Numerical Modeling of Tropical Cyclone-Induced Storm Surge in the Gulf of Oman Using a Storm Surge–Wave–Tide Coupled Model

Ocean Science Journal - A storm surge is a complex phenomenon in which current, tide, and waves interact with each other. Even if the wind is the main force of driving the surge, waves and tide are...     

Modeling and assessing the effects of land use changes on runoff generation with the CLUE-s and WetSpa models

Theoretical and Applied Climatology - Land use change is an important determinant of hydrological processes and is known to affect hydrological parameters such as runoff volume, flood frequency,...     

The effect of different meteorological parameters on the temporal variations of reference evapotranspiration

Temporal changes of meteorological variables can affect reference evapotranspiration (ET₀). The goal of the present research is to analyze the changes of ET₀ and identify the impact of effective meteorological parameters to the changes of ET₀. For this purpose, daily meteorological data recorded in 30 synoptic stations of Iran during 1960–2014 were used. The annual and seasonal values of ET₀ were calculated by the recorded data. To calculate ET₀, FAO56 Penman–Monteith method (standard method) was used. The annual and seasonal trends of ET₀ and its eight effective parameters were analyzed. Then the contributions of effective parameters changes on ET₀ were determined. To analyze ET₀ trend at annual and seasonal scales, two common methods, Spearman’s Rho and Mann–Kendall tests, were used. The R ² = 0.99 showed that the results of the mentioned methods were similar and on the basis of T-statistic <0.057, their difference was not significant (95% confidence level). Therefore, only one method’s results (Spearman’s Rho) were reported. On the basis of Spearman’s Rho results, the annual and seasonal values of ET₀ had negative trend in most of arid and semi-arid stations while the trend of this parameter was positive in humid and very humid stations. At annual and seasonal scales, decreasing in wind speed (W), temperature (T), sunshine hours (n), minimum temperature (TN), dew point temperature (TD), maximum temperature (TX), saturation vapor pressure deficit (SVPD) and solar radiation (RS) was observed in 58, 54, 39, 43, 56, 65, 65 and 37% studied stations, respectively. In many scales, the results showed that TX and W were the most effective meteorological variables on ET₀ changes and then SVPD was located in second step in arid and semi-arid stations. In humid and very humid stations, W was the first effective parameter at all scales, except autumn.     

Application of different data-driven methods for the prediction of total dissolved solids in the Zarinehroud basin

A total dissolved solid (TDS) is an important indicator for water quality assessment. Since the composition of mineral salts and discharge affects the TDS of water, it is important to understand the relationship of mineral salt composition with TDS. In the present study, four artificial intelligence approaches, namely artificial neural networks (ANNs), two different adaptive-neuro-fuzzy inference system (ANFIS) including ANFIS with grid partition (ANFIS-GP) and ANFIS with subtractive clustering (ANFIS-SC), and gene expression programming (GEP) were applied to forecast TDS in river water over a period of 18 years at seven different sites. Five different GEP, ANFIS and ANN models comprising various combinations of water quality and flow variables from Zarinehroud basin in northwest of Iran were developed to forecast TDS variations. The correlation coefficient (R), root mean square error and mean absolute error statistics were used for evaluating the accuracy of models. Based on the comparisons, it was found that the GEP, ANFIS-GP, ANFIS-SC and ANN models could be employed successfully in forecasting TDS variations. A comparison was made between these artificial intelligence approaches which emphasized the superiority of GEP over the other intelligent models.     

Reconstruction of groundwater levels to impute missing values using singular and multichannel spectrum analysis: application to the Ardabil Plain,Iran

ABSTRACT

Groundwater-level time series often have a substantial number of missing values which should be taken into consideration before using them for further analysis, particularly for numerical groundwater flow modelling applications. This study aims to comprehensively compare two data-driven models, singular spectrum analysis (SSA) and multichannel spectrum analysis (MSSA), to reconstruct groundwater-level time series and impute the missing values for 25 piezometric stations in Ardabil Plain, northwest Iran. The reconstructed groundwater-level time series are assessed against the complete observed groundwater time series, while the imputed values are appraised against the artificially created gap values. The results show that both SSA and MSSA demonstrate a solid competency in imputation and reconstruction of groundwater-level data. However, depending on the spatial correlation between the piezometers, and the most suitable probability distribution function (pdf) fitted to the time series of each piezometer, the performance may vary from piezometer to piezometer.     

Study on infiltration rate based on primary particle size distribution data in arid and semiarid region soils

Soil particle size distribution (PSD) is used to estimate some soil processes, soil moisture characteristics, and infiltration rate (IR). Prediction of infiltration rate from soil texture data requires an accurate characterization of PSD. The objective of this study was to determine more important primary particle diameters that control IR. The experiments were conducted using double-ring method with constant head of 5 cm in 15 different soils and three replications. The range of measured IR for studied soils varied from 1.6 to 30.66 cm h^?1. The results indicated that the primary PSD had a significant influence on IR. In other words, most D _n fractions had significant positive effect on the final IR. Among different fractions, D ₃₀, D ₄₀, and D ₆₀ showed higher relationships with IR than the others. These diameters are attributed to particles with diameter of 0.05, 0.08, and 0.16 mm, respectively. The results also showed that increasing the percent of sand have intensified influence on increasing the final IR. Reversely, clay and silt contents showed negative effects on final IR. Furthermore, the CaCO₃ had a meaningful effect on the IR that showed the importance of lime in arid and semiarid regions. Finally, it is revealed that the role of texture was important, especially in behavior of infiltration, runoff, and production capability.     

Relativistic Models for Strange Stars in Massive Brans–Dicke Gravity

Astronomy Reports - In this paper, we examine the salient features of anisotropic quark stellar model in the background of massive Brans–Dicke gravity. We use the MIT bag model along with...     

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).