Geophysical Signature of the Shallow Water Flow in the Deepwater Basin of the Northern South China Sea     

Xiaohua Zhang  Yunbao Sun  Shiguo Wu 《中国海洋大学学报(英文版)》2018,17(4):791-798

Shallow water flow (SWF), a disastrous geohazard in the continental margin, has threatened deepwater drilling operations. Under overpressure conditions, continual flow delivering unconsolidated sands upward in the shallow layer below the seafloor may cause large and long-lasting uncontrolled flows; these flows may lead to control problems and cause well damage and foundation failure. Eruptions from over-pressured sands may result in seafloor craters, mounds, and cracks. Detailed studies of 2D/3D seismic data from a slope basin of the South China Sea (SCS) indicated the potential presence of SWF. It is commonly characterized by lower elastic impedance, a higher Vp/Vs ratio, and a higher Poisson’s ratio than that for the surrounding sediments. Analysis of geological data indicated the SWF zone originated from a deepwater channel system with gas bearing over-pressured fluid flow and a high sedimentation rate. We proposed a fluid flow model for SWF that clearly identifies its stress and pressure changes. The rupture of previous SWF zones caused the fluid flow that occurred in the Baiyun Sag of the northern SCS.  相似文献   

Estimating aboveground biomass using Pléiades satellite image in a karst watershed of Guizhou Province,Southwestern China     

Yin-ming Guo  Jian Ni  Li-bin Liu  Chun-zi Guo  Xin Xu  Qiao-lian Zhong 《山地科学学报》2018,15(5):1020-1034

Biomass in karst terrain has rarely been measured because the steep mountainous limestone terrain has limited the ability to sample woody plants.Satellite observation, especially at high spatial resolution, is an important surrogate for the quantification of the biomass of karst forests and shrublands. In this study, an artificial neural network(ANN) model was built using Pléiades satellite imagery and field biomass measurements to estimate the aboveground biomass(AGB) in the Houzhai River Watershed, which is a typical plateau karst basin in Central Guizhou Province, Southwestern China. A back-propagation ANN model was also developed.Seven vegetation indices, two spectral bands of Pléiades imagery, one geomorphological parameter,and land use/land cover were selected as model inputs. AGB was chosen as an output. The AGB estimated by the allometric functions in 78 quadrats was utilized as training data(54 quadrats, 70%),validation data(12 quadrats, 15%), and testing data(12 quadrats, 15%). Data-model comparison showed that the ANN model performed well with an absolute root mean square error of 11.85 t/ha, which was 9.88%of the average AGB. Based on the newly developed ANN model, an AGB map of the Houzhai River Watershed was produced. The average predicted AGB of the secondary evergreen and deciduous broadleaved mixed forest, which is the dominant forest type in the watershed, was 120.57 t/ha. The average AGBs of the large distributed shrubland,tussock, and farmland were 38.27, 9.76, and 11.69 t/ha, respectively. The spatial distribution pattern ofthe AGB estimated by the new ANN model in the karst basin was consistent with that of the field investigation. The model can be used to estimate the regional AGB of karst landscapes that are distributed widely over the Yun-Gui Plateau.  相似文献   

Spatial downscaling of climate variables using three statistical methods in Central Iran     

Zahra Jaberalansar  Mostafa Tarkesh  Mehdi Bassiri 《山地科学学报》2018,15(3):606-617

Spatial downscaling methods are widely used for the production of bioclimatic variables(e.g. temperature and precipitation) in studies related to species ecological niche and drainage basin management and planning. This study applied three different statistical methods, i.e. the moving window regression(MWR), nonparametric multiplicative regression(NPMR), and generalized linear model(GLM), to downscale the annual mean temperature(Bio1) and annual precipitation(Bio12) in central Iran from coarse scale(1 km × 1 km) to fine scale(250 m ×250 m). Elevation, aspect, distance from sea and normalized difference vegetation index(NDVI) were used as covariates to create downscaled bioclimatic variables. Model assessment was performed by comparing model outcomes with observational data from weather stations. Coefficients of determination(R2), bias, and root-mean-square error(RMSE) were used to evaluate models and covariates. The elevation could effectively justify the changes in bioclimatic factors related to temperature and precipitation. Allthree models could downscale the mean annual temperature data with similar R2, RMSE, and bias values. The MWR had the best performance and highest accuracy in downscaling annual precipitation(R2=0.70; RMSE=123.44). In general, the two nonparametric models, i.e. MWR and NPMR, can be reliably used for the downscaling of bioclimatic variables which have wide applications in species distribution modeling.  相似文献   

Effects of Anthropogenic Disturbance on Sediment Organic Carbon Mineralization Under Different Water Conditions in Coastal Wetland of a Subtropical Estuary     

Xiaojie Mou  Xingtu Liu  Zhigao Sun  Chuan Tong  Jiafang Huang  Siang Wan  Chun Wang  Bolong Wen 《中国地理科学(英文版)》2018,28(3):400-410

The changes in soil organic carbon(C) mineralization as affected by anthropogenic disturbance directly determine the role of soils as C source or sink in the global C budget. The objectives of this study were to investigate the effects of anthropogenic disturbance(aquaculture pond, pollutant discharge and agricultural activity) on soil organic C mineralization under different water conditions in the Minjiang River estuary wetland, Southeast China. The results showed that the organic C mineralization in the wetland soils was significantly affected by human disturbance and water conditions(P 0.001), and the interaction between human disturbance activities and water conditions was also significant(P 0.01). The C mineralization rate and the cumulative mineralized carbon dioxide-carbon(CO_2-C)(at the 49th day) ranked from highest to lowest as follows: Phragmites australis wetland soil aquaculture pond sediment soil near the discharge outlet rice paddy soil. This indicated that human disturbance inhibited the mineralization of C in soils of the Minjiang River estuary wetland, and the inhibition increased with the intensity of human disturbance. The data for cumulative mineralized CO_2-C showed a good fit(R~2 0.91) to the first-order kinetic model C_t = C_0(1 – exp(–kt)). The kinetic parameters C_0, k and C_0 k were significantly affected by human disturbance and water conditions. In addition, the total amount of mineralized C(in 49 d) was positively related to C_0, C_0 k and electrical conductivity of soils. These findings indicated that anthropogenic disturbance suppressed the organic C mineralization potential in subtropical coastal wetland soils, and changes of water pattern as affected by human activities in the future would have a strong influence on C cycling in the subtropical estuarine wetlands.  相似文献   

Study on the performance of the micropile-mechanically stabilized earth wall     

Zhi-chao Zhang  Ronald Y. S. Pak  Yu-min Chen  Han-long Liu 《山地科学学报》2018,15(4):825-844

The Micropile-Mechanically Stabilized Earth (MSE) wall, specially designed for mountain roads, is proposed to improve the MSE wall local stability, global stability and impact resistance of roadside barriers. Model tests and the corresponding numerical modeling were conducted to validate the serviceability of the Micropile-MSE wall and the reliability of the numerical method. Then, a parametric study of the stress and deformation of Micropile-MSE wall based on the backfill strength and interfacial friction angle between backfill and backslope is conducted to evaluate its performance. The test results indicate that the surcharge-induced horizontal earth pressure, base pressure and lateral displacement of the wall panel of Micropile-MSE wall decrease. The corresponding numerical results are nearly equal to the measured values. The basic failure mode of MSE wall in steep terrain is the sliding of backfill along the backslope, while A-frame style micropiles are capable of preventing the sliding trend. The maximum resultant displacement can be decreased by 6.25% to 46.9% based on different interfacial friction angles, and the displacement can be reduced by 6% ~ 56.1% based on different backfill strengths. Furthermore, the reduction increases when the interfacial friction angle and internal friction angle of backfill decrease. In addition, the lateral displacement of wall panel, the deformation of backfill decrease and the tension strain of geogrid obviously, which guarantees the MSE wall functions and provides good conditions for mountain roads.  相似文献   

Using multispectral landsat and sentinel-2 satellite data to investigate vegetation change at Mount St. Helens since the great volcanic eruption in 1980     

Katharina Teltscher  Fabian Ewald Fassnacht 《山地科学学报》2018,15(9):1851-1867

Long-term analyses of vegetation succession after catastrophic events are of high interest for an improved understanding of succession dynamics. However, in many studies such analyses were restricted to plot-based measurements. Contrarily, spatially continuous observations of succession dynamics over extended areas and time-periods are sparse. Here, we applied a change vector analysis (CVA) to investigate vegetation succession dynamics at Mount St. Helens after the great volcanic eruption in 1980 using Landsat. We additionally applied a supervised random forest classification using Sentinel-2 data to map the currently prevailing vegetation types. Change vector analysis was performed with the normalized difference vegetation index (NDVI) and the urban index (UI) for three subsequent decades after the eruption as well as for the whole observation time between 1984 and 2016. The influence of topography on the current vegetation distribution was examined by comparing altitude, slope angles and aspect values of vegetation classes derived by the random forest classification. Wilcox- Rank-Sum test was applied to test for significant differences between topographic properties of the vegetation classes inside and outside of the areas affected by the eruption. For the full time period, a total area of 516 km² was identified as re-vegetated, whereas the area and magnitude of re-growing vegetation decreased during the three decades and migrated closer to the volcanic crater. Vegetation losses were mainly observed in regions unaffected by the eruption and related mostly to timber harvesting. The vegetation type classification reached a high overall accuracy of approximately 90%. 36 years after the eruption, coniferous and deciduous trees have established at formerly devastated areas dominating with a proportion of 66%, whereas shrubs are more abundant in riparian zones. Sparse vegetation dominates at regions very close to the crater. Elevation was found to have a great influence on the reestablishment and distribution of the vegetation classes within the devastated areas showing in almost all cases significant differences in altitude distribution. Slope was less important for the different classes - only representing significantly higher values for meadows, whereas aspect seems to have no notable influence on the reestablishment of vegetation at Mount St. Helens. We conclude that major vegetation succession dynamics after catastrophic events can be assessed and characterized over large areas from freely available remote sensing data and hence contribute to an improved understanding of succession dynamics.  相似文献   

Regional Characteristics and Causes of Haze Events in Northeast China     

Weiwei Chen  Shichun Zhang  Quansong Tong  Xuelei Zhang  Hongmei Zhao  Siqi Ma  Aijun Xiu  Yuexin He 《中国地理科学(英文版)》2018,28(5):836-850

Northeast China experiences severe atmospheric pollution, with an increasing occurrence of heavy haze episodes. However, the underlying forces driving haze formation during different seasons are poorly understood. In this study, we explored the spatio-temporal characteristics and causes of haze events in Northeast China by combining a range of data sources(i.e., ground monitoring, satellite-based products, and meteorological products). It was found that the ‘Shenyang-Changchun-Harbin(SCH)'city belt was the most polluted area in the region on an annual scale. The spatial distribution of air quality index(AQI) values had a clear seasonality, with the worst pollution occurring in winter, an approximately oval-shaped polluted area around western Jilin Province in spring, and the best air quality occurring in summer and most of the autumn. The three periods that typically experienced intense haze events were Period I from mid-October to mid-November(i.e., late autumn and early winter), Period II from late-December to February(i.e., the coldest time in winter), and Period III from April to mid-May(i.e., spring). During Period I, strong PM_(2.5) emissions from seasonal crop residue burning and coal burning for winter heating were the dominant reasons for the occurrence of extreme haze events(AQI 300). Period II had frequent heavy haze events(200 AQI 300) in the coldest months of January and February, which were due to high PM_(2.5) emissions from coal burning and vehicle fuel consumption, a lower atmospheric boundary layer, and stagnant atmospheric conditions. Haze events in Period III, with high PM_(10) concentrations, were primarily caused by the regional transportation of windblown dust from degraded grassland in central Inner Mongolia and bare soil in western Jilin Province. Local agricultural tilling could also release PM_(10) and enhance the levels of windblown dust from tilled soil. Better control of coal burning, fuel consumption, and crop residue burning in winter and autumn is urgently needed to address the haze problem in Northeast China.  相似文献   

Plant diversity and community structure of Brazilian <Emphasis Type="Italic">Páramos</Emphasis>     

Prímula Viana Campos  Pedro Manuel Villa  Jaquelina Alves Nunes  Carlos E.G.R. Schaefer  Stefan Porembski  Andreza Viana Neri 《山地科学学报》2018,15(6):1186-1198

In Eastern South America, high altitude grasslands represent a mountain system that has a high number of endemic species. However, studies on the ecology of plant communities in these environments remain scarce. We aimed to evaluate the patterns of biodiversity and structure of plant communities from rocky outcrops in high altitude grasslands of three areas at the Caparaó National Park, southeastern Brazil, by sampling 300 randomly distributed plots. Then, we compared the floristic composition, relative abundance, and biological and vegetation spectra among areas. We classified species as endemic and non-endemic and verified the occurrence of endangered species. Species richness was evaluated by rarefaction analysis on the sampling units. The importance value and species abundance distribution (SAD) models were assessed. We also performed an indicator species analysis. We sampled 58 species belonging to 49 genera and 32 families. The number of species decreased with increasing altitude, with significant differences being observed among areas regarding richness, abundance, and cover. Of the total number of species, 10 are endemic to the Caparaó National Park and 17 are listed on the Brazilian Red List of endangered species. The dominant families on all peaks were Asteraceae and Poaceae. The SAD models showed lognormal and geometric distributions, corroborating the fact that 10 species that were common to all three areas were also the most dominant ones in the communities and showed the highest importance values, which ranged between 35% and 60%. Indicator species analysis revealed that 28 species (48.27%) were indicators. Of these, 42.85% had maximum specificity, meaning that they occurred only in one area. Thus, the number of species per life form ratio was similar among areas, yet vegetation spectra differed, especially for hemicryptophytes. The altimetric difference among the areas showed to be a very important driver in the community assembly, influencing the evaluated variables, however, other drivers as soil depth, slope and water could also influence the community structure on a smaller and local spatial scale.  相似文献   

Influence of Headland Breakwaters on Morphological Processes at Longfengtou Beach in Haitan Bay,Facing the Taiwan Strait     

Cuiping Kuang  Yue Ma  Binyu Wang  Jueyi Sui  Jie Gu  Jianhui Liu  Gang Lei 《中国海洋大学学报(英文版)》2018,17(6):1290-1300

Breakwaters can be used as artificial headlands in beach nourishment to mitigate coastal erosion. Longfengtou Beach, located on the southwest coast of Haitan Bay facing the Taiwan Strait on the northeast, suffers severe erosion, where the monsoon causes significant season hydrodynamic variations. Headland breakwaters are intended to be employed to mitigate coastal erosion. A 2D sediment transport model is established using MIKE21 based on current-wave coupling and calibrated by measured data. Summer and winter wave conditions are chosen as characteristic weak and strong waves respectively. The numerical results of suspended sediment concentration and seasonal morphological evolution are compared under the conditions with and without the headland breakwaters. Sediment transport in summer can be regarded as mainly determined by current field, while in winter wave effect is strong enough to change current field. The northern breakwater, nearly perpendicular to the ebb current direction, obstructs the currents and decreases velocity of the ebb currents, and confines the water carrying sediments within the protection area during the flood period. The southern breakwater also breaks the waves in advance and significantly reduces the hydrodynamic effects during the flood period and maintains high suspended sediment concentration in the protection area. In general, two headland breakwaters decrease the erosion near the beach and enlarge the deposition area, which play a significant role in prevention of sediment loss in nearshore area and mitigate coastal erosion.  相似文献   

Multi-angle backscatter classification and sub-bottom profiling for improved seafloor characterization     

Evangelos Alevizos  Mirjam Snellen  Dick Simons  Kerstin Siemes  Jens Greinert 《Marine Geophysical Researches》2018,39(1-2):289-306

This study applies three classification methods exploiting the angular dependence of acoustic seafloor backscatter along with high resolution sub-bottom profiling for seafloor sediment characterization in the Eckernförde Bay, Baltic Sea Germany. This area is well suited for acoustic backscatter studies due to its shallowness, its smooth bathymetry and the presence of a wide range of sediment types. Backscatter data were acquired using a Seabeam1180 (180 kHz) multibeam echosounder and sub-bottom profiler data were recorded using a SES-2000 parametric sonar transmitting 6 and 12 kHz. The high density of seafloor soundings allowed extracting backscatter layers for five beam angles over a large part of the surveyed area. A Bayesian probability method was employed for sediment classification based on the backscatter variability at a single incidence angle, whereas Maximum Likelihood Classification (MLC) and Principal Components Analysis (PCA) were applied to the multi-angle layers. The Bayesian approach was used for identifying the optimum number of acoustic classes because cluster validation is carried out prior to class assignment and class outputs are ordinal categorical values. The method is based on the principle that backscatter values from a single incidence angle express a normal distribution for a particular sediment type. The resulting Bayesian classes were well correlated to median grain sizes and the percentage of coarse material. The MLC method uses angular response information from five layers of training areas extracted from the Bayesian classification map. The subsequent PCA analysis is based on the transformation of these five layers into two principal components that comprise most of the data variability. These principal components were clustered in five classes after running an external cluster validation test. In general both methods MLC and PCA, separated the various sediment types effectively, showing good agreement (kappa >0.7) with the Bayesian approach which also correlates well with ground truth data (r²?>?0.7). In addition, sub-bottom data were used in conjunction with the Bayesian classification results to characterize acoustic classes with respect to their geological and stratigraphic interpretation. The joined interpretation of seafloor and sub-seafloor data sets proved to be an efficient approach for a better understanding of seafloor backscatter patchiness and to discriminate acoustically similar classes in different geological/bathymetric settings.  相似文献