Comparison of Near-Fault Displacement Interpretations from Field and Aerial Data for the M 6.5 and 7.1 Ridgecrest Earthquake Sequence Ruptures

2021 ◽  
Vol 111 (5) ◽  
pp. 2317-2333 ◽  
Author(s):  
Christine A. Goulet ◽  
Yongfei Wang ◽  
Chukwuebuka C. Nweke ◽  
Bo-xiang Tang ◽  
Pengfei Wang ◽  
...  
Keyword(s):  
Data Collection ◽  
Field Measurements ◽  
Earthquake Sequence ◽  
Potential Hazard ◽  
Fault Surface ◽  
Ground Deformations ◽  
Fault Displacement ◽  
Aerial Systems ◽  
Remote Sensing Methods ◽  
Distributed Infrastructure

ABSTRACT Coseismic surface fault displacement presents a serious potential hazard for structures and for lifeline infrastructure. Distributed lifeline infrastructure tends to cover large distances and may cross faults in multiple locations, especially in active tectonic regions like California. However, fault displacement measurements for engineering applications are quite sparse, rendering the development of predictive models extremely difficult and fraught with large uncertainties. Detailed fault surface rupture mapping products exist for a few documented cases, but they may not capture the full width of ground deformations that are likely to impact distributed infrastructure. The 2019 Ridgecrest earthquake sequence presented an ideal opportunity to collect data and evaluate the ability of different techniques to capture coseismic deformations on and near the fault ruptures. Both the M 6.5 and 7.1 events ruptured the surface in sparsely populated desert areas where little vegetation is present to obscure surficial features. Two study areas (~400 m × 500 m each) around the surface ruptures from the two events were selected. Teams of researchers were deployed and coordinated to gather data in three ways: field measurements and photographs, imagery from small uninhabited aerial systems, and imagery from airborne light detection and ranging. Each of these techniques requires different amounts of resources in terms of cost, labor, and time associated with the data collection, processing, and interpretation efforts. This article presents the data collection methods used for the two study areas, and qualitative and quantitative comparisons of the results interpretations. While all three techniques capture the key features that are important for displacement design of distributed infrastructure, the use of remote sensing methods in combination with field measurements presents an advantage over the use of any single technique.

scholarly journals Displacement on the San Andreas fault subsequent to the 1966 Parkfield earthquake

1968 ◽  
Vol 58 (6) ◽  
pp. 1955-1973
Author(s):  
Stewart W. Smith ◽  
Max Wyss
Keyword(s):  
Shear Stress ◽  
Ground Motion ◽  
San Andreas Fault ◽  
High Rate ◽  
Aftershock Activity ◽  
Fault Surface ◽  
San Andreas ◽  
Parkfield Earthquake ◽  
Fault Displacement ◽  
Displacement Measurements

ABSTRACT Immediately following the 1966 Parkfield earthquake a continuing program of fault displacement measurements was undertaken, and several types of instruments were installed in the fault zone to monitor ground motion. In the year subsequent to the earthquake a maximum of at least 20 cm of displacement occurred on a 30 km section of the San Andreas fault, which far exceeded the surficial displacement at the time of the earthquake. The rate of displacement decreased logarithmically during this period in a manner similar to that of the decrease in aftershock activity. After the initial high rate of activity it could be seen that most of the displacement was occurring in 4–6 day epochs of rapid creep following local aftershocks. The variation of fault displacement along the surface trace was measured and shown to be consistent with a vertidal fault surface 44 km long and 14 km deep, along which a shear stress of 2.4 bars was relieved.

scholarly journals Liquefaction and Related Ground Failure from July 2019 Ridgecrest Earthquake Sequence

2020 ◽  
Vol 110 (4) ◽  
pp. 1549-1566 ◽  
Author(s):  
Paolo Zimmaro ◽  
Chukwuebuka C. Nweke ◽  
Janis L. Hernandez ◽  
Kenneth S. Hudson ◽  
Martin B. Hudson ◽  
...  
Keyword(s):  
Lateral Spreading ◽  
Earthquake Sequence ◽  
Ground Failure ◽  
Liquefaction Susceptibility ◽  
Ground Deformations ◽  
Us Military ◽  
Liquefaction Hazard ◽  
Frame Buildings ◽  
Sand Boils ◽  
Wood Frame

ABSTRACT The 2019 Ridgecrest earthquake sequence produced a 4 July M 6.5 foreshock and a 5 July M 7.1 mainshock, along with 23 events with magnitudes greater than 4.5 in the 24 hr period following the mainshock. The epicenters of the two principal events were located in the Indian Wells Valley, northwest of Searles Valley near the towns of Ridgecrest, Trona, and Argus. We describe observed liquefaction manifestations including sand boils, fissures, and lateral spreading features, as well as proximate non-ground failure zones that resulted from the sequence. Expanding upon results initially presented in a report of the Geotechnical Extreme Events Reconnaissance Association, we synthesize results of field mapping, aerial imagery, and inferences of ground deformations from Synthetic Aperture Radar-based damage proxy maps (DPMs). We document incidents of liquefaction, settlement, and lateral spreading in the Naval Air Weapons Station China Lake US military base and compare locations of these observations to pre- and postevent mapping of liquefaction hazards. We describe liquefaction and ground-failure features in Trona and Argus, which produced lateral deformations and impacts on several single-story masonry and wood frame buildings. Detailed maps showing zones with and without ground failure are provided for these towns, along with mapped ground deformations along transects. Finally, we describe incidents of massive liquefaction with related ground failures and proximate areas of similar geologic origin without ground failure in the Searles Lakebed. Observations in this region are consistent with surface change predicted by the DPM. In the same region, geospatial liquefaction hazard maps are effective at identifying broad percentages of land with liquefaction-related damage. We anticipate that data presented in this article will be useful for future liquefaction susceptibility, triggering, and consequence studies being undertaken as part of the Next Generation Liquefaction project.

scholarly journals Measuring Transverse Displacements Using Unmanned Aerial Systems Laser Doppler Vibrometer (UAS-LDV): Development and Field Validation

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6051
Author(s):  
Piyush Garg ◽  
Roya Nasimi ◽  
Ali Ozdagli ◽  
Su Zhang ◽  
David Dennis Lee Mascarenas ◽  
...  
Keyword(s):  
Laser Doppler Vibrometer ◽  
Field Tests ◽  
Field Measurements ◽  
Cost Effective ◽  
Laser Doppler ◽  
Unmanned Aerial Systems ◽  
Dynamic Displacement ◽  
Railway Bridges ◽  
Industrial Adoption ◽  
Aerial Systems

Measurement of bridge displacements is important for ensuring the safe operation of railway bridges. Traditionally, contact sensors such as Linear Variable Displacement Transducers (LVDT) and accelerometers have been used to measure the displacement of the railway bridges. However, these sensors need significant effort in installation and maintenance. Therefore, railroad management agencies are interested in new means to measure bridge displacements. This research focuses on mounting Laser Doppler Vibrometer (LDV) on an Unmanned Aerial System (UAS) to enable contact-free transverse dynamic displacement of railroad bridges. Researchers conducted three field tests by flying the Unmanned Aerial Systems Laser Doppler Vibrometer (UAS-LDV) 1.5 m away from the ground and measured the displacement of a moving target at various distances. The accuracy of the UAS-LDV measurements was compared to the Linear Variable Differential Transducer (LVDT) measurements. The results of the three field tests showed that the proposed system could measure non-contact, reference-free dynamic displacement with an average peak and root mean square (RMS) error for the three experiments of 10% and 8% compared to LVDT, respectively. Such errors are acceptable for field measurements in railroads, as the interest prior to bridge monitoring implementation of a new approach is to demonstrate similar success for different flights, as reported in the three results. This study also identified barriers for industrial adoption of this technology and proposed operational development practices for both technical and cost-effective implementation.

Fault network uncertainty assessment with a generative graph-based algorithm – Current status and perspectives

2020 ◽  
Author(s):  
Guillaume Caumon ◽  
Gabriel Godefroy ◽  
Paul Marchal
Keyword(s):  
Spatial Data ◽  
Structural Model ◽  
Field Measurements ◽  
Simulation Method ◽  
Search Space ◽  
Orientation Distribution ◽  
Current Status ◽  
Large Set ◽  
Fault Surface ◽  
Fault Network

<p>Graphs are a commonly used and well-studied mathematical abstraction for the modeling of complex systems. Three-dimensional (3D) structural geology is no exception, and graphs have received significant attention in recent years to characterize the connectivity for fracture sets, faults, geological units and reservoir compartments. The basis for these analyzes is to summarize an existing structural model as a graph, and to label the nodes and edges using the geological features of interest. In this sense, structural geologists building a 3D structural model are actually creating a graph. For this, they use geological reasoning to relate the various rock units of the subsurface.  </p><p>As a matter of fact, the final graph corresponding to a 3D structural model also relates the input spatial data, such as field measurements or interpretive contact lines. Based on this observation, we have proposed a graph-based framework to stochastically model 3D fault networks from incomplete observations, which randomizes the assignment of fault evidence to fault objects. The geometry of these faults is then determined using existing geomodeling techniques. In this approach, each piece of data is considered as a node of a complete graph called a possibility graph. The edges of the possibility graph are valued by a likelihood that two graph nodes belong to the same fault surface, which makes it possible to quickly remove some edges corresponding the associations deemed impossible. A hierarchical simulation algorithm is then proposed, based on the observation that each fault network corresponds to a possible partitioning of the input graph into distinct cliques. This formulation allows to give upper bounds for the (very large) number of possibilities that can be generated. We give several examples of likelihoods that integrate prior geological knowledge (e.g., the fault size distribution and orientation distribution), and check the consistency of the sampling algorithm when more informative rules are used. These preliminary results show that the simulation method consistently explores the search space, but they also highlight the need to further study the mathematical and computational properties of the sampler. Nonetheless, this approach is promising to efficiently generate and cluster a large set of possible structural scenarios and the associated ensemble of structural models obtained by a combination of data-perturbation, interpolation and or model-perturbation.</p><p> </p><p> </p>

scholarly journals ON THE USE OF CITSCI AND VGI IN NATURAL HAZARD ASSESSMENT

2018 ◽  
Vol XLII-5 ◽  
pp. 69-73 ◽  
Author(s):  
S. Kocaman ◽  
C. Gokceoglu
Keyword(s):  
Data Collection ◽  
Natural Hazards ◽  
Natural Hazard ◽  
Communication Technologies ◽  
Mobile App ◽  
Geographical Information ◽  
Research Areas ◽  
Research Fields ◽  
Ground Deformations ◽  
Data Density

<p><strong>Abstract.</strong> The developments in the geospatially-enabled mobile communication technologies have opened new horizons in many fields of geosciences research, especially in those where data collection, processing and interpretation are time consuming and costly. Being one of these research fields, natural hazards also require high spatiotemporal data density and distribution, which is extremely difficult to obtain and also equally essential to secure the main assumptions of these researches and thus yield to proper conclusions. These problems can be solved with the help of citizen science (CitSci) methods and the volunteer geographical information (VGI). These two terms are complementary, or intertwined, and mutually benefit from each other for achieving their goals. This paper investigates the developments in CitSci and VGI with a specific focus of natural hazard researches and gives a brief overview of the literature. The importance of their use in natural hazards, open research areas and future aspects are also analysed. Based on the previous experiences and analyses, the authors foresee that such investigations would help researchers to utilize CitSci and VGI in their studies, and thus benefit the advantages of both approaches and improve the quality of their data. On the other hand, the growing interest of citizen scientists for supporting scientific processes could be steered to the fields where most help is needed. Specifically, detection of ground deformations after earthquakes is explained here and a simple mobile app developed for landslide data collection is briefly depicted as use case.</p>

Development of a Mobile Platform for Wheat Phenotyping

2020 ◽  
Author(s):  
Majid Khak Pour ◽  
Reza Fotouhi ◽  
Pierre Hucl
Keyword(s):  
Data Collection ◽  
High Throughput ◽  
Vegetation Indices ◽  
Field Measurements ◽  
Mobile Platform ◽  
Mechatronic System ◽  
High Quality ◽  
Wheat Field ◽  
Crop Monitoring ◽  
High Throughput Phenotyping

Abstract Designing and implementing an affordable High-Throughput Phenotyping Platform (HTPP) for monitoring crops’ features in different stages of their growth can provide valuable information for crop-breeders to study possible correlation between genotypes and phenotypes. Conducting automatic field measurements can improve crop productions. In this research, we have focused on development of a mechatronic system, hardware and software, for a mobile field-based HTPP for autonomous crop monitoring for wheat field. The system can measure canopy’s height, temperature, vegetation indices and is able to take high quality photos of crops. The system includes developed software for data and image acquisition. The main contribution of this study is autonomous, reliable, and fast data collection for wheat and similar crops.

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