Preprints
https://doi.org/10.5194/nhess-2024-152
https://doi.org/10.5194/nhess-2024-152
19 Sep 2024
 | 19 Sep 2024
Status: this preprint is currently under review for the journal NHESS.

Derivation of Moisture-Driven Landslide Thresholds for Northeastern Regions of the Indian Himalayas

Danish Monga and Poulomi Ganguli

Abstract. Landslides pose a significant threat in the Northeastern Himalayas, driven by monsoonal rains and exacerbated by rapid urbanization. This research establishes moisture (primarily rainfall) thresholds that can cause landslides in Northeastern Himalayas 'hotspots' based on 490 rain-driven landslides catalogued between 2006 and 2019. Coupling the innovative Regularized Expectation-Maximization approach with non-crossing quantile regression, we reveal critical insights into antecedent moisture conditions and their role in shallow to deep landslide genesis. Our derived moisture threshold for the Northeastern Himalayan region, E (mm) = −11.10 + 0.62 D (hour), for 24 < D < 1440 hr, fits within global bounds for both deep and shallow landslides. The spatial analysis demonstrates significant heterogeneity, with Guwahati (located at 26.14° N, 91.74° E in Assam) and Shillong (located at 25.58° N, 91.89° E in Meghalaya) requiring higher cumulative rainfall for landslide triggers compared to Aizwal (located at 23.73° N, 92.72° E in Mizoram). Our analysis shows that environmental controls, e.g., elevation, slope, land use types, CND, and rock types, play significant roles in shaping rainfall thresholds to trigger landslides. The insights from this research offer effective landslide risk management strategies and advance the predictive capabilities of Landslide Early Warning Systems with broader implications for climate resilience and disaster preparedness.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Danish Monga and Poulomi Ganguli

Status: open (until 31 Oct 2024)

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Danish Monga and Poulomi Ganguli
Danish Monga and Poulomi Ganguli

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Short summary
Using novel statistical methodology, non-crossing quantile regression, we develop at-site and regional rainfall thresholds to trigger landslides in vulnerable sites of the Northeast Himalayas. Next, we analyze the influence of potential environmental controls in mediating the rain thresholds. The findings of the study add value to updating, enhancing, and understanding spatial variability of rain thresholds across landslide-affected areas of the Northeast Himalayas.
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