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排序方式: 共有488条查询结果,搜索用时 15 毫秒
61.
Sadeghi Babak Taghavi Farahnaz Akmal Amir Abbas Shayegani 《Geomagnetism and Aeronomy》2019,59(6):770-781
Geomagnetism and Aeronomy - In this study, a hypothesis is proposed about the possible effect of Geomagnetic field (GMF) on the charge structure of a thundercloud based on Lorentz force equation... 相似文献
62.
Evaluation of four supervised learning methods for groundwater spring potential mapping in Khalkhal region (Iran) using GIS-based features 总被引:1,自引:1,他引:0
One important tool for water resources management in arid and semi-arid areas is groundwater potential mapping. In this study, four data-mining models including K-nearest neighbor (KNN), linear discriminant analysis (LDA), multivariate adaptive regression splines (MARS), and quadric discriminant analysis (QDA) were used for groundwater potential mapping to get better and more accurate groundwater potential maps (GPMs). For this purpose, 14 groundwater influence factors were considered, such as altitude, slope angle, slope aspect, plan curvature, profile curvature, slope length, topographic wetness index (TWI), stream power index, distance from rivers, river density, distance from faults, fault density, land use, and lithology. From 842 springs in the study area, in the Khalkhal region of Iran, 70 % (589 springs) were considered for training and 30 % (253 springs) were used as a validation dataset. Then, KNN, LDA, MARS, and QDA models were applied in the R statistical software and the results were mapped as GPMs. Finally, the receiver operating characteristics (ROC) curve was implemented to evaluate the performance of the models. According to the results, the area under the curve of ROCs were calculated as 81.4, 80.5, 79.6, and 79.2 % for MARS, QDA, KNN, and LDA, respectively. So, it can be concluded that the performances of KNN and LDA were acceptable and the performances of MARS and QDA were excellent. Also, the results depicted high contribution of altitude, TWI, slope angle, and fault density, while plan curvature and land use were seen to be the least important factors. 相似文献
63.
64.
Quantitative analyses of groundwater flow and transport typically rely on a physically‐based model, which is inherently subject to error. Errors in model structure, parameter and data lead to both random and systematic error even in the output of a calibrated model. We develop complementary data‐driven models (DDMs) to reduce the predictive error of physically‐based groundwater models. Two machine learning techniques, the instance‐based weighting and support vector regression, are used to build the DDMs. This approach is illustrated using two real‐world case studies of the Republican River Compact Administration model and the Spokane Valley‐Rathdrum Prairie model. The two groundwater models have different hydrogeologic settings, parameterization, and calibration methods. In the first case study, cluster analysis is introduced for data preprocessing to make the DDMs more robust and computationally efficient. The DDMs reduce the root‐mean‐square error (RMSE) of the temporal, spatial, and spatiotemporal prediction of piezometric head of the groundwater model by 82%, 60%, and 48%, respectively. In the second case study, the DDMs reduce the RMSE of the temporal prediction of piezometric head of the groundwater model by 77%. It is further demonstrated that the effectiveness of the DDMs depends on the existence and extent of the structure in the error of the physically‐based model. 相似文献
65.
Amir Hossein Hakimhashemi Jeoung Seok Yoon Oliver Heidbach Arno Zang Gottfried Grünthal 《Journal of Seismology》2014,18(3):671-680
The M w 3.2-induced seismic event in 2006 due to fluid injection at the Basel geothermal site in Switzerland was the starting point for an ongoing discussion in Europe on the potential risk of hydraulic stimulation in general. In particular, further development of mitigation strategies of induced seismic events of economic concern became a hot topic in geosciences and geoengineering. Here, we present a workflow to assess the hazard of induced seismicity in terms of occurrence rate of induced seismic events. The workflow is called Forward Induced Seismic Hazard Assessment (FISHA) as it combines the results of forward hydromechanical-numerical models with methods of time-dependent probabilistic seismic hazard assessment. To exemplify FISHA, we use simulations of four different fluid injection types with various injection parameters, i.e. injection rate, duration and style of injection. The hydromechanical-numerical model applied in this study represents a geothermal reservoir with preexisting fractures where a routine of viscous fluid flow in porous media is implemented from which flow and pressure driven failures of rock matrix and preexisting fractures are simulated, and corresponding seismic moment magnitudes are computed. The resulting synthetic catalogues of induced seismicity, including event location, occurrence time and magnitude, are used to calibrate the magnitude completeness M c and the parameters a and b of the frequency-magnitude relation. These are used to estimate the time-dependent occurrence rate of induced seismic events for each fluid injection scenario. In contrast to other mitigation strategies that rely on real-time data or already obtained catalogues, we can perform various synthetic experiments with the same initial conditions. Thus, the advantage of FISHA is that it can quantify hazard from numerical experiments and recommend a priori a stimulation type that lowers the occurrence rate of induced seismic events. The FISHA workflow is rather general and not limited to the hydromechanical-numerical model used in this study and can therefore be applied to other fluid injection models. 相似文献
66.
67.
Mohammad Hadi Moeini Amir Etemad-Shahidi Vahid Chegini Iraj Rahmani 《Ocean Dynamics》2012,62(5):785-797
The main goal of this study is to develop an efficient approach for the assimilation of the hindcasted wave parameters in
the Persian Gulf. Hence, the third generation SWAN model was employed for wave modeling forced by the 6-h ECMWF wind data
with a resolution of 0.5°. In situ wave measurements at two stations were utilized to evaluate the assimilation approaches.
It was found that since the model errors are not the same for wave height and period, adaptation of model parameter does not
result in simultaneous and comprehensive improvement of them. Therefore, an approach based on the error prediction and updating
of output variables was employed to modify wave height and period. In this approach, artificial neural networks (ANNs) were
used to estimate the deviations between the simulated and measured wave parameters. The results showed that updating of output
variables leads to significant improvement in a wide range of the predicted wave characteristics. It was revealed that the
best input parameters for error prediction networks are mean wind speed, mean wind direction, wind duration, and the wave
parameters. In addition, combination of the ANN estimated error with numerically modeled wave parameters leads to further
improvement in the predicted wave parameters in contrast to direct estimation of the parameters by ANN. 相似文献
68.
Forest cover change assessment in conflict-affected areas of northwest Pakistan: the case of swat and shangla districts 总被引:2,自引:2,他引:0
Faisal Mueen QAMER Sawaid ABBAS Rashid SALEEM Khurram SHEHZAD Hassan ALI Hammad GILANI 《山地科学学报》2012,9(3):297-306
This study examines the spatial and temporal forest cover changes in Swat and Shangla districts to understand the deforestation pattern in context of the recent security conflict in these districts. We used multi-resolution satellite images to assess the long term deforestation from 2001 to 2009 and also to identify episodic forest cutting areas appeared during the conflict period of Oct. 2007 - Oct. 2008. There are only 58 ha of deforestation identified during the conflict period while 1268 ha of gross annual deforestation were assessed during last eight years. Most of the deforestation patches persist around the administrative boundaries at sub-district levels (tehsils) which can be attributed to ambiguity in unclear jurisdiction between the forest official. The results highlight that the forest cutting appeared in Swat and Shangla during the conflict period is not as significant when compared with the long term deforestation pattern in the area. On the one side the results of the study are supportive to the picture that emerges from international studies which report high rate of deforestation in the country and on the other side it negates any relation between the security situation and the increasing deforestation in the north western Pakistan. The study concludes that deforestation assessments require verification by independent sources of data, such as satellite imagery to improve our understanding of deforestation processes. 相似文献
69.
Ali Haghizadeh Safoura Siahkamari Amir Hamzeh Haghiabi Omid Rahmati 《Journal of Earth System Science》2017,126(3):39
With regard to the lack of quality information and data in watersheds, it is of high importance to present a new method for evaluating flood potential. Shannon’s entropy model is a new model in evaluating dangers and it has not yet been used to evaluate flood potential. Therefore, being a new model in determining flood potential, it requires evaluation and investigation in different regions and this study is going to deal with this issue. For to this purpose, 70 flooding areas were recognized and their distribution map was provided by ArcGIS10.2 software in the study area. Information layers of altitude, slope angle, slope aspect, plan curvature, drainage density, distance from the river, topographic wetness index (TWI), lithology, soil type, and land use were recognized as factors affecting flooding and the mentioned maps were provided and digitized by GIS environment. Then, flood susceptibility forecasting map was provided and model accuracy evaluation was conducted using ROC curve and 30% flooding areas express good precision of the model (73.5%) for the study area. 相似文献
70.
Estimation of enterococci input from bathers and animals on a recreational beach using camera images
John D. Wang Helena M. Solo-Gabriele Amir M. Abdelzaher Lora E. Fleming 《Marine pollution bulletin》2010,60(8):1270-6769
Enterococci, are used nationwide as a water quality indicator of marine recreational beaches. Prior research has demonstrated that enterococci inputs to the study beach site (located in Miami, FL) are dominated by non-point sources (including humans and animals). We have estimated their respective source functions by developing a counting methodology for individuals to better understand their non-point source load impacts. The method utilizes camera images of the beach taken at regular time intervals to determine the number of people and animal visitors. The developed method translates raw image counts for week days and weekend days into daily and monthly visitation rates. Enterococci source functions were computed from the observed number of unique individuals for average days of each month of the year, and from average load contributions for humans and for animals. Results indicate that dogs represent the larger source of enterococci relative to humans and birds. 相似文献