Maryam Khosravi; Ali Salajegheh; Mohammad Mahdavi; Mohsen Mohseni Saravi
Abstract
It is necessary to use empirical models for estimating of instantaneous peak discharge because of deficit of gauging stations in the country. Hence, at present study, two models including Artificial Neural Networks and nonlinear multivariate regression were used to predict peak discharge in Taleghan ...
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It is necessary to use empirical models for estimating of instantaneous peak discharge because of deficit of gauging stations in the country. Hence, at present study, two models including Artificial Neural Networks and nonlinear multivariate regression were used to predict peak discharge in Taleghan watershed. Maximum daily mean discharge and corresponding daily rainfall, one day antecedent and five days antecedent rainfall, sum of five days antecedent rainfall and monthly mean temperature were extracted in Gatehdeh, Mehran, Alizan, Joestan and Gelinak hydrological units and entered into neural network model (from upstream to downstream, respectively). The feed forward network was used with one hidden layer and back-propagation algorithm. Then, the models were trained, validated and tested in three stages. The observed and estimated peak discharges of the models were compared based on RMSE and r. The results showed that neural network has better performance than nonlinear multivariate regression.
Maryam Azarakhshi; Behnoush Farokhzadeh; Mohammad Mahdavi; Hossein Arzani; Hassan Ahmadi
Abstract
Iran is located in dry belt of the earth and always involved with drought in different sections. Drought has already caused many losses to natural plant cover, agriculture and human society. For drought monitoring, we can use some drought indecies. In this research, the Standard Index of Annual Precipitation)SIAP),Sandardized ...
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Iran is located in dry belt of the earth and always involved with drought in different sections. Drought has already caused many losses to natural plant cover, agriculture and human society. For drought monitoring, we can use some drought indecies. In this research, the Standard Index of Annual Precipitation)SIAP),Sandardized Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI) were used for assessment of drought effects on rangeland plant production. The research area is located in Qom province that contains eight rangeland sites. Plant production and soil factors were measured in rangeland readiness period from 1997-1998 to 2005-2006 annualy. Regression techniques were used between drought indices and total production and also production of different vegetation forms in seven time scales (early March to late July (growth season) and early February to late July (growth season and the previous month), March to June, March to May, March to April and March (start of growth season). The best drought index was then selected based on the highest correlation coefficient and lowest standard error. The result showed that the best drought indices in Qom rangelands are SPI-3, PDSI, SPI-24 and SPI-6, respectively. Also the most significant time step was resulted growth season and specially early stage of growth season.
v Payravand; ali Salajegheh; mohamad Mahdavi; mohamad ali Zare Chahouki
Volume 63, Issue 2 , September 2010, , Pages 131-18
Abstract
One of the most appropriate approaches for flood forecasting is using peak discharge data of hydrometric stations in each region. However, lack of such stations or short duration of data in most parts of the country, make it necessary to use some alternative methods in order to estimate the flood discharge ...
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One of the most appropriate approaches for flood forecasting is using peak discharge data of hydrometric stations in each region. However, lack of such stations or short duration of data in most parts of the country, make it necessary to use some alternative methods in order to estimate the flood discharge properly. One of these approaches is regional flood analysis method that in a region using observation discharge data in separate points, it calculates relevant regional flood models. These approaches give us possibility at a region without gauging station with similar and homogenous hydrological condition to estimate flood discharge for different return periods with acceptable accuracy. In this research three methods of regional flood analysis including index flood, multivariate regression and hybrid method were considered in 20 watersheds of central Alborz region. After taking into account, the hypothesis and limitations of each method, the results were compared with observed flood discharges using RMSE and MBE. Considering the hypothesis and validation of multiple regression model indicated it is not appropriate. Finally Index Flood method in return periods of 2, 5 and 10 years and hybrid method in return periods of 50 and 100 years proved higher accuracy in the whole region and no difference between these two methods in return period of 25 were shown.
A. Afzali; M. Mahdavi; M. A. Zare Chahoki
Volume 62, Issue 2 , October 2009, , Pages 187-196
Abstract
The most precise and simple method of evaporation measurement is application of pans in which class A pan is used in Iran. In contrast, there are many empirical methods which are used for estimating the evapotraspiration. In this study, Thornthwaite method was used due to the simplicity of its parameters ...
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The most precise and simple method of evaporation measurement is application of pans in which class A pan is used in Iran. In contrast, there are many empirical methods which are used for estimating the evapotraspiration. In this study, Thornthwaite method was used due to the simplicity of its parameters and then we tried to use it for evaluating evapotranspiration by changing it's parameters. Because of its unproper estimation in Iran's climatic conditions in comparison with pan data we concluded that a considerable percentage of monthly evaporation with thornthwaite method with corrected alfa in different stations, have a good conformity with monthly evaporation measured with class A pan in the error range of 30% and in we added 0.5 unit to the exponent of Thornthwaite formula to having acceptable results for arid and semi arid region. In fact, the formula is not efficient in measurement of evapotranspiration without correction.
B. Motamedvaziri; H. Ahmadi; M. Mahdavi; F. Sharifi; N. Javaheri
Volume 62, Issue 2 , October 2009, , Pages 283-298
Abstract
Estimation of river sediment load is one of the most important issues in design of hydraulic structures, investigating water quality, conserving fish habitat, estimating erosion and determining watershed management effects. There are two methods for estimating sediment load: empirical and hydrological ...
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Estimation of river sediment load is one of the most important issues in design of hydraulic structures, investigating water quality, conserving fish habitat, estimating erosion and determining watershed management effects. There are two methods for estimating sediment load: empirical and hydrological methods. Existence of numerous empirical methods for estimation of river sediment load and a wide range of calibration coefficients shows that a suitable analytical or empirical method does not yet exist to accurately estimate the sediment load. Also, hydrological methods are not able to recognize and separate the specific data measuring conditions and they can not show the temporal variation of sediment loads. In spite of these problems, nowadays, researchers are using Artificial Intelligence methods such as Fuzzy Logic. In this study, the measured suspended sediment load at hydrometric station of Sarcham located on Zanjanroud river is analyzed using USBR and FAO methods (common hydrological methods). Furthermore, suspended sediment load are estimated with a model developed based on Fuzzy Logic rules. In order to estimate suspended load using fuzzy method, one method named Supervised Fuzzy C- mean Clustering Method, is used. Then the results of hydrological and fuzzy methods are compared. The results showed that the temporal variation of sediment loads can be analyzed using a fuzzy method. Also the results obtained using the fuzzy method in comparison with the corresponding values obtained using the usual hydrological methods shows a better correlation with the observed values.
H. Saadati; F. Sharifi; M. Mahdavi; H. Ahmadi; M. Mohseni Saravi
Volume 62, Issue 1 , June 2009
Abstract
The main structure of this study includes; isotopic tracer evaluation and measuring, to identify and origin of groundwater recharge, contributions determine of diffused recharge (DR) and concentrated recharge (CR) as well as determine drought and wet periods in Hashtgerd plain. The hydrochemical study ...
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The main structure of this study includes; isotopic tracer evaluation and measuring, to identify and origin of groundwater recharge, contributions determine of diffused recharge (DR) and concentrated recharge (CR) as well as determine drought and wet periods in Hashtgerd plain. The hydrochemical study which involved collection and analysis of water samples from the deep and dug wells, springs, tap water and rainwater showed that the rainwater is little source of groundwater recharge. The isotopical study aimed to determine the origin of the groundwater bodies and to offer support for the hydrochemical analysis. To achieve this purpose samples analyzed for H2 and O18 and data was quoted from literature about the isotopic composition of precipitation. The study shows that the isotopic composition during the rainy season ranges for ?O18 between -6/05 ‰ and -6/92 ‰ and for ?H2 between-45/92 ‰ and -52/27 ‰. The changes in ?O18 are correlated with those of ?H2 with R2 =0.9 that was similar to GMWL line. proving their meteoric origin. Cluster analysis supported by the Hierarchical Cluster Analyze, Chebychev and Mann-Whitney tests classified the analyzed rivers water samples into two main groups: the first cluster was included Kordan, Aqasht, Sorheh and Khor rivers. Because of the low runoff and high infiltration these rivers are recharged through groundwater. The second cluster was consisted Valian, Fashand and Hiv-shalamzar rivers. Because of the low infiltration these rivers are recharged through runoff. Cluster Analysis shows that the samples of groundwater of Hashtgerd plain were divided into three clusters. The first cluster was included west and north-east of Hashtgerd plain (Nazarabad, Hashtgerd town, Baraghan and Kordan) were recharged through surface water and rainfall. The second cluster was included north and center of Hashtgerd plain were recharged through surface and groundwater. The third cluster was included south-west and south-east of Hashtgerd plain which were recharged through groundwater. The results show that concentrated recharge (CR) supply groundwater more than diffused recharge (CR). Concentrated recharge was performed by watersheds and flood spreading. Using isotopic method, mean values of ? O18 and ? H2 in a mass-balance equation, the relative contributions of diffused recharge (DR) and concentrated recharge (CR), to groundwater were estimated to be 78 درصد and 22 درصد, respectively. According to results of this study, groundwater resource level decrease and there is a drought period in Hashtgerd plain.
A. Salajegheh; A. Fathabadi; M. Mahdavi
Volume 62, Issue 1 , June 2009
Abstract
Rainfall-runoff is one of complex hydrological processes that is affected by a variety of physical and hydrological factors. In this study statistical method ARMAX model, neural network, neuro-fuzzy (ANFIS subtractive clustering and grid partition) and two hybrid models of this methods were used to simulate ...
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Rainfall-runoff is one of complex hydrological processes that is affected by a variety of physical and hydrological factors. In this study statistical method ARMAX model, neural network, neuro-fuzzy (ANFIS subtractive clustering and grid partition) and two hybrid models of this methods were used to simulate rainfall-runoff and prediction of streamflow. In each method optimum structure was determined then, streamflow forecasted using the best model. The results showed that hybrid methods have better application than single models and artificial intelligent has better application than linear ARMAX model due to nonlinearity of rainfall-runoff process. In this study all methods showed relatively suitable application but ANFIS method with subtractive clustering is suggested for modeling rainfall-runoff and streamflow prediction.
A. Fathzadeh; M. Mahdavi; R.C. Bales; A. A. Abkar; Askari Shirazi
Volume 62, Issue 1 , June 2009
Abstract
In highland watersheds, runoff generated by snow melting plays an important role in stream water supply. SRM (Snowmelt Runoff Model) is a hydrologic model which simulates and predicts daily flow in mountain watersheds dominated by snow melting process. The SRM is based on the degree-day procedure which, ...
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In highland watersheds, runoff generated by snow melting plays an important role in stream water supply. SRM (Snowmelt Runoff Model) is a hydrologic model which simulates and predicts daily flow in mountain watersheds dominated by snow melting process. The SRM is based on the degree-day procedure which, is a widely used method but does not consider physical factors. In the current research, the factor of radiation was added to the degree-day model to develop a simple energy balance equation. Daily average radiation was calculated by albedo, shortwave and longwave radiation, daily maximum and minimum temperature and relative humidity. The snow covered area (SCA) was obtained from daily MODIS images. The developed model was applied to the stream flow data of Karaj Basin located in northern Iran and the results revealed that the coefficient of determination of the observed and estimated data was 0.677 while the differences between estimated and observed volume of runoff was -5.58%. Therefore, the radiation based of SRM increased the coefficient of determination of estimated and simulated discharge about 9.3%.
