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HESS | Articles | Volume 23, issue 3
Hydrol. Earth Syst. Sci., 23, 1633-1648, 2019
https://doi.org/10.5194/hess-23-1633-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 23, 1633-1648, 2019
https://doi.org/10.5194/hess-23-1633-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 20 Mar 2019

Research article | 20 Mar 2019

Geostatistical interpolation by quantile kriging

Henning Lebrenz and András Bárdossy
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Adhikary, P. P., Dash, C. J., Bej, R., and Chandrasekharan, H.: Indicator and probability kriging methods for delineating Cu, Fe, and Mn contamination in groundwater of Najafgarh Block, Delhi, India, Environ. Monit. Assess., 176, 663–676, https://doi.org/10.1007/s10661-010-1611-4, 2011. a
Ahmed, S. and deMarsily, G.: Comparison of geostatistical methods for estimating transmissivity using data on transmissivity and specific capacity, Water Resour. Res., 23, 1717–1737, 1987. a
Armstrong, M.: Basic Linear Geostatistics, Springer, available at: http://books.google.de/books?id=-9vp1lVuMCsC, Springer Berlin Heidelberg, 1998. a
Basistha, A., Arya, D. S., and Goel, N. K.: Spatial Distribution of Rainfall in Indian Himalayas – A Case Study of Uttarakhand Region, Water Resour. Manag., 22, 1325–1346, https://doi.org/10.1007/s11269-007-9228-2, 2008. a
Bourennane, H., King, D., and Couturier, A.: Comparison of kriging with external drift and simple linear regression for predicting soil horizon thickness with different sample densities, Geoderma, 97, 255–271, https://doi.org/10.1016/S0016-7061(00)00042-2, 2000. a
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Many variables, e.g., in hydrology, geology, and social sciences, are only observed at a few distinct measurement locations, and their actual distribution in the entire space remains unknown. We introduce the new geostatistical interpolation method of quantile kriging, providing an improved estimator and associated uncertainty. It can also host variables, which would not fulfill the implicit presumptions of the traditional geostatistical interpolation methods.
Many variables, e.g., in hydrology, geology, and social sciences, are only observed at a few...
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