**1. Introduction**

Landslides can be considered as processes that move earth and rock downwards by sliding, falling and flowing in response to the extant conditions [1]. Within a span of seven years from 2004 to 2010, a total of 2620 landslides were recorded globally, which led to the loss of 32,322 lives [2]. In India, most of the highlands are affected by landslides and rainfall is identified as the major triggering factor in the Himalayas and Western Ghats [3–6]. The rise in population demands for the urbanization in high-altitude regions, which are usually susceptible to mass movements; therefore, when such places become densely populated areas, landslides cause severe fatalities. Recent changes in climate are also worsening the situation, with an increase in high intensity rainfalls and the consequent triggering of rapid mass movements [7,8], such as the debris flows, which occurred in Wayanad district in the state of Kerala during 2018 and 2019. The region is affected by a number of debris flows, with run-out distances as long as 3 km. Most of the slope failures that occurred during the 2018 monsoon also occurred during the 2019 monsoon as well. Thus, the increasing vulnerability of the region emphasizes the need for landslide early warning systems (LEWS) to forecast future events. Research has been carried out for establishing LEWS using the relationship between rainfalls and landslides in the Indian Himalayas [9–12], but detailed investigations for the Western Ghats have not been conducted yet. A LEWS should be developed on a regional scale for Wayanad district, incorporating monitoring tools and rainfall thresholds so that warnings can be issued to authorities and the local community. As a first step, this study focuses on establishing intensity–duration thresholds for the study area using statistical analysis.

Rainfall thresholds can be defined as a critical state of rainfall parameters from which an effect or result (landslides) can happen [13]. The minimum quantity of accumulated rainfall parameters which are required to trigger a landslide event will define the rainfall threshold for a region. Empirical and process-based approaches are widely used by researchers for developing rainfall thresholds [8,14–23]. The definition of a process-based threshold is associated with detailed site investigations and precise measurements. This approach is suitable for local scale or site-specific studies where the hydro-meteo-geological parameters can be monitored with required accuracy. Owing to the difficulties in estimating such parameters on a regional scale, this research focuses on an empirical approach to derive the rainfall thresholds using historical data. A rainfall event is usually characterized by three parameters: rainfall event (E), intensity (I), and duration (D). An event rainfall is the total accumulated amount of rainfall during a period of continuous precipitation, dubbed the duration of rainfall. The classical definition of intensity of rainfall is the average rate of precipitation usually expressed in mm/h or mm/day. Intensity–duration thresholds were first established by considering 73 landslides in several parts of the world by Caine in 1980 [24]. The definition of threshold, considering the minimum boundary, was then followed by researchers across the globe for analyzing local, regional and global scale thresholds [25–30]. Moreover, high intensity rainfalls are often associated with landslides in hilly areas [31] and when an empirical approach is pursued in regional scale studies, rainfall is more influential that site and slope characteristics [31–33]. For defining the minimum boundary or threshold, different statistical approaches can be used [34]. In literature, different definitions are adopted to calculate the intensity used in threshold analysis, such as mean intensity of an event [24], peak intensity [25] or most extreme intensity of sub-events [23].

Deducing the rainfall event associated with the occurrence of a landslide is the key factor in determining the threshold conditions. A recent review highlights that rain gauges are the most widely used instrument to collect rainfall data [35]. The selection of rain gauge in data-scarce regions are mostly forced, as the nearest rain gauge is selected based on spatial constraints and minor refinements [5,35,36]. In some studies, when rain gauge density is very small, landslides outside a specific radius from rain gauges are discarded, thus further reducing the amount of available data [37]. Moreover, some scholars

observed that the threshold definition can be very sensitive to some boundary conditions, such as the rain gauge selection and characteristics or the delimitation of alert zones [22,38].

This research focuses on the effect of different approaches of analysis, including different definitions of rainfall intensity and different rain gauge configurations by using the database developed for the study area of Kerala (India). The term "approach" is used in this study, denoting the process of identification of a rainfall event which results in a landslide. The objective is to understand how the identification of rainfall parameters can affect the development of the rainfall threshold on both local and regional scales. Being one of the most followed approaches, the reliability of developing rainfall thresholds based on the nearest rain gauge is used as a benchmark and quantitatively compared with other strategies.
