International audienceContinental rifts begin and develop through repeated episodes of faulting and magmatism, but strain partitioning between faulting and magmatism during discrete rifting episodes remains poorly documented. In highly evolved rifts, tensile stresses from far-field plate motions accumulate over decades before being released during relatively short time intervals by faulting and magmatic intrusions1, 2, 3. These rifting crises are rarely observed in thick lithosphere during the initial stages of rifting. Here we show that most of the strain during the July–August 2007 seismic crisis in the weakly extended Natron rift, Tanzania, was released aseismically. Deformation was achieved by slow slip on a normal fault that promoted subsequent dyke intrusion by stress unclamping. This event provides compelling evidence for strain accommodation by magma intrusion, in addition to slip along normal faults, during the initial stages of continental rifting and before significant crustal thinning
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.
along a 20 km-long fracture network extending from the volcano to the city of Goma. The event was captured by InSAR data from the ERS-2 and RADARSAT-1 satellites. A combination of 3D numerical modeling and inversions is used to analyze these displacements. Using Akaike Information Criteria, we determine that a model with two subvertical dikes is the most likely explanation for the 2002 InSAR deformation signal. A first, shallow dike, 2 km high, is associated with the eruptive fissure, and a second, deeper dike, 6 km high and 40 km long, lies about 3 km below the city of Goma. As the deep dike extends laterally for 20 km beneath the gas-rich Lake Kivu, the interaction of magma and dissolved gas should be considered as a significant hazard for future eruptions. A likely scenario for the eruption is that the magma supply to a deep reservoir started ten months before the eruption, as indicated by LP events and tremor. Stress analysis indicates that the deep dike could have triggered the injection of magma from the lake and shallow reservoir into the eruptive dike. The deep dike induced the opening of the southern part of this shallow dike, to which it transmitted magma though a narrow dike. This model is consistent with the geochemical analysis, the lava rheology and the pre-and post-eruptive seismicity. We infer low overpressures (1-10 MPa) for the dikes. These values are consistent with lithostatic crustal stresses close to the dikes and low magma pressure. As a consequence, the dike direction is probably not controlled by stresses but rather by a reduced tensile strength, inherited from previous rift intrusions. The lithostatic stresses indicate that magmatic activity is intense enough to relax tensional stresses associated with the rift extension.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.