Editorial     

Hadi Hajibeygi  Jan Dirk Jansen  Olwijn Leeuwenburgh  Denis Voskov 《Computational Geosciences》2017,21(5-6):833-833

  相似文献   

Applicability of generalized additive model in groundwater potential modelling and comparison its performance by bivariate statistical methods   总被引：3，自引：0，他引：3  

Fatemeh Falah  Samira Ghorbani Nejad  Omid Rahmati  Mania Daneshfar  Hossein Zeinivand 《国际地球制图》2017,32(10):1069-1089

Groundwater is the most valuable natural resource in arid areas. Therefore, any attempt to investigate potential zones of groundwater for further management of water supply is necessary. Hence, many researchers have worked on this subject all around the world. On the other hand, the Generalized Additive Model (GAM) has been applied to environmental and ecological modelling, but its applicability to other kinds of predictive modelling such as groundwater potential mapping has not yet been investigated. Therefore, the main purpose of this study is to evaluate the performance of GAM model and then its comparison with three popular GIS-based bivariate statistical methods, namely Frequency Ratio (FR), Statistical Index (SI) and Weight-of-Evidence (WOE) for producing groundwater spring potential map (GSPM) in Lorestan Province Iran. To achieve this, out of 6439 existed springs, 4291 spring locations were selected for training phase and the remaining 2147 springs for model evaluation. Next, the thematic layers of 12 effective spring parameters including altitude, plan curvature, slope angle, slope aspect, drainage density, distance from rivers, topographic wetness index, fault density, distance from fault, lithology, soil and land use/land cover were mapped and integrated using the ArcGIS 10.2 software to generate a groundwater prospect map using mentioned approaches. The produced GSPMs were then classified into four distinct groundwater potential zones, namely low, moderate, high and very high classes. The results of the analysis were finally validated using the receiver operating characteristic (ROC) curve technique. The results indicated that out of four models, SI is superior (prediction accuracy of 85.4%) following by FR, GAM and WOE, respectively (prediction accuracy of 83.7, 77 and 76.3%). The result of groundwater spring potential map is helpful as a guide for engineers in water resources management and land use planning in order to select suitable areas to implement development schemes and also government entities.  相似文献   

Soil temperature modeling at different depths using neuro-fuzzy,neural network,and genetic programming techniques     

Ozgur?KisiEmail author  Hadi?Sanikhani  Murat?Cobaner 《Theoretical and Applied Climatology》2017,129(3-4):833-848

The applicability of artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and genetic programming (GP) techniques in estimating soil temperatures (ST) at different depths is investigated in this study. Weather data from two stations, Mersin and Adana, Turkey, were used as inputs to the applied models in order to model monthly STs. The first part of the study focused on comparison of ANN, ANFIS, and GP models in modeling ST of two stations at the depths of 10, 50, and 100 cm. GP was found to perform better than the ANN and ANFIS-SC in estimating monthly ST. The effect of periodicity (month of the year) on models’ accuracy was also investigated. Including periodicity component in models’ inputs considerably increased their accuracies. The root mean square error (RMSE) of ANN models was respectively decreased by 34 and 27 % for the depths of 10 and 100 cm adding the periodicity input. In the second part of the study, the accuracies of the ANN, ANFIS, and GP models were compared in estimating ST of Mersin Station using the climatic data of Adana Station. The ANN models generally performed better than the ANFIS-SC and GP in modeling ST of Mersin Station without local climatic inputs.  相似文献   

Comparative analysis of support vector machine and artificial neural network models for soil cation exchange capacity prediction     

A. A. Jafarzadeh  M. Pal  M. Servati  M. H. FazeliFard  M. A. Ghorbani 《International Journal of Environmental Science and Technology》2016,13(1):87-96

  相似文献   

Modeling landfill site selection by multi-criteria decision making and fuzzy functions in GIS,case study: Shabestar,Iran     

Sara Bahrani  Taghi Ebadi  Hadi Ehsani  Hossein Yousefi  Reza Maknoon 《Environmental Earth Sciences》2016,75(4):337

  相似文献   

Modeling river discharge time series using support vector machine and artificial neural networks     

Mohammad Ali Ghorbani  Rahman Khatibi  Arun Goel  Mohammad Hasan FazeliFard  Atefeh Azani 《Environmental Earth Sciences》2016,75(8):685

  相似文献   

Environmental isotope systematics of the groundwater system of southern Kuwait     

Khaled Hadi  U. Saravana Kumar  M. Al-Senafy  H. Bhandary 《Environmental Earth Sciences》2016,75(14):1096

  相似文献   

Monotone multiscale finite volume method     

Yixuan Wang  Hadi Hajibeygi  Hamdi A. Tchelepi 《Computational Geosciences》2016,20(3):509-524

The MultiScale Finite Volume (MSFV) method is known to produce non-monotone solutions. The causes of the non-monotone solutions are identified and connected to the local flux across the boundaries of primal coarse cells induced by the basis functions. We propose a monotone MSFV (m-MSFV) method based on a local stencil-fix that guarantees monotonicity of the coarse-scale operator, and thus, the resulting approximate fine-scale solution. Detection of non-physical transmissibility coefficients that lead to non-monotone solutions is achieved using local information only and is performed algebraically. For these ‘critical’ primal coarse-grid interfaces, a monotone local flux approximation, specifically, a Two-Point Flux Approximation (TPFA), is employed. Alternatively, a local linear boundary condition can be used for the dual basis functions to reduce the degree of non-monotonicity. The local nature of the two strategies allows for ensuring monotonicity in local sub-regions, where the non-physical transmissibility occurs. For practical applications, an adaptive approach based on normalized positive off-diagonal coarse-scale transmissibility coefficients is developed. Based on the histogram of these normalized coefficients, one can remove the large peaks by applying the proposed modifications only for a small fraction of the primal coarse grids. Though the m-MSFV approach can guarantee monotonicity of the solutions to any desired level, numerical results illustrate that employing the m-MSFV modifications only for a small fraction of the domain can significantly reduce the non-monotonicity of the conservative MSFV solutions.  相似文献   

Prediction of porosity and water saturation using pre-stack seismic attributes: a comparison of Bayesian inversion and computational intelligence methods     

Hadi Fattahi  Sadegh Karimpouli 《Computational Geosciences》2016,20(5):1075-1094

Rock physical parameters such as porosity and water saturation play an important role in the mechanical behavior of hydrocarbon reservoir rocks. A valid and reliable prediction of these parameters from seismic data is essential for reservoir characterization, management, and also geomechanical modeling. In this paper, the application of conventional methods such as Bayesian inversion and computational intelligence methods, namely support vector regression (SVR) optimized by particle swarm optimization (PSO) and adaptive network-based fuzzy inference system-subtractive clustering method (ANFIS-SCM), is demonstrated to predict porosity and water saturation. The prediction abilities offered by Bayesian inversion, SVR-PSO, and ANFIS-SCM were presented using a synthetic dataset and field data available from a gas carbonate reservoir in Iran. In these models, seismic pre-stack data and attributes were utilized as the input parameters, while the porosity and water saturation were the output parameters. Various statistical performance indexes were utilized to compare the performance of those estimation models. The results achieved indicate that the ANFIS-SCM model has strong potential for indirect estimation of porosity and water saturation with high degree of accuracy and robustness from seismic data and attributes in both synthetic and real cases of this study.  相似文献   

Expert views on biodiversity conservation in an era of climate change     

Shannon Hagerman  Hadi Dowlatabadi  Terre Satterfield  Tim McDaniels 《Global Environmental Change》2010,20(1):192-207

Adapting conservation policy to the impacts of climate change has emerged as a central and unresolved challenge. In this paper, we report on the results of 21 in-depth interviews with biodiversity and climate change adaptation experts on their views of the implications of climate change for conservation policy. We find a diversity of views across a set of topics that included: changing conservation objectives, conservation triage and its criteria, increased management interventions in protected areas, the role of uncertainty in decision-making, and evolving standards of conservation success. Notably, our findings reveal active consideration among experts with some more controversial elements of policy adaptation (including the role of disturbance in facilitating species transitions, and changing standards of conservation success), despite a comparative silence on these topics in the published literature. Implications of these findings are discussed with respect to: (a) identifying future research and integration needs and (b) providing insight into the process of policy adaptation in the context of biodiversity conservation.  相似文献