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: 2,832 (including HTML, PDF, and XML)
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1,908
824
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2,832
86
100
HTML: 1,908
PDF: 824
XML: 100
Total: 2,832
BibTeX: 86
EndNote: 100
Views and downloads (calculated since 02 Aug 2021)
Cumulative views and downloads
(calculated since 02 Aug 2021)
Total article views: 1,858 (including HTML, PDF, and XML)
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1,317
468
73
1,858
74
86
HTML: 1,317
PDF: 468
XML: 73
Total: 1,858
BibTeX: 74
EndNote: 86
Views and downloads (calculated since 23 May 2022)
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591
356
27
974
12
14
HTML: 591
PDF: 356
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Total: 974
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Viewed (geographical distribution)
Total article views: 2,832 (including HTML, PDF, and XML)
Thereof 2,656 with geography defined
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Total article views: 1,858 (including HTML, PDF, and XML)
Thereof 1,763 with geography defined
and 95 with unknown origin.
Total article views: 974 (including HTML, PDF, and XML)
Thereof 893 with geography defined
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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...
