Landslide hazard remains poorly characterized on regional and global scales. In the tropics in particular, the lack of knowledge on landslide hazard is in sharp contrast with the high landslide susceptibility of the region. Moreover, landslide hazard in the tropics is expected to increase in the future in response to growing demographic pressure and climate and land use changes. With precipitation as the primary trigger for landslides in the tropics, there is a need for an accurate determination of rainfall thresholds for landslide triggering based on regional rainfall information as well as reliable data on landslide occurrences. Here, we present the landslide inventory for the central section of the western branch of the East African Rift (LIWEAR). Specific attention is given to the spatial and temporal accuracy, reliability, and geomorphological meaning of the data. The LIWEAR comprises 143 landslide events with known location and date over a span of 48 years from 1968 to 2016. Reported landslides are found to be dominantly related to the annual precipitation patterns and increasing demographic pressure. Field observations in combination with local collaborations revealed substantial biases in the LIWEAR related to landslide processes, landslide impact, and the remote context of the study area. In order to optimize data collection and minimize biases and uncertainties, we propose a threephase, Search-Store-Validate, workflow as a framework for data collection in a data-poor context. The validated results indicate that the proposed methodology can lead to a reliable landslide inventory in a data-poor context, valuable for regional landslide hazard assessment at the considered temporal and spatial resolutions.
Accurate precipitation data are fundamental for understanding and mitigating the disastrous effects of many natural hazards in mountainous areas. Floods and landslides, in particular, are potentially deadly events that can be mitigated with advanced warning, but accurate forecasts require timely estimation of precipitation, which is problematic in regions such as tropical Africa with limited gauge measurements. Satellite rainfall estimates (SREs) are of great value in such areas, but rigorous validation is required to identify the uncertainties linked to SREs for hazard applications. This paper presents results of an unprecedented record of gauge data in the western branch of the East African Rift, with temporal resolutions ranging from 30 min to 24 h and records from 1998 to 2018. These data were used to validate the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) research version and near-real-time products for 3-hourly, daily, and monthly rainfall accumulations, over multiple spatial scales. Results indicate that there are at least two factors that led to the underestimation of TMPA at the regional level: complex topography and high rainfall intensities. The TMPA near-real-time product shows overall stronger rainfall underestimations but lower absolute errors and a better performance at higher rainfall intensities compared to the research version. We found area-averaged TMPA rainfall estimates relatively more suitable in order to move toward regional hazard assessment, compared to data from scarcely distributed gauges with limited representativeness in the context of high rainfall variability.
Abstract. Natural disasters are too often presented as resulting from extreme natural phenomena affecting helpless populations, with people being insufficiently aware of the factors leading to disasters and of the existing strategies to mitigate their impacts. We developed a board game aimed at raising awareness about geohazards and disaster risk reduction strategies. The target groups are (1) secondary school students and citizens and (2) scientists and stakeholders involved in risk management activities. For the first group, the aim is to induce a better understanding of the geohazards and disasters they are confronted with in the media or in their daily lives; for the second, the objective is to generate discussion about risk management strategies. The game was tested with students in Belgium and with citizens, earth scientists, and risk managers in several African countries. Based on analysis of the most common game strategies observed, the players' reactions during the game, and their answers to a short questionnaire, we analyzed the main learning outcomes conveyed by this game. The game Hazagora appears to positively enhance the players' insights into processes involved in disasters. As such, the game is an effective, fun learning tool to introduce participants to the concepts of geohazards and disasters and to generate discussion.
Classical mechanisms of volcanic eruptions mostly involve pressure buildup and magma ascent towards the surface1. Such processes produce geophysical and geochemical signals that may be detected and interpreted as eruption precursors1–3. On 22 May 2021, Mount Nyiragongo (Democratic Republic of the Congo), an open-vent volcano with a persistent lava lake perched within its summit crater, shook up this interpretation by producing an approximately six-hour-long flank eruption without apparent precursors, followed—rather than preceded—by lateral magma motion into the crust. Here we show that this reversed sequence was most likely initiated by a rupture of the edifice, producing deadly lava flows and triggering a voluminous 25-km-long dyke intrusion. The dyke propagated southwards at very shallow depth (less than 500 m) underneath the cities of Goma (Democratic Republic of the Congo) and Gisenyi (Rwanda), as well as Lake Kivu. This volcanic crisis raises new questions about the mechanisms controlling such eruptions and the possibility of facing substantially more hazardous events, such as effusions within densely urbanized areas, phreato-magmatism or a limnic eruption from the gas-rich Lake Kivu. It also more generally highlights the challenges faced with open-vent volcanoes for monitoring, early detection and risk management when a significant volume of magma is stored close to the surface.
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