Modelling of piping collapses and gully headcut landforms:Evaluating topographic variables from different types of DEM

The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model(DEM)data.The unique terrain characteristics of a particular landscape are derived from DEM,which are responsible for initiation and development of ephemeral gullies.As the topographic features of an area significantly influences on the erosive power of the water flow,it is an important task the extraction of terrain features from DEM to properly research gully erosion.Alongside,topography is highly correlated with other geo-environmental factors i.e.geology,climate,soil types,vegetation density and floristic composition,runoff generation,which ultimately influences on gully occurrences.Therefore,terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility(GES)mapping.In this study,remote sensing-Geographic information system(GIS)tech-niques coupled with machine learning(ML)methods has been used for GES mapping in the parts of Semnan province,Iran.Current research focuses on the comparison of predicted GES result by using three types of DEM i.e.Advanced Land Observation satellite(ALOS),ALOS World 3D-30 m(AW3D30)and Advanced Space borne Thermal Emission and Reflection Radiometer(ASTER)in different resolutions.For further progress of our research work,here we have used thirteen suitable geo-environmental gully erosion conditioning factors(GECFs)based on the multi-collinearity analysis.ML methods of conditional inference forests(Cforest),Cubist model and Elastic net model have been chosen for modelling GES accordingly.Variable's importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods(Cforest=21.4,Cubist=19.65 and Elastic net=17.08),followed by lithology and slope.Validation of the model's result was performed through area under curve(AUC)and other statistical indices.The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs(AUC value of Cforest in ALOS DEM is 0.994,AW3D30 DEM is 0.989 and ASTER DEM is 0.982)used in this study,followed by elastic net and cubist model.The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.     

Metal concentrations in selected tissues and main prey species of the annulated sea snake (Hydrophis cyanocinctus) in the Hara Protected Area, northeastern coast of the Persian Gulf, Iran

This study is the first detailed ecotoxicological study of the annulated sea snake, Hydrophis cyanocinctus. Concentrations of lead, cadmium, nickel and vanadium were evaluated in muscle, liver, kidney, skin and blood of the annulated sea snake (H. cyanocinctus) and in the whole bodies of its main prey species (Periophthalmus waltoni and Boleophthalmus dussumieri) in the Hara Protected Area, the Persian Gulf. The mean concentrations of lead and vanadium were highest in the kidney, which identified the kidney as a target organ for metals in sea snakes as it is in other reptilian groups. Mean concentrations of cadmium and nickel were highest in the liver and skin, respectively. Mean cadmium concentrations were significantly higher in the liver compared to prey species, which indicated that prey items may be a source of cadmium for the annulated sea snake in the study area. Data presented here may be considered as a baseline for further ecotoxicological studies in sea snakes.     

Phenolic endocrine disrupting chemicals (EDCs) in Anzali Wetland, Iran: elevated concentrations of 4-nonylphenol, octhylphenol and bisphenol A

We have studied the distribution and value of phenolic endocrine disrupting chemicals (EDCs) in surface sediment samples taken from Anzali Wetland, Iran. These samples were collected from 22 stations during the time span of June-May 2010. In each of the sampling stations, we detected 4-nonylphenol (4-NP), octylphenol (OP), and bisphenol A (BPA) with maximal concentrations of 29, 4.3, and 7 μg g(-1) dry weight (dw), respectively. High levels of alkylphenols (APs) and BPA were also found near urban areas. Furthermore there were no significant differences between those stations in terms of the detected levels. One of the important factors in controlling the fate of these compounds in the aquatic environment appeared to be Total Organic Carbon (TOC). Hierarchical cluster analysis showed differences in the biomarker characteristics of EDCs and TOC between the stations. Our findings indicate that EDCs are ubiquitous in sediments from northeast Wetlands of Iran, contaminating the aquatic habitats in this area.     

Inversion of surface gravity data for 3-D density modeling of geologic structures using total variation regularization

We develop an inversion procedure using the total variation (TV) regularization method as a stabilizing function to invert surface gravity data to retrieve 3-D density models of geologic structures with sharp boundaries. The developed inversion procedure combines several effective algorithms to solve the TV regularized problem. First, a matrix form of the gradient vector is designed using the Kronecker product to numerically approximate the 3-D TV function. The piecewise polynomial truncated singular value decomposition (PP-TSVD) algorithm is then used to solve the TV regularized inverse problem. To obtain a density model with depth resolution, we use a sensitivity-based depth weighting function. Finally, we apply the Genetic Algorithm (GA) to select the best combination of the PP-TSVD algorithm and the depth weighting function parameters. 3-D simulations conducted with synthetic data show that this approach produces sub-surface images in which the structures are well separated in terms of sharp boundaries, without the need of a priori detailed density model. The method applied to a real dataset from a micro-gravimetry survey of Gotvand Dam, southwestern Iran, clearly delineates subsurface cavities starting from a depth of 40 m within the area of the dam reservoir.     

Flood hazard mapping using synthesis hydraulic and geomorphic properties at watershed scale

The occurrence of natural phenomena such as floods has caused serious consequences for human societies. The simulation of flood hazard maps and its depth in a river is one of the most complex processes in hydrology. In fact both geomorphological and hydraulic procedures for deriving the flood hazard maps and depth are imperfect at watershed scale. In this study, a combination of both procedures, using a probabilistic approach is used. Flood inundation maps for 2-, 10-, 25-,50- and 100-return period floods using flood routine within HEC-RAS in combination of Arc-GIS and topographic wetness index (TWI) map were produced. TWI threshold was identified using a maximum likelihood method in order to produce flood prone areas and calibrated over the reach of Zirab City. The correlation between TWI threshold and the flood depth was carried out and simple linear regression developed for various return periods. The resulting regression model is used in order to create flood hazard maps with various return periods at watershed scale.     

Quantitative analysis of earthquake fatalities: case of Iran

Earthquakes in Iran are major and chronic disasters, but there is a seemingly downward trend in the number of lives lost from earthquake disasters in the past five decades. This paper particularly examines whether factors such as urbanization, literacy rate, wealth, and retrofitting measures have contributed to the declining trend of fatalities over past decades. Data records of 1960–2010 have been used to demonstrate the fatalities trend and a shorter series of 1990–2010 has been used to carry out a statistical analysis due to limited availability of information on retrofitting practices in the country. Regression models run in two stages. The first stage consists of normalized fatalities of Iran’s earthquakes, regressed on urbanization, wealth, and retrofitting. The second stage involves the measure of retrofit as the dependent variable regressed over urbanization and/or wealth as explanatory variables. The resulted regression models clearly explain the importance of retrofitting measure in saving lives in earthquakes disasters, as well as providing economic advantages and robust environment to the population. The study provides significant guidance for public policy. Undoubtedly, retrofitting, started in the country from 1990, has decreased the number of deaths; nonetheless, the measure is found to be mostly enforced in the cities and not in rural areas. Decision makers can use the results of this study to prioritize retrofit in rural areas, more than ever, and as much as possible.     

Numerical evaluation of liquefaction-induced damages in composite breakwaters and its application for performance-based improvement design

Breakwaters provide a calm sea basin for ships and protect harbor facilities by reflecting wave energy toward the open sea area. Their performance under environmental loadings is the main concern for coastal engineers. Liquefaction susceptibility of loose sediments of seabed threatens performance of these structures. The article investigates soil liquefaction effects on the seismic performance of Iran liquefied natural gas (LNG) composite breakwater. Performance-based design method, considering both grade of the breakwater and acceptable level of damages, was selected as design philosophy. Liquefaction-induced damages to the breakwater were determined by numerical analysis. Since the obtained level of deformations did not meet allowable damages, soil improvement against liquefaction was considered. Different improvement patterns were proposed based on distribution of pore pressure ratio (r_u) beneath the breakwater to control its seismic performance. This investigation revealed that the most important area for soil improvement is located near the toes of breakwater to control the slope instability and performance of the breakwater.     

Predicting flow liquefaction,a constitutive model approach

In this paper, flow liquefaction criterion for contractive loose sands is analytically extracted based on the fundamental definition of flow liquefaction. In order to obtain the closed form of this criterion, Dafalias–Manzari constitutive model is employed; so the stress ratio at the onset of flow liquefaction is presented as a function of model parameters, state parameter and void ratio. Flow liquefaction line, as a graphical form of suggested criterion in stress space, shows that the peak points of undrained stress paths with same void ratios are not necessarily in a straight line. In order to validate the reliability of proposed flow liquefaction line to predict the onset of instability, it has been compared with the results of experimental tests performed on Toyoura, Ottawa and Leighton Buzzard sands. The verification results show that the present criterion can satisfactorily predict the onset of flow liquefaction in monotonic and cyclic undrained tests of saturated sands as well as the structural collapse in constant deviatoric stress tests of loose dry sands.