Investigating outliers to improve conceptual models of bedrock aquifers

Numerical models play a prominent role in hydrogeology, with simplifying assumptions being inevitable when implementing these models. However, there is a risk of oversimplification, where important processes become neglected. Such processes may be associated with outliers, and consideration of outliers can lead to an improved scientific understanding of bedrock aquifers. Using rigorous logic to investigate outliers can help to explain fundamental scientific questions such as why there are large variations in permeability between different bedrock lithologies.     

Variographic analysis of chemical and piezometric data from the sandstone aquifer of Ain Oussera, Algeria

The perturbation of piezometric level and the bad water quality in Ain Oussera plain represents a serious problem for local authorities and water resources managers. The spatial distribution of piezometric level and chemical data was analyzed by applying geostatistical methods, which provide an indication of the uncertainty of the estimation using the computer software VARIOWIN 2.2 (Pannatier 1996). In this paper, the evolution of the piezometric level and hydrochemical data by referring to other research campaigns was studied. Two campaigns were chosen; September 2001 and May 2008 for pizometric level and 1994 and 2004 for chemical data. In the beginning, elementary statistics has been carried out to understand the statistical distribution and performed an analysis of variance for comparison between two campaigns. Geostatistics for modeling and cartography were applied. The results showed that piezometric levels admit spherical model that the direction of groundwater flow is from southwest to northeast. High nugget effect characterizes piezometric data and chemical data, linked to the presence of microregions due to excessive pumping and local evaporitics formations. Anisotropy is observed in the northeast-southeast direction from which a spatial continuity in this direction can be deduced.     

Significance of conditioning to piezometric head data for predictions of mass transport in groundwater modeling

Transmissivity and head data are sampled from an exhaustive synthetic reference field and used to predict the arrival positions and arrival times of a number of particles transported across the field, together with an uncertainty estimate. Different combinations of number of transmissivity data and number of head data used are considered in each one of a series of 64 Monte-Carlo analyses. In each analysis, 250 realizations of transmissivity fields conditioned to both transmissivity and head data are generated using a novel geostatistically based inverse method. Pooling the solutions of the flow and transport equations in all 250 realizations allows building conditional frequency distributions for particle arrival positions and arrival times. By comparing these fresquency distributions, we can assess the incremental gain that additional head data provide. The main conclusion is that the first few head data dramatically improve the quality of transport predictions.     

Poroelastic analysis of cover-collapse sinkhole formation by piezometric surface drawdown

Where the water table is above the soil-rock contact in karst regions, cover-collapse sinkholes in the soil and soft sediment above the rock commonly occur as a result of drawdown of the piezometric surface in the karst aquifer. Transient stresses and pore pressures around soil voids at the soil-rock contact can cause hydraulic fracturing of the soil near the wall of the void. After the first such fracture, successive sloughing of soil propagates the soil void rapidly to the surface, resulting in a cover-collapse sinkhole. Sinkhole formation by this mechanism should be strongly a function of rate and magnitude of piezometric surface drawdown, permeability and tensile strength of the soil, and the size, depth, and geometry of the initial soil void. Large soil voids and those with walls that are partly planar or of low curvature are most susceptible to hydraulic fracture and the resulting progression to sinkhole formation.     

Various filtering algorithms used to eliminate outliers in velocity time series obtained by ADVs (acoustic Doppler velocimeter)

The correct measurement of velocities in rivers is important for the true determination of discharge, erosion, scouring, and sediment transport processes. With the goal of increased accuracy, the use of acoustic Doppler velocimeters (ADVs) is increasing in hydrological measurements in rivers, lakes, and laboratories. ADVs are extensively used in the USA. ADVs have advantages when compared with classical measurement devices; however, one must be careful while using an ADV because their sampling approach creates a large number of extreme values by sending signals into the flow, measuring the velocities of particles moving with the water and assuming that these particles move with same velocity as the water. To calculate unbiased statistical properties, outliers must be removed from the time series. This study explains the methods used to filter velocity time series collected with ADVs and investigates the effects of these filters on the statistical characteristics of the filtered time series.     

Some aspects of transformations of compositional data and the identification of outliers

The statistical analysis of compositional data is based on determining an appropriate transformation from the simplex to real space. Possible transfonnations and outliers strongly interact: parameters of transformations may be influenced particularly by outliers, and the result of goodness-of-fit tests will reflect their presence. Thus, the identification of outliers in compositional datasets and the selection of an appropriate transformation of the same data, are problems that cannot be separated. A robust method for outlier detection together with the likelihood of transformed data is presented as a first approach to solve those problems when the additive-logratio and multivariate Box-Cox transformations are used. Three examples illustrate the proposed methodology.     

Coupling isotopic and piezometric data to infer groundwater recharge mechanisms in arid areas: example of Samail Catchment,Oman

Hydrochemistry and well hydrographs are coupled to assess groundwater recharge in the regional catchment of Samail, Oman. The complex geology comprises three aquifers: limestones of the Hajar Supergroup (HSG) at the highlands of North Oman Mountains (NOM); fractured/weathered ophiolites; and Quaternary alluvium. Groundwater flows south–north from the NOM to the coast. Samples from groundwater wells and springs (38) were analyzed for isotopes and major ions. Corrected ¹⁴C dating reveals modern groundwater across the entire catchment, while ⁸⁷Sr/⁸⁶Sr (0.70810–0.70895) shows greater homogeneity. Groundwater in the upper catchment is depleted in ²H and ¹⁸O, indicating a high-altitude recharge source (NOM), and becomes enriched downstream, with a slope indicating an evaporation effect. The hydrographs of nested piezometers located in the upper, middle and lower catchment show different recharge responses between deep and shallower depths. Head difference in response to recharge is observed upstream, suggesting a lateral recharge mechanism, contrary to vertical recharge downstream reflected in identical recharge responses. The homogeneous ⁸⁷Sr/⁸⁶Sr ratio, head changes, downstream enrichment of ²H and ¹⁸O, and the presence of modern groundwater throughout the catchment suggest that groundwater recharge takes place across the entire catchment and that the three aquifers are hydraulically connected. The recharge estimated using the chloride mass balance method is in the range of 0–43% of the mean annual rainfall.     

Accounting for spatial patterns of multiple geological data sets in geological thematic mapping using GIS-based spatial analysis

This paper presents a Geographic Information System (GIS)-based spatial analysis scheme to account for spatial patterns and association in geological thematic mapping with multiple geological data sets. The multi-buffer zone analysis, the main part of the present study, was addressed to reveal the spatial pattern around geological source primitives and statistical analysis based on a contingency table was performed to extract information for the assessment of an integrated layer. Mineral potential mapping using multiple geological data sets from Ogdong in Korea was carried out to illustrate application of this methodology. The results obtained from the case study indicated that some geochemical elements and residual magnetic anomaly dominantly affected spatial patterns of the mineral potential map in the study area and the dominant classes of input data layers were also extracted. This information on spatial patterns of multiple geological data sets around mines could be used as effective evidences for the interpretation of the integrated layer within GIS.     

Explorative data analysis of heavy metal contaminated soil using multidimensional spatial regression

To obtain data on heavy metal contaminated soil requires laborious and time-consuming data sampling and analysis. Not only has the contamination to be measured, but also additional data characterizing the soil and the boundary conditions of the site, such as pH, land use, and soil fertility. For an integrative approach, combining the analysis of spatial distribution, and of factors influencing the contamination, and its treatment, the Mollifier interpolation was used, which is a non-parametric kernel density regression. The Mollifier was capable of including additional independent variables (beyond the spatial dimensions x and y) in the spatial interpolation and hence explored the combined influence of spatial and other variables, such as land use, on the heavy metal distribution. The Mollifier could also represent the interdependence between different heavy metal concentrations and additional site characteristics. Although the uncertainty measure supplied by the Mollifier at first seems somewhat unusual, it is a valuable feature and supplements the geostatistical uncertainty assessment.     

小波分析在试验信号消噪方面的应用

利用小波分析对试验数据进行后处理,较好的消除了系统的噪音。与Fourier变换法、10点平均滤波法比较后可知,小波分析方法能较好的保留原始数据的特征信息。对目前仍因被噪音困扰而不能正常进行的试验分析提供了一条解决途径。     

双边滤波在探地雷达数据去噪处理中的应用

在探地雷达数据的采集过程中,受外界因素影响会不可避免地混入噪声,严重干扰有效回波的识别与解译.为此,利用双边滤波算法进行探地雷达数据的去噪处理,通过在探地雷达正演记录加入高斯白噪声来模拟实测的探地雷达记录,利用双边滤波器对含噪声的合成记录进行滤波处理,结果表明双边滤波算法能除去大部分高斯噪声,突出有效回波信息,峰值信噪...     

Applications of geospatial analysis to surveillance data: a spatial examination of HIV/AIDS prevalence in Zambia

Techniques of spatial statistics and GIS are applied to socio-economic, demographic and HIV sentinel data to characterize the geographical distribution of HIV prevalence in Zambia and to estimate current prevalence rates. Maps of the 4?years under study (i.e. 1994, 1998, 2002 and 2004) reveal a spatial variation in HIV prevalence with urban and provincial districts having higher prevalence than rural areas. However, there was an overall trend of decrease in HIV prevalence across the country. The year 2004 exhibited the most reduction, coinciding with protective sexual behavior campaigns operating in the country. Risk factors for HIV prevalence included literacy rates, unemployment, poverty and urban residency. Analysis of regression residual maps indicated high spatial autocorrelation: Moran’s I value was 0.28 (z?=?4.12 and p?<?0.000) and a highly significant Robust LM (lag; p?<?0.00000) suggestive of contagious and hierarchic spatial diffusion processes. High HIV prevalence rates among interdependent districts and locational similarity patterns suggest that HIV control programs in the country would require an integrated approach combining HIV prevention messages as well as an understanding of social and cultural interactions between interdependent districts that produce behavioral diffusion of HIV prevalence rates.     

Hankel矩阵滤波在微地震数据处理中的应用

针对微地震信号能量弱、信噪比偏低的问题,将基于Hankel矩阵的滤波算法引入微地震信号处理中,用于衰减微地震信号中的随机噪音,提高微地震事件波至时间的拾取精度;采用Akaike信息准则(AIC)自动选取信号特征值,能适用于微地震事件的实时自动处理。与常规滤波方法相比,该方法在压制噪音的同时保护了微地震信号,其有效性和实用性在模型数据和实际微地震数据测试中得到了验证。     

Mapping the HIV/AIDS epidemic in Nigeria using exploratory spatial data analysis

This paper examines the spatial variation of HIV/AIDS prevalence rates in Nigeria. It uses Exploratory Spatial Data Analytical (ESDA) techniques to provide insight into the pattern. The overriding objective is to determine if there is a significant spatial clustering of HIV/AIDS. The calculated and mapped Global and Local Moran’s I, and Getis and Ord G _i * values reveal certain states such as Benue, Nassarawa, Federal Capital Territory (FCT) and Cross River have significant spatial clusters of HIV/AIDS rates in Nigeria. The spatial analysis enables policy makers to identify states most affected, and design effective and culturally acceptable preventive measures. Specific policies targeted at states are a more appropriate approach in tackling the epidemic rather than the usual universal cookie-cut HIV reduction strategies that may not be applicable to the different cultural milieu.     

Geostatistical analysis of soil moisture measurements and remotely sensed data at different spatial scales

The European remote sensing satellite (ERS-2) synthetic aperture radar (SAR) data was used for temporal monitoring of soil moisture at Sukhothai, Thailand. Higher correlations were found between the observed soil moisture and the radar backscattering coefficient. The soil moisture distribution shows great variation in space and time due to its stochastic nature. In order to obtain a better understanding of the nature and causes of spatial variation of soil moisture, the extensive soil moisture measurements observed in Thailand and also remotely sensed ERS-2 SAR data were used for geostatistical analysis. The observed soil moisture shows seasonal variations with mean varying from 3.33 %v/v (dry season) to 33.44 %v/v (wet season). The spatial geostatistical structure also shows clear seasonal variations in the geostatistical characteristics such as range and sill. The sills vary from 1.00 (%v/v)² for the driest day to 107.57 (%v/v)² for one of the wet days. The range or the correlation lengths varies between 46.5 and 149.8 m for the wettest and driest periods. The nugget effect does not show strong seasonal pattern or trend but the dry periods usually have a smaller nugget effect than the wet periods. The spherical variogram model fits the sample variograms very well in the case of soil moisture observations while the exponential model fits those of the remotely sensed data. The ranges observed from the observed soil moisture data and remotely sensed data at the same resolution are very similar. Resolution degradation affects the geostatistical structure of the data by reducing the sills, and increasing the ranges.     

非局部均值滤波在重力异常数据处理中的应用

根据小子域滤波原理,小子域滤波产生异常边界扭曲主要表现为高频干扰,提出小子域滤波与非局部均值滤波联合的方法以克服小子域滤波存在的异常边界扭曲问题。利用小子域滤波良好的边界增强能力和非局部均值滤波高频细节保护能力,在压制小子域滤波缺陷的同时尽可能保护小子域滤波的边界增强效果。通过模拟计算和莱州湾海域实测重力数据处理表明,本文方法在增强异常边界的同时压制小子域滤波产生的边界扭曲效应,获得了更好的重力异常处理效果。与单一小子域滤波相比,本文方法不需要考虑异常边界形态,具有更强的稳定性和普适性。