Articles | Volume 24, issue 5
https://doi.org/10.5194/nhess-24-1579-2024
https://doi.org/10.5194/nhess-24-1579-2024
Research article
 | 
06 May 2024
Research article |  | 06 May 2024

Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico

Rex L. Baum, Dianne L. Brien, Mark E. Reid, William H. Schulz, and Matthew J. Tello

Related authors

Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach
S. Raia, M. Alvioli, M. Rossi, R. L. Baum, J. W. Godt, and F. Guzzetti
Geosci. Model Dev., 7, 495–514, https://doi.org/10.5194/gmd-7-495-2014,https://doi.org/10.5194/gmd-7-495-2014, 2014

Related subject area

Landslides and Debris Flows Hazards
Comparison of conditioning factor classification criteria in large-scale statistically based landslide susceptibility models
Marko Sinčić, Sanja Bernat Gazibara, Mauro Rossi, and Snježana Mihalić Arbanas
Nat. Hazards Earth Syst. Sci., 25, 183–206, https://doi.org/10.5194/nhess-25-183-2025,https://doi.org/10.5194/nhess-25-183-2025, 2025
Short summary
Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems
Benjamin B. Mirus, Thom Bogaard, Roberto Greco, and Manfred Stähli
Nat. Hazards Earth Syst. Sci., 25, 169–182, https://doi.org/10.5194/nhess-25-169-2025,https://doi.org/10.5194/nhess-25-169-2025, 2025
Short summary
Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer
Jui-Sheng Chou, Hoang-Minh Nguyen, Huy-Phuong Phan, and Kuo-Lung Wang
Nat. Hazards Earth Syst. Sci., 25, 119–146, https://doi.org/10.5194/nhess-25-119-2025,https://doi.org/10.5194/nhess-25-119-2025, 2025
Short summary
Limit analysis of earthquake-induced landslides considering two strength envelopes
Di Wu, Yuke Wang, and Xin Chen
Nat. Hazards Earth Syst. Sci., 24, 4617–4630, https://doi.org/10.5194/nhess-24-4617-2024,https://doi.org/10.5194/nhess-24-4617-2024, 2024
Short summary
The vulnerability of buildings to a large-scale debris flow and outburst flood hazard cascade that occurred on 30 August 2020 in Ganluo, southwest China
Li Wei, Kaiheng Hu, Shuang Liu, Lan Ning, Xiaopeng Zhang, Qiyuan Zhang, and Md. Abdur Rahim
Nat. Hazards Earth Syst. Sci., 24, 4179–4197, https://doi.org/10.5194/nhess-24-4179-2024,https://doi.org/10.5194/nhess-24-4179-2024, 2024
Short summary

Cited articles

Aaron, J., McDougall, S., Moore, J. R., Coe, J. A., and Hungr, O.: The role of initial coherence and path materials in the dynamics of three rock avalanche case histories, Geoenvironmental Disasters, 4, 5, https://doi.org/10.1186/s40677-017-0070-4, 2017. 
Alvioli, M. and Baum, R. L.: Parallelization of the TRIGRS model for rainfall-induced landslides using the message passing interface, Environ. Modell. Softw., 81, 122–135, https://doi.org/10.1016/j.envsoft.2016.04.002, 2016a. 
Alvioli, M. and Baum, R. L.: Serial and parallel versions of the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model (TRIGRS, version 2.1), U.S. Geol. Surv. software release [code], https://doi.org/10.5066/F7M044QS, 2016b. 
Alvioli, M., Marchesini, I., Reichenbach, P., Rossi, M., Ardizzone, F., Fiorucci, F., and Guzzetti, F.: Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling, Geosci. Model Dev., 9, 3975–3991, https://doi.org/10.5194/gmd-9-3975-2016, 2016. 
Arnone, E., Noto, L., Lepore, C., and Bras, R.: Physically-based and distributed approach to analyze rainfall-triggered landslides at watershed scale, Geomorphology, 133, 121–131, https://doi.org/10.1016/j.geomorph.2011.03.019, 2011. 
Download
Short summary
We mapped potential for heavy rainfall to cause landslides in part of the central mountains of Puerto Rico using new tools for estimating soil depth and quasi-3D slope stability. Potential ground-failure locations correlate well with the spatial density of landslides from Hurricane Maria. The smooth boundaries of the very high and high ground-failure susceptibility zones enclose 75 % and 90 %, respectively, of observed landslides. The maps can help mitigate ground-failure hazards.
Altmetrics
Final-revised paper
Preprint