Satellite rainfall products for landslide early warning prediction have been spotlighted by several researchers, in the last couple of decades. This study investigates the use of TRMM and ERA-Interim data, for the determination of rainfall thresholds and the prediction of precipitation, respectively, to be used for landslide early warning purposes at the Bogowonto catchment, Central Java, Indonesia. A landslide inventory of 218 landslides for the period of 2003–2016 was compiled, and rainfall data were retrieved for the landslide locations, as given by 6 ground stations, TRMM, and ERA-Interim data. First, rainfall data from the three different sources was compared in terms of correlation and extreme precipitation indices. Second, a procedure for the calculation of rainfall thresholds for landslide occurrence was followed consisting of four steps: i) the TRMM-based rainfall data was reconstructed for selected dates and locations characterized by landslide occurrence and non-occurrence; ii) the antecedent daily rainfall was calculated for 3, 5, 10, 15, 20 and 30 days for the selected dates and locations; iii) two-parameter daily rainfall-antecedent rainfall thresholds were calculated for the aforementioned dates; after analysis of the curves the optimum number of antecedent rainfall days was selected; and (iv) empirical rainfall thresholds for landslide occurrence were determined. The procedure was repeated for the entire landslide dataset, differentiating between forested and built-up areas, and between landslide occurrence in four temporal periods, in relation to the monsoon. The results indicated that TRMM performs well for the detection of very heavy precipitation and can be used to indicate the extreme rainfall events that trigger landslides. On the contrary, as ERA-Interim failed to detect those events, its applicability for LEWS remains limited. The 15-day antecedent rainfall was indicated to mostly affect the landslide occurrence in the area. The rainfall thresholds vary for forested and built-up areas, as well as for the beginning, middle and end of the rainy season.

在过去的几十年中，几位研究人员关注了用于滑坡预警预测的卫星降雨产品。这项研究调查了TRMM和ERA-Interim数据的使用，分别用于确定降雨阈值和预测降水量，这些数据将用于印度尼西亚中爪哇省Bogowonto流域的滑坡预警。编制了2003-2016年间218个滑坡的滑坡清单，并检索了该滑坡位置的降雨数据，该数据由6个地面站，TRMM和ERA-Interim数据给出。首先，比较了三种不同来源的降雨数据的相关性和极端降水指数。其次，遵循了计算滑坡发生的降雨阈值的过程，该过程包括四个步骤：i）针对特定日期和位置重建了基于TRMM的降雨数据，这些数据以滑坡发生和不发生为特征；ii）在选定的日期和地点计算了3、5、10、15、20和30天的前日降雨量；iii）计算了上述日期的两参数日降雨前降雨阈值；在对曲线进行分析之后，选择了最佳的前雨天数；（iv）确定了滑坡发生的经验降雨阈值。对整个滑坡数据集重复此过程，以区分森林和建成区，以及相对于季风在四个时间周期内发生的滑坡。结果表明，TRMM在非常强降水的检测中表现良好，可用于指示触发滑坡的极端降雨事件。相反，由于ERA-Interim无法检测到这些事件，因此其对LEWS的适用性仍然受到限制。前15天的降雨表明该地区大部分地区发生了滑坡。降雨阈值随森林和人为密集地区以及雨季的开始，中期和结束而变化。