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.
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.
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. 相似文献
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. 相似文献
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. 相似文献
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 (Cv) 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. 相似文献
The Taknar Zone is located at the northern margin of the eastern Iranian continental microplate, and it is host to the Taknar massive sulfide deposit. This study was conducted to find new exploration targets. We used multiple data sources (e.g., litho-geochemical and magnetic surveys) to produce more effective predictive maps. Principal component analysis and hierarchical cluster analysis methods were used to organize the new information into favorability maps and to determine multi-element correlations. We then employed fuzzy logic modeling to create favorability maps from geochemical and magnetic data. A concentration–area multifractal method was used to evaluate the final integrated favorability map for massive sulfide exploration. Our new map identifies previously unexploited sites in the eastern part of the study area, near the boundary of the Taknar formation, with intrusive and subvolcanic rocks, with potential for mineral exploration. The newly defined targets are attractive because old mined ore bodies are also identified in the favorability map. 相似文献
Masjed-Daghi is located in Julfa sheet (1:100,000 series) in the northwest of Iran. The area consists of a very likely gold mineralization bearing epithermal mineralization which appears to be associated with a porphyry Cu–Mo system at deeper levels. Ninety-three soil samples were collected and analyzed for 13 elements (Au, Mo, Cu, Pb, Sn, Ag, Zn, Cr, Mn, Ba, Be, Ni, Co) by using emission spectrometry and atomic absorption spectrophotometry. The data were processed and interpreted using univariate and multivariate statistical analyses. The distribution of the majority of variables is slightly to moderately positively skewed which can be interpreted by log-normal model. Only Ni, Be, and Mn show normal distribution. Based on cluster analysis, the variables can be classified into two main groups. The first group consists of the main ore forming elements such as Au, Ag, and Ba which belong to epithermal system and Mo, Sn, and Cu which have more affiliation to porphyry mineralization. The principal component analysis extracted three factors. These factors calculated using varimax rotated R-mode factor loading matrix account for more than 65 % of the total variance. The first factor represents the main constituents of the epithermal system (Au, Ag, Ba) and its geochemical halo at the northeast of the study area. The second factor represents the main constituents of the porphyry system (Cu, Mo, Sn) and its geochemical halo in the western part of the study area which is overlapped with the volcanic rocks affected by local intrusions with higher alteration overprint. The third factor, however with less significance, represents Pb and Zn which are not the main ore constituents but can be considered as pathfinder elements. The results have been used to locate hidden orebodies using presented factor score mapping. 相似文献
