High-resolution Topographic Data Research Articles

Mapping landforms of a hilly landscape using machine learning and high-resolution LiDAR topographic data

Landform maps are important tools in assessment of soil- and eco-hydrogeomorphic processes and hazards, hydrological modeling, and natural resources and land management. Traditional techniques of mapping landforms based on field surveys or from aerial photographs can be time and labor intensive, highlighting the importance of remote sensing products based automatic or semi-automatic approaches. In addition, the time-intensive manual labeling can also be subjective rather than an objective identification of the landform. Here we implemented such an objective approach applying a random forest machine learning algorithm to a set of observed landform data and 1m horizontal resolution bare-earth digital elevation model (DEM) developed from airborne light detection and ranging (LiDAR) data to rapidly map various landforms of a hilly landscape. The landform classification includes upland plateaus, ridges, convex slopes, planar slopes, concave slopes, stream channels, and valley bottoms, across a 400 km2 hilly landscape of the Ozark Mountains in northeastern Oklahoma. We used 4200 landform observations (600 per landform) and eight topographic indices derived from 2 m, 5 m and 10 m resolution LiDAR DEM in random forest algorithm to develop 2 m, 5 m and 10 m resolution landform models. We test the effectiveness of DEM resolution in mapping landforms via comparison of observed landforms with modeled landforms. Results showed that the approach mapped ∼84% of observed landforms when covariates were at 2 m resolution to ∼89% when they were at 10 m resolution. However, predicted maps showed that the 2 m resolution covariates performed better at capturing accurate landform boundaries and details of small-sized landforms such as stream channels and ridges. The approach presented here significantly reduces the time required for mapping landforms compared to traditional techniques using aerial imagery and field observations and allows incorporation of a wide variety of covariates. The landform map developed using this approach has several potential applications. It could be utilized in hydrological modeling, natural resource management, and characterizing soil-geomorphic processes and hazards in a hilly landscape.

Active Fault Interpretation in the Northern Segment of the Red River Fault Based on Multisource Remote Sensing Data

High-resolution topographic and geomorphic data are important basic data for the study of active structures. Here, multisource remote sensing data were used to reinterpret the active faults in the northern segment of the Red River Fault (China). First, we obtained airborne light detection and ranging (LiDAR) data, high-resolution GaoFen-7 (GF-7) remote sensing image data, and historical aerial photographs, and a high-resolution digital elevation model (DEM) was generated based on the airborne LiDAR data and GF-7 data. According to the remote sensing interpretation, the main active faults were identified. We subsequently verified the faults in the field and constrained the geographic locations. The current activity was confirmed to be dominantly normal faulting, with some dextral strike-slip components, and the latest active age was the Late Holocene. It reflects the coordination of structural deformation between the rotation of the secondary block and the sliding of the boundary fault within the Sichuan–Yunnan Block. The results show that airborne LiDAR and GF-7 remote sensing data have a great application value in providing high-resolution topographic and geomorphologic data for the study of active structures. The comprehensive application of multisource remote sensing data can greatly improve the reliability of active fault interpretations and provide a reference for follow-up research within the study area.

Landslide Hazard Prediction Based on UAV Remote Sensing and Discrete Element Model Simulation—Case from the Zhuangguoyu Landslide in Northern China

Rainfall-triggered landslides generally pose a high risk due to their sudden initiation, massive impact force, and energy. It is, therefore, necessary to perform accurate and timely hazard prediction for these landslides. Most studies have focused on the hazard assessment and verification of landslides that have occurred, which were essentially back-analyses rather than predictions. To overcome this drawback, a framework aimed at forecasting landslide hazards by combining UAV remote sensing and numerical simulation was proposed in this study. A slow-moving landslide identified by SBAS-InSAR in Tianjin city of northern China was taken as a case study to clarify its application. A UAV with laser scanning techniques was utilized to obtain high-resolution topography data. Then, extreme rainfall with a given return period was determined based on the Gumbel distribution. The Particle Flow Code (PFC), a discrete element model, was also applied to simulate the runout process after slope failure under rainfall and earthquake scenarios. The results showed that the extreme rainfall for three continuous days in the study area was 151.5 mm (P = 5%), 184.6 mm (P = 2%), and 209.3 mm (P = 1%), respectively. Both extreme rainfall and earthquake scenarios could induce slope failure, and the failure probabilities revealed by a seepage–mechanic interaction simulation in Geostudio reached 82.9% (earthquake scenario) and 92.5% (extreme rainfall). The landslide hazard under a given scenario was assessed by kinetic indicators during the PFC simulation. The landslide runout analysis indicated that the landslide had a velocity of max 23.4 m/s under rainfall scenarios, whereas this reached 19.8 m/s under earthquake scenarios. In addition, a comparison regarding particle displacement also showed that the landslide hazard under rainfall scenarios was worse than that under earthquake scenarios. The modeling strategy incorporated spatial and temporal probabilities and runout hazard analyses, even though landslide hazard mapping was not actually achieved. The present framework can predict the areas threatened by landslides under specific scenarios, and holds substantial scientific reference value for effective landslide prevention and control strategies.

Improving horizon computation algorithm with quasirandom sequences

The topographic horizon can be used to estimate shading for applications requiring an accurate solar resource estimate, including the effects of the local terrain. With high-resolution topography data, horizon estimation significantly contributes to the computation time needed for irradiance simulations. Approximate horizon algorithms have been proposed previously, sampling topography in a finite number of directions. This paper extends this idea by presenting a sampling approach based on the quasirandom sequences. The sampling strategy is optimized with 300,000 km2 of topography data from Europe and the USA. We demonstrate that our algorithm is several orders of magnitude faster than the precise horizon calculation and significantly improves the previous approximate algorithms. In particular, at the ground level with a topography resolution of 1 m/pixel, the proposed method achieved the same accuracy as the old approximate method four times faster. The horizon is one of the key methods in geographical information science and a part of many modeling tools in the built environment. Improvements in computation time benefit all applications that require irradiance modeling, e.g., the yield of vehicle- and building-integrated photovoltaic or temperature modeling of buildings.

Mildly explosive eruptions at Martian low-shield volcanoes

AbstractOngoing acquisition of Martian surface imagery constantly provides new opportunities to reveal previously undiscovered small-scale volcanic landforms, yielding critical insights into volcanic processes, and challenging existing inferences. Here, using the most recent, high-resolution topographical data, we mapped the accumulation of pyroclastic deposits occurring along the margins of several volcanic vents. They share morphological similarities with terrestrial volcanic deposits attributed to low-intensity lava fountaining occurring during mild explosive activity. Our identified, explosive volcanic deposits are associated with late Amazonian volcanic activity in Tharsis. The identification of these very recent (<100 Ma) deposits across the entire Tharsis volcanic province needs reconciling with our current view of the evolution of explosive volcanism on Mars. We contend that these small volume landforms, produced by mildly explosive volcanic activity, need to be considered in models surrounding planet-scale magmatic evolution and atmospheric volatile budgets.

Transfer learning reconstructs submarine topography for global mid-ocean ridges

Mid-ocean ridges are unique, tectonically active geographical units on Earth that profoundly control the ocean environment and dynamics at the global scale. However, high-resolution topographic data from mid-ocean ridges are rarely available due to the difficulty in detecting ocean floors, which further limits ocean research at the global scale. Here, we divide the global mid-ocean ridge system into 2805 tiles and reconstruct their high-resolution topography by using a transfer learning approach with freely available low-resolution digital elevation models (DEMs) and limited high-resolution DEMs. A high-frequency terrain feature-based deep residual network is proposed to generate high-resolution global mid-ocean ridge DEMs. In this network, topographic knowledge related to mid-ocean ridges is integrated and quantified to improve the learning efficiency and reconstruction quality of the network. A series of verifications and evaluations demonstrate the reliability of reconstructed topographies for submarine topography research. We observe that reconstructed topography can achieve good environmental understanding and information acquisition in the global mid-ocean ridge range. We find that the complexity of the previous terrain environment is underestimated by 26.63% in terms of the slope gradient and by 14.95% in terms of terrain relief, while a 101.10% information improvement can be obtained for the reconstructed topography. The reconstructed topography indicates that diverse and intricate topographical environments of mid-ocean ridges exist among different ocean regions. The proposed transfer learning method for reconstructing high-resolution mid-ocean ridge topographies is valuable and can be utilized for reconstructing information in regions that are difficult to observe directly and lack sufficient data.

Evolution of rift faulting in incipient, magma-poor divergent plate boundaries: New insights from the Okavango-Makgadikgadi Rift Zone, Botswana

Continental rifts are thought to transition from a power-law fault length distribution during the juvenile stages of extension, to an exponential distribution during break-up and oceanic spreading. However, fault scaling relationships have rarely been quantified in natural incipient rifts, particularly in the absence of magmatic influence. We address this knowledge-gap in the incipient Okavango-Makgadikgadi Rift Zone, Northern Botswana, consisting of the amagmatic Okavango Rift Basin (ORB) and Makgadikgadi Rift Basin (MRB). We utilize high-resolution satellite topography data (12.5 m TanDEM-X and 30 m SRTM) and aeromagnetic data to image and map faults across the rift zones and generate a new robust fault map for the region. Further, we analyze the length-frequency distribution of faults using a two-sample Kolmogorov-Smirnov test. The results show that the Makgadikgadi Rift Basin exhibits an exponential distribution associated with a nucleating rift as it exhibits diffuse faulting and lacks a border-fault, whereas the Okavango Rift Basin exhibits a power-law distribution that is consistent with its relatively more evolved rift structure with established border faults. Thus, we propose that continental divergent plate boundaries commonly nucleate with an initial exponential distribution of fault lengths which subsequently transition into a power-law distribution as the rift evolves into its stretching phase, and may again transition into an exponential distribution as break-up initializes.

The Use of Unmanned Aerial Systems for River Monitoring: A Bibliometric Analysis Covering the Last 25 Years

Cutting-edge technology for fluvial monitoring has revolutionised the field, enabling more comprehensive data collection, analysis, and interpretation. Traditional monitoring methods were limited in their spatial and temporal resolutions, but advancements in remote sensing, unmanned aerial systems (UASs), and other innovative technologies have significantly enhanced the fluvial monitoring capabilities. UASs equipped with advanced sensors enable detailed and precise fluvial monitoring by capturing high-resolution topographic data, generate accurate digital elevation models, and provide imagery of river channels, banks, and riparian zones. These data enable the identification of erosion and deposition patterns, the quantification of sediment transport, the evaluation of habitat quality, and the monitoring of river flows. The latter allows us to understand the dynamics of rivers during various hydrological events, including floods, droughts, and seasonal variations. This manuscript aims to provide an update on the main research themes and topics in the literature on the use of UASs for river monitoring. The latter is achieved through a bibliometric analysis of the publication trends and identifies the field’s key themes and collaborative networks. The bibliometric analysis shows trends in the number of publications, number of citations, top contributing countries, top publishing journals, top contributing institutions, and top authors. A total of 1085 publications on UAS monitoring in rivers are identified, published between 1999 and 2023, showing a steady annual growth rate of 24.44%. Bibliographic records are exported from the Web of Science (WoS) database using a comprehensive set of keywords. The bibliometric analysis of the raw data obtained from the WoS database is performed using the R software. The results highlight important trends and valuable insights related to the use of UASs in river monitoring, particularly in the last decade. The most frequently used author keywords outline the core themes of UASs monitoring research and highlight the interdisciplinary nature and collaborative efforts within the field. “River”, “topography”, “photogrammetry”, and “Structure-from-Motion” are the core themes of UASs monitoring research. These findings can guide future research and promote new interdisciplinary collaborations.

An aerodynamic digital twin of real-world leading edge erosion: Acquisition, Generation and 3D CFD

Wind turbine blades face extremely challenging environmental conditions over their operating life-time, that can easily exceed 2 decades. Airborne particles (insects, sand, rain, hail, ice, sea spray etc.) strike the blade leading edge (LE) first and erode or attach to it, roughening its surface. Leading edge roughness (LER) can critically alter the aerodynamic performance of blades, as its aerodynamic impact is strongly coupled to its height with respect to the local boundary layer thickness, which is thinnest around the LE. The actual, detailed topographic manifestation of LER on in-service blades—needed to accurately assess its aerodynamic impact—is highly probabilistic, as it depends on the interaction of multiple stochastic parameters, like the environmental conditions, material composition and production process. Yet little high-resolution topographic LER data of this kind is currently available. This paper details how such data is collected from blades of different turbine manufacturers and processed consistently to build digital twins of the measured LER, that can be analysed aerodynamically using 3D CFD or wind tunnels. Here a special focus lies on how to reconstruct the LER topography and build the computational mesh such that the correct aerodynamic response is observed. For this purpose multiresolution signal decomposition is used to process the topographies and a special meshing procedure established.

Improving the Accuracy of Digital Terrain Models Using Drone-Based LiDAR for the Morpho-Structural Analysis of Active Calderas: The Case of Ischia Island, Italy

Over the past two decades, the airborne Light Detection and Ranging (LiDAR) system has become a useful tool for acquiring high-resolution topographic data, especially in active tectonics studies. Analyzing Digital Terrain Models (DTMs) from LiDAR exposes morpho-structural elements, aiding in the understanding of fault zones, among other applications. Despite its effectiveness, challenges persist in regions with rapid deformation, dense vegetation, and human impact. We propose an adapted workflow transitioning from the conventional airborne LiDAR system to the usage of drone-based LiDAR technology for higher-resolution data acquisition. Additionally, drones offer a more cost-effective solution, both in an initial investment and ongoing operational expenses. Our goal is to demonstrate how drone-based LiDAR enhances the identification of active deformation features, particularly for earthquake-induced surface faulting. To evaluate the potential of our technique, we conducted a drone-based LiDAR survey in the Casamicciola Terme area, north of Ischia Island, Italy, known for the occurrence of destructive shallow earthquakes, including the 2017 Md = 4 event. We assessed the quality of our acquired DTM by comparing it with existing elevation datasets for the same area. We discuss the advantages and limitations of each DTM product in relation to our results, particularly when applied to fault mapping. By analyzing derivative DTM products, we identified the fault scarps within the Casamicciola Holocene Graben (CHG) and mapped its structural geometry in detail. The analysis of both linear and areal geomorphic features allowed us to identify the primary factors influencing the current morphological arrangement of the CHG area. Our detailed map depicts a nested graben formed by two main structures (the Maio and Sentinella faults) and minor internal faults (the Purgatorio and Nizzola faults). High-resolution DEMs acquired by drone-based LiDAR facilitated detailed studies of the geomorphology and fault activity. A similar approach can be applied in regions where the evidence of high slip-rate faults is difficult to identify due to vegetation cover and inaccessibility.

Strong-wind events control barchan dune migration

Wind is the most important external force in shaping aeolian landforms. Yet, it remains unclear what role the strong-wind events will play in the development of aeolian landforms compared with the effect of regular winds. A fundamental question is, what are the contributions of different wind speed levels to the deformation of aeolian landforms. Here, through in situ measurements of high-sampling-rate wind data and high-resolution topographic data, we analyzed short-term strong-wind events at different levels and monitored the rapid migration of barchan dunes, enabling us to provide a first report on the contribution rate of short-term strong winds to dune migration. Leveraging the linear relationship between sand flux and the migration distance of barchans, we found that the ratio of sand flux generated by short-term strong winds to the total sand flux is equal to the ratio of barchan migration distance caused by strong winds to the total migration distance in the same period. Moreover, a global analysis of three typical barchan fields confirmed the relationship. This study suggests that the development of aeolian landforms is dominantly controlled by the short-term strong-wind events rather than the previously reported time-averaging wind.

New source model for the 1771 Meiwa tsunami along the southern Ryukyu Trench inferred from high-resolution tsunami calculation

The 1771 Meiwa tsunami which struck the southern Ryukyu Islands (Sakishima Islands) had greater than 22 m run-up height, leaving about 12,000 casualties in its wake. At many places, the tsunami inundation or lack of inundation is well recorded in historical documents. Several tsunami source models have been proposed for this event using historical records as constraints of tsunami calculations. Nevertheless, the source model remains under discussion. This study re-evaluated the tsunami wave source model of the 1771 Meiwa tsunami using high-resolution (10 m mesh) bathymetric and topographical data for tsunami calculation, the latest historical record dataset, and seismological knowledge. Results demonstrated that a tsunami earthquake along the southern Ryukyu Trench was the likely cause of the 1771 event. However, it is noteworthy that assumption of a large slip with 30 m is necessary for a shallow and narrow region (fault depth = 5 km, fault width = 30 km, Mw = 8.49) of the plate boundary in the Ryukyu Trench, which is far larger than previously thought. This requirement of very large initial water level change at the source might involve not only the fault rupture along the plate boundary but also deformation by splay faults, inelastic deformation of unconsolidated sediments near the trench axis, and/or giant submarine landslides. Results also show that the effects of fault parameters on the run-up were quite different depending on the offshore coral reef width. This phenomenon strongly constrained the fault width to 30 km. Our tsunami ray tracing analysis further revealed the effects of bathymetry on tsunami propagation. It is noteworthy that meter-long huge tsunami boulders tend to be distributed along the specific coasts at which the tsunami was concentrated by bathymetric effects. This finding suggests that past tsunamis, including the 1771 event, might have affected the specific coral reefs on Sakishima Islands repeatedly, which is crucially important for understanding the heterogeneous distribution of tsunami boulders. This feature might also be useful to elucidate the effects of large tsunamis on the corals and reefs because a direct comparison of coral reefs that are damaged and not damaged by tsunami waves is testable in narrow areas in the case of the Sakishima Islands.

Time-dependent probabilistic tsunami risk assessment: application to Tofino, British Columbia, Canada, subjected to Cascadia subduction earthquakes

A new time-dependent probabilistic tsunami risk model is developed to facilitate the long-term risk management strategies for coastal communities. The model incorporates the time-dependency of earthquake occurrence and considers numerous heterogeneous slip distributions via a stochastic source modeling approach. Tidal level effects are examined by considering different baseline sea levels. The model is applied to Tofino, British Columbia, Canada within the Cascadia subduction zone. High-resolution topography and high-quality exposure data are utilized to accurately evaluate tsunami damage and economic loss to buildings. The results are tsunami loss curves accounting for different elapsed times since the last major event. The evolutionary aspects of Tofino’s time-dependent tsunami risk profiles show that the current tsunami risk is lower than the tsunami risk based on the conventional time-independent Poisson occurrence model. In contrast, the future tsunami risk in 2100 will exceed the time-independent tsunami risk estimate.

Multi-scale simulation of typhoon wind field at building scale utilizing mesoscale model with nested large eddy simulation

Based on the mesoscale WRF (Weather Research Forecast) and LES (Large Eddy Simulation), an integrated numerical simulation framework aiming to resolve typhoon wind fields around urban building blocks has been developed. The holistic multi-scale simulation spans four scales: macroscale (∼1000 km), mesoscale (∼100 km), microscale (∼1 km), and building scale (0.1–100m). By interactively sharing the meteorological data among different scales, this simulation framework addressed the challenge of downscaling typhoon effects in urban environments. Typhoon weather reanalysis and urban wind field simulation were conducted by the WRF model with nested computational domains incorporating high-resolution topography data. For the downscaled LES model with urban buildings, the wind profiles produced by the WRF model were used at the interface with provided turbulent fluctuations in the flow. K11 building is a 270-m-tall building located in a densely built-up area of Hong Kong. Wind velocity and pressure fields surrounding the K11 building in Hong Kong during Typhoon Kammuri were obtained by the proposed framework, and the simulation results were validated by comparing with the meteorological data and full-scale measurements at the top of the K11 building. The interactions of the wind fields and building clusters resulting in vortex shedding, separation, and channeling effects have been resolved at high resolutions. Probabilistic distributions and higher-order statistics of wind pressure, i.e., skewness and kurtosis, were presented to highlight non-Gaussian characteristics of the simulated local wind pressure on the K11 building. Based on the simulated wind pressure, wind-induced vibration of the K11 building during the typhoon was analyzed and compared to the measurements.

Investigation of the use of topographic data derived from Pléiades imagery for high-resolution hillslope-scale morphometry

Obtaining accurate representations of the Earth surface topography is paramount in many geomorphological investigations. While regional scale studies use Digital Elevation Models (DEM) with resolution of the order of 10–100 m, in many applications resolution <5 m are mandatory to appropriately represent landforms and processes of interest. In particular, hillslopes, which cover the most of continental surfaces, have typical length of the order of 100 m. For that reason, high resolution topographic data are mandatory to correctly represent their morphology. The massive use of higher resolution topographic data has been enabled by a vast array of methodological developments, among which terrestrial and airborne Light Detection And Ranging (LiDAR) or uncrewed aerial vehicle-based photogrammetric approaches are the most commonly used. However, such techniques might be difficult to deploy and not cost-effective, to cover large areas in remote locations.In this study, we present an exploration of the potential of topographic data derived from Pléiades imagery for the characterizing hillslope morphology. We focus on the Gabilan Mesa area in California, where a LiDAR DEM is available and is used as a benchmark. We systematically compare Pléiades-derived topographic data with the DEM constructed from LiDAR data, starting from simple elevation analysis and then using topographic derivatives, such as slope or curvature, which are commonly used in morphometric studies. Finally, we take advantage of the high resolution of the datasets to extract and compare hillslope-scale morphometric parameters, such as length, relief, or hilltop curvature. While some particular situations, such as planar and horizontal surfaces, requires specific attention in terms of the relative differences between the two type of data, the absolute values for the metrics are in good agreement over their relevant range of utilization for hillslope-scale geomorphology.

Mesoscale structure of the atmospheric boundary layer across a natural roughness transition

The structure and intensity of turbulence in the atmospheric boundary layer (ABL) drive fluxes of sediment, contaminants, heat, moisture, and CO[Formula: see text] at the Earth's surface. Where ABL flows encounter changes in roughness-such as cities, wind farms, forest canopies, and landforms-a new mesoscopic flow scale is introduced: the internal boundary layer (IBL), which represents a near-bed region of transient flow adjustment that develops over kilometers. Measurement of this new mesoscopic scale lies outside present observational capabilities of ABL flows, and simplified models fail to capture the sensitive dependence of turbulence on roughness geometry. Here, we use large-eddy simulations, run over high-resolution topographic data and validated against field observations, to examine the structure of the ABL across a natural roughness transition: the emergent sand dunes at White Sands National Park. We observe that development of the IBL is triggered by the abrupt transition from smooth playa surface to dunes; however, continuous changes in the size and spacing of dunes over several kilometers influence the downwind patterns of boundary stress and near-bed turbulence. Coherent flow structures grow and merge over the entire [Formula: see text]10 km distance of the dune field and modulate the influence of large-scale atmospheric turbulence on the bed. Simulated boundary stresses in the developing IBL counter existing expectations and explain the observed downwind decrease in dune migration, demonstrating a mesoscale coupling between flow and form that governs landscape dynamics. More broadly, our findings demonstrate the importance of resolving both turbulence and realistic roughness for understanding fluid-boundary interactions in environmental flows.

Quantifying the migration rate of drainage divides from high-resolution topographic data

Abstract. The lateral movement of drainage divides is co-influenced by tectonics, lithology, and climate and therefore archives a wealth of geologic and climatic information. It also has wide-ranging implications for topography, the sedimentary record, and biological evolution and thus has drawn much attention in recent years. Several methods have been proposed to determine drainage divides' migration state (direction and rate), including geochronological approaches (e.g., 10Be) and topography-based approaches (e.g., χ plots or Gilbert metrics). A key object in these methods is the channel head, which separates the hillslope and channel. However, due to the limited resolution of topography data, the required channel-head parameters in the calculation often cannot be determined accurately, and empirical values are used in the calculation, which may induce uncertainties. Here, we propose two methods to calculate the migration rate of drainage divides based on the relatively accurate channel-head parameters derived from high-resolution topographic data. We then apply the methods to an active rift shoulder (Wutai Shan) in the Shanxi Rift and a tectonically stable area (Yingwang Shan) in the Loess Plateau, to illustrate how to calculate drainage-divide migration rates. Our results show that the Wutai Shan drainage divide is migrating northwestward at a rate between 0.21 and 0.27 mm yr−1, whereas the migration rates at the Yingwang Shan are approximately zero. This study indicates that the drainage-divide stability can be determined more accurately using high-resolution topographic data. Furthermore, this study takes the cross-divide differences in the uplift rate of channel heads into account in the measurement of drainage-divide migration rate for the first time.

The discovery of an active fault in the Qiongdongnan Basin of the northern South China Sea

Fault activities in sea areas always produce devastative marine geohazards. For marine geohazard assessment, it is important to know the location, geometric structure, and activity regularity of active faults. In this study, high-resolution multi-channel seismic and topographic data are used to investigate the exact location, geometric structure and latest activity of the Continental Slope Fault Zone (CSFZ) in the northern South China Sea. The results show that the Qiongdongnan (QDN) segment of the CSFZ is a 194 km long NEE-trending fault zone that developed near the transition of continental shelf and slope. In its geometric structure, the CSFZ (QDN segment) cuts through the Cenozoic basement and breaks upward to near the seafloor with high-angle dip. According to whether it ruptures to the seafloor, it can be divided into eastern and western segments. In the western segment, the fault scarps about 8∼9 m high can clearly be seen on the seafloor. Whereas in the eastern segment, the fault shows a blind characteristic below the seafloor. The analysis of fault throws and expansion indices show that CSFZ (QDN segment) have remained active since the late Pleistocene. Due to the CSFZ is an active fault and geographically adjacent steep slope, which may cause large interpolate landslides, and then leading to destructive tsunamis. As a result, the CSFZ has great seismogenic potential and may produce marine geohazard chain. Thus, it is of great significance to the assessment of marine geohazard chain posed by the CSFZ for improving hazard mitigation.

Simulation of the Hydraulic Model HEC-RAS Coupled with GIS and Remote Sensing to Study the Effect of River Cross-section Width in Detecting Flood-prone Areas

Abstract Flooding is one of the extreme hydrological phenomena. It is a recurring natural disaster that causes loss of life and property in many parts of the world, particularly during the monsoon season. It is important to address such issues for local government and policymakers to manage the flood properly. One such flood management activity is to develop a flood-prone area that depicts the spatial and temporal extent of flood accurately. The integration of the Hydrologic Engineering Centre - River Analysis System (HEC-RAS) model and geospatial tools have emerged as a crucial approach for identifying and mapping flood-prone areas. The successful application of the HEC-RAS model generally depends on the topographical data, which represents the channel and floodplain geometry. In floodplain geometry, discrete cross-sections play a vital role to develop the floodplain map, particularly in the flat topographical region. To extract these data it needs a high-quality digital elevation model (DEM), such as light detection and ranging (LiDAR). However, due to a lack of high-resolution topographical data, flood hazard mapping in developing countries is rare. In common practice, the centerline of the river is considered the flow path for the channel. The orientation of the cross-sections is perpendicular to this line and extends to reach the limits of the floodplain. But, it is difficult to define the limits and it may depend on the magnitude of the flood. Hence, in this study, the HEC RAS model coupled with ArcGIS has been applied to the Ganga River, which traverses through the Bihar state of India to study the effect of cross-sectional width to define the floodplain. The Bihar state is facing substantial hardships from annual flooding events with approximately 16.5% of India’s flood-prone area. The extreme flood values for 5, 10, and 25 years of return period have been determined and the influence of the three different cross-sectional widths to mapping the floodplain has been investigated. This novel perspective adds dimension to the understanding of flood dynamics and its implications for flood risk assessment. In this analysis, it has been observed that, with an increase in the width of the cross-section, the floodplain area also getting increased. In this topographical region, keeping a fixed flow path will underestimate the flood-prone area. The width of the flow path depends on the topography of the region and the river flow. The outcomes of this analysis provide valuable insights into the flood-inundated areas for the specified return periods, enabling the identification and prioritization of flood-prone zones.

Investigating paleoseismicity using high-resolution airborne LiDAR data - A case study of the Huangxianggou fault in the northeastern Tibetan plateau

Fault-offset landforms have long been recognized as holding important information about paleoseismic slip. Constructing an along-strike fault slip distribution could help reveal a fault's long-term rupture patterns and facilitate a more precise assessment of its future behavior. In this study, we documented the paleoseismic history of the Huangxianggou Fault, an oblique sinistral-thrust segment of the West Qingling Fault in the northeastern region of the Tibetan Plateau, using LiDAR-derived high-resolution DEM (0.1 m/pixel) and measurement of offset landforms. A total of 46 well-preserved and well-shaped landforms were chosen for horizontal and vertical displacement measurements, and the dense measurement data allow us to generate the cumulative offset probability distribution curves of horizontal and vertical displacements. Statistical analysis revealed at least seven surface-rupturing events, each with similar coseismic horizontal displacements of ∼7.0 m and vertical displacements of ∼0.7 m, in agreement with previous paleoseismic trench results. Using empirical relationships between moment magnitude and horizontal displacement, a plausible moment magnitude range of Mw7.3–7.7 was determined for these paleoearthquakes. Furthermore, by evaluating rupture parameters and fault slip rate, we determined a recurrence interval of 2.7–3.4 kyr for significant surface-rupturing events on this fault. The elapsed time since the last earthquake closely approaches this interval, suggesting a potential seismic risk for the Huangxianggou Fault. Our results emphasizes the importance of high-resolution topographic data in paleoseismic investigations, enabling the identification of numerous offset landforms and precise displacement measurements across faults. Paleoearthquake counts derived from horizontal and vertical displacement analyses were found to be consistent, highlighting the significance of vertical displacements in quantifying paleoearthquakes for strike-slip faults with a thrust component.