in a 20‐ha steep mountainous catchment in the Swiss pre‐Alps, during nine baseflow snapshot campaigns. The spatial variability in electrical conductivity, stable water isotopic composition, and major and trace ion concentrations was large and for almost all parameters larger than the temporal variability. Concentrations of copper, zinc, and lead were highest at sites that were relatively dry, whereas concentrations of manganese and iron were highest at sites that had persistent shallow groundwater levels. The major cation and anion concentrations were only weakly correlated to individual topographic or hydrodynamic characteristics. However, we could distinguish four shallow groundwater types based on differences from the catchment average concentrations: riparian zone‐like groundwater, hillslopes and areas with small upslope contributing areas, deeper groundwater, and sites characterized by high magnesium and sulfate concentrations that likely reflect different bedrock material. Baseflow was not an equal mixture of the different groundwater types. For the majority of the campaigns, baseflow chemistry most strongly resembled riparian‐like groundwater for all but one subcatchment. However, the similarity to the hillslope‐type groundwater was larger shortly after snowmelt, reflecting differences in hydrologic connectivity. We expect that similar groundwater types can be found in other catchments with steep hillslopes and wet areas with shallow groundwater levels and recommend sampling of groundwater from all landscape elements to understand groundwater chemistry and groundwater contributions to streamflow.     

Impact of climate indicators on continental‐scale potential groundwater recharge in Africa

In the last decades, human activity has been contributing to climate change that is closely associated with an increase in temperatures, increase in evaporation, intensification of extreme dry and wet rainfall events, and widespread melting of snow and ice. Understanding the intricate linkage between climate warming and the hydrological cycle is crucial for sustainable management of groundwater resources, especially in a vulnerable continent like Africa. This study investigates the relationship between climate‐change drivers and potential groundwater recharge (PGR) patterns across Africa for a long‐term record (1960–2010). Water‐balance components were simulated by using the PCR‐GLOBWB model and were reproduced in both gridded maps and latitudinal trends that vary in space with minima on the Tropics and maxima around the Equator. Statistical correlations between temperature, storm occurrences, drought, and PGR were examined in six climatic regions of Africa. Surprisingly, different effects of climate‐change controls on PGR were detected as a function of latitude in the last three decades (1980–2010). Temporal trends observed in the Northern Hemisphere of Africa reveal that the increase in temperature is significantly correlated to the decline of PGR, especially in the Northern Equatorial Africa. The climate indicators considered in this study were unable to explain the alarming negative trend of PGR observed in the Sahelian region, even though the Standardized Precipitation‐Evapotranspiration Index (SPEI) values report a 15% drought stress. On the other hand, increases in temperature have not been detected in the Southern Hemisphere of Africa, where increasing frequency of storm occurrences determine a rise of PGR, particularly in southern Africa. Time analysis highlights a strong seasonality effect, while PGR is in‐phase with rainfall patterns in the summer (Northern Hemisphere) and winter (Southern Hemisphere) and out‐of‐phase during the fall season. This study helps to elucidate the mechanism of the processes influencing groundwater resources in six climatic zones of Africa, even though modelling results need to be validated more extensively with direct measurements in future studies. Copyright © 2016 John Wiley & Sons, Ltd.     

Frequency analysis of nonstationary annual maximum flood series using the time‐varying two‐component mixture distributions

The most popular practice for analysing nonstationarity of flood series is to use a fixed single‐type probability distribution incorporated with the time‐varying moments. However, the type of probability distribution could be both complex because of distinct flood populations and time‐varying under changing environments. To allow the investigation of this complex nature, the time‐varying two‐component mixture distributions (TTMD) method is proposed in this study by considering the time variations of not only the moments of its component distributions but also the weighting coefficients. Having identified the existence of mixed flood populations based on circular statistics, the proposed TTMD was applied to model the annual maximum flood series of two stations in the Weihe River basin, with the model parameters calibrated by the meta‐heuristic maximum likelihood method. The performance of TTMD was evaluated by different diagnostic plots and indexes and compared with stationary single‐type distributions, stationary mixture distributions and time‐varying single‐type distributions. The results highlighted the advantages of TTMD with physically‐based covariates for both stations. Besides, the optimal TTMD models were considered to be capable of settling the issue of nonstationarity and capturing the mixed flood populations satisfactorily. Copyright © 2016 John Wiley & Sons, Ltd.     

AEKF在星敏感器低频误差补偿中的应用

高分辨率对地观测卫星需要精确的姿态信息来满足后续对地定位等工作,因此姿态确定精度十分重要。星敏感器的低频误差是影响卫星姿态确定精度的重要因素之一,主要是由空间周期性的热环境变化引起的。为进一步提高卫星姿态确定精度,对星敏感器的低频误差产生机理即星敏感器主光轴做周期性扰动进行了分析,设计了星敏感器低频误差补偿方案,建立了考虑星敏感器低频误差在内的组合定姿模型,利用拓维卡尔曼滤波(AEKF)对低频误差进行补偿,并引入RTS平滑滤波进一步提高姿态确定精度。仿真实验表明,设计的星敏感器低频误差补偿方案能有效对其进行补偿,提高卫星姿态确定精度。     

青海省祁漫塔格地区1∶5万水系沉积物测量衬值异常圈定实例

青海省祁漫塔格地区位于柴达木盆地西南缘,是青海省重要的铁多金属成矿基地之一。利用88442个野外采样点1∶5万水系沉积物测量数据,采用Geo Expl软件圈定了该地区的衬值异常。衬值是指各元素0.5 km×0.5 km网格化数据与其园域搜索半径5km、移动步长0.5km移动平均值的比值。选用自定义累频"90、95、98、100"确定了异常的外、中、内带。通过常规方法和衬值圈定的异常的对比,表明衬值异常能够削弱不同地质背景差异,使异常形态更为规整,浓集中心更为明显,并且可能发现新异常。     

Impact of the Pacific–Japan Teleconnection Pattern on July Sea Fog over the Northwestern Pacific: Interannual Variations and Global Warming Effect

The northwestern Pacific(NWP) is a fog-prone area, especially the ocean east of the Kuril Islands. The present study analyzes how the Pacific–Japan(PJ) teleconnection pattern influences July sea fog in the fog-prone area using independent datasets. The covariation between the PJ index and sea fog frequency(SFF) index in July indicates a close correlation, with a coefficient of 0.62 exceeding the 99% confidence level. Composite analysis based on the PJ index, a case study, and model analysis based on GFDL-ESM2 M, show that in high PJ index years the convection over the east of the Philippines strengthens and then triggers a Rossby wave, which propagates northward to maintain an anticyclonic anomaly in the midlatitudes,indicating a northeastward shift of the NWP subtropical high. The anticyclonic anomaly facilitates the formation of relatively stable atmospheric stratification or even an inversion layer in the lower level of the troposphere, and strengthens the horizontal southerly moisture transportation from the tropical–subtropical oceans to the fog-prone area. On the other hand, a greater meridional SST gradient over the cold flank of the Kuroshio Extension, due to ocean downwelling, is produced by the anticyclonic wind stress anomaly. Both of these two aspects are favorable for the warm and humid air to cool, condense, and form fog droplets, when air masses cross the SST front. The opposite circumstances occur in low PJ index years, which are not conducive to the formation of sea fog. Finally, a multi-model ensemble mean projection reveals a prominent downward trend of the PJ index after the 2030 s, implying a possible decline of the SFF in this period.     

年最大值抽样估算的暴雨频率设计值的低估问题探讨

由年最大值抽样（AMS）和年超大值抽样（AES）的基本理论及重现期（RP）的定义可知,AMS并不符合以“事件”为基础的重现期的定义.以美国西南半干旱区1438个雨量站和太湖流域96个雨量站的降雨资料为例,通过经验频率与超过概率的比较,发现AMS估算的暴雨频率设计值偏小,尤其是对常遇频率降雨设计值的影响更加显著.美国的降雨量资料站点多、系列长,实际资料验证与理论分析一致.通过对太湖流域AMS资料的分布形态进行分析的结果表明：太湖流域的站点不多,资料长度不够,且大部分站点在雨量大值区数据稀少,使得频率直方图不连续,是造成我国太湖流域的资料验证效果不理想的可能原因.     

1951—2015年乌鲁木齐市升温过程频数及强度气候特征

利用乌鲁木齐市气象站1951年1月1日至2015年12月31日的逐日气温资料,以日最高气温及其升温幅度为指标,整理出乌鲁木齐市近65年升温过程数据库,将升温过程分为Ⅰ级(弱)、Ⅱ级(中等强度)、Ⅲ级(较强)、Ⅳ级(强)以及Ⅴ级(极强)5个等级,分析了乌鲁木齐市各级升温过程发生频数、持续日数、过程不同时段升温幅度、过程最高气温、过程最高气温距平偏高幅度等要素气候特征。结果如下：(1)1951—2015年,乌鲁木齐市出现升温过程5677次,平均每年87.3次,其中Ⅰ级(弱)升温过程占67.8 %。升温过程发生频数的季节分布较均匀,但在春季相对较多。近65年来,年平均升温过程发生频数在7个年代际中差异不大,没有明显的线性变化趋势。(2)1951—2015年,乌鲁木齐市5677次升温过程的平均持续日数为2.14?d,其中持续1 d的过程占43.0 %。随升温过程等级由Ⅰ级到Ⅴ级提高,过程持续日数最高出现频率也从1?d过渡到3?d。升温过程持续日数在春季4、5月份最长。(3)1951—2015年,乌鲁木齐市过程升温幅度平均为5.76℃,在春季最大、秋季最小。Ⅳ级(强)以及Ⅴ级(极强)的过程升温幅度最大的月份分别是5月和3月。65年来,乌鲁木齐市升温过程的最大24h、48h和72h升温幅度平均值分别为3.72℃、6.12℃和8.23℃,最大24 h升温幅度在冬季最大、夏季最小,最大48 h和72 h升温幅度都是在春季最大、秋季最小。(4)1951—2015年,乌鲁木齐市升温过程的最高气温平均值为14.52℃,在夏季7、8月最高,在冬季各月最低,带有显著的季节背景特征。过程最大日气温距平的平均值为2.93℃。Ⅳ级(强)和Ⅴ级(极强)升温过程的日气温距平偏高幅度最大月份分别出现在1月(11.73℃)和12月(19.10℃)。     

时变参数灰色模型背景值重构及实现

针对时变参数灰色模型PGM(1,1)的背景值重构收敛速度及稳定性问题,该文运用积分的方法综合序列在Δt内不同变化趋势,导出背景值模型的准确表达式。实现了反映序列对新老信息偏爱程度的最优权值介于(0,1)内,且非不能越过某一阈值;给出了背景值重构模型最优解准确求取的具体算法步骤。基于MATLAB语言的实验结果表明:改进模型预测精度高,易于实现;所研究的带权灰色模型GM(1,n)背景值模型的重构及计算方法验证了PGM(1,1)模型重构及计算实现方法的有效性和实用性。