珠江流域极端降水阈值不确定性分析

全球气候持续变化下。极端水文事件频发且时空分布规律显著变异,极端水文事件阈值及其时空分布不确定性成为当前水文水资源研究领域的热点问题之一。以珠江流域62个雨量站1959～2009年逐日降水序列为样本,运用固定临界值法、百分位值法和极值分布拟合法等方法,探讨了珠江流域极端降水阈值的时空分布规律和不确定性特征。研究表明,在流域尺度上,利用上述方法分析极端降水阈值时,均存在较多不确定性。(1)固定临界值法无法反映流域降水空间分布不均对极端降水阈值的影响;(2)百分位值法受样本容量、百分位值选取标准等影响较大,流域不同地区同一百分位或同一地区不同百分位下极端降水阈值波动幅度较大,易导致降水高值区阈值偏低,降水低值区阂值偏高;(3)极值分布拟合法受极值分布拟合函数类型、样本容量大小等影响较大,拟合精度不高。     

非平稳条件下北京市最大月降水量频率特征分析

为探究气候变化下极端降水的频率变化特征,基于北京市22个雨量站实测月降水量数据,以时间为协变量构建平稳和非平稳GEV模型,对北京市最大月降水量序列(极值降水序列)进行模拟和频率分析,并采用Bootstrap方法对频率分析结果的不确定性进行评价。结果表明:所有极值降水序列的最优概率分布模型均为非平稳GEV模型,该模型能够抓住序列随时间呈显著下降趋势的变化特征;由非平稳GEV模型估算得到的极值降水重现水平随时间呈减少趋势,这意味着未来极值降水导致洪涝灾害的风险在降低,但导致干旱的风险将增加;随着重现期的增加,极值降水重现水平估计值的不确定性也随之增大。     

基于二元混合分布分位数映射法的长江 上游区域气候模式模拟降水偏差校正

采用4组多参数的二元混合分布QM法对RegCM4模式输出的长江中上游流域日降水进行偏差校正，并对不同单分布和混合分布QM法的偏差校正性能进行评估。结果表明：在选取的单分布中，伽马分布对长江上游流域降水的适用性最高，超过50%的降水事件可由其解释，耿贝尔分布适用性最差，仅能解释10%左右的降水事件。采用二元混合分布QM法订正的模拟降水在均方根误差、和方差、相关系数等性能参数整体优于单分布QM法的校正结果。基于伽马-广义极值分布的QM法对流域内降水的订正效果最佳，能显著降低RegCM4模式中模拟的降水湿偏差。     

河北省地质灾害分布特征及预报

利用河北省近40a的地质灾害发生个例资料,分析了地质灾害时空分布特征;进行预报分区,分别找出了各区泥石流临界雨量指标;采用数学决策模型-权重分布集成法,对未来24h降水预报产品、中央台下发的降水指导预报产品、河北省气象台MM5模式降水预报产品、河北省气象台下发的降水指导预报产品等进行降水集成,将各区的降水集成结果及前期降雨量分别与临界雨量指标进行比较,作出地质灾害预报。     

天山乌鲁木齐河源冰雪径流的极值分析

利用乌鲁木齐河源区近20多年的水文气象实测资料, 研究了河源区冰川、季节积雪和夏季降水等形成径流极值(极大值和极小值)的时空变化特征, 并对其产生过程及其与气温、降水等气象要素的关系进行初步分析. 结果表明: 春季(5月)1号冰川水文点和空冰斗水文点极大值径流呈现出轻微增大的趋势, 总控水文点表现为减小的趋势; 夏季(6～8月)径流极大值变化显示, 空冰斗和总控水文点有增大趋势, 1号冰川水文点总体为轻微的减小趋势. 春季径流极值的主要影响因素是气温; 夏季极大值径流是气温和降水综合作用的结果, 而极小值径流主要源于大降水(雪)后的相对较低气温的影响.     

台风活动对中国沿海地区极端降水的影响

基于1961—2020年格点化数据集逐日降水资料及中国气象局台风最佳路径数据集,计算台风降水对中国沿海地区极端降水事件的贡献率;利用混合和单一元统计极值分布模型量化台风对降水极值概率分布的影响,探究其量化结果的影响因素,并通过典型流域进行流域尺度的应用验证。结果表明：从台风降水的贡献来看,台风降水主要影响中国沿海及部分临近沿海的内陆地区的高重现期极端降水事件;在量化台风影响方面,利用考虑台风降水分布的混合元统计极值分布模型可提高研究区大部分地区降水极值概率的估计,并且沿海地区台风降水的影响大于内陆地区,北方沿海地区的影响大于南方各分区;台风极端降水贡献率、台风与非台风降水差异是台风影响中国沿海地区降水极值概率分布的重要因素。     

TRMM遥感降水低估还是高估中国大陆地区的降水?

卫星降水产品在一定程度上为地表观测稀疏地区的降水提供了参照值,但在具体应用时仍需进行适用性和精度评价.为降低不确定性,通行做法是利用地面观测数据对卫星产品进行融合校正,评价和修正卫星降水产品.以TRMM为例,对研究中国大陆范围的融合TRMM降水的公开成果进行了检视,发现不同研究成果结论之间存在不可忽视的方向性相背情况,极大地影响着生产实践应用中对融合产品的可靠性判断.研究认为,这种融合结果相背的现象与融合校正方法关系不大,而与地面降水参照站点选取的范围有密切关系.研究表明,仅靠TRMM卫星降水自身及与地面融合方法的创新,尚不能降低卫星降水产品的不确定性.目前仍需加强对卫星降水融合中地面观测数据的完整性要求,采用多种独立检验方法验证融合结果的一致性和可靠性.     

气候模式应用中的不确定性分析

为了分析和评价气候变化对水文水资源的影响,根据中国东部地区1956～2000年实测年降水量系列数据,采用多年均值、系列趋势变化指标和反映系列可持续特性的Hurst系数等3项指标,对CGCMA3、MPI-ECHAM5和平均GCM等3种气候模式模拟的同期年降水系列数据进行了检验。检验结果表明,3种气候模式模拟结果与实测值之间,以及不同模式模拟结果之间,不仅定量方面差异很大,而且在定性方面甚至出现相悖的结果,不确定性十分显著。同样,根据3种气候模式预测的未来2001～2050年年降水量和季平均气温推得的未来年径流量系列数据,其多年均值、系列趋势变化指标和干旱年年径流量多项指标也存在明显的不确定性。据此对气候模式及其应用提出了相应的建议。     

考虑地层变异和参数空间变异的浅基础承载力可靠度分析

地层不确定性显著影响浅基础承载力，其不确定性主要包括地层变异和参数空间变异性。以往研究已分别研究了地层变异和参数空间变异性对浅基础承载力的影响。旨在建立浅基础承载力的随机概率计算框架，以揭示地层不确定性对浅基础承载能力的影响。其中，使用马尔可夫随机场模拟地层变异。在此基础上，考虑土体参数竖向相关距离的变化，使用对数正态随机场模拟不同地层中土体参数的空间变异性。基于深圳妈湾的钻孔和土体参数数据，根据所提出的计算框架进行浅基础承载力分析。使用子集模拟方法加速计算各方案的可靠度，提出了缩小系数对计算结果进行不同程度的缩减以达到简化考虑空间变异性的效果。定义了贡献率指标以定量计算地层变异和参数空间变异性对浅基础承载力计算结果的影响。结果表明，如果不考虑地层不确定性，传统确定性的承载力计算会高估浅基础的承载力。当钻孔数量较少时，地层变异对承载力计算起主要影响；当钻孔数量充足时，则由参数空间变异主导。     

珠江流域降水集中度时空变化特征及成因分析

基于珠江流域内43个常规气象站点1960~2012年的逐日降水资料,计算了流域内各站点长期降水集中度(LCI)和逐年降水集中度(ACI);采用Mann-Kendall趋势检验法和Sen’s坡度检验法检测ACI时间上的变化趋势;同时采用反距离权重插值法(IDW)对LCI的区域特征和ACI的变化趋势进行空间插值以分析降水集中度的时空分布规律;采用随机森林(RF)算法对降水集中度的影响因子进行重要度分析。结果表明:(1)珠江流域逐年降水集中度ACI的年际变化不明显,东南部呈上升趋势,西北部呈下降趋势;(2)珠江流域西北部长期降水集中度LCI值偏小,即降水分布较平均;东南部长期降水集中度LCI值偏大,即降水较集中,表明该地区降水极值情况发生的几率相对较高,该空间分布趋势可能是受距离海洋的远近及海拔的影响;(3)众多气候影响因子中,东亚夏季季风(EASMI)对珠江流域的降水集中度影响最明显。     

地球空间数据集成多尺度问题基础研究

多尺度数据集成是地球空间数据集成中最难处理的问题。将多尺度数据的集成分解为空间和时间多尺度数据集成,在分析应用项目对数据尺度需求的基础上,就两种多尺度数据集成的传统和数据意义上的集成方法进行了详细的探讨。     

Multi-scale Characteristics and Comprehensive Evaluation of Precipitation Heterogeneity in Guangxi

Aiming at the uneven spatial and temporal distribution of precipitation and frequent occurrence of drought and waterlogging disasters in Guangxi, the multi-scale characteristics and comprehensive evaluation of precipitation heterogeneity can provide scientific support for regional response to drought and waterlogging disasters and intelligent management of water resources. Based on the daily precipitation data of 87 grid points from 1961 to 2017 in Guangxi, the Precipitation Concentration Degree (PCD) and Precipitation Concentration Period (PCP) index were used to build day, pentad, ten days, month, season precipitation heterogeneity of multiple time scale level evaluation system. By using R/S analysis and geographical spatial analysis methods, the space-time evolution characteristics and climate division in Guangxi were discussed. The study showed that the spatial and temporal variation characteristics of PCD and PCP at the diurnal, synoptic and monthly scales were relatively consistent, and the heterogeneity of precipitation in Guangxi could be better expressed than that at the monthly and seasonal scales. The diachronic change of PCD in precipitation in Guangxi shows an increasing trend in northeast China and a decreasing trend in southwest China, and the trend of its future period is the same as the diachronic evolution. The spatial distribution of PCD in Guangxi has significant spatial autocorrelation and stratification heterogeneity, which are mainly reflected in the mean value, coefficient of variation and frequency of PCD. The comprehensive heterogeneity of precipitation in Guangxi is highly dispersed in the northeast, highly concentrated in the south, and slightly concentrated or dispersed in the northwest and central regions. The time-scale within a month is the best scale to express the non-uniformity of precipitation in Guangxi. If the advantages of more stable climatic and ten-day scales and more fine daily scales are taken into account, the use of climatic scale for daily sliding calculation and analysis will be the best way.     

An analysis of water column distributions in Florida Bay

Florida Bay is a shallow, semi-enclosed lagoon that has recently experienced significant changes to its ecosystem. These include increased turbidity and the occurrence of cyanobacteria blooms in the central region of the bay. To accurately understand these changes we need to understand the spatial and temporal patterns in observed water quality parameters. To this end, we have used empirical orthogonal functions (EOFs) to analyze both the spatial and temporal variability in an 8-yr record of water quality variables. We have used the EOFs in two ways, one highlighting local changes occurring in the bay, the other emphasizing changes occurring on a bay-wide scale. The local analysis shows that the central region of the bay has the greatest variability in water quality parameters, especially with respect to chlorophyll and nutrient concentrations. The bay-wide analysis shows a different picture. The chlorophyll blooms in the central bay are not apparent bay-wide indicating that they are a local manifestation of processes occurring on a bay-wide scale. The spatial and temporal patterns for nitrate are dissimilar from the other nutrients raising the possibility that the mechanisms controlling nitrate differ from those controlling other nutrients. On a bay-wide scale, spatial patterns are similar to distributions of sediment type and show the significance of interactions between the water column and benthos. Time-series analysis of the EOFs shows that the dominant variation of many water quality parameters is seasonal, even though a system-wide shift occurred between 1994–1995 corresponding to an increase in rainfall and runoff from the Everglades.     

Spatial modelling and uncertainty assessment of pyroclastic cover thickness in the Sorrento Peninsula

Assessing spatial variability of soil thickness is a critical issue for understanding and predicting slope processes. The present work was aimed at estimating the spatial scales at which the variation of pyroclastic cover thickness occurs in a sample area in the Sorrento Peninsula (Italy). Stochastic simulation was used to understand the spatial variability of pyroclastic cover thickness on Mount Pendolo and to assess its spatial uncertainty. In the study area, covering about 0.7 km², thickness measurements were collected using electrical resistivity tomography profiles, continuous core drillings and steel rod penetrometric tests. Variographic analysis revealed the occurrence of an anisotropic behaviour along the N50 and N140 directions. In the latter anisotropic direction, a nested variogram was fitted including (1) a long-range component which could be related to large-scale factors, like the curvature of the slope and contributing area and (2) a shorter scale variation which is probably associated with the occurrence of denudation processes or to the articulate cover/bedrock interface. To assess the spatial variability and uncertainty of pyroclastic cover thickness, a stochastic simulation algorithm was used and 500 equally probable images of cover thickness were yielded. The results showed that a better thickness distribution map can be drawn by simulating the data collected on the slope and at the footslope separately. The approach also allowed delineating the areas characterized by greater uncertainty, suggesting supplementary measurements to further improve the cover thickness distribution model, thus reducing the uncertainty.     

Power spectrum of brightness temperature fluctuations derived from solar eclipse observations at 2.8 GHz

In this paper we report on the MEM power spectrum analysis of brightness temperature fluctuations observed at 2.8 GHz during the total solar eclipse of 16 February 1980. The observed periodicities range from 3.5 min to 64 min. These periodicities may arise due to spatial and/or temporal variations in the solar radio emission. The observed periodicities imply presence of scale sizes ranging from 70,000 to 600,000 km assuming that the brightness fluctuations arise because of spatial variation only. On the other hand, if these fluctuations are due to temporal variation, the observed periodicities correspond well to predicted modes of solar global oscillations.     

基于多源、 多时相遥感影像的高原湖泊提取及其不确定性——以西藏羊卓雍错流域为例

基于野外实地考察, 以西藏中南部羊卓雍错流域为例, 探讨了基于多源、 多时相遥感影像的高原湖泊提取. 目前计算机辅助分类方法在高原湖泊提取上存在很大的局限性, 目视解译方法虽然繁琐, 但能结合丰富的经验信息, 故而成为当今高原湖泊提取的较为现实与可行的方法. 为此, 针对各季湖面特征的不同相态, 结合图像增强技术、 DEM等辅助信息和野外实地验证, 建立了高原湖泊不同时相的遥感解译标志. 根据1972-2009年Landsat、 CBERS和HJ-1A/1B等3种不同数据源的37幅遥感影像提取了流域内主要湖泊, 并分析了湖泊面积的年内与年际变化. 在此基础上, 讨论了高原湖泊提取过程的不确定性, 包括遥感影像甄选、 几何校正误差、 数字化容差和目视解译经验等给结果带来的不确定性. 结果表明: 引入高分辨率、 多源遥感影像以及不受天气状况影响的微波影像有助于高原湖泊变化监测能力与解译精度的提高; 而综合考虑地形信息、 湖泊不同时相特征, 适用于多种数据源的计算机自动解译算法研发, 将提高长时间序列高原湖泊提取的效率.     

多元平稳随机过程游程计算方法的探讨及其应用

在一元平稳随机过程游程理论的基础上,提出了多元平稳随机过程游程分析方法,并推导出一系列计算公式。多元平稳随机过程可以划分为四种类型,即:空间和时间均独立的多元平稳随机过程;空间独立,时间相依的多元平稳随机过程;空间相依,时间独立的多元平稳随机过程;空间和时间均相依的多元平稳随机过程。采用统计试验法验证了公式的正确性。将理论方法应用于黄河流域历史干旱重演特性的研究,结果表明:黄河中下游同步发生年干旱现象的重现期为5.78年,连续1年以上发生的重现期为7.76年,连续3年以上出现的重现期为110年左右。     

Equilibrium modeling of U(VI) speciation in high carbonate groundwaters: Model error and propagation of uncertainty

Remediation of U-contaminated sites relies upon thermodynamic speciation calculations to predict U(VI) movement in the subsurface. However, reliability and applicability of geochemical speciation and reactive transport models may be limited by determinate (model) errors and random (uncertainty) errors in the equilibrium speciation calculations. This study examines propagated uncertainty in two types of subsurface calculations: I. Dissolved U(VI) speciation based on measured analytical constraints and solution phase equilibria and II. Overall U(VI) speciation which combined the dissolved phase equilibria with previously published adsorption reactions. Three levels of uncertainty, instrumental uncertainty, temporal variation and spatial variation across a site, were investigated using first-derivative sensitivity calculations and Monte Carlo simulations. Dissolved speciation calculations were robust, with minimal amplification of uncertainty and normal output distributions. The most critical analytical constraints in the dissolved system are pH, DIC, total U and total Ca, with some effect from dissolved . When considering adsorption equilibria, calculations were robust with respect to adsorbed U(VI) concentration prediction, but bimodal distributions of dissolved U(VI) concentrations were observed in simulations with background levels of total U(VI) and higher (spatial and temporal variability) estimates of input uncertainty. Consequently, sorption model predictions of dissolved U(VI) may not be robust with respect these higher levels of uncertainty.     

Seagrass patches and landscapes: The influence of wind-wave dynamics and hierarchical arrangements of spatial structure on macrofaunal seagrass communities

The spatial arrangement of seagrass beds varies from scales of centimeters to meters (rhizomes, shoot groups), meters to tens of meters (patches), to tens of meters to kilometers (seagrass landscapes). In this study we examine the role of patch scale (patch size, seagrass % cover, seagrass biomass), landscape scale (fractal geometry, patch isolation) and wave exposure (mean wind velocity and exceedance) variables in influencing benthic community composition in seagrass beds at three intertidal sites in northern New Zealand (two sites in Manukau Harbour and one site in Whangapoua Harbour). Analysis of univariate community measures (numbers of individuals and species, species richness, diversity and evenness) and multivariate analyses indicated that there were significant differences in community composition inside and outside of seagrass patches at each of the three sites. Partialling out the spatial and temporal components of the ecological variation indicated that seagrass patch variables explained only 3–4% of the patch scale variation in benthic community composition at each of the sites. The temporal component was more important, explaining 12–14% of the variation. The unexplained variation was high (about 75%) at all three sites, indicating that other factors were influencing variation in community composition at the scale of the patches, or that there was a large amount of stochastic variation. Landscape and wave exposure variables explained 62.5% of the variation in the species abundance data, and the unexplained variation at the landscape level was correspondingly low (12%). Canonical correspondence analysis produced an ordination that suggests that, while mean wind velocity and exceedance were important in explaining the differences between the communities in the two harbours, spatial patterning of the habitat, primarily fractal dimension, and secondarily patch isolation (or some factors that were similarly correlated), were important in contributing to variability in community composition at the two sites in Manukau Harbour. This study suggests that spatial patterning of seagrass habitat at landscape scales, independent of the patch scale characteristics of the seagrass beds, can affect benthic community composition. Community composition inside and outside seagrass habitats involves responses to seagrass bed structure at a series of hierarchical levels, and we need to consider more than one spatial scale if we are to understand community dynamics in seagrass habitats.     

Uncertainty Analysis of the Parameters of the Temperature-index Method: A Case Study of Shiyi Glacier in Qilian Mountains

In order to assess the performance of the common temperature-index melt model at both spatial and temporal scale in Qilian Mountains, we performed the sensitivity and uncertainty analysis on the parameters of a common temperature-index method and evaluated the glacier mass balance on a small alpine glacier, which is separated into two relatively independent branches, with the daily mass balance and the meteorological data in the summer of 2011 and 2012. Sensitivity analysis was conducted by perturbation analysis and uncertainty analysis was carried out by Generalized Likelihood Uncertainty Estimation (GLUE) for different conditions. The results showed that the temperature-index method could properly capture the diurnal variability of the glacier mass balance. But strong equifinality of model parameter existsed in model calibration due to the uncertainty in the parameters. The model was very sensitive to changes in the value of K_ice, followed by the K_snow and T_s. It was also found that the GLUE approaches could estimate and derive the posterior distributions of 3 parameters properly. Moreover, there existed an acceptable range, which ensured high precision under different conditions.