ORIGINAL_ARTICLE
Evaluation of leaching and degradation rate of metribuzin herbicide in different soils
The intensive and inappropriate use of pesticides caused environment to be contaminated. Quantifying the fate of applied herbicides in the soil is essential for minimizing their mobility in the soil and environmental pollution. The leaching and degradation of the metribuzin herbicide in three soils were investigated under laboratory conditions. Metribuzin was mobile in the soils when tested using non-aged and aged soil columns. The mobility of herbicide in the soil is related to the adsorption phenomenon in the same soil. It was found that the mobility of metribuzin in the soils 7 and 5 (with less organic carbon) was more than the one in the soil 1. The difference in the adsorption affinity of metribuzin in different soils appears to be due to differences in soil properties, such as clay content, organic matter content and pH value. The calculated half-life values in sterile and non-sterile conditions ranged from 37.92 to 105.74 days. Metribuzin persistent in the soil was corresponded to columns 1, 5 and 7 respectively.
https://ijswr.ut.ac.ir/article_70097_ec6a4c59fedd87dc6e44f732173d533e.pdf
2019-03-21
1
12
10.22059/ijswr.2018.203562.667435
"Pesticide"
"Triazine"
"Leaching"
"Degradation"
"Soil"
Mohammad Reza
Rigi
rezarigi@gmail.com
1
Assistant professor of Higher Educational Complex of Saravan, Saravan, Iran
AUTHOR
Mohsen
Farahbakhsh
mfbakhsh@ut.ac.ir
2
Associate Professor, Department of Soil Science, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
LEAD_AUTHOR
Barriuso, E. and Calvet, R. (1992). Soil type and herbicides adsorption. International Journal of Environmental Analytical Chemistry, 46, 117–128.
1
Bedmar, F., Costa, J. L., Suero, E. and Gimenez, D. (2004). Transport of atrazine and metribuzin in three soils of the humid pampas of Argentina. Weed Technology, 18(1), 1-8.
2
Bollag, J. M. and Liu, S. Y. (1990). Biological transformation processes of pesticides, In: H. H. Cheng (Ed.), Pesticides in the Soil Environment: Processes, Impacts, and Modeling. (pp. 169-211). SSSA Book Series No. 2, Soil Science Society of America, Madison, WI.
3
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5
Calvet, R. (1980). Adsorption-desorption phenomena: Interaction between herbicides and the soil. Academic Press, London.
6
Cerato, A. B. and Lutenegger, A. J. (2002). Determination of Surface Area of Fine-Grained Soils by the Ethylene Glycol Monoethyl Ether (EGME) Method. Geotechnical Testing Journal, ASTM. 25, 315-321.
7
Enell, A., Reichenberg, F., Warfvinge, P. and Ewald, G. (2004). A column method for determined of leaching of polycyclic aromatic hydrocarbons from aged contaminated soil. Chemosphere, 54, 707–715.
8
Gallaher, K. and Mueller, T. (1996). Effect of crop presence on persistence of atrazine, metribuzin, and clomazone in surface soil. Weed Science, 44, 698–703.
9
Garcia-Valcarcel, A. I., Matienzo, T., Sanchez-Brunete, J. and CandTadeo, J. L. (1998). Adsorption of triazines in soils with low organic matter content. Fresenius Environmental Bulletin, 7, 649–656.
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Gerstl, Z. (2000). An update on the concept of Koc in regard to regional scale management. Crop Protection, 19, 643-648.
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15
Khoury, R., Coste, C. M. and Kawar,N. S. (2006). Degradation of metribuzin in two soil types of Lebanon. Journal of Environmental Science and Health Part B, 41, 795–806.
16
Khoury, R., Geahchan, A., Coste, C. M., Cooper J. F. and Bobe, A. (2003). Retention and degradation of metribuzin in sandy loam and clay soils of Lebanon. Weed Research, 43, 252–259.
17
Kim, J. H. and Feagley, S. E. (1998). Adsorption and leachesg of trifluralin, metolachlor, and metribuzin in a commerce soil. Journal of Environmental Science and Health, Part B, 33, 529-546.
18
Lagat, S. C., Lalah, J. O., Kowenje,C. O. and Geteng, Z. M. (2011). Metribuzin mobility in soil column as affected by environmental and physico-chemical parameters in Mumias sugarcane zone, Kenya. Journal of Agricultural and Biological Science, 6(3), 27-33.
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Landlie, J. S., Meggitt, W. F. and Penner, D. (1976). Effect of soil pH on microbial degradation, adsorption, and mobility of metribuzin. Weed Science, 24(5), 477-481.
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Lechon, Y., Garcia-Valcarcel, A. I., Matienzo, T., Sanchez-Brunete C. and Tadeo, J. L. (1997). Laboratory and field studies on metribuzin persistence in soil and its prediction by simulation models. Toxicological and Environmental Chemistry, 63, 47-61.
21
Majumdar, K., & Singh, N. (2007). Effect of soil amendments on sorption and mobility of metribuzin in soils. Chemosphere, 66, 630–637.
22
Mathava, K. and Ligy, P. (2006). Adsorption and desorption characteristics of hydrophobic pesticide endosulfan in four Indian soils. Chemosphere, 62, 1064–1077.
23
Mikata, K., Ohta, K. and Tashiro, S. (2001). Degradation and leaching of herbicide imazosulfuron in upland soils. Journal of Pesticide Science, 26, 376–382.
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Miles, J. R. W., Harris, C. R. and Tu, C. M. (1984). Influence of moisture on the persistence of chlorpyriphos and chlorfenvinphos in sterile and natural mineral and organic soils. Journal of Environmental Science and Health, Part B, 19, 237–243.
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32
Rigi, M. R., Farahbakhsh, M. and Rezaei, K. (2015). Adsorption and desorption behavior of herbicide metribuzin in different soils of Iran. Journal of Agricultural Science and Technology, 3 (17), 777-787.
33
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34
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35
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36
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38
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39
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42
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43
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44
ORIGINAL_ARTICLE
Evaluation of DRAINMOD by a Physical Model to Simulate the Performance of Subsurface Drainage at the Mid and End Season in Paddy Fields
The complexity of drainage process in paddy fields and time consumption of field tests make simulation models to be used inevitably for assessing subsurface drainage systems performance. The objective of this study was to evaluate DRAINMOD model and the effects of drainage management of paddy fields on the salinity of drainage water. In this regard, a physical model with 3m in length, o.6m width and 1m height was constructed and equipped with controlled drainage. The corrugated drainage pipe, covered with geotextile was laid at a depth of 70 cm in the box. The tank was filled with silty loam soil with the same density and layering as in the paddy fields. After rice cultivation and during the experiment, the soil solutions were collected from the depths of 40, 50 and 70 cm and their TDS were measured in the laboratory. In order to evaluate the accuracy of DRIANMOD model for simulation of qualitative and quatitive subsurface drainage water, the solute transport parameters including dispersivity, tortousity factor, molecular diffusion coefficient, precipitation limit and the hydraulic conductivity were obtained through minimizing differences between the observed and the estimated salt solusion and drainage volume using genetic algorithm optimization method. The results showed that the model could simulate the performace of drainage system very well at before and after the midseason (NRMSE < 20%) and excellent at the mid and end season (NRMSE < 10 %). The TDS and drainage volume were estimated by average RMSE of 63.27 mg/l and 0.0145 cm3 respectively. The comparison of estimated and observed values showed a better performance for the model at the non-submerged conditions. The results of calibration and validation of model showed that the DRAINMOD-S model is capable to simulate the performance of subsurface drainage in paddy fields.
https://ijswr.ut.ac.ir/article_70098_83530fed1de213c75335feddfe1c70d2.pdf
2019-03-21
13
24
10.22059/ijswr.2018.224661.667609
rice
Drainage water salinity
Soil profiles salinity
solute transport
genetic algorithm
Zahra
Momen nejad
sanaz.momennezhad@gmail.com
1
M.Sc Student of Water Engineering Department, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
AUTHOR
Maryam
Navabian
navabian@guilan.ac.ir
2
Assistant Prof. of Water Engineering Department, Faculty of Agricultural Sciences, University of Guilan and Department of Water Engineering and Environment, Caspian Sea Basin Research Center, Rasht, Iran
LEAD_AUTHOR
Mehdi
Esmaeili Varaki
esmaeili@guilan.ac.ir
3
Assistant Professor, Water Engineering Department, Faculty of Agricultural Sciences, University of Guilan and Department of Water Engineering and Environment, Caspian Sea Basin Research Center, Rasht, Iran
AUTHOR
Alizadeh, M. Afrasiab, P. Yazdani,M.R. Liaghat, A.M. and Delbari, M. (2016). The Effect of Depth and Space Subsurface Drainage on Paddy Field Drainage Intensity (Case Study: Fields of Rice Research Institute of Iran). Journal of Water and Soil Conservation, 23(4), 219-233.
1
Amin Salehi, A. Navabian, M. Esmaeili Varaki, M. and Pirmoradian, N. (2017). Evaluation of HYDRUS-2D model to simulate the loss of nitrate in subsurface controlled drainage in a physical model scale of paddy fields. Paddy and Water Environment, 15, 433–442.
2
Bannayan, M. and Hoogenboom, G. (2009). Using pattern recognition for estimating cultivar coefficients of a crop simulation model. Field Crops Research, 111(3), 290-302.
3
Breve, M.A. Skaggs, R.W. Parsons, J.E. and Gilliam, J.W. (1997). DRAINMOD-N, A nitrogen model for artificially drained soils. Transaction of the ASAE, 40(4), 1067-1075.
4
Caton, B.P. Foin, T.C. and Hill, J.E. (1999). A plant growth model for integrated weed management in direct seeded rice. II. Validation testing of water-depth effects and monoculture growth. Field Crop Research, 62: 145–155.
5
Farmaha, B.S. (2014). Evaluating Animo model for predicting nitrogen leaching in rice and wheat. Arid Land Research and Management, 28, 25-35.
6
Gauch, H.G. Hwang, J.T.G. and Fick, G.W. (2003). Model evaluation by comparison of model-based predictions and measured values. Agronomy Journal, 95, 1442–1446.
7
Ines, A.V.M. and Droogers, P. (2002). Inverse modeling in estimating soil hydraulic functions a genetic algorithm approach. Hydrology Earth System Science, 6(1), 49-65.
8
Jamieson, P.D. Porter, J.R. and Wilson, D.R. (1991). A test of the computer simulation model ARC-WHEAT1 on wheat crops grown in New Zeland. Field Crops Research, 27(4), 337-350.
9
Kale, A. (2011). Field-evaluation of DRAINMOD-S for predicting soil and drainage water salinity under semi-arid conditions in Turkey. Spanish Journal of Agricultural Research, 9(4), 26-40.
10
Kandil, H.M. Skaggs, R.W. Abdel Dayem, S. Aiad, Y. and Gilliam, J.W. (1992). DRAINMOD-S: Water management model for irrigated arid lands. 1. Theories, and Tests, presented at the ASAE international winter meeting, Paper No. 922566.
11
Nazari, B. Liaghat, A. Parsinezhad, M. and Naseri, A. (2008). Optimizing subsurface drainage installation depth consideration economic and environmental. In: Proceedings of 5th Workshop on Drainage and Environmental Engineering, 6 Nov., Iranian National Committee on Irrigation and Drainage, Tehran, Iran, pp. 107-122. (In Farsi)
12
Noory, H. Abyane, H.Z. Noory, H. and Liaghat, A.M. (2010). Application of DRAINMOD-N model for predicting Nitrate-N in paddy rice fields under controlled drainage in a costal region of Iran. XVIIth World Congress of the International Commission of Agricultural and Biosystems Engineering (CIGR), June 13-17, Québec City, Canada.
13
Okhovat, M. (1997). Rice planting, management and harvest. Iran: Farabi. (In Farsi)
14
Ramezani, M., Jamali, B. and Asgharzade, M. A. (2011). Sensitivity analysis of Drainmod model of input parameters. In: Proceedings of 3rd Irrigation and Drainage Network Management National Conference, 20-21 Feb. Shahid Chamran University of Ahvaz, Ahvaz, Iran, pp. 1-8. (In Farsi)
15
Samipoor, F. Mohammadi, K. Mahdian, M. and Naseri, A. (2011). Evaluating DRAINMOD and SWAP drainage models to determining optimal depth and spacing using crop yield performance and drainage effluent. Iranian Journal of Irrigation and Drainage, 4(3), 375-386. (In Farsi)
16
Skaggs, R.W. (1980). DRAINMOD reference report. United States Department of Agriculture, Soil Conservation Service.
17
Skaggs, R.W. (1982). Field evaluation of a water management simulation model, DRAINMOD. Transactions of the ASAE, 25(3), 666-674.
18
Torkzaban, S. (2000). Evaluation and calibration of DRAINMOD model under arid and semi-arid condition of Iran. M.Sc. dissertation, University of Tehran, Tehran. (In Farsi)
19
Wahba, M.A.S. and Christen, E. W. (2006). Modeling subsurface drainage for salt load management in southeastern Australia. Irrigation and Drainage Systems, 20(2), 267-283.
20
Wahba, M.A.S. (2016). Assessment of options for the sustainable use of agricultural drainage water for irrigation in Egypt by simulation modeling. Irrigation and Drainage, Online Version of Record published before inclusion in an issue, Wiley Online Library.
21
Yufu, T. Sen, D. Yuguang, Zh. Changyu, W. and Jinsong, W. (2013). Improvement effects of subsurface pipe with different spacing on sodic-alkali soil. Transactions of the Chinese Society of Agricultural Engineering, 29(12), 145-153.
22
Zare Abyaneh, H. Noori, H. Liaghat, A.M. Karimi, V. and Noori H. (2011). Calibration of nitrate leaching and water table fluctuation in paddy rice field by DRAINMOD-N software. Journal of Science and Technology of Agriculture and Natural Resources,15(57), 49-60. (In Farsi)
23
ORIGINAL_ARTICLE
Determining the most important soil fertility properties affecting rice yield in paddy fields using principal component analysis
Multi-variate statistical methods such as principal component analysis (PCA) and regressions could be used to facilitate the interpretation of complex relationships. The objective of this study was to determine the most important soil fertility properties affecting rice yield in the paddy fields. For this purpose, soil samples were taken from the plow layers of 119 points with suitable distribution in the paddy fileds located in Shaft and Fouman cities of Guilan province. Then after, physical and chemical properties of the soil fertility were measured and analysed using descriptive statistics, principal component analysis and regression methods. Results showed that three PCs with eigen values greater than one named as “k and it’s preservation factors”, ”Total N and it’s provider factors” and ”P and Thickness of plow layer” are respectively explained more than 67.4% of the variability in the soil physical and chemical properties and 55% of the yield variability. In addition, the corresponded properties to the PCs explained 80% of the yield variability. Consequently, in order to increase the yield, management practices such as proper fertilizer applications of nitrogen, potassium and phosphorous and proper tillage for creating suitable plow layer are recommended.
https://ijswr.ut.ac.ir/article_70099_bfda2b98b409c28ab2dc826efb6e7b3a.pdf
2019-03-21
25
38
10.22059/ijswr.2018.226317.667621
Guilan province
multivariate statistics
rice yield
soil physical and chemical properties
Bahareh
Delsouz Khaki
b_delsooz@yahoo.com
1
PhD Graduate, Department of Soil Science, College of Agriculture, Isfahan ( Khorasgan) Branch , Islamic Azad University, Isfahan, Iran
AUTHOR
Naser
Honarjoo
nhonarjoo@yahoo.com
2
Assistant Professor, Department of Soil Science, College of Agriculture, Isfahan (Khorasgan) Branch , Islamic Azad University, Isfahan, Iran
AUTHOR
Naser
Davatgar
n_davatgar@yahoo.com
3
Associate Professor, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
LEAD_AUTHOR
Ahmad
JALALIAN
a.jalalian@khuisf.ac.ir
4
Professor of Soil Science, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
AUTHOR
Hossein
Torabi
htorabi@shahed.ac.ir
5
Assistant Professor, Department of Agriculture, Shahed University, Tehran, Iran
AUTHOR
Ayoubi, S., Khormali, F. (2009). Spatial variability of soil surface nutrients using principal component analysis and geostatistics: A case study of appaipally village, Andhra pradesh, India. Journal of Science and Technology of Agriculture and Natural Resources, 12 (46), 609-622. (In Farsi)
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Ayoubi, S., Zamani, S. M. and Khormali, F. (2009). Wheat yield prediction through soil properties using principle component analysis. Iranian Journal of Soil and Water Research, 40 (1), 51-57. (In Farsi)
2
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3
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4
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5
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Bremner, J. M. and Mulvaney. C. S. (1982). Total nitrogen. In: A. L. Page (ed.) Methods of SoilAnalysis. P Part 2: Chemical and microbiological properties (2th ed.). Agron. (No.2). (pp.9595-624). Am. Soc. Argon., Madison, WI, USA.
9
Cox M. S., Gerard P. D., Wardlaw M. C. and Abshire M. J. (2003). Variability of selected soil properties and their relationship with soybean yield. Soil Science Society of America Journal, 67, 1296–1302.
10
Davatgar, N. (2010). Prediction of rice yield under water limited conditions using crop growth and yield models at regional scale. Ph. D. dissertation, University of Tabriz, Iran. (In Farsi)
11
Davatgar, N., Kavoosi, M., Alinia, M. H. and Paykan, M. (2006). Study of potassiun status and effect of physical and chemical properties of soil on it in paddy soils of guilan province. Journal of Water and Soil Science, 9(4), 71-89. (In Farsi)
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18
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Hill, T., Lewicki, P., and Lewicki, P. (2006). Statistics: methods and applications: a comprehensive reference for science, industry, and data mining. Tulsa : StatSoft, Inc.
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55
ORIGINAL_ARTICLE
Assessment of spatial and temporal variations of groundwater quality using WQI during two decades in aquifer of Golestan province
Groundwater is of valuable resources that its conservation needs quality and quantity monitoring. Different indices such as WQI (water quality index) are used in order to monitor the groundwater quality. The objective of this study is to assess spatial-temporal changes in WQI in groundwater aquifer of Golestan province including Ghare-Sou, Grgan-Roud and Gorgan gulf basins. The Golestan province was selected as the study area. WQI was calculated based on the quality parameters data of 114 deep wells in the study area, collected during a 21-years period. After zoning WQI in GIS, the spatial-temporal changes of this index were investigated considering the range of changes, the observed minimum and maximum values during the study period. The empirical Bayesian kriging method presented better results in comparison to other methods for WQI zoning in GIS environment. The quality zoning of WQI in the studied area showed that the aquifer is in a good and very good condition and it is only bad in a small part of aquifer located in the eastern shores of the Caspian Sea and the northern part of the study area. In addition, no considerable differences were found between the WQI averages of the two events data sampling during the year. Also, the investigations show a decrease in water quality as closing to the sea shore and to the northern part of the study area. According to the fact that WQI follow the general slope of the region, there was a good spatial structure in the region which caused a better result for empirical Bayesian kriging interpolation method.
https://ijswr.ut.ac.ir/article_70101_dd4a4a4ca9f679cc00b7c6b41b0f8d51.pdf
2019-03-21
39
51
10.22059/ijswr.2018.237952.667723
Groundwater
Quality Monitoring
WQ
Golestan province
Farzaneh
kia
farzaneh.kia20@gmail.com
1
M.Sc.Water Resource Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Golestan, Iran
AUTHOR
Khalil
Ghorbani
ghorbani.khalil@yahoo.com
2
Associate Professor of Water Engineering Department, Gorgan University of Agricultural Sciences and Natural Resources, Golestan, Iran
LEAD_AUTHOR
meysam
salarijazi
meysam.salarijazi@gau.ac.ir
3
Assistant Professor of Water Engineering Department, Gorgan University of Agricultural Sciences and Natural Resources, Golestan, Iran
AUTHOR
Al-Hadithi, M. (2012). Application of water quality index to assess suitability of groundwater quality for drinking purposes in Ratmao-Pathri Rao watershed, Haridwar district, India. American journal of scientific and industrial research. DOI:10.5251/ajsir.
1
Ashayeri, A., Karbasi, A.and Baghvand, A. (2014). Assessing Darreh-rood river water quality for irrigation using sustainable conservation approach and CCME-WQI model. ISSN 2251-7480,3(4):51-61. (In Farsi)
2
Bahrami Jovein, E. and Hosseini, S.M. (2015). A systematic comparison of Geostatistical methods for estimation of groundwater salinity in Desert areas. Case study: Feyz Abad Mahvelat plain. Iran-water Resources,11(2):1-15. (In Farsi)
3
Bharti, N., Katyal, D. (2011). Water quality indices used for surface water Vulnerability assessment.International journal of environmental sciences,2(1).
4
Bora, M .and Goswami, D.C. (2016). water quality assessment in terms of warwe quality index(WQI): Case study of the Kolong river, Assam, India. Appl water Sci. DOI:10.1007/s13201-016-0451-y.
5
Chatterjee, R., Tarafder, G. and Paul, S. (2010). Groundwater quality assessment of Dhanbad district Jharkhand, India. Bull Eng Geol Environ, 69:137-141.
6
Fathi, P., Ebrahimi, E. and Mirghafari, N. (2016). The study and temporal changes of water quality in choghakhor wetland using water quality index(WQI). Journal of Aquatic Ecology, 5(3):41-50. (In Farsi)
7
Ghorbani, Kh. (2012). Geographically weighted regression: A method for mapping isohyets in Gilan province. Journal of water and soil, 26(3):743-752. (In Farsi)
8
Javid, A.H., Mirbagheri, S.A.and Karimian, A. (2014). Assessing Dez Dam reservoir water quality by application of WQI and TSI indices. Iran.J.Health and Environ,7(2):133-142.(In Farsi)
9
Ishaku. J.M. (2011). Assessment of groundwater quality index for Jimeta-Yola area, Northeastern Nigeria. Journal of geology and mining research vol.3(9), pp.219-231.
10
Yisa. J. and T. Jimoh(2010). Analytical studies on water quality index of river Landzu. American journal of applied sciences,7(4):453-458.
11
Kalpana, G.R., Nagarajappa, D.P., Sham Sunder, K.M. and Suresh, B. (2014). Determination of Groundwater Quality Index in Vidyanagar, Davanagere city, Karnataka State, India. International Journal of Engineering and Innovative Technology(IJEIT), 3(12).
12
Ketata Rokbani, M., Gueddari, M.and Bouhlila, R. (2013). Use of Geographical Information System and Water Quality Index to Assess Groundwater Quality in Ei Khairat Deep Aquifer (Enfidha, Tunisian Sahel). Iranica Journal of Energy and Environment, 2(2):133-144.
13
Kumar Tiwari, A., Kumar Singh, P. and Kumar-Mahato, M. (2014). GIS-based of evaluation of warwe quality index of groundwater resources in West Bokaro Coalfield, India. Current world environment, 9(3):843-850.
14
Poonam, T., Tanushree, B. and Sukalyan, Ch. (2013). Water quality indices-Important tools for water quality assessment: A Review. International journal of Advanus in cheistry,1(1).
15
Ramakrishnaiah, C.R., Sadashivaiah, C.and Ranganna, G. (2009). Assessment of Water Quality Index for the Groundwater in Tumkur Taluk, Karnataka, India. CODEN ECJHAO E-Journal of chemistry, 6(2):523-530.
16
Rupal, M., Tanushree, B.and Sukalyan, Ch. (2012). Quality characterization of groundwater using water quality index in Surat city, Gujarat,India. International Research Journal of Environment Sciences, 1(4):14-23
17
Sadat-Noori, S.M., Ebrahimi, K. and Liaghat, A.M. (2013). Groundwater quality assessment using the Water Quality Index and GIS in Saveh-Nobaran aquifer,Iran. Environ Earth Sci. Doi:10/1007/s12665-013-2770-80.
18
Sahu, P. and Sikdar, O.K. (2007). Hydrochemical frame work of the aquifer in and around East Kolkata Wetlands, West Bengal, India. Environ Geol, 55:823-835. Doi:10.1007/s00254-007-1034-x.
19
Subbiah, K., Magesh, N.S., Samuel Godson, P. and Chandrasekar, N. (2015). Hydro-geochemistry and application of water quality in index (WQI) for groundwater quality assessment, Anna Nagar, part of Chennai city, Tamil Nadu, India. Appl water Sci, Doi:10.1007/s13201-014-0196-4.
20
Vasanthavigar, M., Srinivasamoorty, K., Vijayaragavan, K., Rajiv Ganthi, R., Chidambaran, S., Anadhan, P., Manivannan, R. and Vasudevan, S. (2010). Application of water quality index for groundwater quality assessment: Thirumanimuttar Sub-basin, Tamilnadu, India. Environ Monit Assess, 171:595-609. Doi:10/1007/s10661-009-1302-1.
21
WHO .(2004). Guidelines for drinking water quality:training pack.WHO,geneva,Switzerland.
22
ORIGINAL_ARTICLE
The Effect of Wheat Straw on Flow Characteristics and Rill Erosion in Wheat Rainfed Field
Rill erosion is one of the most important reasons of the soil lost in the plowed rainfed fields alongside the slope. Increasing infiltration rate in the soil and decreasing the erosivity of flow is essential for controlling rill erosion as well as increasing crop yield. This research was carried out to find out the effect of wheat straw on hydraulic characteristics of the flow and rill erosion in the wheat rainfed field in semi-arid region in Zanjan. The experiment was performed at seven straw mulch levels (0, 25, 50, 75, 100, 125 and 150 %) using the randomized complete block design with three replicates under the field conditions with plowing alongside the slope. At 100% level, 0.5 kgm-2 equivalent to five tons per hectare of straw mulch was applied into the soil. The results indicated that the effects of wheat straw on flow velocity, flow power and rill erosion was significant (p< 0.05), while its effect on the hydraulic radius and shear stress wasn’t statistically significant. These results were associated with a low depth of flow as affected by straw mulch in the furrow rills (p> 0.05). By increasing the wheat straw mulch level, the flow velocity, flow power and rill erosion decreased about 19, 23 and 55% respectively, as compared to the control treatment. There was a high correlation between the rill erosion and the flow velocity (r=0.71). The 100%-level of wheat straw mulch which decreased the flow power (34%) and the rill erosion (71%), was the most appropriate amount for decreasing rill erosion in rainfed wheat field. Generally, it can be concluded that the application of wheat straw mulch is a biological and proper practice for reducing erosivity of flow and controlling rill erosion in rainfed fields.
https://ijswr.ut.ac.ir/article_70102_cd9f17696929faa9c34cbeebe15b1d20.pdf
2019-03-21
53
63
10.22059/ijswr.2018.243817.667774
Soil amendments
shear stress
Flow velocity
Hydraulic radius
Flow power
Ali Reza
Vaezi
vaezi.alireza@gmail.com
1
Associated Professor, Soil Science Department, Faculty of Agriculture University of Zanjan, Zanjan, Iran.
LEAD_AUTHOR
Mohadeseh
Heidari
moh.hy68@gmail.com
2
MSc. Student, Soil Science Department, Faculty of Agriculture University of Zanjan, Zanjan, Iran.
AUTHOR
Abrahams, A. D., Parsons, A. J. and Luk, S. H. (1986). Field measurement of the velocity of overland flow using dye tracing. Earth Surface Processes and Landforms, 11(6), 653-657.
1
Akbari, S. and Vaezi, A.R. (2015). Investigating aggregates stability against raindrops impact in some soils of a semi-arid region, north west of Zanjan. Water and Soil Science. 25(2), 65-77. (In Farsi)
2
Adelpur, A.A., Soufi, M. and Behnia, A.K. (2006). Evaluation of the impact of mulches in rainfed farms on soil conservation in the arid and semi-arid region in soiuth of Iran. Journal of Agriculture Science and Natural Resources. 13(2), 1-8.
3
Bhatt, R. and Khera, K. L. (2006). Effect of tillage and mode of straw mulch application on soil erosion in the submontaneous tract of Punjab, India. Soil and Tillage Research, 88(1), 107-115.
4
Blanco, H. and Lal, R. (2008). Principles of Soil Conservation and Management: Springer Science Business Media BV, pp. 626.
5
Bohn, H. L., Myer, R. A. and O'Connor, G. A. (2002) Soil Chemistry (3th ed.). Canada, John Wiley and Sons, Inc.
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9
Center for Watershed Protection. (2001). Mats and blankets. Erosion and Sediment Control Fact Sheet 9. Center for Watershed Protection, Ellicott City, MD. pp 371.
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18
Klute, A. (1986). Methods of Soil Analysis. Part 1 (Physical and Mineralogical Methods). American Society of Agronom Madison. No.9.
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Mulumba, L. N. and Lal, R. (2008). Mulching effects on selected soil physical properties. Soil and Tillage Research, 98(1), 106-111.
21
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22
Nzeyimana, I., Hartemink, A. E., Ritsema, C., Stroosnijder, L., Lwanga, E. H. and Geissen, V. (2017). Mulching as a strategy to improve soil properties and reduce soil erodibility in coffee farming systems of Rwanda. Catena, 149, 43-51.
23
Poesen, J., Ingelmo‐Sanchez, F. and Mucher, H. (1990). The hydrological response of soil surfaces to rainfall as affected by cover and position of rock fragments in the top layer. Earth Surface Processes and Landforms, 15(7), 653-671.
24
Prosser, I. P. and Rustomji, P. (2000). Sediment transport capacity relations for overland flow. Progress in Physical Geography, 24(2), 179-193.
25
Prosser, I. P., Dietrich, W. E. and Stevenson, J. (1995). Flow resistance and sediment transport by concentrated overland flow in a grassland valley. Geomorphology, 13(1-4), 71-86.
26
Rahma, A. E., Lei, T., Shi, X., Dong, Y., Zhou, S. and Zhao, J. (2013). Measuring flow velocity under straw mulch using the improved electrolyte tracer method. Journal of Hydrology, 495, 121-125.
27
Rieke‐Zapp, D., Poesen, J. and Nearing, M. A. (2007). Effects of rock fragments incorporated in the soil matrix on concentrated flow hydraulics and erosion. Earth Surface Processes and Landforms, 32(7), 1063-1076.
28
Robichaud, P. R., Jordan, P., Lewis, S. A., Ashmun, L. E., Covert, S. A. and Brown, R. E. (2013). Evaluating the effectiveness of wood shred and agricultural straw mulches as a treatment to reduce post-wildfire hillslope erosion in southern British Columbia, Canada. Geomorphology, 197, 21-33.
29
Roustaii, M., Hosseini, S. K., Hossein Pour, T. and Kalate, M. (2003). A Study of Adaptability and Stability of Grain Yield in Advanced Bread Wheat Genotypes in Warm and Semi-Warm Dryland Areas. Iranian Journal of Agriculture Science, 35(2), 427-436. (In Farsi)
30
Sadusky, M. C., Sparks, D. L., Noll, M. R. and Hendricks, G. J. (1987). Kinetics and mechanisms of potassium release from sandy Middle Atlantic Coastal Plain soils. Soil Science Society of America Journal, 51(6), 1460-1465.
31
Savat, J. and De Ploy, J. (1982). Sheetwash and rill development by surface flow. In Bryan RB and Yair A (ed.). Badland Geomorphology and Piping, 231-247.
32
Sharma, P., Abrol, V. and Sharma, R. K. (2011). Impact of tillage and mulch management on economics, energy requirement and crop performance in maize–wheat rotation in rainfed subhumid inceptisols, India. European Journal of Agronomy, 34(1), 46-51.
33
Smet, T., Poesen, J., Bhattacharyya, R., Fullen, M.A., Subedi, M., Booth, C.A., Kertesz, A., Szalai, Z., Toth, A., Jankauskas, B. and Jankauskiene, G. (2011). Evaluation of biological geotextiles for reducing runoff and soil loss under various environmental conditions using laboratory and field plot data. Land Degradation & Development, 22(5), 480-494.
34
Soil Survey Staff. (2010). Keys to Soil Taxonomy, 11th edn. USDA-Natural Resources Conservation Service: Washington, DC.
35
Tan, K.H. (2005). Soil sampling preparation and Analysis. 2nd edition. Taylor and Francis/ CRC press
36
Tasumi, M. and Kimura, R. (2013). Estimation of volumetric soil water content over the Liudaogou river basin of the Loess Plateau using the SWEST method with spatial and temporal variability. Agricultural Water Management, 118, 22-28.
37
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38
Vaezi, A.R., Abbasi, M., Bussi, G. and Keesstra, S. (2017). Modeling sediment yield in semi-arid pasture micro-catchments, NW Iran. Land Degradation and Development, 28(4), 1274-1286.
39
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40
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41
Wirtz, S., Seeger, M., Remke, A., Wengel, R., Wagner, J. F., and Ries, J. B. (2013). Do deterministic sediment detachment and transport equations adequately represent the process-interactions in eroding rills? An experimental field study. Catena, 101, 61-78.
42
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44
Zarinabadi, A. (2014). Soil erosion and yield of wheat under the influence of plow direction in the slope varying degrees. M.Sc. Thesis, Agriculture Faculty. University of Zanjan. (In Farsi)
45
Zhang, G. H., Liu, B. Y., Nearing, M. A., Huang, C. H. and Zhang, K. L. (2002). Soil detachment by shallow flow. Transactions of the ASAE, 45(2), 351.
46
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47
ORIGINAL_ARTICLE
Estimation of Transient Storage Parameters for Simulation of Pollution Transport in the Gravel Bed Rivers
This research was conducted to test how to exchange mass between the main channel and the stagnant areas of the stream. The transient storage differential equations were selected as the governing equations for simulation of advection- diffusion of pollution in river flow. The experiments were conducted in a gravel bed flume, with length, width and depth of 12, 1.2 and 0.8m, respectively. Three longitudinal slopes of 0.001, 0.004 and 0.007 and three discharges of 7.5, 11.5 and 15.5 (l/s) were selected for the experiments. The numerical model of OTIS-P was used to estimate the four parameters of the transient storage model. Then the observed breakthrough curves were regenerated at the same locations of measured points. Goodness of fit was estimated with the root mean square error (RMSE), Nash and Sutcliffe model efficiency coefficient (NS) and the mean absolute error (MAE). The comparisons revealed that the OTIS-P model (with RMSE between 0.031- 0.118 and Nash- Sutcliffe between 0.48-0.9) could be employed successfully for estimation transient storage parameters. Finally, the reliability of the estimated parameters of the transient storage model was confirmed by the non-dimensional Dam-kohler number.
https://ijswr.ut.ac.ir/article_70104_7303ff888f58f49e52af8f8ae844c5a2.pdf
2019-03-21
65
76
10.22059/ijswr.2018.244186.667776
Tracer Experiment
Mass Exchange
breakthrough curve
OTIS-P
yaghoub
azhdan
azhdan.yaghoub@gmail.com
1
Department of Water Engineering,Sari Agricultural Sciences and Natural Resources University,Sari, Iran.
AUTHOR
Alireza
Emadi
emadia355@yahoo.com
2
Department of Water Engineering, Sari Agricultural Sciences and Natural Resources University,Sari, Iran.
LEAD_AUTHOR
Jafar
Chabokpour
j.chabokpour@maragheh.ac.ir
3
Faculty of Engineering, Maragheh University,Maragheh, Iran,
AUTHOR
Rasoul
Daneshfaraz
daneshfaraz@yahoo.com
4
Faculty of Engineering, Maragheh University, Maragheh, Iran.
AUTHOR
Barati Moghaddam, M., Mazaheri, M. and Samani, J. M. V. (2017). Numerical solution to advection-dispersion equation with transient storage zones, considering unsteady flow in irregular cross section rivers. Irrigation Sciences and Engineering. pp. 99-117. (In Farsi).
1
Bencala, K.E. (1984). Interactions of solutes and streambed sediment: 2. A dynamic analysis of coupled hydrologic and chemical processes that determine solute transport. Water Resources Research, 20, 1804–1814.
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Busolin, A.B. (2010). Transport of solutes in streams with transient storage and hyporheic exchange. Ph.D. thesis, University of Padova.
4
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5
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10
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Tsai, Y.H. and Holly, R.R. (1979). Temporal and spatial moment for longitudinal mixing in prismatic channels with storage in separation zones. Hydraulic Engineering.
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Valentine, E.M., and Wood, I.R. (1977). Longitudinal dispersion with dead zones. J. Hydraul. Div. ASCE, 103,975-990.
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24
Ward, A.S., Keller C.A., Mason S.J.K., Wagener, T., Mcintyre, N., McGlynn, B., Runkel, R.L. and Payn, R.A. (2016). A software tool to assess uncertainty in transient-storage model parameters using Mont Carlo simulations. Freshwater Science 36(1), 195-217.
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28
ORIGINAL_ARTICLE
Investigation of in the Capita Water Consumption Variation in Iran Based on the Past Two-Deca Diet
In this study, the trend of agricultural water consumption was investigated for 22 years (1989-2011) in Iran, considering crop and livestock requirements per capita. Crop and livestock products were categorized into nine groups so that, each group has its particular subgroups. The results of this study showed that the trend of water consumption per capita was ascending over the proposed period with regard to the diet variations. Wheat in cereal crops and meat in livestock products had the largest water consumption values. The average capita water consumption was estimated about 1420 m3 during 1989-2011 which the maximum and minimum amount of water consumption corresponded to the year of 1389 and 2007, respectively. The volume of virtual water consumed by crops and livestock has been increased from 61 billion m3 in 1368 up to 120 billion m3 in 1390. The portion of imported virtual water through agricultural and livestocks products has been 11-27 billion m3 with an average of 17.6 billion m3 in the proposed period. Rainfed productions with average consumption of 17.3 billion m3 of water by rainfall provide a part of annual water consumption. Therefore, the portion of renewable water resources in agriculture was estimated to be varied from 63 (2008) to 81 (2011) billion m3. According to the water resources assessment indices, Iran was faced to water crisis during the proposed period in which population growth and diet changes may be effective. Regulation of Proper diet such as reducing creal and meat consumption, establishing a dynamic market for selling agricultural products, recycling waste products, importing particular food products and increasing water productive could be effective in prevention of water management crises.
https://ijswr.ut.ac.ir/article_70108_de9d6ac891f2080c46ad080411a86ee9.pdf
2019-03-21
77
87
10.22059/ijswr.2018.246084.667795
Trends in water consumption
water resources
Agricultural products
population
Yaser
Hamdi Ahmadabad
hamdiyaser71@ut.ac.ir
1
1 Ph.D student, Department of Irrigation and Reclamation Eng., College of Agriculture and Natural Resources, University of Tehran, P. O. Box 4111, Karaj 31587-77871, Iran. E-mail: hamdiyaser71@ut.ac.ir
LEAD_AUTHOR
Abdolmajid
Liaghat
aliaghat@ut.ac.ir
2
2 Professor, Department of Irrigation and Reclamation Eng., College of Agriculture and Natural Resources, University of Tehran, P. O. Box 4111, Karaj 31587-77871, Iran. E-mail: aliaghat@ut.ac.ir
AUTHOR
Ali
Rasoulzadeh
rasoulzadeh@uma.ac.ir
3
Associate professor, Department of Water Eng., University of Mohaghegh-Ardabili, Ardabil, Iran. E-mail: rasoulzadeh@uma.ac.ir
AUTHOR
rasoul
ghaderpour
rasoulghaderpour@gmail.com
4
M.Sc. Student of Water Engineering Department, Faculty of Agriculture, Islami Azad University of Mahabad, Mahabad, Iran
AUTHOR
Agricultural Statistics: Cultivars “crop years 2004-2011”. Ministry of Agriculture, Program and Budget Deputy Directorate, Department of Statistics and Information. (In Farsi)
1
Ahmadauli, KH. (2013). Development of virtual water transfer model for correction of cropping pattern and optimal use of agricultural water in the country. Ph. D. dissertation, University of Tehran, Iran.
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Alcamo, J., T. Henrichs and T. Rosch. (2000). World Water in 2025: Global Modeling and Scenario Analysis for the World Commision on Water for the 21th Century. Center for Environmental Systems Research, Report A0002, University of Kassel, Germany.
3
Alizadeh, A. and Keshavarz, A. (2005, March). Status of agricultural water use in Iran. In Water conservation, reuse, and recycling: Proceedings of an Iranian-American workshop (pp. 94-105). Washington DC, USA: National Academies Press.
4
Arabi, A., Alizadeh, A., Rajaee, Y. V., Jam, K. and Nikania, N. (2012). Agricultural Water Foot Print and Virtual Water Budget in Iran Related to the Consumption of Crop Products by Conserving Irrigation Efficiency. Journal of Water Resource and Protection 4, 38-324
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Chapagain, A. K., and Hoekstra, A. Y. (2004). Water footprints of nations.
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Cosgrove, W. J. and Rijsberman, F. R. (2014). World water vision: making water everybody's business. Routledge.
7
De Fraiture, C., Cai, X., Amarasinghe, U., Rosegrant, M. and Molden, D. 2004. Does international cereal trade save water? The impact of virtual water trade on global water use. Comprehensive Assessment Research Report 4, Colombo, Sri Lanka.
8
Dehghanpur, H. and Bakhshoodeh, M. (2008). Investigating Virtual Water Trade limitation issues in Marvdasht Region. Journal of Economics and Agriculture Development, 22(1): 137-147. (In Farsi)
9
Ebadi, F. (2016). Food balance of the Islamic Republic of Iran: A survey on the production and supply of coarse cereals and cerebrospinal fluid in foods from 1385 to 1381. Agricultural planning, Economic and Rural Development Research Institute.
10
Ebadi, F. and Saeednia, A. (2009). Food balance of the Islamic Republic of Iran: A survey on the production and supply of coarse cereals and cerebrospinal fluid in foods from 1385 to 1381. Agricultural planning, Economic and Rural Development Research Institute.
11
Ehsani, M. and Khaledi, H. (2002). Recognition and promotion of agricultural water productivity in order to provide water and food security of the country. Eleventh Seminar of the National Irrigation and Drainage Committee, Tehran, Iran. (In Farsi)
12
Faramarzi, M., Yang, H., Mousavi, J., Schulin, R., Binder, C. R. and Abbaspour, K. C. (2010). Analysis of intra-country virtual water trade strategy to alleviate water scarcity in Iran. Hydrology and Earth System Sciences, 14(8), 1417.
13
jafari nejad, A.GH., Alizadeh, A., Neshat, A. and Abolhassani Zeraatkar, M. (2014). Virtual Water Trade to Improve the Efficiency of Water Use (The case by case study of Kerman province). Iranian Journal of Irrigation and Drainage, 8(2): 325-335. (In Farsi)
14
Kirda, C. (2002). Deficit irrigation scheduling based on plant growth stages showing water stress tolerance. Food and Agricultural Organization of the United Nations, Deficit Irrigation Practices, Water Reports, 22, 102.
15
Mohammadian, F., Alizadeh, A., Nairizi, S. and Arabi, A. (2007). Development of a sustainable cropping pattern based on virtual water trade. 2008. Iranian Journal of Irrigation and Drainage, 2(1): 109-126. (In Farsi)
16
Montazar, A., Zadbagher, E. and Heydari, N. (2009). An assessment model for the virtual water of irrigation networks using analytical hierarchy process. Journal of Water and Soil, 23(4):77-89. (In Farsi)
17
Norouzi, F. and Samimi, B. (2002). Food balance of the Islamic Republic of Iran: An assessment of the birth and supply of food in the country from the nutritional perspective of the years 1380- 1368. Agricultural planning, Economic and Rural Development Research Institute. (In Farsi)
18
Oki, T. and Kanae, S. (2004). Virtual water trade and world water resources. Water Science and Technology, 49(7), 203-209.
19
Postel, S. L., Daily, G. C. and Ehrlich, P. R. (1996). Human appropriation of renewable fresh water. Science-AAAS-Weekly Paper Edition 271, 785-787.
20
Qadir, M., Sharma, B. R., Bruggeman, A., Choukr-Allah, R. and Karajeh, F. (2007). Non-conventional water resources and opportunities for water augmentation to achieve food security in water scarce countries. Agricultural water management, 87(1), 2-22.
21
Rouhani, N., Yang, H., Amin Sichani, S., Afyuni, M., Mousavi, S. and Kamgar Haghighi, A. (2009). Assessment of Food Products and Virtual Water Trade as Related to Available Water Resources in Iran. Journal of Water and Soil Science, 12(46):417-432. (In Farsi)
22
Sepaskhah, A. and Tavakoli, A. (2006). Principles and Applications of Irrigation, Iran National Irrigation and Drainage Committee. (In Farsi)
23
Smakhtin, V., Revenga, C., Döll, P., Tharme, R., Nackoney, J. and Kura, Y. (2004). Taking into account environmental water requirements in global-scale water resources assessments (Vol. 2). IWMI.
24
Tantawi, B. A. (2004). Rice-based production systems for food security and poverty alleviation in the Near East and North Africa: new challenges and technological opportunities. In Proceedings of FAO Rice Conference, Rome, Italy (pp. 12-13).
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van Schilfgaarde, J. (1994). Irrigation—a blessing or a curse. Agricultural water management, 25(3), 203-219.
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27
Yang, H., Reichert, P., Abbaspour, K. C. and Zehnder, A. J. (2003). A water resources threshold and its implications for food security.
28
Zarei, GH. and Jafari, A.M. (2016).The Role of Import and Export of Major Crop Productions in Virtual Water Trade and Water Footprint in Agricultural sector of Iran. Iranian Journal of Irrigation & Drainage, 9(5): 784-797. (In Farsi)
29
Zimmer, D. and Renault, D. (2003). Virtual water in food production and global trade: Review of methodological issues and preliminary results. In Virtual water trade: Proceedings of the International Expert Meeting on Virtual Water Trade, Value of Water Research Report Series (Vol. 12, No. 1, pp. 1-19).
30
ORIGINAL_ARTICLE
Simultaneous Effect of Soil Salinity and Matric Suction on Evaporation and Redistribution of Moisture and Salinity in Two Soils with Different Textures
Daily increasing salinity is one of the main problems of agricultural lands, especially in arid and semi-arid regions, with high evapotranspiration rates. The purpose of this research was to investigate the simultaneous effect of salinity at five levels 2, 4, 8, 16 and 20 dSm-1 for wheat and 0.7, 2, 4, 6 and 8 dSm-1 for bean and matric suction at four levels 2, 6, 10 and 33 kPa, on evaporation rate and redistribution of moisture and salinity in the soil profiles of sandy loam and clay loam. This study was conducted in greenhouse conditions in pots by compeletly randomized factorial desigh with 3 replicates. It was found that evaporation rate decreased by time in the saline and water stress treatments, especially in the clay loam soils, and this reduction was more in the high suction and salinity levels. The lowest evaporation reduction was observed in treatments with the highest soil moisture content. Because, water availability reduced the salinity effect on evaporation. As, at the 2kPa matric suction, the evaporation rate was approximately the same at all levels of salinity and the highest throughout the day after treatment. In the 15th day after treatment and at the 33kPa suction, different salinity levels (from 0.7 to 20 dSm-1) reduced the evaporation rate by 19% in both soils. Also, the results showed that the ECe of the drained soils with 10kPa constant suction increased exponentially with moisture reduction. This trend was more in the clay loam soils. Because the evaporation/drainage ratio of the clay loam soil is more than the one in the sandy loam soil. The salinity redistribution in the both soil profiles and for the two plants were almost constant over time. Also, moisture reduction over the time was higher in the clay loam soil than the one in the sandy loam soil, especially under low salinities.
https://ijswr.ut.ac.ir/article_70109_46f5306723de0445406fc1d9ffbf1730.pdf
2019-03-21
89
98
10.22059/ijswr.2018.248788.667826
Salinity redistribution
Moisture redistribution
Evaporation
Drainage
Matric suction
Mahnaz
Khataar
mahnazkhataar@znu.ac.ir
1
Ph.D Student, Department of Soil Science, University of Zanjan, Zanjan, Iran
LEAD_AUTHOR
Mohmmad Hosein
Mohammadi
mhmohmad@ut.ac.ir
2
Associate Professor. Department of Soil Science, University of Tehran, Karaj, Iran
AUTHOR
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.
1
Chorbanian, M,, Liaghat, A.M. and Nouri, H. (2014). Effect of soil compaction and texture on evapotranspiration and Crop coefficient corn fodder. Journal of Water Research in Agriculture. 28:453-463.
2
Dane, J.H. and 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 Science Society of American. Book Ser 5. Soil Science Society of American Madison, USA. Pp, 675–680.
3
Devkota, M., Martius, C., Gupta, R.K., Devkota, K.P., McDonald, A.J. and Lamers, J.P.A. (2015). Managing soil salinity with permanent bed planting in irrigated production systems in Central Asia. Agriculture, Ecosystems and Environment. 202, 90–97.
4
Ebrahimi H. Hasanpour Darvishi . H. (2015). The Relationship Between Corn Yield and Water Consumption (Computational water demand and lack of soil moisture). Iranian Journal of Irrigation and Drainage. 9,605-613.
5
FAO; Food and Agriculture Organization. (2002). Agricultural drainage water management in arid and semi-arid areas. Annex 1. Crop salt tolerance data. FAO, Rome.
6
FAO; Food and Agriculture Organization. (2010). Fish Stat fishery statistical collections: aquaculture production (1950–2008; released March 2010).Food and Agriculture Organization of the United Nations. Rome.
7
Gee, G. W. and Or, D. (2002). Particle-size analysis. In Dane, J. H., and Topp, G. C. (ed.) Methods of soil analysis. Part 4. Book Ser. 5. Soil Science Society American Journal. Pp, 255–293.
8
Gowing, J. W., Konukcu. F., and Rose, D. A. (2006). Evaporative flux from a shallow water table: The influence of a vapour–liquid phase transition. Journal of Hydrology. 321, 77–89.
9
Ha, T.K.T., Maeda, M., Fujiwara, T. and Nagare, H. (2015). Effects of soil type and nitrate concentration on denitrification products (N2O and N2) under flooded conditions in laboratory microcosms. Soil Science and Plant Nutrition. 61, 999-1004.
10
Khataar, M., Mohammadi, H.M., Shekari, F. (2017a). Effect of Soil Salinity and Aeration Stresses on the Root and Yield Components in Wheat and Bean . Iranian journal of soil and water research. 4, 440-429. (In Farsi).
11
Khataar, M., Mohammadi, H.M., Shekari, F. (2017b). Effect of Soil Salinity on the Wheat and Bean Nutrients in Low Matric Suctions. Iranian journal of soil and water research. 1, 38-25. (In Farsi).
12
Khataar, M., Mohammadi, H.M., Shekari, F. (2017c). Some physiological responses of wheat and bean to soil salinity at low matric suctions. International Agrophysics. 31, 83-91.
13
Khataar, M., Mosadedghi, M.R., Mahboubi, A.A. (2012). Water Quality Effect on Plant-Available Water and Pore Size Distribution of Two Texturally-Different Calcareous Soils. 16, 159-172. (In Farsi).
14
Khataar, M., Mohammadi, MH., and Shabani, F. (2018). The effects of soil salinity and matric suction interaction on water use, water use efficiency and yield response factor of bean and wheat. Scientific Reports (Nature Research). (Accepted).
15
Li, X., Chang, S. X. and Salifu, K. F. (2013). Soil texture and layering effects on water and salt dynamics in the presence of a water table: a review. Environmental Reviews. 21, 1-10.
16
Mohammadi, M.H., Khataar, M. Shekari, F. (2016). Effect of soil salinity on the wheat and bean root respiration rate at low matric suctions, Paddy and water environment. 15,639-648.
17
Mohammadi, M.H., Khataar, M. (2017). A simple numerical model to estimate water availability in saline soils. Australian journal of soil research. https://doi.org/10.1071/SR17081
18
Munns, R. and Tester, M. (2008). Mechanisms of salinity tolerance. Annual Review of Plant Biology. 59, 651-681
19
Rafiee, M. and G. Shakarami. (2010). Water Use Efficiency of Corn as Affected by Every Other Furrow Irrigation and Planting Density. World Applied Sciences Journal. 11, 8265829.
20
Schwabe, K., Albiac, J., Connor, J., Hassan, R. and Meza, L. (2013). Drought in arid and semi-arid regions: A multi-disciplinary a nd cross-country perspective, Springer, Dordrecht.
21
Shannon M.C. and Grieve C.M. (1999). Tolerance of vegetable crops to salinity. Horticultural Science. 78, 5–38
22
Sepaskhah, A. R. and M. Ghasemi. (2008). Every 5 other 5 furrow irrigation with different intervals for sorghum. Pak. J. Biol. Sci. 11(9): 123451239. 24.
23
Sepaskhah, A. R and M. H. Khajehabdollahi. 2005. Alternate furrow irrigation with different irrigation intervals for maize (ZeamaysL.). Plant Production Science. 8, 5925600.
24
Slama, I., Ghnaya, T., Messedi, D., Hessini, K., Labidi, N., Savoure, A. and Abdelly, C. (2007). Effect of sodium chloride on the response of the halophyte species Sesuvium portulacastrum grown in mannitol-induced water stress. Journal of Plant Research. 120, 291–299.
25
Wani, A. S., Ahmad, A., Hayat, S. and Fariduddin, Q. (2013). Salt-induced modulation in growth, photosynthesis and antioxidant system in two varieties of Brassica juncea. Saudi. International Journal of Biological Sciences. 20, 183–193.
26
Zarei, M.A., Tabatabaei, H., Shayan nejad, M. and Beigi Harchegani, H. (2008). Salinity distribution pattern in soil profile under three irrigation regimes in Karty irrigation in the eastern Isfahan lands. Journal of research in agricultural science. 3, 196-206.
27
Zarei, G., Homaee, M. Liaghat, A. M., and Hoorafar, A. H. (2010). A model for soil surface evaporation based on Campbell’s retention curve. Journal of Hydrology. 380, 356-361.
28
Zhang, H. J., Dong, H. Z., Li, W. J. and Zhang, D. M. (2011). Effects of soil salinity and plant density on yield and leaf senescence of field grown cotton. Journal of Agronomy and Crop Science. 198, 27–37.
29
ORIGINAL_ARTICLE
The Effect of Different Land Uses on Soil Micro-arthropods and Soil Properties (Case Study: Cheharmaleh and Tolomeh Region, Ilam Province)
Soil mesofauna have important role in different ecosystems by organic matter breakdown and improvement nutrient cycling. Different types of land uses through variations in inputs of organic matter contents affect soil mesofauna communities and their habitation. The aim of this project was to study the effect of three kinds of land uses including forest (oak trees), agriculture (wheat) and pasture (different pasture species) on population and diversity of the soil mesofauna and on physical and chemical properties of the soil in Cheharmaleh and Tolomeh region in Ilam province. According to the results, the kind of land uses have a significant effect (α = 0.01) on all soil chemical and physical properties, indicating the importance of different land uses on soil characteristics in the study area. The soil depth for the top (0-10 cm) and sub (10-30 cm) layers also showed a significant effect (α = 0.01 and 0.05) on most of the soil properties. For example, the soil depth had no significant effect on lime content (TNV) from chemical properties and SP or silt percentage from physical properties. Interaction of the soil depth and the land use had significant effect on pH and EC at 1% level and on P and K at 5% level. In contrast, this interaction had significant effect on some physical characteristics such as porosity and clay percentage at 1% level and on SP, FC, BD and the sand percentage at 5% level. With respect to arthropods in the soil mesofauna, 24 species and 15 different families from insects, mites and pseudo scorpions were identified and collected. There was a significant effect on the insects and mites of the soil mesofauna affected by the land use and soil depth factors. In addition, there was a significant effect on all arthropods orders by different land use and soil depth, with the exception of beetles order. Based on the soil mesofauna communities, the most density of the insects found in the top layer of the forest soil and the least one in the sublayer of the range soil. The most density of mites was found in the top layer of the forest soil and the least one in the sublayer of the agricultural soil. The most density of mites and collembolan communities were found in the top and sub layers of the forest soil.
https://ijswr.ut.ac.ir/article_70110_e69e094949085b7ad1e52de5953f428a.pdf
2019-03-21
99
109
10.22059/ijswr.2018.250107.667833
Acari
Collembola
Ilam
Land Use
mesofauna
Masoud
Bazgir
m.bazgir@ilam.ac.ir
1
Assistant Professor, Department of Water Resources, College of Agriculture, Ilam University, Ilam, Iran
LEAD_AUTHOR
Majid
Mirabbalou
majid.mirab@gmail.com
2
Department of Plant Protection, College of Agriculture, Ilam University, 69315–516, Iran
AUTHOR
Andjus, L. (2007). The thrips fauna on wheat and on plants of the spontaneous flora in the bordering belt surrounding it. Acta Phytopathologica et Entomologica Hungarica, 39(1,3): 255–261.
1
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2
Brown, G.G., Pasini, A., Benito, N.P., De Aquino, A.M. and Correia, M.E.F. (2001). Diversity and functional role of soil macrofauna communities in Brazilian no-tillage agroecosystems. International Symposium on Managing Biodiversity in Agricultural Ecosystems, 6: 310–328.
3
Carnol, M. and Bazgir, M. (2013). Nutrient return to the forest floor through litter and through fall under 7 forest species after conversion from Norway spruce. Forest Ecological Management, 309: 66–75.
4
Coleman, D.C., Crossley, D.A. and Hendrix, P.F. (2004). Fundamentals of soil ecology. Elsevier Academic Press.
5
Ferris, H., Venette, R.C. and Scow, K.M. (2004). Soil management to enhance bacterivore and fungivore nematode populations and their nitrogen mineralization function. Applied Soil Ecology, 24: 19–35.
6
Ghahari, H., Anlas, S., Sakenin, S., Ostovan, H. and Havaskary, M. (2009). Biodiversity of rove beetles (Coleoptera: Staphylinoidea: Staphylinidae) from the Arasbaran biosphere reserve and vicinity, northwestern Iran. Linzer biologische Beiträge., 41(2): 1949–1958.
7
Gongalsky, K.B., Gorshkova, I.A., Karpov, A.I. and Pokarzhevskii, A.D. (2008). Do boundaries of soil animal and plant communities coincide? A case study of a Mediterranean forest in Russia. European Journal of Soil Biology, 44(4): 355–363.
8
Johnson, N.F. and Triplehorn, C.A. (2004). Borror and Delong’s introduction to the study of insects. Thomson Press, California.
9
Hillel, D. and Rosenzweig, C. (2005). Desertification. In Encyclopedia of Soils in the Environment. D. Hillel, J.H. Hatfield, D.S. Powlson, C. Rosenzweig, K.M. Scow, M.J. Singer, and D.L. Sparks, Eds., vol. 1. Elsevier/Academic Press, 382–389.
10
Hopkins, S.P. (1997). Biology of Springtails (Insect: Collembola). Oxford University Press, Cambridge, UK.
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Kiasari, S.H.M., SaghebTalebi, K.H., Rahmani, R. and Amoozad, M. (2011). Invertebrates diversity at natural and planted forests in sari region (in the depth of 0-10 cm of soil). Journal of Sciences and Techniques in Natural Resources, 6(2): 55–69. (In Farsi).
12
Krantz, G.W. and Walter, D.E. (2009). A Manual of Acarology. Third Edition, Texas Technology University Press,Texas, USA, 807 p.
13
Larsen, T., Schjonning, P. and Axelsen, J. (2004). The impact of soil compaction on euedaphic Collembola. AppliedSoilEcology, 26: 273–281.
14
Mahmoudi, M. and Hakimian, S. (1995). Fundamentals of Soil Science. Tehran University Press, 666 p. (In Farsi).
15
Mirab-balou, M. and Chen, X.X. (2010). A new method for preparing and mounting thrips for microscopic examination. Journal of Environmental Entomology, 32(1): 115–121.
16
Mirab-balou, M., Minaei, K. and Chen, X.X. (2013). An illustrated key to the genera of Thripinae (Thysanoptera, Thripidae) from Iran. Zookeys, 317: 27–52.
17
Ouedraogo, E., Mando, A. and Brussaard, L. (2006). Soil macrofauna affect crop nitrogen and water use efficiencies in Semi-arid West Africa. European Journal of Soil Biology, 42: 275–277.
18
Peck, S.B. and Jacquemart, J. (2012). CDF Checklist of Galapagos Springtails, http://checklists.datazone.darwinfoundation.org/terrestrial-invertebrates/collembola/Last updated, 1–6.
19
Rahmani. R. and Mayvan, H.Z. (2004). Diversity and assemblage structure of soil invertebrates in beech, hornbeam and oak -hornbeam forest types. Iranian Journal of Natural Resources, 56(4): 425–436. (In Farsi).
20
Santamaria, J.M., Moraza, M.L., Elustondo, D., Baquero, E., Jordana, R., Bermejo, R. and Arino, A.H. (2012). Diversity of Acari and Collembola along a pollution gradient in soils of a pre-pyrenean forests ecosestem. Environmental Engineering and Management Journal, 11(6): 1159–1169.
21
Seeber, J. (2012). "Drought-induced reduction in uptake of recently photosynthesized carbon by springtails and mites in alpine grassland". Soil Biology and Biochemistry, 55: 37–39.
22
Siadat, H., Bybordi, M. and Malakouti, M.J. (1997). Salt-affected soils of Iran: a country report. A paper presented in the Seminar on the Salt Affected Soils, Cairo, Egypt.
23
Staley, J.T., Hodgson, C.J., Mortimer, S.R., Morecroft, M.D., Masters, G.J., Brown, V.K. and Taylor, M.E. (2007). Effect of summer rainfall manipulations on the abundance and vertical distribution of herbivorous soil macro invertebrates. European Journal of Soil Biology, 43(3): 189–198.
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Weil, R.R. and Brady, N.C. (2016). The nature and properties of soils. Pearson, 1104 p.
27
Zarinkafsh, M. (1993). Applied soil science. Tehran University, 247 p. (In Farsi).
28
ORIGINAL_ARTICLE
The Effect of Diatomite and Incubation Time on Distribution of Chemical Forms of Lead in Calcareous Contaminated Soils
The presence of heavy metals in water and soil are major concern for the environment due to their toxicity to many life forms. Stabilization of heavy metals in remediation of contaminated soils is one of the cost-effectiveness and rapid implementation method. In order to study the effect of diatomite on chemical forms of Lead in calcareous soils, a factorial experiment was conducted in a completely randomized design (CRD) with three levels of diatomite application in soil (0, 2 and 5 % by weight), four levels of incubation time (1, 2, 4 and 8 weeks) and in twocontaminated soils with three replications. Chemical distribution of Lead in soils were determined using Tessier sequential extraction method during the mentioned incubation times and reduced partition index (IR) and mobility factor (MF) of the metals were calculated as a Lead mobility indices in the soils. The obtained results showed that the application of diatomite significantly (p ≤ 0.01) decreases the lead in the exchangeable and carbonate fractions and increases it in the iron and manganese oxide, organic and residual bond fractions significantly in comparison to the control treatment. The IR and pH values increased but MF and DTPA-extractable Lead values decreased with increasing diatomite level and incubation time which demonstrates a decrease in the mobility of lead in the soils. Lead mobility reduction in the clay loam soil compared to the one in the sandy loam soil was probably due to higher content of clay and lower content of Calcium Carbonate Equilibrium. Generally, itcan be concluded that the addition of diatomite into the soil especially with high levels (5%) reduces the bioavailability and mobility of the Lead in the soil.
https://ijswr.ut.ac.ir/article_70114_9dde647a5f707bf565c4a1fcb1098a78.pdf
2019-03-21
111
122
10.22059/ijswr.2018.250404.667835
Keywords: Sequential extraction
Diatomite
lead
Calcareous soil
marziyeh
piri
ma.piri@urmia.ac.ir
1
Department of soil science, urmia university
AUTHOR
Ebrahim
Sepehr
e.sepehr@urmia.ac.ir
2
Associate Prof., Dep. Soil Sci., Urmia University
LEAD_AUTHOR
Abbas
Samadi
ab.samadi@yahoo.com
3
Professor, Department of Soil Science, Urmia University, Urmia, Iran
AUTHOR
Khalil
Farhadi
4
Professor, Department of Chemistry, Urmia University, Urmia, Iran
AUTHOR
Mohammad
Alizadeh
5
Professor, Department of Food Science and Technology, Urmia University, Urmia, Iran
AUTHOR
Abad-Valle, P., Alvarez-Ayuso, E., Murciego, A. and Pellitero E. (2016). Assessment of the use of sepiolite amendment to restore heavy metal polluted mine soil. Geoderma, 280, 57-66.
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Bilgin, M. and Tulun, S. (2015). Use of diatomite for the removal of lead ions from water: thermodynamics and kinetics. Biotechnology and Biotechnological Equipment, 29(4), 696-704, DOI: 10.1080/13102818.2015.1039059.
5
Caliskan, N., Kul, A.R., Alkan, S., Sougut, E.G. and Alacabey, I. (2011). Adsorption of zinc (II) on diatomite and manganese-oxide-modified diatomite: A kinetic and equilibrium study. Journal of Hazardous Materials, 193, 27-36.
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Puga, A.P., Melo, L.C.A., de Abreu, C.A., Coscione, A.R. and Paz-Ferreiro, J. (2016). Leaching and fractionation of heavy metals in mining soils amended with biochar. Soil and Tillage Research, 164, 25–33.
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Saffari, M., Karimian, N., Ronaghi, A., Yasrebi, J., Ghasemi-Fasaei, R. (2015). Stabilization of nickel in a contaminated calcareous soil amended with low-cost amendments. Journal of Soil Science and Plant Nutrition, 15 (4), 896-913.
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Saffari, M., Yasrebi, J., Karimian, N.A., Shan, X. Q. (2009). Effect of Calcium Carbonate Removal on the Chemical Forms of Zinc in Calcareous Soils by Three Sequential Extraction Methods. Research Journal of Biological Sciences, 4, 858-865.
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Vassileva, P.S., Apostolova, M.S., Detcheva, A.K. and Ivanova, E.H. (2013). Bulgarian natural diatomites: modification and characterization. Journal of Chemistry and Chemical Engineering. 67: 342–349.
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Ye X., Kang S., Wang H., Li H. and Zhang Y. (2015). Modified natural diatomite and its enhanced immobilization of lead, copper and cadmium in simulated contaminated soils. Journal of Hazardous Materials, 289:210-218.
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48
ORIGINAL_ARTICLE
Comparison the results of three methods for measuring the amount of Water-Dispersible Clay in Khuzestan soils
The fraction of clay that disperses in water, water-dispersible clay (WDC), is recognized as an important property with respect to predicting soil erosion, colloid leaching and soil development. The WDC is measured by different methods producing different results. In this study, three methods (Rasmussen, Mechanical stirrer and Ultrasound) were compared in terms of measuring the amount of WDC in soils. For this purpose soil samples with different physio-chemical properties were collected from different region of Khuzestan province and the WDC were determined by the proposed methods. The correlation between WDC and the soil properties were analyzed using regression model and equations were fitted for the three methods. The results showed that the WDC measured by Rasmussen, Shaker and Ultrasound methods were 72.6 (%), 33.4 (%) and 14.1 (%) from total clay, respectively. The results showed that the most important soil properties affecting the WDC for Rasmussen method were gypsum and clay, for Mechanical stirrer were linear extensibility coefficient (COLE), organic matter (OM), clay, gypsum and total sand, and for Ultrasound method were gypsum content, linear extensibility coefficient and silt. These varieties could be related to the nature of each method. Also, statistical analysis showed that the gypsum, COLE, and silt content had maximum effect on the WDC in Rasmussen, Mechanical stirrer, and Ultrasound methods, respectively. Organic matter, gypsum, sodium adsorption ratio (SAR), soluble sodium, and electrical conductivity had negative correlations with WDC, and the total clay content, lime, COLE, cation exchange capacity and pH had a positive correlation. Therefore, it is suggested that the selected method for measuring WDC should be according to the research emphasizes and soil characteristics. Also, the effect of aggregates size, type and organic matter composition on the WDC should be investigated in future study.
https://ijswr.ut.ac.ir/article_70117_a050a58c66836ad5bdad48e95b09d7ac.pdf
2019-03-21
123
134
10.22059/ijswr.2018.246794.667803
-Dispersible Clay
Ultrasound
Rasmussen
Mechanical stirrer
siroos
jafari
siroosjafari@yahoo.com
1
Associate Professor, Soil Science Department, Agricultural sciences and Natural Resources University of Khuzestan,Ahwaz, Iran
LEAD_AUTHOR
Elham
Bordbar
elham.bordbar@ymail.com
2
Graduated M.Sc Student, Soil Science Department, Agricultural sciences and Natural Resources University of Khuzestan,Ahwaz, Iran
AUTHOR
Mansur
Ghanian
m_ghanian@yahoo.com
3
Associate Professor, Human Geography & Rural Planning, Agricultural sciences and Natural Resources University of Khuzestan,Ahwaz, Iran
AUTHOR
Asgari, N. and Jafari. S. (2017). The study of particle size distribution of calcium carbonate and its effects on some soil properties in Khuzestan province. Agriculture research Journal, 36(2), 71-80.
1
Brubaker, S. C., Holzhey, C. S. and Brashert, B. R. (1992). Estimating the water-dispersible clay content of soils. Soil Science Society of America Journal, 56(4), 1226-1232.
2
Chapman, H.D. (1965). Cation exchanges capacity. PP. 891-901. In: Black, C. A (Eds.), Methods of soil analysis. Part 2. Chemical analysis. American Society of Agronomy. Madison, Wisconsin.
3
Curtin, D., Steppuhn, H. and Selles, F. (1994). Effects of magnesium on cation selectivity and structural stability of sodic soils. Soil Science Society of America Journal, 58(3), 730-737.
4
Franzen, D.W. and Richardson, J.L. (2000). Soil factors affecting Fe chlorosis of soybeans in the Red River Valley of North Dakota and Minnesota. Journal of Plant Nutrition, 23, 67-78.
5
Fuller, L. G., Tee Boon, G.and Oscarson, D. W. (1995). Cultivation effects on dispersible clay of soil aggregates. Canadian Journal of Soil Science, 75(1), 101-107.
6
Gee, G.W. and Bauder, J.W. (1986). Particle-Size analysis. P. 383-411. In: Klute, A. (Eds.), Methods of soil analysis. Part7. Soil Science Society of American.
7
Ghorbani, Z., Jafari S.and Khalili MoghaddamB. (2014). The effect of physicochemical properties of soils under different land use on aggregate stability in somepart of Khuzestan province. Soil management and sustainable production,3(2),29-51. (In Farsi)
8
Hosseini, M. and GolchinA. (2011). The effect of salinity and sodic of irrigation water on water dispersible clay in a soil under different land use. 5th National conference and exhibition on environmental engineering.Tehran. (in Farsi)
9
Khazaei, A., Mosaddeghi, M.R. and Mahboubi, A.A. (2008) Impacts of test conditions, soil organic matter, clay and calcium carbonate contents on mean weight diameter and tensile strength of aggregates of some hamedan soils.Journal of Science and Technology of Agriculture and Natural Resources, 12(44),123-134. (In Farsi)
10
Kjaergaard, C., Jonge, L. W., Moldrup, P. and Schjonning, P. (2004). Water-dispersible colloids. Vadose Zone Journal, 3(2), 403-412.
11
Marquez, C. O., Garcia, V. J., Cambardella, C. A., Schultz, R. C. and Isenhart, T. M. (2004). Aggregate-Size Stability Distribution and Soil Stability. Soil Science Society of America Journal, 68(3), 725–735.
12
Nelson, R.E. (1982). Carbonate and gypsum. P. 181-199. In: Page, A.L. (Eds.), Methods of soil Analysis. Part 2. American Society of Agronomy. Madison, Wisconsin.
13
Rasmussen, P. E. and Collins, H. P. (1991). Long -term impacts of tillage, fertilizer, and crop residue on soil organic matter in temperate semi-arid regions. Advanced Agronomy, 45,93-134.
14
Rhoades, J. D. (1996). salinity: Electrical Conductivity and Total Dissolved Solid.P. 417-435. In: sparks, D. L., Helmke, P. A., Leoppet, R. H., Soltanpour. P. N. Tabatabai, M. A., Johnston, C. T. and Summer, M. E. (Eds),Methods of soil analysis. Part 3. Chemical Methods Soil Science Society American Inc. Book series, No. 5, Madison, WI, USDA.
15
Sposito, G. (1996). The chemistry of soils. First edition. Oxford university press.
16
Sposito, G. (2008). The chemistry of soils(2th ed.). Oxford university press.
17
Thomas, G. W. (1996). Soil pH and soil Acidity. P. 475-490.In: sparks, D. L., Helmke, P. A., Leoppet, R. H., Soltanpour. P. N. Tabatabai, M. A., Johnston, C. T. and Summer, M. E(Eds),Methods of soil analysis. Part 3. Chemical Methods Soil Science Society American Inc. Book series, No. 5, Madison, WI, USDA.
18
Walkley, A. 1947. A Critical examination of a rapid method for determining soil organic carbon in soils. Effect of variations in digestion conditions and inorganic soil constituents. Soil Sci. 63: 251-264.
19
ORIGINAL_ARTICLE
Numerical Simulation of Lateral Pipe Intake from Open Channel
Intake structures which are used as water diverting structures in open channels, rivers, and reservoirs are of the oldest issues of hydraulic engineering. In this study, a lateral pipe intake was proposed as a flow diversion structure provided in side walls of a channel, and its discharge characteristics and flow pattern was studied numerically using 3D CFD package, Flow-3D. The simulations have been performed for various parameters. The results showed that the lateral pipe intake with 90o angle has the highest efficiency among all of our simulation scenarios. The vortex and the separation zone in the lateral pipe intake were formed behind the pipe. Also, formation of the recirculation zone behind the lateral pipe intake can be affected by other parameters like inlet Froude number and transversal position of the pipe intake mouth. Furthermore, an equation was developed for the discharge coefficient in the lateral pipe intake. The computed discharges were within ±15% of the observed ones.
https://ijswr.ut.ac.ir/article_70118_44cdb2e08018bbab2e18932cfd76eda0.pdf
2019-03-21
135
147
10.22059/ijswr.2018.252260.667851
Discharge coefficient
lateral intake
Numerical simulation
pipe
Mahmood
Rahmani Firozjayi
mrahmanif69@gmail.com
1
Former MSc. Student, Civil Engineering Department, University of Tarbiat Modares, Tehran, Iran
LEAD_AUTHOR
Ehsa
Behnamtalab
behnamtalab@yahoo.com
2
Assistant Professor, Civil Engineering Department, Hakim Sabzevari University, Sabzevar, Iran
AUTHOR
Seyed Aliakbar
Salehi Neyshabouri
salehi@modares.ac.ir
3
Professor, Civil Engineering Department, University of Tarbiat Modares, Tehran, Iran
AUTHOR
Asnaashari, A., & Merufinia, E. (2015). Numerical Simulation of Velocity Distribution in the River Lateral Intake Using the SSIIM2 Numerical Model. Cumhuriyet Science Journal, 36(3), 1473-1486.
1
Azimi, H., Shabanlou, S., Ebtehaj, I., Bonakdari, H., & Kardar, S. (2017). Combination of Computational Fluid Dynamics, Adaptive Neuro-Fuzzy Inference System, and Genetic Algorithm for Predicting Discharge Coefficient of Rectangular Side Orifices. Journal of Irrigation and Drainage Engineering, 143(7), 04017015.
2
Barkdoll, B. D., Ettema, R., & Odgaard, A. J. (1999). Sediment control at lateral diversions: Limits and enhancements to vane use. Journal of Hydraulic Engineering, 125(8), 862-870.
3
Biswal, S. K., Mohapatra, P., & Muralidhar, K. (2016). Hydraulics of combining flow in a right-angled compound open channel junction. Sadhana, 41(1), 97-110.
4
Eghbalzadeh, A., Javan, M., Hayati, M., & Amini, A. (2016). Discharge prediction of circular and rectangular side orifices using artificial neural networks. KSCE Journal of Civil Engineering, 20(2), 990-996.
5
Gómez-Zambrano, H. J., López-Ríos, V. I., & Toro-Botero, F. M. (2017). New methodology for calibration of hydrodynamic models in curved open-channel flow. Revista Facultad de Ingeniería Universidad de Antioquia, (83), 82.
6
Goudarzizadeh, R., Hedayat, N., & Jahromi, S. M. (2010). Three-dimensional simulation of flow pattern at the lateral intake in straight path, using finite-volume method. World Academy of Science, Engineering and Technology, 47, 656-661.
7
Guo, J. C., & Stitt, R. P. (2017). Flow through Partially Submerged Orifice. Journal of Irrigation and Drainage Engineering, 143(8), 06017006.
8
Haddad, H., Ahmad, E., & Azizi, K. (2017). Numerical simulation of the inlet sedimentation rate to lateral intakes and comparison with experimental results. Journal of Research on Ecology, 5(1): 464-472.
9
Hashid, M., Hussain, A., & Ahmad, Z. (2015). Discharge characteristics of lateral circular intakes in open channel flow. Flow Measurement and Instrumentation, 46, 87-92.
10
Hirt, C. W. (1988). Flow-3D User’s Manual, Flow Sciences.
11
Hussain, A., Ahmad, Z., & Asawa, G. L. (2010). Discharge characteristics of sharp-crested circular side orifices in open channels. Flow Measurement and Instrumentation, 21(3), 418-424.
12
Kasthuri, B., & Pundarikanthan, N. V. (1987). Discussion of “Separation zone at open-channel junctions” by James L. Best and Ian Reid (November, 1984). Journal of Hydraulic Engineering, 113(4), 543-544.
13
Mirzaei, S. H. S., Ayyoubzadeh, S. A., & Firoozfar, A. R. (2014). The effect of submerged-vanes on formation location of the saddle point in lateral intake from a straight channel. American Journal of Civil Engineering and Architecture, 2(1), 26-33.
14
Neary, V. S., & Odgaard, A. J. (1993). Three-dimensional flow structure at open-channel diversions. Journal of Hydraulic Engineering, 119(11), 1223-1230.
15
Neary, V. S., Sotiropoulos, F., & Odgaard, A. J. (1999). Three-dimensional numerical model of lateral-intake inflows. Journal of Hydraulic Engineering, 125(2), 126-140.
16
Ouyang, H. T., & Lin, C. P. (2016). Characteristics of interactions among a row of submerged vanes in various shapes. Journal of hydro-environment research, 13, 14-25.
17
Ramamurthy, A. S., Qu, J., & Vo, D. (2007). Numerical and experimental study of dividing open-channel flows. Journal of Hydraulic Engineering, 133(10), 1135-1144.
18
Schindfessel, L., Creëlle, S., & De Mulder, T. (2017). How Different Cross-Sectional Shapes Influence the Separation Zone of an Open-Channel Confluence. Journal of Hydraulic Engineering, 143(9), 04017036.
19
Seyedian, S. M., Bajestan, M. S., & Farasati, M. (2014). Effect of bank slope on the flow patterns in river intakes. Journal of Hydrodynamics, Ser. B, 26(3), 482-492.
20
Swamee, P. K., & Swamee, N. (2010). Discharge equation of a circular sharp-crested orifice. Journal of Hydraulic Research, 48(1), 106-107.
21
ORIGINAL_ARTICLE
Study of the Optimal Conditions for 〖Zn〗^(+2) Removal Using the Biomass of Isolated Bacteria from Ravang Mine
Environmental pollution consist of heavy metals is the most important environmental problems and leads to serious damage for human health. In order to reduce the harmful effects of heavy metals, their treatment methods should be developed, of which the use of biological absorbers are particularly important. The objective of this study was to isolate the -resistant bacteria from Ravanj lead- and zinc-Mine in Markazi Province and to find the most efficient strains for zinc adsorption. For this purpose, samples were collected from the mine sediments and the resistant bacteria were enriched in the medium and isolated. After determining the resistance of isolated bacteria to , the most effective strain (MS3, Delftia lacustris) were detected by 16S rDNA sequencing. Then after the dried strains biomass was prepared and the effect of main operational variables such as, Zinc to Bacteria Biomass concentration ratio (), and the retention time of bacteria biomass in the Zinc medium on Zinc removal has been evaluated and analyzed using the response surface method and Box-Behnken model. A numerical optimization model was performed to obtain the maximum amount of Zinc removal from aqueous solution. Among the isolated strains, the MS3 (Delftia lacustris) was the most tolerance strain to the Zinc (1200 mg/l). The maximum percentage of Zinc removal based on the quadratic model was obtained at (means), (means Zinc to Bacteria Biomass concentration ratio of), and (means). The maximum amount of Zinc removal percentages based on the experimental design and the simulated model were 9.86% and 9.49% respectively, indicating the high accuracy of the model. Therefore, the MS3 strains can be used as a bio-absorbent for Zinc removal.
https://ijswr.ut.ac.ir/article_70119_54f6eb496d6ca521d0e49b5b6f35dbca.pdf
2019-03-21
149
160
10.22059/ijswr.2018.253277.667859
Zinc removal
biosorption
bactria
Optimization
Response surface
mehdi
safari
mb.safari@yahoo.com
1
Assistant Professor of Department of Geology, Payame Noor University, Tehran, Iran
AUTHOR
mohsen
shahriari moghadam
mohsen.mshahriari@gmail.com
2
Department of Environment, Faculty of Natural Resources, University of Zabol, Zabol, Iran
LEAD_AUTHOR
Mohsen
Samimi
m.samimi@hotmail.com
3
Assistant professor of Department of Chemical Engineering, Faculty of Energy, Kermanshah University of Technology, Kermanshah, Iran
AUTHOR
zahra
azizi
zahraazizi9@gmail.com
4
Graduate Student (MSc) of Animal Biosystematics, Faculty of Biological Sciences and Technology, Shahid Behshti University, Tehran
AUTHOR
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30
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31
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34
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42
ORIGINAL_ARTICLE
Evaluation of Heavy Metal Pollution Indices for Surface Water of the Sarcheshmeh Copper Mine using Multivariate Statistical Methods and GIS
Sarcheshmeh copper mine is the second largest open-pit copper mine in the world which its mining activities, dewatering operations, and dam construction could cause pollution to the surface and groundwater of the region. In this study, the heavy metal pollution index (HPI), heavy metal evaluation index (HEI), and degree of contamination (Cd) were used to evaluate heavy metal concentration in the 82 samples of surface water. Also, the main effective parameters on the heavy metal pollution indices were investigated using principal component analysis (PCA). The hybrid multiple linear regression (MLR) and PCA model was used to develop new equations for HPI, HEI, and Cd indices using minimum number of heavy metal variables. The study area was divided into three sub-sections with different mining activities. The concentrations of elements in water samples were compared with the maximum admissible concentration values of WHO standard for drinking purposes. Based on the spatial distribution maps in GIS, the highest concentrations of heavy metals were found in mining sites and sedimentary dam, and the lowest ones found in the Shour River. Based on the HPI values, 70% of the samples were in the critical range of 100- 482245.3 and only 30% of samples were classified as having low pollution levels. The HEI and Cd results revealed that the 79 (96%) and 69 (84.2%) samples were polluted with heavy metals, respectively. The PCA extracted four components, of which the first component with 63.3% of the total variance contains high loadings for Al, Cd, Co, Fe, Zn, Mn, and Ni elements. Despite of very wide ranges of indices variation, the accuracy of proposed MLR-PCA model was confirmed for less number variables in the study area. Findings of this study can be used for investigating preventive measures and to control pollution in the study area and similar regions for drinking purposes in the future.
https://ijswr.ut.ac.ir/article_70120_73136e7d55ae4ba04794989f1d0a6d4f.pdf
2019-03-21
161
176
10.22059/ijswr.2018.254261.667869
Cluster Analysis
Principal Component Analysis
Pollutant critical limit
Degree of contamination
Quality classification
Akram
Seifi
seifi.akram@gmail.com
1
Assistant Professor, Department of Water Engineering, Vali-e-Asr University, Rafsanjan, Iran
LEAD_AUTHOR
Hossien
Riahi
hossien.riahi@gmail.com
2
Assistant Professor, Department of Water Engineering, Vali-e-Asr University, Rafsanjan, Iran
AUTHOR
Ahmad, Z., Rahim, N. A., Bahadori, A. and Zhang, J. (2017). Improving water quality index prediction in Perak River basin Malaysia through a combination of multiple neural networks. International Journal of River Basin Management, 15(1), 79-87.
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2
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3
Cheng, H., & Hu, Y. (2010). Lead (Pb) isotopic fingerprinting and its applications in lead pollution studies in China: a review. Environmental Pollution, 158(5), 1134-1146.
4
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8
Ghaderian, S. M. and Ravandi, A. A. G. (2012). Accumulation of copper and other heavy metals by plants growing on Sarcheshmeh copper mining area, Iran. Journal of Geochemical Exploration, 123, 25-32.
9
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10
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11
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12
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13
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14
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17
Malakooti, S. J., Shahhosseini, M., Ardejani, F. D., Tonkaboni, S. Z. S. and Noaparast, M. (2015). Hydrochemical characterisation of water quality in the Sarcheshmeh copper complex, SE Iran. Environmental Earth Sciences, 74(4), 3171-3190.
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27
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28
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Zabowski, D., Henry, C. L., Zheng, Z. and Zhang, X. (2001). Mining impacts on trace metal content of water, soil, and stream sediments in the Hei River basin, China. Water, Air, and Soil Pollution, 131(1-4), 261-273.
44
ORIGINAL_ARTICLE
Introducing a Hybrid Method for Estimating Wind Speed Using Information from Neighboring Stations in Isfahan Province
The prediction of wind components including wind speed is one of the important factors, especially in the case of evaporation in a watershed. In this paper, in order to increase the efficiency of support vector machines (SVM) for predicting wind speed, the SVM model was combined with the firefly optimization algorithm called hybrid model (HM). In this regard, the wind speed data from synoptic stations of Isfahan province were used to estimate the monthly wind speed values of the unknown neighboring stations. Then, the efficiency of the SVM and HM models was compared. Finally, the RMSE, MAE, WI, and NS indices were used to evaluate the both models performance efficiency. The results in the evaluation step showed that the hybrid model (HM) with high correlation and lower error values has higher performance efficiency as compared to the SVM model. as Also, the method of using neighboring stations data as inputs for the predictive models of unknown station is a proper method for estimation of wind speed.
https://ijswr.ut.ac.ir/article_70123_a91b35bf4a65ecfb1b325926760bbf79.pdf
2019-03-21
177
188
10.22059/ijswr.2018.254410.667873
Isfahan
firefly optimization algorithm
neighboring station
hybrid method
wind speed
Babak
Mohammadi
babakmohammadi@ut.ac.ir
1
Irrigation & Reclamation Engrg. Dept. University of Tehran Karaj, Iran.
AUTHOR
Zahra
Aghashariatmadari
zagha@ut.ac.ir
2
Zahra Shariatmadari Assistant Prof., Irrigation & Reclamation Engrg. Dept. University of Tehran Karaj, Iran.
LEAD_AUTHOR
Afkhami, H., Talebi, A., Mohammadi, M. and Fotouhi, F. (2015). Investigation of the feasibility of wind speed prediction using hybrid model of neural networks, neural -fuzzy networks and wavelet (Case Study: Station of Yazd). jwmseir. 9 (30): 31-40. (In Farsi)
1
Alexiadis, M. C., Dokopoulos, P. S. and Sahsamanoglou, H. S. (1998). Short-term forecasting of wind speed and related electrical power.Solar Energy. 63(1): 61-68,1998.
2
Burton, T., Sharpe, D., Jenkins, N. and Bossanyi, E. (2001). Wind energy handbook. Chichester: John Wiley and Sons.
3
Cadenas, E. and Rivera, W. 2007. Wind speed forecasting in the south coast of Oaxaca, Mexico. Renewable Energy. 32 (12): 2116-2128.
4
Deo, R., Ghorbani. M.A., Samadianfard, S., Maraseni, T., Bilgili, M. and Biazar, M. (2017). Multi-layer perceptron hybrid model integrated with the firefly optimizer algorithm for wind speed prediction of target site using a limited set of neighboring reference station data. Renewable Energy. 116: 309-323.
5
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Ghorbani, M. A., Deo, R., Yaseen, Z.M., Kashani, M.H. and Mohammadi, B. (2017a). Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran. Theoretical and Applied Climatology. 129:1-13.
7
Ghorbani, M. A., Shamshirband, SH., Zare Haghie, D., Azania, A., Bonakdarif, H. and Ebtehajf, I. (2017b). Application of firefly algorithm-based support vector machines for prediction of field capacity and permanent wilting point. Soil & Tillage Research. 172: 32–38.
8
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10
Kazemzadeh, M,J., Daneshmand. and Ahmadfard, M. A. (2015). Optimal Remediation Design of Unconfined Contaminated Aquifers Based on the Finite Element Method and a Modified Firefly Algorithm. Water Resources Management. 29(8): 2895-2912.
11
Kisi, O., Genc. O., S. Dinc and M. Zounemat-Kermani. (2016). Daily pan evaporation modeling using chi-squared automatic interaction detector, neural networks. Classification and Regression tree Computers and Electronics in Agriculture. 122: 112–117.
12
Kisi, O., Shiri, J., Karimi, S., Shamshirband, Sh., Motamedi, Sh., Petkovic, D. and Hashim, R. (2015). A survey of water level fluctuation predicting in Urmia Lake using support vector machine with firefly algorithm. Applied Mathematics and Computation. 270: 731-743.
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Liu, H., Chen, C., Tian, H. and Li., Y. (2012b). A hybrid model for wind speed prediction using empirical mode decomposition and artificial neural networks. Renewable Energy. 48: 545-556.
15
Mohammadi, B. (2017). Daily Evaporation prediction based on a hybridization of Artificial Neural Network and firefly Optimization Algorithm. Thesis is approved for the degree of Master of Science in Water Resources. Department of Water Engineering, Faculty of Agriculture, University of Tabriz. (In Farsi)
16
Mohammadi, B. and Emamgholizadeh, S. (2017). Using principal component analysis to inputs the effective rainfall estimates based on entries to help support vector machine and artificial neural network. Journal of Rainwater Catchment Systems. 4(4): 67-75. (In Farsi)
17
Mohammadi, B., Moazenzadeh, R. (2017). Uncertainty analysis of artificial neural network models and support vector machine in rainfall estimation. Journal of Rainwater Catchment Systems. 5(1): 43-50. (In Farsi)
18
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19
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20
Philippopoulos, K. and Deligiorgi, D. (2012). Application of artificial neural networks for the spatial estimation of wind speed in a coastal region with complex topography. Renewable Energy. 38(1): 75-82.
21
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22
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23
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24
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26
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27
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28
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29
Zhang, Q. and Benveniste, A. (1992). Wavelet networks. IEEE Transactions on Neural Networks. 3(6): 889-898.
30
ORIGINAL_ARTICLE
Effect of irrigation interval on yield and yield components of New Corn Cultivars
In order to investigate the effect of irrigation interval on water use efficiency, yield, yield components and also determining the most suitable maize cultivar, a split plot experiment in a randomized completely block design was implemented with four replicates for two years (2014-2016) in Behbahan Agricultural Research Station. The main factor of drought stress was irrigation after 100 and 200 mm evaporation from class A pan and the sub factor was cultivars in four levels including Karoon 701, S.C. Mobin, S.C 704 and PH1. After the complete emergence of the field when the total evaporation from the class A reaches to 100 and 200 millimeters, the amount of irrigation water is calculated based on the deficit moisture content to field capacity and is applied to each sub-plot by a flowmeter. The comparison of mean irrigation treatments showed 100 mm evaporation from class A pan had a significant superiority in all properties than 200 mm evaporation from class A pan. The yield of corn in stress treatment (200 mm) showed a decrease of 16.7% as compared to the non-stress (100 mm) treatment. For each cm reduction in water consumption per hectare, the yield of corn decreased 164 kg per hectare. The earlier appearance of corn in PH1 variety of maize caused a premature cultivar and a reduction in the growth period which cause a less water consumption and a more opportunity for land preparation for the next cultivation. The comparison of traits mean in irrigation and cultivar interaction showed that the PH1 cultivar with 100 mm evaporation from class A pan was superior in terms of grain yield and water use efficiency which were equal to 7143.5 kg/ha and 1.353 kg/m3, respectively. The results of Pearson correlation coefficient showed by increasing the yield components of corn, the grain yield and water use efficiency increases and vice versa.
https://ijswr.ut.ac.ir/article_70124_359bf135647fd0c1eca5d9200ec88f1b.pdf
2019-03-21
189
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10.22059/ijswr.2018.255156.667880
1000-grain weight
Water use efficiency
Evaporation
Nader
Salamati
nadersalamati@gmail.com
1
Scientific Broad Member, Agricultural Engineering Research Department, Khuzestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Ahvaz, Iran.
LEAD_AUTHOR
Amirkhosro
Danaie
amirkhosrodanaie@yahoo.com
2
Member of Scientific Board, Seed and Plant lmprovement Department, Khuzestan. Agricultural and Natural Resources Research and Education Center, AREEO, Ahvaz, Iran
AUTHOR
Ahmadi, J., Zainali Khaneghah, H., Rustami, M. And Chuckan, R. (2000). Evaluation of drought resistance in late commercial commercial corn hybrids. Iranian Journal of Agricultural Science, No. 4, pp. 891-899. (In Farsi)
1
Afuni, M. and Rezaei Nejad, Y. (1999). Effect of Organic Materials on Chemical Properties and Corn Cultivation and Functioning, Abstract of Articles of the Sixth Iranian Soil Science Congress. P. 146. (In Farsi)
2
Azarpanah, A., Alizadeh, O., Dehghanzadeh, H. and Zare, M. (2013). The effect of irrigation levels in various growth stages on morphological characteristics and yield components of Zea mays L. Technical Journal of Engineering and Applied Sciences. (14) 3: 1459-1447.
3
Barzegari, M. (2017). Report on the introduction of maize variety: PH1. Agricultural Research, Education and Extension Organization. Seed and Plant Improvement Institute. Safiabad Agricultural Research Center: 3-5. (In Farsi)
4
Bigloi, M., Kafi Ghasemi, A., Javaherdashti, M. And Esfahani, M. (2013). The effect of irrigation regimes on yield and quality of corn (S C 704) in Rasht area. Journal of Agricultural Sciences of Iran. 3 (15): 206-196. (In Farsi)
5
Cakir, R. (2004). Effect of water stress at different development stages on vegetative and reproductive growth of corn. Field Crops Research 89: 1-6.
6
Choukan, R.(2015). Final report of Yield trial of promising late and medium maturing maize hybrids (final stage). Ministry OF Jahad – e- Agriculture. Agricultural Research, Education and Extension Organization. Seed and Plant Improvement Institute: 16. (In Farsi)
7
Cooper, M., Van Eeuwijk, F., Chapman, S. C., Podlich, D. W. and Löffler, C. (2006). Genotype-by-environment interactions under water-limited conditions. In: Ribaut J. M. (Ed.). Drought adaptation in cereals. Binghamton, NY, The Haworth Press, Inc.pp: 51-96.
8
Dehghanpoor, Z. (2013). Directions for planting, keeping and harvesting corn. Ministry OF Jahad – e- Agriculture. Agricultural Research, Education and Extension Organization. Seed and Plant Improvement Institute: 91-97. (In Farsi)
9
Dehghanpour, Z. (2014). Technical instruction on planting, harvesting and harvesting of corn (grains and forage). Karaj, Ministry of Agriculture, Agricultural Research, Education and Promotion Institute, Seed and Plant Improvement Research Institute, Agricultural Education Publishing. (In Farsi)
10
Edmeades, G.O., Bolanos, J., Banziger, M. and Ortega, A. (1998). Developing drought and low-nitrogen tolerant. Maize Symposium Abstracts.Dept. Agriculture, University of Queensland, Brisbane 4072. Australia.
11
Emam, Y. and Niknejad, M. (2004). An Introduction to the Physiology of Crop Yield. Shiraz University Press, 571 p.(In Farsi).
12
Farshi, A.A., Shariati, M., Jarolahi, R., Ghaemi, M.R., Shahabi Far, M. and Tavalaie, Mir.M. (2007). Estimated Water Requirements for Plants. Agricultural Education Publishing, Agricultural Research, Education and Promotion Organization, Soil and Water Research Institute. (In Farsi)
13
Grant, R.F., Jackson, B.C., Kiniry, J.R. and Arikin, G.F. (1989). Water deficit timing effects on yield Components in maize. Agronomy Journal. 81: 61-65.
14
Hall, A.J.L., Emcoff, J.H., and Trapani, N. (1981). Water stress before and during flowering in maize and its effects on yield its Components, and Their determinants. Maydica 26: 19-38.
15
Herero, M. P. and Johnson, R. R. (1981). Drought stress and its effects on maize reproductivte systems. Crop Science. 21: 105-110.
16
Howell, T.A., Tock, J.A., Schneider, A.D and Evett, S.R. (1998). Evapotranspiration, yield and water use efficiency of corn hybrids differing in maturity. Agronomy Journal. 90: 3-9.
17
Kang, S.Z., Zhang, L., Liang ,Y.L., Hu, X.T., Cai, H.J. and Gu, B.J. (2002). Effects of limited irrigation on yield and water use efficiency of winter wheat in the Loess Plateau of China. Agricultural Water Management. 55: 203-216.
18
Karlen, D.M. and Camp, C.R.. (1985). Row spacing plant population, and water management effect on corn in the in the Atlanta coastal plain. Agronomy Journal. 77:393-398.
19
Mohammadai, H., Soleymani, A. and Shams, M. (2012). Evaluation of Drought Stress Effects on Yield Components and Seed Yield of Three Maize Cultivars (Zea mays L.) in Isfahan region. International Journal of Agriculture and Crop Sciences, (19) 4: 1436-1439.
20
Mostafavi, Kh., Shoahosseini, M. and Sadeghi Geive, H. (2011). Multivariate analysis of variation among traits of corn hybrids traits under drought stress. International Journal of Agricultural Sciences. 1 (7): 416-422.
21
Musick,J.T., and D.A.Dusek . (1980). Irrigated corn yield response to water. Transaction of the ASAE, 23(1):92-98.
22
Nesmith, D.S. and Ritchie, J.T. (1992). Short and long term responses of corn to a pre-anthesis soil water deficit Agronomy Journal. 84: 106-113.
23
Panday, R.K., Marienville, J.W. and Adum, A. (2000). Deficit irrigation and nitrogen effect on maize in a sahelian environment. I. Grain yield components. Agricultural water management. 46: 1-13.
24
Parvizi, Y. and Nabati, A. (2004). Effect of irrigation intervals and manure on water use efficiency and quantitative and qualitative yield of corn. Research and construction. No. 63. 21-29.
25
Richards, R.A., Rebtzke, G.J., Condon, A.G. and van Herwaarden, A. F. (2002). Breeding opportunities for increasing the efficiency of water use and crop yield in temperate cereals. Australian Journal of Crop Science, 42: 111-121.
26
Shoaa Hossaini, S.M., Babaeeyan, N. and Farsi, M. (2001). Effect of drought stress on yield and its components in some corn hybrids using causality analysis. Master's thesis, Faculty of Agricultural Sciences, Mazandaran University, 117 p. (In Farsi)
27
Sing, N.P. and Sinka, S.K. (1997). Water use efficiency in crop production. In: Water requirement and irrigation management of crops in India, ed. Indian Agricultural Research Institute. New Delhi .Water technology center: 289-335.
28
Song, Y., Qu, C., Birch, S., Doherty, A. and Hanan, J. (2010). Analysis and modelling of the effects of water stress on maize growth and yield in dryland conditions. Plant Production Science. 13 (2): 199-208.
29
Westgate, M.E. (1994). Water statues and development of the maize endosperm and embryo during drought stress. Crop science 34:76-83.
30
Zarabi, M., Alahdadi, I., Akbari, G. A. and Akbari, G. A. (2011). A study on the effects of different biofertilizer combinations on yield, its componentsand growth indices of corn (Zea mays L.) under drought stress condition. African Journal of Agricultural Research. 6 (3): 681-685.
31
ORIGINAL_ARTICLE
Estimation of Hydrodynamic Infiltration Coefficients Using Optimization of SCS & Horton Equations
Determination of infiltration equations coefficients with proper accuracy is one of the important issues in irrigation planning. For determination of these coefficients, double-ring test method is usually used which only involves the point and hydrostatic dimension of infiltration. In this research, a parabolic shape furrow was used for simulation of an irrigation furrow with 50 m length, 12 cm depth, and 0.20 m/m bed slope. Three experiments were performed with lengths of 4.7, 20 and 40 m, and inflow of 0.6±0.02 lit/s with three replicates. For each length, a test with the minimum measurement error was selected. To determine the infiltration equations coefficients, input and output hydrographs were measured using flow measurement flume and the output hydrographs were routed by Muskingum-Cunje, Zero-inertia and kinematic wave methods. Finally, the infiltration discharge values were obtained by considering the SCS and Horton infiltration equations and the average flow area in the proposed furrows. Computational hydrographs were obtained from the difference between routed output hydrographs and infiltration discharges. Finally, the objective function was derived using the least square method (LSM) for observational and computational output hydrographs. The results indicated that the mean value of the relative error between the observed and optimized output hydrographs of the proposed method is less than 5 percent. By increasing the length interval, the amounts of infiltration discharges decrease due to the reduction of static head water. The efficiency of the model for all lengths was more than 90 percent based on the Nash-Sutcliff criterion which indicates that the simultaneous use of the Horton equation and the zero-inertia method provides the best results.
https://ijswr.ut.ac.ir/article_70125_fe99140abf2dc3bdfa281e1120f4b60a.pdf
2019-03-21
201
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10.22059/ijswr.2018.256348.667893
furrow irrigation"
" infiltration"
" optimization"
" flood routing
hadi
roshani
hadiroshani.6236@yahoo.com
1
MSc Student of Water Science and Engineering Dept., Imam Khomeini International University, Qazvin, Iran.
AUTHOR
majid
heydari
mheydari_ir@yahoo.com
2
Assistant Professor of Water Science and Engineering Dept., Bualisina University, Hamadan, Iran.
LEAD_AUTHOR
abbas
sotoodehnia
sotoodehnia@eng.ikiu.ac.ir
3
Associate Professor of Water Science and Engineering Dept., Imam Khomeini International University, Qazvin, Iran.
AUTHOR
Abasizadeh, M., Mahdavi, M. and Salajghe, A. (2010). Evaluation of hydrologic routing methods in DEZ river. Natural geographic journal. (In Farsi)
1
Abbasi, F., Simunek, J., van Genuchten, M. T., Feyen, J., Adamsen, F. J., Hunsaker, D. J., Strelkoff, T. S. and Shouse, P. (2003). Overland water flow and solute transport: model development and field-data analysis. Irrigation and Drainage Engineering journal. 129(2), 71-81. (In Farsi)
2
Alizadeh, A. (2002). Applied hydrology. RAZAVI publication. (In Farsi)
3
Allen, JB. And Brand, HJ. (1968). How cracks and initial moisture content affect infiltration in Sharkey clay. Agric Engin (49), 589-594.
4
Bahrami, M., Boroomand Nasab, S. and Naseri, A. (2009). Comparison of Muskingum – Cunge model with irrigation hydraulic models in estimation of furrow irrigation advance phase. Iranian Journal of lrrigation and drainage. 2(3), 40-49. (In Farsi)
5
Chaudhry, M.H. (2008). Open_Channel Flow. New York: Springer Science.
6
Chow, V. T. (1959). Open Channel Hydraulics. McGraw-Hill. New York.
7
Ebrahimian, H., and Liaghat, A. (2011). Field evaluation of various mathematical models for furrow and border irrigation systems. Soil and Water Research, 6(2), 91-101. (In Farsi)
8
Habibikhaveh, M., Montazer, AA. and Behbahani, MR. (2008). Sensitivity analysis of infiltration parameters with different estimation methods in furrow irrigation. Second seminar on improvement of surface irrigation systems, Karaj, Iran. (In Farsi)
9
Haverkamp, R.‚ Rendon, L. and Vachaud, G. (1987). Infiltration equations and their applicability for predictive use. In: Fok Y. (ed). International Conference on Infiltration Development and Application, 6-8 January, Honolulu, Hawaii, USA, pp. 142- 152.
10
Hillel, D. (1988). Environmental soil physics Acad. Press. UK.
11
Mahmoodian shoushtari, M. (2008). Open channel flow principles. chamran university publication. (In Farsi)
12
Moradi, H., Vafakhah, M. and Akbari, A. (2007). Evaluation of routing by Muskingum and Muskingum-cunge method in LIGHVAN River. Journal of Sciences and Technology of Agriculture and Natural Resources. 41(b). (In Farsi)
13
Nasseri, A., Neyshabouri, MR., Fakherifard, A., Mogaddam, M. and Nazem, AH. (2004). Fieldmeasured furrow infiltration function. Turk. J Agric 28, 93-99 (In Farsi)
14
Neshat, A. and Parehkar, M. (2007). The comparison of methods for determining the vertical infiltration rate. J. Agric. Sci. Natur. Resour. 14(3). (In Farsi)
15
Ojaghloo, H., Ghobadinia, M., Majdzadeh, B., Sohrabi, T. and Abbasi, F. (2008). Estimation of infiltration parameters for flow simulation in furrow irrigation. Second seminar on improvement of surface irrigation systems, Karaj, Iran. (In Farsi)
16
Rawls, WJ. (1993). Infiltration and soil water movement. In: Maidment D.R. (ed). Handbook of Hydrology. McGraw-Hill, New York, USA, Chapter 5, pp. 1/5- 51/5.
17
Shayannejad, M., Akbari, N. and Honarbakhsh, A. (2014). Comparing of linear Muskingum method with HEC-RAS model for flood routing in rivers. Journal of ecology, 2. (In Farsi)
18
Salahzadeh, H. (2010). Principles of geotechnical engineering, 2nd ed. Iran University of science and technology publishing center. (In Farsi)
19
U.S. Department of the Interior Bureau of Reclamation. (2001). water measurement manual, Washington DC: U.S. Government printing Office.
20
ORIGINAL_ARTICLE
Application of Structure from Motion (SFM) Method to Determine the Bed Surface Particles Sizes in Gravel Bed Rivers
Accurate and precise characterization of the natural rough bed has great importance. Without any doubt, there is not any example of natural flow or flow near hydraulic structures with no roughness on their surrounding walls Although the traditional bed roughness characterization approach is based on the grain size distribution curve, in the recent approach, roughness determination is based on the point-to-point height measurement of the bed, which cannot be easily determined. Therefore, despite of many studies and various methods and tools which have been developed for determining the digital model elevation and statistical properties of such substrates, there is a lack of simple and low-cost method with high accuracy. In the present study, the capabilities of a close-range photogrammetric method called the Structure from Motion (SFM) have been investigated for determining the bed surface particles sizes. For verification, the digital elevation of various objects with regular geometric shapes, such as spheres and cubes, was determined using SFM method and compared with the theoretical values derived from their mathematical equation. The results of the model derived by the structure from motion method for irregular geometric shapes was performed using a laser scanner and a caliper which indicated the high precision of the simple and low-cost SFM method. The results showed that the SFM method could accurately developed a digital model of an artificial gravel and sand bed (absolute error of 0.19 to 1 mm). Furthermore, this method was applied in the real environment; Kordan River bed and the size distribution of the point to point bed particles were calculated based on the cloud points of the developed digital model, indicating the capability of the method for determining the natural roughness of the river bed based on the concepts of statistical methods.
https://ijswr.ut.ac.ir/article_70126_77fd44d8b9945e86489fc4c183e19191.pdf
2019-03-21
215
230
10.22059/ijswr.2018.254906.667879
Close-Range Photogrammetry
Digital Elevation Model
Laser Scanner
Rough bed
Structure from Motion
Parisa
Zamani
parisa.zamani916@gmail.com
1
Graduated M.Sc., Water Eng. Dept., Faculty of Agriculture and Natural Resources, Imam Khomeini International University (IKIU), Qazvin, Iran.
AUTHOR
Seyed Hossein
Mohajeri
hossein.mohajeri@gmail.com
2
Assistant Professor, Civil Eng. Dept., Faculty of Eng. and Tech., Kharazmi University, Karaj, Iran.
AUTHOR
Amir
Samadi
samadi_59@yahoo.com
3
Assistant Professor, Water Eng. Dept., Faculty of Agriculture and Natural Resources, Imam Khomeini International University (IKIU), Qazvin, Iran.
LEAD_AUTHOR
Aberle, J., and Nikora, V. (2006). Statistical properties of armored gravel bed surfaces. Water Resources Research. 42, W11414.
1
Afshin, Y. (2004). Iran Rivers, Vols. 1-2, Ministry of Energy, Jamab Consulting Engineers Company, Tehran.
2
AgiSoft. (2012). AgiSoft PhotoScan User Manual: Professional Edition. Version0.9.0. Retrieved June 15, 2012 from: http://www.agisoft.ru/products/photoscan/professional/.
3
Bathurst, J.C. (1985). Theoretical aspects of flow resistance, in Gravel-Bed Rivers, edited by R.D. Hey, J.C. Bathurst, and C.R. Thorne, pp. 83-108, John Wiley, New York, 1985.
4
Bomminayun, S. and Stoesser, T. (2011). Turbulence Statistics in an Open-Channel Flow over a Rough Bed, J. Hydraul. Eng., 137(11), 1347-1358.
5
Bray, D.I. (1985). Flow resistance in gravel-bed rivers, in Gravel-Bed Rivers, edited by R.D. Hey, J.C. Bathurst, and C.R. Thorne, pp. 109-132, John Wiley, New York.
6
Carbonneau, P., Fonstad, M.A., Marcus, W.A. and Dugdale, S.J. (2012). Making riverscapes real. Geomorphology, 137, 74–86. DOI: 10.1016/j.geomorph.2010.09.03033.
7
Dietrich, J.T., 2014. Applications of structure-from-motion photogrammetry to fluvial geomorphology, PhD Thesis, Department of Geography, University of Oregon, USA.
8
Dugdale, S.J., Carbonneau, P.E., Campbell, D. (2010). Aerial photosieving of exposed gravel bars for the rapid calibration of airborne grain size maps. Earth Surface Processes and Landforms, 35, 627–639.
9
Esmaeelpour, M. (2009). Evaluation of a method for justifying video-based video frames for 3D image reconstruction, M.Sc. Thesis, Department of Surveying Engineering, University of Tehran. (In Farsi)
10
Fausch, K.D., Torgersen, C.E., Baxter, C.V., Li, H.W. (2002). Landscapes to Riverscapes: Bridging the Gap between Research and Conservation of Stream Fishes. BioScience, 52, 483–498.
11
Fonstad, M.A. and Marcus, W.A. (2010). High resolution, basin extent observations and implications for understanding river form and process. Earth Surface Processes and Landforms, 35, 680–698.
12
Fonstad, M.A., Dietrich, J.T., Courville, B.C., Jensen, J.L., Carbonneau, P.E. (2013). Topographic structure from motion: a new development in photogrammetric measurement, Earth Surface Processes and Landforms, 38(4), 421-430.
13
Furbish, D.J. (1987). Conditions for geometric similarity of coarse streambed roughness, Math. Geol., 19(4), 291-307.
14
Griffiths, G.A. (1981). Flow resistance in coarse gravel-bed rivers, J. Hydraul. Div., Am. Soc. Civ. Eng., 107(HY7), 899-918.
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Hey, R.D. (1979). Flow resistancein gravel-bed rivers, J. Hydraul. Div., Am. Soc. Civ. Eng., 105, 365-379.
16
James, M.R., and Robson, S. (2012). Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application, Journal of Geophysical Research, Earth Surface, 117, F03017.
17
Javernick, L., Brasington, J., Caruso, B.S. (2014). Modeling the topography of shallow braided rivers using Structure-from-Motion photogrammetry, Geomorphology, 213, 166–182.
18
Kirchner, J.W., Dietrich, W.E., Iseya, F. and Ikeda, H. (1990). The variability of criticals hear stress friction angle and grain protrusion in water worked sediments, Sedimentology, 37, 647- 672.
19
Micheletti, N., Chandler, J.H., Lane, S.N. (2014). Structure from Motion (SFM) Photogrammetry, BSG, ISSN 2047-0371.
20
Mohajeri S.H. (2014a). Hydrodynamics of gravel bed flows (Implications in colmation). PhD Thesis, Department of Civil, Mechanics and Environmental Engineering, University of Trento and School of Geography, Queen Mary University of London.
21
Mohajeri, S.H. (2014b). An Investigation on Gravel-Bed Roughness Characterization, Journal of Hydraulics, 9(4), 73-86. (In Farsi)
22
Mohajeri, S.H., Grizzi, S., Righetti, M., Romano, G.P., and Nikora, V. (2015). The structure of gravel-bed flow with intermediate submergence: A laboratory study. Water Resources Research, 51(11), 9232-9255.
23
Nikora, V.I., Goring, D.G. and Biggs, B.F. (1998). On gravel-bed roughness characterization. Water Resources Research, 34, 517-527.
24
Robert, A. (1988). Statistical properties of sediment bed profiles in alluvial channels, Math. Geol., 20(3), 205-225.
25
Robert, A. (1990). Boundary roughness in coarse-grained channels, Prog. Phys. Geogr., 14(1), 42-70.
26
Shapiro, L. and Stockman, G. (2001). Computer Vision. Prentice Hall. ISBN 0-13-030796-3.
27
Ullman, S. (1979). The Interpretation of Structure from Motion. The royal society. Available from: http://rspb.royalsocietypublishing.org/content/203/1153/405
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Westoby, M.J., Brasington, J., Glasser N.F., Hambrey, M.J., and Reynolds, J.M. (2012). ‘Structure-from-Motion’ photogrammetry: A low-cost, effective tool for geoscience applications, Geomorphology, 179, 300-314.
29
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31
ORIGINAL_ARTICLE
The Effect of Different Pistachio Wastes Biochar Application on Some Fertility Properties of a Loam Soil
In this research, the short-term beneficial effect of using different pistachio wastes biochars on improving some fertility properties of a loam soil was investigated. Therefore, the effects of two factors 1) types of amendments added to the soil, including biochars of pistachio mildew (PM), pistachio hard skin (PHS) and wood of 20-year pistachio trees (W) papered at 600o C (with amount of %5 by wt), and 2) time of incubation (1, 2, 3, 4, 5 months), were investigated on pH, electrical conductivity, soluble potassium, nitrate and availability of iron, copper, manganese and zinc. This experiment was performed as factorial based on the completely randomized design with three replicates. The results of this study showed that the application of biochars and different incubation times does not have a significant effect on soil pH. But, the threated soils at all incubation times showed a significant increase in electrical conductivity and organic carbon as compared to the control treatment. Addition of biochars and incubation time increased significantly potassium content of the soil solution, so that the treated soils had an increase of approximately two times solution potassium as compared to the control. Application of biochars to the soil caused an increase in nitrate retention and a decrease in nitrate solution as compared to the control sample. Biochars application led to a significant increase in iron content and irregular increase in zinc, copper and manganese. The availability of these elements in the soil decreased by time due to reduction of biochar decomposition and transformation of those elements from available into less available forms.
https://ijswr.ut.ac.ir/article_70127_26fbe30aba450a981afa8423c8efee61.pdf
2019-03-21
231
246
10.22059/ijswr.2018.244637.667780
Biochar
Pistachio wastes
loam soil
Soil fertility
ABOLFAZL
KHADEMI JOLGENEJAD
a.khademianar@gmail.com
1
M.Sc. Student, Department of Soil Science, Agriculture Faculty, Shahid Bahonar University of Kerman. Iran.
LEAD_AUTHOR
majid
fekri
mjdfekri@yahoo.com
2
Professor, Department of Soil Science, Agriculture Faculty, Shahid Bahonar University of Kerman. Iran.
AUTHOR
majid
mahmoodabadi
mmahmoodabadi@yahoo.com
3
Associate Professor, Department of Soil Science, Agriculture Faculty, Shahid Bahonar University of Kerman. Iran
AUTHOR
Ahmad, M., Rajapaksha, A. U., Lim, J. E., Zhang, M., Bolan, N., Mohan, D., and Ok, Y. S. (2014). Biochar as a sorbent for contaminant management in soil and water: a review. Chemosphere, 99, 19-33.
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71
ORIGINAL_ARTICLE
Evaluation of Moving Average Pre-processing Approach to Improve the Efficiency of Support Vector Regression Model for Inflow Prediction
Accurate hydrologicalforecasting is a main tool for the water resources planning. In this paper, the inflow rates to Bakhtiari and Rudbar Dams in Lorestan province – IRAN, were forecasted using support vector regression (SVR), Multiple Linear Regression (MLR) and Autoregressive Moving Average (ARMA) models. In order to pre-process the input data for the above mentioned models, the moving average approach was used. Furthermore, Nash-Sutcliffe Efficiency (NSE), Root Mean Square Error (RMSE), correlation coefficient (R) and Taylor diagram were used to evaluate the efficiency of the models. The results showed that the moving average pre-processing approach improved the performance of the above mentioned models dramatically. For instance, the values of Nash-Sutcliff correspond to SVR hybrid model in forecasting inflow rate to Bakhtiari and Rudbar-Lorestan dams with moving average pre-processing were improved by 13.4% and 6.6%, respectively, as compared to those in the SVR model without pre-processing.
https://ijswr.ut.ac.ir/article_70128_897d99a34732cde3b3c93ad8c3a6e7cf.pdf
2019-03-21
247
258
10.22059/ijswr.2018.250803.667838
Forecasting Time Series
Support Vector Regression
Moving Average
Mahdi
Abbasi
m.abbasi@ut.ac.ir
1
MSc in Water Resources Engineering, Department of Irrigation & Reclamation Engineering, University of Tehran, Karaj, Iran
AUTHOR
Shahab
Araghinejad
araghinejad@ut.ac.ir
2
Associate Professor, Department of Irrigation and Reclamation Engineering, University of Tehran, Karaj, Iran
LEAD_AUTHOR
Kumars
Ebrahimi
ebrahimik@ut.ac.ir
3
Professor, Department of Irrigation and Reclamation Engineering, University of Tehran, Karaj, Iran
AUTHOR
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1
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7
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25