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

Related authors

Potential of satellite-derived hydro-meteorological information for landslide initiation thresholds in Rwanda
Judith Uwihirwe, Alessia Riveros, Hellen Wanjala, Jaap Schellekens, Frederiek Sperna Weiland, Markus Hrachowitz, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 22, 3641–3661, https://doi.org/10.5194/nhess-22-3641-2022,https://doi.org/10.5194/nhess-22-3641-2022, 2022
Short summary
Interactions between deforestation, landscape rejuvenation, and shallow landslides in the North Tanganyika–Kivu rift region, Africa
Arthur Depicker, Gerard Govers, Liesbet Jacobs, Benjamin Campforts, Judith Uwihirwe, and Olivier Dewitte
Earth Surf. Dynam., 9, 445–462, https://doi.org/10.5194/esurf-9-445-2021,https://doi.org/10.5194/esurf-9-445-2021, 2021
Short summary

Related subject area

Landslides and Debris Flows Hazards
InSAR-informed in situ monitoring for deep-seated landslides: insights from El Forn (Andorra)
Rachael Lau, Carolina Seguí, Tyler Waterman, Nathaniel Chaney, and Manolis Veveakis
Nat. Hazards Earth Syst. Sci., 24, 3651–3661, https://doi.org/10.5194/nhess-24-3651-2024,https://doi.org/10.5194/nhess-24-3651-2024, 2024
Short summary
A coupled hydrological and hydrodynamic modeling approach for estimating rainfall thresholds of debris-flow occurrence
Zhen Lei Wei, Yue Quan Shang, Qiu Hua Liang, and Xi Lin Xia
Nat. Hazards Earth Syst. Sci., 24, 3357–3379, https://doi.org/10.5194/nhess-24-3357-2024,https://doi.org/10.5194/nhess-24-3357-2024, 2024
Short summary
More than one landslide per road kilometer – surveying and modeling mass movements along the Rishikesh–Joshimath (NH-7) highway, Uttarakhand, India
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci., 24, 3207–3223, https://doi.org/10.5194/nhess-24-3207-2024,https://doi.org/10.5194/nhess-24-3207-2024, 2024
Short summary
Temporal clustering of precipitation for detection of potential landslides
Fabiola Banfi, Emanuele Bevacqua, Pauline Rivoire, Sérgio C. Oliveira, Joaquim G. Pinto, Alexandre M. Ramos, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 24, 2689–2704, https://doi.org/10.5194/nhess-24-2689-2024,https://doi.org/10.5194/nhess-24-2689-2024, 2024
Short summary
Shallow-landslide stability evaluation in loess areas according to the Revised Infinite Slope Model: a case study of the 7.25 Tianshui sliding-flow landslide events of 2013 in the southwest of the Loess Plateau, China
Jianqi Zhuang, Jianbing Peng, Chenhui Du, Yi Zhu, and Jiaxu Kong
Nat. Hazards Earth Syst. Sci., 24, 2615–2631, https://doi.org/10.5194/nhess-24-2615-2024,https://doi.org/10.5194/nhess-24-2615-2024, 2024
Short summary

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. 
Bogaard, T. and Greco, R.: Preface “Hillslope hydrological modelling for landslides prediction,” Hydrol. Earth Syst. Sci., 18, 4185–4188, https://doi.org/10.5194/hess-18-4185-2014, 2014. 
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. 
Download
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.
Altmetrics
Final-revised paper
Preprint