Geostatistical Uncertainty Modelling for the Environmental Hazard Assessment During Single Erosive Rainstorm Events

This paper presents an environmental hazard assessment to account the impacts of single rainstorm variability on river-torrential landscape identified as potentially vulnerable mainly to erosional soil degradation processes. An algorithm for the characterisation of this impact, called Erosive Hazard Index (EHI), is developed with a less expensive methodology. In EHI modelling, we assume that the river-torrential system has adapted to the natural hydrological regime, and a sudden fluctuation in this regime, especially those exceeding thresholds for an acceptable range of flexibility, may have disastrous consequences for the mountain environment. The hazard analysis links key rainstorm energy variables expressed as a single-storm erosion index (EI_sto), with impact thresholds identified using an intensity pattern model. Afterwards, the conditional probabilities of exceeding these thresholds are spatially assessed using non-parametric geostatistical techinques, known as indicator kriging. The approach was applied to a test site in river-torrential landscape of the Southern Italy (Benevento province) for 13 November 1997 rainstorm event.     

川中丘陵县域土壤pH空间变异及影响因素分析——以四川仁寿县为例

利用2012年在仁寿县采集的555个表层土样(0~20cm),应用地统计学方法分析了该县域尺度表层土壤pH值的空间变异特征;并采用方差分析和回归分析量化主要影响因素对土壤pH值空间变异的影响程度。结果表明:研究区土壤pH值在4.02~8.14之间,平均为6.80,总体上以中性和碱性土壤为主;变异系数为14.48%,属中等程度的空间变异性。地统计分析表明,研究区土壤pH值变异函数的最佳理论模型为球状模型,具有中等程度的空间自相关性,且空间自相关范围较大。方差分析和回归分析表明,土壤类型、成土母质和土地利用方式是显著影响土壤pH值的主要因素。其中,成土母质和土地利用方式分别能独立解释76.2%和4.8%的土壤pH值空间变异。土壤类型的解释能力与分类级别有关,土类、亚类和土属可分别独立解释41.3%、57.3%和83.7%的土壤pH值空间变异,因而能反映成土过程和母质特性的土属是研究区土壤pH值空间变异的主控因素。研究结果可为川中丘陵县域尺度土壤pH空间变异分析及区域生态环境管理与建设提供有益参考。     

典型小城市土壤重金属空间异质性及其风险评价:以临安市为例

城市土壤是城市生态系统不可分割的一部分,与城市居民的人体健康和生活质量密切相关.本研究以浙江省典型小城市——临安市为研究样区,共采集62个土壤表层样品(0~15 cm,样品采样密度:5个·km~(-2)),基于多元统计学、地统计学结合GIS技术研究该地区土壤重金属的污染特征、空间变异结构与分布规律.土壤重金属Mn全量、Cu全量、Zn全量、Pb全量、Cr全量、Cd全量的平均含量分别为439.42、42.23、196.80、62.55、63.65、0.22 mg·kg~(-1),与浙江省土壤背景值及环境质量标准相比较,这些重金属在临安市存在不同程度的累积,局部污染严重.单个重金属潜在生态风险危害指数表明,Pb的潜在生态危害指数最高.p H与大部分重金属全量以及重金属全量之间存在显著相关关系.研究区土壤Pb、Zn和Cu主要来自于城市交通运输工具的使用和尾气排放,而Mn和Cr主要来自于母岩,Cd主要由市区工厂的长期有害物质排放.研究区土壤重金属全量及其有效态均具有较强的空间自相关性[C_0/(C_0+C)50%],其空间分布特征受人为活动的影响极为明显.     

上海宝山区农用土壤重金属分布与来源分析

以上海宝山区为典型区域,在获取216个农用表层土壤样品重金属实测数据的基础上,运用多元统计和地统计相结合的方法,对上海宝山区农用土壤重金属的含量水平、分布特征和来源进行系统分析.结果表明,上海市宝山区农用土壤重金属Cd、Hg、As、Cr、Pb、Cu、Zn的平均含量值分别为0.195、0.148、7.44、82.5、29.1、33.2、124.5 mg.kg-1,均没有超过国家土壤环境质量二级标准,但Cd、Zn、Cr、Pb、Cu、Hg元素平均含量值超过上海市土壤背景值,其中Cd、Hg、Zn最为显著,分别是对应背景值的1.50、1.48、1.45倍,呈现出明显的累积趋势.相关分析和因子分析结果显示,各元素的来源可分为三类,Zn、Cd、Hg和Pb为一类,Cr和Cu为一类,As单独为一类;前两类元素含量远高于对应元素背景值,来源主要受各种人为活动影响,As元素含量与背景值相当,各样品含量的变异程度最低,来源主要与成土母质有关.空间结构分析表明,As元素以土壤母质、地形等结构性变异为主,其它元素主要受人为活动等随机因子影响;通过对临界值概率等值线的分布分析发现,Cd、Zn、Cr、Cu、Hg来源以点源为主,来源较为集中,Pb来源相对较为分散.     

Modis reflectance and active fire data for burn mapping and assessment at regional level

This paper presents an algorithm for rapid and accurate burn mapping that is applied here to the forest fires occurred in Galicia (northwest Spain) in August 2006, when nearly 930 km² were almost entirely burned over the course of eight days. The algorithm synergistically combines remotely-sensed reflectance and active fire data as measured by the MODIS (MODerate resolution Imaging Spectrometer) sensor on board Terra and Aqua NASA (National Aeronautics and Space Administration) satellites. Burned area data collected from this work was compared to official fires statistics from the Spanish Ministry of Environment and to perimeters that were derived using a high spatial resolution satellite image. In a later step, burn patches area analyzed using information from the National Forest Map (1:50,000) and some Geographical Information Systems (GIS) tools.     

基于地统计模型的上海大气污染物多建模方法的比较

地统计模型被广泛应用于环境空气污染物暴露模拟,但不同建模方法及其模拟结果之间的对比研究较少.基于上海2016~2019年55个环境空气监测点位的NO₂和PM_2.5观测数据,以及交通路网、排放源兴趣点和卫星数据等地统计变量,应用偏最小二乘回归（PLS）、监督学习线性回归（SLR）和机器学习随机森林（RF）这3种建模方法创建年暴露模型,并进一步应用普通克里金插值（OK）法分析模型残差,构建复合模型.应用交叉验证对模型的模拟效果进行检验,选取每一种建模方法的最优模型结构（是否应用OK）作为最终模型.结果表明,NO₂模型中表现最好的是RF-OK （R_mse²为0.70~0.82）和PLS-OK模型（R_mse²为0.78~0.84）;PM_2.5模型中PLS模型（R_mse²为0.62~0.71）优于SLR-OK （R_mse²为0.40~0.79）和RF-OK （R_mse²：0.31~0.56）模型.应用3种建模方法对上海1 km网格开展年暴露模拟和对比,NO₂模型间模拟结果的相关性（r为0.82~0.91）高于PM_2.5模拟结果的相关性（r为0.66~0.96）.基于3种模型2019年的模拟结果,评估了上海NO₂和PM_2.5的人群暴露水平.     

引黄灌区不同尺度农田土壤重金属空间分布及污染评价：以银川市兴庆区为例

确定农田土壤重金属分布及其污染状况,对于评价农业生态环境质量、保障食品安全和人类健康都具有重要作用.以宁夏引黄灌区农田土壤为研究对象,在10 m(L尺度)和1 m(M尺度)两种尺度上网格取样,共取耕层土样(0~20 cm)223个,利用经典统计和地统计相结合的方法对土壤铜(Cu)、锌(Zn)、铬(Cr)、镉(Cd)和铅(Pb)的空间变异性进行研究,并利用单因子指数(Pi)和内梅罗综合指数(P综)评价土壤重金属的污染程度.结果表明,两种尺度下,Cu、Zn、Cr、Cd、Pb均属中等变异性,其变异系数(CV)顺序为:Cd>Pb>Cr>Zn>Cu.地统计分析表明,L尺度下Cd和M尺度下Pb块金系数为100%,表现为纯块金效应,主要受随机因素影响,具较弱的空间相关性.其它重金属元素在两种尺度下块金系数均小于25%,说明主要受结构性因素的影响,具有强烈的空间相关性.结合Pi和P综值可知,两种尺度下除了Cu外,其它4种重金属元素出现轻度污染的样点数较多,表明研究区已出现重金属富集的趋势.     

土壤污染调查加密布点优化方法构建及验证

鉴于传统调查布点方法对土壤污染物平均含量的估计精度较高,但对污染区范围的估计精度不能满足修复治理需求的问题,同时,为了准确估计土壤污染区面积及其空间位置,提出了土壤污染详查样点优化方法.在初步调查的基础上,首先利用地统计条件模拟方法预测土壤污染概率,基于污染概率和土壤污染物含量局部空间变异确定加密布点的优先区域,并根据污染物含量的空间变化趋势布设样点,然后根据优化后的土壤污染调查布点方案估计污染区面积和空间位置.最后,以某Cd污染场地为例,验证了布点优化方法的效果.结果表明,土壤污染调查加密布点方法显著提高了污染区面积及其空间位置的估计精度.案例场地土壤Cd污染区面积的预测误差为4.10%,污染区空间位置的精度为86.10%.土壤污染调查布点优化方法在保证土壤污染调查精度的同时,相比于传统调查方法可显著降低土壤污染调查的样本量.     

某重金属污染场地典型物质浓度空间分布研究

以上海某重金属污染场地为例,运用地统计方法探索了研究区内三种典型物质(Cu、Sb和Ni)的空间变异特征、分布特征和相关关系.结果表明,受人为作用下的随机因素影响,三种重金属浓度分布的空间变异性较强,占场地面积80%范围内的三种重金属浓度超过背景值,占场地面积21.37%和23.33%的Sb和Ni超过上海市敏感用地筛选值,且表层污染范围大于深层,主要分布于原冶炼车间和机械加工车间.此外Sb和Ni分别与Cu表现出显著的共生关系.     

GEOSTATISTICAL ESTIMATION OF HORIZONTAL HYDRAULIC CONDUCTIVITY FOR THE KIRKWOOD‐COHANSEY AQUIFER1

ABSTRACT: The Kirkwood‐Cohansey aquifer has been identified as a critical source for meeting existing and expected water supply needs for southern New Jersey. Several contaminated sites exist in the region; their impact on the aquifer has to be evaluated using ground water flow and transport models. Ground water modeling depends on availability of measured hydrogeologic data (e.g., hydraulic conductivity, for parameterization of the modeling runs). However, field measurements of such critical data have inadequate spatial density, and their locations are often clustered. The goal of this study was to research, compile, and geocode existing data, then use geostatistics and advanced mapping methods to develop a map of horizontal hydraulic conductivity for the Kirkwood‐Cohansey aquifer. Spatial interpolation of horizontal hydraulic conductivity measurements was performed using the Bayesian Maximum Entropy (BME) Method implemented in the BMELib code library. This involved the integration of actual measurements with soft information on likely ranges of hydraulic conductivity at a given location to obtain estimate maps. The estimation error variance maps provide an insight into the uncertainty associated with the estimates, and indicate areas where more information on hydraulic conductivity is required.