Water quality data for Fall Creek,New York,USA: 1972–1995     

David R. Bouldin  Niamh O'Leary 《水文研究》2021,35(1):e13968

The 33 086 ha mixed land use Fall Creek watershed in upstate New York is part of the Great Lakes drainage system. Results from more than 3500 water samples are available in a data set that compiles flow data and measurements of various water quality analytes collected between 1972 and 1995 in all seasons and under all flow regimes in Fall Creek and its tributaries. Data is freely accessible at https://ecommons.cornell.edu/handle/1813/8148 and includes measurements of suspended solids, pH, alkalinity, calcium, magnesium, potassium, sodium, chloride, nitrate nitrogen (NO3-N), sulphate sulphur (SO4-S), phosphorus (P) fractions molybdate reactive P (MRP) and total dissolved P (TDP), percent P in sediment, and ammonium nitrogen (NH4-N). Methods, sub-watershed areas, and coordinates for sampling sites are also included. The work represented in this data set has made important scientific contributions to understanding of hydrological and biogeochemical processes that influence loading in mixed use watersheds and that have an impact on algal productivity in receiving water bodies. In addition, the work has been foundational for important regulatory and management decisions in the region.  相似文献   

Determination of subcatchment and watershed boundaries in a complex and highly urbanized landscape          下载免费PDF全文

Aimé Kayembe  Carl P. J. Mitchell 《水文研究》2018,32(18):2845-2855

Urban development significantly alters the landscape by introducing widespread impervious surfaces, which quickly convey surface run‐off to streams via stormwater sewer networks, resulting in “flashy” hydrological responses. Here, we present the inadequacies of using raster‐based digital elevation models and flow‐direction algorithms to delineate large and highly urbanized watersheds and propose an alternative approach that accounts for the influence of anthropogenically modified land cover. We use a semi‐automated approach that incorporates conventional drainage networks into overland flow paths and define the maximal run‐off contributing area. In this approach, stormwater pipes are clustered according to their slope attributes, which define flow direction. Land areas drained by each cluster and contributing (or exporting) flow to a topographically delineated catchment were determined. These land masses were subsequently added or removed from the catchment, modifying both the shape and the size. Our results in a highly urbanized Toronto, Canada, area watershed indicate a moderate net increase in the directly connected watershed area by 3% relative to a topographically forced method; however, differences across three smaller scale subcatchments are greater. Compared to topographic delineation, the directly connected watershed areas of both the upper and middle subcatchments decrease by 5% and 8%, respectively, whereas the lower subcatchment area increases by 15%. This is directly related to subsurface storm sewer pipes that cross topographic boundaries. When directly connected subcatchment area is plotted against total streamflow and flashiness indices using this method, the coefficients of variation are greater (0.93 to 0.97) compared to the use of digital elevation model‐derived subcatchment areas (0.78 to 0.85). The accurate identification of watershed and subcatchment boundaries should incorporate ancillary data such as stormwater sewer networks and retention basin drainage areas to reduce water budget errors in urban systems.  相似文献   

Developing constitutive models from EPR‐based self‐learning finite element analysis          下载免费PDF全文

Ali Nassr  Akbar Javadi  Asaad Faramarzi 《国际地质力学数值与分析法杂志》2018,42(3):401-417

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.  相似文献   

基于噪声谱比法的内蒙古西部地区台站场地响应研究     

张珂  王鑫  王树波  张红才  宋晓燕 《大地测量与地球动力学》2020,40(6):646-651

利用内蒙古西部12个台站的地脉动噪声数据，采用噪声谱比法研究台站的场地响应情况。分析表明，台站场地响应按曲线形态可分为3类，且可能受地形地貌、局部构造和台基状况等条件影响。对比分析噪声谱比法与Moya方法的场地响应结果发现，场地响应曲线形态基本一致，只有极少数台站存在明显差异。结果表明，内蒙古西部区域大部分台站的台基状况总体较好，场地响应曲线较为平坦，无明显频率放大点。  相似文献   

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing     

Peng Yue  Fan Gao  Boyi Shangguan  Zheren Yan 《International journal of geographical information science》2020,34(11):2243-2274

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.  相似文献   

FEASIBLE STUDY ON THE INTEGRATION SYSTEM FOR THE SPACE MONITORING OF MAJOR EARTHQUAKES AND VOLCANOES IN TERRESTRIAL LAND   总被引：1，自引：1，他引：0  

BOLi-qun 《中国地理科学(英文版)》2002,12(4):350-353

With the rapid development of space technology, earth observation technology and sky observatory technolo-gy, they have played a more and more important part in monitoring and predicting of earthquakes and volcanoes in the terres-trial land. In recent years, the related agencies have done the experiments and researches on monitoring and predicting ofearthquakes and volcanoes in the forewarning period by means of many approaches, such as satellite thermal infrared re-mote sensing (TIRS), Global Positioning System (GPS), differential interferometric synthesis aperture radar (D-INSAR),astronomical time-latitude residual anomaly, and Geographic Information Systems (GIS), etc. A quite large number of re-search foundation has been built in the fundamental theories and application methods. The experiments and researcheshave shown that these technology is efficient methods for high frequency crust movement. If the existed separate scientificforces and results are possibly assembled together to form a more complete integration monitoring system with the combina-tion of space, sky observation, ground, deep geology and macro anomaly, it will come into a new stage of monitoring andpredicting of earthquakes and volcanic eruptions.  相似文献   

A highly automated moving object detection package   总被引：1，自引：0，他引：1  

J.-M. Petit  M. Holman  H. Scholl  J. Kavelaars  B. Gladman † 《Monthly notices of the Royal Astronomical Society》2004,347(2):471-480

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Polar shapelets     

Richard Massey  Alexandre Refregier 《Monthly notices of the Royal Astronomical Society》2005,363(1):197-210

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MATLAB在运用系统建模处理南海气象数据过程中应用     

董言治  周晓东  娄树理  陈永刚  沈同圣 《成都信息工程学院学报》2004,19(1):76-81

介绍了MATLAB语言特点和系统建模方法的基本理论.根据南海气象数据的实际建模处理过程,给出了建模的详细步骤及其MATLAB实现过程以及MATLABTM的主要实现程序.试验讨论和结果表明利用MATLAB语言可以方便地对南海气象数据用系统建模方法进行建模和处理,MATLAB在运用系统建模法处理南海气象数据方面具有明显的优越性.  相似文献   

Automated analysis of eclipsing binary light curves – II. Statistical analysis of OGLE LMC eclipsing binaries     

T. Mazeh  O. Tamuz  P. North 《Monthly notices of the Royal Astronomical Society》2006,367(4):1531-1542

In the first paper of this series, we presented EBAS – Eclipsing Binary Automated Solver, a new fully automated algorithm to analyse the light curves of eclipsing binaries, based on the ebop code. Here, we apply the new algorithm to the whole sample of 2580 binaries found in the Optical Gravitational Lensing Experiment (OGLE) Large Magellanic Cloud (LMC) photometric survey and derive the orbital elements for 1931 systems. To obtain the statistical properties of the short-period binaries of the LMC, we construct a well-defined subsample of 938 eclipsing binaries with main-sequence B-type primaries. Correcting for observational selection effects, we derive the distributions of the fractional radii of the two components and their sum, the brightness ratios and the periods of the short-period binaries. Somewhat surprisingly, the results are consistent with a flat distribution in log P between 2 and 10 d. We also estimate the total number of binaries in the LMC with the same characteristics, and not only the eclipsing binaries, to be about 5000. This figure leads us to suggest that  (0.7 ± 0.4)  per cent of the main-sequence B-type stars in the LMC are found in binaries with periods shorter than 10 d. This frequency is substantially smaller than the fraction of binaries found by small Galactic radial-velocity surveys of B stars. On the other hand, the binary frequency found by Hubble Space Telescope ( HST ) photometric searches within the late main-sequence stars of 47 Tuc is only slightly higher and still consistent with the frequency we deduced for the B stars in the LMC.  相似文献