Abstract

This study proposes a regional landslide early warning system for Idukki (India), using a decisional algorithm. The algorithm forecasts the possibility of occurrence of landslide by comparing the rainfall thresholds with the cumulated rainfall values. The region has suffered severe socio-economic setbacks during the disastrous landslides that happened in 2018 and 2019. Rainfall thresholds are defined for Idukki, using the total amount of precipitation cumulated at different time intervals ranging from 1 to 30 days. The first three-day cumulative values were used for evaluating the effect of short-term rainfall and the remaining days for the effect of long-term rainfall. The derived thresholds were calibrated using historical landslides and rainfall data from 2009 to 2017, optimized to reduce the false alarms and then validated using the 2018 data. The validation results show that the model is effectively predicting 79% of the landslides that happened in the region during 2018 and can be easily integrated with a rainfall forecasting system for the prediction of landslides. The model can be further improved with the availability of better spatial and temporal resolution of rainfall data and can be used as an effective tool for predicting the occurrence of landslides.

摘要

这项研究提出了使用决策算法的Idukki（印度）的区域滑坡预警系统。该算法通过将降雨阈值与累积的降雨值进行比较来预测发生滑坡的可能性。在2018年和2019年发生的灾难性山崩期间，该地区遭受了严重的社会经济挫折。为Idukki定义了降雨阈值，使用了在1到30天的不同时间间隔内累计的降水总量。前三天的累积值用于评估短期降雨的影响，其余几天用于评估长期降雨的影响。使用2009年至2017年的历史滑坡和降雨数据对得出的阈值进行校准，对其进行优化以减少虚假警报，然后使用2018年的数据进行验证。验证结果表明，该模型可以有效预测2018年该地区发生的79％的滑坡，并且可以轻松地与降雨预测系统集成以预测滑坡。该模型可以通过提供更好的时空分辨率的降雨数据而得到进一步改进，并且可以用作预测滑坡发生的有效工具。