Abstract
Abstract. Landslides pose a serious threat to life and property in Central America and the Caribbean Islands. In order to allow regionally coordinated situational awareness and disaster response, an online decision support system was created. At its core is a new flexible framework for evaluating potential landslide activity in near real time: Landslide Hazard Assessment for Situational Awareness. This framework was implemented in Central America and the Caribbean by integrating a regional susceptibility map and satellite-based rainfall estimates into a binary decision tree, considering both daily and antecedent rainfall. Using a regionally distributed, percentile-based threshold approach, the model outputs a pixel-by-pixel nowcast in near real time at a resolution of 30 arcsec to identify areas of moderate and high landslide hazard. The daily and antecedent rainfall thresholds in the model are calibrated using a subset of the Global Landslide Catalog in Central America available for 2007–2013. The model was then evaluated with data for 2014. Results suggest reasonable model skill over Central America and poorer performance over Hispaniola due primarily to the limited availability of calibration and validation data. The landslide model framework presented here demonstrates the capability to utilize globally available satellite products for regional landslide hazard assessment. It also provides a flexible framework to interchange the individual model components and adjust or calibrate thresholds based on access to new data and calibration sources. The availability of free satellite-based near real-time rainfall data allows the creation of similar models for any study area with a spatiotemporal record of landslide events. This method may also incorporate other hydrological or atmospheric variables such as numerical weather forecasts or satellite-based soil moisture estimates within this decision tree approach for improved hazard analysis.
Highlights
The ability to estimate or forecast landslide activity is largely dependent on the scale at which the analysis is undertaken as well as the availability of geomorphologic, atmospheric and landslide data for the study region
The Landslide Hazard Assessment for Situational Awareness (LHASA) model was evaluated over Central America and Hispaniola for 2007–2013 and compared with an independent validation data set for 2014
The ultimate goal of this paper is to present the LHASA model framework with a set of calibrated thresholds for Central America and the Caribbean region
Summary
The ability to estimate or forecast landslide activity is largely dependent on the scale at which the analysis is undertaken as well as the availability of geomorphologic, atmospheric and landslide data for the study region. Empirical studies can focus on local to regional scales but are constrained by the availability of landslide information and surface products that can be used to create a homogenous picture of landslide hazard over the region. Satellite rainfall products provide the opportunity to approximate the conditions that lead to rainfall-triggered landslides over regional scales, especially where rain gauge networks are sparse. The Tropical Rainfall Measuring Mission (TRMM) and its successor, the Global Precipitation Measurement (GPM) mission, provide a multidecadal record of precipitation estimates that can be used to systematically evaluate rainfall and estimate landslide triggering relationships over multiple spatial and temporal scales
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