Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 3.102
IF3.102
IF 5-year value: 3.284
IF 5-year
3.284
CiteScore value: 5.1
CiteScore
5.1
SNIP value: 1.37
SNIP1.37
IPP value: 3.21
IPP3.21
SJR value: 1.005
SJR1.005
Scimago H <br class='widget-line-break'>index value: 90
Scimago H
index
90
h5-index value: 42
h5-index42
Preprints
https://doi.org/10.5194/nhess-2020-309
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-309
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  26 Oct 2020

26 Oct 2020

Review status
This preprint is currently under review for the journal NHESS.

Land Subsidence due to groundwater pumping: Hazard Probability Assessment through the Combination of Bayesian Model and Fuzzy Set Theory

Huijun Li1, Lin Zhu1, Gaoxuan Guo2, Yan Zhang3, Zhenxue Dai4, Xiaojuan Li1, Linzhen Chang5, and Pietro Teatini6,7 Huijun Li et al.
  • 1Laboratory Cultivation Base of Environment Process and Digital Simulation, Beijing Laboratory of Water Resources Security, Key Laboratory of 3-Dimensional Information Acquisition and Application, Capital Normal University, Beijing, 100048, China
  • 2Beijing Institute of Hydrogeology and Engineering Geology, Beijing, China
  • 3Key Laboratory of Earth Fissures Geological Disaster, Ministry of Natural resource,Geological Survey of Jiangsu Province, Jiangsu, China
  • 4College of Construction Engineering, Jilin University, Changchun 130026, China
  • 5Fourth Institute of Hydrogeology and Engineering Geology, Hebei Geology and Mineral Exploration and Development, Hebei, China
  • 6Dept. of Civil, Environmental and Architectural Engineering, University of Padova, Padova 3512 1, Italy
  • 7UNESCO-LaSII (Land Subsidence International Initiative), Querétaro, Mexico

Abstract. Land subsidence caused by groundwater over-pumping threatens the sustainable development in Beijing. Hazard assessments of land subsidence can provide early warning information to improve prevention measures. However, uncertainty and fuzziness are the major issues during hazard assessments of land subsidence. We propose a method that integrates fuzzy set theory and weighted Bayesian model (FWBM) to evaluate the hazard probability of land subsidence measured by Interferometric Synthetic Aperture Radar (InSAR) technology. The model is structured as a directed acyclic graph. The hazard probability distribution of each factor triggering land subsidence is determined using Bayes’ theorem. Fuzzification of the factor significance reduces the ambiguity of the relationship between the factors and subsidence. The probability of land subsidence hazard under multiple factors is then calculated with the FWBM. The subsidence time-series obtained by InSAR is used to infer the updated posterior probability. The upper and middle parts of the Chaobai River alluvial fan is taken as a case-study site, which locates the first large-scale Emergency Groundwater Resource Region in Beijing plain. The results show that rates of groundwater level decrease larger than 1 m/y in the confined and unconfined aquifers, compressible layer thicknesses between 160 and 170 m, and Quaternary thicknesses between 400 and 500 m yield maximum hazard probabilities of 0.65, 0.68, 0.32, and 0.35, respectively. The overall hazard probability of land subsidence in the study area decreased from 51.3 % to 28.3 % between 2003 and 2017 due to lower rates of groundwater level decrease. This study provides useful insights for decision-makers to select different approaches for land subsidence prevention.

Huijun Li et al.

Interactive discussion

Status: open (until 30 Dec 2020)
Status: open (until 30 Dec 2020)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Huijun Li et al.

Huijun Li et al.

Viewed

Total article views: 180 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
150 26 4 180 2 3
  • HTML: 150
  • PDF: 26
  • XML: 4
  • Total: 180
  • BibTeX: 2
  • EndNote: 3
Views and downloads (calculated since 26 Oct 2020)
Cumulative views and downloads (calculated since 26 Oct 2020)

Viewed (geographical distribution)

Total article views: 141 (including HTML, PDF, and XML) Thereof 139 with geography defined and 2 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 02 Dec 2020
Publications Copernicus
Download
Citation
Altmetrics