Hybrid denoising-jittering data processing approach to enhance sediment load prediction of muddy rivers

Successful modeling of hydro-environmental processes widely relies on quantity and quality of accessible data, and noisy data can affect the modeling performance. On the other hand in training phase of any Artificial Intelligence (AI) based model, each training data set is usually a limited sample of possible patterns of the process and hence, might not show the behavior of whole population. Accordingly, in the present paper, wavelet-based denoising method was used to smooth hydrological time series. Thereafter, small normally distributed noises with the mean of zero and various standard deviations were generated and added to the smooth time series to form different denoised-jittered data sets. Finally, the obtained pre-processed data were imposed into Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) models for daily runoff-sediment modeling of the Minnesota River. To evaluate the modeling performance, the outcomes were compared with results of multi linear regression (MLR) and Auto Regressive Integrated Moving Average (ARIMA) models. The comparison showed that the proposed data processing approach which serves both denoising and jittering techniques could enhance the performance of ANN and ANFIS based runoff-sediment modeling of the case study up to 34% and 25% in the verification phase, respectively.     

Evaluation of ecotourism potential in the northern coastline of the Persian Gulf

This research has identified areas located in the northern coastline of the Persian Gulf in the south of Iran, as strategic and ecological sites, based on tourism potential assessing criteria. To this end coastal limits were identified by satellite imagery in terms of shorelines and the maximum extent of water approach into the land and taking into consideration the characteristics of the nearby coastal villages. The studied region was then compared to similar international criteria and experiences. The original criteria were then divided into three main and four sub criteria. The Kangan region was found to have a potential for tourism industry according to the mentioned criteria. Naiband Gulf with a score of 20 was ranked first followed by Asalouyeh with a score of 18 and finally Taheri and Kangan Ports with scores of 16 and 15, respectively. With a high tourism industry potential in the studied region the necessity of ecotourism quality enhancement and environmental management planning for the northern shoreline of the Persian Gulf becomes of vital importance.     

Water flux and sediment transport within a forested landscape: the role of connectivity,subsurface flow,and slope length scale on transport mechanism

The connectivity and upscaling of overland runoff and sediment transport are important issues in hillslope hydrology to identify water flux and sediment transport within landscape. These processes are highly variable in time and space with regard to their interactions with vegetation and soil surface conditions. The generation of overland runoff and its spatial connectivity were examined along a slope to determine the variations in the transport mechanism of runoff and soil particles by rain splash and overland runoff. Field experiments were conducted by erosion plots on a steep hillslope at lengths of 5, 10, and 15 m. The overland runoff connectivity and flow transport distance decreased with the slope length, while spatial variability of infiltration increased significantly with the slope length. Observation of subsurface flow revealed that surface soil and litter layer could have important role in water transport. However, the surface soil water content and water flux transport along the slope was highly variable for different storm events; the variability was related to the complexity of the system, mainly by way of the initial wetness conditions and infiltration characteristics. Only net rain‐splashed soil was measurable, but examination of the water flux, overland runoff and sediment transport connectivity, characteristics of sheetwash, and the variability in spatial infiltration indicated an increase in the contribution of the rain splash transport mechanism along the slope. Copyright © 2013 John Wiley & Sons, Ltd.     

Geotechnical Characterization of Compost Based Biocover Materials

Landfills are one of the major sources of methane (CH₄) emission which is a very potent greenhouse gas. The use of a natural process for microbial CH₄ oxidation through biocovers provides a source reduction of CH₄ emission. Previous studies have mostly focused on biochemical properties, and limited research has been conducted with regards to the geotechnical characterization of compost based biocovers. This paper presents the results of a comprehensive laboratory investigation on pure compost and compost–sand mixtures (with mix ratio of 3:1, 1:1, and 1:3 w/w) to determine the compaction, shear strength, compressibility, and hydraulic and thermal conductivity properties of compost based biocovers. Direct shear and ring shear tests have shown that the cohesion (c) and friction angle (?) are in the range of 2.1–19.7 kPa and 44.1°–54.7°, respectively. Based on the results of one dimensional consolidation tests, the coefficient of consolidation (C_v) values are in the range of 1.71–0.63 m²/year, which is a function of the moisture and organic contents of the samples. The lowest hydraulic conductivity ranges from 6.09 × 10^?8 to 1.78 × 10^?7 cm/s which occur at optimum moisture contents. Thermal conductivity is measured under various porosities and moisture contents. By increasing the dry density and sand content of the mixtures, thermal conductivity increases. The results presented in this paper will contribute to a better understanding of the geotechnical behaviour of compost based biocover, and thus to a more cost-effective design of biocovers.     

Exploring the sample size and replications scenarios effect on spatial prediction of flood,using MARS and MaxEnt methods case study: saliantape catchment,Golestan, Iran

Flood has always been a destructive natural hazard during the recent years. Hence, this research aimed to predict the potentiality and probability of flood phenomenon by using the two well-known models, i.e., the MARS algorithm (multivariate adaptive regression splines) and MaxEnt (maximum entropy) method in the Saliantapeh catchment, Golestan province, Iran, covering 4515.47 km². First, documentary sources report and field surveys were used to provide a flood database map. Then, to prepare the flood spatial potentiality map (FSPM), we select sixteen influential variables as predictors. Furthermore, the relative contributions of predicting factors are estimated using the MaxEnt method. For the analysis of data sensitivity and the uncertainty of the proposed models, different scenarios including the sample size (50%/50%, 80%/20%, and 70%/30%, respectively, for training and validation), and the number of replications (5, 10, and 20) were used. Along with the area under the ROC curve (AUC), the highest accuracy for both models corresponds to the first scenario of sample size (80/20%). Contrarywise, it can be concluded that for this scenario, the MARS technique indicated higher predictive skill (AUC?=?98.51%). Regarding the second scenario, which is corresponding to the replicate, the MARS model with 20 replications still has the highest accuracy (94.70%) compared to the other scenarios and the MaxEnt model. The findings of robustness demonstrated that the scenarios with the greatest AUC value have the highest robustness. This work demonstrates that the utilization of the best accurate model with high certainty along with FSPM may be useful to identify and manage the areas that are most susceptible to flood.

     

Evaluation of the Instability Risk of the Dam Slopes Simulated with Monte Carlo method (Case Study: Alborz Dam)

Embankment dams are one of the most important geotechnical structures that their failures can lead to disastrous damages. One of the main causes of dam failure is its slope instability. Slope Stability analysis has traditionally been performed using the deterministic approaches. These approaches show the safety of slope only with factor of safety that this factor cannot take into account the uncertainty in soil parameters. Hence, to investigate the impact of uncertainties in soil parameters on slope stability, probabilistic analysis by Monte Carlo Simulation (MCS) method was used in this research. MCS method is a computational algorithm that uses random sampling to compute the results. This method studies the probability of slope failure using the distribution function of soil parameters. Stability analysis of upstream and downstream slopes of Alborz dam in all different design modes was done in both static and quasi-static condition. Probability of failure and reliability index were investigated for critical failure surfaces. Based on the reliability index obtained in different conditions, it can be said that the downstream and upstream slope of the Alborz dam is stable. The results show that although the factor of safety for upstream slope in the state of earthquake loading was enough, but the results derived from probabilistic analysis indicate that the factor of safety is not adequate. Also the upstream slope of the Alborz dam is unstable under high and uncontrolled explosions conditions in steady seepage from different levels under quasi-static terms.

     

Development of analytical seismic fragility functions for the common buildings in Iran

Bulletin of Earthquake Engineering - One of the main components for developing regional seismic risk models is the fragility functions of common building types. Due to the differences between the...     

Seismic assessment of nature-inspired hexagrid lateral load-resisting system

This paper provides a general perspective of the seismic performance of a nature-inspired, honey-comb grid structural system, known as a hexagrid, under near-field ground motions. Seismic performance of this skeleton is then compared to that of a bundled-tube, as a conventional and efficient load-resisting system in order to provide a better perception of the seismic behavior of a hexagrid skeleton. Two 20-story buildings with bundled-tube and hexagrid skeleton were studied. Nonlinear behavior of the structures was investigated through 3-D finite element computer models and nonlinear time history analyses by subjecting the models to seven three-component records of scaled near-field ground motions. Distribution of peak inter story drift and corner beam-column joint rotations were calculated and compared. Results indicated that by replacing the exterior columns of the bundled-tube system with inclined beam-column elements of nature-inspired hexagons, lateral stiffness of the building increased and it would tolerate less deformations before global dynamic instability is reached. The presence of inclined columns in the hexagrid skeleton helped to concentrate local nonlinearities in ring beams rather than exterior columns.     

Effects of Roof-Edge Roughness on Air Temperature and Pollutant Concentration in Urban Canyons

The influence of roof-edge roughness elements on airflow, heat transfer, and street-level pollutant transport inside and above a two-dimensional urban canyon is analyzed using an urban energy balance model coupled to a large-eddy simulation model. Simulations are performed for cold (early morning) and hot (mid afternoon) periods during the hottest month of the year (August) for the climate of Abu Dhabi, United Arab Emirates. The analysis suggests that early in the morning, and when the tallest roughness elements are implemented, the temperature above the street level increases on average by 0.5 K, while the pollutant concentration decreases by 2% of the street-level concentration. For the same conditions in mid afternoon, the temperature decreases conservatively by 1 K, while the pollutant concentration increases by 7% of the street-level concentration. As a passive or active architectural solution, the roof roughness element shows promise for improving thermal comfort and air quality in the canyon for specific times, but this should be further verified experimentally. The results also warrant a closer look at the effects of mid-range roughness elements in the urban morphology on atmospheric dynamics so as to improve parametrizations in mesoscale modelling.     

Geochemistry and speciation of metals in sediments of the Maharlu Saline Lake,Shiraz, SW Iran

In this study, the total concentration and speciation of trace elements (As, Cr, Cu, Cd, Pb, Zn, and Ni), in sediments of the Maharlu saline Lake, SW Iran are investigated. Comparison with sediment quality guidelines, calculation of the enrichment factors, and trace metal profiles in the Khoshk River inflow point indicate that Maharlu Lake is in the threat of contamination, especially with respect to Ni and Cd. Sequential extraction analysis reveals that elemental speciation in this lake is strongly affected by oxidizing condition of the lake water. The studied elements (except Cr) are mainly associated with oxide phases, as a result of prevailing oxidizing conditions of the lake and also probably due to the source of elements. The ratio of metals in mobile fractions to sum of fractions in lake sediments is very low. However, metal ratios (except for Cr) in mobile fractions are much higher in surface sediments, indicating the impact of anthropogenic loading of trace metals in the recent years.