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1.
The availability of high‐resolution, multi‐temporal, remotely sensed topographic data is revolutionizing geomorphic analysis. Three‐dimensional topographic point measurements acquired from structure‐from‐motion (SfM) photogrammetry have been shown to be highly accurate and cost‐effective compared to laser‐based alternatives in some environments. Use of consumer‐grade digital cameras to generate terrain models and derivatives is becoming prevalent within the geomorphic community despite the details of these instruments being largely overlooked in current SfM literature. A practical discussion of camera system selection, configuration, and image acquisition is presented. The hypothesis that optimizing source imagery can increase digital terrain model (DTM) accuracy is tested by evaluating accuracies of four SfM datasets conducted over multiple years of a gravel bed river floodplain using independent ground check points with the purpose of comparing morphological sediment budgets computed from SfM‐ and LiDAR‐derived DTMs. Case study results are compared to existing SfM validation studies in an attempt to deconstruct the principle components of an SfM error budget. Greater information capacity of source imagery was found to increase pixel matching quality, which produced eight times greater point density and six times greater accuracy. When propagated through volumetric change analysis, individual DTM accuracy (6–37 cm) was sufficient to detect moderate geomorphic change (order 100 000 m3) on an unvegetated fluvial surface; change detection determined from repeat LiDAR and SfM surveys differed by about 10%. Simple camera selection criteria increased accuracy by 64%; configuration settings or image post‐processing techniques increased point density by 5–25% and decreased processing time by 10–30%. Regression analysis of 67 reviewed datasets revealed that the best explanatory variable to predict accuracy of SfM data is photographic scale. Despite the prevalent use of object distance ratios to describe scale, nominal ground sample distance is shown to be a superior metric, explaining 68% of the variability in mean absolute vertical error. Published 2016. This article is a U.S. Government work and is in the public domain in the USA  相似文献   

2.
In floodplains, anthropogenic features such as levees or road scarps, control and influence flows. An up‐to‐date and accurate digital data about these features are deeply needed for irrigation and flood mitigation purposes. Nowadays, LiDAR Digital Terrain Models (DTMs) covering large areas are available for public authorities, and there is a widespread interest in the application of such models for the automatic or semiautomatic recognition of features. The automatic recognition of levees and road scarps from these models can offer a quick and accurate method to improve topographic databases for large‐scale applications. In mountainous contexts, geomorphometric indicators derived from DTMs have been proven to be reliable for feasible applications, and the use of statistical operators as thresholds showed a high reliability to identify features. The goal of this research is to test if similar approaches can be feasible also in floodplains. Three different parameters are tested at different scales on LiDAR DTM. The boxplot is applied to identify an objective threshold for feature extraction, and a filtering procedure is proposed to improve the quality of the extractions. This analysis, in line with other works for different environments, underlined (1) how statistical parameters can offer an objective threshold to identify features with varying shapes, size and height; (2) that the effectiveness of topographic parameters to identify anthropogenic features is related to the dimension of the investigated areas. The analysis also showed that the shape of the investigated area has not much influence on the quality of the results. While the effectiveness of residual topography had already been proven, the proposed study underlined how the use of entropy can anyway provide good extractions, with an overall quality comparable to the one offered by residual topography, and with the only limitation that the extracted features are slightly wider than the investigated one. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

3.
Modeling of dam-break flooding in an urban residential area in southern California is presented. Modeling is performed using BreZo, an unstructured grid, Godunov-type, finite volume model that solves the shallow-water equations. The model uses terrain data from a 1.5 m Light Detection and Ranging (LiDAR) Digital Terrain Model (DTM) and contour data depicting the reservoir and breach geometry. A spatially distributed Manning coefficient based on a landcover classification derived from digital orthophotos and vector data (e.g., parcel outlines) is also used, and the interception of flow by storm drains is modeled with sink terms in the 2D continuity equation. The model is validated with flood extent and stream flow measurements, and a sensitivity analysis is completed to identify the necessary level of data and model complexity for accuracy purposes. Results show street depressions in the land surface should be resolved by the computational mesh for flood extent and stream flow accuracy. A ca. 5 m resolution mesh that spans streets by approximately 3 cells achieves a good balance between accuracy and computational effort. Results also show that heterogeneous resistance is important for stream flow accuracy, and the interception of overland flow by storm sewers is important for flood extent accuracy. The sensitivity of predictions to several additional factors such as the reservoir level, breach geometry and DTM source (LiDAR, National Elevation Data, Shuttle Radar Topography Mission Data) is also reported.  相似文献   

4.
The production of topographic datasets is of increasing interest and application throughout the geomorphic sciences, and river science is no exception. Consequently, a wide range of topographic measurement methods have evolved. Despite the range of available methods, the production of high resolution, high quality digital elevation models (DEMs) requires a significant investment in personnel time, hardware and/or software. However, image‐based methods such as digital photogrammetry have been decreasing in costs. Developed for the purpose of rapid, inexpensive and easy three‐dimensional surveys of buildings or small objects, the ‘structure from motion’ photogrammetric approach (SfM) is an image‐based method which could deliver a methodological leap if transferred to geomorphic applications, requires little training and is extremely inexpensive. Using an online SfM program, we created high‐resolution digital elevation models of a river environment from ordinary photographs produced from a workflow that takes advantage of free and open source software. This process reconstructs real world scenes from SfM algorithms based on the derived positions of the photographs in three‐dimensional space. The basic product of the SfM process is a point cloud of identifiable features present in the input photographs. This point cloud can be georeferenced from a small number of ground control points collected in the field or from measurements of camera positions at the time of image acquisition. The georeferenced point cloud can then be used to create a variety of digital elevation products. We examine the applicability of SfM in the Pedernales River in Texas (USA), where several hundred images taken from a hand‐held helikite are used to produce DEMs of the fluvial topographic environment. This test shows that SfM and low‐altitude platforms can produce point clouds with point densities comparable with airborne LiDAR, with horizontal and vertical precision in the centimeter range, and with very low capital and labor costs and low expertise levels. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

5.
Drainage channels are an integral part of agricultural landscapes, and their impact on catchment hydrology is strongly recognized. In cultivated and urbanized floodplains, channels have always played a key role in flood protection, land reclamation, and irrigation. Bank erosion is a critical issue in channels. Neglecting this process, especially during flood events, can result in underestimation of the risk in flood‐prone areas. The main aim of this work is to consider a low‐cost methodology for the analysis of bank erosion in agricultural drainage networks, and in particular for the estimation of the volumes of eroded and deposited material. A case study located in the Veneto floodplain was selected. The research is based on high‐resolution topographic data obtained by an emerging low‐cost photogrammetric method (structure‐from‐motion or SfM), and results are compared to terrestrial laser scanning (TLS) data. For the SfM analysis, extensive photosets were obtained using two standalone reflex digital cameras and an iPhone5® built‐in camera. Three digital elevation models (DEMs) were extracted at the resolution of 0.1 m using SfM and were compared with the ones derived by TLS. Using the different DEMs, the eroded areas were then identified using a feature extraction technique based on the topographic parameter Roughness Index (RI). DEMs derived from SfM were effective for both detecting erosion areas and estimating quantitatively the deposition and erosion volumes. Our results underlined how smartphones with high‐resolution built‐in cameras can be competitive instruments for obtaining suitable data for topography analysis and Earth surface monitoring. This methodology could be potentially very useful for farmers and/or technicians for post‐event field surveys to support flood risk management. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

6.
Different high‐resolution techniques can be employed to obtain information about the three‐dimensional (3D) surface of glaciers. This is typically carried out using efficient, but also expensive and logistically demanding, light detection and ranging (LiDAR) technologies, such as airborne scanners and terrestrial laser scanners. Recent technological improvements in the field of image analysis and computer vision have prompted the development of a low‐cost photogrammetric approach, which is referred to as ‘structure‐from‐motion’ (SfM). Combined with dense image‐matching algorithms, this method has become competitive for the production of high‐quality 3D models. However, several issues typical of this approach should be considered for application in glacial environments. In particular, the surface morphology, the different substrata, the occurrence of sharp contrast from solar shadows and the variable distance from the camera positions can negatively affect the image texture, and reduce the possibility of obtaining a reliable point cloud from the images. The objective of this study is to test the structure‐from‐motion multi view stereo (SfM‐MVS) approach in a small debris‐covered glacier located in the eastern Italian Alps, using a consumer‐grade reflex camera and the computer vision‐based software PhotoScan. The quality of the 3D models produced by the SfM‐MVS process was assessed via the comparison with digital terrain models obtained from terrestrial laser scanning (TLS) surveys that were performed at the same epochs. The effect of different terrain gradients and different substrata (debris, snow and firn) was also evaluated in terms of the accuracy of the reconstruction by SfM‐MVS versus TLS. Our results show that the quality of this new photogrammetric approach is similar to the quality of TLS and that point cloud densities are comparable or even higher compared with TLS. However, special care should be taken while planning the SfM survey geometry, to optimize the 3D model quality and spatial coverage. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

7.
This is the era of digital landscapes; the widespread availability of powerful sensing technologies has revolutionized the way it is possible to interrogate landscapes in order to understand the processes sculpting them. Vastly greater areas have now been acquired at ‘high resolution’: currently tens of metres globally to millimetric precision and accuracy locally. This permits geomorphic features to be visualized and analysed across the scales at which Earth‐surface processes operate. Especially exciting is the capturing of process dynamics in repeated surveying, which will only become more important with low‐cost accessible data generation through techniques such as Structure from Motion (SfM). But the key challenge remains; to interpret high resolution Digital Terrain Models (DTMs), particularly by extracting geomorphic features in robust and objective ways and then linking the observed features to the underlying physical processes. In response to the new data and challenges, recent years have seen improved processing of raw data into DTMs, development of data fusion techniques, novel quantitative analysis of topographic data, and innovative geomorphological mapping. The twelve papers collected in this volume sample this progress in interrogating Earth‐surface processes through the analysis of DTMs. They cover a wide range of disciplines and spatio‐temporal scales, from landslide prone landscapes, to agriculturally modified regions, to mountainous landscapes, and coastal zones. They all, however, showcase the quantitative exploitation of information contained in high‐resolution topographic data that we believe will underpin the improvement of our understanding of many elements of Earth‐surface processes. Most of the papers introduced here were first presented in a conference session at the European Geosciences Union General Assembly in 2011. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

8.
Flood modelling of urban areas is still at an early stage, partly because until recently topographic data of sufficiently high resolution and accuracy have been lacking in urban areas. However, digital surface models (DSMs) generated from airborne scanning laser altimetry (LiDAR) having sub‐metre spatial resolution have now become available, and these are able to represent the complexities of urban topography. This paper describes the development of a LiDAR post‐processor for urban flood modelling based on the fusion of LiDAR and digital map data. The map data are used in conjunction with LiDAR data to identify different object types in urban areas, though pattern recognition techniques are also employed. Post‐processing produces a digital terrain model (DTM) for use as model bathymetry, and also a friction parameter map for use in estimating spatially distributed friction coefficients. In vegetated areas, friction is estimated from LiDAR‐derived vegetation height, and (unlike most vegetation removal software) the method copes with short vegetation less than ～1 m high, which may occupy a substantial fraction of even an urban floodplain. The DTM and friction parameter map may also be used to help to generate an unstructured mesh of a vegetated urban floodplain for use by a two‐dimensional finite element model. The mesh is decomposed to reflect floodplain features having different frictional properties to their surroundings, including urban features (such as buildings and roads) and taller vegetation features (such as trees and hedges). This allows a more accurate estimation of local friction. The method produces a substantial node density due to the small dimensions of many urban features. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

9.
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10.
This study uses landform curvature as an approach for channel network extraction. We considered a study area located in the eastern Italian Alps where a high‐quality set of LiDAR data was available and where channel heads and related channel network were mapped in the field. In the analysis, we derived 1‐m DTMs from different ground LiDAR point densities, and we used different smoothing factors for the landscape curvature calculation in order to test the suitability of the LiDAR point density and the derived curvature maps for the recognition of channel network. This methodology is based on threshold values of the curvature calculated as multiples (1–3 times) of the standard deviation of the curvature. Our analyses suggested that (i) the window size for curvature calculations has to be a function of the size of the features to be detected, (ii) a coarse ground LiDAR point density could be as useful as a finer one for the recognition of main channel network features and (iii) rougher curvature maps are not optimal as they do not explore a sufficient range at which features occur, while smoother curvature maps overcome this problem and are more appropriate for the extraction of surveyed channels. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

11.
The development of high resolution LiDAR digital terrain models (DTMs) has enabled the exploration of the statistical signature of morphology on curvature distributions. This work analyzes Minimum Curvature distributions to identify the statistical signature of two types of LiDAR‐DTM errors (outliers and striping artifacts) in the derived estimates, rather than morphology itself. The analysis shows the importance of modeling these errors correctly, in relation to the scale of analysis and DTM resolution, in order to have reliable curvature estimates. Nine DTMs of different morphological areas are considered, and grouped into a training dataset (without errors) and a test dataset (with errors). In the training dataset, the original DTMs are considered as true values; errors are then applied to these data. Minimum Curvature is computed at multiple scales from each DTM: changes in curvature distributions due only to morphology and scale are characterized from the original data; error effects are then identified from the datasets with simulated errors, and validated against the test dataset. The analysis shows that outliers and striping artifacts can be realistically simulated by heavily left tailed distributions. For DTMs without errors, the scale‐dependent change in curvature distribution is primarily controlled by real morphology. When DTMs include errors, curvature distributions become controlled by these errors, whose propagation depends on error distribution, error spatial correlation, and the scale of analysis. This study shows that the curvature distributions are impacted upon differently by striping artifacts and outliers, and that these are clearly distinguishable from the signal of morphological features: a scale‐dependent change in curvature distribution can therefore be interpreted as the signature of these specific errors, rather than morphology. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

12.
Stream bathymetry is a critical variable in a number of river science applications. In larger rivers, bathymetry can be measured with instruments such as sonar (single or multi‐beam), bathymetric airborne LiDAR (light detection and ranging), or acoustic Doppler current profilers. However, in smaller streams with depths less than 2 m, bathymetry is one of the more difficult variables to map at high‐resolution. Optical remote sensing techniques offer several potential solutions for collecting high‐resolution bathymetry. In this research, I focus on direct photogrammetric measurements of bathymetry using multi‐view stereo photogrammetry, specifically Structure‐from‐Motion (SfM). The main barrier to accurate bathymetric mapping with any photogrammetric technique is correcting for the refraction of light as it passes between the two different media (air and water), which causes water depths to appear shallower than they are. I propose and test an iterative approach that calculates a series of refraction correction equations for every point/camera combination in a SfM point cloud. This new method is meant to address shortcomings of other correction techniques and works within the current preferred method for SfM data collection, oblique and highly convergent photographs. The multi‐camera refraction correction presented here produces bathymetric datasets with accuracies of ~0.02% of the flying height and precisions of ~0.1% of the flying height. This methodology, like many fluvial remote sensing methods, will only work under ideal conditions (e.g. clear water), but it provides an additional tool for collecting high‐resolution bathymetric datasets for a variety of river, coastal, and estuary systems. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

13.
In August 2009, the typhoon Morakot, characterized by a cumulative rainfall up to 2884 mm in about three days, triggered thousands of landslides in Taiwan. The availability of LiDAR surveys before (2005) and after (2010) this event offers a unique opportunity to investigate the topographic signatures of a major typhoon. The analysis considers the comparison of slope–area relationships derived by LiDAR digital terrain models (DTMs). This approach has been successfully used to distinguish hillslope from channelized processes, as a basis to develop landscape evolution models and theories, and understand the linkages between landscape morphology and tectonics, climate, and geology. We considered six catchments affected by a different degree of erosion: three affected by shallow and deep‐seated landslides, and three not affected by erosion. For each of these catchments, 2 m DTMs were derived from LiDAR data. The scaling regimes of local slope versus drainage area suggested that for the catchments affected by landslides: (i) the hillslope‐to‐valley transitions morphology, for a given value of drainage area, is shifted towards higher value of slopes, thus indicating a likely migration of the channelized processes and erosion toward the catchment boundary (the catchment head becomes steeper because of erosion); (ii) the topographic gradient along valley profiles tends to decrease progressively (the valley profile becomes gentler because of sediment deposition after the typhoon). The catchments without any landslides present a statistically indistinguishable slope–area scaling regime. These results are interesting since for the first time, using multi‐temporal high‐resolution topography derived by LiDAR, we demonstrated that a single climate event is able to cause significant major geomorphic changes on the landscape, detectable using slope–area scaling analysis. This provides new insights about landscape evolution under major climate forcing. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

14.
A prime requirement for hydrological applications,such as sediment budgeting or numerical modelling,is that produced Digital Terrain Models(DTMs)accurately represent the shape of landforms,especially for river reaches where data are not homogeneous.DTM error is a function of data point measurement accuracy and density and also of the field survey strategy when limited amounts of data will be acquired.This paper aims to advance the importance of the field survey strategy for the specific,but common cases,where only limited topographic data will be available.This methodology is based on the idea that any feature can be properly described by a set of cross sections and breaklines describing both main and secondary directions of the flow.Then,a longitudinal linear interpolation can be applied to the defined homogeneous zones.This morphologically oriented(MO)method that includes data acquisition strategy and interpolation,was validated using a reference DTM derived from LiDAR measurements.An estimation of the uncertainties also is suggested based on the distance of the nearest point and the local slope using a geographically weighted regression.The proposed MO method is typically applicable to Alpine river reaches characterized by multiple channels that may always be underwater and not navigable such as an alternate bar system with secondary and transverse channels.  相似文献   

15.
洪湖湿地抗渍蓄洪能力分析   总被引：3，自引：0，他引：3  
肖飞  蔡述明  杜耘 《湖泊科学》2003,15(Z1):243-248
鉴于洪湖湿地为渍涝灾害的多发区,并在江汉平原具有一定的代表意义,本文以该区为研究对象,利用遥感和地理信息系统技术进行分析,以便正确认识洪湖湿地的抗渍蓄洪能力.建立洪湖湿地的TIN模型以分析该区的抗渍蓄洪能力,并分别计算出洪湖湖泊的调蓄能力和整个洪湖湿地水位同蓄水面积及蓄水容量之间的关系.通过TIN模型与2001年的LandSat-ETM+遥感图像的叠加分析,统计出不同湿地类型的平均高程.依此计算出23. Ini高程线为水稻田的耕作线,由此推算出水稻基本不受影响条件下洪湖湿地的调蓄容量为1.087×109 m3.并提出在该区建立基于地理信息系统的减灾决策体系的建议,以便进行有效的防灾减灾.  相似文献   

16.
Large-scale flood modelling approaches designed for regional to continental scales usually rely on relatively simple assumptions to represent the potentially highly complex river bathymetry at the watershed scale based on digital elevation models (DEMs) with a resolution in the range of 25–30 m. Here, high-resolution (1 m) LiDAR DEMs are employed to present a novel large-scale methodology using a more realistic estimation of bathymetry based on hydrogeomorphological GIS tools to extract water surface slope. The large-scale 1D/2D flood model LISFLOOD-FP is applied to validate the simulated flood levels using detailed water level data in four different watersheds in Quebec (Canada), including continuous profiles over extensive distances measured with the HydroBall technology. A GIS-automated procedure allows to obtain the average width required to run LISFLOOD-FP. The GIS-automated procedure to estimate bathymetry from LiDAR water surface data uses a hydraulic inverse problem based on discharge at the time of acquisition of LiDAR data. A tiling approach, allowing several small independent hydraulic simulations to cover an entire watershed, greatly improves processing time to simulate large watersheds with a 10-m resampled LiDAR DEM. Results show significant improvements to large-scale flood modelling at the watershed scale with standard deviation in the range of 0.30 m and an average fit of around 90%. The main advantage of the proposed approach is to avoid the need to collect expensive bathymetry data to efficiently and accurately simulate flood levels over extensive areas.  相似文献   

17.
Airborne scanning laser altimetry (LiDAR) is an important new data source that can provide two‐dimensional river flood models with spatially distributed floodplain topography for model bathymetry, together with vegetation heights for parameterization of model friction. Methods are described for improving such models by decomposing the model's finite‐element mesh to reflect floodplain vegetation features such as hedges and trees having different frictional properties to their surroundings, and significant floodplain topographic features having high height curvatures. The decomposition is achieved using an image segmentation system that converts the LiDAR height image into separate images of surface topography and vegetation height at each point. The vegetation height map is used to estimate a friction factor at each mesh node. The spatially distributed friction model has the advantage that it is physically based, and removes the need for a model calibration exercise in which free parameters specifying friction in the channel and floodplain are adjusted to achieve best fit between modelled and observed flood extents. The scheme was tested in a modelling study of a flood that occurred on the River Severn, UK, in 1998. A satellite synthetic aperture radar image of flood extent was used to validate the model predictions. The simulated hydraulics using the decomposed mesh gave a better representation of the observed flood extent than the more simplistic but computationally efficient approach of sampling topography and vegetation friction factors on to larger floodplain elements in an undecomposed mesh, as well as the traditional approach using no LiDAR‐derived data but simply using a constant floodplain friction factor. Use of the decomposed mesh also allowed velocity variations to be predicted in the neighbourhood of vegetation features such as hedges. These variations could be of use in predicting localized erosion and deposition patterns that might result in the event of a flood. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   

18.
The boat‐based, mobile mapping system (BoMMS) with a laser scanner allows the derivation of detailed riverine topographical data for fluvial applications. Combined with data acquisition from static terrestrial LiDAR (light detection and range) or mobile terrestrial LiDAR on the ground, boat‐based laser scanning enables a totally new field mapping approach for fluvial studies. The BoMMS approach is an extremely rapid methodology for surveying riverine topography, taking only 85 min to survey a reach approximately 6 km in length. The BoMMS approach also allowed an effective survey angle for deep river banks, which is difficult to achieve with aerial or static terrestrial LiDAR. Further, this paper demonstrates the three‐dimensional mapping of a point‐bar and its detailed morphology. Compared with the BoMMS surface, approximately, 80% and 96% of the terrestrial LiDAR points showed a height deviation of less than 2 cm and 5 cm, respectively, with an overall standard deviation of ± 2·7 cm. This level of accuracy and rapidity of data capture enables the mapping of post‐flood deposition directly after a flood event without an extensive time lag. Additionally, the improved object characterisation may allow for better 3D mapping of the point bar and other riverrine features. However, the shadow effect of the BoMMS survey in point bar mapping should be removed by additional LiDAR data to acquire entire riverine topography. The approach demonstrated allowed a large reach to be surveyed compared with static terrestrial LiDAR and increased the spatial limit of survey towards aerial LiDAR, but it maintains the same or even better temporal resolution as static terrestrial LiDAR. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

19.
Coastal areas are vulnerable to the impacts of tropical cyclones (TC), tsunamis and other water super‐elevation events, but the frequency of these events is often poorly represented by conventional records. Coastal overwash deposits (including washover fans) can provide a longer‐term archive of event frequency. Because of their low‐gradient geomorphic form, washover fans require high accuracy (centimetre‐resolution) topographic models to understand patterns of connectivity and dynamics that control archive formation. Using images collected by a remotely piloted aircraft system (RPAS, or ‘drone’) and Structure‐from‐Motion (SfM) photogrammetry techniques, we apply a novel point‐cloud filtering technique based on KMeans classification of the R‐G‐B colour of each X‐Y‐Z point to remove vegetation and create a centimetre‐resolution and accuracy bare‐earth digital terrain model (DTM) of a washover fan in Exmouth Gulf (Western Australia). Using the RPAS‐SfM orphophoto and DEM data, supported by ground‐penetrating radar (GPR) and field stratigraphic analysis, we show how this approach can be applied to understand dynamics controlling low‐gradient geomorphic landforms, using an example of a washover fan sedimentary archive in northwestern Australia created by extreme overwash events. Our approach reveals the likely role of backflooding and terrestrial runoff in creating backwater environment for sub‐aqueous deposition and good sediment preservation and identifies key areas to target for detailed dating and stratigraphic analysis of a potentially decadal to sub‐millennial resolution sediment archive of TC activity. Copyright © 2018 John Wiley & Sons, Ltd.  相似文献   

20.
Flood modelling inputs used to create flood hazard maps are normally based on the assumption of data stationarity for flood frequency analysis. However, changes in the behaviour of climate systems can lead to nonstationarity in flood series. Here, we develop flood hazard maps for Ho Chi Minh City, Vietnam, under nonstationary conditions using extreme value analysis, a coupled 1D–2D model and high-resolution topographical data derived from LiDAR (Light Detection and Ranging) data. Our findings indicate that ENSO (El Niño Southern Oscillation) and PDO (Pacific Decadal Oscillation) influence the magnitude and frequency of extreme rainfall, while global sea-level rise causes nonstationarity in local sea levels, having an impact on flood risk. The detailed flood hazard maps show that areas of high flood potential are located along river banks, with 0.60 km2 of the study area being unsafe for people, vehicles and buildings (H5 zone) under a 100-year return period scenario.  相似文献   

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