ORIGINAL_ARTICLE
Evaluation of Different Missing Data Reconstruction Methods for Daily Minimum Temperature in Elevated Stations of Iran: Comparison with New Proposed Approach
Daily minimum air temperature data are greatly needed in climatic studies of first-fall and last-spring frosts, frost periods, evaluation and improvement of crop production potentials, and eventually their effects upon food security. Despite the fact that climate stations, set up at high elevations play important roles in accurate estimate of temperature parameter gradients, and on their mappings, the number of such established stations in Iran is limited, causing many gaps to be served in their data time series. Hence, reconstruction of temperature data for elevated stations is considered to be essential, especially for studies requiring long-term homogeneous data items. This study was aimed at making a comparison of the different methods of readjustment of the daily minimum temperature data (obtained from highly elevated stations) and to determine the most suitable method for readjusting and lengthening of their record periods. To follow the purpose, a number of 12 stations at elevations exceeding 1900 m were selected. A number of 500 randomly sampled (minimum daily temperature) data were taken and reconstructed through 31 classic methods, and as well, through a new proposed approach, based on Cumulative Distribution Function (CDF) of minimum temperature data. Accuracies of these methods were tested using RMSE within 90 and 95 % of confidence interval of errors. Results revealed that Principle Component Analysis, proposed method based on CDF, and Artificial Neural Network stood in priority for reconstruction of daily minimum temperature data, with 95% of confidence intervals, reconstructed error of ±2.0, ±2.2 and ± 3.1 °c, respectively. This study led to completion of daily minimum temperature data series of highly elevated stations for the period of 1965-2010. This can be employed in climate change studies and as well in first-fall vs. last-spring frost risks, and reform of farming calendar depending upon climate change.
https://ijswr.ut.ac.ir/article_62576_1067f3a5ea8cf9662e99a265a40169a9.pdf
2017-07-23
231
239
10.22059/ijswr.2017.62576
Reconstruction of Daily Temperature
Elevated Meteorological Stations
Temperature Estimation Error
Iran
Jaber
Rahimi
jaberrahimy@ut.ac.ir
1
Ph.D.Student/ Univ.ofTehran
AUTHOR
ali
Khalili
akhalili@ut.ac.ir
2
Professor/University of Tehran
LEAD_AUTHOR
Javad
Bazr afshan
jbazr@ut.ac.ir
3
َAssociate Professor /Univ. of Tehran
AUTHOR
Ashraf, M., Loftis, J. C., & Hubbard, K. G. (1997). Application of geostatistics to evaluate partial weather station networks. Agricultural and forest meteorology, 84(3), 255-271.
1
Carrega, P. (1995). A method for the reconstruction of mountain air temperatures with automatic cartographic applications. Theoretical and applied climatology, 52(1-2), 69-84.
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Coulibaly, P., & Evora, N. D. (2007). Comparison of neural network methods for infilling missing daily weather records. Journal of hydrology, 341(1), 27-41.
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Demyanov, V., Kanevsky, M., Chernov, S., Savelieva, E., & Timonin, V. (1998). Neural network residual kriging application for climatic data. Journal of Geographic Information and Decision Analysis, 2(2), 215-232.
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Di Piazza, A., Conti, F. L., Noto, L. V., Viola, F., & La Loggia, G. (2011). Comparative analysis of different techniques for spatial interpolation of rainfall data to create a serially complete monthly time series of precipitation for Sicily, Italy. International Journal of Applied Earth Observation and Geoinformation, 13(3), 396-408.
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Khalil, M., Panu, U. S., & Lennox, W. C. (2001). Groups and neural networks based streamflow data infilling procedures. Journal of Hydrology, 241(3), 153-176.
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Khalili A (1991) Integrated Water Plan of Iran, Jamab Consulting Engineering Co., The Ministry of Energy, Tehran, 111-122. (In Farsi)
7
Henn, B., Raleigh, M. S., Fisher, A., & Lundquist, J. D. (2013). A comparison of methods for filling gaps in hourly near-surface air temperature data. Journal of Hydrometeorology, 14(3), 929-945.
8
Khorshiddoust, A. M., Nassaji, Z. M., and Ghermez, C. B. (2012). Time Series Reconstruction of Daily Maximum and Minimum Temperature using Nearest Neighborhood and Artificial Neural Network Techniques (Case Study: West of Tehran Province). Geographical Space, 12 (38), 197-214. (In Farsi)
9
Kim, J. W., & Pachepsky, Y. A. (2010). Reconstructing missing daily precipitation data using regression trees and artificial neural networks for SWAT streamflow simulation. Journal of hydrology, 394(3), 305-314.
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Mileva-Boshkoska, B., & Stankovski, M. (2007). Prediction of missing data for ozone concentrations using support vector machines and radial basis neural networks. Informatica, 31(4).
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Mwale, F. D., Adeloye, A. J., & Rustum, R. (2012). Infilling of missing rainfall and streamflow data in the Shire River basin, Malawi–A self organizing map approach. Physics and Chemistry of the Earth, Parts A/B/C, 50, 34-43.
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Teegavarapu, R. S., & Chandramouli, V. (2005). Improved weighting methods, deterministic and stochastic data-driven models for estimation of missing precipitation records. Journal of Hydrology, 312(1), 191-206.
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Wagner, P. D., Fiener, P., Wilken, F., Kumar, S., & Schneider, K. (2012). Comparison and evaluation of spatial interpolation schemes for daily rainfall in data scarce regions. Journal of Hydrology, 464, 388-400.
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Xia, Y., Fabian, P., Stohl, A., & Winterhalter, M. (1999). Forest climatology: estimation of missing values for Bavaria, Germany. Agricultural and Forest Meteorology, 96(1), 131-144.
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16
You, J., Hubbard, K. G., & Goddard, S. (2008). Comparison of methods for spatially estimating station temperatures in a quality control system. International Journal of Climatology, 28(6), 777-787.
17
ORIGINAL_ARTICLE
Assessing reference evapotranspiration changes during the 21st century in some semi-arid regions of Iran
Changes of ET0 and its atmospheric control were investigated in six stations located in West Iran during the period of 1966-2100. The outputs related to HadCM3 under B2 emission scenario were downscaled through SDSM. The results revealed that ET0, as averaged across all stations, would increase by 5.12, 7.33 and 11.01% respectively over the early, middle and late 21st century relative to the baseline period (1966-2010). The results obtained through Mann-Kendall test revealed that there was an insignificant positive trend in ET0 at the level of 95% over 1966-2010 in most of the surveyed sites. This increasing trend could be explained by an upward trend in temperature and solar radiation vs. a negative trend of relative humidity within the study area. The increasing trend in ET0 will likely be significant during 2011-2040 and 2071-2100 while insignificant during 2041-2070. The occurrence of ET0 upward trend in the future is most likely due to temperature rise.
https://ijswr.ut.ac.ir/article_62578_f43a169066b00b4acc9e2b14c7d0d1fb.pdf
2017-07-23
241
252
10.22059/ijswr.2017.62578
climate change
Reference Evapotranspiration
SDSM
Statistical Downscaling
Milad
Nouri
miladnouri85@gmail.com
1
Ph.D. Student
AUTHOR
Mahdi
Homaee
mhomaee@modares.ac.ir
2
Tarbiat Modares University
LEAD_AUTHOR
Mohammad
Bannayan
banayan@um.ac.ir
3
Ferdowsi University of Mashhad
AUTHOR
Allen, R. G., Pereira, L. S., Raes, D. and Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome, 300, 6541.
1
Bannayan, M., Sanjani, S., Alizadeh, A., Lotfabadi, S. S. and Mohamadian, A. (2010). Association between climate indices, aridity index, and rainfed crop yield in northeast of Iran. Field Crops Res., 118(2), 105-114.
2
Chu, J., Xia, J., Xu, C.-Y. and Singh, V. (2010). Statistical downscaling of daily mean temperature. pan evaporation and precipitation for climate change scenarios in Haihe River, China. Theor. Appl. Climatol., 99(1-2), 149-161.
3
Dai, A. (2011). Drought under global warming: a review. Wiley Interdiscip. Rev. Clim. Change, 2(1), 45-65.
4
Dettori, M., Cesaraccio, C., Motroni, A., Spano, D. and Duce, P. (2011). Using CERES-Wheat to simulate durum wheat production and phenology in Southern Sardinia, Italy. Field Crops Res., 120(1), 179-188.
5
Dinpashoh, Y., Jhajharia, D., Fakheri-Fard, A., Singh, V. P. and Kahya, E. (2011). Trends in reference crop evapotranspiration over Iran. J. Hydrol., 399(3), 422-433.
6
Fowler, H., Blenkinsop, S. and Tebaldi, C. (2007). Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int. J. Climatol., 27(12), 1547-1578.
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Ghorbani, M. (2013). Nature of Iran and Its Climate The Economic Geology of Iran (pp. 1-44): Springer Netherlands.
8
Gulizia, C. and Camilloni, I. (2015). Comparative analysis of the ability of a set of CMIP3 and CMIP5 global climate models to represent precipitation in South America. Int. J. Climatol., 35(4), 583-595.
9
Hashmi, M. Z., Shamseldin, A. Y. and Melville, B. W. (2011). Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed. Stochastic Environmental Research and Risk Assessment, 25(4), 475-484.
10
Hassan, Z., Shamsudin, S. and Harun, S. (2014). Application of SDSM and LARS-WG for simulating and downscaling of rainfall and temperature. Theor. Appl. Climatol., 116(1-2), 243-257.
11
Huang, J., Zhang, J., Zhang, Z., Sun, S. and Yao, J. (2012). Simulation of extreme precipitation indices in the Yangtze River basin by using statistical downscaling method (SDSM). Theor. Appl. Climatol., 108(3-4), 325-343.
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Hundecha, Y. and Bárdossy, A. (2008). Statistical downscaling of extremes of daily precipitation and temperature and construction of their future scenarios. Int. J. Climatol., 28(5), 589-610.
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IPCC. (2013). Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Retrieved from Cambridge, United Kingdom and New York, NY, USA.
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Khan, M. S., Coulibaly, P. and Dibike, Y. (2006). Uncertainty analysis of statistical downscaling methods. J. Hydrol., 319(1), 357-382.
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Kistler, R., Collins, W., Saha, S., White, G., Woollen, J., Kalnay, E., Chelliah, M., Ebisuzaki, W., Kanamitsu, M. and Kousky, V. (2001). The NCEP-NCAR 50-year reanalysis: Monthly means CD-ROM and documentation. Bull. Am. Meteorol. Soc., 82(2), 247-267.
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Li, Z., Zheng, F.-L. and Liu, W.-Z. (2012). Spatiotemporal characteristics of reference evapotranspiration during 1961–2009. and its projected changes during 2011–2099 on the Loess Plateau of China. Agr. Forest Meteorol., 154, 147-155.
17
Liu, Z., Xu, Z., Charles, S. P., Fu, G. and Liu, L. (2011). Evaluation of two statistical downscaling models for daily precipitation over an arid basin in China. Int. J. Climatol., 31(13), 2006-2020.
18
Nouri, M., Homaee, M. and Bybordi, M. (2014). Quantitative Assessment of LNAPL Retention in Soil Porous Media. Soil Sediment Contam., 23(8), 801-819.
19
Peel, M. C., Finlayson, B. L. and McMahon, T. A. (2007). Updated world map of the Köppen-Geiger climate classification. Hydrol. Earth Syst. Sci. Discussions, 4(2), 439-473.
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Sadeghi, A., Kamgar-Haghighi, A., Sepaskhah, A., Khalili, D. and Zand-Parsa, S. (2002). Regional classification for dryland agriculture in southern Iran. J. Arid Environ., 50(2), 333-341.
22
Samadi, S., Wilson, C. A. and Moradkhani, H. (2013). Uncertainty analysis of statistical downscaling models using Hadley Centre Coupled Model. Theor. Appl. Climatol., 114(3-4), 673-690.
23
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24
Tabari, H., Aeini, A., Talaee, P. H. and Some'e, B. S. (2012). Spatial distribution and temporal variation of reference evapotranspiration in arid and semi‐arid regions of Iran. Hydrol. Process., 26(4), 500-512.
25
Tabari, H. and Talaee, P. H. (2011a). Analysis of trends in temperature data in arid and semi-arid regions of Iran. Global Planet. Change, 79(1), 1-10.
26
Tabari, H. and Talaee, P. H. (2011b). Temporal variability of precipitation over Iran: 1966–2005. J. Hydrol., 396(3), 313-320.
27
Talaee, P. H., Some’e, B. S. and Ardakani, S. S. (2014). Time trend and change point of reference evapotranspiration over Iran. Theor. Appl. Climatol., 116(3-4), 639-647.
28
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29
Wang, W., Shao, Q., Peng, S., Xing, W., Yang, T., Luo, Y., Yong, B. and Xu, J. (2012a). Reference evapotranspiration change and the causes across the Yellow River Basin during 1957–2008 and their spatial and seasonal differences. Water Resour. Res., 48(5).
30
Wang, W., Xing, W., Shao, Q., Yu, Z., Peng, S., Yang, T., Yong, B., Taylor, J. and Singh, V. P. (2013). Changes in reference evapotranspiration across the Tibetan Plateau: Observations and future projections based on statistical downscaling. J. Geophys. Res. Atmospheres, 118(10), 4049-4068.
31
Wang, X., Yang, T., Shao, Q., Acharya, K., Wang, W. and Yu, Z. (2012b). Statistical downscaling of extremes of precipitation and temperature and construction of their future scenarios in an elevated and cold zone. Stochastic Environmental Research and Risk Assessment, 26(3), 405-418.
32
Wilby, R. and Dawson, C. (2007). SDSM 4.2–A decision support tool for the assessment of regional climate change impacts, User Manual. Department of Geography, Lancaster University, UK.
33
Wilby, R., Dawson, C., Murphy, C., O’Connor, P. and Hawkins, E. (2014). The Statistical DownScaling Model-Decision Centric (SDSM-DC): conceptual basis and applications. Clim. Res., 61(3), 259-276.
34
Wilby, R. L. and Dawson, C. W. (2012). The statistical downscaling model: insights from one decade of application. Int. J. Climatol., 33(7), 1707-1719.
35
Wilby, R. L. and Dawson, C. W. (2013). The statistical downscaling model: insights from one decade of application. Int. J. Climatol., 33(7), 1707-1719.
36
Wilby, R. L., Dawson, C. W. and Barrow, E. M. (2002). SDSM—a decision support tool for the assessment of regional climate change impacts. Environ. Model. Software, 17(2), 145-157.
37
Wilby, R. L. and Harris, I. (2006). A framework for assessing uncertainties in climate change impacts: Low‐flow scenarios for the River Thames, UK. Water Resour. Res., 42(2).
38
Xu, C.-Y. and Singh, V. (2005). Evaluation of three complementary relationship evapotranspiration models by water balance approach to estimate actual regional evapotranspiration in different climatic regions. J. Hydrol., 308(1), 105-121.
39
Yang, T., Li, H., Wang, W., Xu, C. Y. and Yu, Z. (2012). Statistical downscaling of extreme daily precipitation, evaporation, and temperature and construction of future scenarios. Hydrol. Process., 26(23), 3510-3523.
40
Yue, S., Pilon, P., Phinney, B. and Cavadias, G. (2002). The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrol. Process., 16(9), 1807-1829.
41
Yue, S. and Wang, C. (2002). The influence of serial correlation on the Mann–Whitney test for detecting a shift in median. Advances in Water Resources, 25(3), 325-333.
42
ORIGINAL_ARTICLE
Performance assessment of LARS-WG and SDSM downscaling models in simulation of precipitation and temperature
Throughout the present study, the results of two downscaling models (SDSM vs. LARS-WG) are compared, considering the error criteria in terms of daily rainfall, daily minimum and maximum temperatures within two research stations of Ravansar and Kermanshah. In either of the models, 1988-1961 and 1989-2001 periods were respectively considered for calibration and validation. The results indicated that in either of the calibration and validation periods, SDSM model benefits from a more appropriate performance than LARS-WG in the simulation of daily minimum vs. maximum temperatures at the two stations, whereas LARS-WG model presents a more acceptable performance than that in the simulation of daily rainfall. The results of downscaling indicate that Kermanshah and Ravansar stations will be faced with less precipitation under A2 scenario and HadCM3 model in 2020s and 2050s. Also, it is concluded that in both models, minimum and maximum temperatures increase in the next two decades under the A2 scenario in either one of the stations.
https://ijswr.ut.ac.ir/article_62601_0266206a5f0e3693b3a25b6ca8a52a23.pdf
2017-07-23
253
262
10.22059/ijswr.2017.62601
climate change
Precipitation
Minimum Temperature
maximum temperature
Ali
Salajegheh
salajegh@ut.ac.ir
1
Tehran University, natural resources faculty.
AUTHOR
Elham
Rafiei Sardoii
ellrafiei@gmail.com
2
دانشکده منابع طبیعی دانشگاه تهران
LEAD_AUTHOR
Alireza
Moghaddamnia
a.moghaddamnia@ut.ac.ir
3
Tehran University. natural resources faculty
AUTHOR
Arash
Malekian
malekian@ut.ac.ir
4
Tehran University. Natural resources faculty.
AUTHOR
Shahab
Araghinejad
araghinejad@ut.ac.ir
5
Tehran University. Irrigation faculty
AUTHOR
Shahram
Khalighi Sigarodi
khalighi@ut.ac.ir
6
Tehran University, Natural resources faculty
AUTHOR
Amin
Saleh Pourjam
aminpourjam@yahoo.com
7
Assistant Professor of Soil Conservation and Watershed Management Research Institute
AUTHOR
Aghashahi, M. (2012) Comparison between LARS-WG and SDSM in order to downscaling environmental parameters in climate change studies. The sixth National Conference of Environmental Engineering. Tehran University. Environment Faculty.
1
Alireza Zamani Nuri, Mohammadreza Farzaneh, Kiamars Espanayi. 2014. Assessment of climatic parameters uncertainty under effect of different downscaling techniques. International Research Journal of Applied and Basic Sciences. 8(9), 838-225.
2
Alizadeh, H and Zahraei, B. (2014). Comparison of statistical downscaling models in simulation of the daily rainfall, The Sixteenth Conference of Iran Geophysics, Pages 128-132.
3
Andersen, H. E., Kronvang, B., Larsen, S. E., Hoffmann, C. C., Jensen, T. S and Rasmussen, E. K. (2006). Climate-change impacts on hydrology and nutrients in a Danish lowland river basin. Science of the Total Environment, 365(1), 223-237.
4
Chen, H., Xu, C. Y and Guo, S. (2012). Comparison and evaluation of multiple GCMs, statistical downscaling and hydrological models in the study of climate change impacts on runoff. Journal of hydrology, 434, 36-45.
5
Farzaneh M, Samadi, S. Z., Akbarpour, A and Eslamian S. S. (2010). Introduction of selected predictors for statistical downscaling in Behesht-Abad subbasin of northern Karoon. The first conference of practical researches of water resources of Iran, Kermanshah, Industrial Kermanshah University.
6
Goudarzi, M., Salahi, B and Hosseini, S. A. (2015). Performance Assessment of LARS-WG and SDSM Downscaling Models In Simulation of Climate Changes in Urmia Lake Basin. Iran-Watershed Management Science & Engineering. 9(31).
7
Harpham, C and Wilby, R. L. (2005). Multi-site downscaling of heavy daily precipitation occurrence and amounts. Journal of Hydrology, 312(1), 235-255.
8
Hashmi, M. Z., Shamseldin, A. Y and Melville, B. W. (2011). Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed. Stochastic Environmental Research and Risk Assessment, 25(4), 475-484.
9
IPCC, (2014), Summary for policymakers. In: Climate Change. 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1-32.
10
Kabiri, R., Ramani Bai, V and Chan, A. (2015). Assessment of hydrologic impacts of climate change on the runoff trend in Klang Watershed, Malaysia, Environmental Earth Science Journal, 73, 27-37.
11
Tatsumi, K., Oizumi, T and Yamashiki, Y. (2013). Introduction of daily minimum and maximum temperature change signals in the Shikoku region using the statistical downscaling method by GCMs. Hydrological Research Letters, 7(3), 48-53.
12
Zulkarnain H., Shamsudin, S and Sobri, H. (2014). Application of SDSM and LARS-WG for simulating and downscaling of rainfall and temperature, Theor. Appl. Climatol., 116, 243–257.
13
ORIGINAL_ARTICLE
Drought monitoring in the last two centuries in the arid and semi-arid reigon using dendrochronology, a Case Study of Karkheh basin
Through a measurement of the annual growth of a tree ring and finding out of its chronology, the possibility of study and reconstruction of Palmer Drought Severity Index (PDSI) in the habitat areas is provided. The aim followed in this research is to reconstruct PDSI using dendrochronology, and drought monitoring within Karkheh basin. Throughout the research the chronology index of two tree species, namely Quercus brantii, and Quercus infectoria, in the central Zagross region during the period of 1840-2010 were used to reconstruct Palmer Drought Severity Index in KarkhehBasin. Correlations between Palmer Drought Severity Index and regional chronology index were positive and significant within 1% of confidence level. With regard to this fact, the Palmer Drought Severity Indexes from year 1840 to 2010 were reconstructed. The values of observed vs. reconstructed Palmer Drought Severity Index within the common statistical period are consistent with each other. Within further steps, the hydrological conditions during chronology period were studied and accordingly, hydrological drought was analyzed within the Basin for years, 1840 to 2010. Severity and duration of the droughts as well as decades of the highest number of drought and wet events were determined. In addition, the results were compared with those obtained by other researchers as well.
https://ijswr.ut.ac.ir/article_62619_65b1e80fc38171262534c570322fe9c7.pdf
2017-07-23
263
273
10.22059/ijswr.2017.62619
Palmer Drought Severity Index
Dendroclimatology
tree ring
Drought Monitoring
Karkheh basin
Farid
Foroughi
foroughifarid@gmail.com
1
PhD student / Tehran University
LEAD_AUTHOR
Shahab
Araghinejad
araghinejad@ut.ac.ir
2
Associate Professor/ Tehran University
AUTHOR
Ghasem
Azizi
ghazizi@ut.ac.ir
3
Associate Professor/ Tehran University
AUTHOR
Mohsen
Arsalani
arsalan_mohsen@yahoo.com
4
PhD Student /Tehran University
AUTHOR
Akkemik, U., and Aras, A. (2005). Reconstruction (1689–1994) of April-August precipitation in southwestern part of central Turkey. International Journal of Climatology, 25, 537–548.
1
Akkemik, U., Dagdeviren, N., and Aras, N. (2005). A preliminary reconstruction (A.D. 1635–2000) of spring precipitation using oak tree rings in the western Black Sea region of Turkey. International Journal of Biometeorology, 49(5), 297–302.
2
Akkemik, U., D’Arrigo, R., Cherubini, P., Köse, N., and Jacoby G. C. (2008). Tree-ring reconstructions of precipitation and streamflow for north-western Turkey. International Journal of Climatology, 28, 173–183.
3
Akkemik, U., Nüzhet, D. H., and Ozeren, M. S. (2011). Tree-ring Reconstructions of May–June Precipitation for Western Anatolia. Quaternary Research, 75(3), 438-450.
4
Arsalani, M. (2012). Reconstruction of precipitation and temperature variations using Oak tree rings in central Zagros, M.A. dissertation, University of Tehran, Faculty of Geography, Tehran, Iran.
5
Arsalani, M., Azizi, GH., and Bräuning, A. (2015). Dendroclimatic reconstruction of May–June maximum temperatures in the central Zagros Mountains, western Iran. International Journal of Climatology, 35: 408–416.
6
Azadi, S., Soltani, S., Faramarzi, M., Soltani todeshki, A. R., and Pour manafi, S. (2015). Palmer drought index in areas of Central Iran. Journal of Science and Technology of Agriculture and Natural Resources, water and soil sciences, 19(72), 305-318.
7
Carson, E. C., and Munroe, J. S. (2005). Tree-ring based streamflow reconstruction for Ashley Creek, northeastern Utah: implications for palaeohydrology of the southern Uinta Mountains. The Holocene, 15(4), 602-611.
8
Cook, E. R., (1985). A time series analysis approach to tree-ring standardization. Un published Ph.D. Dissertation, University of Arizona, Tucson, AZ, USA, P. 171.
9
D’Arrigo, R., and Cullen, H. M. (2001). A 350-year (AD 1628–1980) reconstruction of Turkish precipitation. Dendrochronologia, 19(2), 169–177.
10
Dai, A., K. E. Trenberth and T. Qian. 2004. A global data set of Palmer Drought Severity Index for 1870-2002: relationship with soil moisture and effects of surface warming. J. Hydrometeorol, 5, 1117–1130.
11
Eckstein, D. (2005). Human time in tree rings. Abstract book of Eurodendro. International Conference of Dendrochronology, September, 28-October 2nd, Viterbo – Italy.
12
Foroughi, F., Araghinejad, Sh., Azizi, Gh., and Arsalani, M. (2016). Streamflow reconstruction using dendrochronology, and modeling and classification of hydrological drought in Karkheh basin. Iranian Journal of Soil and Water Research, 46(4), 617-629.
13
Fritts, H. C. (1976) Tree rings and climate. Academic press, University of Arizona, Tucson, 567p.
14
Fritts, H. C., Guiot, J., Gordon, G. A., and Schweingruber, F. (1990.) Methods for calibration, verification and reconstruction. In: Kairiukstis L, Cook E, eds Methods of Tree-Ring Analysis: Applications in the Environmental Sciences, Reidel Press, Dordrecht. pp. 163-218.
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Garcia- Suarez, A. M., Butler, C.J., Bailli, and M. G. L. (2009). Climate signal in tree-ring chronologies in temperature climate: A multi-species approach. Dendrochronologia, 27, 183-198.
16
Heim R.R. (2000). Drought indices: a review. In: Wilhite DA (ed) Drought: a global assessment. Routledge, London.
17
Hessari, B,. Bruggeman, A,. Akhoond-Ali1, A., Oweis, T., and Abbasi, F. (2012). Supplemental irrigation potential and impact on downstream flow of Karkheh River Basin of Iran. Hydrology and Earth System Science. Discussions, 9, 13519–13536.
18
Hughes, M. K, Kuniholm, P. I, Garfin, G. M, Latini, C, and Eischeid, J. (2001). Aegean tree-ring signature years explained. Tree-ring Research, 57(1), 67-73.
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Jamab Consulting Engineers. (2006). Water balance report of Karkheh River basin area: Preliminary analysis, Ministry of Energy, Tehran. Iran.
20
Karamouz, M., and Araghinejad, Sh. (2010) Advance Hydrology. Amir Kabir University Press, Tehran, Iran.
21
Kim, T. J., B. Valdes and J. Aparicio.(2002). Frequency and spatial characteristics of in the Conchos River Basin, Mexico. Water International, 27,(3) 420- 430.
22
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Touchan, R., Akkemik, U., Hughes, M. K., and Erkan, N. (2007). May-June Precipitation reconstruction of southwestern Anatolia, Turkey during the Last 900 years from tree rings. Quaternary Research, 68, 196-202.
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Yevjevich, V. (1967). An objectives approach to definition and investigations of continental droughts. Hydrology Paper, 23, Colorado State University, Fort Collins, Colorado.
41
Yinpeng, L., Y. Wei, W. Meng and Y. Xiaodong. 2009. Climate change and drought: a risk assessment of crop yield impacts. J. Clim, 39, 31-46.
42
ORIGINAL_ARTICLE
Assessment and Uncertainty Analysis of Different Time of Concentration Methods
There are many uncertainty sources initiated from dependency of time of concentration equations (Tc) upon different parameters, which generally include rainfall intensity, topographic and land use map scale, DEM resolution and streams' delineation threshold. Throughout the present research the uncertainty and the performance of twenty Tc equations were investigated in the Kasilian and Amameh catchments. Results indicate that in either of the catchments, BransbyWilliams and Morgali-Linsley equations show good agreement with the observed values, with a relative error of less than 10%. Also, the uncertainty analysis of different Tc equations by use of delta method illustrates that McCuen, ASCE, Eagleson and FAA, Johnstone-Cross equations are of the highest vs. lowest uncertainties, respectively. In the geomorphological-based equations, the uncertainty that is caused by streams delineation threshold is approximately 3-4 times that of DEM and data resolutions' uncertainties. This indicates that streams delineation threshold is the most important factor and should be more consideration, especially in ungagged catchments.
https://ijswr.ut.ac.ir/article_62625_72d036a9c36c148070d549d9c3ba60ed.pdf
2017-07-23
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10.22059/ijswr.2017.62625
time of concentration
uncertainty
Geomorphological Parameters
Data Resolution
Asghar
Azizian
azizian@eng.ikiu.ac.ir
1
Assistant Professor in Water Engineering Department/ Imam Khomeini International University
LEAD_AUTHOR
Azizian, A. and Shokoohi, A.R. (2014). DEM resolution and stream delineation threshold effects on the results of geomorphologic-based rainfall runoff models. Turkish J Eng Env Sci, 38, 64-78.
1
Azizian, A. and Shokoohi, A.R. (2015a). Effects of Data resolution and stream delineation threshold effects on the results of a Kinematic Wave based GIUH model. Journal of Water S.A, 4(9), 61-70.
2
Azizian, A. and Shokoohi A.R. (2015b). Investigation of the Effects of DEM Creation Methods on
3
the Performance of a Semi distributed Model: TOPMODEL. J. Hydro. Eng, 20(11), 05015005 (1-9).
4
Azizian, A. and Shokoohi, A.R. (2016). Effect of Data Spatial Resolution on Topographic Index and Performance of the Simi-Distributed Model (TOPMODEL). Modares Civil Engineering Journal, 16(2), 187-201 (In Farsi).
5
Comina, C., Lasagna, M., Luca, D. A. De., and Sambuelli, L. (2013). Discharge measurement with salt dilution method in irrigation canals: direct sampling and geophysical controls. Hydrol. Earth Syst. Sci. Discuss, 10, 10035-10060.
6
Dastourani, M.T., Abdollahvand, A., Osareh, H., Talebi, A. and Moghaddamnia, A. (2013). Determination of application of some experimental relations of concentration time for estimation of surveying time in waterway. Journal of Watershed Management Research, 99, 42-52 (In Farsi).
7
Dingman, S. L. (2002). Physical Hydrology, Prentice Hall.
8
Eslamian, S. and A. Mehrabi. (2005). Determination of experimental relations in estimation of concentration time in mountainous watershed basins. Journal of Natural Resources and Agricultural Sciences, 12(5), 23-34 (In Farsi).
9
Fang, X., Thompson, D. B., Cleveland, T. G., and Pradhan, P. (2007). Variations of time of concentration estimates using NRCS velocity method. J. Irrig. Drain Eng, 133(4), 314–322.
10
Fang, X., Thompson, D. B., Cleveland, T. G., Pradhan, P., and Malla, R. (2008). Time of concentration estimated using watershed parameters determined by automated and manual methods. J. Irrig. Drain Eng, 134(2), 202–211.
11
Froehlich, D.C. (2011). NRCS overland flow travel time calculation. J. Irrig. Drain Eng, 137(4), 258–262.
12
Kirpich, Z. P. (1940). Time of concentration of small agricultural watersheds. Civil Eng, 10(6), 362–368.
13
Khan, A.L., Lye, L. and Husain, T. (2008). Latin Hypercube Sampling for Uncertainty Analysis in Multiphase Modelling, J. of Environ. Eng. Sci., 7, 617-626.
14
Kosari, M.R., Saremi Nayeeni, M.A., Tazeh, M. and Rahim Firrozeh, M. (2010). Sensitivity analysis of four concentration time estimation methods in watershed basins. Journal of Khoshkboom, 1(1), 43- 55 (in Farsi).
15
Kumar, R., Chatterjee, C., Singh, R.D., Lohani, A.K. and Kumar, S. (2004). GIUH based Clark and Nash models for runoff estimation for an ungauged basin and their uncertainty analysis. Intl. J. River Basin Management, 2(4), 281–290.
16
Loucks, D.P., Van Beek, E., Stedinger, J., Dijkman, J.P.M. and Villars, M.T. (2005). Water Resources Systems Planning and Management An Introduction to Methods, Models and Applications. UNESCO publishing, Turin, Italy.
17
Manjo, K.C. and Fang, X. (2014). Estimating Time of Concentration of Overland Flow on Impervious Surface using Particle Tracking Model. World Environmental and Water Resources Congress. Water without Borders © ASCE.
18
McCuen, R. (2009). Uncertainty Analyses of Watershed Time Parameters. J. Hydrol. Eng, 14(5), 490-498.
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McCuen, R. H. and Spiess, J. M. (1995). Assessment of kinematic wave time of concentration. J. Hydraul. Eng, 121(3), 256–266.
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21
Mobaraki, J. (2006). Analysis the accuracy of empirical Tc and time to peak equations. MSc. Dissertation, Natural resources faculty. Tehran.
22
Moghaddamnia, E. (2000). Comparing time of concentration, lag time and time to peak equations with using empirical equations and the shape of hydrograph, MSc. Dissertation, Natural resource and marine sciences, Tarbiat Modares university, Tehran.
23
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Pavlovich, S. B. and Moglen, G. E. (2008). Discretization issues in travel time calculation. J. Hydrol. Eng, 13(2), 71–79.
25
Razmjoei, N., Mahdavi, M., Mohseni Saravi, M. and MoetamedVaziri, B. (2011). Comparing some of Tc equations (case study: Tehran). 7th National Conference on Watershed Management Sciences and Engineering of Iran, Esfahan University.
26
Sadeghi, S. H. R., Mostafazadeh, R. and Sadoddin, A. (2015). Changeability of simulated hydrograph from a steep watershed resulted from applying Clark’s IUH and different time–area histograms. J. of Environ. Eng. Sci, 74(4), 3629-3643.
27
Sharifi, S. and Hosseini, S.M. (2011). Methodology for identifying the best equations for estimating the time of concentration of watersheds in a particular region. J. Irrig. Drain Eng. 137(11), 712–719.
28
Singh, V. P. (1988). Hydrologic systems: Rainfall-runoff modeling. Vol. 1, Prentice Hall, Englewood Cliffs, NJ.
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USWRC (U.S. Water Resources Council). 1981. Estimating peak flow frequencies for natural ungaged watersheds. Washington, D.C.
33
Viessman, W. Jr. and Lewis, G. L. (2003). Introduction to hydrology. Pearson Education, New York.
34
Wong, T. S. W. (2005). Assessment of time of concentration formulas for overland flow. J. Irrig. Drain Eng, 131(4), 383–387.
35
Wong, T. S. W. (2009). Evolution of kinematic wave time of concentration formulas for overland flow. J. Hydrol. Eng, 14(7), 739–744.
36
ORIGINAL_ARTICLE
Treatment a soil against piping phenomenon using geogrid sheets
Piping is an erosive process that occurs in hydraulic structures under the influence of upward seepage. Lack of sufficient notice of this phenomenon may seriously affect the stability of hydraulic structures. In this research work the effect of reinforcement soil on the variations of critical hydraulic gradient and seepage force were investigated through experimental tests. Reinforcement of samples was performed by two geo grids with mesh diameters of 6mm (No.1) and 2mm (No.2). One dimensional piping test were carried out on non-reinforced vs. reinforced sandy soil samples, compacted and fabricated through static methods, and in a specially designed apparatus. The results indicated that the critical hydraulic gradient and resistance against seepage force increased by reinforcement of the samples and that the resistance is a function of the number of the geogrid sheets as well as their location. In addition, the results indicated that the effect of the two geo grids is nearly the same for treatment of the soil against piping.
https://ijswr.ut.ac.ir/article_62629_abed3172e2bf4ae0191070af4bda9a09.pdf
2017-07-23
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10.22059/ijswr.2017.62629
piping
seepage velocity
critical hydraulic gradient
Soil reinforcement
Geogrid
sepideh
akrami
sepideh.akrami@ut.ac.ir
1
MSc Student, Dept. of Hydraulic Structures irrigation and reclamation, univ of Tehran, Tehran, Iran
LEAD_AUTHOR
ali
raeesi estabragh
raeesi@ut.ac.ir
2
Associate Prof., Dept of irrigation and reclamation, univ of Tehran, Tehran, Iran
AUTHOR
jamal
Abdolahi Baik
jaabaik@ut.ac.ir
3
Lecturer., Dept of irrigation and reclamation, univ of Tehran, Tehran, Iran
AUTHOR
Das, A., Jayashrec, Ch. and Viswandahm, B.V.S. (2009). Effect of randomly distributed geofibers on the piping behaviour of embankments constructed with fly ash as a fill material. Geotextiles and Geomembranes, 27 (5), 341–349.
1
Foster, M.A., Fell, R. and Spannagle, M. (2000). The statistics of embankment dam failures and accidents. Canadian Geotechnical Journal, 37 (5), 1000–1024.
2
Iizuka A., Kawai, K., Kim, E.R. and Hirata, M. (2004). Modeling of the confining effect due to the geosynthetic wrapping of compacted soil specimens. Geotextiles and Geomembranes, 22 (5), 329-358.
3
Ojha, C.S., Singh, V.P. and Adrian, D.D., (2003). Determination of critical head in soil piping. Journal of Hydraulic Engineering, ASCE 129 (7), 511–518.
4
Patra, C.R., Das, B.M. and Atalar, C., (2005). Bearing capacity of embedded strip foundation on geogrid-reinforced sand. Geotextiles and Geomembranes, 23 (5), 454-462.
5
Park, T. and Tan S.A., (2005). Enhanced performance of reinforced soil walls by the inclusion of short fiber. Geotextiles and Geomembranes, 23 (4), 348-361.
6
Sherard, J.L., Dunnigan, L.P.and. Talbot, J.R., (1984). Basic properties of sand and gravel filters. Journal of Geotechnical Engineering, ASCE 110 (6), 684–700.
7
Skempton, A.W., and Brogan, J.M., (1994). Experiments on piping in sandy Gravel, journal of Geotechnique, 44 (3), 444-460.
8
Sivakumar Babu, G.L., Vasudevan, A.K., (2008). Seepage velocity and piping resistance of coir fiber mixed soils. Journal of Irrigation and Drainage Engineering, ASCE 134 (4), 485–492.
9
Vidal, M.H. (1978). The development and future of reinforced earth. Proceedings of a Symposium on Earth Reinforcement at the ASCE Annual Convention, Pittsburgh, Pennsylvania, 1-61.
10
Varuso, R.J., Grieshaber, J.B. and Nataraj M.S. (2005). Geosynthetic reinforced levee test section on soft normally consolidated clays. Geotextiles and Geomembranes, 23 (4), 362-383.
11
Zornberg, J.G. (2002). Discrete Framework for Limit Equilibrium Analysis of Fibre-Reinforced Soil. Géotechnique, 52 (8), 593-604.
12
ASTM D698. Standard test method for laboratory compaction characteristics of soil using standard effort. ASTM International West Conshohochen, PA, USA.
13
ORIGINAL_ARTICLE
Temporal changes of runoff generation and soil loss during the growth season of rainfed chickpea (A case study: in Tikmeh- dash research station, East Azerbaijan)
Proper information concerning the temporal changes of soil loss and runoff generation during growth season is not only valuable in soil conservation programing but could also be used in soil erosion and runoff estimation models. This study was conducted to investigate soil loss and runoff generation trend within in different sowing rates during growth season in erosion plots of Tikmeh- dash research station. The study was performed in a randomized complete block design of with three cultivation densities of 30, 35 and 40 kg per hectare of rain fed chickpea in three replications, and the resultant data were analyzed in a split plot of time design. The plots were plowed on April 6 2013, then, the seeds placed at a depth of approximately 5 cm of soil. During the growing season, the generated runoff and amount of sediments were recorded. Results revealed that soil loss and runoff generation were significantly (P≤0.01) affected by plant density and as well by sampling time. But their interactions did not significantly affect runoff generation. Overall, plant density was more effective in sediment control, as compared with runoff control. A minimum level of runoff and sediment formation occurred at 40 kg/ha treatment within the third sampling time (421.88 l/ha and 2.45 kg/ha respectively) while a maximum degree of runoff and soil loss occurred within first sampling time at 30 g of seed per hectare treatment (1550 l/ha and 31.54 kg/ha, respectively). Results also indicated that total runoff and soil loss in the 30 kg/ha treatment were 1.1 and 1.4 times those in 35 kg/ha treatments and 1.5 and 1.9 times those in 40 kg/ha treatments, respectively. So 40 kg/ha of sowing density (For rainfed pea) is recommended for better soil conservation practices to be observed in similar conditions in conditions this region.
https://ijswr.ut.ac.ir/article_62631_348d764366e28a79eb181e873ca1ab91.pdf
2017-07-23
299
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10.22059/ijswr.2017.62631
Erosion plots
Plant canopy
Soil erosion
Soil loss
Abbas
Ahmadi
a_ahmadi@tabrizu.ac.ir
1
University of Tabriz
LEAD_AUTHOR
Vahid
Jafari
vahid_jafari1990@yahoo.com
2
University of Tabriz
AUTHOR
Nosratollah
Najafi
nanajafi@yahoo.com
3
University of Tabriz
AUTHOR
Habib
Palizvanzand
habib.palizvan@gmail.com
4
University of Tabriz
AUTHOR
Mohammad Ebrahim
Sadeghzadeh
mebsadeghzadeh@yahoo.com
5
Agricultural Research Center of Eastern Azarbaijan
AUTHOR
Ahmadi Kh. and Kanouni, H. (1994). Investigation effect of seeding rate on seed yield of Kabuli type chickpea in Kurdistan. Seed an Plant Journal. 10, 32-38, (In Farsi)
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Ayaz, S., Mc Neil, D.L., Mc kenzie, B.A., and Hill, G.D. (2001). Effect of plant population and sowing depth on yield components of grain legumes. Proceedings of the 10th Australian Agronomy Conferenc. Tasmania.
2
Casermeiro, M.A., Molina, J.A., De La Cruz Caravaca, M.T., Costa, J.H., Massanet, M.H. and Moreno, P.S., (2004). Influence of scrubs on runoff and sediment loss in soils of Mediterranean climate. Catena, 57(1), 91-107.
3
Cerda, A. (1999). Parent material and vegetation affect soil erosion in eastern Spain. Soil Science Society of America, Journal of Soil Science Society of America, 63, 362-368
4
Feiznia, S., Sharifi, F. and Zare, M. (2003). Sensibility of formations to erosion in Chandab watershed basin of Varamin. Journal of Pajoohesh and Sazandegi, 61,33-38.
5
Francis, C.F., Thornes, J.B. (1990). Runoff hydrographs from three Mediterraneam vegetation cover types. In: Thornes, J.B. (Ed), Vegetation and Erosion. Wiley, Chichester, 363-384.
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Gee, G.W., and Or, D. (2002). Particle-size analysis. In: Warren, A.D. (ed.) Methods of Soil Analysis. Part 4. Physical Methods. Soil Science Society America, Inc., pp. 255-295.
7
Gonzalez, J.L., Schneiter, A.A., Riveland, N.R. and Johnson, B.L. (1994). Response of hybrid and open-pollinated safflower to plant population. Agronomy Journal, 86(6),1070-1073.
8
Kato, H., Onda, Y., Tanaka, Y. and Asano, M.,(2009). Field measurement of infiltration rate using an oscillating nozzle rainfall simulator in the cold, semiarid grassland of Mongolia. Catena, 76(3),173-181.
9
Kazemi, H. and Sadegi, S. (2014). Land suitability evaluation of Aq-Qalla region for rainfed chickpea cropping by Boolean logic and analytical hierarchy process (AHP). Iranian Dryland Agronomy Journal. 3(1), 1-20 (In Persian).
10
Khan, R.U., Ahad, A. and Rashid, A.,(2001). Chickpea production as influenced by row spacing under rainfed conditions of Dera Ismail Khan. Journal of Biological Science, 1 (3),103-104.
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Lal R. (1995). Sustainable Management of Soil Resources in the Humid Tropics. United Nations University Press, Tokyo.
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Leach, G.J. and Beech, D.F., (1988). Response of chickpea accessions to row spacing and plant density on a vertisol on the Darling Downs, south-eastern Queensland. 2. Radiation interception and water use. Animal Production Science, 28(3),377-383.
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Majnoon Hosseini N. 2008. Agriculture and grain production. Fourth edition. Tehran University Press.
14
Malakouti M.J. (2000). Determine of critical level of nutrient for strategic crops and optimum fertilizer recommendation in Iran. Agriculture Education Publication, Karaj, (In Farsi).
15
Molinar, F., Galt, D. and Holechek, J., (2001). Managing for mulch. Rangelands, 23(4),3-7.
16
Morgan, R.P.C., McIntyre, K., Vickers, A.W., Quinton, J.N. and Rickson, R.J. 1997. A rainfall simulation study of soil erosion on rangeland in Swaziland. Journal of Soil Technology, 11 (3), 291-299.
17
Morgan, R.P.C.1996. Soil erosion and conservation. 2nd ed, Silsoe College, Cranfield University, UK.
18
Morin, J. and Kosovsky, A., (1995). The surface infiltration model. Journal of Soil and Water Conservation, 50(5), 470-476.
19
Mousavi, S. F. and Raisian, R. (2000). Investigation effect of plant cover on rainfall infiltraion in soil and runoff loss using rainfall simulator. Proceeding of Sediment and Erosion Conference of Jihad-e-Sazandegi, Lorestan University. Lorestan. 141p.
20
Najafian, L., Kavian, A., Ghorbani J. and Tamartash, R. (2010). Effect of life form and vegetation cover on runoff and sediment yield in rangelands of Savadkooh region, Mazandaran. Rangeland, 4 (2):334-347, (In Farsi)
21
Nelson, D.W. and Sommer, L.E. (1982). Total carbon, organic carbon, and organic matter. pp. 539–579. In: Page, A.L., R.H. Miller and D.R. Keeney. (1982). Methods of Soil Analysis; Part 2. Chemical and Microbiological Properties. ASA-CSSA-SSSA Publisher, Madison, Wisconsin, USA.
22
Nunes, A.N., Coelho, C.O.A., Almeida, A. C., and Figueiredo, A. (2010). Soil erosion and hydrological response to land abandonment in a central Inland area of Portugal, Land Degradation and Development, 21 (3), 260-273.
23
Nunes, A.N., De Almeida, A.C. and Coelho, C.O., (2011). Impacts of land use and cover type on runoff and soil erosion in a marginal area of Portugal. Applied Geography, 31(2),687-699.
24
Poesen, J.W.A., (1990). Conditions for the evacuation of rock fragments from cultivated upland areas during rainstorms. IAHS Publication, 189,145-160.
25
Raisian, R. (1997). Investigation effects of rainfall intensity, soil texture and plant cover on infiltration and runoff in some waterseed of Chaharmahale Bakhtiyari province. MSc. Thesis, Agriculture Collage, Isfahan University of Technology, 129p (In Farsi).
26
Rastgar, S., Barani, H., Darijani, A., Sheikh, V., Ghorbani, J., Ghorbani, M., (2014). The Comparison of Soil Loss and Sediment Yield of Some Geology Formations in Plant Vegetation Gradients (Case study: Summer Rangelands of Balade in Mazandaran Province). Journal of Range and Watershed Management, 67(1), 31-44.
27
Refahi, H.G. (2000), Soil Erosion by Water & Conservation. Tehran University Publication.
28
Regan, K.L., Siddique, K.H.M. and Martin, L.D., (2003). Response of kabuli chickpea (Cicer arietinum L.) to sowing rate in Mediterranean-type environments of south-western Australia. Animal Production Science, 43(1),87-97.
29
Richards, L.A. (1969). Diagnosis and improvement of saline and alkali soils. US Salinity Laboratory Staff, Agricultural Handbook No. 60, USDA, USA.
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Singh, K.B., Tuwafe, S. and Kamal, M., (1980). Factors responsible for tallness and low yield in tall chickpea: suggestions for improvement. International Chickpea Newsletter.
31
Snyman, H.A. and Van Rensburg, W.L.J. (1986). Effect of slope and plant cover on run‐off, soil loss and water use efficiency of natural veld. Journal of the Grassland Society of southern Africa, 3(4),153-158.
32
Snyman, H.A., and Du Preez, C.C. (2005). Rangeland degradation in semi-arid South Africa-II: influence on soil quality, Journal of Arid Environments, 60 (3), 483–507.
33
Vásquez-Méndez, R., Ventura-Ramos, E., Oleschko, K., Hernández-Sandoval, L., Parrot, J.F. and Nearing, M.A., (2010). Soil erosion and runoff in different vegetation patches from semiarid Central Mexico. Catena, 80 (3),162-169.
34
Whish, J.P.M., Sindel, B.M., Jessop, R.S., and Felton, W.L. (2002). The effect of row spacing and weed density on yield loss of chickpea. Aust. Agric. Res., 53, 1335-1340.
35
Wildhaber, Bänninger, D., Burri, K. and Alewell, C., (2012). Evaluation and application of a portable rainfall simulator on subalpine grassland. Catena, 91,56-62.
36
Zhang, G.H., Liu, G.B., Wang, G.L., and Wang, Y.X. (2011). Effects of vegetation cover and rainfall intensity on sedimentbound nutrient loss, size composition and volume fractal dimension of sediment particles. Pedosphere, 21(5) 676–684.
37
Zhang, W.T., Yu, D.S., Shi, X.Z., Tan, M.Z., and Liu, L.S. (2010). Variation of sediment concentration and its drivers under different soil management systems. Pedosphere, 20(5),578–585.
38
ORIGINAL_ARTICLE
Long-lead streamflow forecasting using singular spectrum analysis in the Karkheh basin
In the past decade the different methods have been used to analyze and predict the physical variables, one of which is singular spectrum analysis (SSA) statistical methods. SSA is one of the methods, used in modeling various statistical processes and more recently, its use in various engineering disciplines including water resources, in order to eliminate random components in time series has been expanded. The main objective of this study was to forecast streamflow in the Karkheh basin using singular spectrum analysis. The gage stations in the Karkheh basin (five station) were selected for this study. The high flow period for these gage stations were determined. In order to modeling methods, 70% and 30% of data were used for calibration and validation respectively. The singular spectrum analysis method was used for pre-processing of data and elimination of noise in the time series of streamflow. Then, the recursive algorithm of the singular spectrum analysis model was used to develop forecasts models of streamflow in the Karkheh basin gage stations. To evaluate the performance of the model Normalized root mean square error, mean absolute error and correlation coefficient were used. In the validation the highest and lowest value of the NRMSE and MARE statistics were 0.47 and 0.50 for Pol Chehr station. The lowest value of the NRMSE statistic for Pol Dokhtar and Cham Anjir stations was 0.3 and 0.31 respectively and close to each other and the lowest value of the MARE statistic for Cham Anjir and Pol Dokhtar stations was 0.29 and 0.30 respectively and close to each other. Finally, the best and the weakest results in two stages of calibration and validation were for Cham Anjir and Pol Chehr Stations respectively. The results of this research showed that singular spectrum analysis can be used to forecast streamflow with reasonable accuracy
https://ijswr.ut.ac.ir/article_62633_155d525beb4cfbb5a1a138ede7e6137e.pdf
2017-07-23
309
321
10.22059/ijswr.2017.62633
Long lead forecasting
discharge
Streamflow
Singular Spectrum Analysis
Karkheh basin
Farid
Foroughi
foroughifarid@gmail.com
1
Faculty member of Shiraz Uinversity Ph.D Student of Tehran University
LEAD_AUTHOR
Shahab
Araghinejad
shahab_araghinejad@yahoo.com
2
Faculty member / Tehran University
AUTHOR
Akbarinia, M. (2012). Long Lead Stream flow Forecasting using data-driven models case study: Karkheh river MSc. thesis, Irrigation and reclamation engineering group, Tehran University, Karaj. (In Farsi)
1
Basilevsky, A., Derek, P., and Hum, J. (1979). Karhunen-Loeve analysis of historical time series with an application to plantation births in Jamaica. Journal of the American Statistical Associations, 74: 284-290.
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Broomhead, D. S., King, G. P., and Pike, E. R. (1987). Singular spectrum analysis with application to dynamical systems. Noise and Fractal, IOP Publication, Bristol.
4
Danilov, D. (1997). Principal components in time series forecast. Journal of Computational and Graphical Statistics, 6:112–121.
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Golyandina, N., Nekrutkin, V., and Zhiglovsky, A. (2001). Analysis of time series structure: SSA and related techniques. Chapman & Hall/CRC.
6
Hajibigloo, M., Ghezelsofloo, A. A., and Alimirzaei, H. (2013). Discussion and forecast monthly average rainfall techniques using SARIMA (case study: pluviometry station Babaaman Bojnourd). Journal of Irrigation Science and Engineering, 36 (3): 41-54. (In Farsi)
7
Hassani, H. (2007). Singular Spectrum Analysis: Methodology and Comparison. Journal of Data Science, 5(2007): 239-257.
8
Hassani, H., Mahmoudvand, R., and Yarmohammadi, M. (2010). Filtering and denoising in linear regression analysis. Fluctuation and Noise Letters, 9 (4): 343-358.
9
Hassani, H. Mahmoudvand, R. and Zokaei, M. (2011). Separability and window length in singular spectrum analysis. C. R. Acad. Sci. Paris, Ser. I, 349: 987–990.
10
Hassani, H., and Thomakos, D. (2010). A review on singular spectrum analysis for economic and financial time series, Statistics and Its Interface. 3(3): 377–397.
11
Jamab Consulting Engineers. (2006). Water balance report of Karkheh River basin area: Preliminary analysis, Ministry of Energy, Tehran. Iran. (In Farsi)
12
Jamali, F. S., (2009). An artificial neural network model for Shahcheraghi reservoir inflow forecasting using snow cover area data. MSc. thesis, Irrigation and drainage engineering group, Tehran University, Pakdasht. (In Farsi)
13
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Lisi, F. Nicolis, O., and Sandri, M. (1995). Combining singular-spectrum analysis and neural networks for time series forecasting. Neural Processing Letters, 2 (4): 6-10.
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Marques, C. A. F., Ferreira, J. A., Rocha, A., Castanheira, J. M., Melo-Goncalves, P., Vaz, N., and Dias, J. M. (2006). Singular spectrum analysis and forecasting of hydrological time series. Physics and Chemistry of the Earth, 31:1172–1179.
16
Meidani, E. (2012). Long lead streamflow forecasting using statistical methods: case study of Karoon and Dez rivers. MSc. thesis, Irrigation and reclamation engineering group, Tehran University, Karaj. (In Farsi)
17
Menezes, M. L., Souza, R. C., and Moreira Pessanha, J. F. (2015). Electricity consumption forecasting using singular spectrum analysis, Dyna. rev. fac. nac. minas, 82 (190): 138-146.
18
Sivapragasam, C., Liong, S. Y., and Pasha, M. F. K. (2001). Rainfall and runoff forecasting with SSA-SVM approach. Journal of Hydroinformatics 3 (7): 141-152.
19
Vautard, R., and M. Ghil. (1989). Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series. Physica D, 35: 395–424.
20
Wu, C. L., Chau, K. W., and Fan, C. (2010). Prediction of rainfall time series using modular artificial neural networks coupled with data-preprocessing techniques. Journal of Hydrology, 389: 146-167.
21
ORIGINAL_ARTICLE
Comparison of Hedging Policy using MetaHuristic Algorithm and Standard Operation Policy in Optimal Operation of Voshmgir Reservoir Dam in during Drought
Surface water resources constitute a main part of water resources on earth, specifically surfaces of water at dam reservoirs. One of the methods to improve utilization of such rich storage reservoirs is the policy of Hedging. The objective function followed in this study is to minimize the rate of this scarcity through implementing the policy of water rationing for agricultural purposes in conjuction with Voshmgir Dam in Golestan province. Hence, a three-year consecutive period of drought (1380- 1382) was selected for the study. The Hedging policy was performed using Annealing, Genetic and Imperialist competition algorithms. Then, the results were compared with the Standard Optimization Policy (SOP). The results showed that the Annealing Algorithm with the Hedging policy of 99.94% reliability, 50% Resilience, 49.39 Sustainability, 6% Vulnerability and 99 percent supply presented a high performance. Also the Standard operation policy with 99.25% reliability, 11 Resilience, 9.22 Sustainability, 15.5 Vulnerability along with 80 percent supply renders a low performance in Voshmgir reservoir operation during drought periods.
https://ijswr.ut.ac.ir/article_62634_be27022b0db62118f9ca5d7c3b248d65.pdf
2017-07-23
323
333
10.22059/ijswr.2017.62634
Drought
Hedging Policy
Standard Operation Policy
Voshmgir Dam
MetaHiuristic Algorithm
Amolbani
Mohammadreza poor
nmohammadrezapour@yahoo.com
1
Zabol University
LEAD_AUTHOR
Zohreh Sadat
Moosavi Rastegar
zmr_1989@yahoo.com
2
Zabol University
AUTHOR
Omid
Bozorg Haddad
obhaddad@ut.ac.iق
3
University of Tehran
AUTHOR
Mahboobeh
Ibrahimi
ebrahimi_mahboub@yahoo.com
4
Payame noor University of Booshehr
AUTHOR
Adeloye, A. J., Soundharajan, B. S., Ojha, C. S. P. and Remesan, R. (2015). Effect of Hedging-Integrated Rule Curves on the Performance of the Pong Reservoir (India) During Scenario-Neutral Climate Change Perturbations. Water Resour Manag. 29,3387–3407
1
Afshar, A., Masoumi, F. and Sandoval Solis, S. (2015). Reliability Based Optimum Reservoir Design by Hybrid ACO-LP Algorithm. Journal of Water Resour Manage. 29,2045–2058.
2
Ashofteh, P.S and Bozorg Haddad, O. 2015. Use of Multi-Conditional Functions in the Field of Reservoir Management and under Climate Change. Iranian Journal of Soil and water Research. 45(4), 397-404. (In Farsi)
3
Atashpaz-Gargari, E., Lucas, C. (2007). Imperialist Competitive Algorithm: An algorithm for Optimization inspired by imperialistic competition, IEEE Congress on Evolutionary Computation, 4661–4667.
4
Azarafza, H., Rezaii, H., Behmanesh, J. and Besharat, S. (2012). Results Comparison of Employing PSO, GA and SA Algorithms in Optimizing Reservoir Operation (Case Study: Shaharchai Dam, Urmia, Iran). Journal of Water and Soil. 26(5), 1101-1108.(In Farsi)
5
Bashiri-Atrabi, H., Qaderi, K., Rheinheimer, D., E. and Sharifi, E. (2015). Application of Harmony Search Algorithm to Reservoir Operation Optimization. Journal of Water Resources Manage. 29,5729–5748
6
Borhani Dariane, A., Shahidi, L. (2008). Optimization of Reservoir Operation using Simulated Annealing and other Heuristic Methods. International Journal of Engineering Sciences. 19(8), 31-40
7
Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley, Boston.
8
Goodarzi, E., Ziaei, M. and Hossinipour, E. (2015.) Optimization Analysis in Hydrosystem Engineering,Topics in Safety, Risk, Reliability and Quality.Springer International Publishing Switzerland.Chapter 7, 218-238.
9
Hoseini, H., Nagafi Gilaii, A., Zakertiri, M., (2013). Optimal Operation in Actual, satisfied and Hedging Condition and Application in Drawing of Latian, Mamloo Reservoirs Rule Curve. Fifth conference of Water Resource Management. University of Shahid Beheshti.Tehran, Iran.
10
Hogati, A., Farid_ Hoseini, A. R., Alizadeh, A., Entezari, M. (2013). Reservoir operation model with the Hedging policy procedure and its application in the preparation of the Dosty reservoir rule curve. Sevens Conference of Civil Engineering, Zahedan University. Iran.
11
Karami, F., Borhani Dariane, A. (2013). Comparison of Hedging Policies in Reservoir Management under Drought Condition. Journal of Water and wastewater. 25(3), 76-85.
12
Kirkpatrick, S., Gelatt, C. D. and Vecchi, M. P. (1983). Optimization by simulated annealing. Science, (220), 671-680.
13
Marton, D., Kapelan, Z. (2014). Risk and Reliability Analysis of Open Reservoir Water Shorages Using Optimization. Procedia Engineering. 89, 1478-1485 (In Farsi)
14
Ming, B., Chang, J.X., Huang, Q., Wang, Y., Huang, S.Z. (2015). Optimal Operation of Multi-Reservoir System Based-On Cuckoo Search Algorithm. Journal of Water Resource Management. 29, 5671–5687.
15
Razaghi, P., Babazadeh, H. and Shourian, M. 2014. Development of multi-purpose reservoir operation hedging rule in water resources shortage conditions using MODSIM8.1. Journal of Water and Soil Resource Conservation. 3(2), 11-23. (In Farsi)
16
Taghian, M., Radmanesh, F., Akhondali, A. and Haghighi, a. 2012. Optimization of hedging Rule for Reservoir Dams via Connecting a Genetic Algorithm to a Simulation Model. Journal of Irrigation Science and Engineering. 35(2), 41-50. (In Farsi)
17
Zeynali, M.J., Mohammad Reza Pour, O. and Foroghi, F. 2015. Evaluation of Particle Swarm, Genetic and Continuous Ant Colony Algorithms in Optimal Operation of Doroodzan Dam Reservoir. Journal of Water and Soil sciences. 25(3), 27-40.
18
ORIGINAL_ARTICLE
Management of operation of Amirkabir Dam water using System Dynamics and Nonlinear Planning Method
Water resource management is nowadays considered as one of the most prominent challenges facing mankind in the current century it could become the origin of many either positive or negative changes throughout the world. The challenge of water resources in the Middle-East countries is of a more serious concern. The limitations of available water resources and the recent droughts in countries like Iran indicate that Iran is facing a serious and protracted water crisis. Here a key decisive requirement would be a suitable water resource management strategy. In this research, an integrated method of system dynamic approach, classical nonlinear optimization, as well as Box–Jenkins Linear prediction model is proposed for the proper management of dam operations. First, the monthly operation of the reservoir was simulated based upon their storage and outflow characteristics through VENSIM software. Then, the volume of inflow and also evaporation losses from the reservoir were predicted from 2014 to 2018 by use of Box and Jenkins method. Finally the reservoir operations were optimized through LINGO software and classical nonlinear method. The results indicated that in optimization conditions, scarcity and overflow values are adjusted by their division into different months. Hence, probable damages can most probably be prevented.
https://ijswr.ut.ac.ir/article_62635_813000eef128992a8b335dcbf0fc1f58.pdf
2017-07-23
335
347
10.22059/ijswr.2017.62635
time series
System Dynamics
dam operations
VENSIM
LINGO
Hamed
Nozari
hamnozari@yahoo.com
1
Bualisina University of Hamedan
LEAD_AUTHOR
مژگان
مصطفی
moj.mostafa@ymail.com
2
دانشجوی کارشناسی ارشد گروه علوم و مهندسی آب دانشگاه بوعلی سینا همدان
AUTHOR
Akiner M.E., and Akkoyunlu A. (2012). Modeling and Forecasting River Flow Rate from the Melen Watershed, Turkey, Journal of Hydrology, Volume 456, pages 121-129.
1
Azarafza, H., Rezaei, H., Behmanesh, J. and Besharat, S. (2012). Results Comparison of Employing SO, GA and SA Algorithms in Optimizing Reservoir Operation (Case Study: Shaharchai Dam, Urmia, Iran). Journal of Water and Soil, Volume. 26, Number 5, pages 1101-1108. (In Farsi)
2
Bagheri, A. and Hosseini,S.A. (2011). A system dynamics approach to assess water resources development scheme in the Mashad plain, Iran, versus sustainability. ASCE Conference on the 4th International Perspective on Water Resources & the Environment, 4-6 January, Singapore
3
Dabral P.P., Jhajharia D., Mishra P., Hangshing L. and Doley B.J. (2014), Time Series Modelling of Pan Evaporation: A Case Study in the Northeast India, Global NEST Journal, Vol.16, No.2, p. 280-292.
4
Dodangeh, S., Abedi Koupai, J. and Gohari, S.A. (2012). Application of Time Series Modeling to Investigate Future Climatic Parameters Trend for Water Resources Management Purposes. J. Sci. & Technol. Agric. & Natur. Resour., Water and Soil Sci. Volume 16, Number 59. (In Farsi)
5
Ghahraman, B. and Sepaskhah, A.R. (2005). Reservoirs Operation Management. Iran-Water Resources Research. Volume 1, Number 2. (In Farsi)
6
Li, Y.P., Huang, G.H., and Nie, S.L. (2006). An interval-parameter multi-stage stochastic programming model for water resources management under uncertainty. Advances in Water Resources, 29, pages 776-789.
7
Madani, K. and Mariño,M.A. (2009). System Dynamics Analysis for Managing Iran’s Zayandeh-Rud River Basin. Water Resource Management, Volume 23, Number 11, pages 2163–2187.
8
Moghaddasi, M., Morid, S. and Araghinejad, Sh. (2009). Optimization of Water Allocation during Water Scarcity Condition Using Non-Linear Programming, Genetic Algorithm and Particle Swarm Optimization (Case Study). Iran-Water Resources Research. Volume 4, Number 3. (In Farsi)
9
Rastegaripour, F., and Karbasi, A. (2015). The Role of Marketing Mixed Elements in Consumers, Satisfaction. Journal of agricultural economics research, Volume 6, Number 4, Pages 21-37. (In Farsi)
10
Razaghi, P., Babazadeh, H. and Shourian, M. (2014). Development of multi-purpose reservoir operation hedging rule in water resources shortage conditions using MODSIM8.1. Journal of Water and Soil Resources Conservation, Volume 3, Number 2. (In Farsi)
11
Shahbazbegian, M.R. Bagheri, A. (2010). Representing systemic strategies to cope with drought impacts using system dynamics modeling. Case study: Hamadan province, Iran. Options Méditerranéennes : Série A. Séminaires Méditerranéens.
12
Sánchez, R., Rodrigo, M., Folegatti, M., Orellana, G., Alba María Guadalupe, S. and Rogério T. (2009). Dynamic systems approach assess and manage water resources in river basins. Scientia Agricola. Volume 66, Number 4, pages 427-435.
13
Sheikh khozani, Z., Hosseiny, Kh. And Rahimian, M. (2010). System Dynamic Modeling of Multipurpose Reservoir Operation To Estimate The Optimal Height Of The Dam. Journal of Modeling in Engineering. Volume 8, Number 21. (In Farsi)
14
Simonovic, P. S. (2002). World Water Dynamics: Global Modeling of Water Resources. Journal of Water Environmental Management, Volume 66, pages 249-267.
15
Wu, X., Wei, X., and Guo, W. (2012). Multi-Objective Ecological Operation Model of Cascade Hydropower Reservoirs. International Workshop on Information and Electronics Engineering (IWIEE). Proceeding Engineering. 29: pages 3996-4001.
16
Yurekli, K.and BKurunc, A. (2005). Performances of Stochastic Approaches in Generating Low Streamflow Data for Drought Analysis. Journal of Spatial Hydrology, Volume 5, Number 1, pages 20-32.
17
ORIGINAL_ARTICLE
Cadmium adsorption on TiO2 Nanoparticles in soil suspensions
In this study, some factors affect cadmium adsorption onTiO2 nanoparticles in soil and stability of nanoparticles in soil suspensions have been investigated. The results of this study showed that in soil contaminated with cadmium in suspension conditions the amount of cadmium stabilized by nanoparticles, which is attributed to adsorption of cadmium on surface of the nanoparticles, will depend on soil to water ratio (1:20, 1:10 and 1: 5), amount of soil pollution cadmium (5 and 10 mg of cadmium per kg of soil) and the use of nanoparticles (zero, 5.0, 1, 5%). So that the least amount of Cd-DTPA was found in soil to water ratio of 1: 5 and 5% of nanoparticles and in the soil contamination level of 10 milligrams per kilogram of cadmium. Also the results of stability tests indicated that the stability of titanium dioxide nanoparticles in soil suspensions over the ten days of release was comparable with that at the beginning of addition of nanoparticles, is good. In total, considering the fact that immobilization of cadmium in soils is a technique to improve the quality of soil and titanium dioxide nanoparticles showed proper stability in soil suspensions, it becomes evident that the use of nanoparticles in the decontamination of calcareous soils is appropriate.
https://ijswr.ut.ac.ir/article_62637_76f5ae734e12b86a2fd989d7684a8670.pdf
2017-07-23
349
358
10.22059/ijswr.2017.62637
Soil contamination
Cd-DTPA
TiO2 nanoparticles
Coating
Stabilization
Samaneh
Aryabod
aryabod87@yahoo.com
1
Ferdowsi University of Mashhad
AUTHOR
Amir
Fotovat
afotovat@um.ac.ir
2
Ferdowsi University of Mashhad
LEAD_AUTHOR
Reza
Khorasani
khorasani@um.ac.ir
3
Ferdowsi University of Mashhad
AUTHOR
Mohammad Hassan
Entezari
moh_entezari@yahoo.com
4
Ferdowsi University of Mashhad
AUTHOR
Bernhardt, E.S., Colman, B.P., Hochella, M.F., Cardinale,B.J., Nisbet, R.M., Richardson,C.J. and Yin, L. (2010). An ecological perspective on nanomaterial impacts in the environment. Journal of Environmental Quality.39, 1954–1965.
1
Bhatt, I. and Tripathi, B.N. (2011). Interaction of engineered nanoparticles with various components of the environment and possible strategies for their risk assessment. Chemosphere.82, 308-317.
2
Chen, G., Liu, X. and Su, C. (2011). Transport and retention of TiO2 rutile nanoparticles in saturated porous media under low – ionic – strength condition: Measurements and mechanisms. Langmuir. 27, 5393-5402
3
Chen, Q., Yin, D., Zhu, S. and Hu, X. (2012). Adsorption of cadmium (II) on humic acid coated titanium dioxide. Journal of Colloid and Interface Science. 357, 241- 248
4
Fang, J., Shan, X-Q., Wen, B., Lin, J-M. and Owens, G. (2009). Stability of titania nanoparticles in soil suspensions and transport in saturated homogeneous soil columns. Environmental Pollution. 157, 1101-1109
5
Farre, M., Sanchis, J., and Barcelo, D. 2011. Analysis and assessment of the occurrence, the fate and the behavior of nonomaterials in the environment. Trends in Analytical Chemistry. 30: 517-527
6
Fathi, M. and Mazaheri Nia, S. (2011). Effect of iron oxide nanoparticles on the availability of iron in a calcareous soil. In: Proceedings of 12th Iranian Soil Science Congress, 3-5 Sep., Tabriz University, Tabriz, Iran
7
French, R.A., Jacobson, A.R., Kim, B., Isley, S.L., Penn, R.L. and Baveye, P.C. (2009). Influence of ionic strength, pH, and cation valance on aggregation kinetics of titanium dioxide nanoparticles. Environmental Science and Technology. 43, 1354-1359
8
Gao, Y., Wahi, R., Kan, A.T., Falkner, J.C., Colvin, V.L. and Tomson, M.B. (2004). Adsorption of Cadmium on anatase nanoparticles – effect of crystal size and pH. Langmuir. 20, 9585-9593
9
Ghodsi, A., Astaraei, A. R., Emami, H. and Mirzapoor, M. H. (2011). Effect of iron oxide nanoparticles and municipal solid waste compost coated with sulfur on the concentration of micronutrients in sodic saline soil. In: Proceedings of 12th Iranian Soil Science Congress, 3-5 Sep., Tabriz University, Tabriz, Iran
10
He, Y.T., Wan, J. and Tokunaga, T. (2008). Kinetic stability of hematite nanoparticles: the effect of particle sizes. Journal of Nanoparticle Research. 10, 321-332
11
Hua, M., Zhang, S., Pan, B., Zhang, W., Lv, L. and Zhang, Q. (2012). Heavy metal removal from water/wastewater by nanosized metal oxides: a review. Journal of Hazardous Materials. 211-212, 317-331
12
Isley, S.L. and Penn, R.L. (2006). Relative brookite and anatase content in sol-gel-synthesized titanium dioxide nanoparticles. Journal of Physical Chemistry. 110, 15134-15139
13
Lecoanet, H.F., Bottero, J.Y. and Wiesner, M.R. (2004). Laboratory assessment of the mobility of nanomaterials in porous media. Environmental Science and Technology. 38, 5164-5169 in “French, R.A., Jacobson, A.R., Kim, B., Isley, S.L., Penn, R.L. and Baveye, P.C. (2009). Influence of ionic strength, pH, and cation valance on aggregation kinetics of titanium dioxide nanoparticles. Environmental Science and Technology. 43, 1354-1359”
14
Lindsay, W.L. and Norvell, W.A. (1978). Development of DTPA soil test for Zn, Fe, Mn and Cu. Soil Science Society America Journal.42, 421-428
15
Lin, D., Tian, X., Wu, F. and Xing, B. (2010). Fate and transport of engineered nonomaterials in the environment. Journal of Environmental Quality. 39, 1896-1908
16
Liu, R. and Zhao, D. (2007). Reducing leachability and bioaccessibility of lead in soils using a new class of stabilized iron phosphate nanoparticles. Water Research. 41, 2491-2502
17
Mattigod, S.V., Fryxell, G.E., Alford, K., Gilmore, T., Parker, K., Serner, J. and Engelhard, M. (2005). Functionalized TiO2 nanoparticles for use for in situ anion immobilization. Environmental Science & Technology. 39, 7306-7310
18
Mirhabibi, A.R., Aghababazade, R., Ameri, N., Poorasad, J. and Vesali N, M. R. (2006). Use of nanoparticles for removal of water pollution. Quarterly nanosociety. 2 (6), 34-38. (In Farsi)
19
Owen, R. and Depledge, M. (2005). Nanotechnology and the environment: risks and rewards. Marine Pollution Bulletin. 50, 609-612
20
Pan, G., Li, L., Zhao, D. and Chen, H. (2010). Immobilization of non-point phosphorus using stabilized magnetite nanoparticles with enhanced transportability and reactivity in soils. Environmental Pollution. 158, 35-40
21
Recillas, S., Garcia, A., Gonzalez, E., Casals, E., Puntes, V., Sanchez, A. and Font, X. (2011). Use of CeO2, TiO2 and Fe3O4 nanoparticles for the removal of lead from water - toxicity of nanoparticles and derived compounds. Desalination. 277, 213-220
22
Reddy, K.R. (2010). Nanotechnology for site Remediation: Dehalogenation of organic pollutants in soils and groundwater by nanoscale iron particles. 6th International Congress on Environmental Geotechnics, 8-12 Nov. New Delhi, India
23
Shafaei, S., Fotovat, A. and Khorasani, R. (2011). The effect of zero-valent iron nanoparticles on chemical distribution of nickel and cadmium in a calcareous soil. In: Proceedings of 12th Iranian Soil Science Congress, 3-5 Sep., Tabriz University, Tabriz, Iran
24
Shipley, H.J., Engates, K.E. and Guettner, A.M. (2011). Study of iron oxide nanoparticles in soil for remediation of arsenic. Journal of Nanoparticle Research. 13, 2387-2397
25
Varanasi, P., Fullana, A. and Sidhu, S. (2007). Remediation of PCB contaminated soils using iron nano – particles. Chemosphere. 66, 1031-1038
26
Wang, C.Y., Chen, Z.Y., Chen, B., Zhu, Y.H. and Liu, H.J. (1999). The preparation, surface modification, and characterization of metallic α-Fe nanoparticles. Chinese Journal of Chemical Physics. 12,670-674. in" Zhang, J., Hao, Z., Zhang, Z., Yang, Y. and Xu, X. (2010). Kinetics of nitrate reductive denitrification by nanoscale zero–valent iron. Process Safety and Environmental Protection. 88, 439-445"
27
Wilson, M.A., Tran, N.H., Milev, A.S., Kamali Kannangara, G.S, Volk, H. and Lu, M. (2008). Nonomaterials in Soils. Geoderma. 146, 291–302.
28
ORIGINAL_ARTICLE
Effects of salinity and soil contaminated with sewage on cadmium uptake by corn
Environmental pollution by cadmium is one of the most hazardous challenges occurring in ecosystem. This research work was conducted to study the effect of sewage sludge and water salinity on remediation of cadmium in soil through corn (Zea mays L.). The study was carried out employing corn as crop in a factorial experiment based on a completely randomized design, of 3 replications at 3 soil pollution levels of control, 20 mg.kg-1 cadmium, soil treated with sewage sludge of 20 mg.kg-1) and saline water in 2 levels (control, 3 dS.m-1). The results indicated that treated soil with cadmium and sewage sludge, decreased dry and fresh wet weight of the plant. With increase in salinity of water, dry and fresh wet weight of plant decreased. With increase in salinity, cadmium concentration present in crop shoots and roots increased by 52% as compared with control. But it could not increase cadmium uptake because of decreasing shoot and root dry matter. Sewage sludge increased the level of cadmium concentration in shoot and root by almost 12% and 15% as against treated soil with cadmium, but it could not increase cadmium uptake because of decrease in shoot and root dry matter.
https://ijswr.ut.ac.ir/article_62642_959547142206f4de35c19ee6a0100669.pdf
2017-07-23
359
368
10.22059/ijswr.2017.62642
Soil Pollution
Heavy metals
availability
Accumulation
Phytoremediation
elham
fathi
fathi_elham@ut.ac.ir
1
Studentuniversity of tehran
LEAD_AUTHOR
masoud
parsinejad
parsinejad@ut.ac.ir
2
Associate Professoruniversity of tehran
AUTHOR
farhad
mirzaei
fmirzaei@ut.ac.ir
3
Associate Professoruniversity of tehran
AUTHOR
babak
motesharezadeh
moteshare@ut.ac.ir
4
Associate Professor university of tehran
AUTHOR
Acosta J.A., Jansen B., Kalbitz K., Faz A., and Martinez S. (2011). Salinity increases mobility of heavy metals in soils. Chemosphere, 85, 1318-1324.
1
Al-Karaki, G. N. (2000). Growth and mineral acquisition by mycorrhizal tomato grown under salt stress. Mycorrhiza, 10, 51-54.
2
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31
ORIGINAL_ARTICLE
Effect of biochar and biological treatments on nutrient elements content (P, K, Ca, Mg, Fe and Mn) of Amaranthus in oil polluted soil
The presence of petroleum compounds in the soil causes environmental problems. Therefore, attempting to remediate contaminated soils is important. The present study was aimed at studying the effects of (1) different levels of biochar obtained from urban wastes and (2) the bacterium that degrades petroleum hydrocarbons on levels of nutrients in amaranth. The treatments were raw oil (0 , 2.5, and 5%; weight-based), biochar obtained from urban waste compost and fresh urban wastes (0, 1, and 2 %, weight-based), and bacterium (with and without Pseudomonas ). The results showed that with increasing the biochar level, the plant growth was promoted, with the highest values for growth parameters in plants treated with highest level of biochar. The dry and fresh weights of shoots in treatments with Pseudomonas florescence had statistically considerable differences compared to those in the other treatments. Overall, with the application of biochar and Pseudomonas, the levels of nutrients studied increased, and the maximum nutrient level was observed in the plants treated with the highest level of biochar. The highest P level (0.37%) was detected in plants treated with P1B0Ba1, and the lowest (0.23%) in plants treated with P2BM2Ba1. Moreover, the highest K level (5.16%) was recorded in plants treated with P2BM2Ba1, while the lowest (2.15%) was measured in plants treated with P0BM1Ba0 (no biological factor). The highest levels of Ca and Mg were found in treatments with biochar. The highest levels of Fe (1200.33 mg/kg) and Mn (441.5 mg/kg) were found in plants treated with P0B0Ba1, which had the biological factor, while the lowest was recorded in treatments where Pseudomonas florescence was absent. Accordingly, in order to increase the efficiency of soil remediation, it is recommended that organic matters, especially biochar, and bacterial treatments be exploited so that favorable conditions could be provided for plant growth and development.
https://ijswr.ut.ac.ir/article_62645_4b94c82d02bf600770f97f40cca8a649.pdf
2017-07-23
369
384
10.22059/ijswr.2017.62645
Oil components
Nutrient element availability
Biochar
bioremediation
pseudomonas fluorescence
Hamid
Habibi
hamid.habibi@alumni.ut.ac.ir
1
University of Tehran
AUTHOR
Babak
motesharezadeh
moteshare@ut.ac.ir
2
University of Tehran
LEAD_AUTHOR
Hoseinali
Alikhani
halikhan@ut.ac.ir
3
University of Tehran
AUTHOR
ASTM, E871-82. (2006). Standard test method for moisture analysis of particulate wood fuels, ASTM International, Pennsylvania, USA.
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49
ORIGINAL_ARTICLE
Assessment of potassium releasing ability of some bacterial isolates in in-vitro condition and identification of efficient isolates
Potassium (K) is an essential macronutrient that plays an important role in the growth and development of plants. Throughout the present study the possibility of K-release from mica minerals was evaluated through the action of several bacteria isolated from rhizosphere samples of grasses. The experiment was conducted as a factorial one, based upon a completely randomized design of three replicates comprised of two factors including 8 isolates of bacteria and two sources of potassium mineral. Following isolation of bacteria from the plant roots through NFB medium, eight selected isolates were ultimately used for the final experiment. Potassium release capability of these isolates was assessed using liquid Aleksandrov culture medium. Acid washed pretreated minerals, as a source of potassium, were added to 30 ml of Aleksandrov medium. Following incubation for one week at 26 °C and shaking at 120 rpm, released K in supernatant was assessed through flame photometer. The highest K release on the average was obtained by the isolate Az-8 (11.16 mg/l) and it was revealed that this bacterium was more efficient in releasing K from biotite than from muscovite, and the lowest rate of K release was obtained by Az-15 (2.8 mg/l). The results also revealed that K released from biotite exceed muscovite when the two types of mica compared. Among the bacterial isolates Az-8, Az-12 and Az-19 showed great potential for K release and their molecular (16S rDNA) and biochemical identification revealed that Az-8, Az-12 and Az-19 belonged to Pseudomonas genus. According to the promising results of in-vitro assays, inoculation and application of these efficient isolates will be recommended in greenhouse and field tests with different crops.
https://ijswr.ut.ac.ir/article_62647_db7ebffef44b5ec2ee6ba0c087149fcc.pdf
2017-07-23
385
395
10.22059/ijswr.2017.62647
Potassium releasing bacteria
Aleksandrov
Pseudomonas
biotite
Muscovite
Shokoofeh
Moradi
moradishokufeh@gmail.com
1
University of Tabriz
AUTHOR
Mohammad Reza
Sarikhani
rsarikhani@yahoo.com
2
University of Tabriz
LEAD_AUTHOR
Naser
Aliasgharzad
n-aliasghar@tabrizu.ac.ir
3
University of Tabriz
AUTHOR
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31
Uroz, S., Calvaruso, C., Turpault, M. P., and P. Frey-Klett. (2009). Mineral weathering by bacteria: ecology, actors and mechanisms. Trends in Microbiology, 17(8), 378–387
32
YiFeng, Z., L. YunXia., and L. HuaZhong. (2009). Separation and purification of the potassium - releasing bacteria. Journal of Hubei University for Nationalities - Natural Science edition, 27(3), 285-288.
33
Zhang, C., and F. Kong. (2014). Isolation and identification of potassium-solubilizing bacteria from tobacco rhizospheric soil and their effect on tobacco plants.Applied Soil Ecology, 82, 18-25.
34
ORIGINAL_ARTICLE
Optimization of Removal Process of Petroleum Hydrocarbons from Soil Using Microwave Radiation and Its Effect on Some Soil Biological Characteristics
Such thermal methods as MicroWave (MW) radiations are considered as fast and efficient approaches in removal of organic pollutants from aquatic and terrestrial environments. This study was carried out to find the optimum conditions for oil removal from contaminated soils treated by MW irradiation. Following soil sampling from Tehran Refinery surroundings, the samples were treated under various conditions for including MW power intensity (770, 1100 and 1250 w) and frequency of 2.45 GHz, time of irradiation (5, 10 and 15 min), soil moisture (1, 10 and 15 % w/w) and added activated carbon (0, 2.5 and 5 % w/w). The optimum conditions of oil removal were obtained from results of Taguchi L9 orthogonal array. Besides, the effect of MW irradiation on some chemical and biological properties of soil was also investigated. Results indicated that the optimum conditions of the investigated parameter ranges were as follows: MW power (1100 w), irradiation time (15 min), soil moisture (1 % w/w) and added activated carbon (5 % w/w). About 70 % of petroleum hydrocarbons were dissipated within optimum conditions. Although the method exhibited some negative effects on respiration and population and respiration of soil microorganisms, still it can be used as an effective and fast approach for remediation of highly polluted soils considering the economic feasibility.
https://ijswr.ut.ac.ir/article_62656_55cc977f39c8d6a02d3106941113432b.pdf
2017-07-23
397
404
10.22059/ijswr.2017.62656
Microwave
Petroleum Pollutants
Soil Pollution
Remediation
محسن
سلیمانی
m.soleimani@cc.iut.ac.ir
1
عضو هیات علمی گروه محیط زیست/ دانشگاه صنعتی اصفهان
LEAD_AUTHOR
نجمه
جابری
sonia_jaberi@yahoo.com
2
فارغ التحصیل کارشناسی ارشد محیط زیست/ دانشگاه صنعتی اصفهان
AUTHOR
Appleton, T., Colder, V., Kingman, S., Lowndes, I. and Read, A. (2005) Microwave technology for energy-efficient processing of waste. Applied Energy, 81, 85–113.
1
Bloem, J., Hopkins, D. W. and Benedetti, A. (2005) Microbiological methods for assessing soil quality. Wallingford: CABI.
2
Chang, C. J., Tyagi, V. K. and Lo S. L. (2011) Effects of microwave and alkali induced pretreatment on sludge solubilization and subsequent aerobic digestion. Bioresource Technology, 102, 7633-7640.
3
Chien, Y. C. (2012) Field study of in situ remediation of petroleum hydrocarbon contaminated soil on site using microwave energy. Journal of Hazardous Materials 15, 457– 461.
4
Cioni, B. and Petarca, L. (2011) Petroleum products removal from contaminated soils using microwave heating. Chemical Engineering Transactions, 24, 1033-1038.
5
Darbar, S. R. and Lakzian, A. (2007) Evaluation of chemical and biological consequences of soil sterilization methods. Caspian Journal of Environmental Sciences, 5, 87-91.
6
Department of Environmental Quality (DEQ), (2003) Risk-Based Decision Making for the Remediation of Petroleum-Contaminated Sites. State of Oregon, Land Quality Division.
7
Ferris, R. S. (1983) Effect of microwave oven treatment on microorganisms in soil. The American Phytopathological Society, 74(1), 121-126.
8
Jacob, J., Chia, L. H .L. and Boey, F. Y. C. (1995) Review—thermal and non-thermal interaction of microwave radiation with materials. Journal of Materials Science, 21, 5321–5327.
9
Jones, D. A., Lelyveld, T. P., Mavrofidis, S. D., Kingman, S. W. and Miles, N. J. (2002) Microwave heating applications in environmental engineering – a review. Resources, Conservation and Recycling, 34, 75–90.
10
Kawala, Z. and Atamanaczuk, T. (1998) Microwave-enhanced thermal decontamination of soil, Environmental Science and Technology, 32, 2602-2607.
11
Lin, Q. and Brooks, P. C. “(1999) An evaluation of the substrate-induced respiration method. Soil Biology and Biochemistry, 31, 1969-1983.
12
Li, D., Quan, X., Zhang, Y. and Zhao, Y. (2008) Microwave-induced thermal treatment of petroleum hydrocarbon-contaminated soil, Soil and Sediment Contamination, 17, 486–496.
13
Li, D., Zhang, Y., Quan, X. and Zhao, Y. (2009) Microwave thermal remediation of crude oil contaminated soil enhanced by carbon fiber, Journal of Environmental Sciences, 21, 1290–1295.
14
Lordache, D. 2010. Utilization of microwave energy for decontamination of oil polluted soils. Journal of Microwave Power and Electromagnetic Energy. 44 (4), 213-221.
15
Mansurov, Z. A., Ongarbaev, E. K. and Tuleutaev, B. K. (2001) Contamination of soil by crude oil and drilling muds: Use of wastes by production of road construction materials. Chemistry and Technology of Fuels and Oils, 6, 441–443.
16
Menendez, J. A., Inguanzo, M. and Pis, J. J. (2002) Microwave-induced pyrolysis of sewage sludge, Water Research, 36, 3261– 3264.
17
Pietikainen, J., Pettersson, M. and Baath, E. (2005) Comparison of temperature effects on soil respiration and bacterial and fungal growth rates , FEMS Microbiology Ecology, 52, 49-58.
18
Ranjit, K. R. (2001). Design of experiments using the Taguchi approach: 16 steps to product and process improvement. New York: Wiley.
19
Remya, N. and Jih, G. L. (2011) Current status of microwave application in wastewater treatment, A review. Chemical Engineering Journal, 166, 797–813.
20
Sang, A. H. and Kyoung, S. C. (2010) A study of a combined microwave and thermal desorption process for contaminated soil. Environmental Engineering Research, 15(4), 225-230.
21
Schumacher, B. A. (2002) Methods for the determination of total organic carbon (TOC) in soils and sediments. United States Environmental Protection Agency Environmental Sciences Division National.
22
Shang, H., Robinson, J. P., Kingman, S. W., Snape, C. E. and Wu, Q. (2007) Theoretical study of microwave enhanced thermal decontamination of oil contaminated waste. Chemical Engineering and Technology, 30(1), 121–130.
23
Shang. H., Kingman, S. W., Snape, C. E. and Robinson, J. P. (2006) Microwave remediation of oil contaminated soils. Chinese Journal of Geochemistry, 25, 113.
24
USEPA (2006). In situ Tretment Technologies fot Contaminated Soil.Engineering Forum Issue Paper. USA.
25
Waling, I. W., Vanvark, V. J. G., Houba, J. J. and Vander, I. (1989) Soil and plant analysis, a series of syllab. In Dixon, J. B., Weed, S. B. (Eds.), Plant analysis procedures. Wageningen Agriculture University. pp. 567-589.
26
Windgasse, G. and Dauerman L. (1992) Microwave treatment of hazardous wastes: remediation of soils contaminated by non-volatile organic chemicals like dioxins. Microwave Power Electromagnetic Energy Journal, 27, 54–61.
27
Xitao, L. and Gang, Y. (2006) Combined effect of microwave and activated carbon on the remediation of polychlorinated biphenyl-contaminated soil, Chemosphere, 63, 228–235.
28
Xitao, L., Quan, Z., Guixiang, Z. and Run, W. (2008) Application of microwave irradiation in the removal of polychlorinated biphenyls from soil contaminated by capacitor oil, Chemosphere, 72, 1655–1658.
29
Zolfaghari ,Gh., Esmaili-Sari, A., Anbia, M.,Younesi, H., Amirmahmoodi, Sh. and Ghafari-Nazari, A. (2011) Taguchi optimization approach for Pb (II) and Hg (II) removal from aqueous solutions using modified mesoporous carbon. Journal of Hazardous Materials, 192, 1046-1055.
30
ORIGINAL_ARTICLE
Synthesis of Nano and Micro-Organobentonite Using Hexadecyltrimethylammonium Bromide and Evaluation of Their Absorption Efficiency and Release of Nitrate in Aqueous Solution
Organoclays are natural clay minerals modified through polymer compounds and applied for especial purposes. By being done so, the clay layers are permanently propped with high surface areas in the interlayers. The objective followed in this study was to find out the absorption efficiency and release of nitrate in aqueous solutions through modified Iranian bentonite (Arak). Micro and nano-bentonites were first modified by hexadecyltrimethylammonium bromide, a cationic surfactant. The adsorption efficiencies within 0, 3, 6, 9, 14, 20, 30 and 40 mM nitrate (by modified micro and nano-organobentonite particles) in surfactant loadings of 100 and 200% CEC were investigated in a completely randomized factorial design. Furthermore, to identity the stability of adsorbed nitrate by modified bentonite, the nitrate desorption process was performed at nitrate concentrations of 6 and 20 mM within 15, 30, 45 minutes and in 1, 2, 8 and 16 hours in a completely randomized factorial design. The results indicated that absorption efficiency of nitrate by nano-organobentonite with surfactant loading of 200% CEC in 3, 6, 9, 14, 20, 30 and 40 mM nitrate were 96, 94, 91, 90, 84, 76 and 68%, whereas in micro-organobentonite were 87, 92, 89, 86, 74, 80 and 68% respectively. The results finally revealed that concentration of surfactant was significant on adsorption and release of nitrate (p≤0.01), but the size particles was not significant (p≤0.01). Nano-bentonite in 200% CEC of HDTMA and low concentration of nitrate benefits from a highest adsorption efficiency (96%) with minimum release of 3.7%.
Akbarzadeh, A., Manshori, M., Bashiri, S. and Moradi, M. (2011). Evaluation of efficacy modified bentonite to reduce phosphorus from aqueous solutions. International Conference on Water and Wastewater.26-28 April, 2011, pp.9-14.
Armstrong , G.A. (1963). Determination of intrate in water by ultraviolet Spectrophotometry . Anal. chem., 35:1292.
Aroke, U.O., El-Nafaty, U.A, and Osha, O.A. (2014). Removal of oxyanion contaminents from wastewater by sorptio on to HDTMA-Br surface modified organo-kaolinit clay. International Journal of Emerging Technology and Advanced Engineering,4(1) 475-484.
Azam, N., Eslamian, S., Gheisari, M., and Abedi-Koupani, J. (2013). Reduce nitrate from aqueous solution using surfactant-modified bentonite. 1st national conference planning, conservation, environmental protection and sustainable development, 3 Dec., Shahid Mofateh University of Hamadan.
Bhattacharya, S., and Aadhar, M. (2014). Studies on Preparation and analysis of Organoclay Nano Particles. Research Journal of Engineering Sciences, 10-16.
Bakhtyari, S., Shirvani, M., and Sharyatmadari, H. (2014). Effect of modified Bentonite clay to reduce leaching of 2,4D herbicide. 1st National Conference on Sustainable Management of Soil and Environmental Resources, 10-11 Sep., Shahid Bahonar University of Kerman.
Bagherifam, A., S., Komarneni, S., Lakzian, A., Fotovati, A., Khorasani, R., Huang, W., Wang, Y. (2014). Highly selective removal of nitrate and perchlorate by organoclay. Applied clay science. No. 6, 126-132.
Boyd, S.A., and Jaynes, W.F. 1994. Role of layer charge in organic contaminant sorption by organoclays. P. 48-77. In A.R. Mermut (ed.) Layer charge characteristics of 2:1 silicate clay minerals. Vol. 6. The Clay Minerals Society, Boulder, CO.
Cho, H.H., Lee, T., Hwang, S.j., and Park, J.W. (2005). Iron and organo-bentonite for the reduction and sorption. Chemosphere, 58(1):103-108.
Gunay, A., Arslankaya, E., and Tosun, I. (2007). Lead removal from aqueous solution by natural and pretreated clinoptilolite: Adsorption equilibrium and kinetics, J. Hazard. Mater. 146(1–2), 362–371.
Hrenovic, R., Sekovanic, and An.(2008). Interaction of surfactant-modified zeolites and phosphate accumulating bacteria. J. Hazard. Mater. 156(1-3): 576-582.
Jaynes, W.F., and Boyd S.A. 1991a. Clay mineral type and organic compound sorption by hexadecyltrimethylammonium-exchanged clays, Soil Sci. Soc. Am. J. 55:43-48.
Jaynes, W.F., and Boyd S.A. 1991b. Hydrophobicity of siloxane surfaces in smectites as evealed by aromatic hydrocarbon adsorption from water. Clays Clay Minerals. 39:428-436.
Kittrick, J.A., and Hope, E.W. (1963). A procedure for particle size separations of soils for x-ray diffraction analysis. Soil science, 96(5)319-325.
Lee, J., Choi, J., and Park, J.W. (2002). Simultaneous sorption of lead and chlorobenzene by organobentonite. Chemosphere, 49, 1309–1315.
Li, Z. (2003). Use of surfactant-modified zeolite as fertilizer carrier sto control nitrate release.Micropor. Mesopor. Mat. 61(1-3): 181-188.
Li, Z., and Bowman, R.S. (1998). sorption of choromate and PCE by surfactant-modified clay minerals.Environmental Engineering Science, 15 (3), 237-245
Li, Z. (1999). Sorption Kinetics of Hexadecyltrimethylammonium on Natural Clinoptilolite. Langmuir, 1999, 15 (19), pp 6438–6445
Lima-Guerra, D., Mello, I., Resende, R., and Silva, R. (2014). Use of Bentonite and Organobentonite as Alternatives of Partial Substitution of Cement in Concrete Manufacturing. International Journal of Concrete Structures and Materials, 15-26.
Mahdavi Mazde, A., Liaghat, A., and Sheikh mohamadi, Y. (2011). Nitrate Removal from agricultural wastes using modified zeolite. IWRJ, 117-124. (In Farsi)
Malakootian, M., Yousefi, N., and Jafarzade, N. (2010). Kinetics modeling and isotherm for adsorption of phosphate from aqueous solution by modified clinoptilolite. Journal of Water and Soil, 21-29. (In Farsi)
Malekian, R., Abedi-Koupai, J., and Eslamian, S. S. (2013). Ion-Exchange Process for nitrate removal and release using surfactant modified zeolite. Sci. and Technol. Agric. and Natur. Resour. Water and Soil Sci., 190-202. (In Farsi)
Malla, P.B. (2002). Vermiculite. pp. 501-530. In J. B. Dixon and D. G. Schulze (ed.) Soil mineralogy with environmental application. Soil Science Society of America, Inc. Madison, Wisconsin, USA.
Nabizadeh, R., Mahdavi, A. H., Ghadiri, S., Nasseri, S., Mesdaghinia, A., and Abouee, A. (2012). MTBE adsorption on Surfactant-Modified Zeolites from aqueous solutions. Journal of North Khorasan University of Medical Sciences, 4(3):493, 483-492.(In Farsi)
Nawani, P., Desai, P., Lundwall, M., Gelfer M.Y., Hsiao, B.S. Rafailovich, M., Frenkel, A., Tsou, A.H., Gilman, J.W., and Khalid, S. (2007). Polymer nanocomposites based on transition metal ion modified organoclay. Polymer, 48 (3), 827-840.
Pernyeszi, T., Kasteel, R., Witthuhn, B., Klahre, P., Vereecken, H., and Klumpp, E. (2006). Organoclays for soil remediation: Adsorption of 2,4-dichlorophenol on organoclay/aquifer material mixtures studiedunder static and flow conditions. Applied Clay Science.,32; 179-189.
Rafiei, H., Shirvani, M., and Behzad, T. (2014). Performance of Cationic Surfactant Modified Sepiolite and Bentonite in Lead Sorption from Aqueous Solutions. Journal of Water and Soil, 28(4), 818-835.(In Farsi).
Ranjbaran, M., Lancarani, M., and Zamanzade, M. (2013), Applied clay mineralogy. Tehran Un. Press, 187p. (Translated in Persian).
Reid-Soukup, D. A. and Ulery, A. L. (2002). Smectite. pp. 467-500. In J. B. Dixon and D. G. Schulze (ed.) Soil mineralogy with environmental application. Soil Science Society of America, Inc. Madison, Wisconsin, USA.
Rhoades, J. D. (1982). Cation-exchange capacity. pp. 149-157. In A. L. Page et al. (ed.) Methods of soil analysis. Part 2. 2nd ed. Agron. Monogr. 9. ASA and SSSA, Madison, WI.
Sheng, G., Xu, S., and Boyd, S. 1996. Mechanism(s) controlling sorption of neutral organic contaminants by surfactant-derived and natural organic matter. Environental Science Technology, 30:1553-1557.
Shokouh Saljoghi, Z., malekpour, A., Rafiee, G., Imani, A., and Bakhtiary, M. (2010). Removal of Nitrite and Nitrate from Recirculation Aquaculture System Effluent (RAS) by Modified Bentonites. J. of Water and Wastewater, 46-54. (In Farsi)
Wang , Y., Liu , S., Xu,, Z., Han, T., Chuan, S., and Zhu, T. (2007). Ammonia removal from leachate solution using natural Chinese clinoptilolite. J. Hazard Mater, 136(3):735-740.
Xi, Y., Mallavarapu, M., and Naidu, R. (2010). Preparation, characterization of surfactants modified clay minerals and nitrate adsorption. Applied Clay Science, 48: 92–96
Xu, L., Zhanga, M., and Zhu, L. (2014). Adsorption–desorption behavior of naphthalene onto CDMBA modified bentonite: Contribution of the π–π interaction. Applied Clay Science, 100: 29-34.
Xu, S., and Boyd, S.A. 1994. Cation exchange chemistry of hexadecyltrimethylammonium in a subsoil containing vermiculite. Soil Sci. Soc. Am. J. 58:1382-1391
Zhu, R., Zhu, L. Zhu, J., Ge, F. and Wang, T. (2009). Sorption of naphthalene and phosphate to the CTMAB–Al13 intercalated bentonites. Journal of Hazardous Materials. 168: 1590–1594.
https://ijswr.ut.ac.ir/article_62657_e2f0e21f23c1097be325ef27261e2b03.pdf
2017-07-23
405
415
10.22059/ijswr.2017.62657
Modified bentonite
cationic surfactant
organoclay
CEC
Fariba
Nemati
nemati.fariba@gmail.com
1
1. M.Sc. Student, Department of Soil Sciences, Faculty of Agricultural Sciences, Shahed University
AUTHOR
Hossein
Torabi
htorabi@shahed.ac.ir
2
Shahed University
LEAD_AUTHOR
Amir Mohammad
Naji
amnaji1976@yahoo.com
3
Assist. Prof., Department of Plant Breeding and Biothecnology, Faculty of Agricultural Sciences, Shahed University
AUTHOR
Akbarzadeh, A., Manshori, M., Bashiri, S. and Moradi, M. (2011). Evaluation of efficacy modified bentonite to reduce phosphorus from aqueous solutions. International Conference on Water and Wastewater.26-28 April, 2011, pp.9-14.
1
Armstrong , G.A. (1963). Determination of intrate in water by ultraviolet Spectrophotometry . Anal. chem., 35:1292.
2
Aroke, U.O., El-Nafaty, U.A, and Osha, O.A. (2014). Removal of oxyanion contaminents from wastewater by sorptio on to HDTMA-Br surface modified organo-kaolinit clay. International Journal of Emerging Technology and Advanced Engineering, 4(1) 475-484.
3
Azam, N., Eslamian, S., Gheisari, M., and Abedi-Koupani, J. (2013). Reduce nitrate from aqueous solution using surfactant-modified bentonite. 1st national conference planning, conservation, environmental protection and sustainable development, 3 Dec., Shahid Mofateh University of Hamadan.
4
Bhattacharya, S., and Aadhar, M. (2014). Studies on Preparation and analysis of Organoclay Nano Particles. Research Journal of Engineering Sciences, 10-16.
5
Bakhtyari, S., Shirvani, M., and Sharyatmadari, H. (2014). Effect of modified Bentonite clay to reduce leaching of 2,4D herbicide. 1st National Conference on Sustainable Management of Soil and Environmental Resources, 10-11 Sep., Shahid Bahonar University of Kerman.
6
Bagherifam, A., S., Komarneni, S., Lakzian, A., Fotovati, A., Khorasani, R., Huang, W., Wang, Y. (2014). Highly selective removal of nitrate and perchlorate by organoclay. Applied clay science. No. 6, 126-132.
7
Boyd, S.A., and Jaynes, W.F. 1994. Role of layer charge in organic contaminant sorption by organoclays. P. 48-77. In A.R. Mermut (ed.) Layer charge characteristics of 2:1 silicate clay minerals. Vol. 6. The Clay Minerals Society, Boulder, CO.
8
Cho, H.H., Lee, T., Hwang, S.j., and Park, J.W. (2005). Iron and organo-bentonite for the reduction and sorption. Chemosphere, 58(1):103-108.
9
Gunay, A., Arslankaya, E., and Tosun, I. (2007). Lead removal from aqueous solution by natural and pretreated clinoptilolite: Adsorption equilibrium and kinetics, J. Hazard. Mater. 146(1–2), 362–371.
10
Hrenovic, R., Sekovanic, and An.(2008). Interaction of surfactant-modified zeolites and phosphate accumulating bacteria. J. Hazard. Mater. 156(1-3): 576-582.
11
Jaynes, W.F., and Boyd S.A. 1991a. Clay mineral type and organic compound sorption by hexadecyltrimethylammonium-exchanged clays, Soil Sci. Soc. Am. J. 55:43-48.
12
Jaynes, W.F., and Boyd S.A. 1991b. Hydrophobicity of siloxane surfaces in smectites as evealed by aromatic hydrocarbon adsorption from water. Clays Clay Minerals. 39:428-436.
13
Kittrick, J.A., and Hope, E.W. (1963). A procedure for particle size separations of soils for x-ray diffraction analysis. Soil science, 96(5)319-325.
14
Lee, J., Choi, J., and Park, J.W. (2002). Simultaneous sorption of lead and chlorobenzene by organobentonite. Chemosphere, 49, 1309–1315.
15
Li, Z. (2003). Use of surfactant-modified zeolite as fertilizer carrier sto control nitrate release. Micropor. Mesopor.
16
Mat. 61(1-3): 181-188.
17
Li, Z., and Bowman, R.S. (1998). sorption of choromate and PCE by surfactant-modified clay minerals. Environmental Engineering Science, 15 (3), 237-245
18
Li, Z. (1999). Sorption Kinetics of Hexadecyltrimethylammonium on Natural Clinoptilolite. Langmuir, 1999, 15 (19), pp 6438–6445
19
Lima-Guerra, D., Mello, I., Resende, R., and Silva, R. (2014). Use of Bentonite and Organobentonite as Alternatives of Partial Substitution of Cement in Concrete Manufacturing. International Journal of Concrete Structures and Materials, 15-26.
20
Mahdavi Mazde, A., Liaghat, A., and Sheikh mohamadi, Y. (2011). Nitrate Removal from agricultural wastes using modified zeolite. IWRJ, 117-124. (In Farsi)
21
Malakootian, M., Yousefi, N., and Jafarzade, N. (2010). Kinetics modeling and isotherm for adsorption of phosphate from aqueous solution by modified clinoptilolite. Journal of Water and Soil, 21-29. (In Farsi)
22
Malekian, R., Abedi-Koupai, J., and Eslamian, S. S. (2013). Ion-Exchange Process for nitrate removal and release using surfactant modified zeolite. Sci. and Technol. Agric. and Natur. Resour. Water and Soil Sci., 190-202. (In Farsi)
23
Malla, P.B. (2002). Vermiculite. pp. 501-530. In J. B. Dixon and D. G. Schulze (ed.) Soil mineralogy with environmental application. Soil Science Society of America, Inc. Madison, Wisconsin, USA.
24
Nabizadeh, R., Mahdavi, A. H., Ghadiri, S., Nasseri, S., Mesdaghinia, A., and Abouee, A. (2012). MTBE adsorption on Surfactant-Modified Zeolites from aqueous solutions. Journal of North Khorasan University of Medical Sciences, 4(3):493, 483-492.(In Farsi)
25
Nawani, P., Desai, P., Lundwall, M., Gelfer M.Y., Hsiao, B.S. Rafailovich, M., Frenkel, A., Tsou, A.H., Gilman, J.W., and Khalid, S. (2007). Polymer nanocomposites based on transition metal ion modified organoclay. Polymer, 48 (3), 827-840.
26
Pernyeszi, T., Kasteel, R., Witthuhn, B., Klahre, P., Vereecken, H., and Klumpp, E. (2006). Organoclays for soil remediation: Adsorption of 2,4-dichlorophenol on organoclay/aquifer material mixtures studiedunder static and flow conditions. Applied Clay Science.,32; 179-189.
27
Rafiei, H., Shirvani, M., and Behzad, T. (2014). Performance of Cationic Surfactant Modified Sepiolite and Bentonite in Lead Sorption from Aqueous Solutions. Journal of Water and Soil, 28(4), 818-835.(In Farsi).
28
Ranjbaran, M., Lancarani, M., and Zamanzade, M. (2013), Applied clay mineralogy. Tehran Un. Press, 187p. (Translated in Persian).
29
Reid-Soukup, D. A. and Ulery, A. L. (2002). Smectite. pp. 467-500. In J. B. Dixon and D. G. Schulze (ed.) Soil mineralogy with environmental application. Soil Science Society of America, Inc. Madison, Wisconsin, USA.
30
Rhoades, J. D. (1982). Cation-exchange capacity. pp. 149-157. In A. L. Page et al. (ed.) Methods of soil analysis. Part 2. 2nd ed. Agron. Monogr. 9. ASA and SSSA, Madison, WI.
31
Sheng, G., Xu, S., and Boyd, S. 1996. Mechanism(s) controlling sorption of neutral organic contaminants by surfactant-derived and natural organic matter. Environental Science Technology, 30:1553-1557.
32
Shokouh Saljoghi, Z., malekpour, A., Rafiee, G., Imani, A., and Bakhtiary, M. (2010). Removal of Nitrite and Nitrate from Recirculation Aquaculture System Effluent (RAS) by Modified Bentonites. J. of Water and Wastewater, 46-54. (In Farsi)
33
Wang , Y., Liu , S., Xu,, Z., Han, T., Chuan, S., and Zhu, T. (2007). Ammonia removal from leachate solution using natural Chinese clinoptilolite. J. Hazard Mater, 136(3):735-740.
34
Xi, Y., Mallavarapu, M., and Naidu, R. (2010). Preparation, characterization of surfactants modified clay minerals and nitrate adsorption. Applied Clay Science, 48: 92–96
35
Xu, L., Zhanga, M., and Zhu, L. (2014). Adsorption–desorption behavior of naphthalene onto CDMBA modified bentonite: Contribution of the π–π interaction. Applied Clay Science, 100: 29-34.
36
Xu, S., and Boyd, S.A. 1994. Cation exchange chemistry of hexadecyltrimethylammonium in a subsoil containing vermiculite. Soil Sci. Soc. Am. J. 58:1382-1391
37
Zhu, R., Zhu, L. Zhu, J., Ge, F. and Wang, T. (2009). Sorption of naphthalene and phosphate to the CTMAB–Al13 intercalated bentonites. Journal of Hazardous Materials. 168: 1590–1594.
38
ORIGINAL_ARTICLE
Numerical modeling of dewatering system to construct pump basins in open sea water intake system by MODFLOW
Pump basins are important structures in open sea water intakes. Dewatering construction site of these structures with no leakage inside the site is an essential issue. Throughout this paper, two common aspects of dewatering systems, namely big wells and well points are evaluated to make the construction site of the pump basin ready at the intake system of Bushehr desalination installations. To achieve this, MODFLOW software was employed to model the dewatering systems with results demonstrating the performance of the considered dewatering methods. According to the observed results, to have an efficient dewatering system, a number of about 26 wells as high capacity ones (well discharges ranging from 0.5 to 5.5 lit/s)are needed vs. 119 well points (well discharges ranging from 0.1 to 1.1 lit/s). In addition, sensitivity analysis of the system, as regards the variation of soil conductivity (in both space and time) proves that the well point system is more efficient than the high capacity well system, for dewatering an uncertain site.
https://ijswr.ut.ac.ir/article_62658_8b55ec5e89bb9fd152337a7999618cd7.pdf
2017-07-23
428
417
10.22059/ijswr.2017.62658
Dewatering
big well
well point
Bushehr beach
morteza
zanganeh
m.zanganeh@gu.ac.ir
1
Golestan Universirty
LEAD_AUTHOR
Seyed Hamed
Meraji
h.meraji@pgu.ac.ir
2
Khalije Fars University
AUTHOR
Barani, S., Shafiei, S., Malekinezhad, H. and Nezhadkoraki F. (2010). Modeling of ground water in Morost aquifer via MODFLOW and Pest, 1th international conference on plant, water, soil and weather modeling. (In Farsi)
1
Chitsazan, M. and Kashkoli H.A. )2002(. Groundwater modeling and problems, Shahid Chamran University publishing, Ahwaz (In Farsi)
2
Derakhshandehro, G., Vaghefi, M. and Saeidi G.R. (2009). Determination of groundwater storage and velocity head via the MODFLOW (Case study: Bashar River watershed), 10th national irrigation and evaporation conference. (In Farsi)
3
Derakhshandehro and Barani G.A., (2015). Evaluation of Artificial inchagre on Gachsaran Emamzadeh Jafar aquifer by Mathematical model and MODFLOW. International Conference of Science and Technology (In Farsi).
4
Fethi L., Ammar M., Mourad B., Jamila T., Christian L. (2012). Implementation of a 3-D groundwater flow model in a semi-arid region using MODFLOW and GIS tools: The Zéramdine–Béni Hassen Miocene aquifer system (east-central Tunisia). Computers & Geosciences, Volume 48, November, Pages 187-198
5
Hossiensarbazi A. and Esmaeili K. (2012). Modeling of groundwater (Case study: Nishabor Aquifer). Journal of Science and Irigation, P.P. 66, No. 4. (In Farsi).
6
Janparvar M. and Alavimoghadam M.R. (2015). Estimating water discharge decreasing of Ghazvin Aquifer to have an equilibrium condition. First National Conference on Agriculture, Ardebil (In Farsi).
7
Kalantari, N.(1998). Groundwater Hydrogeology, 3th publishing, Shahid Chamran University publishing, Ahwaz (In Farsi).
8
Mashhadi, L. and Baghvand A. (2010). Evaluation and modeling of burial waste load contamination effects over groundwater resources (Case study: Amanabad Aquifer) . 4th conference and exhibition of environmental engineering.
9
Norvijeh, Geotechnical Report for Bushehr Desalination factory, (2015), Geotechnical Lab for Iran transportation ministry.
10
McDonald, J. M., & Harbaugh, A. W. (1988). MODFLOW, a modular 3D finite difference ground-water flow model. US Geological Survey, Open File Report, 83-875
11
Mohamadkhani M. and Katibeh H. )2004(. Modeling of groundwater in Sechahoon mine by MODFLOW, Mineral Engineering Conference (In Farsi).
12
Nemati, K. M. (2007), Temporary Structures, Construction Dewatering and Ground Freezing, UNIVERSITY OF WASHINGTON, DEPARTMENT OF CONSTRUCTION MANAGEMENT
13
Saghravani S. R. and Mustaph S. (2011). A Prediction of Contamination Migration in an Unconfined Aquifer. with Visual MODFLOW: A Case Study, World Applied Sciences Journal 14 (7): 1102-1106, 2011.
14
THCDWAI (Temporary High Capacity Dewatering Well Application Instructions) (2012). Department of Natural Resources, State of Wisconsin.
15
Todd W. R. and R. B. Kenneth. (2001). Report: Delineation of capture zones for municipal wells in fractured dolomite, Sturgeon Bay, Wisconsin, USA. Hydrogeology Journal, 9:432–450. M.
16
Torshizi, S., Haghighatjoo, P., R., Sheibanian, A., R. and Roeintan, S. (2015). Modeling of Sarvestan aqueifer groundware via MODFLOW package. Water engineering conference and exhibition (In Farsi).
17
Thorley, M. and P. Callander. (2005). Christchurch city groundwater model. Environment Canterbury Report, Vol. 05/53,
18
Zeighaminezhad, M., Ghazanfarimoghadam, M.S. and Barani. G.A. (2015). Determintion of freshwater well restriction by MODFLOW model. 2 th Conference of Agriculture, Natural resources and environment of Iran. (In Farsi)
19
www.groundwatereng.com.
20
www.khansahebsykes.com.
21
ORIGINAL_ARTICLE
Effect of Soil Salinity and Aeration Stresses on the Root and Yield Components in Wheat and Bean
The effects of soil matric suction and salinity were investigated on the yield components and root development of the corps, wheat and bean within greenhouse conditions. The results showed that yield components and root dry weights of wheat and bean increased with increase in matric suction (from 2kPa) and reached their maximum values at suctions of 6-10 kPa. At suctions higher than 10kPa and under EC≤8dSm-1 for wheat vs. EC≤4dSm-1 for bean, all the yield components of wheat and bean (except for 1000-kernel weight) decreased, while under higher salinities, their values remained nearly the same. At suctions higher than 10kPa and under all salinity levels, 1000-kernel weights of wheat and bean remained nearly constant. The salinities of low to medium levels did not clearly affect yield and root development of either plant. Minimum root densities of wheat and bean occurred at suction 6kPa while at other points of suction (2, 10 and 33kPa), their values almost corresponded with each other. Salinity did not clearly affect wheat and bean root densities. Wheat shoot-root ratio decreased with matric suction (up to 10kPa) under EC≤8dSm-1, while under higher salinities, this ratio increased with suctions. At 10kPa suction, weight ratio values approached each other, then remained nearly constant at higher suctions. The results finally revealed that plant response to salinity stress depends on aeration conditions in the root zone and the deficit in soil aeration can amplify the salinity stress.
https://ijswr.ut.ac.ir/article_62659_de3e2aeaad9f2b17f6d1e0f73ea43a7c.pdf
2017-07-23
429
440
10.22059/ijswr.2017.62659
Aeration stress"
Soil matric suction"
Salinity stress"
Yield"
Mahnaz
Khatar
mahnazkhataar@znu.ac.ir
1
Zanjan University
LEAD_AUTHOR
Mohammad Hosein
Mohammadi
mhmohmad@ut.ac.ir
2
University of Tehran
AUTHOR
Farid
Shekari
shekari@znu.ac.ir
3
University of Zanjan
AUTHOR
Abedi, R.A., Tadayyon, A. and Aminian, R. (2005). Economic Investigation of Common Bean in Chaharmohal and Bakhtiari. The first conference of national grain. Ferdowsi university of mashhad. 172-176. (In Farsi).
1
Aggarwal, P.K., Kalra, N., Singh, A.K. and Singha, S.K. (1994). Analyzing the limitations set by climatic factors, genotype, and water and nitrogen availability on productivity of wheat I. The model description, parameterization and validation. Field Crops Research. 38, 73-91.
2
Andrenelli, M.C., Mocali, S., Pellegrini, S. and Vignozzi, N. (2016). Modification of hydrological properties in a fine textured soil following field application of pelletized biochar: investigation of the mechanism involved. EGU General Assembly in Vienna Austria. p. 12847.
3
Bagheri, A., Nezami, A. and Persa, H. (2006). An Analysis to Strategy of Pulse Research in Iran Based Upon the First National Pulse Symposium Approaches. Iranian agricultural research. Science information database, 4, 1-13. (In Farsi).
4
Barrett-Lennard, E. G. (2003). The interaction between waterlogging and salinity in higher plants: causes, consequences and implications. Plant and Soil. 253, 35-54.
5
Bhattarai, S. P., Su, N. and Midmore, D. J. (2005). Oxygen unlocks yield potential of crops in oxygen-limited soil environments. Advances in Agronomy. 88, 313-377.
6
Brzezinska, M., Wodarczyk, T. and Glinski, J. (2004). Effect of methane on soil dehydrogenase activity. International Agrophysics. 18, 213–216.
7
Carter, J. L., Colmer, T. D. and Veneklaas, E. J. (2006). Variable tolerance of wetland tree species to combined salinity and waterlogging is related to regulation of ion uptake and production of organic solutes. New Phytologist. 69, 123–134.
8
Chapman, H. D. and Pratt, F. P. (1982). Determination of Minerals by Titration Method Methods of Analysis forSoils,Plants and Water 2(Edn.), CaliforniandUniversity, Agriculture Division, USA., PP: 169-170.
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Cha-um, S., Pokasombat, Y. and Kirdmanee, C. (2011). Remediation of salt-affected soil by gypsum and farmyard manure − Importance for the production of Jasmine rice. Australian Journal of Crop Science. 5, 458-465.
10
Conaty, W. C., Tan, D. K. Y., Constable, G. A., Sutton, B. G., Field, D.J., Mamum, E. A. (2008). Genetic variation for waterlogging tolerance in cotton. Journal of Cotton Science. 12, 53–61.
11
Coohi Chelecaran, N., Alizade, A., Davari, K. (2015). The effect of different amounts of irrigation on root length density and corn yield in drip irrigation and. J. Water research in Agriculchur. 29, 331-340. (In Farsi).
12
Dane, J. H., Hopmans, J. (2002). Water retention and storage: Laboratory, Introduction. In Dane, J. H. and Topp, G. C. (ed.) Methods of soil analysis. Part 4: Physical Methods. Soil Sci. Soc. Am. Book Ser 5. Soil Science Society of America, USA. pp: 675–680.
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FAO (Food and Agriculture Organization), (2002). Agricultural drainage water management in arid and semi-arid areas. Annex 1. Crop salt tolerance data. FAO, Rome. Available from http://www.fao.org/docrep/005/y4263e/y4263e0e.htm.
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15
Hasanuzzaman, M., Nahar, K., Fujita, M. (2013). Plant response to salt stress and role of exogenous protectants to mitigate salt-induced damages. In: Ahma, P.; Azooz, M. M.; Prasad, M. N. V. (Eds.), Ecophysiology and Responses of Plants Under Salt Stress. Springer. New York. 25-87.
16
Jaleel, C. A., Manivannan, P., Wahid, A., Farooq, M., Somasundaram, R. and Panneerselvam, R. (2009). Drought stress in plants: a review on morphological characteristics and pigments composition. International Journal of Agricultural and Biological Engineering. 11, 100–105.
17
Jarecke, K.M., Loecke, T.D. and Burgin, A.J. (2016). Coupled soil oxygen and greenhouse gas dynamics under variable hydrology. Soil Biology and Biochemistry. 95, 164-172.
18
Jiang, H., Du, H., Bai, Y., Hu, Y., Rao, Y., , Chen, C.,, and Cai, Y. (2016). Effects of spatiotemporal variation of soil salinity on fine root distribution in different plant configuration modes in new reclamation coastal saline field. Environmental Science and Pollution Research. 23, 6639-6650.
19
Kiani, A.R. and Raeisi, S. (2013). Assessment of water use efficiency in some soybean cultivars under different amount of irrigation. Journal of Water and Soil Conservation. 20, 179-192.
20
Kotula, L., Khan H. A., Quealy, J., Turner, N. C., Vadez, V., Siddique, K. H., et al. (2015). Salt sensitivity in chickpea (Cicer arietinum L.): ions in reproductive tissues and yield components in contrasting genotypes. Plant Cell Environ. 38 1565–1577.
21
Liu, H., Li, F. and Jia, Y. (2006). Effects of shoot removal and soil water content on root respiration of spring wheat and soybean. Environmental and Experimental Botany. 56, 28–35.
22
Liu, B., Asseng, S., Liu, L., Tang, L., Cao, W. and Zhu, Y. (2016). Testing the responses of four wheat crop models to heat stress at anthesis and grain filling. Global Change Biology. 22, 1890-1903.
23
Maghsoudi Moud, A. and Maghsoudi, K. (2008). Salt Stress Effects on Respiration and Growth of Germinated Seeds of Different Wheat (Triticum aestivum L.) Cultivars. World Journal of Agricultural Sciences. 4, 351-358.
24
Manosalva, P. M., Davidson, R. M. Liu, B., Zhu, X., Hulbert, S. H. Leung, H. and Leach, J. E. (2009). A germin-Like protein gene family functions as a complex quantitative trait locus conferring broad-spectrum disease resistance in rice. Plant Physiolgy. 149, 286–296.
25
Meskini-Vishkaee F, Mohammadi M H, Neishaboori M R, Shekari F. (2016). Effect of soil moisture on Wheat and Canola root respiration rates in two soil textures. Plant Process and Function. 4 , 177-188.
26
Meskini-Vishkaee, F., Mohammadi, M. H., Neyshabouri, M. R. and Shekari, F. (2015). Evaluation of canola chlorophyll index and leaf nitrogen under wide range of soil moisture. International Agrophysics. 29, 83-90.
27
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28
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29
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33
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43
Zhu, J. K. (2007). Operator theory in function spaces. First edition.
44
ORIGINAL_ARTICLE
Determining economic depth of agricultural well in sprinkler irrigated farms in Qazvin plain
Decline of groundwater level in many plains of Iran has been accompanied by increase in energy consumption for pumping out water for irrigation. Long this line, a determination of the economic depth of wells, as related to pumping costs, crop value and other costs of agricultural expenditure is indispensable. This study was aimed at determining the economic depth of wells as applied in sprinkler irrigation considering two subsidized vs. non-subsidized energy costs, drilling costs, total cost of agricultural practices and benefit-cost ratio for one as a farmer. In this regard, detailed information, comprised of data from irrigation systems as well as crop yields from Qazvin Plain in year 2011 was used. Under the non-subsidized case, cost of electricity used as energy was much higher than that of diesel fuel. The average income-cost ratio obtained by farmers with electricity used as energy was more than those with diesel fuel under subsidized case, while the reverse was obtained under non-subsidized case. Increasing the depth of the well led to some partial reduction in benefit-cost ratio. The results finally revealed that due to the unusually low cost of energy, there seems to be no limit for drilling to increasing the depth of wells.
https://ijswr.ut.ac.ir/article_62660_c62c8133b70ca66484b9f7fe4e12e3e7.pdf
2017-07-23
441
449
10.22059/ijswr.2017.62660
Sprinkler irrigation
Groundwater
energy cost
well excavation
Zeynab
Gholami
zgholami1369@ut.ac.ir
1
University College of Agriculture and Natural Resources, University of Tehran
AUTHOR
Hamed
Ibrahimian
ebrahimian@ut.ac.ir
2
University College of Agriculture and Natural Resources, University of Tehran
LEAD_AUTHOR
Hamideh
Noory
hnoory@ut.ac.ir
3
University College of Agriculture and Natural Resources, University of Tehran
AUTHOR
Dinar A. (1994). Impact of energy cost and water resource availability on agriculture and ground water quality in California. Resource and Energy Economics, 16(1), 47-66.
1
Ghasemi, A., Zaree – Abyaneh, H., Maroufi, S., Sepehri, N., Hassan Nejad, M.S. (2007). Status of Hamedan-Bahar Plain Groundwater between 2005 and 2006. The Second Conference and Specialized Exhibition of Environmental Engineering, Tehran. (In Farsi).
2
Khajeddin, S. J. (2007). Trend of desertification in Iran. Journal of Forest, Range and Watershed, 74: 42-45. (In Farsi)
3
Kitani, O., Jungbluth, T., Peart, R., Ramdani, A. (1999). CIGR Handbook of Agricultural Engineering Volume V Energy and Biomass Engineering, Published by the American Society of Agricultural Engineers. 326 page.
4
Martin, D. L., Dorn, T. W., Melvin, S. R., Corr, A. J., Kranz, W. L. (2011). Evaluating energy use for pumping irrigation water. Proceedings of the 23rd Annual Central Plains Irrigation Conference, Burlington, CO., February 22-23, Available from CPIA, 760 N. Thompson, Colby, Kansas.
5
Ministry of Agriculture Jihad. (2012). Studies of updating Project and Implementing of the national document model for efficient water use in agriculture in the two pilot plain of Qazvin and Foumanat. Department of Water, Soil and Industries, Karaj, Iran. (In Farsi)
6
Ministry of Agriculture Jihad. (2014). Agricultural statistics, Volume I, Agricultural and horticultural crops. Center of Statistics and Information Technology, http://dbagri.maj.ir. (In Farsi)
7
Ministry of Energy. (2011). Energy balance sheet. Department of Electricity and Energy, Tehran, Iran, Page 570. (In Farsi)
8
Mojarrad, A., Sabouhi, M. (2009). Determining the economic optimum depth of irrigation water wells, Case Study of Bojnourd plain. Journal of Agricultural Economics Research, 2(1): 93-103. (In Farsi)
9
Mukherji, A. (2007). The energy-irrigation nexus and its impact on groundwater markets in eastern Indo-Gangetic basin: Evidence from West Bengal, India. Energy Policy, 35(12), 6413-6430.
10
Nissen, J., Mancilla, M. (2009). Actibilidad técnica y económica de riego por aspersión en praderas artificiales destinadas a leche del sur de chile. Agro sur, 37(2), 110-125.
11
Ortega, L. (2000). Informe Final Estudio “Rentabilidad de Rubros Agropecuarios con Riego en la Xa. Región”(CORFO/INIA). CRI Remehue-INIA. Osorno, Chile.
12
Shah T., Scott C., Kishore A., Sharma A. (2004). Energy-irrigation nexus in South Asia: Improving groundwater conservation and power sector viability. Second (Revised) Edition. Research Report 70. Colombo, Sri Lanka: International Water Management Institute.
13
ORIGINAL_ARTICLE
Laboratory investigation of quick coupling valves minor head loss in solid set sprinkler systems
One of the main reasons for sprinklers, low pressure in sprinkler irrigation systems is related to incorrect estimate of quick coupling valves, minor (local) head losses. In order to measure the quick coupling valves, minor head losses, a laboratory study was conducted in accordance with ISO 9644 and ISO 4059 international standards during year 2014. Seventy-five quick coupling valve samples were selected from fifteen manufacturers, and made of three materials of cast iron, aluminum and polymer within three sizes comprised of 1, 1.5 and 2 inch. They were tested in terms of head loss. For each sample, the minor head losses were assessed using five flow rates including the maximum, minimum as well as three intermediate flow tests. Results indicated that, there are significant differences in the minor head loss values of similar quick coupling valves due mostly to manufacturing quality. Based upon the obtained results, the average minor head losses of 1 inch quick coupling valves obtained within the maximum vs. minimum flow rates were 0.46 and 10.23 m, respectively. As for 1.5 inch they were recorded 0.60 and 4.31 m, respectively, whereas for 2 inch, the figures were 0.21 and 1.76 m. Head loss values for low level flows were close to those given in their catalogues. But as for high flows, the head loss was recorded higher than those in the catalogue values. The head loss coefficients (K) of seventy-three quick coupling valve samples were recorded in the range of 7.26 to 9.79. However, based on the standards and criteria of pressurized irrigation systems, the minor head loss coefficients of quick valves should stand in the range of 2 to 2.2. The results finally indicated that the head loss related to quick coupling valves is high and that can be an important cause of low pressure in sprinkler irrigation systems.
https://ijswr.ut.ac.ir/article_62661_9e3ac896c2443a4bf15f62b892ed8c4f.pdf
2017-07-23
461
451
10.22059/ijswr.2017.62661
Minor Head Loss
Minor Head Loss Coefficient
Sprinkler irrigation
Vahid
Rezaverdinejad
rezaverdinejad@gmail.com
1
Urmia University
LEAD_AUTHOR
Mohamad Saied
Rashidi
msrashidi@yahoo.com
2
Jihad Keshavarzi Organization of Kordestan
AUTHOR
Isa
Maropoor
isamarofpoor@yahoo.com
3
University of Kordestan
AUTHOR
Hosein
Rezaei
h.rezaei@urmia.ac.ir
4
Urmia University
AUTHOR
Javad
Sarabi
sarabijavad@yahoo.com
5
Urmia University
AUTHOR
Aghaie-Rad, A., and Rahbar, A. (2002). Pressurized irrigation equipment's standard. IRNCID: Iranian National Committee on Irrigation and Drainage, No. 68, 223 P.
1
Douglas, J.F., Gasoriek, J.M., Swaffield, J., and Jack, L. (2006). Fluid Mechanics. Prentice Hall, 5th edition. 992 P.
2
Ebrahimi, H. (2006). Analysis and evaluation of simplified irrigation systems in Khorasan. Journal of Agriculture Sciences, 12(3),577-589.
3
Ghomshi, M., and Emamgholi-Zadeh, S. (2008). Hydraulic fluid mechanics and simple language.1th edition, University of Shahid Chamran.
4
Haque, F.M., Haider, F., Rahman, A., and Islam, Q. (2010). Study of different types of valves & determination of minor head loss for various openings of locally available plastic valve. Proceedings of the 13th Asian congress of fluid mechanics, Dhaka, Bangladesh, 605-608.
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Howell, T.A., and Barinas, F. A. (1980). Pressure losses across trickle irrigation fittings and emitters. Trans. ASAE, 23(4), 928–933.
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Iran Water Resources Management Company. (2005). Design criteria for pressurized irrigation systems. Office of standard and technical criteria, No. 268, 240 P.
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Keller, J., and Bliesner, R.D. (2000). Sprinkle and trickle irrigation, 2th edition, Caldwell, NJ: Blackburn press. 652 P.
8
Liaghat, A.M., Mokari Ghahroodi, E., Noory, H., andSotoudenia, A. (2015). Evaluation of Qazvin plain irrigation systems through an assessment of classical vs neoclassical irrigation efficiencies. Iranian Journal Soil and Water Research, 46 (2), 341-353.
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Majd-Salimi, K., Salvatian, S.B., and Amiri, E. (2015). Technical evaluation of sprinkler irrigation systems which were implemented in tea fields of the Guilan Province. Journal of Water and Soil, 29 (2), 336-349.
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17