GGMCalc a software for calculation of the geoid undulation and the height anomaly using the iteration method, and classical gravity anomaly

The Global Geopotential Models (GGMs) are very significant because of their usefulness in determination of the parameters like geoidal undulations, height anomalies, gravity anomalies, and so on. In this paper, first, we review the calculation of such parameters and then present the GGMCalc software, which is prepared in Fortran 95 under GNU/Linux Operating System. This software is capable of using the files presented by the International Center for Global Earth Models (ICGEM) directly without need to apply any changes on them. The software is completely structural and user friendly and could be used conveniently for academic purposes.     

A hybrid computational approach to formulate soil deformation moduli obtained from PLT

In this study, new empirical equations were developed to predict the soil deformation moduli utilizing a hybrid method coupling genetic programming and simulated annealing, called GP/SA. The proposed models relate secant (E_s), unloading (E_u) and reloading (E_r) moduli obtained from plate load–settlement curves to the basic soil physical properties. Several models with different combinations of the influencing parameters were developed and checked to select the best GP/SA models. The database used for developing the models was established upon a series of plate load tests (PLT) conducted on different soil types at various depths. The validity of the models was tested using parts of the test results that were not included in the analysis. The validation of the models was further verified using several statistical criteria. A traditional GP analysis was performed to benchmark the GP/SA models. The contributions of the parameters affecting E_s, E_u and E_r were analyzed through a sensitivity analysis. The proposed models are able to estimate the soil deformation moduli with an acceptable degree of accuracy. The E_s prediction model has a remarkably better performance than the models developed for predicting E_u and E_r. The simplified formulations for E_s, E_u and E_r provide significantly better results than the GP-based models and empirical models found in the literature.     

A new approach for developing comprehensive agricultural drought index using satellite-derived biophysical parameters and factor analysis method

The accurate assessment of drought and its monitoring is highly depending on the selection of appropriate indices. Despite the availability of countless drought indices, due to variability in environmental properties, a single universally drought index has not been presented yet. In this study, a new approach for developing comprehensive agricultural drought index from satellite-derived biophysical parameters is presented. Therefore, the potential of satellite-derived biophysical parameters for improved understanding of the water status of pistachio (Pistachio vera L.) crop grown in a semiarid area is evaluated. Exploratory factor analysis with principal component extraction method is performed to select the most influential parameters from seven biophysical parameters including surface temperature (T _s), surface albedo (α), leaf area index (LAI), soil heat flux (G _o), soil-adjusted vegetation index (SAVI), normalized difference vegetation index (NDVI), and net radiation (R _n). T _s and G _o were found as the most effective parameters by this method. However, T _s, LAI, α, and SAVI that accounts for 99.6 % of the total variance of seven inputs were selected to model a new biophysical water stress index (BPWSI). The values of BPWSI were stretched independently and compared with the range of actual evapotranspiration estimated through well-known METRIC (mapping evapotranspiration at high resolution with internal calibration) energy balance model. The results showed that BPWSI can be efficiently used for the prediction of the pistachio water status (RMSE of 0.52, 0.31, and 0.48 mm/day on three image dates of April 28, July 17, and August 2, 2010). The study confirmed that crop water status is accounted by several satellite-based biophysical parameters rather than single parameter.     

Computing eddy-current response and current-channeling response of the spheroidal conductor for the separated receiver and transmitter systems

In this article the response of the induced eddy-current in an unlimited conduction spheroidal as well as the response of the current-channeling resulted from the presence of the spheroidal in a weakly conducted medium are derived. The common methods are based on receiving electromagnetic induction response from the homocentric and coaxial receiver and transmitter coils which are exactly over the anomaly. As the spheroidal location is unknown in the practice, it is suggested to measure the electromagnetic induction response in a case that the receiver and the transmitter have an arbitrary situation regarding to the anomaly. In this article, eddy-current response and current-channeling response of the spheroid have been computed in a more general case in which at least one axis of spheroid and the dipole axes of the receiver and transmitter coils are on the same plate; however, none of the coils are laid over the anomaly. Using this method, we can determine the location and the depth of the spheroid through fixing the transmitter’s position and of the receivers’ coil movements.     

Evaluation of public participation in reconstruction of Bam,Iran, after the 2003 earthquake

In the midst of the ever-increasing natural and human-induced disasters, where many of the preparedness and mitigation measures show inefficiencies, there is narrow margin for decision-makers to make mistakes by misallocating budgets, designing infeasible reconstruction plans, and in other terms, making decisions not in line with the public preferences. In particular, public participation in post-disaster measures seems undoubtedly necessary to reduce the possible economic, social, political, and cultural conflicts around the stressful community after a major disaster. This paper aims at evaluating the role of public participation in increasing the reconstruction phase efficiency through a case study of the reconstruction process in Bam, a southeastern Iranian city, after the 2003 earthquake. It is attempted to identify the major motivators of the public participation through a combination of quantitative and qualitative studies. Statistical data are generated through a set of questionnaires being filled by a number of 200 randomly selected survivors. The numerical results were then discussed through the Focus Group technique sessions to determine the main contributors to the public participation. It is later found that the answers are found among the performance of the reconstruction authorities, financial policies, emotional resiliency of the survivors, public information mechanisms, public satisfaction, the pace of reconstruction, and temporary housing policies.     

Forecasting monthly inflow with extreme seasonal variation using the hybrid SARIMA-ANN model

The optimal operation of dam reservoirs can be programmed and managed by predicting the inflow to these structures more accurately. To this end, there are various linear and nonlinear models. However, some hydrological problems like inflow with extreme seasonal variation are not purely linear or nonlinear. To improve the forecasting accuracy of this phenomenon, a linear Seasonal Auto Regressive Integrated Moving Average (SARIMA) model is combined with a nonlinear Artificial Neural Network (ANN) model. This new model is used to predict the monthly inflow to the Jamishan dam reservoir in West Iran. A comparison of the SARIMA and ANN models with the proposed hybrid model’s results is provided accordingly. More specifically, the models’ performance in forecasting base and flood flows is evaluated. The effect of changing the forecasting period length on the models’ accuracy is studied. The results of increasing the number of SARIMA model parameters up to five are investigated to achieve more accurate forecasting. The hybrid model predicts peak flood flows much better than the individual models, but SARIMA outperforms the other models in predicting base flow. The obtained results indicate that the hybrid model reduces the overall forecast error more than the ANN and SARIMA models. The coefficient of determination of the hybrid, ANN and SARIMA models were 0.72, 0.64 and 0.58, and the root mean squared error values were 1.02, 1.16 and 1.27 respectively, during the forecast period. Changing the forecasting length also indicated that these models can be used in the long term without increasing the forecast error.     

Assessment of geomorphological bank evolution of the alluvial threshold rivers based on entropy concept parameters

The complex stream bank profiles in alluvial channels and rivers that are formed after reaching equilibrium has been a popular topic of research for many geomorphologists and river engineers. The entropy theory has recently been successfully applied to this problem. However, the existing methods restrict the further application of the entropy parameter to determine the cross-section slope of the river banks. To solve this limitation, we introduce a novel approach in the extraction of the equation based on the calculation of the entropy parameter (λ) and the transverse slope of the bank profile at threshold channel conditions. The effects of different hydraulic and geometric parameters are evaluated on a variation of the entropy parameter. Sensitivity analysis on the parameters affecting the entropy parameter shows that the most effective parameter on the λ-slope multiplier is the maximum slope of the bank profile and the dimensionless lateral distance of the river banks.     

The effect of traffic on levels,distribution and chemical partitioning of harmful metals in the street dust and surface soil from urban areas of Tehran,Iran

Due to the explosive industrialization and rapid expansion of the population in many parts of the world, heavy metals are released into the environment continuously and pose a great risk on human health. Street dust and surface soil samples from very heavy, heavy, medium and low traffic areas and a natural site in Tehran, Iran, were analyzed for some physicochemical features, total and chemical fractionating of selected metals (Zn, Al, Sr, Pb, Cu, Cr, Cd, Co, Ni and V) to investigate the influence of traffic on their mobility and accumulation in the environment. The pH, electrical conductivity (EC), carbonates and organic carbon contents were similar in soil and dust samples from the areas with same traffic. The traffic increases EC contents in dust/soil matrixes, but has no effect on concentrations of metals in soil samples. Rises in metal levels with traffic were found in dust samples. Moreover, the traffic increases the percentage of both acid-soluble and reducible fractions, which are related to Pb and Zn. The mobilization of Cu, Zn, Pb, Cr in dust samples was easier than in soil. The speciation of metals except Cd is mainly affected by physicochemical features in soil, though total metals affected the speciation in dust samples (except chromium and nickel).     

Empirical modeling of plate load test moduli of soil via gene expression programming

New empirical models were developed to predict the soil deformation moduli using gene expression programming (GEP). The principal soil deformation parameters formulated were secant (E_s) and reloading (E_r) moduli. The proposed models relate E_s and E_r obtained from plate load-settlement curves to the basic soil physical properties. The best GEP models were selected after developing and controlling several models with different combinations of the influencing parameters. The experimental database used for developing the models was established upon a series of plate load tests conducted on different soil types at depths of 1–24 m. To verify the applicability of the derived models, they were employed to estimate the soil moduli of a part of test results that were not included in the analysis. The external validation of the models was further verified using several statistical criteria recommended by researchers. A sensitivity analysis was carried out to determine the contributions of the parameters affecting E_s and E_r. The proposed models give precise estimates of the soil deformation moduli. The E_s prediction model provides considerably better results in comparison with the model developed for E_r. The simplified formulation for E_s significantly outperforms the empirical equations found in the literature. The derived models can reliably be employed for pre-design purposes.