Depression filling is a critical step in distributed hydrological modeling using digital elevation models (DEMs). The traditional Priority‐Flood (PF) approach is widely used due to its relatively high efficiency when dealing with a small‐sized DEM. However, it seems inadequate and inefficient when dealing with large high‐resolution DEMs. In this work, we examined the relationship between the PF algorithm calculation process and the topographical characteristics of depressions, and found significant redundant calculations in the local micro‐relief areas in the conventional PF algorithm. As such calculations require more time when dealing with large DEMs, we thus propose a new variant of the PF algorithm, wherein redundant points and calculations are recognized and eliminated based on the local micro‐relief water‐flow characteristics of the depression‐filling process. In addition, depressions and flatlands were optimally processed by a quick queue to improve the efficiency of the process. The proposed method was applied and validated in eight case areas using the Shuttle Radar Topography Mission digital elevation model (SRTM‐DEM) with 1 arc‐second resolution. These selected areas have different data sizes. A comparative analysis among the proposed method, the Wang and Liu‐based PF, the improved Barnes‐based PF, the improved Zhou‐based PF, and the Planchon and Darboux (P&D) algorithms was conducted to evaluate the accuracy and efficiency of the proposed algorithm. The results showed that the proposed algorithm is 43.2% (maximum) faster than Wang and Liu's variant of the PF method, with an average of 31.8%. In addition, the proposed algorithm achieved similar performance to the improved Zhou‐based PF algorithm, though our algorithm has the advantage of being simpler. The optimal strategies using the proposed algorithm can be employed in various landforms with high efficiency. The proposed method can also achieve good depression filling, even with large amounts of DEM data. 相似文献
In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of landscape types. Analyzing and simulating spatio-temporal dynamic features of urban landscape can help to reveal its driving mechanisms and facilitate reasonable planning of urban land resources. The purpose of this study was to design a hybrid cellular automata model to simulate dynamic change in urban landscapes. The model consists of four parts: a geospatial partition, a Markov chain (MC), a multi-layer perceptron artificial neural network (MLP-ANN), and cellular automata (CA). This study employed multivariate land use data for the period 2000–2015 to conduct spatial clustering for the Ganjingzi District and to simulate landscape status evolution via a divisional composite cellular automaton model. During the period of 2000–2015, construction land and forest land areas in Ganjingzi District increased by 19.43% and 15.19%, respectively, whereas farmland, garden lands, and other land areas decreased by 43.42%, 52.14%, and 75.97%, respectively. Land use conversion potentials in different sub-regions show different characteristics in space. The overall land-change prediction accuracy for the subarea-composite model is 3% higher than that of the non-partitioned model, and misses are reduced by 3.1%. Therefore, by integrating geospatial zoning and the MLP-ANN hybrid method, the land type conversion rules of different zonings can be obtained, allowing for more effective simulations of future urban land use change. The hybrid cellular automata model developed here will provide a reference for urban planning and policy formulation. 相似文献
Natural Hazards - Coastal inundation due to storm tides is computed using ADvanced CIRCulation (ADCIRC) model along the east coast of India. Inland inundation due to storm tides is calculated every... 相似文献
Based on the three-dimensional digital image correlation (3D-DIC) technique, the stereovision system has been applied to the improved triaxial apparatus to obtain 3D full-field deformation of the specimen during triaxial testing. Through the calibration process, the 3D-DIC technique can obtain the accurate specimen’s spatial displacement deformation. Meanwhile, a subpixel edge detection algorithm has been combined with 3D-DIC technique to calculate the radial strain and the volume strain of the specimen directly. Furthermore, a series of consolidated drained and undrained triaxial tests were carried out on Hainan (China) sand specimens and measured by the conventional and the image measurement methods. Compared to the results measured by the conventional method, the image measurement technique can obtain the more experimental data, such as the 3D displacement field of the whole specimen, the local strain distribution, and so on. The measurement results also show the conventional method would be disturbed by the end constraints in triaxial tests so that the strength of the soil would be overestimated. Meanwhile, the middle of the specimen would be selected to calculate the stress–strain relationship without the influence of the end constraints in the proposed method. Based on the image measurement results, the proposed method has the potential to be used in geotechnical tests for exploring the soil’s progressive failure behaviors, inhomogeneous deformation and mechanical characteristics.
“Belt and Road” regions include Asia, Europe and eastern and northern Africa, with a wide spatial distribution. The cryosphere is undergoing rapid changes in the Belt and Road regions with global warming, and has an important impact on water resources, ecosystems and Arctic waterways in these regions. This article reviewed recent cryospheric changes and associated impacts on water resources in the Belt and Road regions during the last decades. The main cognitions are as follows: Most glaciers are shrinking and glacier mass balances are most negative, but there are regional differences in the changes of glaciers. Global temperature rise has resulted in permafrost degradation, including a rise in permafrost temperature and decreasing permafrost thickness as well as an increase in active layer thickness. There is a significant decrease in snow cover extent and an increase in snow depth. Snow cover duration has shortened, the onset of snow cover has delayed, and the end of snow cover has advanced. However, there are still obvious regional differences in the changes of snow cover. Arctic sea ice has declined precipitously in both extent and thickness in summer, and multi-year sea ice has decreased,indicating the precipitous retreat of sea ice. The freeze-up date of some lakes has been delayed, the break-up date has advanced, and the ice cover duration of river/lake ice has significantly shortened. Glacial runoff has increased significantly in China. Snowmelt and permafrost degradation have also increased the basin runoff, which indicates the important impact of cryospheric changes on runoff. This study will provide a baseline and important scientific support for addressing climate change and regional sustainable development. 相似文献