Precipitation pattern modeling using cross-station perception: regional investigation     

Sadeq Oleiwi Sulaiman  Jalal Shiri  Hamed Shiralizadeh  Ozgur Kisi  Zaher Mundher Yaseen 《Environmental Earth Sciences》2018,77(19):709

Establishing robust models for predicting precipitation processes can yield a significant aspect for many applications in water resource engineering and environmental prospective. In particular, understanding precipitation phenomena is crucial for managing the effects of flooding in watersheds. In this research, a regional precipitation pattern modeling was undertaken using three intelligent predictive models incorporating artificial neural network (ANN), support vector machine (SVM) and random forest (RF) methods. The modeling was carried out using monthly time scale precipitation information in a semi-arid environment located in Iraq. Twenty weather stations covering the entire region were used to construct the predictive models. At the initial stage, the region was divided into three climatic districts based on documented research. Initially, modeling was carried out for each district using historical information from regionally distributed meteorological stations for calibration. Subsequently, cross-station modeling was undertaken for each district using precipitation data from other districts. The study demonstrated that cross-station modeling was an effective means of predicting the spatial distribution of precipitation in watersheds with limited meteorological data.  相似文献   

Health risk assessments due to nitrate levels in drinking water in villages of Azadshahr,northeastern Iran     

Mehdi Qasemi  Mansoureh Farhang  Hamed Biglari  Mojtaba Afsharnia  Afsaneh Ojrati  Fatemeh Khani  Mohammad Samiee  Ahmad Zarei 《Environmental Earth Sciences》2018,77(23):782

Groundwater is the main water source used for drinking and cooking purposes globally. Nitrate level in most groundwater resources in arid and semi-arid areas has increased in the past several decades as a result of human activities and natural processes. This may exert a great impact on human health. To learn the contamination circumstances of groundwater nitrate in villages of Azadshahr, Iran and assess its probable risk to the health of adults, children and infants, fifty-eight groundwater samples were collected from wells and springs in 2018. Nitrate concentrations had a wide spatial variability in wells and springs of the studied villages, with values going from 1 up to 51 mg/L. Exceedances of the EPA standard value were limited to two village springs (villages Nili and Narab, with nitrate level of 51 and 46 mg/L, respectively). The hazard quotients (HQ) values for 41% of children and infants were above the safety level (i.e., HQ?>?1), suggesting that groundwater nitrate would have significant health effects on these age groups. Therefore, appropriate control measures and sanitation improvement programs should be put in place to protect the health of the residents in the contaminated villages.  相似文献   

Prediction of river flow using hybrid neuro-fuzzy models     

Armin Azad  Saeed Farzin  Hamed Kashi  Hadi Sanikhani  Hojat Karami  Ozgur Kisi 《Arabian Journal of Geosciences》2018,11(22):718

The complex nature of hydrological phenomena, like rainfall and river flow, causes some limitations for some admired soft computing models in order to predict the phenomenon. Evolutionary algorithms (EA) are novel methods that used to cover the weaknesses of the classic training algorithms, such as trapping in local optima, poor performance in networks with large parameters, over-fitting, and etc. In this study, some evolutionary algorithms, including genetic algorithm (GA), ant colony optimization for continuous domain (ACO_R), and particle swarm optimization (PSO), have been used to train adaptive neuro-fuzzy inference system (ANFIS) in order to predict river flow. For this purpose, classic and hybrid ANFIS models were trained using river flow data obtained from upstream stations to predict 1-, 3-, 5-, and 7-day ahead river flow of downstream station. The best inputs were selected using correlation coefficient and a sensitivity analysis test (cosine amplitude). The results showed that PSO improved the performance of classic ANFIS in all the periods such that the averages of coefficient of determination, R², root mean square error, RMSE (m³/s), mean absolute relative error, MARE, and Nash-Sutcliffe efficiency coefficient (NSE) were improved up to 0.19, 0.30, 43.8, and 0.13%, respectively. Classic ANFIS was only capable to predict river flow in 1-day ahead while EA improved this ability to 5-day ahead. Cosine amplitude method was recognized as an appropriate sensitivity analysis method in order to select the best inputs.  相似文献   

Peri-Gondwana Late Early–Middle Cambrian trilobites from the Kuhbanan Formation in Dahu section,Kerman Province,Iran     

Hamed?AmeriEmail author 《Arabian Journal of Geosciences》2015,8(3):1467-1478

Outcropped of the Kuhbanan Formation at Dahu, near Zarand, about 63 km north of Kerman, Iran contains peri-Gondwana trilobites. In this study, 185 trilobite samples including six species and genera were identified and described from Dahu section. This trilobite’s assemblage including Redlichia noetlingi, Redlichia sp., Kermanella kuhbananensis, Kermanella lata lata, Kermanella lata minuta, Iranoleesia pisiformis, and Iranaspis sp. based on occurrence of the trilobite fauna a late Early to Middle Cambrian (Series 2–3) is suggested for this strata. These trilobite fauna help confirm conclusions from recent geological studies that place the Kerman Basin of Iran during the Cambrian.  相似文献   

Integration of cadastral survey data into building information models     

Behnam Atazadeh  Leila Halalkhor Mirkalaei  Hamed Olfat  Abbas Rajabifard  Davood Shojaei 《地球空间信息科学学报》2021,24(3):387-402

Cadastral surveying plays an important role in defining legal boundaries of land and property. The current practice for recording cadastral survey data mainly relies on 2D digital or analog documents. This practice is efficient for simple land parcels but can be challenged in complex building developments. To address the issues stemmed from 2D methods of representing cadastral survey data, 3D spatial information models can be considered as a viable solution for managing cadastral survey data. Building Information Modeling (BIM) enables colsslaborative 3D management of the design, construction, and operation of buildings. There have been extensive studies conducted to investigate the connectivity between BIM and 3D cadaster. Most of these studies focus on managing legal information, such as ownership boundaries and attributes, in BIM-based environments. However, there is limited investigation on how survey- ing measurements can be mapped into BIM. In this study, the proposed method for integrating the cadastral survey data into the BIM environment includes identifying cadastral survey requirements, using BIM entities relevant to cadastral survey data, enrichment of a BIM proto- type, and evaluation of the prototype. The major contribution of this study is to demonstrate the storage of cadastral survey data such as survey marks and traverse lines in the BIM environment. Therefore, this research contributes to the further enrichment of BIM with incorporating data elements related to cadastral surveying practices. It is confirmed that current BIM-based tools provide restricted capabilities for explicit management and visualiza- tion of cadastral survey data. This limitation can be addressed in the future enhancements of BIM in terms of supporting important elements for cadastral survey data.  相似文献   

Evaluating scale effects and bearing portions in centrifuge modeling of helical anchors: sand     

Heshmati Rafsanjani  Ali Akbar  Salehzadeh  Hossein  Nuri  Hamed 《Acta Geotechnica》2021,16(9):2917-2932

Acta Geotechnica - Helical anchors are bearing elements that can resist uplift loads by a combination of shaft and helical plate bearing. The application of helical piles as offshore wind turbine...  相似文献   

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

Rajabi  Ahmad  Shabanlou  Saeid  Yosefvand  Fariborz  Kiani  Afshin 《Natural Hazards》2021,109(1):871-901

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.

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Geostatistics-Based Method for Irregular Mineral Resource Estimation,in Ouenza Iron Mine,Northeastern Algeria     

Zerzour  Oussama  Gadri  Larbi  Hadji  Riheb  Mebrouk  Faouzi  Hamed  Younes 《Geotechnical and Geological Engineering》2021,39(5):3337-3346

Geotechnical and Geological Engineering - Geostatistical techniques are usually practical in the development and production stages of mining projects. The Ouenza deposit is the main iron ore...  相似文献   

Biomass energy consumption and economic growth: panel data evidence from ASEAN member countries     

Hamisu Sadi Ali  Abdelhakhem Hamed Mohamed Ali Adaa  Woon Leong Lin  Mbodou Ali Youssouf 《GeoJournal》2018,83(6):1339-1348

The present study investigates the dynamic impact of biomass energy consumption on economic growth across nine (9) ASEAN economic union member countries for the period of 1980–2011. We applied heterogeneous panel cointegration techniques. The result based on Pedroni panel cointegration test shows that, variables have long-run relationship as the null hypothesis of no cointegration was rejected at 1% and 5% respectively. Kao residual cointegration test also shows the same result as null hypothesis of no cointegration is rejected at 1% level of significance. The main empirical finding based on dynamic OLS, fully modified OLS and panel OLS reveals that; there is a positive and significant relationship between biomass energy consumptions and economic growth in the region. Moreover, the result based on dynamic ordinary least square (DOLS) also shows that; capital stock and human capital have a positive and significant impact on economic growth. Same result is also obtained from fully modified OLS (FMOLS) with the exception of human capital which is insignificant on economic growth. Panel ordinary least square also reconfirmed the finding of DOLS as all the three variables significantly influences economic growth. The policy suggestion remains that, authorities in ASEAN economic union should focus more on encouraging the use of renewable sources of energy, particularly biomass source of energy considering its positive impact on enhancing economic growth with little or no environmental degradation.  相似文献   

Measuring the relationships between landscape aesthetics suitability and spatial patterns of urbanized lands: an informed modelling framework for developing urban growth scenarios     

Yousef Sakieh  Abdolrassoul Salmanmahiny  Seyed Hamed Mirkarimi  Sepideh Saeidi 《国际地球制图》2017,32(8):853-873

This study develops an informed modelling approach that follows a bottom-up planning strategy to define plausible urban growth scenarios. In this case, landscape aesthetics suitability of the area was first generated using multi-criteria evaluation method. Then, a buffer zone of 1 km was considered to extract the average values of aesthetics suitability scores surrounding urban patches with medium physical size (10–30 hectares). The averaged values were considered as the dependent variable. In the next step, landscape metrics of these urban patches, as explanatory variables, were also computed to measure compositional and configuration-based attributes of urban clusters. Bivariate associations (Pearson correlation analysis) and statistical relationships (linear regression algorithm) between landscape metrics and their associated aesthetics values were measured and modelled. According to the results, both composition and configuration values are significantly correlated to the dependent variable in which configuration-based attributes depicted a stronger explanatory power.  相似文献