caa a22 4500 469064781 CHVBK 20180323132904.0 cr unu---uuuuu 170328e19920501xx s 000 0 eng 10.1007/BF00891272 doi (NATIONALLICENCE)springer-10.1007/BF00891272 Sen Zekâi Faculty of Earth Sciences, Hydrogeology Department, King Abdulaziz University, P. O. Box 1744, 21441, Jeddah, Kingdom of Saudi Arabia aut Standard cumulative semivariograms of stationary stochastic processes and regional correlation [Elektronische Daten] [Zekâi Sen] The standard cumulative semivariograms (SCS), obtained analytically from the currently employed stationary stochastic processes, provide a basis for the model identification and its parameter as well as regional correlation estimations. The analytical solutions for different stationary stochastic processes such as independent (IP), moving average (MA), autoregressive (AR), and autoregressive integrated moving average ARIMA (1,0,1) processes give rise to different types of SCSs which can be expressed in terms of the autocorrelation structure parameters only. The SCSs of independent and MA processes appear as linear trends whereas other type of processes have SCSs which are nonlinear for short distances but become linear at large distances. Irrespective of the stationary stochastic process type the linear portions of SCSs have unit slopes. The vertical distance between these linear portions and that of the IP cumulative semivariogram (CS), provide an indicator for measuring the regional correlation. In the case of stationary processes, the straight line portions of any CS are parallel to each other. Hence, it is possible to identify the model from the sample CS. Finally, necessary procedures are provided for the model parameters estimation. The methodology developed, herein, is applied to some hydrochemical ions in the groundwater of the Wasia aquifer in central part of Kingdom of Saudi Arabia. International Association for Mathematical Geology, 1992 autocorrelation function nationallicence cumulative semivariogram nationallicence regional correlation nationallicence regionalized variables nationallicence stationary stochastic process nationallicence Mathematical Geology Kluwer Academic Publishers-Plenum Publishers 24/4(1992-05-01), 417-435 0882-8121 24:4<417 1992 24 11004 https://doi.org/10.1007/BF00891272 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00891272 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Sen Zekâi Faculty of Earth Sciences, Hydrogeology Department, King Abdulaziz University, P. O. Box 1744, 21441, Jeddah, Kingdom of Saudi Arabia aut NATIONALLICENCE 773 0- Mathematical Geology Kluwer Academic Publishers-Plenum Publishers 24/4(1992-05-01), 417-435 0882-8121 24:4<417 1992 24 11004 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer