Articles | Volume 22, issue 5
https://doi.org/10.5194/nhess-22-1723-2022
https://doi.org/10.5194/nhess-22-1723-2022
Research article
 | 
23 May 2022
Research article |  | 23 May 2022

Integration of observed and model-derived groundwater levels in landslide threshold models in Rwanda

Judith Uwihirwe, Markus Hrachowitz, and Thom Bogaard

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Cited articles

Bakker, M. and Schaars, F.: Solving Groundwater Flow Problems with Time Series Analysis: You May Not Even Need an other Model, National Ground Water Association, 57, 826–833, https://doi.org/10.1111/gwat.12927, 2019. 
Berti, M., Martina, M. L. V., Franceschini, S., Pignone, S., Simoni, A., and Pizziolo, M.: Probabilistic rainfall thresholds for landslide occurrence using a Bayesian approach, J. Geophys. Res.-Earth, 117, F04006, https://doi.org/10.1029/2012JF002367, 2012. 
Bishop, A. W.: Some Factors Controlling the Pore Pressures set up during the Construction of Earth Dams, Imperial College, University of London, https://doi.org/10.1680/geot.1954.4.4.148, 1954. 
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Bogaard, T. and Greco, R.: Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds, Nat. Hazards Earth Syst. Sci., 18, 31–39, https://doi.org/10.5194/nhess-18-31-2018, 2018. 
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Short summary
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.
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