Abbas Abbasi; Keivan Khalili; Javad Behmanesh; Akbar Shirzad
Abstract
The correct and accurate estimation of river flow can play an important role in reducing the effects of flood damage. In this research, Gene Expression Programming (GEP) model and Bayesian Network (BN) were used to predict daily flow of Mahabad River in Urmia Lake Basin. Accordingly, four input models ...
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The correct and accurate estimation of river flow can play an important role in reducing the effects of flood damage. In this research, Gene Expression Programming (GEP) model and Bayesian Network (BN) were used to predict daily flow of Mahabad River in Urmia Lake Basin. Accordingly, four input models with a delay of one to four days used to estimate daily flow at time t+1 over a 23-years period and 75% of data was used to train the models and 25% of the remaining data was used for the test stage. Results showed that the best model in both methods was the input pattern with three-time lags. Also, based on the correlation coefficient (R), Root Mean Square Error (RMSE) and Nash-Sutcliffe (E) coefficient in the test stage of the GEP method with R=0.902, RMSE=2.71(m3s-1) and E=0.812 compared to the BN method with R=0.905, RMSE=2.679(m3s-1( and E=0.817 is more accurate. In general, both methods have acceptable accuracy and are they relatively similar, but because of the simpler modeling, Bayesian Network method can be used as an efficient method for predicting river flow.
Parvaneh Mahmudi; Baharak Motamedvaziri; majid hosseini; Hasan Ahmadi; Ata Amini
Abstract
This study focuses on simulation and management the various hydrological responses to climatic changes. The semi-distributed hydrologic model SWAT (soil and water assessment tool) was used to evaluate runoff and water balance due to climate changes in Siminehroud and Zarrinehroud watersheds. The simulation ...
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This study focuses on simulation and management the various hydrological responses to climatic changes. The semi-distributed hydrologic model SWAT (soil and water assessment tool) was used to evaluate runoff and water balance due to climate changes in Siminehroud and Zarrinehroud watersheds. The simulation period was selected between 1990 and 2014. The assessment results in the calibration and validation periods using the NS and R2 obtained 0.75, on average. Using statistical multisite downscaling of LARS-WG climatic models MIROC-ESM-CHEM، GFDL-ESM2M and NorESM1-M the future climatic condition entered to the model using two optimistic RCP2.6 and pessimistic RCP8.5 scenarios. The largest changes in runoff in the upcoming period, May, reduced by 2.4 m3 s-1 and in April, increased by 1.49 m3 s-1 in the optimistic scenario. In RCP8.5 pessimistic scenario in May and June, also the highest runoff was observed. The rate of actual monthly evaporation will increase in the optimistic scenario up to 3 mm and in the pessimistic scenario up to 8 mm increase will have a negative impact on the available water resources in the watershed. With estimation the climate changes and its effect on the stream flow discharge is possible performing a suitable management in Siminehroud and Zarrinehroud watersheds.
Abbas Abbasi; Keivan Khalili; Javad Behmanesh; Akbar Shirzad
Abstract
Awareness of the drought status and the prediction of its future conditions play an important role in water resources management programs. In this regard, rainfall and temperature variables have a great influence on the severity and duration of this phenomenon. Regarding the status of the Urmia Lake ...
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Awareness of the drought status and the prediction of its future conditions play an important role in water resources management programs. In this regard, rainfall and temperature variables have a great influence on the severity and duration of this phenomenon. Regarding the status of the Urmia Lake in recent years and the water stress in its watershed, in this study, the drought situation in Saghez synoptic station as one of the important stations of this basin in different time-scales using the Standardized Evapotranspiration Index (SPEI) and SVM model with three linear, polynomial, and radial basis function and Bayesian network (BN) models, were investigated. For this purpose, the SPEI index in the short-term (1 and 3 months), mid-term (6, 12-months) and long-term (24 and 48-months) during the 49-year statistical period for monitoring the drought status at this station was used. Results showed that there was 8 prolonged periods of drought for the years 1962-1968, 1972-1974, 1978-1979, 1980-1982, 1983-1984, 1986-1987, 1999-2003 and 2007-2009 during the statistical period. Then SPEI values were applied to five input models with a delay of 1 to 5 months and SVM and BN models were used to predict drought. The results showed that in both methods, the model with 5-time delay had better performance and the linear basic function in the SVM method was more accurate than the other two functions. Also, the predictive accuracy of these models is directly correlated with increasing the SPEI scale, so that the correlation coefficient in the Bayesian network method at the test stage ranged from 0.174 in 1-month time-scale to 0.985 on a 48-month time-scale and in the SVM method with a linear basic function, it has risen from 1.149 to 0.983.
Mohammad NazeriTahrudi; Yousef Ramezani
Abstract
Estimating return period of hydrological processes such as flood flow, maximum discharge, drought and etc, is related directly to selecting a suitable probability distribution function. With selecting a proper distribution function, estimated return period will be more close to actual data and error ...
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Estimating return period of hydrological processes such as flood flow, maximum discharge, drought and etc, is related directly to selecting a suitable probability distribution function. With selecting a proper distribution function, estimated return period will be more close to actual data and error will be reduced. So, it should be tried to select the best probability distribution function. In this study, using daily discharge of western rivers of Urmia Lake, as well as the annual mean method, the data of the drought volume of these rivers were extracted. Several distributions from each of the continuous distributions, such as the continuous distribution of generalized maximums and wakeby, the continuous non-zero Erlang distribution, the continuous Johnson SB distribution, and the continuous boundary of Normal distribution for fitting the data of the dry volume of the western rivers Lake Urmia was used in the 38-year statistical period. Anderson-Darling and Kolmogorov-Smirnov tests used to compare results of each distribution. Also correlations between the data obtained from the sample data and statistical models computed. The results of the frequency distribution of the data of the three rivers showed that among the distributions of the continuous group, the advanced statistical distributions of Wakeby and Johnson SB had the best distribution and also had better performance than the conventional statistical methods.
