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Ata Amini
Kurdistan Agricultural and Natural Resources Research and Education Center, AREEO, Sanandaj 66177-15175, Iran

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Journal article
Published: 28 April 2021 in Ecohydrology & Hydrobiology
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In most of the basins, due to the lack of sedimentation stations, there is no accurate information on sediment deposition and soil erosion. In such basins, empirical models are used to estimate the sediment rate. At the basin scale, the applicability of these models is troublesome. The objectives of this study were to determine the erosion status of the Zarivar lake basin and to evaluate the efficiency of the Factorial Scoring Model, FSM, in estimating the sediment rate. Physiological and hydrological characteristics of 10 sub-basins of Zarivar lake were obtained using field measurements and aerial data in the GIS environment. The specific weight of the sediments was calculated in the laboratory and used to determine the weight of sediments. The sediment rate in sub-basins was measured in situ. Furthermore, by determining the effective parameters, the sediment rate for each sub-basin was obtained using FSM, and the results were compared with the measured rate. For the whole basin, the average, minimum, and maximum rate of observed sediment were 0.28, 0.007, and 1.17 m3/ha.yr, respectively. However, these rates were obtained by FSM as 103.70, 20.90, and 365 m3/ha.yr, respectively, which differed from the observed values. Based on the results, the model is not sufficiently efficient to evaluate the sediment rate in the studied sub-basins.

ACS Style

Ata Amini; Hossein Khaledian; Hosna Shafaei. Field Evaluation of Soil Erosion Yield and the FSM Model Efficiency in Zarivar Lake Basin, Kurdistan, Iran. Ecohydrology & Hydrobiology 2021, 1 .

AMA Style

Ata Amini, Hossein Khaledian, Hosna Shafaei. Field Evaluation of Soil Erosion Yield and the FSM Model Efficiency in Zarivar Lake Basin, Kurdistan, Iran. Ecohydrology & Hydrobiology. 2021; ():1.

Chicago/Turabian Style

Ata Amini; Hossein Khaledian; Hosna Shafaei. 2021. "Field Evaluation of Soil Erosion Yield and the FSM Model Efficiency in Zarivar Lake Basin, Kurdistan, Iran." Ecohydrology & Hydrobiology , no. : 1.

Journal article
Published: 23 April 2021 in International Journal of River Basin Management
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Proper placement of dams along a river entails a lot of studies including the impact of the upstream dam on downstream dams and lands. In case of inaccurate placement of the dams, the flood arisen from the failure of the upstream dam break leads to the breakage of downstream dams. In this research, the reservoir volumes of two successive dams were optimized to evaluate the stability of the downstream dam and present a decision basis for dams’ safety. To this end, the two successive dams of Vahdat located at the upstream of the Zhave dam, in the Sirvan basin, Kurdistan province, Iran were investigated. The HEC-RAS model was applied to the simulation of the upstream dam failure and the routing of the following flood up to the downstream dam reservoir. The digital elevation model, DEM, concerning the study area was derived. After converting DEM to Triangulated Irregular Networks, TIN, the required parameters and the lines pertaining to the cross sections were drawn on the river via ArcMap software. The cross sections were modified by field surveys, and the Manning coefficient was measured for different zones. By inputting the input hydrographs as well as the data related to the dam side wall and sluice gates, several likely scenarios were defined and performed in HEC-RAS. The scenarios were taken into account based on different volumes of water in the reservoirs along with piping and overtopping for the dam breaks. The results showed that in most situations, the upstream dam failure yields the downstream dam break. The maximum height of water in the reservoir so that it will not lead to overtopping breakage due to the upstream dam failure was 1295 m above sea level which was equivalent to 6.43×107 m3. In case of upstream dam failure, the water volume of the downstream dam exceeds the above-mentioned critical values, the latter would likely undergo the breakage.

ACS Style

Ata Amini; Jamil Bahrami; Azad Miraki. Effects of dam break on downstream dam and lands using GIS and Hec Ras: a decision basis for the safe operation of two successive dams. International Journal of River Basin Management 2021, 1 -12.

AMA Style

Ata Amini, Jamil Bahrami, Azad Miraki. Effects of dam break on downstream dam and lands using GIS and Hec Ras: a decision basis for the safe operation of two successive dams. International Journal of River Basin Management. 2021; ():1-12.

Chicago/Turabian Style

Ata Amini; Jamil Bahrami; Azad Miraki. 2021. "Effects of dam break on downstream dam and lands using GIS and Hec Ras: a decision basis for the safe operation of two successive dams." International Journal of River Basin Management , no. : 1-12.

Original paper
Published: 08 January 2021 in Theoretical and Applied Climatology
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Land evaluation based on its characteristics is a criterion for the proper use of land potential. The high benefit and low water requirement of pistachio has significantly increased its cultivation area in Iran. The objective of this study was to evaluate the suitability of lands for pistachio cultivation based on climatic variables in four provinces, which located in northwestern part of Iran. The climatic requirements of pistachio were specified based on its phenological information. Then, the suitability map of pistachio cultivation zones, spatially modeled in GIS environment based on long term of meteorological data. Subsequently, the results were verified due to field survey and interviews with farmers. The results showed study area classified into three categories from suitable (class S1), moderate suitable (S2), and non-suitable (class N) based on FAO land capability guidelines. So, accuracy of suitability map was validated by overlaying of spatial information of existing pistachio orchards. The results indicated that 33, 33.4, 60, and 12.4% of the East Azerbaijan, West Azerbaijan, Kurdistan, and Ardabil provinces are suitable for pistachio cultivation (class S1), respectively, while the area of unsuitable class (class N) in these provinces was 40, 34.7, 22.7, and 62%, respectively. It was found that the temperature and relative humidity during pollination and growth periods are the main limiting factors for construction of pistachio orchards. The obtained maps can be used as a guide to prevent the planting of pistachios in unsuitable areas and consequently save water consumption in drought conditions.

ACS Style

Jamshid Yarahmadi; Ata Amini. Determining land suitability for pistachio cultivation development based on climate variables to adapt to drought. Theoretical and Applied Climatology 2021, 143, 1631 -1642.

AMA Style

Jamshid Yarahmadi, Ata Amini. Determining land suitability for pistachio cultivation development based on climate variables to adapt to drought. Theoretical and Applied Climatology. 2021; 143 (3-4):1631-1642.

Chicago/Turabian Style

Jamshid Yarahmadi; Ata Amini. 2021. "Determining land suitability for pistachio cultivation development based on climate variables to adapt to drought." Theoretical and Applied Climatology 143, no. 3-4: 1631-1642.

Journal article
Published: 15 December 2020 in Journal of Hydroinformatics
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In this research, the accuracy of the Flow-3D numerical model in the flow simulation in a stepped spillway was probed using data obtained from the physical model. In addition, the effects of block barriers on the energy dissipation rate were investigated. To adopt a proper turbulent model, Renormalization Group k-ε, RNG k-ε, and standard k-ε models were employed. Then, the Flow-3D was run in five discharges for nine spillways with the ratios of block length to step length (Lb/l) and block height to step height (Hb/h) as 0.3, 0.4, and 0.5. The results indicated that both turbulent models had almost similar outcomes though the run time of the RNG k-ε model was shorter. The blocks with a shorter length in low ratios of Hb/h and the lengthier blocks in high ratios of Hb/h undergo more relative energy dissipation relative to the no-block situation. For Hb/h = 0.3 and Lb/l equal to 0.3, 0.4, and 0.5, the relative energy dissipation climbed on average as 8.5, 6.5, and 4.5% respectively, compared with the no-block case. The most influence exerted on relative energy dissipation was obtained via the blocks with Hb/h = Lb/l equal to 0.3 and 0.5 with respective increases of 8.6 and 8.4%.

ACS Style

Mehdi Karami Moghadam; Ata Amini; Ehsan Karami Moghadam. Numerical study of energy dissipation and block barriers in stepped spillways. Journal of Hydroinformatics 2020, 23, 284 -297.

AMA Style

Mehdi Karami Moghadam, Ata Amini, Ehsan Karami Moghadam. Numerical study of energy dissipation and block barriers in stepped spillways. Journal of Hydroinformatics. 2020; 23 (2):284-297.

Chicago/Turabian Style

Mehdi Karami Moghadam; Ata Amini; Ehsan Karami Moghadam. 2020. "Numerical study of energy dissipation and block barriers in stepped spillways." Journal of Hydroinformatics 23, no. 2: 284-297.

Research article
Published: 24 August 2020 in Marine Georesources & Geotechnology
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The use of complex piers to build bridges has become widespread. In this study the experimental data was obtained to determine scour hole's dimension and its changes versus pile cap elevation. Five models with different geometry were used in experiments under clear water condition and thresholds velocity. The models were made with an appropriate scale from real piers of bridges. A 3D illustration of the model for each experiment was drawn. The length, width and depth of the scour hole coordinates were measured in three directions. The results showed that similar to the scour depth, the scour length and width, apart from pier geometry, are significantly depended on the pile cap elevation. It was found that the variation in scour hole dimensions can be categorized into two cases as before and after pile cap undercutting. Moreover, the maximum length and width of the scour hole at each model were derived.

ACS Style

Valeh Khaledi; Ata Amini; Jamil Bahrami. Physical simulation of scour width and length variation around complex piers under clear water condition. Marine Georesources & Geotechnology 2020, 1 -8.

AMA Style

Valeh Khaledi, Ata Amini, Jamil Bahrami. Physical simulation of scour width and length variation around complex piers under clear water condition. Marine Georesources & Geotechnology. 2020; ():1-8.

Chicago/Turabian Style

Valeh Khaledi; Ata Amini; Jamil Bahrami. 2020. "Physical simulation of scour width and length variation around complex piers under clear water condition." Marine Georesources & Geotechnology , no. : 1-8.

Journal article
Published: 13 May 2020 in Water Supply
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In this research, the ejecting jet from a flip bucket downstream of a chute spillway was simulated using physical modeling. The effects of influencing parameters upon fluctuations and extreme values of dynamic pressure were investigated. The angles of 0°, 30°, 45°, and 60° were adopted for the mobile bottom wall. The discharges were set as 67, 86, 161, and 184 litre/s and the depths of water cushion on the mobile bottom wall were set as 0, 15, 30, and 45 cm. The method suggested by Castillo for computation of fluctuating coefficient of dynamic pressure (see Castillo (2007) Pressure characterization of undeveloped and developed jets in shallow and deep pool. Proceedings of the Congress-International Association for Hydraulic Research32 (2), 645) was validated via the laboratory data. The results showed that the increase in water cushion depth downstream has led to a decrease in mean pressure and in pressure fluctuations. The analyses showed that the fluctuating pressure coefficient was a function of water cushion depth, and its maximum value was taken when there was a water cushion on the mobile bottom wall. With an increase in discharge and mobile bottom wall angle, the maximum value of the fluctuating coefficient occurred in less water cushion depth. Moreover, with the growth of discharge, the maximum positive and negative fluctuations of the pressure increased first and then decreased.

ACS Style

Mehdi Karami Moghadam; Ata Amini; Hasan Hosseini. Experimental evidence dynamic pressures reduction on plunge pool floors downstream flip bucket for increasing downstream face slopes. Water Supply 2020, 20, 1834 -1846.

AMA Style

Mehdi Karami Moghadam, Ata Amini, Hasan Hosseini. Experimental evidence dynamic pressures reduction on plunge pool floors downstream flip bucket for increasing downstream face slopes. Water Supply. 2020; 20 (5):1834-1846.

Chicago/Turabian Style

Mehdi Karami Moghadam; Ata Amini; Hasan Hosseini. 2020. "Experimental evidence dynamic pressures reduction on plunge pool floors downstream flip bucket for increasing downstream face slopes." Water Supply 20, no. 5: 1834-1846.

Original paper
Published: 27 April 2020 in Natural Hazards
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In recent years, the influence of natural agents such as drought and human activities has contributed to the intensification of dust phenomena. The storms came up in recent decade in most parts of Iran are new-fangled phenomena as regards intensification, extent, and frequency. Some reasons encouraging such environmental changes are shared by climate parameters. In this research, climate variations were investigated by scrutinizing long-term rainfall and temperature data via statistical and graphical tools. The relation between these variations and dust rate in Kurdistan Province, Iran, was studied. Mann–Kendall graphical test was used to explore the changes that occurred in the time series for average monthly temperature and rainfall. Spatial distribution of temperature and rainfall along with drought indices was supplied in the GIS environment. Also, alterations in the dust phenomenon were studied by analyzing the number of days with dust. The results showed that the changes in rainfall and temperature parameters have led to drought spread in the area. Within a long-term 30-year time series, 19 and 31 months were recorded as for changes in, respectively, average precipitation and temperature in the stations of the study area. In this trend, 7 and 5 months were reported with reference to abrupt changes in precipitation and temperature, respectively. Also, the number of days with dust has been increasing significantly. The results of this research could help quantify the role factors affecting the development of this phenomenon in the region.

ACS Style

Ata Amini. The role of climate parameters variation in the intensification of dust phenomenon. Natural Hazards 2020, 102, 445 -468.

AMA Style

Ata Amini. The role of climate parameters variation in the intensification of dust phenomenon. Natural Hazards. 2020; 102 (1):445-468.

Chicago/Turabian Style

Ata Amini. 2020. "The role of climate parameters variation in the intensification of dust phenomenon." Natural Hazards 102, no. 1: 445-468.

Articles
Published: 16 April 2020 in International Journal of River Basin Management
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Scouring is the most common cause of bridge failure. This study was conducted to evaluate the efficiency of the Artificial Neural Networks (ANN) in determining scour depth around composite bridge piers. The experimental data, attained in different conditions and various pile cap locations, were used to obtain the ANN model and to compare the results of the model with most well-known empirical, HEC-18 and FDOT, methods. The data were divided into training and evaluation sets. The ANN models were trained using the experimental data, and their efficiency was evaluated using statistical test. The results showed that to estimate scour at the composite piers, feed-forward propagation network with three neurons in the hidden layer and hyperbolic sigmoid tangent transfer function was with the highest accuracy. The results also indicated a better estimation of the scour depth by the proposed ANN than the empirical methods.

ACS Style

Ata Amini; Shahriar Hamidi; Ataollah Shirzadi; Javad Behmanesh; Shatirah Akib. Efficiency of artificial neural networks in determining scour depth at composite bridge piers. International Journal of River Basin Management 2020, 19, 327 -333.

AMA Style

Ata Amini, Shahriar Hamidi, Ataollah Shirzadi, Javad Behmanesh, Shatirah Akib. Efficiency of artificial neural networks in determining scour depth at composite bridge piers. International Journal of River Basin Management. 2020; 19 (3):327-333.

Chicago/Turabian Style

Ata Amini; Shahriar Hamidi; Ataollah Shirzadi; Javad Behmanesh; Shatirah Akib. 2020. "Efficiency of artificial neural networks in determining scour depth at composite bridge piers." International Journal of River Basin Management 19, no. 3: 327-333.

Journal article
Published: 02 March 2020 in Water
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Flash floods are one of the most devastating natural hazards; they occur within a catchment (region) where the response time of the drainage basin is short. Identification of probable flash flood locations and development of accurate flash flood susceptibility maps are important for proper flash flood management of a region. With this objective, we proposed and compared several novel hybrid computational approaches of machine learning methods for flash flood susceptibility mapping, namely AdaBoostM1 based Credal Decision Tree (ABM-CDT); Bagging based Credal Decision Tree (Bag-CDT); Dagging based Credal Decision Tree (Dag-CDT); MultiBoostAB based Credal Decision Tree (MBAB-CDT), and single Credal Decision Tree (CDT). These models were applied at a catchment of Markazi state in Iran. About 320 past flash flood events and nine flash flood influencing factors, namely distance from rivers, aspect, elevation, slope, rainfall, distance from faults, soil, land use, and lithology were considered and analyzed for the development of flash flood susceptibility maps. Correlation based feature selection method was used to validate and select the important factors for modeling of flash floods. Based on this feature selection analysis, only eight factors (distance from rivers, aspect, elevation, slope, rainfall, soil, land use, and lithology) were selected for the modeling, where distance to rivers is the most important factor for modeling of flash flood in this area. Performance of the models was validated and compared by using several robust metrics such as statistical measures and Area Under the Receiver Operating Characteristic (AUC) curve. The results of this study suggested that ABM-CDT (AUC = 0.957) has the best predictive capability in terms of accuracy, followed by Dag-CDT (AUC = 0.947), MBAB-CDT (AUC = 0.933), Bag-CDT (AUC = 0.932), and CDT (0.900), respectively. The proposed methods presented in this study would help in the development of accurate flash flood susceptible maps of watershed areas not only in Iran but also other parts of the world.

ACS Style

Binh Thai Pham; Mohammadtaghi Avand; Saeid Janizadeh; Tran Van Phong; Nadhir Al-Ansari; L.S. Ho; Sumit Das; Hiep Van Le; Ata Amini; Saeid Khosrobeigi Bozchaloei; Faeze Jafari; Indra Prakash. GIS Based Hybrid Computational Approaches for Flash Flood Susceptibility Assessment. Water 2020, 12, 683 .

AMA Style

Binh Thai Pham, Mohammadtaghi Avand, Saeid Janizadeh, Tran Van Phong, Nadhir Al-Ansari, L.S. Ho, Sumit Das, Hiep Van Le, Ata Amini, Saeid Khosrobeigi Bozchaloei, Faeze Jafari, Indra Prakash. GIS Based Hybrid Computational Approaches for Flash Flood Susceptibility Assessment. Water. 2020; 12 (3):683.

Chicago/Turabian Style

Binh Thai Pham; Mohammadtaghi Avand; Saeid Janizadeh; Tran Van Phong; Nadhir Al-Ansari; L.S. Ho; Sumit Das; Hiep Van Le; Ata Amini; Saeid Khosrobeigi Bozchaloei; Faeze Jafari; Indra Prakash. 2020. "GIS Based Hybrid Computational Approaches for Flash Flood Susceptibility Assessment." Water 12, no. 3: 683.

Journal article
Published: 03 February 2020 in Sustainability
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Local scour depth at complex piers (LSCP) cause expensive costs when constructing bridges. In this study, a hybrid artificial intelligence approach of random subspace (RS) meta classifier, based on the reduced error pruning tree (REPTree) base classifier, namely RS-REPTree, was proposed to predict the LSCP. A total of 122 laboratory datasets were used and portioned into training (70%: 85 cases) and validation (30%: 37 cases) datasets for modeling and validation processes, respectively. The statistical metrics such as mean absolute error (MAE), root mean squared error (RMSE), correlation coefficient (R), and Taylor diagram were used to check the goodness-of-fit and performance of the proposed model. The capability of this model was assessed and compared with four state-of-the-art soft-computing benchmark algorithms, including artificial neural network (ANN), support vector machine (SVM), M5P, and REPTree, along with two empirical models, including the Florida Department of Transportation (FDOT) and Hydraulic Engineering Circular No. 18 (HEC-18). The findings showed that machine learning algorithms had the highest goodness-of-fit and prediction accuracy (0.885 < R < 0.945) in comparison to the other models. The results of sensitivity analysis by the proposed model indicated that pile cap location (Y) was a more sensitive factor for LSCP among other factors. The result also depicted that the RS-REPTree ensemble model (R = 0.945) could well enhance the prediction power of the REPTree base classifier (R = 0.885). Therefore, the proposed model can be useful as a promising technique to predict the LSCP.

ACS Style

Dieu Tien Bui; Ataollah Shirzadi; Ata Amini; Himan Shahabi; Nadhir Al-Ansari; Shahriar Hamidi; Sushant K. Singh; Binh Thai Pham; Baharin Bin Ahmad; Pezhman Taherei Ghazvinei. A Hybrid Intelligence Approach to Enhance the Prediction Accuracy of Local Scour Depth at Complex Bridge Piers. Sustainability 2020, 12, 1063 .

AMA Style

Dieu Tien Bui, Ataollah Shirzadi, Ata Amini, Himan Shahabi, Nadhir Al-Ansari, Shahriar Hamidi, Sushant K. Singh, Binh Thai Pham, Baharin Bin Ahmad, Pezhman Taherei Ghazvinei. A Hybrid Intelligence Approach to Enhance the Prediction Accuracy of Local Scour Depth at Complex Bridge Piers. Sustainability. 2020; 12 (3):1063.

Chicago/Turabian Style

Dieu Tien Bui; Ataollah Shirzadi; Ata Amini; Himan Shahabi; Nadhir Al-Ansari; Shahriar Hamidi; Sushant K. Singh; Binh Thai Pham; Baharin Bin Ahmad; Pezhman Taherei Ghazvinei. 2020. "A Hybrid Intelligence Approach to Enhance the Prediction Accuracy of Local Scour Depth at Complex Bridge Piers." Sustainability 12, no. 3: 1063.

Journal article
Published: 15 January 2020 in Water
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Risk of flash floods is currently an important problem in many parts of Vietnam. In this study, we used four machine-learning methods, namely Kernel Logistic Regression (KLR), Radial Basis Function Classifier (RBFC), Multinomial Naïve Bayes (NBM), and Logistic Model Tree (LMT) to generate flash flood susceptibility maps at the minor part of Nghe An province of the Center region (Vietnam) where recurrent flood problems are being experienced. Performance of these four methods was evaluated to select the best method for flash flood susceptibility mapping. In the model studies, ten flash flood conditioning factors, namely soil, slope, curvature, river density, flow direction, distance from rivers, elevation, aspect, land use, and geology, were chosen based on topography and geo-environmental conditions of the site. For the validation of models, the area under Receiver Operating Characteristic (ROC), Area Under Curve (AUC), and various statistical indices were used. The results indicated that performance of all the models is good for generating flash flood susceptibility maps (AUC = 0.983–0.988). However, performance of LMT model is the best among the four methods (LMT: AUC = 0.988; KLR: AUC = 0.985; RBFC: AUC = 0.984; and NBM: AUC = 0.983). The present study would be useful for the construction of accurate flash flood susceptibility maps with the objectives of identifying flood-susceptible areas/zones for proper flash flood risk management.

ACS Style

Binh Thai Pham; Tran Van Phong; Huu Duy Nguyen; Chongchong Qi; Nadhir Al-Ansari; Ata Amini; Lanh Si Ho; Tran Thi Tuyen; Hoang Phan Hai Yen; Hai-Bang Ly; Indra Prakash; Dieu Tien Bui. A Comparative Study of Kernel Logistic Regression, Radial Basis Function Classifier, Multinomial Naïve Bayes, and Logistic Model Tree for Flash Flood Susceptibility Mapping. Water 2020, 12, 239 .

AMA Style

Binh Thai Pham, Tran Van Phong, Huu Duy Nguyen, Chongchong Qi, Nadhir Al-Ansari, Ata Amini, Lanh Si Ho, Tran Thi Tuyen, Hoang Phan Hai Yen, Hai-Bang Ly, Indra Prakash, Dieu Tien Bui. A Comparative Study of Kernel Logistic Regression, Radial Basis Function Classifier, Multinomial Naïve Bayes, and Logistic Model Tree for Flash Flood Susceptibility Mapping. Water. 2020; 12 (1):239.

Chicago/Turabian Style

Binh Thai Pham; Tran Van Phong; Huu Duy Nguyen; Chongchong Qi; Nadhir Al-Ansari; Ata Amini; Lanh Si Ho; Tran Thi Tuyen; Hoang Phan Hai Yen; Hai-Bang Ly; Indra Prakash; Dieu Tien Bui. 2020. "A Comparative Study of Kernel Logistic Regression, Radial Basis Function Classifier, Multinomial Naïve Bayes, and Logistic Model Tree for Flash Flood Susceptibility Mapping." Water 12, no. 1: 239.

Journal article
Published: 13 January 2020 in Remote Sensing
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Mapping flood-prone areas is a key activity in flood disaster management. In this paper, we propose a new flood susceptibility mapping technique. We employ new ensemble models based on bagging as a meta-classifier and K-Nearest Neighbor (KNN) coarse, cosine, cubic, and weighted base classifiers to spatially forecast flooding in the Haraz watershed in northern Iran. We identified flood-prone areas using data from Sentinel-1 sensor. We then selected 10 conditioning factors to spatially predict floods and assess their predictive power using the Relief Attribute Evaluation (RFAE) method. Model validation was performed using two statistical error indices and the area under the curve (AUC). Our results show that the Bagging–Cubic–KNN ensemble model outperformed other ensemble models. It decreased the overfitting and variance problems in the training dataset and enhanced the prediction accuracy of the Cubic–KNN model (AUC=0.660). We therefore recommend that the Bagging–Cubic–KNN model be more widely applied for the sustainable management of flood-prone areas.

ACS Style

Himan Shahabi; Ataollah Shirzadi; Kayvan Ghaderi; Ebrahim Omidvar; Nadhir Al-Ansari; John J. Clague; Marten Geertsema; Khabat Khosravi; Ata Amini; Sepideh Bahrami; Omid Rahmati; Kyoumars Habibi; Ayub Mohammadi; Hoang Nguyen; Assefa M. Melesse; Baharin Bin Ahmad; Anuar Ahmad. Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier. Remote Sensing 2020, 12, 266 .

AMA Style

Himan Shahabi, Ataollah Shirzadi, Kayvan Ghaderi, Ebrahim Omidvar, Nadhir Al-Ansari, John J. Clague, Marten Geertsema, Khabat Khosravi, Ata Amini, Sepideh Bahrami, Omid Rahmati, Kyoumars Habibi, Ayub Mohammadi, Hoang Nguyen, Assefa M. Melesse, Baharin Bin Ahmad, Anuar Ahmad. Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier. Remote Sensing. 2020; 12 (2):266.

Chicago/Turabian Style

Himan Shahabi; Ataollah Shirzadi; Kayvan Ghaderi; Ebrahim Omidvar; Nadhir Al-Ansari; John J. Clague; Marten Geertsema; Khabat Khosravi; Ata Amini; Sepideh Bahrami; Omid Rahmati; Kyoumars Habibi; Ayub Mohammadi; Hoang Nguyen; Assefa M. Melesse; Baharin Bin Ahmad; Anuar Ahmad. 2020. "Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier." Remote Sensing 12, no. 2: 266.

Journal article
Published: 01 January 2020 in Sustainability
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In recent years, the intensification of drought and unsustainable management and use of water resources have caused a significant decline in the water level of the Urmia Lake in the northwest of Iran. This condition has affected the lake, approaching an irreversible point such that many projects have been implemented and are being implemented to save the natural condition of the Urmia Lake, among which the inter-basin water transfer (IBWT) project from the Zab River to the lake could be considered an important project. The main aim of this research is the evaluation of the IBWT project effects on the Gadar destination basin. Simulations of the geometrical properties of the river, including the bed and flow, have been performed, and the land cover and flood map were overlapped in order to specify the areas prone to flood after implementing the IBWT project. The results showed that with the implementation of this project, the discharge of the Gadar River was approximately tripled and the water level of the river rose 1 m above the average. In April, May, and June, about 952.92, 1458.36, and 731.43 ha of land adjacent to the river (floodplain) will be inundated by flood, respectively. Results also indicated that UNESCO’s criteria No. 3 (“a comprehensive environmental impact assessment must indicate that the project will not substantially degrade the environmental quality within the area of origin or the area of delivery”) and No. 5 (“the net benefits from the transfer must be shared equitably between the area of origin and the area of water delivery”) have been violated by implementing this project in the study area. The findings could help the local government and other decision-makers to better understand the effects of the IBWT projects on the physical and hydrodynamic processes of the Gadar River as a destination basin.

ACS Style

Dieu Tien Bui; Dawood Talebpour Asl; Ezatolla Ghanavati; Nadhir Al-Ansari; Saeed Khezri; Kamran Chapi; Ata Amini; Binh Thai Pham. Effects of Inter-Basin Water Transfer on Water Flow Condition of Destination Basin. Sustainability 2020, 12, 338 .

AMA Style

Dieu Tien Bui, Dawood Talebpour Asl, Ezatolla Ghanavati, Nadhir Al-Ansari, Saeed Khezri, Kamran Chapi, Ata Amini, Binh Thai Pham. Effects of Inter-Basin Water Transfer on Water Flow Condition of Destination Basin. Sustainability. 2020; 12 (1):338.

Chicago/Turabian Style

Dieu Tien Bui; Dawood Talebpour Asl; Ezatolla Ghanavati; Nadhir Al-Ansari; Saeed Khezri; Kamran Chapi; Ata Amini; Binh Thai Pham. 2020. "Effects of Inter-Basin Water Transfer on Water Flow Condition of Destination Basin." Sustainability 12, no. 1: 338.

Journal article
Published: 12 December 2019 in Sustainability
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Landslides affect properties and the lives of a large number of people in many hilly parts of Vietnam and in the world. Damages caused by landslides can be reduced by understanding distribution, nature, mechanisms and causes of landslides with the help of model studies for better planning and risk management of the area. Development of landslide susceptibility maps is one of the main steps in landslide management. In this study, the main objective is to develop GIS based hybrid computational intelligence models to generate landslide susceptibility maps of the Da Lat province, which is one of the landslide prone regions of Vietnam. Novel hybrid models of alternating decision trees (ADT) with various ensemble methods, namely bagging, dagging, MultiBoostAB, and RealAdaBoost, were developed namely B-ADT, D-ADT, MBAB-ADT, RAB-ADT, respectively. Data of 72 past landslide events was used in conjunction with 11 landslide conditioning factors (curvature, distance from geological boundaries, elevation, land use, Normalized Difference Vegetation Index (NDVI), relief amplitude, stream density, slope, lithology, weathering crust and soil) in the development and validation of the models. Area under the receiver operating characteristic (ROC) curve (AUC), and several statistical measures were applied to validate these models. Results indicated that performance of all the models was good (AUC value greater than 0.8) but B-ADT model performed the best (AUC= 0.856). Landslide susceptibility maps generated using the proposed models would be helpful to decision makers in the risk management for land use planning and infrastructure development.

ACS Style

Viet-Tien Nguyen; Trong Hien Tran; Ngoc Anh Ha; Van Liem Ngo; Al-Ansari Nadhir; Van Phong Tran; Huu Duy Nguyen; Malek M. A.; Ata Amini; Indra Prakash; L.S. Ho; Binh Thai Pham. GIS Based Novel Hybrid Computational Intelligence Models for Mapping Landslide Susceptibility: A Case Study at Da Lat City, Vietnam. Sustainability 2019, 11, 7118 .

AMA Style

Viet-Tien Nguyen, Trong Hien Tran, Ngoc Anh Ha, Van Liem Ngo, Al-Ansari Nadhir, Van Phong Tran, Huu Duy Nguyen, Malek M. A., Ata Amini, Indra Prakash, L.S. Ho, Binh Thai Pham. GIS Based Novel Hybrid Computational Intelligence Models for Mapping Landslide Susceptibility: A Case Study at Da Lat City, Vietnam. Sustainability. 2019; 11 (24):7118.

Chicago/Turabian Style

Viet-Tien Nguyen; Trong Hien Tran; Ngoc Anh Ha; Van Liem Ngo; Al-Ansari Nadhir; Van Phong Tran; Huu Duy Nguyen; Malek M. A.; Ata Amini; Indra Prakash; L.S. Ho; Binh Thai Pham. 2019. "GIS Based Novel Hybrid Computational Intelligence Models for Mapping Landslide Susceptibility: A Case Study at Da Lat City, Vietnam." Sustainability 11, no. 24: 7118.

Journal article
Published: 09 December 2019 in Applied Sciences
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The present research was carried out to study drought and its effects upon water resources using remote sensing data. To this end, the tropical rainfall measuring mission (TRMM) satellite precipitation, the synoptic stations, and fountain discharge data were employed. For monitoring of drought in the study area, in Kermanshah province, Iran, the monthly precipitation data of the synoptic stations along with TRMM satellite precipitation datasets were collected and processed in the geographic information system (GIS) environment. Statistical indicators were applied to evaluate the accuracy of TRMM precipitation against the meteorological stations’ data. Standardized precipitation index, SPI, and normalized fountain discharge were used in the monitoring of drought conditions, and fountains discharge, respectively. The fountains were selected so that in addition to enjoying the most discharge rates, they spread along the study area. The evaluation of precipitation data showed that the TRMM precipitation data were of high accuracy. Studies in temporal scale are indicative of the strike of drought in this region to the effect that for most months of the year, frequency and duration in dry periods are much more than in wet periods. As for seasonal scales, apart from winter, the frequency and duration of drought in spring and autumn have been longer than in wet years. Moreover, the duration of these periods was different. A comparison between the results of changes in fountain discharges and drought index in the region has verified that the drought has caused a remarkable decline in the fountain discharges.

ACS Style

Ata Amini; Abdolnabi Abdeh Kolahchi; Nadhir Al-Ansari; Mehdi Karami Moghadam; Thamer Mohammad. Application of TRMM Precipitation Data to Evaluate Drought and Its Effects on Water Resources Instability. Applied Sciences 2019, 9, 5377 .

AMA Style

Ata Amini, Abdolnabi Abdeh Kolahchi, Nadhir Al-Ansari, Mehdi Karami Moghadam, Thamer Mohammad. Application of TRMM Precipitation Data to Evaluate Drought and Its Effects on Water Resources Instability. Applied Sciences. 2019; 9 (24):5377.

Chicago/Turabian Style

Ata Amini; Abdolnabi Abdeh Kolahchi; Nadhir Al-Ansari; Mehdi Karami Moghadam; Thamer Mohammad. 2019. "Application of TRMM Precipitation Data to Evaluate Drought and Its Effects on Water Resources Instability." Applied Sciences 9, no. 24: 5377.

Research article
Published: 13 September 2019 in Journal of Crop Science and Biotechnology
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Soil, available water and nitrogen are limiting factors that restrict the production of wheat in arid lands of Iran. To evaluate the effects of nitrogen on yield and drought tolerance of rainfed wheat by stress susceptibility indices, a two-year field experiment was conducted under two irrigation conditions. Treatments consist of three nitrogen timing, as main plots including total nitrogen in fall, 2/3 in the fall+1/3 in the spring, and 1/2 in the fall+1/2 in the spring. The five nitrogen rates with 0, 30, 60, 90, and 120 kg.ha−1 of urea were applied as sub-plots. The experiments were conducted using randomized complete block designs in a split-plot arrangement with three replications during the 2012–2013 and 2013–2014 cropping seasons. The results showed that yield in stress and non-stress conditions were significantly and positively correlated with most of the drought stress indices (P < 0.01) and negatively correlated with the Stress Susceptibility Index, SSI, (P < 0.05). The Tolerance Index (STI) was the best index for drought tolerance. Results of nitrogen treatment showed that nitrogen increased drought tolerance, while applying 60 kg.ha−1 nitrogen in the fall was with the highest yield in wheat.

ACS Style

Mohammad Hossein Sedri; Ata Amini; Ahmad Golchin. Evaluation of Nitrogen Effects on Yield and Drought Tolerance of Rainfed Wheat using Drought Stress Indices. Journal of Crop Science and Biotechnology 2019, 22, 235 -242.

AMA Style

Mohammad Hossein Sedri, Ata Amini, Ahmad Golchin. Evaluation of Nitrogen Effects on Yield and Drought Tolerance of Rainfed Wheat using Drought Stress Indices. Journal of Crop Science and Biotechnology. 2019; 22 (3):235-242.

Chicago/Turabian Style

Mohammad Hossein Sedri; Ata Amini; Ahmad Golchin. 2019. "Evaluation of Nitrogen Effects on Yield and Drought Tolerance of Rainfed Wheat using Drought Stress Indices." Journal of Crop Science and Biotechnology 22, no. 3: 235-242.

Journal article
Published: 15 August 2019 in Water
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The effects of changes in the angle of pool impact plate, plunging depth, and discharge upon the dynamic pressure caused by ski-jump buckets were investigated in the laboratory. Four impact plate angles and four plunging depths were used. Discharges of 67, 86, 161, and 184 L/s were chosen. For any discharge, plunging depth and impact plate angle were regulated, and dynamic pressures were measured by a transducer. The results showed that with the increase in the ratio of drop length of the jet to its break-up length (H/Lb), and with an increase in the impact plate angle, the mean dynamic pressure coefficient decreased. An inspection of the plunging depth (Y) ratio to the initial thickness of the jet (Bj) revealed that when Y/Bj > 3, the plunging depth of the downstream pool reduced dynamic pressure. At the angle of 60°, the dynamic pressure coefficient due to increasing in plunging depth varied from 34% to 95%.

ACS Style

Mehdi Karami Moghadam; Ata Amini; Marlinda Abdul Malek; Thamer Mohammad; Hasan Hoseini. Physical Modeling of Ski-Jump Spillway to Evaluate Dynamic Pressure. Water 2019, 11, 1687 .

AMA Style

Mehdi Karami Moghadam, Ata Amini, Marlinda Abdul Malek, Thamer Mohammad, Hasan Hoseini. Physical Modeling of Ski-Jump Spillway to Evaluate Dynamic Pressure. Water. 2019; 11 (8):1687.

Chicago/Turabian Style

Mehdi Karami Moghadam; Ata Amini; Marlinda Abdul Malek; Thamer Mohammad; Hasan Hoseini. 2019. "Physical Modeling of Ski-Jump Spillway to Evaluate Dynamic Pressure." Water 11, no. 8: 1687.

Journal article
Published: 15 July 2019 in Applied Sciences
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We proposed an innovative hybrid intelligent approach, namely, the multiboost based naïve bayes trees (MBNBT) method for the spatial prediction of landslides in the Mu Cang Chai District of Yen Bai Province, Vietnam. The MBNBT, which is an ensemble of the multiboost (MB) and naïve bayes trees (NBT) base classifier, has rarely been applied for landslide susceptibility mapping around the world. For the modeling, we selected 248 landslide locations in the hilly terrain of the study area. Fifteen landslide conditioning factors were selected for the construction of the database based on the one-R attribute evaluation (ORAE) technique. Model validation was done using statistical metrics, namely, sensitivity, specificity, accuracy, mean absolute error (MAE), root mean square error (RMSE), and the area under the receiver operating characteristics curve (AUC). Performance of the hybrid model was evaluated and compared with popular soft computing benchmark models, namely, multiple perceptron neural network (MLPN), Support Vector Machines (SVM), and single NBT. Results indicated that the proposed MBNBT (AUC = 0.824) model outperformed the popular models, namely, the MLPN (AUC = 0.804), SVM (AUC = 0.804), and NBT (AUC = 0.800) models. Analysis of the model results also suggested that the MB meta classifier ensemble model could enhance the prediction power of the NBT model. Therefore, the MBNBT is a suitable method for the assessment of landslide susceptibility in landslide prone areas.

ACS Style

Phong Tung Nguyen; Tran Thi Tuyen; Ataollah Shirzadi; Binh Thai Pham; Himan Shahabi; Ebrahim Omidvar; Ata Amini; Hersh Entezami; Indra Prakash; Tran Van Phong; Ba Thao Vu; Tran Thanh; Lee Saro; Dieu Tien Bui. Development of a Novel Hybrid Intelligence Approach for Landslide Spatial Prediction. Applied Sciences 2019, 9, 2824 .

AMA Style

Phong Tung Nguyen, Tran Thi Tuyen, Ataollah Shirzadi, Binh Thai Pham, Himan Shahabi, Ebrahim Omidvar, Ata Amini, Hersh Entezami, Indra Prakash, Tran Van Phong, Ba Thao Vu, Tran Thanh, Lee Saro, Dieu Tien Bui. Development of a Novel Hybrid Intelligence Approach for Landslide Spatial Prediction. Applied Sciences. 2019; 9 (14):2824.

Chicago/Turabian Style

Phong Tung Nguyen; Tran Thi Tuyen; Ataollah Shirzadi; Binh Thai Pham; Himan Shahabi; Ebrahim Omidvar; Ata Amini; Hersh Entezami; Indra Prakash; Tran Van Phong; Ba Thao Vu; Tran Thanh; Lee Saro; Dieu Tien Bui. 2019. "Development of a Novel Hybrid Intelligence Approach for Landslide Spatial Prediction." Applied Sciences 9, no. 14: 2824.

Journal article
Published: 01 May 2019 in Water Resources
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Roughness coefficient, also called Manning’s coefficient, is one of the most important hydraulic parameters in the rivers. This coefficient, in addition to the flow conditions, depends on streambed characteristics such as type and density of vegetation. In this study, a physical model in a flume with 7 m length, 0.25 m width and 0.25 m height was conducted to evaluate the streambed roughness coefficient and consequently the discharge passing from waterways. Flume bed was filled using uniform sediment with median grain diameter of 1.9 mm, variation coefficient of 1.4 mm and a thickness of 0.4 m. Roughness coefficient variation in the slopes of 0.2, 0.4 ,and 0.6%, discharges of 4, 6, and 8 L/s and vegetation cover densities as 0, 12, 25, and 50% were investigated. To simulate the covering of streambed, vegetation scrub was used in the experiments. The results showed that by increasing the density of vegetation, roughness coefficient increases while with increasing flow velocity, slope and Froude number decreases. By analyzing the data from this study, streambed roughness coefficient was obtained in terms of different variables as applicable relationships for different conditions of flow and streambed. The results of this study with quantifying the effects of various parameters on the roughness coefficient can be used by water engineers.

ACS Style

Hosna Shafaei; Ata Amini; Azim Shirdeli. Assessing Submerged Vegetation Roughness in Streambed under Clear Water Condition Using Physical Modeling. Water Resources 2019, 46, 377 -383.

AMA Style

Hosna Shafaei, Ata Amini, Azim Shirdeli. Assessing Submerged Vegetation Roughness in Streambed under Clear Water Condition Using Physical Modeling. Water Resources. 2019; 46 (3):377-383.

Chicago/Turabian Style

Hosna Shafaei; Ata Amini; Azim Shirdeli. 2019. "Assessing Submerged Vegetation Roughness in Streambed under Clear Water Condition Using Physical Modeling." Water Resources 46, no. 3: 377-383.

Book chapter
Published: 24 April 2019 in Climate Change and Global Warming
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ACS Style

Ata Amini. Introductory Chapter: Lake Urmia - A Witness to the Simultaneous Effects of Human Activities, Climate Change, and Global Warming. Climate Change and Global Warming 2019, 1 .

AMA Style

Ata Amini. Introductory Chapter: Lake Urmia - A Witness to the Simultaneous Effects of Human Activities, Climate Change, and Global Warming. Climate Change and Global Warming. 2019; ():1.

Chicago/Turabian Style

Ata Amini. 2019. "Introductory Chapter: Lake Urmia - A Witness to the Simultaneous Effects of Human Activities, Climate Change, and Global Warming." Climate Change and Global Warming , no. : 1.