Mountain resilience: a tool for mudflow risk management in the Ile Alatau Mountains, KazakhstanMussina, A., Raimbekova, Z., Shahgedanova, M. ORCID: https://orcid.org/0000-0002-2320-3885, Barandun, M., Narbayeva, K., Abdullayeva, A. and Nyssanbayeva, A. (2023) Mountain resilience: a tool for mudflow risk management in the Ile Alatau Mountains, Kazakhstan. Mountain Research and Development, 43 (1). ISSN 1994-7151
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1659/mrd-journal-d-22-00004 Abstract/SummaryThe densely populated central part of the Ile Alatau mountains is one of the most mudflow-prone areas of Kazakhstan. Implementation of protection measures, early warning systems, and risk management plans is crucial to protect livelihoods and infrastructure from damage caused by mudflows. Increasing harm and damage from mudflows in recent decades—due to more frequent events, as well as increased economic development of the area—has made the establishment and implementation of a mudflow risk management system a priority. The effectiveness of such a system largely depends on the scientific validity of the management plan and hence is determined by the level of knowledge of the physical processes triggering such events. This knowledge is based on information that must be collected, analyzed, and systematized. However, such data are not easy to access; they are scattered over different archives and research institutes or simply missing. In recent years, scientific monographs, articles, and reports have been published that attempt to collect and systematize data on mudflow phenomena in general. These efforts provide a basis for further work but are often not readily available for use. This article presents the updateable, interactive, intelligent information system “Mudflow phenomena of the central part of the Ile Alatau” that links cartographic information with data on mudflow formation centers. This system concentrates and collates existing knowledge, making it accessible to stakeholders and decision-makers who can turn this knowledge into suitable applications for adaptive and sustainable risk management.
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