This paper applies and validates a method for generating spatially
distributed hydraulic conductivity (k) based on the specific capacity (Q
(s)) for data-scarce regions. This method has been applied to the
Araripe sedimentary basin, Brazil, and consists of four steps: (1)
selection of (32) wells for which both k and Q (s) data are available;
(2) estimation of k as a function of Q (s) for the (128) wells for which
only specific capacity data are available; (3) spatial distribution of k
using the kriging geostatistical tool; (4) validation of the method,
using (17) representative wells with k measured data. The equation
relating k and Q (s) showed a statistically significant linear relationship (R = 0.93), from which a database has been generated using
kriging with the spherical model. The results showed a calibration
coefficient of Nash and Sutcliffe (NS) of 0.54 and moderate spatial
dependence ratio of 69 %. The validation process provided only a moderate efficiency (NS = 0.22), possibly due to the geological
complexity of the focus system. Despite its limitations, the method
indicates the possibility of application of ordinary kriging to generate
reliable data from auxiliary variables, especially for the water
management of data-scarce areas.
%0 Journal Article
%1 WOS:000329996200035
%A de Fontenele, Savio Brito
%A Mendonca, Luiz Alberto Ribeiro
%A de Araujo, Jose Carlos
%A Santiago, Maria Marlucia Freitas
%A de Brito Goncalves, Jose Yarley
%C 233 SPRING ST, NEW YORK, NY 10013 USA
%D 2014
%I SPRINGER
%J ENVIRONMENTAL EARTH SCIENCES
%K Geostatistic} Kriging; Linear Specific capacity; conductivity; relationship; {Hydraulic
%N 2, SI
%P 885-894
%R 10.1007/s12665-013-2491-z
%T Relationship between hydrogeological parameters for data-scarce regions:
the case of the Araripe sedimentary basin, Brazil
%V 71
%X This paper applies and validates a method for generating spatially
distributed hydraulic conductivity (k) based on the specific capacity (Q
(s)) for data-scarce regions. This method has been applied to the
Araripe sedimentary basin, Brazil, and consists of four steps: (1)
selection of (32) wells for which both k and Q (s) data are available;
(2) estimation of k as a function of Q (s) for the (128) wells for which
only specific capacity data are available; (3) spatial distribution of k
using the kriging geostatistical tool; (4) validation of the method,
using (17) representative wells with k measured data. The equation
relating k and Q (s) showed a statistically significant linear relationship (R = 0.93), from which a database has been generated using
kriging with the spherical model. The results showed a calibration
coefficient of Nash and Sutcliffe (NS) of 0.54 and moderate spatial
dependence ratio of 69 %. The validation process provided only a moderate efficiency (NS = 0.22), possibly due to the geological
complexity of the focus system. Despite its limitations, the method
indicates the possibility of application of ordinary kriging to generate
reliable data from auxiliary variables, especially for the water
management of data-scarce areas.
@article{WOS:000329996200035,
abstract = {This paper applies and validates a method for generating spatially
distributed hydraulic conductivity (k) based on the specific capacity (Q
(s)) for data-scarce regions. This method has been applied to the
Araripe sedimentary basin, Brazil, and consists of four steps: (1)
selection of (32) wells for which both k and Q (s) data are available;
(2) estimation of k as a function of Q (s) for the (128) wells for which
only specific capacity data are available; (3) spatial distribution of k
using the kriging geostatistical tool; (4) validation of the method,
using (17) representative wells with k measured data. The equation
relating k and Q (s) showed a statistically significant linear relationship (R = 0.93), from which a database has been generated using
kriging with the spherical model. The results showed a calibration
coefficient of Nash and Sutcliffe (NS) of 0.54 and moderate spatial
dependence ratio of 69 %. The validation process provided only a moderate efficiency (NS = 0.22), possibly due to the geological
complexity of the focus system. Despite its limitations, the method
indicates the possibility of application of ordinary kriging to generate
reliable data from auxiliary variables, especially for the water
management of data-scarce areas.},
added-at = {2022-05-23T20:00:14.000+0200},
address = {233 SPRING ST, NEW YORK, NY 10013 USA},
author = {de Fontenele, Savio Brito and Mendonca, Luiz Alberto Ribeiro and de Araujo, Jose Carlos and Santiago, Maria Marlucia Freitas and de Brito Goncalves, Jose Yarley},
biburl = {https://www.bibsonomy.org/bibtex/2f5f6738fa512fa9f2097c63e56559e68/ppgfis_ufc_br},
doi = {10.1007/s12665-013-2491-z},
interhash = {284e8a5c8ddbc524ffdc2ab35be9120f},
intrahash = {f5f6738fa512fa9f2097c63e56559e68},
issn = {1866-6280},
journal = {ENVIRONMENTAL EARTH SCIENCES},
keywords = {Geostatistic} Kriging; Linear Specific capacity; conductivity; relationship; {Hydraulic},
number = {2, SI},
pages = {885-894},
publisher = {SPRINGER},
pubstate = {published},
timestamp = {2022-05-23T20:00:14.000+0200},
title = {Relationship between hydrogeological parameters for data-scarce regions:
the case of the Araripe sedimentary basin, Brazil},
tppubtype = {article},
volume = 71,
year = 2014
}