The SAFER geodatabase for the Kathmandu valley: Bayesian kriging for data-scarce regions

Raffaele De Risi; Flavia De Luca; Charlotte Gilder; Rama Pokhrel; Paul J Vardanega

doi:10.1177/8755293020970977

The SAFER geodatabase for the Kathmandu valley: Bayesian kriging for data-scarce regions

Raffaele De Risi
, Flavia De Luca^*
, Charlotte Gilder
, Rama Pokhrel
, Paul J Vardanega

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

24 Citations (Scopus)

137 Downloads (Pure)

Abstract

Geostatistical methods are valuable to understand better the spatial distribution of geotechnical parameters at regional scale and to optimise the locations of future ground investigations. This paper investigates the use of the kriging interpolation method to extend the knowledge of a specific geotechnical property from a few sites to a broader geographical area with a focus on the Kathmandu valley (Nepal). A Bayesian form of kriging is proposed. The estimation of the shear wave velocity in the uppermost 30 meters of soil (VS30) in the Kathmandu valley is examined. Slope-based VS30 estimates from the United States Geological Survey are used as prior information, and 15 VS30 measurements are used as more precise data. Considering the limited number of high-quality VS30 measurements available in the valley, it is shown that the Bayesian scheme can lead to a more robust estimation of VS30 than that obtained with the Ordinary kriging approach. A methodology for conditioning prior low-precision data to the measurements is also presented.

Original language	English
Pages (from-to)	1108-1126
Number of pages	19
Journal	Earthquake Spectra
Volume	37
Issue number	2
Early online date	26 Nov 2020
DOIs	https://doi.org/10.1177/8755293020970977
Publication status	Published - 1 May 2021

Research Groups and Themes

PREPARE

Keywords

Kathmandu valley
Bayesian kriging
VS30
SAFER geodatabase
soil classification

Access to Document

10.1177/8755293020970977

Full-text PDF (final published version)
This is the final published version of the article (version of record). It first appeared online via Earthquake Engineering Research Institute at https://doi.org/10.1177/8755293020970977 . Please refer to any applicable terms of use of the publisher.
Final published version, 6.97 MBLicence: CC BY

Handle.net

Persistent link

Embargoed Document

Full-text PDF (author’s accepted manuscript)
Accepted author manuscript, 32.1 MB
Request copy

24 Citations
1 Conference Contribution (Conference Proceeding)

Use of Bayesian Kriging to develop new soil property maps for Quito, Ecuador
Gilder, C. E. L., Othman, M. M., Zapata, C., Holcombe, E. A., De Risi, R., De Luca, F. & Vardanega, P. J., 17 Sept 2024, Geotechnical Engineering Challenges to Meet Current and Emerging Needs of Society: Proceedings of the XVIII European Conference on Soil Mechanics and Geotechnical Engineering, 26–30 August 2024, Lisbon, Portugal. Guerra, N., Fernandes, M. M., Ferreira, C., Correia, A. G., Pinto, A. & Sêco e Pinto, P. (eds.). 1st ed. Abingdon, Oxon: CRC Press/Balkema, Taylor & Francis Group, p. 1131-1135 5 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

Open Access
File
89 Downloads (Pure)

3 Finished

8035 GCRF GLOBAL RESEARCH TRANSLATIONAL AWARDS EP/T015462/1 - SAFER PREPARED
Sextos, A. (Principal Investigator), Macdonald, J. H. G. (Co-Investigator), Biggs, J. J. (Co-Investigator), De Risi, R. (Co-Investigator), Werner, M. (Co-Investigator), Agarwal, J. (Co-Investigator) & De Luca, F. (Co-Investigator)
1/10/19 → 31/03/22
Project: Research
PREPARE: Enhancing PREParedness for East African Countries through Seismic Resilience Engineering
Biggs, J. J. (Principal Investigator) & Macdonald, J. H. G. (Principal Investigator)
1/05/17 → 31/03/22
Project: Research, Parent
SAFER Seismic safety and resilience of schools in Nepal
Sextos, A. (Principal Investigator), De Luca, F. (Co-Investigator), Vardanega, P. J. (Co-Investigator), Agarwal, J. (Co-Investigator), Alexander, N. A. (Co-Investigator) & Werner, M. (Co-Investigator)
1/05/17 → 30/06/21
Project: Research, Parent

The SAFER Borehole Database (SAFER/GEO-591_v1.1)
Gilder, C. (Creator), Pokhrel, R. M. (Creator) & Vardanega, P. (Creator), University of Bristol, 18 Dec 2019
DOI: 10.5523/bris.3gjcvx51lnpuv269xsa1yrb0rw, http://data.bris.ac.uk/data/dataset/3gjcvx51lnpuv269xsa1yrb0rw
Dataset

Cite this

@article{e6dc5c2457f6442395e77f5f8c06ff5d,

title = "The SAFER geodatabase for the Kathmandu valley: Bayesian kriging for data-scarce regions",

abstract = "Geostatistical methods are valuable to understand better the spatial distribution of geotechnical parameters at regional scale and to optimise the locations of future ground investigations. This paper investigates the use of the kriging interpolation method to extend the knowledge of a specific geotechnical property from a few sites to a broader geographical area with a focus on the Kathmandu valley (Nepal). A Bayesian form of kriging is proposed. The estimation of the shear wave velocity in the uppermost 30 meters of soil (VS30) in the Kathmandu valley is examined. Slope-based VS30 estimates from the United States Geological Survey are used as prior information, and 15 VS30 measurements are used as more precise data. Considering the limited number of high-quality VS30 measurements available in the valley, it is shown that the Bayesian scheme can lead to a more robust estimation of VS30 than that obtained with the Ordinary kriging approach. A methodology for conditioning prior low-precision data to the measurements is also presented.",

keywords = "Kathmandu valley, Bayesian kriging, VS30, SAFER geodatabase, soil classification",

author = "\{De Risi\}, Raffaele and \{De Luca\}, Flavia and Charlotte Gilder and Rama Pokhrel and Vardanega, \{Paul J\}",

year = "2021",

month = may,

day = "1",

doi = "10.1177/8755293020970977",

language = "English",

volume = "37",

pages = "1108--1126",

journal = "Earthquake Spectra",

issn = "8755-2930",

publisher = "John Wiley and Sons Inc",

number = "2",

}

TY - JOUR

T1 - The SAFER geodatabase for the Kathmandu valley

T2 - Bayesian kriging for data-scarce regions

AU - De Risi, Raffaele

AU - De Luca, Flavia

AU - Gilder, Charlotte

AU - Pokhrel, Rama

AU - Vardanega, Paul J

PY - 2021/5/1

Y1 - 2021/5/1

N2 - Geostatistical methods are valuable to understand better the spatial distribution of geotechnical parameters at regional scale and to optimise the locations of future ground investigations. This paper investigates the use of the kriging interpolation method to extend the knowledge of a specific geotechnical property from a few sites to a broader geographical area with a focus on the Kathmandu valley (Nepal). A Bayesian form of kriging is proposed. The estimation of the shear wave velocity in the uppermost 30 meters of soil (VS30) in the Kathmandu valley is examined. Slope-based VS30 estimates from the United States Geological Survey are used as prior information, and 15 VS30 measurements are used as more precise data. Considering the limited number of high-quality VS30 measurements available in the valley, it is shown that the Bayesian scheme can lead to a more robust estimation of VS30 than that obtained with the Ordinary kriging approach. A methodology for conditioning prior low-precision data to the measurements is also presented.

AB - Geostatistical methods are valuable to understand better the spatial distribution of geotechnical parameters at regional scale and to optimise the locations of future ground investigations. This paper investigates the use of the kriging interpolation method to extend the knowledge of a specific geotechnical property from a few sites to a broader geographical area with a focus on the Kathmandu valley (Nepal). A Bayesian form of kriging is proposed. The estimation of the shear wave velocity in the uppermost 30 meters of soil (VS30) in the Kathmandu valley is examined. Slope-based VS30 estimates from the United States Geological Survey are used as prior information, and 15 VS30 measurements are used as more precise data. Considering the limited number of high-quality VS30 measurements available in the valley, it is shown that the Bayesian scheme can lead to a more robust estimation of VS30 than that obtained with the Ordinary kriging approach. A methodology for conditioning prior low-precision data to the measurements is also presented.

KW - Kathmandu valley

KW - Bayesian kriging

KW - VS30

KW - SAFER geodatabase

KW - soil classification

U2 - 10.1177/8755293020970977

DO - 10.1177/8755293020970977

M3 - Article (Academic Journal)

SN - 8755-2930

VL - 37

SP - 1108

EP - 1126

JO - Earthquake Spectra

JF - Earthquake Spectra

IS - 2

ER -

The SAFER geodatabase for the Kathmandu valley: Bayesian kriging for data-scarce regions

Abstract

Research Groups and Themes

Keywords

Access to Document

Handle.net

Embargoed Document

Fingerprint

Research output

Use of Bayesian Kriging to develop new soil property maps for Quito, Ecuador

Projects

8035 GCRF GLOBAL RESEARCH TRANSLATIONAL AWARDS EP/T015462/1 - SAFER PREPARED

PREPARE: Enhancing PREParedness for East African Countries through Seismic Resilience Engineering

SAFER Seismic safety and resilience of schools in Nepal

Datasets

The SAFER Borehole Database (SAFER/GEO-591_v1.1)

Cite this