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Neda Khanmohammadi Hossein Rezaie Majid Montaseri Javad Behmanesh 《Environmental Earth Sciences》2017,76(15):540
Temporal changes of meteorological variables can affect reference evapotranspiration (ET0). The goal of the present research is to analyze the changes of ET0 and identify the impact of effective meteorological parameters to the changes of ET0. For this purpose, daily meteorological data recorded in 30 synoptic stations of Iran during 1960–2014 were used. The annual and seasonal values of ET0 were calculated by the recorded data. To calculate ET0, FAO56 Penman–Monteith method (standard method) was used. The annual and seasonal trends of ET0 and its eight effective parameters were analyzed. Then the contributions of effective parameters changes on ET0 were determined. To analyze ET0 trend at annual and seasonal scales, two common methods, Spearman’s Rho and Mann–Kendall tests, were used. The R 2 = 0.99 showed that the results of the mentioned methods were similar and on the basis of T-statistic <0.057, their difference was not significant (95% confidence level). Therefore, only one method’s results (Spearman’s Rho) were reported. On the basis of Spearman’s Rho results, the annual and seasonal values of ET0 had negative trend in most of arid and semi-arid stations while the trend of this parameter was positive in humid and very humid stations. At annual and seasonal scales, decreasing in wind speed (W), temperature (T), sunshine hours (n), minimum temperature (TN), dew point temperature (TD), maximum temperature (TX), saturation vapor pressure deficit (SVPD) and solar radiation (RS) was observed in 58, 54, 39, 43, 56, 65, 65 and 37% studied stations, respectively. In many scales, the results showed that TX and W were the most effective meteorological variables on ET0 changes and then SVPD was located in second step in arid and semi-arid stations. In humid and very humid stations, W was the first effective parameter at all scales, except autumn. 相似文献
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Application of different data-driven methods for the prediction of total dissolved solids in the Zarinehroud basin 总被引：3，自引：3，他引：0
Sarvin Zaman Zad Ghavidel Majid Montaseri 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(8):2101-2118
A total dissolved solid (TDS) is an important indicator for water quality assessment. Since the composition of mineral salts and discharge affects the TDS of water, it is important to understand the relationship of mineral salt composition with TDS. In the present study, four artificial intelligence approaches, namely artificial neural networks (ANNs), two different adaptive-neuro-fuzzy inference system (ANFIS) including ANFIS with grid partition (ANFIS-GP) and ANFIS with subtractive clustering (ANFIS-SC), and gene expression programming (GEP) were applied to forecast TDS in river water over a period of 18 years at seven different sites. Five different GEP, ANFIS and ANN models comprising various combinations of water quality and flow variables from Zarinehroud basin in northwest of Iran were developed to forecast TDS variations. The correlation coefficient (R), root mean square error and mean absolute error statistics were used for evaluating the accuracy of models. Based on the comparisons, it was found that the GEP, ANFIS-GP, ANFIS-SC and ANN models could be employed successfully in forecasting TDS variations. A comparison was made between these artificial intelligence approaches which emphasized the superiority of GEP over the other intelligent models. 相似文献
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Drought monitoring is carried out using various drought indices, including SPI, to generate time series of dry and wet periods. Furthermore, the dispersion of dry and wet periods was embossed with different intensities (high, medium, and low) over the data record years. Although these results were very necessary for planning and predicting future droughts, it appeared that the application of any trend over dry and wet periods could provide more accurate and unbiased or safer predictions in terms of analysis process. Generally, most of the researchers believed that the results of a drought trend analysis have been influenced by short-term persistence or significant autocorrelation with different lags on drought event time series and the mentioned impact should be preferably removed. Accordingly, drought monitoring was accomplished using SPI and PNPI drought indices to extract time series of dry and wet periods in terms of 50-year (1965–2014) annual rainfall data of 40 synoptic stations over Iran. Having used the basic and modified Mann–Kendall nonparametric tests, it was attempted to analyze the trend of dry and wet periods extracted from mentioned indices. The results represent the relative advantage of using the modified Mann–Kendall test in drought trend analysis. Furthermore, it was shown that the trend of dry and wet periods was negative in the majority of selected stations and that this trend was significant at 95% confidence level in northwest of Iran. Also, the results indicated the similar performance of SPI and PNPI indices in trend analysis of dry and wet periods.
相似文献5.
Neda?Khanmohammadi Hossein?Rezaie Majid?Montaseri Javad?BehmaneshEmail author 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(3):661-673
Trend analysis of reference evapotranspiration (ET0), as a key factor in irrigation programming, has an important role in water resources management. Many parameters affect ET0 and their variations can change its values. In this paper, the effect of temporal variation of meteorological variables including wind speed, temperature, solar radiation and saturation vapor pressure deficit on temporal variations of ET0 was analyzed. Trend analysis of ET0 and its more effective meteorological parameters was accomplished in 30 synoptic stations which are located in Iran using Spearman’s Rho test. The multiple linear regressions were also used to determine the relationship between ET0 trend and the trend of its more effective parameters. Increasing and decreasing trends in ET0 were obtained at annual and seasonal scales. Many studied stations which had decreasing trend in the annual and seasonal periods have been located in the arid climates while all stations which have been located in humid and very-humid climates, had an increasing trend in annual and seasonal periods. The trend results in studied variables showed that annual and seasonal values of wind speed, temperature and saturation vapor pressure deficit decrease however the values of solar radiation increases in most studied stations. Multiple linear regressions results demonstrated that ET0 trend can be calculated by the trend of two more effective variables including wind speed and saturation vapor pressure deficit. 相似文献
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In recent years, the bivariate frequency analysis of drought duration and severity using independent drought events and copula functions has been under extensive application. Meanwhile, emphasis on the procedure of independent drought data collection leads to the omission of the actual potential of short-term extreme droughts within a long-term independent drought. However, a long-term individual continuous drought as an Unconnected Drought Runs can be considered as a combination of short-term Connected Drought Runs. Thus, an advanced and new procedure of data collection in the bivariate drought characteristics analysis has been developed in this study. The results indicated a high relative advantage of the new proposed procedure in analysing bivariate drought characteristics (i.e., drought duration and severity frequency analysis). This advantage has been reflected in the more appropriate determination of the best copula and significant reduction in the uncertainty of bivariate drought frequency analysis. 相似文献
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Rahim Bagheri Arash Nadri Ezzat Raeisi G. A. Kazemi H. G. M. Eggenkamp Ali Montaseri 《Environmental Earth Sciences》2014,72(4):1055-1072
The Kangan Permo-Triassic brine aquifer and the overlying gas reservoir in the southern Iran are located in Kangan and Dalan Formations, consisting dominantly of limestone, dolomite, and to a lesser extent, shale and anhydrite. The gasfield, 2,900 m in depth and is exploited by 36 wells, some of which produce high salinity water. The produced water gradually changed from fresh to saline, causing severe corrosion in the pipelines and well head facilities. The present research aims to identify the origin of this saline water (brine), as a vital step to manage saline water issues. The major and minor ions, as well as δ2H, δ18O and δ37Cl isotopes were measured in the Kangan aquifer water and/or the saline produced waters. The potential processes causing salinity can be halite dissolution, membrane filtration, and evaporation of water. The potential sources of water may be meteoric, present or paleo-seawater. The Na/Cl and I/Cl ratios versus Cl? concentration preclude halite dissolution. Concentrations of Cl, Na, and total dissolved solid were compared with Br concentration, indicating that the evaporated ancient seawater trapped in the structure is the cause of salinization. δ18O isotope enrichment in the Kangan aquifer water is due to both seawater evaporation and interaction with carbonate rocks. The δ37Cl isotope content also supports the idea of evaporated ancient seawater as the origin of salinity. Membrane filtration is rejected as a possible source of salinity based on the hydrochemistry data, the δ18O value, and incapability of this process to dramatically enhance salinity up to the observed value of 330,000 mg/L. The overlaying impermeable formations, high pressure in the gas reservoir, and the presence of a cap rock above the Kangan gasfield, all prevent the downward flow of meteoric and Persian Gulf waters into the Kangan aquifer. The evaporated ancient seawater is autochthonous, because the Kangan brine aquifer was formed by entrapment of brine seawater during the deposition of carbonates, gypsum, and minor clastic rocks in a lagoon and sabkha environment. The reliability of determining the source of salinity in a deep complicated inaccessible high-pressure aquifer can be improved by combining various methods of hydrochemistry, isotope, hydrodynamics, hydrogeology and geological settings. 相似文献
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Majid?Montaseri Sarvin?Zaman Zad GhavidelEmail author Hadi?Sanikhani 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(8):2253-2273
In present paper, wavelet analysis of total dissolved solid that monitored at Nazlu Chay (northwest of Iran), Tajan (north of Iran), Zayandeh Rud (central of Iran) and Helleh (south of Iran) basins with various climatic conditions, have been studied. Daubechies wavelet at suitable level (db4) has been calculated for TDS of each selected basins. The performance of artificial neural networks (ANN), two different adaptive-neurofuzzy inference system (ANFIS) including ANFIS with grid partition (ANFIS-GP) and ANFIS with subtractive clustering (ANFIS-SC), gene expression programming (GEP), wavelet-ANN, wavelet-ANFIS and wavelet-GEP in predicting TDS of mentioned basins were assessed over a period of 20 years at twelve different hydrometric stations. EC (μmhos/cm), Na (meq L?1) and Cl (meq L?1) parameters were selected (based on Pearson correlation) as input variables to forecast amount of TDS in four studied basins. To develop hybrid wavelet-AI models, the original observed data series was decomposed into sub-time series using Daubechies wavelets at suitable level for each basin. Based on the statistical criteria of correlation coefficient (R), root mean square error (RMSE) and mean absolute error (MAE), the hybrid wavelet-AI models performance were better than single AI models in all basins. A comparison was made between these artificial intelligence approaches which emphasized the superiority of wavelet-GEP over the other intelligent models with amount of RMSE 18.978, 6.774, 9.639 and 318.363 mg/l, in Nazlu Chay, Tajan, Zayandeh Rud and Helleh basins, respectively. 相似文献
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