Hydrology
Soraya Nouri -Sangarab; Asghar Asghari - Moghaddam; Nasser Jabraeeli-Andrian
Abstract
Recently, due to the trend of decreasing rainfall and increasing groundwater pumping rate, there have been concerns about the risks caused by the decrease in the volume of aquifer reserves and the drop in the groundwater level, and as a consequence the land subsidence. Also, in Ajabshir plain due to ...
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Recently, due to the trend of decreasing rainfall and increasing groundwater pumping rate, there have been concerns about the risks caused by the decrease in the volume of aquifer reserves and the drop in the groundwater level, and as a consequence the land subsidence. Also, in Ajabshir plain due to a gradual decrease in the water level, it is necessary to estimate the subsidence and investigate the subsidence potential to prevent its harmful risks in the future. For this purpose, using the ALPRIFT framework, which includes seven layers of parameters affecting subsidence, the subsidence potential map was zoned. The subsidence potential index was obtained in low and moderate ranges. In the next step, using Sentinel-1 satellite images, the subsidence during the years 2020-2021 was estimated to be 2.4 cm, which had a significant correlation with the groundwater level of the water year 2020-2021 and subsidence potential. In addition, artificial intelligence optimization methods including fuzzy logic (Sugeno) and genetic algorithm were used in order to fix the defects of applying expert opinions and increase the correlation between subsidence (Insar) and ALPRIFT, among these models, Sugeno's fuzzy method provided the best correlation between the two subsidence maps and ALPRIFT. The correlation between subsidence with ALPRIFT, ALPRIFT-GA and ALPRIFT-SFL was obtained as 0.46, 0.62 and 0.72 respectively.
Hydrology
Elham EbrahimZadeh; Ebrahim Rahimi; Vahid Gagheri
Abstract
Identifying landslide-prone areas provides a basis for slope-stabilization and mitigation programs. In Hablehroud watershed, artificial neural network and fuzzy logic (FL) as one of the methods of multicriteria-decision analysis based on ArcGIS were used in the scientific evaluation of landslide-prone ...
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Identifying landslide-prone areas provides a basis for slope-stabilization and mitigation programs. In Hablehroud watershed, artificial neural network and fuzzy logic (FL) as one of the methods of multicriteria-decision analysis based on ArcGIS were used in the scientific evaluation of landslide-prone areas. For this purpose, MATLAB, IDRISI and ArcGIS software were used. After preparing landslide-susceptibility maps, the prone zones predicted by FL and multilayer perceptron artificial neural network (MLP-ANN) were compared with the Hablehroud landslide database (distribution map). The results indicate a good overlap between the prone zones predicted by the MLP-ANN and landslide field observations. Finally, the performance of different methods in generating landslide-susceptibility maps were compared to each other using the validation indicators of "quality-sum index (Qs)" and "receiver-operating-characteristic curve (ROC)" to specify the optimal and applicable method for the landslide risk management of the Hablehroud watershed. By analyzing the obtained zoning maps and considering the Qs and "area-under curve (AUC)" values of different FL operators and MLP-ANN for the landslide-susceptibility maps, it is observed that the Qs (1.6299) and AUC (0.806–very good) values of the MLP-ANN are higher than those calculated for the sensitivity maps by different FL operators.
Hydrology
Ghazaleh Mohebbi Tafreshi; Mohammad Nakhaei; razieh Lak
Abstract
Land subsidence is a nonlinear and complex process that data-driven computational intelligence models can model it. In this study, the accuracy and efficiency of hybrid fuzzy logic gene expression planning hybrid model in estimating land subsidence risk and its factors in Varamin aquifer standardized. ...
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Land subsidence is a nonlinear and complex process that data-driven computational intelligence models can model it. In this study, the accuracy and efficiency of hybrid fuzzy logic gene expression planning hybrid model in estimating land subsidence risk and its factors in Varamin aquifer standardized. For this purpose, after selecting and gathering information from 15 factors affecting the subsidence event based on research records in the GIS environment, they were first standardized by fuzzy membership functions and then gene expression programming method was used to integrate the layers. Finally, using seven important statistical benchmarks based on radar image data, the model was validated in 4 different scenarios in input data and operators. The results showed scenario 1 with input parameters of bedrock level, Debi of pumping wells, groundwater drawdown, geology and operators, +, - ×, ÷, sqr, exp, Ln, ^ 2, ^ 3,3Rt, sin, cos, Atan, is the best model in training and testing. Accordingly, the groundwater drawdown parameter had the highest effect on land subsidence in the study area.
R. Akbari Jonosh; M. Ghorashi; Hasan. A. Babaei; M. Nakhaei; M. Pourkermani
Abstract
Considering Iran’s situation in drought risk area, in this study karstic waters are investigated. The study area is located in central of Iran, Semnan province. Several factors are important in Karstification and formation water resources in carbonate, among them important are petrology, topography, ...
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Considering Iran’s situation in drought risk area, in this study karstic waters are investigated. The study area is located in central of Iran, Semnan province. Several factors are important in Karstification and formation water resources in carbonate, among them important are petrology, topography, climate, geomorphology and hydrogeology are pointed out. In this research, the role of structural factors in the development of karstic water resources in Semnan province has been studied. firstly, information layers of each factor prepared. For example, tectonic elements, includes maps: lineament density, faults length density, faults intersection density and density distance from faults making use geological maps and processing of satellite images. Information layers analyzed in the geographical information system (GIS), Expert Choice Software making use geostatistical methods. In this study, multi methods like analytic hierarchy process (AHP) and Fuzzy analytic hierarchy process (Fuzzy AHP) used in study of karstic water resources.
S. Yusefzadeh; A. A. Nadiri
Abstract
Today Ground water is the main source of drinking, agriculture and other uses for humans. The demand for this critical and strategic natural resource increased with population growth and development of society. This increasing has been declining water resources and damage aquifers environment. Therefore, ...
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Today Ground water is the main source of drinking, agriculture and other uses for humans. The demand for this critical and strategic natural resource increased with population growth and development of society. This increasing has been declining water resources and damage aquifers environment. Therefore, we need to manage aquifers and understanding the hydrogeological parameters to deal with the water crisis and prevent the distraction of aquifers. The one of most important parameter is hydraulic conductivity. Although, the ground water system is a complex system and estimation of hydrogeological parameters is associated with inherent uncertainty and also is costly and time consuming that usually done with classical methods such as laboratory tests, slug test, tracing test and pumping tests. So recently use artificial intelligence methods for estimation of hydraulic conductivity, reduced the uncertainty of this parameter and it adds up some accuracy. So that it can overcome on the shortcoming of classical methods. In this study, four artificial intelligence methods; mamdani fuzzy logic(MFL) system, sugeno fuzzy logic(SFL) system, Wavelet-neural network method and Least square support vector machine(LS-SVM) method were used as individual models to estimate the hydraulic conductivity by using of surface geophysical data in Maragheh-Bonab aquifer. Given that each these models based on their inherent properties, they presented good results in some parts of area. Therefore, for concurrent use of performance of all these models the nonlinear combination method as a supervised committee machine artificial intelligence (SCMAI) model were used to estimate the hydraulic conductivity in maragheh-bonab aquifer. The result of this model showed that this new combinational model has high performance than other single models that presented by using different evaluation criteria. Therefore, this model could also be used for estimation hydrogeological parameters in areas with high complexity. The SCMAI model was tested against 15 data. The RMSE and for SCMAI prediction were computed as 0.045 and 0.97, respectively. Comparing the error measure values with dose of individual models above, it is seen that SCMAI outperforms individual AI models with low RMSE and high values. This result implies that SCMAI model shows high performance for estimation the hydraulic conductivity values in the heterogeneous unconfined aquifer in Maragheh-Boanb plain.
E Ghadiri-Sufi; M Yousefi
Abstract
Integration of different kinds of data is a useful method which can be used in exploration studies to determine the location of undiscovered hidden or outcropping mineral deposits in an area under prospecting. The results obtained by considering all data sources and their relations have better reliability. ...
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Integration of different kinds of data is a useful method which can be used in exploration studies to determine the location of undiscovered hidden or outcropping mineral deposits in an area under prospecting. The results obtained by considering all data sources and their relations have better reliability. In this regard, modeling the mineral potential is commonly used to combine the results achieved by different exploration methods in order to generate target areas. In this research, surface exploration data over the 1:100000 geological map of the Manheshan quadrangle (Zanjan Province) were integrated by a new data-driven and knowledge-driven fuzzy approach to determine areas of high mineralization potential. Various dataset used in this study include geological map, geochemical stream sediment data, and fault distribution map. In this new approach, evidential geochemical and fault density maps were weighted ad produced without the use of any analyst’s subjective judgment and location of known indices. In contrast, the evidential weighted geological map was produced considering the analyst’s subjective judgment. The weighted data layers produced by fuzzy logic were then integrated using OR and Gamma fuzzy logic operators. Finally, known mineral occurrences (Zn-Pb) in the Mahneshan area were used to evaluate the generated models. Results show that the generated target areas have a good spatial coincidence with the position of known mineral occurrences.
E Ghanavati; A Karam; E Taghavi Moghdam
Abstract
Ground assessment to identify and map of susceptible land are as to slope movements especially landslides is of studies related to natural geographers, particularly geomorphologists. Determining and recognition of susceptive areas to sliding could prevent making loss as well as facilitating slope stability ...
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Ground assessment to identify and map of susceptible land are as to slope movements especially landslides is of studies related to natural geographers, particularly geomorphologists. Determining and recognition of susceptive areas to sliding could prevent making loss as well as facilitating slope stability operations. In this study, the variables such as slope, the aspect of slope, petrology, land use, rainfall, and distance from river, fault, and road were used to map the risk of landslide in the Taleghan watershed. After constructing and analyzing the information layers by means of Arc GIS Software, the fuzzy membership functions were used for weighting the layers. The standardized fuzzy layers were overlapped in GIS environment and the landslide risk mapping was produced by means of fuzzy logic operators. The results of this study indicated that gamma function 0.7 is more appropriate than other fuzzy operators. Based on the abovementioned gamma, 18.91% of the area was identified as the high-risk areas. Obviously, allocating these areas for housing, facilities, etc. increases financial and physical damages.
M Yamani; A. A. Shamsipour; M. Jafari Aghdam; S. Bagheri Seyed shokr
Abstract
The Cheleh basin is located in the south of Kermanshah province and the Zagros morphotectonic zone. According to the vast of limestone formation, and the presence of tectonic faults, developed karst land forms has evolved. The purpose of this study is to survey the development of karst and the effect ...
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The Cheleh basin is located in the south of Kermanshah province and the Zagros morphotectonic zone. According to the vast of limestone formation, and the presence of tectonic faults, developed karst land forms has evolved. The purpose of this study is to survey the development of karst and the effect of permeable factors on it. Main data of the research are formed by topographic and geologic maps and aerial photos along with hydrology stats of Department Energy. In this study are nine environmental factors as independent variables and Geomorphological karstic landforms as the dependent variable were examined. At first was identified quantitative and qualitative criteria and then doing field works, interviews and questionnaires, these criteria and factors are analyzed using Analytical Hierarchy Process and finally were gained in GIS, maps and unificating and Final correction with the help of fuzzy logic, respectively. In order to better conclusions, the region in terms of development in karst was divided into four sections. Combining data layers approve the effective role of lithology (Asmari Formation) in the process of development in karsting. Also has seen development in karst on the southern highlands of basin and flat lands at the head of the northern anticline and along the main fault of the region. karst areas Developed 107.95 square kilometers about 22.5 percent and regions with average development of karst covers 34 percent of the watershed basin.
K. Habibi; M. Behzadfar; A. Meshkini; S. Nazari
Abstract
Due to its geographic position and located on the World earthquake belt; Iran is always under threat from earthquakes and several shakes are recorded every year all over the country. The most recent earthquake with 6.8 degree magnitude on the Richter scale hit the city of Bam in 2003 and caused large ...
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Due to its geographic position and located on the World earthquake belt; Iran is always under threat from earthquakes and several shakes are recorded every year all over the country. The most recent earthquake with 6.8 degree magnitude on the Richter scale hit the city of Bam in 2003 and caused large losses of human life and infrastructure. The 2003 Bam earthquake, with more than 30,000 casualties and 10,000 injuries, was the most Destructive earthquake in the current century in Iran. We aim to recognize the main reasons causing these deterioration problems. To this end, we first conceptualize thirteen physical-spatial factors. These factors are analyzed using fuzzy logic and IHPW (Inverse Hierarchy Process Weight) within Geographical Information System. We also attempt to identify the Correlation coefficient analyses between urban vulnerability and damage using Fuzzy logic and GIS. In statistics, correlation and dependence are any of a broad class of statistical relationships between two or more random variables or observed data values. With respect to the covariance between two variables (urban vulnerability map and damage post earthquake) the correlation coefficient is calculated 0.59. The results of the model as applied to the structures of the city of Bam illustrate that a fuzzy approach is a basic tool that can be used to identify urban vulnerability and damage post earthquake incident. Its application to the problem assists in unifying relevant theories and practices.
M. Farzamian; A. Kamkar Rouhani; M. Ziaiie; H. A. Faraji Sabokbar; K. Seif panahi
Abstract
Chichakloo Lead and Zinc ore deposit is one of mineral potential areas, located in Lead and Zinc belt limit of Takab zone and 25 km far from Anguran mine. This ore deposit has been prospected and explored in different scales several times within the last few decades. The last exploration activity over ...
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Chichakloo Lead and Zinc ore deposit is one of mineral potential areas, located in Lead and Zinc belt limit of Takab zone and 25 km far from Anguran mine. This ore deposit has been prospected and explored in different scales several times within the last few decades. The last exploration activity over the deposit is the detailed geophysical survey (using resistivity and induced polarization methods) and also geochemical survey for potential mapping of Lead and Zinc zones. In this paper, after modeling and interpretation of geophysical data and processing and interpretation of geochemical data, we have prepared suitable exploration maps in GIS environment. For this, we have taken a new fuzzy approach for exploration maps using trapezoidal membership function. Then, for integration of exploration fuzzy layers, we have used fuzzy operations. The results of investigation of the final integrated exploration map indicate lead and zinc zones having a fuzzy favorability of greater than 0.5 in southeast of the study area that is obtained from remarkable overlapping of geophysical and geochemical anomalies. The results of drilling boreholes in the area confirm the exploration results obtained in this research work.
M. Rajabi; B. Bohloli; M. Mohammadinia; E. Gholampour Ahangar
Abstract
The shear and compressional wave velocities (Vs and Vp, respectively) have many applications in petrophysical, geophysical and geomechanical studies. Vp is very easily obtained from sonic logs that are available in most of oil and gas wells, but some wells (especially old wells) may not have Vs data. ...
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The shear and compressional wave velocities (Vs and Vp, respectively) have many applications in petrophysical, geophysical and geomechanical studies. Vp is very easily obtained from sonic logs that are available in most of oil and gas wells, but some wells (especially old wells) may not have Vs data. In this study Vs was predicted from porosity well log data (neutron, density and sonic) using fuzzy logic and neuro-fuzzy techniques. For this purpose a total of 3910 data points from Sarvak carbonate reservoir which have Vs and porosity log data were utilized. These data were divided into two parts, one part included 2046 data points used for constructing models and the other part included 1864 data points used for testing models. The results show that fuzzy logic and neuro-fuzzy techniques were useful methods for prediction of Vs in this carbonate oil reservoir.
G. R. Elyasi; M. Karimi; A. Bahroudi; A. Adeli Sarcheshme
Abstract
Piles of maps from different sources with varying scales and formats and different styles and absence of a proper solution for integrating vast amount of information has resulted in a complexity for preparing mineral potential map. Using GIS not only organizes the information related to mineral exploration ...
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Piles of maps from different sources with varying scales and formats and different styles and absence of a proper solution for integrating vast amount of information has resulted in a complexity for preparing mineral potential map. Using GIS not only organizes the information related to mineral exploration but also has the ability to produce and integrate information layers in different models with more precision and speed and supports spatial decision makings. In this article mineral potential map of Now Chun copper prospect has been produced for determination of drilling points. Used layers in this study include rock type, structure, alteration, mineralization indicators, anomaly zone of chargeability and apparent resistivity and metal factor, anomaly of copper and molybdenum and Cu-Mo additive indexes. After information preparation, Factor maps were weighted and integrated in the inference network. Integration use of Fuzzy logic and index overlay operators in inference network can eliminate defects in other models and provide more flexible integration of factor maps. Regarding to produce mineral potential map, mineral potential zones of porphyry copper were located in north-east parts of studied area. Eventually, the degree of correlation between mineral potential map and those operated exploration boreholes have been estimated for two different classes, 63.16 % and 64.52 %. Comparison between the high potential points indicated by our mineral potential maps with those previous drilled boreholes reveals about 26% discorrelation. It means that if such present study had been done before any drilling operation, it could have saved 200,000$ just for drilling expenditure.