Abstract
Landslides are natural disasters which can create major setbacks to the socioeconomic of a region. Destructive landslides may happen in a quick time, resulting in severe loss of lives and properties. Landslide Early Warning Systems (LEWS) can reduce the risk associated with landslides by providing enough time for the authorities and the public to take necessary decisions and actions. LEWS are usually based on statistical rainfall thresholds, but this approach is often associated to high false alarms rates. This manuscript discusses the development of an integrated approach, considering both rainfall thresholds and field monitoring data. The method was implemented in Kalimpong, a town in the Darjeeling Himalayas, India. In this work, a decisional algorithm is proposed using rainfall and real-time field monitoring data as inputs. The tilting angles measured using MicroElectroMechanical Systems (MEMS) tilt sensors were used to reduce the false alarms issued by the empirical rainfall thresholds. When critical conditions are exceeded for both components of the systems (rainfall thresholds and tiltmeters), authorities can issue an alert to the public regarding a possible slope failure. This approach was found effective in improving the performance of the conventional rainfall thresholds. We improved the efficiency of the model from 84% (model based solely on rainfall thresholds) to 92% (model with the integration of field monitoring data). This conceptual improvement in the rainfall thresholds enhances the performance of the system significantly and makes it a potential tool that can be used in LEWS for the study area.
Highlights
Landslides are geomorphological processes, which can sometimes lead to severe loss of lives and properties [1,2]
The rainfall thresholds defined for Kalimpong region in Darjeeling Himalayas has been evaluated quantitatively, using the recent rainfall and landslide data from 2017 to 2020 monsoons
The analysis proves that the large number of false alarms makes the conventional empirical rainfall thresholds unsuitable for use in an Landslide Early Warning Systems (LEWS)
Summary
Landslides are geomorphological processes, which can sometimes lead to severe loss of lives and properties [1,2]. Water 2020, 12, 3453 associated with landslides is increasing worldwide in similar environments, leading to the need of establishing early warning systems. The definition of rainfall thresholds is the most widely followed approach for the setting up of landslide early warning systems [3,4]. While at the local scale rainfall thresholds can be defined with physically-based approaches [5,6,7,8], at regional scale empirical approaches are used and the threshold definition is usually based on establishing a statistical correlation between the occurrence of landslides in the study area and some parameters describing the triggering rainfall [9,10,11,12]. Three parameters are considered to define a rainfall event: (i) The cumulative event rainfall (E), which is the total precipitation recorded from the beginning of continuous rainfall till the time of occurrence of failure; (ii) the rainfall duration (D) and (iii) the rainfall intensity (I), which is calculated as the ratio of cumulated event rainfall to duration
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