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
Viewed
Total article views: 3,431 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
2,304
1,003
124
3,431
122
145
HTML: 2,304
PDF: 1,003
XML: 124
Total: 3,431
BibTeX: 122
EndNote: 145
Views and downloads (calculated since 02 Aug 2021)
Cumulative views and downloads
(calculated since 02 Aug 2021)
Total article views: 2,329 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
1,640
593
96
2,329
105
130
HTML: 1,640
PDF: 593
XML: 96
Total: 2,329
BibTeX: 105
EndNote: 130
Views and downloads (calculated since 23 May 2022)
Cumulative views and downloads
(calculated since 23 May 2022)
Total article views: 1,102 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
664
410
28
1,102
17
15
HTML: 664
PDF: 410
XML: 28
Total: 1,102
BibTeX: 17
EndNote: 15
Views and downloads (calculated since 02 Aug 2021)
Cumulative views and downloads
(calculated since 02 Aug 2021)
Viewed (geographical distribution)
Total article views: 3,431 (including HTML, PDF, and XML)
Thereof 3,242 with geography defined
and 189 with unknown origin.
Total article views: 2,329 (including HTML, PDF, and XML)
Thereof 2,221 with geography defined
and 108 with unknown origin.
Total article views: 1,102 (including HTML, PDF, and XML)
Thereof 1,021 with geography defined
and 81 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...
