共查询到20条相似文献，搜索用时 31 毫秒
1.
降水空间化信息在很多领域都具有重要意义,而进行空间插值方法形成降水空间化信息是当代较为常用的方式。面对众多的插值方法其插值精度成为我们是否采用的关键,就kirging插值法与IDW(Inverse Distance Weighting)插值进行研究以探讨其插值效果,为此类科学研究提供依据。研究以漓江流域内各气象站点降水统计资料为基础分别采用上述两种方法进行插值处理,通过与预留实测站点比较评判方法的插值效果的优劣。结果表明,多年月平均降水量作为时间步长时,降水丰沛的月份使用kriging插值法较优于IDW插值法,而枯水月份则使用IDW插值法较优于kriging插值法。 相似文献
2.
SWAT模型水文过程模拟的数据不确定性分析——以青海湖布哈河流域为例 总被引：4，自引：2，他引：2
降水、 气温的空间分布是影响流域水量平衡模拟的关键因素, 运用距离权重反比法(IDW)、 梯度距离权重反比法(GIDW)、 样条函数法(Spline)和克里金插值法(Kriging)对青海湖流域及周边地区43个气象站1995-2009年逐日气温和降水进行了空间插值, 并以气象要素空间插值数据驱动模型, 进行布哈河流域径流模拟. 选用布哈河口月平均流量, 以Nash-Suttclife系数(Ens)、 相关系数(R)和相对误差(RE)为评价指标, 进行校准期(2000-2004年)和验证期(2005-2009年)的径流模拟效果比较. 结果表明: 径流模拟精度较高, GIDW和IDW更适合于布哈河流域的气象要素空间化, 并且气象要素空间插值数据误差是引起模型模拟不确定性和参数据不确定性的原因之一. 相似文献
3.
为对比分析大雨、中雨、小雨条件下,不同空间插值方法模拟地市州尺度降雨的差异,基于四川省南充市9个县级辖区三次24h降雨量数据,采用反距离加权(Inverse Distance Weighting,IDW)、张力样条函数(Spline with Tension,ST)、局部多项式(Local Polynomial Interpolation,LPI)、ANUDEM四种插值方法,从插值平均误差(ME)、中误差(RMSE)角度进行了对比分析。结果显示,按ME排序,大雨、中雨时LPISTIDWANUDEM,小雨时IDW、ANUDEM、ST基本相似,LPI最大;三种降雨条件下四种插值方法 ME均小于0.5mm。从RMSE看,大雨、中雨、小雨时ANUDEM插值RMSE为1.79mm、3.07mm和0.05mm,显著小于IDW、LPI和ST;三种插值方法之间差异微小,大雨、中雨、小雨时均接近13mm、8mm和0.5mm。在降雨量等级为大雨和中雨时,ANUDEM插值方法优于其他插值方法,而在降雨量等级为小雨时,四种插值方法差异较小。 相似文献
4.
Conclusions The foregoing discussion indicates that geostatistical estimation of ore deposits is not local; it is not objective; it is not sensitive to local data trends; and it is not unrestrained by the range of data values.Kriging, as an interpolation method, is a variant of IDW least squares linear fit. As such, it suffers from the limitations of all IDW linear interpolation methods that employ only data values.The estimation variance, currently used to calculate the confidence limits of values for individual mining blocks, is hypothetical and globally derived. It is more closely related to sampling density than to local variation in the data set.Geostatistical methods, of course, have a real place in ore deposit assessment, e.g. global, comparative evaluation to assist decisions on development and investment. What is questioned here is the validity of employing a global method to assess detail (mining blocks) within an ore deposit. 相似文献
5.
Masoomeh Delbari 《Arabian Journal of Geosciences》2014,7(10):4221-4233
This paper presents the incorporation of a digital elevation model into the spatial prediction of water table elevation in Mazandaran province (Iran) using a range of interpolation techniques. The multivariate methods used are: linear regression (LR), cokriging (COK), kriging with an external drift (KED) and regression kriging (RK). The analysis is performed on 3 years (1987, 1997 and 2007) of water table elevation data from about 260 monitoring wells. Prediction performances of the different algorithms are compared with two univariate techniques, i.e. inverse distance weighting and ordinary kriging (OK), through cross validation and examination of the consistency of the generated maps with the natural phenomena. Significantly smaller prediction errors are obtained for four multivariate algorithms but, in particular, KED and RK outperform LR and COK for 3 years. The results show the potential for using elevation for a more precise mapping of water table elevation. 相似文献
6.
Soil pH plays an important role in biogeochemical processes in soils. The spatial distribution of soil pH provides basic and useful information relevant to soil management and agricultural production. To obtain an accurate distribution map of soil pH on the Loess Plateau of China, 382 sampling sites were investigated throughout the region and four interpolation methods, i.e., inverse distance weighting (IDW), splines, ordinary kriging, and cokriging, were applied to produce a continuous soil pH surface. In the study region, soil pH values ranged from 6.06 to 10.76, with a mean of 8.49 and a median of 8.48. Land use type had a significant effect (p < 0.01) on soil pH; grassland soils had higher pHs than cropland and forestland soils. From a regional perspective, soil pH showed weak variation and strong spatial dependence, indicated by the low values of the coefficient of variation (0.05) and the nugget-to-sill ratios (<0.25). Indices of cross-validation, i.e., average error, mean absolute error, root mean square error, and model efficiency coefficient were used to compare the performance of the four different interpolation methods. Kriging methods interpolated more accurately than IDW and splines. Cokriging performed better than ordinary kriging and the accuracy was improved using soil organic carbon as an auxiliary variable. Regional distribution maps of soil pH were produced. The southeastern part of the region had relatively low soil pH values, probably due to higher precipitation, leaching, and higher soil organic matter contents. Areas of high soil pH were located in the north of the central part of the region, possibly associated with the salinization of sandy soils under inappropriate irrigation practices in an arid climate. Map accuracy could be further improved using new methods and incorporating other auxiliary variables, such as precipitation, elevation, terrain attributes, and vegetation types. 相似文献
7.
Shahab Shahbeik Peyman Afzal Parviz Moarefvand Mania Qumarsy 《Arabian Journal of Geosciences》2014,7(9):3693-3704
Estimation of mineral resources and reserves with low values of error is essential in mineral exploration. The aim of this study is to compare inverse distance weighted (IDW) and ordinary kriging (OK) methods based on error estimation in the Dardevey iron ore deposit, NE Iran. Anisotropic ellipsoid and variograms were calculated and generated for estimation of Fe distribution by both methods. Density, continuity of ore and waste, the number of points involved, and the discretization factor in the estimation of ore and waste boundaries were determined and the resource estimated by IDW and OK methods. Estimation errors were classified based on JORC standard, and both methods were compared due to distribution of error estimation. Results obtained by the study indicate that error estimation of OK method is less than IDW method and that the results of OK method are reliable. 相似文献
8.
The multiquadric method (MQ) with high interpolation accuracy has been widely used for interpolating spatial data. However, MQ is an exact interpolation method, which is improper to interpolate noisy sampling data. Although the least squares MQ (LSMQ) has the ability to smooth out sampling errors, it is inherently not robust to outliers due to the least squares criterion in estimating the weights of sampling knots. In order to reduce the impact of outliers on the accuracy of digital elevation models (DEMs), a robust method of MQ (MQ-R) has been developed. MQ-R includes two independent procedures: knot selection and the solution of the system of linear equations. The two independent procedures were respectively achieved by the space-filling design and the least absolute deviation, both of which are very robust to outliers. Gaussian synthetic surface, which is subject to a series of errors with different distributions, was employed to compare the performance of MQ-R with that of LSMQ. Results indicate that LSMQ is seriously affected by outliers, whereas MQ-R performs well in resisting outliers, and can construct satisfactory surfaces even though the data are contaminated by severe outliers. A real-world example of DEM construction was employed to evaluate the robustness of MQ-R, LSMQ, and the classical interpolation methods including inverse distance weighting method, thin plate spline, and ANUDEM. Results showed that compared with the classical methods, MQ-R has the highest accuracy in terms of root mean square error. In conclusion, when sampling data is subject to outliers, MQ-R can be considered as an alternative method for DEM construction. 相似文献
9.
M. H. Saffaripour M. A. Mehrabian H. Bazargan 《International Journal of Environmental Science and Technology》2013,10(4):761-768
The mean daily global solar radiation flux is influenced by astronomical, climatological, geographical, geometrical, meteorological, and physical parameters. This paper deals with the study of the effects of influencing parameters on the mean daily global solar radiation flux, and also with the computation of the solar radiation flux at the surface of the earth in locations without solar radiation measurements. The reference–real data were borrowed from the Iranian Meteorological Organization. The analysis of data showed that the mean daily solar radiation flux on a horizontal surface is related to parameters such as: mean daily extraterrestrial solar radiation, average daily ratio of sunshine duration, mean daily relative humidity, mean daily maximum air temperature, mean daily maximum dew point temperature, mean daily atmospheric pressure, and sine of the solar declination angle. Multiple regression and correlation analysis were applied to predict the mean daily global solar radiation flux on a horizontal surface. The models were validated when compared with the reference–measured data of global solar radiation flux. The results showed that the models estimate the global solar radiation flux within a narrow relative error band. The values of mean bias errors and root mean square errors were within acceptable margins. The predicted values of global solar radiation flux by this approach can be used for the design and performance estimation in solar applications. The model can be used in areas where meteorological stations do not exist and information on solar radiation flux cannot be obtained experimentally. 相似文献
10.
Risk assessment of natural hazards is often based on the actual or forecast weather situation. For estimating such climate-related risks, it is important to obtain weather data as frequently as possible. One commonly used climate interpolation routine is DAYMET, which in its current form is not able to update its database for periods of less than a year. In this paper, we report the construction of a new climate database with a standard interface and implement a framework for providing daily updated weather data for online daily weather interpolations across regions. We re-implement the interpolation routines from DAYMET to be compliant with the data handling in the new framework. We determine the optimal number of stations used in two possible interpolation routines, assess the error bounds using an independent validation dataset and compare the results with a previous validation study based on the original DAYMET implementation. Mean absolute errors are 1°C for maximum and minimum temperature, 28 mm for precipitation, 3.2 MJ/m² for solar radiation and 1 hPa for vapour pressure deficit, which is in the range of the original DAYMET routine. Finally, we provide an example application of the methodology and derive a fire danger index for a 1 km grid over Austria. 相似文献
11.
Towards spatial geochemical modelling: Use of geographically weighted regression for mapping soil organic carbon contents in Ireland 总被引：6，自引：0，他引：6
It is challenging to perform spatial geochemical modelling due to the spatial heterogeneity features of geochemical variables. Meanwhile, high quality geochemical maps are needed for better environmental management. Soil organic C (SOC) distribution maps are required for improvements in soil management and for the estimation of C stocks at regional scales. This study investigates the use of a geographically weighted regression (GWR) method for the spatial modelling of SOC in Ireland. A total of 1310 samples of SOC data were extracted from the National Soil Database of Ireland. Environmental factors of rainfall, land cover and soil type were investigated and included as the independent variables to establish the GWR model. The GWR provided comparable and reasonable results with the other chosen methods of ordinary kriging (OK), inverse distance weighted (IDW) and multiple linear regression (MLR). The SOC map produced using the GWR model showed clear spatial patterns influenced by environmental factors and the smoothing effect of spatial interpolation was reduced. This study has demonstrated that GWR provides a promising method for spatial geochemical modelling of SOC and potentially other geochemical parameters. 相似文献
12.
Statistical bias correction methods for numerical weather prediction (NWP) forecasts of maximum and minimum temperatures over India in the medium-range time scale (up to 5 days) are proposed in this study. The objective of bias correction is to minimize the systematic error of the next forecast using bias from past errors. The need for bias corrections arises from the many sources of systematic errors in NWP modeling systems. NWP models have shortcomings in the physical parameterization of weather events and have the inability to handle sub-grid phenomena successfully. The statistical algorithms used for minimizing the bias of the next forecast are running-mean (RM) bias correction, best easy systematic estimator, simple linear regression and the nearest neighborhood (NN) weighted mean, as they are suitable for small samples. Bias correction is done for four global NWP model maximum and minimum temperature forecasts. The magnitude of the bias at a grid point depends upon geographical location and season. Validation of the bias correction methodology is carried out using daily observed and bias-corrected model maximum and minimum temperature forecast over India during July–September 2011. The bias-corrected NWP model forecast generally outperforms direct model output (DMO). The spatial distribution of mean absolute error and root-mean squared error for bias-corrected forecast over India indicate that both the RM and NN methods produce the best skill among other bias correction methods. The inter-comparison reveals that statistical bias correction methods improve the DMO forecast in terms of accuracy in forecast and have the potential for operational applications. 相似文献
13.
Marketa Prusova Lucie Orlikova Marketa Hanzlova 《Central European Journal of Geosciences》2012,4(4):603-613
This paper deals with a stochastic simulation. Snow cover, representing a regionalized variable, was studied and used as an input parameter for a stochastic simulation. The first step included basic statistical analysis of individual parameters of snow, e.g. snow height. In the next step, an analysis of relationships between the snow and the geomorphological parameters (altitude, slope and aspect) was conducted. The most current methods of spatial interpolation and multifactor evaluation are based on weighted regression relationships. Primarily, the use of conditional stochastic simulation was tested in a variety of software. The main aim of this investigation is to compare selected interpolation methods with stochastic simulation, based on the development of the values and on the evaluation of the incidence of extreme events. The study shall provide users with recommendations for selecting the optimal interpolation method and its application to real data. 相似文献
14.
局域地应力场获取的插值平衡方法 总被引：4，自引：1，他引：3
针对由整体地应场插值计算局域地应力场的问题计算量大、受地质结构的影响大、不过分追求高精度等特点,改进了反距离加权插值法,考虑了单元体积的影响,提高了该方法在此问题中的适用性。基于此,提出了平面问题、三维地面和地下工程局域地应力场的求取策略,建议了边界全平动约束和法向约束两种边界条件,并验证了其合理性和适用场合。最后,在大型水电工程深切河谷坝肩边坡分析中进行了应用分析。结果表明：该插值方法简单实用,能够满足工程分析的精度要求;局域地应力场的求取策略计算效率高,计算精度能够满足工程分析的要求。 相似文献
15.
An Experimental Comparison of Ordinary and Universal Kriging and Inverse Distance Weighting 总被引：17，自引：0，他引：17
A factorial, computational experiment was conducted to compare the spatial interpolation accuracy of ordinary and universal kriging and two types of inverse squared-distance weighting. The experiment considered, in addition to these four interpolation methods, the effects of four data and sampling characteristics: surface type, sampling pattern, noise level, and strength of small-scale spatial correlation. Interpolation accuracy was measured by the natural logarithm of the mean squared interpolation error. Main effects of all five factors, all two-factor interactions, and several three-factor interactions were highly statistically significant. Among numerous findings, the most striking was that the two kriging methods were substantially superior to the inverse distance weighting methods over all levels of surface type, sampling pattern, noise, and correlation. 相似文献
16.
基于新疆96个气象站1961-2010年的逐日平均气温和冻土深度资料,使用线性趋势分析、Mann-Kendall检测以及基于ArcGIS的混合插值法,对新疆冬季负积温和季节性最大冻土深度的时空变化及其相互关系进行了分析. 结果表明：50 a来,新疆冬季负积温绝对值总体以51.5 ℃·d·(10a)-1的倾向率减少,并于1985年发生了突变. 受其影响,最大冻土深度以-3.5 cm·(10a)-1的倾向率减小,也于1988年发生了突变. 就全疆平均而言,1961-2010年,负积温每减少100 ℃·d,最大冻土深度将减小4.6 cm.但这种影响区域性差异显著,最大冻土深度减小量呈现"南疆小,北疆和天山山区大"的格局.南疆大部最大冻土深度对负积温变化的响应相对较敏感,一般为-3.0~-12.7 cm·(100℃·d)-1;北疆和天山山区响应的敏感性较小,多为0.0~-4.9 cm·(100℃·d)-1,其成因很可能是北疆和天山山区冬季积雪较南疆厚,较厚的积雪所具有的低导热性和较大的容积热容减小了气候变暖对冻土热状况的影响.负积温减少、最大冻土深度变浅将改变土壤的水热物理性状,加剧土壤干化、草场退化以及土地的荒漠化,对新疆脆弱的生态环境产生更加不利的影响.因此,应根据最大冻土深度对负积温变化响应的实际,采取趋利避害的技术措施积极应对. 相似文献
17.
区域积温插值的GIS方法 总被引：2，自引：0，他引：2
阐述了积温期分解对区域积温插值GIS方法的改进.运用该方法对台站各旬日均温纪录进行分解,得到>0℃期间的积温期长度与对应的气温下降累计值,发现它们之间呈现很好的线性关系,而积温值与积温期之间用指数回归拟合曲线代表更切合.在气温垂直递减率的基础上,用上述直线关系为参数,构建基于GIS(ARC/INFO地理信息系统)GRID模块的插值方法,依据高分辨率的DEM与台站海拔高度TIN之间的高度差进行高度订正以生成多山区域的积温数据库.与改进前的GIS插值相比,该方法可使甘肃省区域内积温插值的相对精度提高近3倍.这种方法可以在甘肃省退耕还林还草等生态建设信息化管理中得到应用. 相似文献
18.
基于栅格叠合的沉积物底质图生成方法 总被引：2，自引：0，他引：2
文章提出了一种基于GIS空间插值和栅格图叠合技术,分析生成沉积物底质图的方法,并以曹妃甸海区为例,以170个海底表层沉积物样的粒度分析结果为依据,应用本文设计的方法生成这一海区的底质分布图,并用预留的20个采样点进行了精度分析和检验,在此基础上比较了不同的空间插值方法对生成的底质图结果的影响.结果显示出这一方法成图速度快、自动化程度高,但也存在对原始数据精度要求高、插值方法带来误差等问题.在借鉴传统底质图生成方法的基础上,运用三维TIN模型对成图结果进行改进,最终形成一种结合地貌要素的栅格叠合的沉积物底质图生成方法. 相似文献
19.
A nonlinear wavelet neural network (WNN) model with natural orthogonal expansion (NOE) and combined weights is constructed to predict the annual frequency of tropical cyclones (TCF) occurring over the coastal regions of Southern China. Combined weights are obtained by calculating categorical weights, based on the particle swarm projection pursuit, and ranking weights, based on fuzzy mathematics, followed by optimization. The global monthly mean heights at 500?hPa and sea-surface temperature fields are used as two predictors. The linear and nonlinear information of the predictors with reduced dimensions is gathered through the NOE and combined weights, respectively, and treated as the input into the WNN model. This model is first trained with the 55-year (i.e., 1950?C2004) TCF data and then used to predict annual TCFs for the subsequent 5?years (i.e., 2005?C2009). Results show that the mean absolute and relative errors are 0.6175 and 9.34?%, respectively. The impacts of the combined weights, NOE and WNN as well as the traditional multi-regression approach on the TCF prediction are examined. Results show superior performance of the WNN-based model in the annual TCF prediction. 相似文献
20.
合肥义城地区土壤重金属污染评价中典型插值方法的对比 总被引：5，自引：0，他引：5
空间插值对于土壤中重金属元素的空间分布及污染评价具有重要意义。对合肥义城地区土壤中的Cu、Pb、Zn、Cd、As、Hg等污染重金属元素,以常用且具有代表性的反距离加权法、径向基函数法、普通克里格法,进行了空间插值的对比验证分析和评价。通过对各种元素的空间插值各种误差进行综合比较的结果表明：Cu、Pb、As元素采用普通克里格法进行插值结果最优,而Zn元素采用反距离加权法最优,对于Cd、Hg元素则径向基函数插值法最优。 相似文献