GMDH-GEP to predict free span expansion rates below pipelines under waves

ABSTRACT

In this research, group method of data handling (GMDH) as a one of the self-organized approaches is utilized to predict three-dimensional free span expansion rates around pipeline due to waves. The GMDH network is developed using gene-expression programming (GEP) algorithm. In this way, GEP was performed in each neuron of GMDH instead of polynomial quadratic neuron. Effective parameters on the three-dimensional scour rates include sediment size, pipeline geometry, and wave characteristics upstream of pipeline. Four-dimensionless parameters are considered as input variables by means of dimensional analysis technique. Furthermore, scour rates along the pipeline, vertical scour rate, and additionally scour rates in the left and right of pipeline are determined as output parameters. Results of the proposed GMDH-GEP models for the training stages and testing ones are evaluated using various statistical indices. Performances of the GMDH-GEP models are compared with artificial neural network (ANN), GEP, GMDH, and traditional equations-based regression models. Moreover, sensitivity analysis and parametric study are conducted to perceive influences of different input parameters on the three-dimensional scour rates.     

Orebody Modelling for Exploration: The Western Mineralisation, Broken Hill, NSW

The Western Mineralisation in the Broken Hill deposit was studied to identify the zonation sequence of lithogeochemical haloes along and across the strike of the orebody. Samples used are from 77 drill holes and the samples were assayed for Pb, Zn, Fe, S, Cu, Ag, Cd, Sb, Bi and As. Variogram analyses were calculated for all the elements and kriging was used to construct the 3D block model. Analysis of cross sections along and across the strike of the orebody shows that Bi and Sb form broader halos around sulphide masses and this suggests that they are pathfinder elements for the Pb and Zn elements of this orebody. The threshold concentrations (minimum anomaly) of the 10 elements were determined using the concentration-area analysis. On east?Cwest vertical cross sections, the values of linear productivity, variability gradient and zonality index were calculated for each element. Based on the maximum zonality index of each element, the sequence of geochemical zonation pattern was determined from top to bottom of the orebody. The result shows that S, Pb, Zn and Cd tend to concentrate in the upper part of the mineralisation whereas Ag, Cu, Bi and As have a tendency to concentrate in the lower part of the mineralised rocks. Also, an empirical product ratio index was developed based on the position of the elements in the zonation sequence. The methods and results of this research are applicable to exploration of similar Zn and Pb sulphide ore deposits.     

Near surface lithology and spatial variation of arsenic in the shallow groundwater: southeastern Bangladesh

This study investigated the relationship between near-surface lithology and the spatial variability of As concentrations using sediment grain-size analysis and electromagnetic induction survey in the southeast Bangladesh. It has been observed that the aquifers overlain by finer sediments have higher concentrations of As in groundwater, whereas As concentrations are remarkably low in aquifers having permeable sandy materials or thinner silt/clay layer at the surface. The near-surface lithology acts as a controlling factor for spatial distributions of groundwater As within the very shallow depths (<15 m). Shallow alluvial aquifers can provide low-As drinking water in many areas of the country when tube wells are properly installed after investigation of the overlying near-surface sediment attributes and hydraulic properties.     

Hydrochemical characteristics and seasonal variations in groundwater quality of an alluvial aquifer in parts of Central Ganga Plain,Western Uttar Pradesh,India

The present study was undertaken to assess major ion chemistry of groundwater in parts of the Central Ganga Plain and observe seasonal variations in its chemical quality. Systematic sampling was carried out during November 2005 and June 2006. The major ion chemistry of groundwater shows large variations, so much so that at times the meteoric signature seems to be completely obliterated. In many samples the concentrations of SO₄, NO₃ and F are above the permissible limit for human consumption. The graphical treatment of major ion chemistry helps in identifying four types of groundwater. All possible ionic species such as NaCl, KCl, NaHCO₃, NaSO₄, KNO₃, NaNO₃, CaHCO₃, MgHCO₃, MgSO₄ are likely to occur in groundwater system. The observed chemical variations may be attributed to sediment water interaction, ion exchange, dissolution mechanisms and anthropogenic influences such as application of fertilizers and effluents from sugar factories and paper mills. A general increase in TDS is observed in samples during June 2006. The increase in salinity is attributed to evaporation from water table, irrigation return flows, anthropogenic activities and below average rainfall in 2005 and 2006. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Flooding and its relationship with land cover change,population growth,and road density

Bangladesh experiences frequent hydro-climatic disasters such as flooding.These disasters are believed to be associated with land use changes and climate variability.However,identifying the factors that lead to flooding is challenging.This study mapped flood susceptibility in the northeast region of Bangladesh using Bayesian regularization back propagation(BRBP)neural network,classification and regression trees(CART),a statistical model(STM)using the evidence belief function(EBF),and their ensemble models(EMs)for three time periods(2000,2014,and 2017).The accuracy of machine learning algorithms(MLAs),STM,and EMs were assessed by considering the area under the curve-receiver operating char-acteristic(AUC-ROC).Evaluation of the accuracy levels of the aforementioned algorithms revealed that EM4(BRBP-CART-EBF)outperformed(AUC＞90％)standalone and other ensemble models for the three time periods analyzed.Furthermore,this study investigated the relationships among land cover change(LCC),population growth(PG),road density(RD),and relative change of flooding(RCF)areas for the per-iod between 2000 and 2017.The results showed that areas with very high susceptibility to flooding increased by 19.72％between 2000 and 2017,while the PG rate increased by 51.68％over the same period.The Pearson correlation coefficient for RCF and RD was calculated to be 0.496.These findings highlight the significant association between floods and causative factors.The study findings could be valuable to policymakers and resource managers as they can lead to improvements in flood management and reduction in flood damage and risks.     

Potential of <Emphasis Type="Italic">Micranthemum umbrosum</Emphasis> for phytofiltration of organic arsenic species from oxic water environment

Arsenic (As) is a toxic and carcinogenic metalloid that causes various hazards to human health. Phytofiltration is a more eco-friendly and green approach than chemoremediation, or other traditional technologies, for removing As from aquatic environments. Recently, Micranthemum umbrosum was shown as a promising candidate for phytofiltration of inorganic As species. This work examines the potential application of M. umbrosum to phytofiltration of organic As species, such as monomethylarsonic acid (MMAA, CH₅AsO₃) and dimethylarsinic acid (DMAA, C₂H₇AsO₂), from oxic water environments. M. umbrosum plants were grown in two test concentrations of MMAA and DMAA, or a control, in a hydroponic experiment. After seven days, leaves accumulated 90 ± 3.2 and 48 ± 1.6 µg As g^?1 (oven dry basis) from 1 µg As mL^?1 of water added from MMAA and DMAA, respectively. Bioconcentration factor values and translocation factor values were always greater than 1.0, indicating that M. umbrosum was a good As accumulator and that leaves accumulated significantly higher amounts of As than stems and roots. Analysis of macro- and micronutrient data showed that M. umbrosum had higher resistance to organic As treatments than the control. These results confirm the potential application of M. umbrosum for phytofiltration of organic As from contaminated oxic water environments.     

Assessment of discontinuous rock slope stability with block theory and numerical modeling: a case study for the South Pars Gas Complex,Assalouyeh, Iran

In this study, a geotechnical model has been used to analyze the stability of a discontinuous rock slope. The main idea behind block theory is that it disregards many different combinations of discontinuities and directly identifies and considers critical rock blocks known as “key blocks”. The rock slope used as a case study herein is situated in the sixth phase of the gas flare site of the South Pars Gas Complex, Assalouyeh, Iran. In order to analyze the stability of discontinuous rock slopes, geotechnical modeling which was divided into geometrical sub-modeling and mechanical sub-modeling has been utilized. This model has been established upon the KGM (key-group method) algorithm which was based on the limit equilibrium method and block theory and prepared and coded by the Mathematica software. According to the results of the stability analysis, the analyzed slope was determined to be in the category of “needs attention,” and the security level, calculated through the FORM (first-order reliability method) analysis, was estimated to be 1.16. In order to verify the model, the results obtained from the model were compared with those of the UDEC software, which is a numerical method based on distinct components. As a conclusion, it was determined that the results of the model agreed well with those of the numerical method.     

Integration of inland and coastal storms for flood hazard assessment using a distributed hydrologic model

Due to increasing flood severities and frequencies, studies on coastal vulnerability assessment are of increasing concern. Evaluation of flood inundation depth and extent is the first issue in flood vulnerability analysis. This study has proposed a practical framework for reliable coastal floodplain delineation considering both inland and coastal flooding. New York City (NYC) has been considered as the case study because of its vulnerability to storm surge-induced hazards. For floodplain delineation, a distributed hydrologic model is used. In the proposed method, the severities of combined inland and coastal floods for different recurrence intervals are determined. Through analyzing past storms in the study region, a referenced (base) configuration of rainfall and storm surge is selected to be used for defining flood scenarios with different return periods. The inundated areas are determined under different flooding scenarios. The inundation maps of 2012 superstorm Sandy in NYC is simulated and compared with the FEMA revised maps which shows a close agreement. This methodology could be of significant value to the planners and engineers working on the preparedness of coastal urban communities against storms by providing a platform for updating inundation maps as new events are observed and new information becomes available.     

Groundwater quality assessment using integrated geochemical methods,multivariate statistical analysis,and geostatistical technique in shallow coastal aquifer of Terengganu,Malaysia

Extensive agricultural, residential, and industrial activities have increased demand for water supplies, which can lead to groundwater quality degradation. The integration of geochemical methods, multivariate statistical analysis, and geostatistical approaches were carried out on 169 groundwater samples to elucidate the regional factors and processes that influencing the geochemical composition of groundwater in coastal shallow aquifer of Terengganu, Malaysia. Hydrochemical modelling revealed that the abundance of Ca and Mg was contributed by carbonate and silicate weathering while higher HCO₃ and Cl were resulted from reverse ion exchange reaction. Therefore, the dominant hydrogeochemical facies of groundwater was Ca-Mg-HCO₃-Cl type. The influence of salinization resulting from seawater mixing to the groundwater was corroborated by Cl/HCO₃ ratio, which affected around 50.9% of the groundwater samples slightly or moderately. Spatial mapping using ordinary kriging found that the threat of sea water intrusion is more prominent in the major river confluence especially around Terengganu and Marang River in the northeast and Dungun and Kemaman River confluence in southeast of study area. Moreover, factor analyses concluded that salinization, anthropogenic activities, reverse ion exchange, weathering processes, agricultural impact, and seasonal variations were the factors that regulate 63% of the major ion chemistry in study area. Finally, these findings showed the importance of understanding the hydrochemical characteristics for effective utilization, aquifer protection, and prediction of changes to minimize the effects of salinization and reduce human pollution such as agriculture and urbanization. It is essential steps in order to safeguard the utilization of groundwater resources for future generations.     

Using of gene expression programming and climatic data for forecasting flow discharge by considering trend,normality, and stationarity analysis

In this research, the main hydrological characteristics (such as trend, stationarity, and normalization of hydrological data) of the Kasilian watershed are considered from 1970 to 2009. For forecasting of discharge, gene expression programming (GEP) method is applied. Normality and stationarity of time series are necessary for application of GEP method. For this purpose, third edition of Mann-Kendall trend test and skewness test are used for detection of trend and normalization of data, respectively. Also, five methods are applied for detection of stationarity of data. Modified Mann-Kendall trend test and Theil and Sen’s median slope method illustrate that annual and monthly precipitation data have slight decreasing trend, annual and monthly discharge data have insignificant decreasing trend, and annual and monthly temperature data have an increasing trend. Skewness test illustrates that annual, monthly, and daily discharge and precipitation data are not normal. By using logarithm function, skewness is minimized and symmetry of data is improved. After normalization of time series by logarithm function, five methods are applied for testing of stationarity of time series. These methods show that different normalized time series are stationarity and stationarity of time series is improved by elimination of periodic properties of data. For forecasting of daily discharge by GEP method, 85% of data are used for training and 15% of data are used for testing. By using data of 3 days ago, the GEP has the best efficiency. Coefficient of correlation (CC), root mean square error (RMSE), mean absolute error (MAE), and mean absolute relative error (MARE) are 0.9, 0.495 lit/s, 0.288 lit/s, and 0.053, respectively.