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EN
This study aimed to understand the new management challenges related to the impact of climate change on biodiversity, deterioration of agricultural productivity, food security, and increasing rates of desertification. This constitutes an important indicator for studying Land Degradation Neutrality (SDGs Target 15.3), which is considered a significant target in achieving the Sustainable Development Goals 2030. The present study is concerned with assessing and monitoring land management and land degradation in Wadi El Farigh from 2000 to 2019. Soil quality is a major part of the chain that leads to understanding sustainable land management of natural resources (land, groundwater, and natural vegetation). A geopedological approach produced the studied area’s physiographic and soil map. The study of changes in land degradation level in Wadi El Farigh over 20 years with a period of every five years shows a very high improvement in the study area from the year 2000 up to 2014. From 2015 to 2019, this class was reduced due to the effects of land degradation reflected by the use of saline water for irrigating crops. Using remote sensing and geostatistical analyses within the GIS environment illustrated that the soils were classified as Entisols, representing 79.45 of the total studied area, and Aridisols representing 20.55% of the total studied area.
EN
This study used a geospatial model to evaluate the regional distributions and buildup of various Heavy Metals (HM) and micronutrients as a result of groundwater irrigation used for lengthy periods in Egypt’s El-Kharga and El-Farafra oases, which were formed on western desert terrain, were the subject of the study. To fulfill this aim, field sampling of soil and groundwater was integrated with cartographic modeling. The evaluated HM concentrations in the water samples are below the permitted level for irrigation. The surface soil’s element concentrations were within acceptable limits. However, protracted mobility and a potency risk for soil smearing were not spotted. The apportionment of HM concentricity versus soil profundity showed that the assemblage was primarily in the topsoil. Future management plans should consider ongoing HM level monitoring. The lands are divided into three classes: II, III, and IV, according to their capabilities, while the soils are divided into three classes based on their suitability: moderately suitable class S2, marginally acceptable class S3, and permanently unsuitable class N2. Additionally, soil fertility and quality were categorized into low and moderate categories. Land evaluations indicate that they are promising areas for agricultural investment under the conditions of using modern agricultural techniques. The most important results of the study are that the non-technical use of irrigation water in some areas has exacerbated the problems of salinity, especially in those where the drainage characteristics are poor. Concentrations of HM were found only in agricultural areas adjacent to urban areas and poor drainage, especially in agricultural areas reclaimed for more than 50 years. High concentrations of HM were also found in shallow wells close to the same places, and there were no significant concentrations in blind wells. The main recommendation of the study is the necessity of using modern agricultural and irrigation systems in those places.
EN
A multi-disciplinary approach is indispensable for adequate acid rock drainage (ARD), mineral leaching impact, and groundwater management. Groundwater is a valuable resource, and it is critical to protect as well as mitigate the effects of pollution such as ARD in the mining environment. Mine waste storage facilities (waste rocks and tailings) are potential ARD sources capable of degrading groundwater reserves. This research investigated and reported the application of a case study of multivariate statistical and spatial variability of selected parameters associated with ARD in groundwater around WRD and TSF at mine sites. Water quality analysis data of seventy water samples from 10 boreholes located at the WRD and TSF mine were utilised in this study. The correlation matrix and principal components analysis was applied to the data set to determine the associated variability in groundwater in relation to ARD. Geostatistical analysis was used to produce contour maps to ARD principal components of the study site, using ordinary kriging of the best fit models. The application of multivariate statistical and geospatial analysis in groundwater quality assessment with coupled soil and groundwater modelling of flow and transport at waste rock dump and tailings storage sites provides an essential tool for exploratory data analysis, and spatial extent determination of the relationship between various data sets significant to acid rock drainage.
EN
Acid volatile sulphide (AVS), one of the most reactive phases in sediments, is a crucial link in explaining a dynamic biogeochemical cycle in a marine ecosystem. Research gaps exist in describing the spatial variation of AVS and interconnections with sediment covariates in the Eastern Upper Gulf of Thailand. Measurements of AVS and auxiliary parameters followed the standard protocol. A comparison of ordinary kriging (OK), cokriging (CK), and regression kriging (RK) performance was evaluated based on the mean absolute error (MAE) and root mean square error (RMSE). The concentrations of AVS ranged from 0.003 to 0.349 mg g−1 sediment dry weight. Most parameters contained short range spatial dependency except for oxidation-reduction potential (ORP) and pH. The AVS tended to be both linearly and non-linearly related to ORP and readily oxidisable organic matter (ROM). The RK model, using inputs from the tree-based model, was the most robust of the three kriging methods. It is suggested that nonlinear interactions should be taken into account when predicting AVS concentration, and it is expected that this will further increase the model accuracy. This study helps establish a platform for ecological health and sediment quality guidelines.
EN
Toxicity assessment of environmental compartments, in particular sediments as a highly complex matrix, provides a more direct way to assess potential adverse effects of pollutants present in a sample in contrast to chemical analysis estimating only a quantitative level of xenobiotics. Interactions between chemicals, formations of derivatives and the influence of chemical properties of sediments such as the organic matter content causing the intensified sorption of hydrophobic pollutants suggest that a traditional approach to the sediment quality, based only on chemical analysis may be insufficient. The presented study describes the vertical and horizontal variability of toxicity of Gdańsk Basin sediments. Based on 128 surface sediments samples and using geostatistical methods, a prediction map for the EC50 parameter was created. This allowed the evaluation of the toxicity of the surface sediment layer at any selected point of the study area. The applied analysis can be functional for many other locations worldwide. In the present study, the hypothesis about the location of toxic sediments in the vicinity of Gdańsk Deep, outer Puck Bay and close to Vistula River mouth was further confirmed.
EN
The wide access to source data, published by numerous websites, results in situation, when information acquisition is not a problem any more. The real problem is how to transform information in the useful knowledge. Cartographic method of research, dealing with spatial data, has been serving this purpose for many years. Nowadays, it allows conducting analyses at the high complexity level, thanks to the intense development in IT technologies, The vast majority of analytic methods utilizing the so-called data mining and data enrichment techniques, however, concerns non-spatial data. According to the Authors, utilizing those techniques in spatial data analysis (including analysis based on statistical data with spatial reference), would allow the evolution of the Spatial Information Infrastructure. (SII) into the Spatial Knowledge Infrastructure (SKI). The SKI development would benefit from the existence of statistical geoportal. Its proposed functionality, consisting of data analysis as well as visualization, is outlined in the article. The examples of geostatistical analyses (ANOVA and the regression model considering the spatial neighborhood), possible to implement in such portal and allowing to produce the “cartographic added value”, are also presented here.
PL
Szeroki dostęp do danych źródłowych publikowanych w licznych serwisach internetowych sprawia, iż współcześnie problemem jest nie pozyskanie informacji, lecz umiejętne przekształcenie jej w użyteczną wiedze. Kartograficzna metoda badan, która od wielu lat służy temu celowi w odniesieniu do danych przestrzennych, zyskuje dziś nowe oblicze - pozwala na wykonywanie złożonych analiz dzięki wykorzystaniu intensywnego rozwoju technologii informatycznych. Znacząca większość zastosowań metod analitycznych tzw. eksploracyjnej analizy danych (data mining) i ich „wzbogacania” (data enrichment) dotyczy jednakże danych nieprzestrzennych. Wykorzystanie tych metod do analizy danych o charakterze przestrzennym, w tym danych statystycznych, i zapewnienie dostępu do nich w formie dedykowanych usług przyczyniłoby się, zdaniem Autorów, do przetworzenia infrastruktury informacji przestrzennej (Spatial Information Infrastructure - SII) w infrastrukturę wiedzy przestrzennej (Spatial Knowledge Infrastructure - SKI). Rozwojowi SKI mógłby służyć geoportal statystyczny, którego propozycje funkcjonalności, obejmujące zarówno analizę jak i wizualizacje danych, zarysowano w artykule. Zaprezentowano tez przykłady analiz statystycznych (ANOVA, regresja z uwzględnieniem sąsiedztwa przestrzennego), możliwych do zaimplementowania w takim portalu, a które mogłyby się przyczynić do wytworzenia „kartograficznej wartości dodanej”.
PL
Analiza geostatystyczna parametrów zbiornikowych wykonana została w celu określenia zgeneralizowanego modelu zmienności parametrów charakteryzujących poziomy mioceńskich struktur. Modelowania geostatystyczne przeprowadzone zostały przy wykorzystaniu semiwariogramów: bezwzględnego (klasyczny semiwariogram Matherona) oraz względnego (semiwariogram standaryzowany na wariancję). Ponadto do badań geostatystycznych zastosowano semiawiogram relatywny, którego zaletą jest możliwość bezpośredniego porównania siły i struktury zmienności parametrów różnego typu (również wyrażanych w różnych jednostkach). Kolejnym etapem badań była aproksymacja semiwariogramów za pomocą ciągłych funkcji analitycznych, stanowiących w dalszym ciągu rolę geostatystycznych modeli zmienności parametrów. Do semiwariogramów analizowanych parametrów dopasowane zostały modele teoretyczne sferyczne, które pozwoliły określić względne wielkości składnika losowego i nielosowego składającego się w konsekwencji na całkowitą zmienności parametru.
EN
Analysis of geostatistic basin parameters was executed for determination of generalized variability model of parameters characterizing levels of Miocene structure. Modelings of geostatistic were carried out with utilization of classic semivariograms: unrelative (semivariogram of Matheron) and relative (semivariogram standarized for variance). Besides, a relative semivariogram was employed for geostatistic research where capability of comparison of direct power and also variability structures of different parameter types are advantage (in different units expressed). Next period of research was approximation of semivariograms with the aid of continuous analytical function, which presents a models of variability of geostatistic parameters. Theoretical, spherical models were adjusted for analyzed parameters of semivariograms, which have allowed to define relative largeness of fate and unfate components and in consequence on total variability of parameter.
9
Content available remote Geostatystyczna identyfikacja mechanizmów transportu roztworów w ciekach
EN
The geostatistical structural analysis was used to detect hidden mechanisms of solute transport in two contrasting temperate catchments: low land lakeland one and m ountainous. The data set consist two years of daily measurements of the discharge and two solute components for each catchment. In both catchment dissimilarity structure of analysed data in terms of semivariogram , is much the same: small nugget variance and two spherical components with the range 56 or 68 days first and 34-36 or 25-27 day second for mountainous and low land catchments respectively. With daily sampling interval the water in both river can be treated as mixture of three components, presumably surface, subsurface and ground outflow. Weak relationships between solute concentrations and discharge is mainly result of the share of first time component (quick runoff). Codispersion coefficients rise rapidly up to six days lag between discharge and solute concentration, and reaches its maximum between 15 and 30 days. For the quick runoff component relationship between solute concentration and discharge is positive, probably as an effect of periodic flushing effect of surface and subsuiface runoff (Klein 1981, Stach 2002). Factorial kriging can be used for separation time components both for river hydrogram and chemogram.
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