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1.
In sparsely monitored basins, accurate mapping of the spatial variability of groundwater level requires the interpolation of scattered data. This paper presents a comparison of deterministic interpolation methods, i.e. inverse distance weight (IDW) and minimum curvature (MC), with stochastic methods, i.e. ordinary kriging (OK), universal kriging (UK) and kriging with Delaunay triangulation (DK). The study area is the Mires Basin of Mesara Valley in Crete (Greece). This sparsely sampled basin has limited groundwater resources which are vital for the island’s economy; spatial variations of the groundwater level are important for developing management and monitoring strategies. We evaluate the performance of the interpolation methods with respect to different statistical measures. The Spartan variogram family is applied for the first time to hydrological data and is shown to be optimal with respect to stochastic interpolation of this dataset. The three stochastic methods (OK, DK and UK) perform overall better than the deterministic counterparts (IDW and MC). DK, which is herein for the first time applied to hydrological data, yields the most accurate cross-validation estimate for the lowest value in the dataset. OK and UK lead to smooth isolevel contours, whilst DK and IDW generate more edges. The stochastic methods deliver estimates of prediction uncertainty which becomes highest near the southeastern border of the basin.  相似文献   

2.
The purpose of this study was to determine and evaluate the spatial changes in soil salinity by using geostatistical methods. The study focused on the suburb area of Beijing, where urban development led to water shortage and accelerated wastewater reuse to farm irrigation for more than 30 years. The data were then processed by GIS using three different interpolation techniques of ordinary kriging (OK), disjunctive kriging (DK), and universal kriging (UK). The normality test and overall trend analysis were applied for each interpolation technique to select the best fitted model for soil parameters. Results showed that OK was suitable for soil sodium adsorption ratio (SAR) and Na+ interpolation; UK was suitable for soil Cl? and pH; DK was suitable for soil Ca2+. The nugget-to-sill ratio was applied to evaluate the effects of structural and stochastic factors. The maps showed that the areas of non-saline soil and slight salinity soil accounted for 6.39 and 93.61 %, respectively. The spatial distribution and accumulation of soil salt were significantly affected by the irrigation probabilities and drainage situation under long-term wastewater irrigation.  相似文献   

3.
The Harran Plain is located in the southeastern part of Turkey and has recently been developed for irrigation agriculture. It already faces soil salinity problems causing major yield losses. Management of the problem is hindered by the lack of information on the extent and geography of the salinization problem. A survey was carried out to delineate the spatial distribution of salt-affected areas by randomly selecting 140 locations that were sampled at two depths (0 to 30 and 30 to 60 cm) and analyzed for soil salinity variables: soil electrical conductivity (EC), soluble cations (Ca2+, Mg2+, Na+, and K+), soluble anions (SO 4 2? , Cl?), exchangeable Na+ (me 100 g?1) and exchangeable sodium percentage. Terrain attributes (slope, topographical wetness index) were extracted from the digital elevation model of the study area. Variogram analyses after log transformation and ordinary kriging (OK) were applied to map spatial patterns of soil salinity variables. Multivariate geostatistical methods—regression kriging (RK) and kriging with external drift (KED)—were used using elevation and soil electrical conductivity data as covariates. Performances of the three estimation methods (OK, RK, and KED) were compared using independent validation samples randomly selected from the main dataset. Soils were categorized into salinity classes using disjunctive kriging (DK) and ArcGIS, and classification accuracy was tested using the kappa statistic. Results showed that soil salinity variables all have skewed distribution and are poorly correlated with terrain indices but have strong correlations among each other. Up to 65 % improvement was obtained in the estimations of soil salinity variables using hybrid methods over OK with the best estimations obtained with RK using EC0–30 as covariate. DK–ArcGIS successfully classified soil samples into different salinity groups with overall accuracy of 75 % and kappa of 0.55 (p?<?0.001).  相似文献   

4.
The USDA Forest Service, Forest Inventory and Analysis program (FIA) recently produced a nationwide map of forest biomass by modeling biomass collected on forest inventory plots as nonparametric functions of moderate resolution satellite data and other environmental variables using Cubist software. Efforts are underway to develop methods to enhance this initial map. We explored the possibility of modeling spatial structure to make such improvements. Spatial structure in the field biomass data as well as in residuals from the map was investigated across 18 ecological zones in the Interior Western U.S. Exploratory tools included directional graphs of summary statistics, three dimensional maps, Moran’s I correlograms, and variograms. Where spatial pattern was present, field and residual biomass were kriged, and predictions made for an independent test set were evaluated for improvement over predictions in the initial biomass map. While kriging has some potential benefit when analyzing the field data and exploring spatial structure, kriging residuals resulted in little or no improvement in the initial biomass map developed using Cubist software. Stationarity assumptions, variogram behavior, and appropriate model fitting strategies are discussed.  相似文献   

5.
The exploration, exploitation, and unscientific management of groundwater resources in the National Capital Territory (NCT) of Delhi, India have posed a serious threat of reduction in quantity and deterioration of quality. The objective of the study is to determine the groundwater quality and to assess the risk of groundwater pollution at Najafgarh, NCT of Delhi. The groundwater quality parameters were analyzed from the existing wells of the Najafgarh and the thematic maps were generated using geostatistical concepts. Ordinary kriging and indicator kriging methods were used as geostatistical approach for preparation of thematic maps of the groundwater quality parameters such as bicarbonate, calcium, chloride, electrical conductivity (EC), magnesium, nitrate, sodium, and sulphate with concentrations equal or greater than their respective groundwater pollution cutoff value. Experimental semivariogram values were fitted well in spherical model for the water quality parameters, such as bicarbonate, chloride, EC, magnesium, sodium, and sulphate and in exponential model for calcium and nitrate. The thematic maps of all the groundwater quality parameters exhibited an increasing trend of pollution from the northern and western part of the study area towards the southern and eastern part. The concentration was highest at the southernmost part of the study area but it could not reflect correctly the groundwater pollution status. The indicator kriging method is useful to assess the risk of groundwater pollution by giving the conditional probability of concentrations of different chemical parameters exceeding their cutoff values. Thus, risk assessment of groundwater pollution is useful for proper management of groundwater resources and minimizing the pollution threat.  相似文献   

6.
A prerequisite to sustaining ecosystems is the inventory and classification of landscape structure and composition. Ecological classification and mapping involves the delineation of landscapes into easily recognizable units. Topography, soils, vegetation, physical landscape form, and successional pathways are delineation criteria commonly used.Damman (1967) developed a forest type classification system for Newfoundland using vegetation, soil and landforms as the defining criteria. Damman's forest types were used in combination with mensurational data to assign forest types to timber volume productivity classes. Since each of the Damman forest types is associated with characteristic soils, parent materials, moisture regime and topographic position, the mapping units are similar to Canada Land Inventory (CLI) mapping units. Field work to confirm the correlation between Damman forest types and CLI capability classes was initiated in 1993. CLI maps were recoded in 1994 and Damman forest types were determined; resulting ecosystem-based maps provide a common framework to assess forestry/wildlife interactions in an ecosystem planning process.  相似文献   

7.
Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions, kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional role was found very useful in aiding decisions in conservation planning.  相似文献   

8.
Two non-parametric kriging methods such as indicator kriging and probability kriging were compared and used to estimate the probability of concentrations of Cu, Fe, and Mn higher than a threshold value in groundwater. In indicator kriging, experimental semivariogram values were fitted well in spherical model for Fe and Mn. Exponential model was found to be best for all the metals in probability kriging and for Cu in indicator kriging. The probability maps of all the metals exhibited an increasing risk of pollution over the entire study area. Probability kriging estimator incorporates the information about order relations which the indicator kriging does not, has improved the accuracy of estimating the probability of metal concentrations in groundwater being higher than a threshold value. Evaluation of these two spatial interpolation methods through mean error (ME), mean square error (MSE), kriged reduced mean error (KRME), and kriged reduced mean square error (KRMSE) showed 3.52% better performance of probability kriging over indicator kriging. The combined result of these two kriging method indicated that on an average 26.34%, 65.36%, and 99.55% area for Cu, Fe, and Mn, respectively, are coming under the risk zone with probability of exceedance from a cutoff value is 0.6 or more. The groundwater quality map pictorially represents groundwater zones as ??desirable?? or ??undesirable?? for drinking. Thus the geostatistical approach is very much helpful for the planners and decision makers to devise policy guidelines for efficient management of the groundwater resources so as to enhance groundwater recharge and minimize the pollution level.  相似文献   

9.
For the sustainable development of forest land, as recently prescribed by the Canadian Forest Strategy, a land classification project in northern Newfoundland was initiated to support the local forest management activities. The method adopted here is a modification of the Canadian Committee for Ecological Land Classification's (CCELC) system, and it applies various levels of mapping to uniform areas based on geomorphology, soils, vegetation, climate, water, and fauna.In this study, all CCELC levels were mapped; resulting maps were digitized and imported into a Geographic Informations System (GIS). The GIS data base contained the following maps: 1) digital terrain model, 2) bedrock geology, 3) surficial geology, 4) forest inventory, and 5) various levels of the ecological land classification, including Vegetation Types at the lowest level. In addition to the mapping, mensurational data were analyzed to provide stand and stock tables for each of the forest types, including growth curves that could be entered into specific forest growth modelling systems to predict wood supply scenarios based upon different management interventions.  相似文献   

10.
Understanding soil gas radon spatial variations can allow the constructor of a new house to prevent radon gas flowing from the ground. Indoor radon concentration distribution depends on many parameters and it is difficult to use its spatial variation to assess radon potential. Many scientists use to measure outdoor soil gas radon concentrations to assess the radon potential. Geostatistical methods provide us a valuable tool to study spatial structure of radon concentration and mapping. To explore the structure of soil gas radon concentration within an area in south Italy and choice a kriging algorithm, we compared the prediction performances of four different kriging algorithms: ordinary kriging, lognormal kriging, ordinary multi-Gaussian kriging, and ordinary indicator cokriging. Their results were compared using an independent validation data set. The comparison of predictions was based on three measures of accuracy: (1) the mean absolute error, (2) the mean-squared error of prediction; (3) the mean relative error, and a measure of effectiveness: the goodness-of-prediction estimate. The results obtained in this case study showed that the multi-Gaussian kriging was the most accurate approach among those considered. Comparing radon anomalies with lithology and fault locations, no evidence of a strict correlation between type of outcropping terrain and radon anomalies was found, except in the western sector where there were granitic and gneissic terrain. Moreover, there was a clear correlation between radon anomalies and fault systems.  相似文献   

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