Section Water Resources, Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, the Netherlands
Department of Irrigation and Drainage, School of Agricultural Engineering, College of Agriculture, Animal Sciences and Veterinary Medicine, University of Rwanda, P.O. Box 210, Musanze, Rwanda
Section Water Resources, Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, the Netherlands
Section Water Resources, Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, the Netherlands
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Total article views: 1,841 (including HTML, PDF, and XML)
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1,271
516
54
1,841
36
36
HTML: 1,271
PDF: 516
XML: 54
Total: 1,841
BibTeX: 36
EndNote: 36
Views and downloads (calculated since 02 Aug 2021)
Cumulative views and downloads
(calculated since 02 Aug 2021)
Total article views: 1,030 (including HTML, PDF, and XML)
HTML
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XML
Total
BibTeX
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727
271
32
1,030
26
23
HTML: 727
PDF: 271
XML: 32
Total: 1,030
BibTeX: 26
EndNote: 23
Views and downloads (calculated since 23 May 2022)
Cumulative views and downloads
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Total article views: 811 (including HTML, PDF, and XML)
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BibTeX
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544
245
22
811
10
13
HTML: 544
PDF: 245
XML: 22
Total: 811
BibTeX: 10
EndNote: 13
Views and downloads (calculated since 02 Aug 2021)
Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 1,841 (including HTML, PDF, and XML)
Thereof 1,689 with geography defined
and 152 with unknown origin.
Total article views: 1,030 (including HTML, PDF, and XML)
Thereof 954 with geography defined
and 76 with unknown origin.
Total article views: 811 (including HTML, PDF, and XML)
Thereof 735 with geography defined
and 76 with unknown origin.
This research tested the value of regional groundwater level information to improve landslide predictions with empirical models based on the concept of threshold levels. In contrast to precipitation-based thresholds, the results indicated that relying on threshold models exclusively defined using hydrological variables such as groundwater levels can lead to improved landslide predictions due to their implicit consideration of long-term antecedent conditions until the day of landslide occurrence.
This research tested the value of regional groundwater level information to improve landslide...
