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February 8, 2026Natural hazards and earth system sciences0 citationsOpen Access

Modelling the effectiveness of GLOF DRM measures – a case study from the Ala-Archa valley, Kyrgyz Republic

LNLaura NiggliHFHolger FreySASimon Allen

Key Points

  • The study aims to assess and model the effectiveness of different DRM measures for GLOFs in the Ala-Archa catchment.
  • Utilized numerical modelling techniques to assess DRM measures.
  • Evaluated three different measures: lake lowering, deflection dam, and retention basin.
  • Developed a hazard reduction score to compare the effectiveness of measures.
  • Compared outcomes against the current baseline hazard map.
  • Identified the relative effectiveness of each DRM measure in reducing GLOF risks.
  • Demonstrated cost and benefit considerations for each intervention.
  • Proposed a conceptual framework for future GLOF management.

Abstract

Abstract. Disaster risk management (DRM) for glacial lake outburst floods (GLOFs) is critical due to the increasing risk posed by GLOFs to downstream communities and infrastructure. However, the effectiveness of DRM measures remains insufficiently understood, which hinders effective and target-oriented decision-making in GLOF DRM. Existing research predominantly focuses on hazard aspects, with few scientific studies modelling the impacts of DRM measures comprehensively. In order to fill this gap, this study assesses the effectiveness of three different DRM measures for GLOFs in the Ala-Archa catchment, Kyrgyz Republic. Using numerical modelling, we map and assess the effect of three DRM measures: lake lowering, a deflection dam, and a retention basin and compare it to the current baseline hazard map. We develop a hazard reduction score for comparison of the measures and evaluate their effectiveness based on cost and benefit considerations. This study proposes a conceptual framework and methodology that can guide the management of GLOF and debris flow risks in similar contexts globally.

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Cite This Study

Niggli et al. (2026) studied this question.

synapsesocial.com/papers/698828330fc35cd7a8847781https://doi.org/10.5194/nhess-26-733-2026
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