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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534
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BibTeX: 41
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Views and downloads (calculated since 02 Aug 2021)
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Total article views: 1,125 (including HTML, PDF, and XML)
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800
284
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1,125
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HTML: 800
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Total: 1,125
BibTeX: 31
EndNote: 26
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545
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817
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Viewed (geographical distribution)
Total article views: 1,942 (including HTML, PDF, and XML)
Thereof 1,787 with geography defined
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Total article views: 1,125 (including HTML, PDF, and XML)
Thereof 1,046 with geography defined
and 79 with unknown origin.
Total article views: 817 (including HTML, PDF, and XML)
Thereof 741 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...
