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Abstract Understanding how soil thickness and bedrock weathering vary across ridge and valley topography is needed to constrain the flowpaths of water and sediment production within a landscape. Here, we investigate saprolite and weathered bedrock properties across a ridge‐valley system in the Northern California Coast Ranges, USA, where topography varies with slope aspect such that north‐facing slopes have thicker soils and are more densely vegetated than south‐facing slopes. We use active source seismic refraction surveys to extend observations made in boreholes to the hillslope scale. Seismic velocity models across several ridges capture a high velocity gradient zone (from 1,000 to 2,500 m/s) located ∼4–13 m below ridgetops that coincides with transitions in material strength and chemical depletion observed in boreholes. Comparing this transition depth across multiple north‐ and south‐facing slopes, we find that the thickness of saprolite does not vary with slope aspects. Additionally, seismic survey lines perpendicular and parallel to bedding planes reveal weathering profiles that thicken upslope and taper downslope to channels. Using a rock physics model incorporating seismic velocity, we estimate the total porosity of the saprolite and find that inherited fractures contribute a substantial amount of pore space in the upper 6 m, and the lateral porosity structure varies strongly with hillslope position. The aspect‐independent weathering structure suggests that the contemporary critical zone structure at Rancho Venada is a legacy of past climate and vegetation conditions. 

{"Abstract":["Supplementary code and model files for the manuscript entitled "Elucidating the Magma Plumbing System of Ol Doinyo Lengai (Natron Rift, Tanzania) Using Satellite Geodesy and Numerical Modeling". OlDoinyoLengai_code_and_models.zip contains all necessary Matlab code, functions, input and output files for the GNSS, InSAR, and joint inversions presented in our manuscript necessary to reproduce the results. dMODELS is an open source code developed by the United States Geological Survey. The originally published program is available here: https://pubs.usgs.gov/tm/13/b1/ and the revised software archived here will also be available through the USGS website code.usgs.gov/vsc/publications/OlDoinyoLengai or by contacting Maurizio Battaglia. With this manuscript we are providing an update to dMODELS that includes improved graphics and joint inversion capabilities for both InSAR and GNSS data. <\/p>"],"Other":["This work was funded by the National Science Foundation (NSF) grant number EAR-1943681, Virginia Tech, Korean Institute of Geosciences and Minerals (KIGAM), and Ardhi University. Funding for this work also came from USAID via the Volcano Disaster Assistance Program and from the U.S. Geological Survey (USGS) Volcano Hazards Program.This material is based on services provided by the GAGE Facility, operated by UNAVCO, Inc., with support from the National Science Foundation, the National Aeronautics and Space Administration, and the U.S. Geological Survey under NSF Cooperative Agreement EAR-1724794. We acknowledge and thank Alaska Satellite Facility for making InSAR data freely available and TZVOLCANO GNSS data sets available through the UNAVCO data archive."]} 

Abstract On August 14, 2021, aMw7.2 earthquake struck the Tiburon Peninsula of western Haiti triggering thousands of landslides. Three days after the earthquake on August 17, 2021, Tropical Storm Grace crossed shallow waters offshore of southern Haiti triggering more landslides worsening the situation. In the aftermath of these events, several organizations with disaster response capabilities or programs activated to provide information on the location of landslides to first responders on the ground. Utilizing remote sensing to support rapid response, one organization manually mapped initiation point of landslides and three automatically detected landslides. The 2021 Haiti event also provided a unique opportunity to test different automated landslide detection methods that utilized both SAR and optical data in a rapid response scenario where rapid situational awareness was critical. As the methods used are highly replicable, the main goal of this study is to summarize the landslide rapid response products released by the organizations, detection methods, quantify accuracy and provide guidelines on how some of the shortcomings encountered in this effort might be addressed in the future. To support this validation, a manually mapped polygon-based landslide inventory covering the entire affected area was created and is also released through this effort. 

Abstract Over the last 7 years, geodetic data have detected periods of uplift and subsidence of the active volcano Ol Doinyo Lengai in Tanzania. Although numerous eruptions of the volcano have occurred historically, a systematic investigation of transient deformation using continuous Global Navigation Satellite System (GNSS) data has not been undertaken. We use the Targeted Projection Operator (TPO) to assess 7 years of continuous GNSS data from the TZVOLCANO network for transient signals and find rapid uplift spanning March 2022–December 2022 and then steady‐state uplift through August 2023. We conduct a nonlinear inversion of the GNSS velocities associated with the transient signal using dMODELS and find consistency with an inflating spheroidal source located 2.3 ± 0.6 km beneath the crater. Prior to March 2022, geodetic data indicated quiescence just below Ol Doinyo Lengai, thus detecting transient deformation with TPO allows for tracking changes in the magmatic system over time in the Natron Rift. 

Abstract The creation of fractures in bedrock dictates water movement through the critical zone, controlling weathering, vadose zone water storage, and groundwater recharge. However, quantifying connections between fracturing, water flow, and chemical weathering remains challenging because of limited access to the deep critical zone. Here we overcome this challenge by coupling measurements from borehole drilling, groundwater monitoring, and seismic refraction surveys in the central California Coast Range. Our results show that the subsurface is highly fractured, which may be driven by the regional geologic and tectonic setting. The pervasively fractured rock facilitates infiltration of meteoric water down to a water table that aligns with oxidation in exhumed rock cores and is coincident with the adjacent intermittent first‐order stream channel. This work highlights the need to incorporate deep water flow and weathering due to pervasive fracturing into models of catchment water balances and critical zone weathering, especially in tectonically active landscapes. 

Abstract The intrusion of magma into Kīlauea's lower East Rift Zone in May 2018 led to the largest eruption along this segment of the volcano in over 200 years. As magma drained from the rift zone, leading to the collapse of Pu'u ‘Ō‘ō, pressure at the summit initially remained elevated and dropped at a slower rate compared to historical intrusion events. The anomalously long timescale of summit deflation suggests that the dike was fed from multiple sources. Here we show that dikes can serve as “dipsticks” of magma reservoirs and that the co‐evolution of dike growth and reservoir deflation constrains key magma transport parameters. Using coupled dike‐chamber models constrained by ground deformation and seismicity, we test four configurations of magma plumbing in order to illuminate which reservoirs and transport pathways were activated during the intrusion phase (30 April to 3 May) of the 2018 event. Slow summit deflation relative to the rate of dike propagation is best explained by a model in which the dike initiates from a compressible magma reservoir in the East Rift Zone, which then drains magma upstream from the Halema'uma'u reservoir through a shallow transport system. We use a Bayesian Markov chain Monte Carlo (MCMC) approach to estimate storage parameters for both reservoirs as well as the effective conductivity of the shallow magma transport system in the East Rift Zone, finding good agreement with independent estimates. Our results suggest that the rupture of reservoirs from within the East Rift Zone presents a unique hazard at Kīlauea. 

Abstract Interseismic deformation describes the gradual accumulation of crustal strain within the tectonic plate and along the plate boundaries before the sudden release as earthquakes. In this study, we use 5 years of high spatial and temporal geodetic measurements, including Global Navigation Satellite System and Interferometric Synthetic Aperture Radar to monitor 3‐dimension interseismic crustal deformation and horizontal strain rate in Taiwan. We find significant deformation (strain rate >8  10⁻⁶ yr⁻¹) along the plate boundary between the Philippine Sea and the Eurasian Plates in east Taiwan. The high strain rate in the southern part of the Western Foothills is distributed along a few major fault systems, which reveals the geometry of the deformation front in west Taiwan. Our results help identify active faults in southwest and north Taiwan that were not identified before. These findings can be insightful in informing future seismic hazard models. 

Abstract. Rapid detection of landslides is critical for emergency response, disaster mitigation, and improving our understanding of landslide dynamics. Satellite-based synthetic aperture radar (SAR) can be used to detect landslides, often within days of a triggering event, because it penetrates clouds, operates day and night, and is regularly acquired worldwide. Here we present a SAR backscatter change approach in the cloud-based Google Earth Engine (GEE) that uses multi-temporal stacks of freely available data from the Copernicus Sentinel-1 satellites to generate landslide density heatmaps for rapid detection. We test our GEE-based approach on multiple recent rainfall- and earthquake-triggered landslide events. Our ability to detect surface change from landslides generally improves with the total number of SAR images acquired before and after a landslide event, by combining data from both ascending and descending satellite acquisition geometries and applying topographic masks to remove flat areas unlikely to experience landslides. Importantly, our GEE approach does not require downloading a large volume of data to a local system or specialized processing software, which allows the broader hazard and landslide community to utilize and advance these state-of-the-art remote sensing data for improved situational awareness of landslide hazards. 

ABSTRACT The Mw 7.5 earthquake that struck central Papua New Guinea in 2018 was the largest event ever recorded in the region with modern seismic instruments. The ground motions associated with this event also triggered widespread landslides and affected more than 500,000 people. However, due to the absence of a local seismic and Global Positioning System network in the vicinity, the fault location, system, and slip distribution of this earthquake are not well documented. In this study, we use the subpixel offset method on the Copernicus Sentinel-1 Synthetic Aperture Radar (SAR) images to calculate the 3D coseismic displacement of the 2018 Papua New Guinea earthquake. The results show clear fault traces that suggest coseismic slip on the Mubi fault and the Mananda fault that triggered landslides that spread out in a more than 260  km2 region. Finite-source inversions based on the subpixel offset measurements show up to 4.1 and 6.5 m coseismic slip on the Mubi and Mananda faults, respectively. Despite higher data uncertainty (∼0.4–0.8  m) of the subpixel offset data, synthetic resolution tests show resolvable slip above 8 km in depth. The lack of shallower slip on the west side of the Mananda fault could be due to an inflated geothermal gradient near the dormant volcano, Mount Sisa, as a slip barrier. The result of the coulomb stress change suggests possible southeastward slip propagation from the Mananda fault to the Mubi fault. Our work successfully resolves 3D coseismic displacement in highly vegetated terrains and demonstrates the feasibility of using the subpixel offset on SAR images to help our understanding of regional active tectonic systems.