# Rainfall Induced Landslide Studies in Indian Himalayan Region: A Critical Review
## 3 Results
### Landslide Forecasting  
Landslide forecasting is a key element for disaster risk reduction and is also the most challenging. Most of the landslides in the Indian Himalayan region are shallow in nature, of which rainfall is the primary triggering factor [34]. The analysis of precipitation for landslide occurrence can be performed by estimating minimum rainfall conditions, sub surface monitoring, or slope stability analysis. The minimum rainfall conditions, also known as thresholds, can be classified as empirical and physical approaches [40; 41; 42]. Physical models assess the relationship between rainfall conditions and hydrological conditions of the soil, which affects slope stability. The model analyzes the spatial variation of several factors such as geotechnical parameters, soil depth, volumetric water content, geology, and topography to determine the pore water pressure change and estimate the factor-of-safety. Such models need a large dataset of many parameters in spatial and temporal context, which is usually not available for the Indian Himalaya. Empirical methods analyze the rainfall conditions using statistical methods to determine threshold levels of precipitation. Such models are simpler to apply because they require only the spatial and temporal dataset of precipitation and landslide events [43; 44]. The threshold values can be greatly affected by the data quantity and quality, the rain gauge density, and the methodology used. The thresholds are usually determined by drawing (usually with statistical techniques) a lower line to the precipitation conditions corresponding to landslide events in log-log, semi-log, or Cartesian coordinate system [3; 41]. [PERSON] et al. [43] reviewed the type of thresholds, data collected, and other important information for thresholds determined in the global context for 2008-2017. The studies on rainfall thresholds for the Indian Himalayan region have been very limited. The use of empirical approach has been explored for different Himalayan regions. [PERSON] et al. [45] proposed the use of EMAP for Sikkim Himalayas, which is the ratio of cumulative event rainfall (E) to mean annual rainfall (MAP) (E\({}_{\text{MAP}}\) = EMAP), instead of rainfall event-duration (ED) or rainfall intensity-duration (ID) thresholds. [PERSON] and [PERSON] [3] determined ID thresholds for Garhwal Himalayas using best fit of the lower boundary of ID plane. [PERSON] and [PERSON] [4] developed the ID thresholds for Kalimpong region using frequentist statistical approach. The use of probabilistic [22; 46] and semi-automated algorithmic approach [47] has only been attempted for Kalimpong region. [PERSON] et al. [48] developed both regional (Sikkim) and local (Gangtok, Sikkim) ID thresholds using statistical approach. The main concerns with these studies are the coarse spatial distribution of rain gauges, all studies being performed using a single rain gauge, and the availability of only daily rainfall data. In this regard, [PERSON] et al. [49] highlighted that a coarse temporal resolution dataset of precipitation could lead to an underestimation of rainfall thresholds, which culminates in a higher number of false alarms when using thresholds for operational early warning system. In addition, the thresholds determined are rainfall intensity-duration thresholds, which should be avoided, while the determination of event rainfall-duration (ED) thresholds should be encouraged. [PERSON] et al. [50] established ID thresholds along the Rishikesh-Mana pilgrimage route for Garhwal Himalaya using Tropical Rainfall Measuring Mission (TRMM)-based Multi-satellite Precipitation Analysis (TMPA) data. Despite using different methods to determine various aspects of rainfall characteristics, all studies were unified in the effect of antecedent rainfall in the region. [PERSON] et al. [50] also suggested that antecedent rainfall ranging from 15 to 30 days plays an influential role for destabilizing slopes in the Himalayan region, which leads the subsequent rainfall of short duration (24-72 h) to trigger landslides.