Delineation of groundwater potential zones using remote sensing,GIS, and AHP technique in Tehran–Karaj plain,Iran     

Mohammad Reza Panahi  S. Morteza Mousavi  Majid Rahimzadegan 《Environmental Earth Sciences》2017,76(23):792

Evaluation of groundwater resources in dry areas without enough data is a challenging task in many parts of the world, including Tehran–Karaj plain in Iran, which includes Tehran, the capital city of Iran and Karaj, one of Iran’s biggest cities. Water demand due to increasing agricultural and industrial activities caused many problems in the field of water resources management. In this study, the potential of groundwater resources was evaluated using remote sensing, geographic information system (GIS), and analytic hierarchy process (AHP) for the first time. Digital Elevation Model from Shuttle Radar Topography Mission was used to generate a slope map and drainage density map. Three Landsat-8 satellite images were utilized to provide lineament density and land cover/land use maps. Geological and soil type maps were provided from the Geological Survey and Mineral Explorations of Iran (GSI). Tropical Rainfall Measuring Mission data were used to prepare average annual precipitation map. Discharge values from 102 pumping wells in the time period of 2002–2014 were used to evaluate the results. Seven data layers were prepared, and the geodatabase was made in GIS. The layers and their classes were assigned weights using AHP method. Finally, the layers were overlaid based on their weights, and the potential map of groundwater resources was generated. The area was classified into five zones with very high, high, moderate, low, and very low potentials. The zones covered 5.95, 32.90, 22.70, 10.20, and 28.25% of the study area, respectively. The results showed good agreement with the field data obtained from discharge wells.  相似文献   

Comparing different statistical models for assessing Fe-contaminated soils based on VNIR/SWIR spectral data     

Mahboobeh Tayebi  Mehdi Naderi  Jahangard Mohammadi  Mohammad H. Tayebi 《Environmental Earth Sciences》2017,76(21):734

Two statistical models including partial least squares regression (PLSR) and principal component regression were comparatively utilized to determine the predictive accuracy of visible–near-infrared and short-wave infrared reflectance spectroscopy in quantifying the Fe concentration in contaminated soils. Two scenarios were applied to select the best model: Scenario I included all wavelengths (400–2450 nm) and Scenario II encompassed characteristic bands of Fe. Pre-processing techniques used to select the best model included: first and second derivatives (FD and SD), multiplicative scatter correction (MSC) and standard normal variate. The abilities of the predictive models were evaluated by splitting soil samples into two random groups (80 and 20%). The first group (80%) was used to evaluate calibration and validation sets by employing the cross‐validation method, and the second group (20%) was applied to test the models. The coefficient of determination (R ²), root mean square error and residual prediction deviation were calculated to evaluate the models. Applying Scenario I indicated that the PLSR model with SD pre-processing was a more accurate technique for predicting the Fe concentration, whereas in the Scenario II, the PLSR model with MSC pre-processing had a better performance. Comparing Scenarios I and II indicated that the more reliable models for predicting the soil Fe content could be constructed by the PLSR model with the SD pre-processing techniques and all wavelengths. The modeling results produced by the PLSR model with the SD pre-processing could be used to detect, map and monitor Fe-contaminated soils by proximal and remote sensing in the mining areas.  相似文献   

Modeling and mapping of solar radiation using geostatistical analysis methods in Iran     

Hassan Fathizad  Mohammad Hossein Mobin  Azam Gholamnia  Hamid Sodaiezadeh 《Arabian Journal of Geosciences》2017,10(17):391

Because of economic and technical limitations, measuring solar energy received at ground level (R _s ) isn’t possible in all parts of the country, and in only 12% of synoptic stations is this parameter measured and recorded. Thus, it should be estimated and modeled spatially based on other climatic variables using mathematical methods. In this research, many attempts have been made to introduce an air temperature-based model for Rs estimation, and then, based on the output of the mentioned models, several geostatistical methods have been tested, and finally an elegant spatial model is proposed for (Rs) zoning in Iran. In this regard, the relationships between the measured amounts of monthly solar radiation and other climatic parameters, such as a monthly average, maximum and minimum temperature, precipitation, relative humidity, and the number of sunny hours during the period 1970–2010, are examined and modeled. It was revealed that based on the linear relationship between the monthly average air temperatures and solar radiation values recorded in each of the stations, that the best-fit linear model, with R ²  = 0.822, MAE = 1.81, RMSE = 2.51%, and MAPE = 10.08, can be introduced for Rs estimation. Then, using the outputs of the proposed model, the amounts of (R _s ) are estimated in another 171 meteorological stations (a total of 192 stations), and eight geostatistical methods (IDW, GPI, RBF, LPI, OK, SK, UK, and EBK) were investigated for zoning. Comparing the resulting variograms showed that in addition to proof of spatial correlation between solar radiation data, they can be applied for modeling changes in various directions. Analyzing the ratio of the nugget effect on the roof of the variograms showed that the Gaussian model with the lowest ratio (Co/Co + C = 0.883) and (R ²  = 0.972), could model the highest correlation between the data and, therefore, it was used for data interpolation. To select the best geostatistical model, R2, MAE, and RMSE were used. On this basis, it was found that the RBF method with R ²  = 0.904, MAE = 3.02, RMSE = 0.39% is the most effective. Also, the IDW method with R ²  = 0.90, MAE = 3.08, RMSE = 0.391%, compared to other methods is the most effective. In addition, for data validation, correlations between observed and estimated values of solar radiation were studied and found R ²  = 0.86.  相似文献   

A comparative assessment between linear and quadratic discriminant analyses (LDA-QDA) with frequency ratio and weights-of-evidence models for forest fire susceptibility mapping in China   总被引：1，自引：0，他引：1  

Haoyuan Hong  Seyed Amir Naghibi  Mostafa Moradi Dashtpagerdi  Hamid Reza Pourghasemi  Wei Chen 《Arabian Journal of Geosciences》2017,10(7):167

Forest fire is known as an important natural hazard in many countries which causes financial damages and human losses; thus, it is necessary to investigate different aspects of this phenomenon. In this study, performance of four models of linear and quadratic discriminant analysis (LDA and QDA), frequency ratio (FR), and weights-of-evidence (WofE) was investigated to model forest fire susceptibility in the Yihuang area, China. For this purpose, firstly, a forest fire locations map was prepared implementing MODIS satellite images and field surveys. Then, it was classified into two groups including training (70%) and validation (30%) by a random algorithm. In addition, 13 forest fire effective factors were prepared and used such as slope degree, slope aspect, altitude, Topographic Wetness Index (TWI), plan curvature, land use, Normalized Difference Vegetation Index (NDVI), annual rainfall, distance from roads and rivers, wind effect, annual temperature, and soil texture. Using the training dataset and effective factors, LDA, QDA, FR, and WofE models were applied and forest fire susceptibility maps were prepared. Finally, area under the curve (AUC) of receiver operating characteristics (ROC) was implemented for investigating the performance of the models. The results depicted that WofE had the best performance (AUC = 82.2%), followed by FR (AUC = 80.9%), QDA (AUC = 78.3%), and LDA (AUC = 78%), respectively. The results of this study showed the high contribution of altitude, slope degree, and temperature. On the other hand, it was seen that slope aspect and soil had the lowest importance in forest fire susceptibility mapping. From the AUC results, it can be concluded that FR, WofE, LDA, and QDA had acceptable performance and could be used for forest fire susceptibility mapping at the regional scale.  相似文献   

U, Th, K and Cs activity concentrations along the southern coast of the Caspian Sea, Iran     

Mohammad Reza Abdi  Smaeyl Hassanzadeh  Hamid Reza Raji 《Marine pollution bulletin》2009,58(5):658-662

The determination of activity concentrations of the radioactive elements ²³⁸U, ²³²Th, ⁴⁰K and ¹³⁷Cs was performed on grab samples taken from a polluted environment. The samples were sliced into strata from 5 cm depth, dried and ground to sieved through a 170 mesh size prior to the analysis. Activity concentration was quantified using gamma spectroscopy. The results showed that the concentrations of activity in the sediment samples are 177 ± 12.4, 117 ± 11.5, 1085 ± 101.6 and 131 ± 4.8 Bq kg⁻¹ for ²³⁸U, ²³²Th, ⁴⁰K and ¹³⁷Cs, respectively. In general, the distribution of activity concentrations along the southern coast of the Caspian Sea area exceeded international limits. The hazard index of the samples was 0.19-0.88, with an average of 0.49. The mean values of radium equivalent activity and dose rate are 176 Bq kg⁻¹ and 63 nGy h⁻¹, respectively.  相似文献   

Optimal design of soil dynamic compaction using genetic algorithm and fuzzy system     

Maziar Pasdarpour  Mahmoud Ghazavi  Mohammad Teshnehlab  S. Amiroddin Sadrnejad 《Soil Dynamics and Earthquake Engineering》2009

Computational intelligent techniques, such as fuzzy and genetic algorithm, have proven to be useful in modeling of complex nonlinear phenomena such as dynamic compaction. Dynamic compaction method is used to improve the mechanical behavior of underlying soil layers especially loose granular materials. The method involves the repeated impart of high-energy impacts to the soil surface using steel or concrete tampers with weights ranging 10–40 ton and with drop heights ranging 10–40 m. A relatively exact estimation of dynamic compaction level is of major concern to geotechnical engineers. This paper develops a fuzzy set base method for the analysis of dynamic compaction phenomenon. In this model, the input variables are tamper weight, height of tamper drop, print spacing, tamper radius, number of impact and soil layer geotechnical properties. The main shortcoming of this technique is uncertainty to locate the best sketch of dynamic compaction to gain maximum effect of this method of soil improvement. Therefore, this paper describes the incorporation of genetic algorithm methodology using fuzzy system for determining the optimum design of dynamic compaction. Subsequently, it will be shown that the genetic algorithm has some abilities in the optimization of dynamic compaction design. Also different manners of this algorithm are compared and then the optimized structure of genetic algorithm will be suggested for dynamic compaction.  相似文献   

Trends and occurrences of nitrate in the groundwater of the West Bank, Palestine   总被引：2，自引：0，他引：2  

Fathi M. Anayah  Mohammad N. Almasri   《Applied geography (Sevenoaks, England)》2009,29(4):588-601

Groundwater is the major source of water to the Palestinians. Efficient management of this resource requires a good understanding of its status. This understanding necessitates a characterization of the quality of the utilizable volumes. This paper focuses on the assessment of nitrate concentrations in the aquifers of the West Bank, Palestine. A preliminary statistical analysis is carried out for the spatial and temporal distributions of the nitrate concentrations. GIS is utilized to facilitate the analysis and to efficiently account for the spatiality of nitrate concentrations. The analysis was carried out at different spatial levels and key parameters including soil type, watersheds, depth, population, and rainfall. It is observed that elevated nitrate concentrations in the groundwater greatly coincide with increasing rainfall, particularly in the last few years. Results confirm that the annual mean nitrate concentration in the Western groundwater basin has an increasing trend over the period from 1982 to 2004 indicating its vulnerability to contamination. This result can be attributed to the agricultural activities along with the high groundwater recharge. However, leaking septic and sewer systems are considerably causing nitrate contamination of groundwater in populated areas. Overall, the recommendations call for an immediate intervention to manage the quality problems in the West Bank aquifers.  相似文献   

Petrochemistry of sandstones from Neoproterozoic basins of the Bastar craton, Central Indian Shield: Implications for paleoweathering, provenance and tectonic history     

Hamidullah  Wani  Mohammad E. A.  Mondal 《Island Arc》2009,18(2):352-374

Petrographic analysis and chemical analysis of major and trace elements including rare earth elements of the Neoproterozoic sandstones from the Chandarpur Group and the Tiratgarh Formation have been carried out to determine their provenance, tectonic setting and weathering conditions. All sandstone samples are highly enriched in quartz but very poor in feldspar and lithic fragments. Petrographically and geochemically these sandstones are classified as subarkose, sublitharenite and arenite. The Chemical Index of Alteration (CIA mean 68) and Th/U ratios (mean 4.2) for these sandstones suggest their moderate weathering nature. Generally, all sandstone samples are strongly depleted in major elements (except SiO₂), trace elements (except Zr) and REE in comparison with Post Archean Australian Shale (PAAS) and Upper Continental Crust (UCC). Their mineralogy and mean of elemental ratios suitable for determination of provenance and tectonic setting, e.g. Al₂O₃/SiO₂ (0.02), K₂O/Na₂O (10), Eu/Eu* (0.67), (La/Lu)n (10.4), La/Sc (3), Th/Sc (1.2), La/Co (0.22), Th/Co (0.08), and Cr/Th (7.2), support a felsic source and a passive margin tectonic setting for these sandstones. Also these key elemental ratios do not show much variation over a range of SiO₂. Thus we attest their significance in determining source rock characteristics of quartz rich sandstones. Chondrite‐normalized REE patterns with LREE enrichment and a strong negative Eu anomaly are also attributed to felsic source rock characteristics for these sandstones. The source rocks identified are granite and gneiss of the Bastar craton. Minor amounts may have been derived from older supracrustals of the Bastar craton. However, the major element data of the Paleoproterozoic Sakoli schists when compared with those of the Neoproterozoic sandstones indicate that the schists were derived from a mafic source and deposited in an active continental margin tectonic setting. There is, however, little difference in CIA values between the Paleoproterozoic Sakoli schists and Neoproterozoic sandstones, indicating prevailing of similar (moderate‐intense) weathering conditions throughout the Proterozoic in the Bastar craton. Our study also suggests a change in the provenance and tectonic setting of deposition of sediments from dominantly a mafic source and an active continental margin in the Paleoproterozoic to dominantly granite and gneiss (felsic source) and a passive continental margin in the Neoproterozoic in the Bastar craton.  相似文献   

Geodetic deformation vs. seismic strain deduced by historical earthquakes across the Alborz Mountains   总被引：1，自引：0，他引：1  

Mohammad Reza Zolfaghari 《Journal of Seismology》2009,13(4):647-663

Historical seismicity is used in order to map spatial distribution of seismic moment released by past earthquakes and to compare strain rate deduced from seismicity to those measured by geodetic GPS survey. Spatial analyses are performed on the seismicity of northern boundary of Central Iranian Block which coincides with the Alborz Mountains. This belt has been responsible for several catastrophic earthquakes in the past. In this study, the records of historical and instrumental earthquakes in the Alborz Mountains are used to calculate and plot geographical distribution of seismic moment released in time. A two-dimensional distribution function is proposed and used here to spread seismic moment along causative tectonic features. Using accumulated seismic moment, average slip rates across active faults are estimated for 32 sub-zones along the Alborz Mountains and western Kopet Dag. Seismic moment released by historical and recent earthquakes on this belt accounts for slip rate of 3–5 mm/year which is in good agreement with the geodetic vectors recently deduced from GPS survey in this region. The study also reveals geographical variations of slip rates along some 900 km length of this zone based on seismic history. The results are compared against finding from similar study in this region. Portions of Central and Eastern Alborz show lower seismic strain rate which could imply aseismic motion or overdue earthquakes. Completeness of historical earthquake catalogue and its reliability with regard to earthquake magnitudes, locations, and rupturing systems are among many plausible factors controlling the credibility of such results. Therefore, any conclusions derived from these results remain as reliable as the data and assumptions used for the analyses.  相似文献   

Feed forward neural network and interpolation function models to predict the soil and subsurface sediments distribution in Bam,Iran   总被引：1，自引：1，他引：0  

Khalil Rezaei  Bernard Guest  Anke Friedrich  Farajollah Fayazi  Muhammad Nakhaei  Ali Beitollahi  Seyed Mahmoud Fatemi Aghda 《Acta Geophysica》2009,57(2):271-293

An application of the artificial neural network (ANN) approach for predicting mean grain size using electric resistivity data from Bam city is presented. A feed forward back propagation network was developed employing 45 sets of input data. The input variables in the ANN model are the electrical resistivity, water table as a Boolean value and depth; the output is the mean grain size. To demonstrate the authenticity of this approach, the network predictions are compared with those from interpolation methods and the same data. This comparison shows that the ANN approach performs better results. The predicted and observed mean grain size values were compared and show high correlation coefficients. The ANN approach maps show a high degree of correlation with well data based grain size maps and can therefore be used conservatively to better understand the influence of input parameters on sedimentological predictions.  相似文献