ORIGINAL_ARTICLE
Using compression curve characteristics to estimate water content by the van Genuchten model
van Genuchten model is a well-known and most widely used model for the estimation of soil water retention curve. The parameters of this model have been estimated by different estimators such as soil texture. But so far the properties of compaction curve have not been used to estimate the parameters of van Genuchten model. Compaction curve is one of the soil mechanical properties and shows the relationship between the stress-strain with the elasticity modulus. Soil water retention and compaction curves have similarities. Measurement of soil water retention curve is time-consuming and costly while the measurement of compaction curve is cheap and needs less time. For this study, 150 soil samples (distributed and undistributed) were collected from five provinces of Iran. Soil water retention was measured at 12 suctions and the compaction curve was obtained using uniaxial apparatus in the confined sample. In this research, 6 levels of estimators including compaction characteristics and equations coefficients were used to estimate water content. In general, results showed that the use of compaction curve was useful to estimate the soil water retention curve. The second and sixth levels with the estimators of Pc-Cc-Cs and parameters of stress-strain model (indirectly), respectively along with basic soil properties had higher estimation accuracy compared to other estimator levels. The reason for the excellence of these estimators can be due to their correlation with van Genuchten model parameters and mechanical concept of estimators. Moreover, the similarity between the two curves was one of the reasons for the appropriate estimation of soil water retention curve.
https://ijswr.ut.ac.ir/article_58328_3a4846b3803cc1aecb4a6883f4d318c6.pdf
2016-07-22
217
228
10.22059/ijswr.2016.58328
Precompression Stress
model
Soil Water Retention Curve
Compression Curve
Eisa
Ebrahimi
ebrahimi.soilphysic@yahoo.com
1
Bu Ali Sina Hamedan University
LEAD_AUTHOR
Hosein
Bayat
h.bayat@basu.ac.ir
2
استادیار گروه خاکشناسی دانشکده کشاورزی دانشگاه بو علی سینا همدان
AUTHOR
Saeedeh
sadeghi
sadeghi.saeedeh2013@gmail.com
3
MSc in physics and soil conservation Gorgan University of Agricultural Sciences and Natural
AUTHOR
mahbobeh
fallah
mah.fallah@yahoo.com
4
دانش آموخته کارشناسی ارشد فیزیک و حفاظت خاک دانشگاه گیلان
AUTHOR
Mohammad
Jorreh
jorreh2010@yahoo.com
5
MSc in soil physics and conservation at Bu Ali Sina Hamedan University
AUTHOR
Mohammad
zanganeh
mkz1348@gmail.com
6
MSc in engineering water at Bu Ali Sina Hamedan University
AUTHOR
Akaike, H., 1974. A new look at the statistical model identification. IEEE Trans Automa Contr. 19:716-723.
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Patil, N. G., Pal, D. K., Mandal, C., and Mandal, D. K. (2012). Soil water retention characteristics of vertisoils and pedotransfer functions based on near neighbor and neural networks approach to estimateAWC. Journal of arrigation and drainage engineering, 138(2), 1-10.
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64
ORIGINAL_ARTICLE
Evaluation of temporal variation of soil water infiltration coefficients in furrow irrigation
Recognition of soil water infiltration process is essential for improving irrigation efficiency, decreasing water losses and management of surface runoff. The aim of this research was to evaluate temporal variation of the Kostiakove-Louise infiltration coefficient parameters during a corn growing season. In this research, 16 irrigation events for 8 large scale furrow experiments were analyzed by the volume balance method for evaluating the Kostiakove-Louise infiltration parameters. The length of the experimental furrows used for this study were 120 meters. The results indicated that temporal variation of the Kostiakove-Lewise parameters during the growing season were not meaningful and possible error was less than 5%.
https://ijswr.ut.ac.ir/article_58329_59d6e4d8fe19791fd9b33e723bd28f61.pdf
2016-07-22
229
236
10.22059/ijswr.2016.58329
Corn
Infiltration
Kostiakove-Louise
Volume balance
Ghazaleh
Ziaei
rrttgh@gmail.com
1
کارشناس ارشد آبیاری و زهکشی
AUTHOR
Fariborz
Abbasi
fariborzabbasi@ymail.com
2
موسسه تحقیقات فنی و مهندسی کشاورزی
LEAD_AUTHOR
Hosein
Babazadeh
h_babazadeh@srbiau.ac.ir
3
دانشگاه آزاد اسلامی واحد علوم و تحقیقات تهران
AUTHOR
Fereydoon
Kaveh
fhnkaveh@yahoo.com
4
دانشگاه آزاد اسلامی واحد علوم و تحقیقات تهران
AUTHOR
Abbasi, F., 2013. Principle of Flow in Surface Irrigation. Iranian National Committee on Irrigation and Drainage (IRNCID). IRAN. (in Farsi).
1
Austin, N. and. Prendergast J.B., 1997.Use of kinematic wave theory in model irrigation on cracking soil. Irrigation Science, 18(1):1-10.
2
Benham, B.L., Reddel, D.L. and Marek, T.H., 2000.Performance of three infiltration model under surge irrigation. Irrigation Science, 20:34-43.
3
Ebrahimian, H., Ghanbarian-Alavijeh, B., Abbasi, F. and Hoorfar, H., 2010.Two-point method for estimating infiltration parameters in furrow and border irrigation and comparison with other methods. J. Water and Soil, 24(4):690-698. (in Farsi).
4
Elliott, R.L., Walker, W.R. and Skogerboe, G.V. 1982. Field evaluation of furrow infiltration and advance functions. Trans. ASAE, 25(2):396-400.
5
Elliott, R.L., Walker, W.R. and Skogerboe, G.V. 1983. Infiltration parameters from furrow irrigation advance data. Trans. ASAE, 26(6):1726-1731.
6
Emdad, M.M., Shojaeefar, M. and Fardad, H., 2008. Time affection of infiltration in furrow irrigation management. J. Soil Research, 24(2).(in Farsi).
7
Gates, K. and Clyma, W., 1984. Designing furrow irrigation system for improved seasonal performance. Trans. ASAE, 26(6):1817-1824.
8
Green, W.A. and Ampt, G.A., 1911. Studies on soil physics I. the flow of air and water through soils. J. Agric Sci., 4:1-24.
9
Horton R.E., 1940. An approach towards a physical interpretation of infiltration capacity. Soil Sci. Soc. Am. Proc., 5:399-417.
10
Jaynes, D.B. and Hunsaker, D.J., 1989. Spatial and temporal variability of water content and infiltration on a flood irrigated field. Trans ASAE, 32:1229-1238.
11
Karami, A., Homaii, M., Baybordi, M. and Mahmodian Shooshtari, M. 2013.Quantification water infiltration in soil parameters by scaling. J. Water Research, 6(11): 65-73. (in Farsi).
12
Kostiakov, A.V., 1932. On dynamic of the coefficient of water percolation in soils and on the necessity for studying it from dynamics point of view for purposes of a melioration. Transactions of the Sixth Commission of International Society of Soil Science, Part A, 17-21.
13
Machiwal, D., Madan, K.J. and Mal, B.C., 2006. Modeling infiltration and quantifying spatial soil variability in wasteland of Khoragpur, India. BioSystem Engineering, 95(4): 569-582.
14
Mcclymont, D. and Raine, R., 1996. The predication of furrow irrigation performance using the surface irrigation model SIRMON. Australian Solutions, Adelaide Convention and Exhibition Centre South Australia, 14-16 May 1996: 1-10.
15
Medina, J. and Martin, D., 1998. Infiltration model for furrow irrigation. J. Irrig. Drain. Eng., 124(2): 73-80.
16
Mezencv, V.J., 1984. Theory of formation of the surface runoff. Meteorologia Igridrologia, 3:33-46.
17
Michael, A.M., 1982. Irrigation: Theory and Practice. Orient Longman, New Delhi.
18
Milhole, J.C., Pirol, M. and Benali, M., 1999.A furrow irrigation model to improve irrigation practices in the Ghrab valley of Marocco. Agric. Water Manage., 42(1):65-80.
19
Philip, J.R., 1957. The theory of infiltration 4.Sorptivity and algebraic infiltration equations. Soil Sci., 84:257-264.
20
Playán, E., Rodriguez, J. A., Garcia-Navarro, P. 2004. Simulation model for level furrows. I: Analysis of field experiments. J. Irrig. Drain. Eng., 130 (2), 106–112.
21
Rasoulzadeh, A. and Sepaskhah, A.R., 2003. Scaled infiltration equation for furrow irrigation. BioSystem Eng., 86:375-383.
22
Raine, R., 1999. Research, development and extention in irrigation. National Center for Engineering in Agriculture. NCEA Publication, 179743/2:1-12.
23
Rodriguez, J.A. 2003. Estimation of advance and infiltration equations in furrow irrigation for untested discharges. Agric. Water Manage., 60, 227–239.
24
Tabatabai, S.H., Neyshabouri, M.R., Fardad, H. and Liaghat, A.M., 2004. Evaluation of time and spatial variability of cross sections coefficient in furrow irrigation. J. Agriculture Science and Natural Resource of Gorgan. 11(2), 171-179. (in Farsi).
25
Zapata, N and Playan, E., 2000. Elevation and infiltration in a level basin I. Irrig. Sci., 19 (4), 155-164.
26
ORIGINAL_ARTICLE
Investigation of Qazvin Marshland Interceptor Drain Effects on Water Table Using Seep/w Model
The groundwater level dropping has many problems. One of the most important problems is saline groundwater advancing in the upper area of the plains. Also, decreasing of saline effluent from the groundwater is another problem that occurs. The interceptor drain is a method for solving these problems. In this study, effect of Qazvin marshland interceptor drain is simulated. To monitor the effectiveness of these drains, wells of 99 loops were excavated in 9 sections perpendicular to the drain (A to I). Seven wells per section were excavated in the upstream at 10, 25, 50, 100, 250, 500 and 1000 meters distances from the drain and 4 wells in the downstream at 10, 25, 50 and 250 m. The wells water level was measured in once a month and a water sample was taken from each. Chemical analysis of the samples, and chemical changes in ground water drainage were determined. The condition of affected by drainage was simulated using the software package Geostudio. Model, the hydraulic conditions (model Seep/ w) is the model. The numerical model used in section B was calibrated using observations of August 2010 and the data were collected four months after it was verified. In the calibration phase, Values of modeling efficiency and coefficient of determination were 0.91 and 0.97, respectively. These values were 0.87 and 0.91 in validation phase, respectively. These values of validation show the good efficiency of the model in groundwater level prediction.
https://ijswr.ut.ac.ir/article_58330_cf82d88538796fcf4e736509e8013a69.pdf
2016-07-22
237
245
10.22059/ijswr.2016.58330
Saline groundwater advancing
Geostudio
Hydraulic conductivity
abbas
Sotoodehnia
sotoodehnia@eng.ikiu.ac.ir
1
استاد یار و مدیر گروه مهندسی آب دانشگاه بین المللی امام خمینی (ره)
LEAD_AUTHOR
Mohadese
Jafarei
m_jafari363@yahoo.com
2
Imam Khomeini International University, Water Engineering Dep.
AUTHOR
Akram, M. and Sotoodehnia, A. (2011). “Monitoring plan of interceptor drain in Qazvin”. Company Reports, Kamab Pars Saman Abran, Ministry of Agricultural. (In Farsi)
1
Azari, A., Liaghat, Z. and Darbandi, S. (2002). “Drainage, quantity and quality of the return flow”. Drainage Working Group, publisher of Iranian National Committee on Irrigation and Drainage, first published. (In Farsi)
2
Carluer, N. and Marsily, G. D. (2004). “Assessment and modeling of the influence of man-made networks on the hydrology of a small watershed: implications for fast flow components, water quality and landscape management”. Journal of Hydrology, 285, 76–95.
3
Dykes, A. P., Gunn, J. and Convery, K. J. (2008) “Landslides in blanket peat on Cuilcagh Mountain, northwest Ireland”, Geomorphology, 102, 325–340.
4
Honar. M. R., Shamsnia, S. A. and Gholami, A. (2011). “Evaluation of water flow and infiltration using HYDRUS model in sprinkler irrigation system”. 2nd International Conference on Environmental Engineering and Applications IPCBEE. IACSIT Press, Singapore.
5
Iranian National Committee on Irrigation and Drainage Development Committee Newsletter, (2008). Iranian National Committee on Irrigation and Drainage, No. 71.
6
Lashgaripur, Gh. R., Kazemi Golian, R. and Mirshahi, M. (2007). “Effect of groundwater level decline in the quality of the plain frame - Torbatjam”. Proceedings of the First International Congress of Applied Geology, May (2007), Mashhad. (in Farsi)
7
Lashgaripur, Gh. R., Gafuri, M., Babai. M. and Salehi moteahed, F., (2009). “Effect of indiscriminate harvesting of the quality and quantity of Sabzevar Aquifer using Arcview GIS software and Plotchem” Proceedings of the Second National Conference on Drought Management Strategies, May 2009, Isfahan, Iran (In Farsi).
8
Moriasi, D. N, Fouss. J.L, Bengtson. R.L, 2007, “Modeling the Effects of Deep Chiseling with DRAINMOD for Alluvial Soils”. Transactions of the ASABE, 50(2), 543-556.
9
Ronkanen, A. K, Klove. B, 2008, “Hydraulics and flow modeling of water treatment wetlands constructed on peatlands in Northern Finland”. Water Search. 42, 3826–3836.
10
ORIGINAL_ARTICLE
Implementation of Shannon Entropy Method to Determine Areas Suitable for Artificial ground water recharge Case Study: Sarkhoon Plain
Artificial recharge of groundwater plays a pivotal role in the sustainable management of these resources. Sarkhoon plain in Hormozgan was carried out using geographic information system and combining it with the Shannon entropy and a pair-wise comparison test. For this purpose, 9 affecting elements of, water quality, water depth, permeability coefficient, thickness of alluvium, land use, transfer capability, land morphology and drainage density were selected and prepared. Then using entropy method and pair-wise comparisons, the weight of each standard and the classes of each layer were calculated. Next, the areas with constraint for flood spreading are removed and finally the entire area was divided and zoned into four classes using GIS analytical functions and Jencks algorithm. Results showed that drainage density factor weighing 0.211 is the most important factor for locating flood spreading in Sorkhun plain. Areas suited for flood spreading are frequently located at the morphological units of alluvial fan in the north part of the plain, with slopes of less than three percent, and allocated approximately 17.70% of the plain. Evaluate the results by comparing the successful implementation projects in the region was 78 percent overlap model can lead to weight each criterion in considering the impact of the uncertainty, Which can enhance the accuracy of the model output.
https://ijswr.ut.ac.ir/article_58331_33072dca72fb2e295749302afca29c49.pdf
2016-07-22
247
258
10.22059/ijswr.2016.58331
water resources
Floodwater
drainage density
interpolation
Hormozgan Province
mohammad
kamangar
mohamad.kamangar63@gmail.com
1
سنندج
LEAD_AUTHOR
Firoozeh
Ghaderi
arshad93.gh@gmail.com
2
دانشگاه علمی کاربردی
AUTHOR
Peymani
Karami
pymank@yahoo.com
3
کارشناس ارشد، دانشکده منابع طبیعی، دانشگاه هرمزگان
AUTHOR
Adamowski, J., & Chan, H. F. (2011). A wavelet neural network conjunction model for groundwater level forecasting. Journal of Hydrology, 407(1–4), 28-40.
1
Ale sheikh, A. A., Soltani, M. J., Nouri, N., Khalilzadeh, M., (2008). Land assessment for flood spreading site selection using geospatial information system. International Journal of Environmental Science & Technology, 5(4): 455-462
2
ASCE STANDARD, (2001). Standard Guidelines for Artificial Recharge of Ground Water, Environmental and Water Resource Institute, American Society of Civil Engineers, ASCE standard, EWRI/ ASCE 106, 34-10.[A1]
3
Chabok Boldaji, M., Hassanzadeh Nofoti, M., Ibrahim Khosfi, Z. (2011). Suitable Areas Selection Using AHP (Case study watershed Ashgabat Tabas), Journal of Science and Engineering watershed, Fourth year, No, 13, 127-14.
4
Chowdhury, A., Chowdhury, Jha, A. M. (2010). Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS, GIS and MCDM techniques. Environmental Earth Sciences, 59(6): 1209-1222.
5
Faraji Sabokbar, h., et al. [A2] (2012). Identification of suitable areas for artificial groundwater recharge using integrated ANP and pair wise comparison methods in GIS environment, (case study: Garbaygan Plain of Fasa). Geography and Environmental Planning, 44(4): 143-166. (In Farsi)
6
Ghayoumian, J., Ghermez Cheshme, B., Feiznia, S., Noroozi A. (2004). Integrating GIS and DSS for Identification of Suitable Areas for Artificial Recharge (Case study: Meimeh Basin, Isfahan, Iran), journal of science Teacher Training University, 3, 115-131.
7
Gleeson, T., Alley, M., Allen, M., Sophocleous, A., Zhou, Y., Taniguchi, M, & VanderSteen, J., (2012). Towards Sustainable Groundwater Use: Setting Long-Term Goals, Backcasting, and Managing Adaptively, Ground Water, 50(1), 19-26. doi: 10,1111/j,1745-6584,2011,00825,x
8
Khasheii [A3] sivaki, A., Ghahraman, B.Koochek zadeh, M. (2013). Comparison of artificial neural network models, ANFS and regression in the estimation of shallow Neshoba aquifer, Journal of Irrigation and Drainage, 1, 7, 10-22. (In Farsi)
9
Masomi ashkori, H. (2006) Principles of regional planning.Payam. Tehran. 250p. (In Farsi)
10
Magesh, S., Chandrasekar, N. and Soundranayagam, J. (2012). Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques, Geoscience Frontiers, 3(2), 189-196.
11
Mohanty, S., Jha, M, Kumar, A. and Sudheer, K, P. (2010). Artificial Neural Network Modeling for Groundwater Level Forecasting in a River Island of Eastern India, Water Resources Management, 24(9), 1845-1865. From: doi: 10,1007/s11269-009-9527-x
12
Pasha, E. and Mostafavi, H. (2013). Calculate the Uncertainty Interval Based on Entropy and Dempster Shafer Theory of Evidence. In: International Journal of Industrial Engineering & Production Management, August 2013, pp. 215-22. (In Farsi)
13
Portaheri, M. (2006) Application of Multi-Attribute Decision Making Methods in Geography. Samt. 232p. (In Farsi)
14
Rahman, M. A., Kasemsan M., and Nuttee, A. (2013). An integrated study of spatial multicriteria analysis and mathematical modelling for managed aquifer recharge site suitability mapping and site ranking at Northern Gaza coastal aquifer. Journal of Environmental Management, 124(0): 25-39.
15
Reddy, k. and Maharaj, V. (2009). World Heritage Site selection in sensitive areas: Andaman and Nicobar Islands. Reconstructing Indian population history, 585p.
16
Sethi, R. R., Kumar, A., Sharma, S. P., & Verma, H. C. (2010). Prediction of water table depth in a hard rock basin by using artificial neural network. International Journal of Water Resources and Environmental Engineering, 2(4), 95-102. http://www.academicjournals.org/journal/IJWREE/article-abstract/F4998981720
17
Zarcheshme, M., Kheirkhah Zarkesh, M. Davood, Gh. (2011). Combining GIS and Decision Support Systems to Determine Suitable Areas Flood Spreading (study area: Mashkyd watershed in Sistan and Baluchestan province). National Conference of Geomatics. Iran Cartography organization, 9, 87-101.
18
Yazdani Moghadam, Y. (2011). Performance multi-criteria decision method in locating spreading, Case study: Kashan Plain. Journal of Remote Sensing and GIS of Iran, 3:65-80. (In Farsi)
19
Adamowski, J., & Chan, H. F. (2011). A wavelet neural network conjunction model for groundwater level forecasting. Journal of Hydrology, 407(1–4), 28-40.
20
Ale sheikh, A. A., Soltani, M. J., Nouri, N., Khalilzadeh, M., (2008). Land assessment for flood spreading site selection using geospatial information system. International Journal of Environmental Science & Technology, 5(4): 455-462
21
ASCE STANDARD, (2001). Standard Guidelines for Artificial Recharge of Ground Water, Environmental and Water Resource Institute, American Society of Civil Engineers, ASCE standard, EWRI/ ASCE 106, 34-10.[A1]
22
Chabok Boldaji, M., Hassanzadeh Nofoti, M., Ibrahim Khosfi, Z. (2011). Suitable Areas Selection Using AHP (Case study watershed Ashgabat Tabas), Journal of Science and Engineering watershed, Fourth year, No, 13, 127-14.
23
Chowdhury, A., Chowdhury, Jha, A. M. (2010). Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS, GIS and MCDM techniques. Environmental Earth Sciences, 59(6): 1209-1222.
24
Faraji Sabokbar, h., et al. [A2] (2012). Identification of suitable areas for artificial groundwater recharge using integrated ANP and pair wise comparison methods in GIS environment, (case study: Garbaygan Plain of Fasa). Geography and Environmental Planning, 44(4): 143-166. (In Farsi)
25
Ghayoumian, J., Ghermez Cheshme, B., Feiznia, S., Noroozi A. (2004). Integrating GIS and DSS for Identification of Suitable Areas for Artificial Recharge (Case study: Meimeh Basin, Isfahan, Iran), journal of science Teacher Training University, 3, 115-131.
26
Gleeson, T., Alley, M., Allen, M., Sophocleous, A., Zhou, Y., Taniguchi, M, & VanderSteen, J., (2012). Towards Sustainable Groundwater Use: Setting Long-Term Goals, Backcasting, and Managing Adaptively, Ground Water, 50(1), 19-26. doi: 10,1111/j,1745-6584,2011,00825,x
27
Khasheii [A3] sivaki, A., Ghahraman, B.Koochek zadeh, M. (2013). Comparison of artificial neural network models, ANFS and regression in the estimation of shallow Neshoba aquifer, Journal of Irrigation and Drainage, 1, 7, 10-22. (In Farsi)
28
Masomi ashkori, H. (2006) Principles of regional planning.Payam. Tehran. 250p. (In Farsi)
29
Magesh, S., Chandrasekar, N. and Soundranayagam, J. (2012). Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques, Geoscience Frontiers, 3(2), 189-196.
30
Mohanty, S., Jha, M, Kumar, A. and Sudheer, K, P. (2010). Artificial Neural Network Modeling for Groundwater Level Forecasting in a River Island of Eastern India, Water Resources Management, 24(9), 1845-1865. From: doi: 10,1007/s11269-009-9527-x
31
Pasha, E. and Mostafavi, H. (2013). Calculate the Uncertainty Interval Based on Entropy and Dempster Shafer Theory of Evidence. In: International Journal of Industrial Engineering & Production Management, August 2013, pp. 215-22. (In Farsi)
32
Portaheri, M. (2006) Application of Multi-Attribute Decision Making Methods in Geography. Samt. 232p. (In Farsi)
33
Rahman, M. A., Kasemsan M., and Nuttee, A. (2013). An integrated study of spatial multicriteria analysis and mathematical modelling for managed aquifer recharge site suitability mapping and site ranking at Northern Gaza coastal aquifer. Journal of Environmental Management, 124(0): 25-39.
34
Reddy, k. and Maharaj, V. (2009). World Heritage Site selection in sensitive areas: Andaman and Nicobar Islands. Reconstructing Indian population history, 585p.
35
Sethi, R. R., Kumar, A., Sharma, S. P., & Verma, H. C. (2010). Prediction of water table depth in a hard rock basin by using artificial neural network. International Journal of Water Resources and Environmental Engineering, 2(4), 95-102. http://www.academicjournals.org/journal/IJWREE/article-abstract/F4998981720
36
Zarcheshme, M., Kheirkhah Zarkesh, M. Davood, Gh. (2011). Combining GIS and Decision Support Systems to Determine Suitable Areas Flood Spreading (study area: Mashkyd watershed in Sistan and Baluchestan province). National Conference of Geomatics. Iran Cartography organization, 9, 87-101.
37
Yazdani Moghadam, Y. (2011). Performance multi-criteria decision method in locating spreading, Case study: Kashan Plain. Journal of Remote Sensing and GIS of Iran, 3:65-80. (In Farsi)
38
[A1]در متن به آن اشاره نشده است.
39
[A2]در فهرست بایستی نام تمام نویسندگان آورده شود.
40
[A3]در متن به آن اشاره نشده است.
41
ORIGINAL_ARTICLE
Quality variations of cow manure biochar generated at different pyrolysis temperatures
Biochar has received great attention recently due to its potential to improve soil productivity andimmobilize contaminants and is proper as a way of carbon sequestration in soil. In this study, biocharproduced from cow manure by slow pyrolysis at different temperatures (300, 400, 500, 600, 700 ◦C) and their physicochemical properties were analysed. Experiments were conducted to examine the effectof pyrolysis temperature on the cow manure biochar and to identify the optimal pyrolysis temperaturefor converting cow manure to biochar with agricultural usage. The results showed that with anincremental increase in temperature from 300 to700 ◦C, biochar yield, total N content, and organiccarbon (OC) decreased, while pH, EC, ash content, and OC stability increased. The yield and stable OC of biochar was observed between 22.14 to 44.36 % and 35.63 to 72.36 % respectively. To produce cow manure biochar of proper for agricultural applications and a carbon sequestration, temperatures 400 and 500 ◦C are recommended respectively.
https://ijswr.ut.ac.ir/article_58332_2b65498e78e0c22a1294350a9a6f5bb2.pdf
2016-07-22
259
267
10.22059/ijswr.2016.58332
Biochar
Carbon sequestration
Biochar Yeild
Carbon Stability
Mehdi
Beheshti
m.beheshti@ut.ir
1
دانشجوی کارشناسی ارشد بیولوژی و بیوتکنولوژی خاک، بلوار امامزاده حسن، پردیس کشاورزی و منابع طبیعی
AUTHOR
Hoseinali
Alikhani
halikhan@ut.ac.ir
2
استاد گروه علوم و مهندسی خاک، پردیس کشاورزی و منابع طبیعی
LEAD_AUTHOR
Babak
Motesharezadeh
moteshare@ut.ac.ir
3
دانشیار گروه علوم و مهندسی خاک، بلوار امامزاده حسن، پردیس کشاورزی و منابع طبیعی
AUTHOR
Leila
Mohammadi
lemohammadi@ut.ac.ir
4
بلوار امامزاده حسن، پردیس کشاورزی و منابع طبیعی
AUTHOR
Abe, F., (1988). The thermochemical study of forest biomass. Bulletin of the Forestry and Forest Products Research Institute, Japan(352): 1-95.
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Cheng, C.-H., Lehmann, J., Thies, J.E., Burton, S.D. and Engelhard, M.H., (2006). Oxidation of black carbon by biotic and abiotic processes. Organic Geochemistry, 37(11): 1477-1488.
2
Claoston, N. Samsuri, A.,Husni, M.A. and Amran, M.M .,(2014). Effects of pyrolysis temperature on the physicochemical properties of empty fruit bunch and rice husk biochars. Waste Management & Research, 32(4): 331-339.
3
Dai, X. and Antal, M.J., (1999). Synthesis of a high -yield activated carbon by air gasificat ion of macadamia nut shell charcoal. Industrial & Engineering Chemistry Research, 38(9): 3386-3395.
4
Demirbaş, A., (2001). Biomass resource facilities and biomass conversion processing for fuels and chemicals. Energy conversion
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Dueck, T.A., Zuin, A. and Elderson, J., (1998). Influence of ammonia and ozone on growth and drought sensit ivity of) Pinus sylvestris(. Atmospheric Environment, 32(3): 545-550.
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Gaskin, J., Steiner, C., Harris, K., Das, K. and Bibens, B., (2008). Effect of low-temperature pyrolysis conditions on biochar for agricultural use. Trans. Asabe, 51(6): 2061-2069.
7
Glaser, B., Lehmann, J. and Zech, W., (2002). Ameliorating physical an d chemical properties of highly weathered soils in the tropics with charcoal–a review. Biology and Fertility of Soils, 35(4): 219-230.
8
Haluschak, P., (2006). Laboratory methods of soil analysis. Canada -Manitoba soil survey: 3-133.
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Horne, P.A. and Williams, P.T.,(1996). Influence of temperature on the products from the flash pyrolysis of b iomass. Fuel, 75(9): 1051-1059.
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Hossain, M.K., Strezov, V., Chan, K.Y., Ziolkowski, A. and Nelson, P.F., (2011). Influence of pyrolysis temperature on production and nutrient properties of wastewater sludge biochar. Journal of Environmental Management, 92(1): 223 -228.
11
Hwang, I., Ouchi, Y. and Matsuto, T., ( 2007). Characteristics of leachate from pyrolysis residue of sewage sludge. Chemosphere, 68(10): 1913-1919.
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James, D., Kotuby -Amacher, J., Anderson, G. and Huber, D., (1996). Phosphorus mobility in calcareous s oils under heavy manuring. Journal of environmental quality, 25(4): 770-775.
13
Joseph, S., Downie, A., M unroe, P., Crosky, A. and Lehmann, J., (2007). Biochar for carbon sequestration, reduction of greenhouse gas emissions and enhancement of soil fertility; A review of the materials science, Proceeding of the Australian Combustion Symposium.
14
Kim, K.H., Kim, J.-Y ., Cho, T.-S. and Choi, J.W., (2012). Influence of pyrolysis temperature on physicochemical properties of biochar obtained from the fast pyrolysis of pitch pine ( Pinus rigida). Bioresource technology, 118: 158-162.
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Lehmann, J. and Joseph, S.,( 2009). Biochar for environmental management: science and technology. Earthscan.
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Liang, B. et al., (2006). Black carbon increases cation exchange capacity in soils. Soil Science Society of America Journal, 70(5): 1719-1730.
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Lua, A.C., Yang, T. and Guo, J., (2004). Effects of pyrolysis conditions on the properties of activated carbons prepared from pistachio-nut shells. Journal of analytical and applied pyrolysis, 72(2): 279-287.
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Mohan, D., Pittman, C.U. and Steele, P.H., (2006). Pyrolysis of wood/biomass for bio -oil: a critical review. Energy & Fuels, 20(3): 848-889.
21
Novak, J.M. et al., (2009). Characterization of designer biochar produced at different temperatures and their effects on a loamy sand. Annals of Environ mental Science, 3(1): 2.
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Peters, J. and Basta, N., (1996). Reduction of excessive bioavailable phosphorus in soils by using municipal and industrial wastes. Journal of environmental quality, 25(6): 1236-1241.
24
Ryan, J., Estefan, G. and Rashid, A., (2007). Soil and plant analysis laboratory manual. ICARDA .
25
Schumacher, B.A., (2002). Methods for the determination of total organic c arbon (TOC) in soils and sediments. Ecological Risk Assessment Support Center: 1-23.
26
Shinogi, Y. and Kanri, Y., (2003). Pyrolysis of plant, animal and human waste: physical and chemical characterization of the pyrolytic products. Bioresource technology, 90(3): 241 -247.
27
Singh, B., Singh, B.P. and Cowie, A.L., (2010). Characterisation and evaluation of biochars for their application as a soil amendment. Soil Research, 48(7): 516-525.
28
Singh, B.P., Cowie, A.L. and Smernik, R.J., (2012). Biochar carbon stability in a clayey soil as a function of feedstock and pyrolysis temp erature. Environmental Science & Technology, 46(21): 11770-11778.
29
Sohi, S., Krull, E., Lopez-Capel, E. and Bol, R., (2010). A review of biochar and its use and function in soil. Advances in agronomy, 105: 47-82.
30
Sommer, S.G. and Dahl, P., (1999). Nutrient and carbon balance during the composting of deep litter. Journal of Agricultural Engineering Research, 74(2): 145-153.
31
Song, W. and Guo, M., (2012). Quality variations of poultry litter biochar generated at different pyrolysis temperatures. Journal of analytical and applied pyrolysis, 94: 138-145.
32
Thangalazhy-Gopakumar, S. et al., (2010). Physiochemical properties of bio -oil produced at various temperatures from pine wood using an auger reactor. Bioresource technology, 101(21): 8389 -8395.
33
Tsai, W.-T., Liu, S.-C., Chen, H.-R., Chang, Y .-M. and Tsai, Y.-L., (2012). Textural and chemical properties of swine-manure-derived biochar pertinent to its potential use as a soil amendment. Chemosphere, 89(2): 198-203.
34
Woolf, D., Amonette, J.E., Street-Perrott, F.A., Lehmann, J. and Joseph, S., (2010). Sustainable biochar to mitigate global climate change. Nature communications, 1: 56.
35
ORIGINAL_ARTICLE
Assessment of groundwater vulnerability using Modified DRASTIC, Logistic Regression and AHP-DRASTIC (Hashtgerd plain)
Parts of the Plain are different roles as pollutants velocity and reach into groundwater. Land assessment and their proper management for a variety of land uses, due to their susceptibility to transfer contaminations is essential. DRASTIC method as overlaying way has the seven influencing parameters for contamination susceptibility mapping. Due to local effects on DRASTIC model parameters, coefficients modify for the input data is required. . According to multiple studies in the Hashtgerd plain, to assess the aquifer vulnerability, modified DRASTIC method, logistic regression-DRASTIC and hierarchical analysis process DRASTIC was used. In addition to the DRASTIC input parameters, land uses were used in analysis considering its role in the production of contamination. The western part of the study area, there is an aquifer that charged from the eastern of the plain. DRASTIC model as output of the model validate with nitrates and eastern areas was excluded. In validating indicators of vulnerability, Spearman correlation, are calculated respectively 0.79, 0.84, 0.86 and 0.91 for DRASTIC, modified DRASTIC, logistic regression-DRASTIC and hierarchical analysis process –DRASTIC and Analytical Hierarchy Process has the highest correlation coefficient.
https://ijswr.ut.ac.ir/article_58333_c14d67b8a85e42d9739d96c51208d31b.pdf
2016-07-22
269
279
10.22059/ijswr.2016.58333
Groundwater vulnerability
DRASTIC
Logistic regression
Hierarchical Analysis Process
Bahram
Bakhtiare Enayat
bakhtiare@ut.ac.ir
1
university of tehran
LEAD_AUTHOR
Arash
Malekian
malekian@ut.ac.ir
2
University of Tehran faculty
AUTHOR
Ali
Salajeghe
salajegh@ut.ac.ir
3
professor of university of Tehran
AUTHOR
al-Adamat, R. A., Foster, I. D. & Baban, S. M. 2003. Groundwater vulnerability and risk mapping for the Basaltic aquifer of the Azraq basin of Jordan using GIS, Remote sensing and DRASTIC. Applied Geography, 23, 303-324.
1
Aller, L., Lehr, J. H., Petty, R. & Bennett, T. 1987. drastic: a standhrdized system to evaluate ground water pollution potential using hydrugedlugic settings.
2
Fritch, T. G., Mcknight, C. L., Yelderman Jr, J. C. & Arnold, J. G. 2000. An aquifer vulnerability assessment of the Paluxy aquifer, central Texas, USA, using GIS and a modified DRASTIC approach. Environmental Management, 25, 337-345.
3
Gemitzi, A., Petalas, C., Tsihrintzis, V. A. & Pisinaras, V. 2006. Assessment of groundwater vulnerability to pollution: a combination of GIS, fuzzy logic and decision making techniques. Environmental Geology, 49, 653-673.
4
Kalinski, R. J., Kelly, W. E., Bogardi, I., Ehrman, R. L. & Yaniamoto, P. D. 1994. Correlation between DRASTIC vulnerabilities and incidents of VOC contamination of municipal wells in Nebraska. Groundwater, 32, 31-34.
5
Panagopoulos, G., Antonakos, A. & Lambrakis, N. 2006. Optimization of the DRASTIC method for groundwater vulnerability assessment via the use of simple statistical methods and GIS. Hydrogeology Journal, 14, 894-911.
6
Rupert, M. 2001. Calibration of the DRASTIC ground water vulnerability mapping method. Groundwater, 39, 625-630.
7
Satty, T. L. 1980. The analytic hierarchy process. New York: McGraw-Hill New York.
8
Secunda, S., Collin, M. & Melloul, A. 1998. Groundwater vulnerability assessment using a composite model combining DRASTIC with extensive agricultural land use in Israel's Sharon region. Journal of Environmental Management, 54, 39-57.
9
Shahmaleki, N. K., S.M.R.Behbahani, Boani, A. M. & K.Khodai. 2013. Copparson of Logistic Regression, modified drastic and AHP-DRASTIC for groundwater vulnerability. Journal of Environmental Studies, 38, 79-92.
10
Shemshaki, A., Mohammadi, Y. & Bolourchi, M. J. 2011. Investigation on Confined Aquifer & its Role on Subsidence Occurrence in Hashtgerd Plain. Scientific Quarterly Journal, GEOSCIENCES, 20, 137-142.
11
Tim, U., Jain, D. & Liao, H. H. 1996. Interactive Modeling of Ground‐Water Vulnerability Within a Geographic Information System Environmenta. Groundwater, 34, 618-627.
12
ORIGINAL_ARTICLE
Developing Modified Conceptual Model for Plants Response to Simultaneous Salinity and Water Stress
In arid and semi-arid regions in addition to water quality, water quantity also limits agricultural production development. In this situation, plant is put under simultaneous water and salinity stress conditions. Modeling agronomical plant response to simultaneous water and salinity stress can help operation management of the country's limited water resources. The objective of this study was to model agronomical plant response to simultaneous water and salinity stress. To do so, first the important water uptake reduction functions are investigated using basil greenhouse data. The results of these investigations indicated that there are no relationships between matric potential at readily available water (h3) and osmotic potential in any mathematical models. In this paper, a new mathematical model for investigating agronomical plant response to simultaneous water and salinity stress is given by modifying conceptual model of Homaee et al., at h3 arm (branch). The results of evaluating this new model using basil observed data, indicated that model is able to simulate plant response to salinity stress, water stress, and simultaneous water and salinity stress very accurately (RMSE=8.5% and R2=0.97).
https://ijswr.ut.ac.ir/article_58334_5126f09e500f4cac19ef2069be5593bf.pdf
2016-07-22
281
292
10.22059/ijswr.2016.58334
Combined stress
Uptake reduction function
h3 arm
Hosein
Babazadeh
h_babazadeh@srbiau.ac.ir
1
دانشیار؛ دانشگاه آزاد اسلامی؛ واحد علوم وتحقیقات تهران
AUTHOR
Hamzehali
Alizadeh
hamzehalizadeh@ut.ac.ir
2
استادیار/ دانشگاه ایلام
LEAD_AUTHOR
Mahdi
Saraei Tabrizi
mahdisarai@yahoo.com
3
استادیار؛ دانشگاه آزاد اسلامی؛ واحد علوم وتحقیقات تهران؛
AUTHOR
Alizadeh H.A., Liaghat, A.M. and Noorimohamadeh M. 2009. Evaluating water uptake reduction functions under salinity and water stress conditions. Journal of Water and Soil, 23 (3):88-97.
1
Dirksen, C. and Augustijn, D. C. 1988. Root water uptake function for nonuniform pressure and osmotic potentials. Agric. Abstracts, pp. 188.
2
Dudley L.M., and Shani U. 2003. Modeling Plant Response to Drought and Salt Stress: Reformulation of the Root-Sink Term. Vadose Zone Journal, 2:751-758.
3
Ekren, S., Sonmez, C., Ozcakal, E., Kukul Kurttas, Y. S., Bayram, E. and Gurgulu, H. 2012. The effect of different irrigation water levels on yield and quality characteristics of purple basil (Ocimum basilicum L.). Agric. Water Manage. 57(2): 111-126.
4
Feddes RA, Kowalik P and Zarandy H. 1978. Simulation of Field Water Use and Crop Yield. Pudoc. Wageningen. The Netherlands Saline water in supplemental irrigation of wheat and barley under rainfed agriculture. Agric. Water Manage. 78: 122-127.
5
Homaee, M. 1999. Root water uptake under non-uniform transient salinity and water stress. PhD dissertation, Wageningen Agricultural University, The Netherlands, 173 pp.
6
Homaee, M., Dirksen, C. and Feddes, R. A. 2002a. Simulation of root water uptake. I. Non-uniform transient salinity using different macroscopic reduction functions. Agric. Water Manage. 57: 89-109.
7
Homaee, M., Feddes, R. A. and Dirksen, C. 2002b. Simulation of root water uptake. III. non-uniform transient combined salinity and water stress. Agric. Water Manage. 57: 127-144.
8
Homaee, M., Feddes, R. A. and Dirksen, C. 2002c. A macroscopic water extraction model for non-uniform transient salinity and water stress. Soil Sci. Soc. Am. J. 66: 1764-1772.
9
Huston J. L., Dudley, L. M. and Wagenet R. J. 1990. Modeling transient root zone salinity. In K.K. Tanji (ed.) Agricultural salinity assessment and mangement. ASCE manuals and reports on engineering practice No. 71. Am. Soc. Civil Eng., Irrig. Drain. Div., New York.
10
Kiani A.R., Homaee, M. and Mirlatifi, M. 2004. Evaluating yield reduction functions under salinity and water stress conditions. Soil and Water Sciences, 20 (1):73-83.
11
Loague K., and Green R.E. 1991. Statistical and graphical methods for evaluating solute transport models: overview and application. Journal of Contaminant Hydrology, 7: 51-73.
12
Maas, E. V. and Hoffman, G. J. 1977. Crop salt tolerance-current assessment. J. Irrig. and Drainage Div., ASCE, 103 (IR2): 115-134.
13
Omidbaigi R (2009). Production and processing of medicinal plants.Astan Quds Razavi publications, No. 149, 397 pp. (In Persian).
14
Richards, L. A. 1931. Capillary conduction of liquids in porous mediums. Physics. 1: 318-333.
15
Sarai Tabrizi, M., Babazadeh, H., Homaee, M., Kaveh, F. and Parsinejad, M. 2015. Simulating Basil Response to Irrigation Water Salinity. Journal of Water Research in Agriculture, 28 (4): 691-701.
16
Sepaskhah, A. R. and Yarami, N. 2010. Evaluation of macroscopic water extraction model for salinity and water stress in saffron yield production. International Journal of Plant Production,4 (3):175-186.
17
Skaggs T.H., van Genuchten M.Th., Shouse P.J., and Poss J.A. 2006. Root uptake and transpiration: From measurements and models to sustainable irrigations. Agric. Water Manage, 86, 140–179.
18
van Dam J.C., Huygen J., Wesseling J.G., Feddes R.A., Kabat P., Van Walsum P.E.V, Groenendijk P. and Van Diepen C.A. 1997. Theory of SWAP, version 2. Simulation of water flow, solute transport plant growth in the soil-water-atmosphere-plant environment. Report No.71, Dept. of Water Resources, Wageningen Agricultural Univ., 167 P.
19
van Genuchten, M. Th. 1987. A numerical model for water and solute movement in and below the root zone. Research Report. US Salinity Laboratory, Riverside, CA.
20
van Genuchten, M. Th. and Hoffman, G. J. 1984. Analysis of crop production. In: I. Shainberg and J. Shalhevet (eds), Soil salinity under irrigation. pp. 258-271. Springer-Verlag.
21
ORIGINAL_ARTICLE
Analysis of Physicochemical Properties of Sediments Trapped in Successive Check Dams
Check dams have been widely used in erosion control projects of upland areas especially in arid and semi arid regions. These structures control and reduce the amount of sediments entering main rivers by trapping the sediment load of floods. Trapped sediments by check dam systems reduce the slope of gully and provide ideal condition to starting biological measures of erosion control such as vegetation cover establishment. Physical and chemical properties of check dam sediments have major role in determining the different aspects of their behavior like water holding capacity, water infiltration rate, and controlling nutrient loss and pollutants transportation. This study aims to analyze physicochemical properties of sediments in some successive check dam systems. The study was carried out in four seasonal waterways from two different region of Urmia city, northwestern Iran. Results indicated that the average sand content of the sediments in waterways lies between 54.4 and 88.4 percent. Sediments samples with sandy and loamy sand texture were coarser than the original soils of the adjacent hillslopes. Sediments were poor in macronutrients in comparison with original soils and the enrichment ratio of the N, P, and K were 0.53, 0.66 and 0.60 respectively. In the partially filled check dam systems, as a result of selective sediment deposition, sediment characteristics change regularly and the amount of clay and macro nutrients were higher in the downstream dams than the upstream dams. Results indicated that the check dam systems are not able to trap all sediment sizes and the great amounts of particles smaller than 2 micrometer in diameter, passed through the system in the form of suspended load. Principle component analysis of sediment properties strongly suggested the importance of macronutrients with sand and silt content in characterization of sediment properties.
https://ijswr.ut.ac.ir/article_58335_37cc9efad84ce1f824bb16e6dacdf639.pdf
2016-07-22
293
306
10.22059/ijswr.2016.58335
enrichment ratio
Particle size distribution
Fredlund model
selective deposition
Farrokh
Asadzadeh
farrokhasadzadeh@gmail.com
1
عضو هیات علمی گروه مهندسی علوم خاک دانشگاه ارومیه
LEAD_AUTHOR
Abbas
Samadi
ab.samadi@yahoo.com
2
استاد گروه مهندسی علوم خاک، دانشگاه ارومیه
AUTHOR
Abbasi, A., Sedigh, R. and Ahar, M.H. (2008) Investigation of the check dams effects in controlling fine sediments. In: Proceedings of 6th National Conference on Watershed Engineering and Management. 20-21 February. University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
1
Abedini, M., Md-Said, M.A. and Ahmad, F. (2012) Effectiveness of check dam to control soil erosion in a tropical catchment (The Ulu Kinta Basin). Catena, 97, 63-70.
2
Asadi, H., Moussavi, A., Ghadiri, H. and Rose, C.W. (2011) Flow- driven soil erosion processes and the size selectivity of sediment. Journal of Hydrology, 406, 73-81.
3
Baker, J.L., Laflen, J.M. (1983) Water quality consequences of conservation tillage. Journal of Soil & Water Conservation, 38 (3), 186–193.
4
Bao, Y.X., Wu, F.Q. and Tan, H.C. (2005) Distribution characteristics of soil nutrients in Dam Land. B. Soil & Water Conservation, 25 (2), 12–15
5
Boroshkeh, E. and Arabkhedri, M. (2013) Regression model for estimating annual sediment yield of small waresheds in West Azerbaijan. Journal of Watershed Engineering and Management, 4(4): 170-178. (In Farsi)
6
Boroshkeh, E. and Arabkhedri, M. (2015) Evaluation of MPSIAC and EPM empirical models in western Azarbayjan provincebased on sediment surveying behind small dams. Journal of Watershed Engineering and Management, 7(3): 265-273. (In Farsi)
7
Bremner, J.M. and Mulvaney, C.S. (1982) Nitrogen-Total. In: A.L. Page and R.H. Miller (Eds). Methods of Soil Analysis. Part 2. 2nd ed. Agron. Monogr. 9. ASA and SSSA, Madison, WI, pp: 595-624.
8
Chartier, M.P., Rostagno, C.M. and Videla, L.S. (2013) Selective erosion of clay, organic carbon and total nitrogen in grazed semiarid rangelands of northeastern Patagonia, Argentina. Journal of Arid Environments, 88, 43-49.
9
Fredlund, M.D., Fredlund D.G. and Wilson, G.W. (2000) An equation to represent grain size distribution. Canadian Geotechnical Journal, 37, 817–827.
10
Gee, G.W. and Bauder, J.W. (1986) Particle-size Analysis. In A. Klute (ed): Methods of soil analysis, Part 1, Physical and Mineralogical Methods. Madison,Wis., 393–394.
11
Ghadiri, H. and Rose, C.W. (1991) Sorbed chemical transport in overland flow. II. Enrichment ratio variation with erosion processes. Journal of Environmental Quality, 20, 634-641.
12
Haregeweyn, N., Poesen, J., Deckers, J., Nyssen, J., Mitiku, Haile, Govers, G., Verstraeten, G. and Moeyersons, J. (2008) Sediment-bound nutrient export from micro dam catchments in Northern Ethiopia. Land Degradation and Development. 19, 136–152.
13
Hashemi, S.A.A. and Arabkhedri, M. (2008) Evaluation of EPM Model by Sediment Measurement in Reservoirs of Small Dams. JWSS - Isfahan University of Technology. 11 (42):345-355. (In Farsi)
14
Hashemi, S.A.A. and Arabkhedri, M. (2010) Sediment measurement in reservoirs of small dams for evaluation of MPSIAC model in Semnan province. Journal of Watershed Engineering and Management. 1(2): 25-34. (In Farsi)
15
Hassanli, A. M., Esmaeli Nameghi, A. and Beecham, S. (2009) Evaluation of the effect of porous check Dam location on fine sediment retention (a case study). Environ Monit Assess. 152, 319-326.
16
Lal, R.(2005) Influence of soil erosion on carbon dynamics in the world. In: E.R. Roose, (Eds.). Soil erosion and carbon dynamic (23-37). Boca Raton: CRC press.
17
Martinez-Mena, M., Lopez, J., Almagro, M., Albaladejo, J., Castillo, V., Ortiz, R. and Boix-Fayos, C. (2012) Organic carbon enrichment in sediments: Effects of rainfall characteristics under different land uses in a Mediterranean area. Catena. 94, 36-42.
18
Morgan, R.P.C. (2005) Soil Erosion and Conservation, 3rd edition. Blackwell Publishing, Oxford, 304 pp
19
Onda, Y., Gomi, T., Mizugaki, Sh., Nonoda, T. and Roy, C.S. (2010) An Overview of the Field and Modelling Studies on the Effects of Forest Devastation on Flooding and Environmental Issues. Hydrological Processes. 24, 527- 534.
20
Romero-Diaz. A., Marín-Sanleandro, P. and Ortiz-Silla, R. (2012) Loss of soil fertility estimate from sediment trapped in check dams. South-eastern Spain. Catena, 99, 42-53.
21
Rowell, D.L. (1994) Soil Science: Methods and Applications. Longman Scientific & Technical. ISBN: 0 582 08784 8. 350 p.
22
Shahbazi, A., Ahmadi, H. and Nazari Samani, A.A. (2013) Investigation of sediments deposition in streams and its impact on the volume of reservoir (Case study: Taleghan region). Iranian Journal of Irrigation and Drainage, 7(2): 259-269. (In Farsi)
23
Sun, W.Y. and Guo, S.L. (2011) The spatial distribution of soil organic carbon and it’s influencing factors in hilly region of the Loess Plateau. Acta Ecol. Sin. 31, 1604–1616.
24
Tejada, M. and Gonzalez, J.L. (2008) Influence of two organic amendments on the soil physical properties, soil losses, sediments and runoff water quality. Geoderma. 145, 325-334.
25
Tesfahunegn, G.B. and Velk, P.L.G. (2013) Assessing Sediment-Nutrient Export Rate and Soil Degradation in Mai-Negus Catchment, Northern Ethiopia. ISRN, Soil Science, Article ID 748561, 10 page.
26
Wang, X.L., Guo, S.L., Ma, Y.H., Huang, D.Y. and Wu, J.S. (2007) Effects of land use type on soil organic C and total N in a small watershed in loess hilly-gully region. Chinese J. App. Ecol. 18, 1281–1285.
27
Zhang, C.E., Wang, S.Q. and Deng, X.P. (1999) Primary fertility and approaches of improving fertility in Yaner Gully watershed of North Yan’an area. Bull. Soil & Water Conservation, 19 (5), 15–20.
28
Zhang. F., He, X., Gao, X. and Tang, K. (2005) Effects of erosion patterns on nutrient loss following deforestation on the Loess Plateau of China. Agriculture, Ecosystems and Environment. 108, 85–97.
29
Zhang, G.H., Liu, G.B., Wang, G.L. and Wang, Y.X. (2011) Effects of vegetation cover and rainfall intensity on sediment-associated nitrogen and phosphorus losses and particle size composition on the Loess Plateau. Journal of Soil and Water Conservation. 66(3), 192-200
30
ORIGINAL_ARTICLE
Modeling Water Table Rise Between Two Canal In Aquifer with Differential Quadrature Method.
In many of agricultural land water table is raised because of seepage from canal and surface recharge. This raised is gradually caused some problem appear in land such as waterlogging and salinity, ultimately leading to land degradation. Therefore development of agriculture and economics in that region are endangered. It is necessary before problems appear engineers and researchers consider the variation of the groundwater table.In this article that problem has selected which shows an aquifer lied on a slopping impervious barrier which is discharged by a constant discharge from the surface and two canals with (L) horizontal distance. The initial water table is located horizontally h0 above the either horizontal or slopping bottom. After recharge and canal commencement, water table starts to rise. The rate of rising depends on the rate and duration of recharge and seepage from canal.In this article, application of DQM in discretization of governing equations for chosen case study and formulation of the problem is presented. For further comparison and find more reliable answer are used three method for discretization of governing equation:1-Explicit Scheme,2-Implicit Scheme,3-Semi Implicit Crank Nicholson Scheme.This investigation confirm that DQM has vast capability and simplicity to produce accurate results which is satisfactory compatible with Finite Difference numerical model as well as whit analytical solution while is highly efficient in time and low cost of running. The discretization scheme in this method does not establish large sets of simultaneous equation to be solved and is not sensitive to the number of grids in its mesh. There for with a very small number of grids comparing to a very large number of required grids in Finite Difference scheme produce very accurate results close to analytical solution results and create exactly the same results as Finite Difference scheme produce.
https://ijswr.ut.ac.ir/article_58336_fecc5b17bc8bc7cf07258fe433acb81d.pdf
2016-07-22
307
317
10.22059/ijswr.2016.58336
Boussinesq equation
Numerical Modeling
DQM
davood
moshirpanahi
davood.moshir@gmail.com
1
علم و صنعت ایران
AUTHOR
S.hamed
Meraji
h.meraji@pgu.ac.ir
2
دانشگاه خلیج فارس
LEAD_AUTHOR
Abass
Ghaheri
ghaheri@iut.ac.ir
3
علم و صنعت ابران
AUTHOR
Mustafa, S. (1987).Water table rise a semiconfined aquifer due to surface onfiltration and canal recharge. J.of Hydrology. 95(3),269-276.
1
Rai, S.N., Singh, R.N.(1992) .Water table fluctuations in an aquifer system owing to time-varying surface infiltration and canal recharge. J. of Hydrology. 136(1),381–387.[A1]
2
Sewa, R., Jaiswal, C.S., Chauhan, H.S..(1994).Transient water table rise with canal seepage and recharge. J.of Hydrology. 163(3), 197–202.
3
Manglik, A., Rai, S. N., Singh, R. N..(1994). Water table fluctuation in response to transient recharge from a rectangular basin. J. Water Resource Management. 8(1),1-10.[A2]
4
Manglik, A., Rai, S. N., Singh, R. N. .(1997). Response of an unconfined aquifer induced by time varying recharge from a rectangular basin. J. Water Resource Management . 11(3),185–196.
5
Upadhyaya , A. , Chauhan, H.S..(2001). Water table fluctuations due to canal seepage and time varying recharge. J. of Hydrology. 244 (1),1–8.
6
Upadhyaya , A. , Chauhan, H.S..(2002).Water Table Rise in Sloping Aquifer due to Canal Seepage and Constant Recharge. J. of Irrigation and Drainage Engineering. 2002, 128(3),160-167.
7
Bellman, R. ,Casti, J..(1971).Differential quadrature and long term integration. J. Math. Anal.Appl. 34(2),235–238.
8
Chen, R.P. , Zhou, W.H. , Wang, H.Z. , Chen, Y.M..(200). One - dimensional nonlinear consolidation of multi-layered soil by differential quadrature method. J. Computers and Geotechnics. 32(5) .358-369.
9
Hashemi ,M.R., Abedini ,M.J., Malekzadeh ,P.(2007). A Differential quadrature analysis of unsteady open channel flow. J. Appleid Math. Model. 31(8),1594–1608.
10
Hashemi ,M.R., Abedini ,M.J., Malekzadeh, P. (2006). Numerical modeling oflong waves in shallow water using incremental differential quadrature method . J.Ocean engineering.33(13) 1749-1764.
11
Robati, A. ,Barani, G.A. (2009). Modeling of water surface profile in subterranean channel by differential quadrature method (DQM). J. Appleid Math. Model.33(3),1295–1305.
12
Ozisik, M. N. (1980) Heat conduction. New York .Wiley.[A3]
13
Shu,C. ,Richards, B.E.(1990) High resolution of natural convection in square cavity by generalized differential quadrature. Proc of 3rd Conf on Adv in Numer. Methods in Eng. Theoryand App., Sewansea, UK, pp 978–985.
14
Shu, C.(2000) Differential Quadrature and its Application in Engineering.", London, Springer.
15
Jain, M. K., Iyenger, S. R. K., Jain, R. K.(1994) Computationalmethods for partial differential equations.New Delhi, Wiley.
16
ORIGINAL_ARTICLE
Oct, p: 636-646 . (In Farsi)
The effects of climate change on DeMartone climatic classification in Golestan province
Increasing trend of greenhouse gasses in recent decades has affected weather and climatic zones across the globe. The aim of this study is to investigate the effect of climate change on climatic classes of Golestan province, Iran based on the extended de-Martone index. Rainfall data of 60 rain gauges and daily minimum/ maximum temperature data of 22 weather stations during period of 1982-2010 were used as baseline observations. Besides, HadCM3 model outputs were statistically downscaled using LARS-WG model under A1B ,A2 وB1scenarios to project rainfall and temperature data for three periods of 2011-2040,2041-2070 and 2071 to 2100.Generated time series of mean annual rainfall, mean temperature and minimum temperature of coldest month of the year were interpolated using Kriging method. Based on extended de-Martonne index, climatic zones were worked out and drawn using GIS tools. Results indicated that Kriging method interpolated rainfall data with less error comparing to other methods. According to the results both temperature and rainfall in the region would increase but the increase magnitude may vary in different periods, such that in near future (2011-20140) the rate of rainfall increase would be more than temperature which lead to more humid climates. This will be reverse during 2071-2100 in which drier years are expected. Among the chose scenarios, the A2 projects the worse conditions for the study region. Taking into account the temperature gradient, the Geographically Weighted Regression method is suitable for regionalization of temperature. Comparative examination of climatic zones of province under climate change scenarios showed that warm semi-arid climatic class which does not exist at present, would cover about 5 % of the province. in the last study period.i.e.2071-2100 under A2 scenario.
https://ijswr.ut.ac.ir/article_58337_f9daac68a786d2e6ab77825e3b5d19c2.pdf
2016-07-22
319
332
10.22059/ijswr.2016.58337
LARS-WG
Hadcm3
extended de-Martone
climate change
climatic zones
Khalil
Ghorbani
ghorbani.khalil@yahoo.com
1
Faculty member
LEAD_AUTHOR
Mehrnaz
Bazrafshan Daryasary
mbazrafshan150@yahoo.com
2
دانشآموخته گرایش کارشناسی ارشد مهندسی منابع آب
AUTHOR
Mehdi
Meftah Halaghi
meftah_20@yahoo.com
3
عضو هیأت علمی گروه مهندسی آب دانشگاه علوم کشاورزی و منابع طبیعی گرگان
AUTHOR
Nozar
Ghahreman
nghahreman@ut.ac.ir
4
عضو هیأت علمی گروه مهندسی آب دانشگاه تهران
AUTHOR
Abassi, F. Malbusi, S. Babaeian, I. Asmari, M and Borhani, R. (2010). Climate change prediction of South Khorasan Province during 2010-2039 by using statistical downscaling of ECHO-G data. Journal of Water and Soil. 24(2), 218-233. (In Farsi)
1
Aghdasi, F. (2004). Study of some geostatistical methods for mapping of daily and annual precipitation (case study: Borkhar Plain), MSc. Thesis, University of Tehran. 112 p. (In Farsi)
2
Asakereh, H. (2008). Application of Kriging interpolation of rainfall, Case Study: interpolation of precipitation 1998/3/17 in Iran. Journal of Geography and Development, 12, 25-42. (In Farsi)
3
Babaeian, I. and Najafi Nick, Z. (2007). Climate change assessment in Khorasan-e Razavi Province from 2010 to 2039 using statistical downscaling of GCM Output. Development of Geography and Regional Magazine, 15,1-19. (In Farsi)
4
Babaeian, I. Najafi Nick, Z. Nokhandan Habibi, M., Zabul Abbasi, F., Adab, H. and Malboci, Sh. (2007). Modeling the climate of Iran in the period 2010-2039 using a statistical overview of the output of small-scale model ECHO-G. Technical Workshop on the Climate Change Impacts on Water Resources Management. (In Farsi)
5
Bahri, M., Dastorany, M. and Goudarzi, M. (2013). Assessment of the effects of climate change on precipitation and temperature 2011-2030 period using LARS-WG (case study: Watershed Eskandari, Isfahan). The 9th National Congress of Watershed Management Science and Engineering, Nov. 8-9, 2013, University of Yazd, Yazd, Iran. (In Farsi)
6
Bazrafshan, J. 2009. Agricultural drought risk assessment and searching a sufficient method for estimating its quantitative impact on crops yield of wheat and barley. Ph.D. Dissertation, University of Tehran. 253p.
7
Ebrahimpour, M. Ghahreman, N. and Orang, M. (2014). Assessment of climate change impacts on reference evapotranspiration and simulation of daily weather data using SIMETAW. Journal of Irrigation and Drainage Engineering. 140(2): 04013012[u1] . (In Farsi)
8
Farahmand, A. Golkar, F. and Farahmand, F. (2010). Estimating the spatial distribution of rainfall in the Dorudzan Dam Basin using GIS. Geomatics Conference, May.[u2] (In Farsi)
9
Fotheringham, A.S., Brunsdon, C. and Charlton, M. (2002). Geographically weighted regression. John Wiley & Sons Inc.
10
Ghamghami, M. and Ghahreman, N. (2013). Downscaling of climatic change using a non-parametric statistical approach in Karkheh Basin. Iranian Journal of Geophysics. 7(2): 142-157. (In Farsi)
11
Ghamghami, M., Ghahreman, N. and Hejabi, S. (2014). Detection of climate change effects on meteorological droughts in northwest of Iran. Journal of Earth and Space Physics. 40(1): 167-184. (In Farsi)
12
Gharekhani, A. and Ghahreman, N. (2010). Seasonal and annual trend of relative humidity and dew point temperature in several climatic regions of Iran. Journal of Water and Soil. 24(4): 636-646. (In Farsi)
13
Ghorbani, Kh. (2014). Evaluation data mining models in downscaling of precipitation based on NCEP general circulation model output (case study: Kermanshah synoptic station). Iranian Water Research Journal. 8(15), 177-186. (In Farsi)
14
Ghorbani, Kh. and Agha Shariatmadari, Z. (2014). The effect of local gradients on increasing of climatic data interpolation accuracy by geographically weighted regression (case study: air temperature and relative humidity). Journal of Watershed Management Research. 5(10),132-143. (In Farsi)
15
Goovaerts, P. (2000). Geostatistical approach for incorporating elevation into spatial interpolation of rainfall. Journal of Hydrology. 228 (2), 113-129.
16
Gruza, G., Rankova, E., Razuvaev, V. and Bulygina, O. (1999). Indicators of climate change for the Russian Federation. Climatic Change. 42, 219–242.
17
Gundogdu, I. and Esen, O. (2010). The importance of secondary variables for mapping of meteorological data. The 3rd International Conference on Cartography and GIS. Jun. 15-20, 2010, Nessebar, Bulgaria.
18
Hadley Center. (2006). Effect of climate change in the developing countries. The UK Meteorological Office.
19
Hess, T.M., Stephens, W. and Maryah, U.M. (1995). Rainfall trends in the north east arid zone of Nigeria 1961–1990. Agricultural and Forest Meteorology. 74: 87–97.
20
IPCC. (2007). Climate change: The physical science basis. Contribution of Working Group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge. 996 p.
21
Kakavand, R. and Najaf Abadi, M. (2008). Qazvin climatic maps using GIS. Conference on Geographic Information System. Azad University of Qazvin. (In Farsi)
22
Karamooz, M. and Araghinejad, Sh. (2006). Advanced hydrology, Amir Kabir University Press, 464 p. (In Farsi)
23
Khalili, A. (1973). The scientific understanding of climate and weather. IRIMO publication. (In Farsi)
24
Khorshid Doust, M.A. and Ghavidel Rahimi, Y. (2006). The simulation of atmospheric carbon dioxide doubling impacts on climatic changes in Tabriz using Geophysical Fluid Dynamics Laboratory (GFDL) General Circulation Model. Journal of Environmental Studies. 32(39), 1-10. (In Farsi)
25
Lashany Zand, M., Shah Hosseini, M. and Beyranvand Zade, M. (2010). Climate zoning of Gilan using classical methods. Conference on Applications of Natural Geography in Environmental Planning. Jun. 5-6, 2010, Islamic Azad University of Khorramabad, Khorramabad, Iran. (In Farsi)
26
Massah Bavani, A.R. and Morid, S. (2006). Impact of climate change on the water resources of Zayandeh Rud Basin. JWSS - Isfahan University of Technology. 9(4), 17-28. (In Farsi)
27
Mennis, J. 2006. Mapping the results of geographically weighted regression. The Cartographic Journal, 43(2), 171-179.
28
Meshkatee, A., Kordjazi, M. and Babaeian, I. (2010). Evaluation of the simulation model LARS during the 1993-2007. Journal of Geographical Sciences and Applied Research, 16(19): ??????. [u3] (In Farsi)
29
Mohammadi, Gh.H. and Husseini Sadr, A. (2010). District of West Azerbaijan Province from the perspective of agricultural climatology using GIS. The 3rd National Conference on Geography and Scientific Approach to Sustainable Development. Nov. 11-12, 2010, Pyranshahr, West Azarbaijan, Iran. (In Farsi)
30
Plummer, N., Salinger, M.J., Nicholls, N., Suppiah, R., Hennessy, K.J., Leighton, R.M., Trewin, B., Page, C.M. and Lough, J.M. (1999). Changes in climate extremes over the Australian region and New Zealand during the twentieth century. Climatic Change. 42, 183–202.
31
Racsko, P. and Szeidl, L. (1991). A serial approach to local stochastic weather models. Ecological Modelling. 57, 27-41.
32
Rahimi, J., Ebrahimpour, M. and Khalili, A. (2013). Spatial changes of Extended De Martonne climatic zones affected by climate change in Iran. Theoretical and Applied Climatology. 112(3), 409-418. (In Farsi)
33
Sabohi, R. and Soltani, S. (2009). Trend analysis of climatic factors in great cities of Iran. JWSS - Isfahan University of Technology. 12(46), 303-321. (In Farsi)
34
Semenov, M.A., Brooks, R.J., Barrow, E.M. and Richardson, C.W. (1998). Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates. Climate Research. 10, 95-107.
35
Suppiah, R. and Hennessy, K. (1998). Trends in total rainfall, heavy rain events and number of dry days in Australia, 1910–1990. International Journal of Climatology. 10, 1141–1164.
36
Turke¸ S.M. (1996). Spatial and temporal analysis of annual rainfall variations in Turkey. Internatonal Journal of Climatology. 16, 1057–1076.
37
Varshavian, V., Khalili, A., Ghahreman, N. and Hajjam, S. (2011). Trend analysis of minimum, maximum, and mean daily temperature extremes in several climatic regions of Iran. Journal of the Earth and Space Physics. 37(1), 169-179.
38
Viglizzo, E.F., Roberto, Z.E., Filippin, M.C. and Pordomingo, A.J. (1995). Climate variability and agroecological change in the central Pampas of Argentina. Agricultural Ecosystem and Environment. 55, 7–16.
39
Xu, C.Y. (1999). From GCMs to river flow: a review of downscaling methods and hydrologic modeling approaches. Progress in Physical Geography. 23(2), 229-249
40
Zhai, P., Sun, A., Ren, F., Liu, X., Gao, B. and Zhang, Q. (1999). Changes of climate extremes in China. Climatic Change. 42, 203–218.
41
ORIGINAL_ARTICLE
Effect of arsenic contamination on phosphoure of soil and phosphorus concentration in soybean
This study aimed to investigate the effect of arsenic and phosphorus bioavailability of soil phosphorus and total phosphorus concentration in soybean for this purpose a factorial experiment in a completely randomized design with 3 factors and 3 replicates was conducted into the pots with soil media in the greenhouse of Agricultural Research. The factors were soybean with two levels (L17 native varieties and promising lines), arsenic with four levels (0, 10, 50 and 100 mg.kg-1) and phosphorus with four levels (0, 25, 50 and 100 mg.kg-1). Di potassium hydrogen phosphate and disodium hydrogen arsenate salts of phosphorus and arsenic in soil added. The results showed that by increasing in the concentration of arsenic in the phosphorus treatment, phosphorus bioavailability of soil increased (P≤0.05). 10 mg.kg-1 Arsenic in soil germination percentage increased to 6.4% compared to control (P≥0.05). High levels of arsenic (50 and 100 mg.kg-1) caused decrease (16.11 and 76.68 %, respectively) in the germination percentage in comparison to the control (P≤0.01). Adverse effects of concentrations of arsenic, which stop the growth and eventually death of the plant. Arsenic reduced shoot biomass and increased total phosphorus plant (P≤0.01). The results of interaction of phosphorus and arsenic showed that with increasing concentration of phosphorus in soil containing arsenic, total phosphorus concentration rose plant (P≤0.05).
https://ijswr.ut.ac.ir/article_58338_5916f594a734ddf53a51f0755a873432.pdf
2016-07-22
333
343
10.22059/ijswr.2016.58338
Contamination
arsenic
phosphoure
soybean
Competitive effect
Fateme
Ajili
ajili.f@chmail.ir
1
دانشگاه شاهد
LEAD_AUTHOR
Abdol Amir
Bostani
bostani@shahed.ac.ir
2
Shahed univercity
AUTHOR
nejat
Pir vali
npirvali@nrcam.org
3
Institute of Nuclear Agriculture
AUTHOR
darush
talei
d.talei1348@gmail.com
4
Shahed Univercity
AUTHOR
mohammad
babaakbari
babaakbari@znu.ac.ir
5
zanjan Unevercity
AUTHOR
Ahmed, S.F.R., Killham, K. and Alexander, I., (2006). Influences of arbuscular fungus Glomus mosseae on growth and nutrition of lentil irrigated with arsenic contaminated water. Plant Soil, 258, 33–41.
1
Antelo, J., Avena, M., Fiol, S., López, R. and Arce F. (2005). Effects of pH and ionic strength on the adsorption of phosphate and arsenate at the goethite–water interface, Journal of Colloid and Interface Science, 285, 476–486.
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Asher, C.J., and Reay, P.F. (1979). Arsenic uptake by barley seedlings. Aust. J. Plant Physiol, 6,459-466.
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Bhagawan More, S., (2008),Evalution of induced mutants for phosphorus use efficiency in soybean [Glycine max (L.) Merill],Thesis submitted to department of crop physiology collage of agriculture, Dharwad University of Agricultural Sciences, Dharwad.
6
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Cozzolino, V., Pigna, M., Di Meo, V., Caporale, A. G., Violante, A. and Meharg, A. A., (2010). Influence of phosphate addition on the assenic uptake by wheate (Triticum durum) grown in arsenic polluted soils. Fresenius Environmental Bulletin, 19 (5), 838-845.
9
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Gulz, P. A. (2002). Arsenic Uptake of Common Crop Plants from Contaminated Soils and Interaction with Phosphate. PhD thesiss, Dipl. Geogr., University of Munich, Zurich, pp:108.
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Hongshao, Z. and Stanforth, R. (2001). Competitive adsorption of phosphate and arsenate on goethite. Environ Sci Technol,35(24),4753-4757.
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Jacobs, L.W., and Keeney, D.R., (1970). Arsenic - Phosphorus Interaction in Corn. Soil Science and Plant Analysis. 1,85-93.
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Jahangiri, Sh., Suri, B., Badakhshan, H., (2011), The relationship between physical and chemical properties of calcareous soil and arsenic of soil in Ghorveh plain, Journal of Soil Research (soil and water science), 25 (4), 337 -348.[in farsi]
15
Karimi, N., Ghaderian, S. M., Raab, A., Feldmann, J. and Meharg, A.A. (2009). An arsenic accumulating, hyper-tolerant brassica, Isatis capadocica. New Phytol, 184, 41-47.
16
Lakzian, A., Halajnia, M., Nassiri Mallati, M. and Nikbin, F. (2009). The effect of Rhizobium leguminsarum bv. Phaseoli on uptake and tolerance to arsenic in common bean. journal of water and soil, 23, 3, 36- 44.(In farsi)
17
Lasat, M.M. (2002). Phytoextraction of toxic metals: a review of biological mechanisms. J. Environ. Qual, 31, 109-120.
18
Lee, D.A., Chen, A. and Schroeder, J.I. (2003) Ars1, an Arabidopsis mutant exhibiting increased tolerance to arsenate and increased phosphate uptake. The Plant Journal, 35, 637- 646.
19
Liao M., Hocking P.J., Dong B., Delhaize E., Richardson A.E., and Ryan P.R. (2008). Variation in early phosphorusuptake efficiency among wheat genotypes grown on two contrasting Australian soil. Aust. J. Agr. Res, 59, 157-166.
20
Liebig, J., Bradford, G. F., G.R. Bradford, and Vanslow, A.P. (1959). Effects of arsenic compounds on citrus plants in solution culture. Soil Sei. 88:342-348.
21
Liu, X., Zhang, S., Shan, X. and Zhu, Y.G. (2005). Toxicity of arsenate and arsenite on germination seedling growth and amylolytic activity of wheat. Chemosphere, 61, 293-301.
22
Magdi selm, H. (2001). heavy metals release in soil, chapter 10.
23
Mahdiyeh, Sh., Ghaderian, S.M. and Karimi, N. (2012). Evaluating the effect of phosphorus on arsenic uptake and accumulation in two cultivars of wheat (Triticum aestivum L.). Plant Production. 19 (2), 105 – 121.(In farsi)
24
Manning, B.A. and Goldberg, S. (1996). Modeling arsenate competitive adsorption on kaolinite, montmorillonite, and illite. Clays and Clay Minerals, 44 (5), 609-623.
25
Meharg, A. A. and Macnair, M. R. (1990). An altered phosphate uptake system in arsenate-tolerant Holcus Lanatus L. New Phytol, 116, 29-35.
26
Meharg, A.A. and Macnair, M.R. (1994). Relationship between plant phosphorus status and the kinetics of arsenate influx in clones of Deschampsia caespitosa (L.) Beauv. that differ in their tolerance of arsenate. Plant and Soil, 162, 99- 106.[A1]
27
Mehmood, A., Hayat, R., Wasim, M. and Akhtar, M. S. (2009). Mechanisms of Arsenic Adsorption in Calcareous Soils Published in J. agric. biol. sci, 1 (1), 59-65.
28
Munns, R. (2005). Genes and salt tolerance: bringing them together. New Phytol, 167, 645-663.
29
Mwamila, L.B. (2012). Arsenic (V) and Phosphate sorption to Swedish clay soils – Freundlich sorption modeling. TRITA LWR Degree Project, 12, 02- 21.
30
Nadiri, A., Asghari Moghadam, A., Sadeghi, F., Aghaei, H., (2012), Investigate anomalous arsenic in water resources Sahand Dam, JES, 3, 61- 74.[ in farsi]
31
O’Reilly, S.E. Strawn, D.G. and Sparks, D.L. (2001). Residence Time Effects on Arsenate Adsorption/Desorption Mechanisms on Goethite. Soil Sci. Soc. Am. J, 65, 67–77.
32
Olsen, S.R. and Sammers, L.E. (1982). phosphorus. In: A.L. page, R.H. Miller, and D. R. keeney (eds) methods of soil analysiss. Part 2. Chemical and microbiological properties. 2nd ed. Monogr. 9. ASA and SSSA, Madison, WI. P. 403 – 430
33
Olyaie, E., Banejad, H., Rahmani, A.R., Afkhami, A. and Khodaveisi, J. (2012). Feasibility study of using Calcium Peroxide Nanoparticles in Arsenic Removal from Polluted Water in Agriculture and It’s Effect on the Irrigation Quality Parameters. Iran. J. Health & Environ, 5 (4), 319- 330.(In farsi)
34
Pigna, M., Caporale, A.G., Cozzolino, V., Fernández López, C., Mora, M.L., Sommella, A. and Violante, A. (2012). Influence of phosphorus on the arsenic uptake by tomato (Solanum lycopersicum L) irrigated with arsenic solutions at four different concentrations. Journal of Soil Science and Plant Nutrition, 12 (4), 775- 784.
35
Pigna, M., Cozzolino, V., Violanto, A. and Meharg, A. (2009). Influence of phosphate on the arsenic uptake by wheat (Triticum durum L.) irrigated with arsenic solutions at three different concentrations. Water Air Soil Pollut,197, 371–380.
36
Renkou, XU., Yong W., Diwakar, T. and Houyan, W. (2009). Effect of ionic strength on adsorption of As(III) and As(V) on variable charge soils. Journal of Environmental Sciences, 21, 927–932.
37
Rhoades, J. D. (1982). Soluble salts. In: A.L. page(ed.). Method of soil analysis. part2. Chemical and microbiological Properties. Agronomy monograph no. 9. 2nd ed. SSSA and ASA, Madison, WI. P.167-179.
38
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39
Salehi-Lisar, S.Y., Sardari, M., Movafeghi, A.and Mustafavi, S.H. (2013). Effects of Arsenic Speciation and Concentrations on Germination Behavior and Seedling Growth of four Wheat Cultivar (Triticum aestivum L.). International Journal of Agronomy and Plant Production, 4 (11), 2872-2876.
40
Sharma, A., Gontia-Mishra,I. and Srivastava, A.K. (2011). Toxicity of Heavy Metals on Germination and Seedling Growth of Salicornia brachiate. Journal of Phytology, 3(9), 33-36.
41
Sheppard, S. C. (1992). Summary of Phytotoxic Levels of Soil Arsenic. Water Air Soil Pollution. 64, 539-550.
42
Smith, E., Naidu, R. and Alston, A.M. (2002). Chemistry of inorganic arsenic in soils: ii. effect of phosphorus, sodium and calcium on arsenic sorption. Journal of Environmental Quality, 31, 557–563.
43
Srivastava, S., Srivastava, A.K., Suprasanna, P. and D’Souza, S.F. (2009). Comparative biochemical and transcriptional profiling of two contrasting varieties of Brassica juncea L. in response to arsenic exposure reveals mechanisms of stress perception and tolerance. J Exp Bot, 181, 1–13.
44
Stoeva, N., Berova, M. and Zlatev, Z. (2005). Effect of arsenic on some physiological parameters in bean plants. Biologia plantarum, 49 (2), 293-296.
45
Sultana, R., Rahman, A., Kibria, K.Q., Islam, S. and Haque, M. (2012). Effect of Arsenic Contaminated Irrigation Water on Growth, Yield and Nutrient Accumulation of Vigna radiate. Indian J. Innovations Dev, 1(9), 682 -686.
46
Talukdar, D. (2011). Effect of Arsenic-induced Toxicity on Morphological Traits of Trigonella foenum-graecum L. and Lathyrus sativus L. During Germination and Early Seedling Growth. Current Research Journal of Biological Sciences, 3(2), 116-123.
47
Tu, S. and Ma, L.Q. (2003). Interactive effects of pH, arsenic and phosphorus on uptake of As and P and growth of the arsenic hyperaccumulator Pteris vittata L. under hydroponic conditions. Environmental and Experimental Botany, 50, 243-251.
48
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49
Violante, A. and Pigna, M. (2002). Competitive sorption of arsenate and phosphate on different clay minerals and soils. Soil Sci. Soc. of Am. J, 66, 1788-1796.
50
Vodyanitskii, Yu. N. (2009). Chromium and Arsenic in Contaminated Soils (Review of Publications). Eurasian Soil Science, 42 (5), 507–515.
51
Wang, J.R., Zhao, F.J., Meharg, A.A., Raab, A., Feldmann, J. and McGrath, S.P. (2002). Mechanisms of arsenic hyperaccumulation in Pteris vittata. uptake kinetics, interactions with phosphate, and arsenic speciation. Plant Physiol, 130, 1552–1561.
52
Wang, S. and Mulligan, C.N. (2006). Effect of natural organic matter on arsenic release from soils and sediments into groundwater. Environmental Geochemistry and Health, 28, 197–214.
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56
Zeng, X., Wu,P., Su,S., Bai, L., Feng, Q.. (2012). Phosphate has a differential influence on arsenate adsorption by soils with different properties. Plant soil environ, 58 (9), 405–411
57
Zhu, J., Pigna, M., Cozzolino, V., Giandonato Caporale, A. and Violante, A. (2013). Higher sorption of arsenate versus arsenite on amorphous Al-oxide, effect of ligands. Environ Chem Lett, 11 (3), 289-302.
58
ORIGINAL_ARTICLE
Two-objective design of groundwater-level monitoring network using NSGA-II in Eshtehard plain
Groundwater monitoring plays a significant role in groundwater management to control aquifer behavior. Thus, a groundwater monitoring network is required to control spatial and temporal fluctuations of groundwater characteristics. This study describes a new optimization method to design an optimum groundwater-level monitoring network and was implemented on Eshtehard aquifer. Database of the study was provided by kriging interpolation. Optimization of groundwater monitoring network was implemented by Non-Dominated Sorting Genetic Algorithm II (NSGA-II) with two objective functions of minimizing the root mean square error (RMSE) and minimizing the number of network wells which representing the cost of constructing, maintenance service and collecting data. Inverse Distance Weighting (IDW) was used to compute the groundwater-level in simulation part of optimization. The result of the study is a Pareto front showing the number of wells and corresponding RMSE which would be a guideline for groundwater monitoring network design. By selecting the required accuracy of the monitoring network data, the number of observation wells and their locations in the study area would be demonstrated.
https://ijswr.ut.ac.ir/article_58339_85e5560206f56f68a2b1725cda9a2053.pdf
2016-07-22
345
354
10.22059/ijswr.2016.58339
Two-Objective Optimization
Groundwater-Level Monitoring Network
Kriging
IDW
NSGA-II
Fahimeh
Mirzaei-Nodoushan
fhmnodoushan@ut.ac.ir
1
Student
LEAD_AUTHOR
Omid
Bozorg Haddad
obhaddad@ut.ac.ir
2
هیئت علمی دانشگاه تهران
AUTHOR
Majid
khayyat kholghi
kholghi@ut.ac.ir
3
هیئت علمی دانشگاه تهران
AUTHOR
Asefa, T., Kemblowski, M.W., Urroz, G., McKee, M., and Khalil, A. (2004). “Support vectors-based groundwater head observation networks design”, Water Resources Research, 40(11), DOI: 10.1029/2004WR003304.
1
Barca, E., Passarella, G., Vurro, M., and Morea, A. (2015). “MSANOS: Data-Driven, Multi-Approach Software for Optimal Redesign of Environmental Monitoring Networks”, Water Resources Management, 29(2), 619-644.
2
Bivand, R.S., Pebesma, E., and Gómez-Rubio, V. (2008). “Applied spatial data analysis with R”, Springer, New York.
3
Cressie, N.A.C. (1991). “Statistics for spatial data”, John Wiley & Sons.
4
Datta, B. and Dhiman, D.S. (1996). “Chance-constrained optimal monitoring network design for pollutants in groundwater”, Journal of Water Resources Planning and Management, 122(3), 180-188.
5
Dhar, A. and Patil, R.S. (2012). “Multiobjective design of groundwater monitoring network under epistemic uncertainty”, Water Resources Management, 26(7), 1809-1825.
6
Dokou, Z. and Pinder, G. (2009). “Optimal search strategy for the definition of a DNAPL source”, Journal of Hydrology, 376(3-4), 542-556.
7
Esquivel, J.M., Morales, G.P., and Esteller, M.V. (2015). “Groundwater monitoring network design using GIS and multicriteria analysis”, Water Resources Management, 29(9), 3175-3194.
8
Hudak, P.F. and Loaiciga, H.A. (1993). “An optimization method for monitoring network design in multilayered groundwater flow systems”, Water Resources Research, 29(8), 2835-2845.
9
Hudak, P. (2006). “Heuristic for constructing minimum-well groundwater monitoring configurations at waste storage facilities”, Environmental Science and Health, 41(2), 185-193.
10
Khader, A.I. and McKee, M. (2014). “Use of a relevance vector machine for groundwater quality monitoring network design under uncertainty”, Environmental Modelling and Software, 57, 115-126.
11
Loaiciga, H., Charbeneau, R.J., Everett, L.G., Fogg, G.E., Hobbs, B.F., and Rouhani, S. (1992). “Review of ground-water quality monitoring network design”, Journal of Hydraulic Engineering, 118(1), 11-37.
12
Mogheir, Y., de Lima, J.L.M.P., and Singh, V.P. (2003). “Assessment of spatial structure of groundwater quality variables based on the entropy theory”, Hydrology and Earth System Sciences, 7(5), 707-721.
13
Wilson, C., Einberger, C., Jackson, R., and Mercer, R. (1992). “Design of ground-water monitoring networks using the monitoring efficiency model (MEMO)”, Ground Water, 30(6), 965-970.
14
Wu, J., Zheng, C., Chien, C.C., and Zheng, L. (2006). “A comparative study of Monte Carlo simple genetic algorithm and noisy genetic algorithm for cost-effective sampling network design under uncertainty”, Advances in Water Resources, 29(6), 899-911.
15
Yang, F., Cao, S., Liu, X., and Yang, K. (2008). “Design of groundwater level monitoring network with ordinary kriging”, Journal of Hydrodynamic, 20(3), 339-346.
16
ORIGINAL_ARTICLE
Accuracy of SEEP/W model in predicting seepage line and flow rate through lengthy coarse porous medium
In this paper, subsurface water profiles through coarse porous medium are investigated numerically and then are compared with experimental data. Numerical simulations have been conducted using SEEP/W model which is based on the finite element method. Laboratory model of the porous medium has 6.4m length, 0.8m width and 1m height. Crushed materials were used as porous media. Modeling scenarios were conducted for different values of flow discharges and three bed slopes of 0, 4 and 20.3 % and then flow profiles and discharges were computed and compared with those provided form experimental. The results indicated that application of SEEP/W model for simulating flow properties through coarse materials and rockfill structures do not always present satisfactory outputs, wherein in most cases specifically in low slopes underestimated subsurface water profiles ( seepage line) compared to observed profiles. Also computed flow discharge give a different behavior depend on bed slope and kind of materials. The results of numerical model showed a good agreement in steep slope comparing to low slopes.
https://ijswr.ut.ac.ir/article_58340_a2c1f7798ac1a4915739c39323ff8898.pdf
2016-07-22
355
362
10.22059/ijswr.2016.58340
Porous media
Numerical model
Laboratory Model
Flow Profile and seepage discharge
Eshagh
Ansari
ansari.eshagh@yahoo.com
1
دانش آموخته کارشناسی ارشد مهندسی عمران-دانشگاه آزاد اسلامی واحد یاسوج
LEAD_AUTHOR
Mohammad
Sedghi Asl
m_sedghiasl@yahoo.com
2
عضو هیات علمی/دانشگاه یاسوج
AUTHOR
Mansour
Parvizi
parvizi@yu.ac.ir
3
عضو هیات علمی دانشگاه یاسوج. گروه مهندسی عمران. دانشکده مهندسی
AUTHOR
Bazargan, H., H. Bayat (2002). Determination of non-linear flow coefficients through coarse alluvial foundations. Esteghlal. 21(1), 101-112.
1
Sedghi-Asl, M., H Rahimi, J, Farhoudi, JMV, Samani (2010a). Analysis of the Water Surface Profiles through Coarse Porous Medium. Iranian Water Research Journal, 4(7), 77-84.
2
Sedghi-Asl, M., H. Rahimi., J. Farhoudi and JMV , Samani (2010b). On the Flow Profiles in Coarse Porous Media. 9th Conference of Iranian Hydraulic Association, University of Tarbiat Modares. 9-11 November, Tehran, Iran.
3
Bari R, Hansen D. (2002). Application of gradually-varied Flow algorithms to simulate buried streams. Journal of Hydra. Res (IAHR) 40(6), pp 673-683.
4
Bear J. (1972). Dynamics of Fluids in Porous Media. Elsevier Science, New York.
5
Hansen D, Zhao W.Z. and Han S.Y.(2005). Hydraulic performance and stability of coarse rockfill deposits. Water Management VOL. 158 Issue WM4.
6
Hosseini S. M., Joy, D. M. 2(006). Calibration of Hydraulic Parameters for Water Research Foundation of Australia, Melbourne.
7
Samani H. M. V, Samani. J M. V, Shaiannejad M . 2003. Reservoir Routing using Steady and Unsteady Flow through Rockfill Dams. Journal of Hydra. Eng (ASCE) Vol. 129, No. 6.
8
Parkin A.K. 1963. Rockfill dams with inbuilt spillways I-hydraulic characteristics. Bulletin 6, University if Melbourne and of Civil Engineering, Technical University of Nova Scotia, Halifax, NS, Canada.
9
Stephenson D. 1979. Rockfill in Hydraulic Engineering. Elsevier Scientific, Amsterdam.
10
Wilkins J.K. 1956. Flow of water through rockfill and its application to the design of dams. Proc. 2nd Australia-New Zealand Conf. on Soil Mechanics and Foundation Engineering Christchurch, pp 141-149.
11
ORIGINAL_ARTICLE
Depth based regional flood frequency analysis
By using regionalization methods information from gauged sites transform to desired site. Up until now a variety of regionalization approaches have been proposed. In every site it is necessary to evaluate these methods and select the best method. It is of interest to understand how spatial weighted least square regression method based on depth function flood quantiles (SWLSR) compare with multivariate regression (MR) and Physiographical space-based kriging (PSK) methods. In each iteration desired station regarded as ungauged site then using genetic algorithm depth functions weights were optimized, finally (regarding) by taking account similarity between desired site and others sites flood quantiles corresponding to different return periods were estimated. By means of a leave-one-out cross-validation procedure, the performance of SWLSR was compared to MR and PSK methods for prediction of 10, 50 and 100 yr for 26 gauging station in the Southern Alborz. . The Result showed SWLSR approach yielded lower root-mean-square estimation errors and higher Nush Sutcliffe criteria thaneither the MR or the PSK approaches. PSK method estimated foold discharge in ungaged basin better than MR. In depth based approach Nush Sutcliffe criteria values for flood quintiles (Nash–Sutcliffe efficiency values for 10,50 and 100 yr floods were 0.64, 0.65 and 0.65 respectivly) three corresponding to different return periods were similar.In this method relative error to area in small catchment were biger than those obtained in big catchment.
https://ijswr.ut.ac.ir/article_58341_4bedd7ebb6bd141f077a00f1a29f89b9.pdf
2016-07-22
363
375
10.22059/ijswr.2016.58341
data Depth
Kriging
multivariate regression
canonical correlation analysis
Abolhasan
FathAbadi
fathbabadi@ut.ac.ir
1
عضو هیات علمی، دانشگاه گنبد کاووس
LEAD_AUTHOR
Hamed
Rohani
rouhani.hamed@yahoo.com
2
عضو هیات علمی دانشگاه گنبد کاووس
AUTHOR
Seyed Morteza
Seyedian
s.m.seyedian@gmail.com
3
عضو هیات علمی دانشگاه گنبد کاووس
AUTHOR
Archfield, S. A., Pugliese, A., Castellarin, A., Skøien, J. O. and Kiang, J. E. (2013.) Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach?.Hydrol. Earth Syst. Sci, 17, pp.1575–1588.
1
Bardossy, A. and Singh, S. K. (2008) Robust estimation of hydrologi-cal model parameters, Hydrol. Earth Syst. Sci, 12, pp. 1273–1283.
2
Burn, D.H. (1990) Evaluation of regional flood frequency analysis with a region of influence approach, Water Resour. Re., 26, pp. 2257–2265.
3
Castiglioni, S., Castellarin, A. and Montanari, A. (2009) Prediction of low-flow indices in ungauged basins through physio-graphical space-based interpolation, J. Hydrol, 378, PP.272–280
4
Chebana, F. and Ouarda, T. B. M. J. (2008) Depth and homogeneity in regional flood frequency analysis, Water Resour. Res, 44, W11422, doi :10.1029/2007WR006771.
5
Chebana, F. and Ouarda, T. B. M. J. (2011a) Depth-based multivariate de-scriptive statistics with hydrological applications, J. Geophys. Res.-Atmos, 116, D10120.
6
Chebana, F. and Ouarda, T. B. M. J. (2011b) Multivariate extreme value identification using depth functions, Environmetrics, 22, PP. 441–455.
7
Chokmani, F. and Ouarda, T. B. M. J. (2004) Physiographical space based kriging for regional flood frequency estimation at ungauged sites,Water Resour. Res, 40, PP. 1–13.
8
Cunderlik, J.M and Burn, D.H. (2006) Switching the pooling similarity distances: Mahalanobis for Euclidean. WATER RESOURCES RESEARCH, VOL. 42, W03409.
9
Gingras, D. and Adamowski, K. (1992) Coupling of nonparametric frequency and L-moment analysis for mixed distribution identification. Water Resources Bulletin, 28: PP. 263 – 272.
10
Grehys, (1996) Presentation and review of some methods for regional flood frequency analysis, J. Hydrol, 186, PP. 63–84.
11
Grover, P.L., Burn, D.H. and Cunderlik, J.M. (2002) A comparison of index flood estimation procedures for ungauged catchments. Canadian Journal of Civil Engineering, 29 : PP. 734 – 741.
12
Javelle, P., Ouarda, T.B.M.J., Lang, M., Bobee, B., Galea, G. and Gresillon, G.M. (2002) Development of regional flood-duration-frequency curves based on the index-flood method. Journal of Hydrology, 258(1 – 4): PP. 249 – 259.
13
Kraube, T. and Cullmann, J. (2012) Towards a more representative parametrisation of hydrologic models via synthesizing the strengths of Particle Swarm Optimisation and Robust Parameter Estimation, Hydrol. Earth Syst. Sci, 16, PP. 603–629.
14
Kraube, T., Cullmann, J., Saile, P. and Schmitz, G. H. (2012) Robust Multi objective calibration strategies possibilities for improv-ing flood forecasting, Hydrol. Earth Syst. Sci, 16,PP. 3579–3606,
15
Ouarda, T. B. M. J., Girard, C., Cavadias, G. S. and Bobee, B. (2001) Regional flood frequency estimation with canonical correlation analysis, J. Hydrol, 254, PP.157–173.
16
Ouarda, T. B. M. J., Ba, K. M., Diaz-Delgado, C., Carsteanu, A., Chokmani, K., Gingras, H., Quentin, E., Trujillo, E. and Bobee, B. (2008) Intercomparison of regional flood frequency estimation methods at ungauged sites for a Mexican case study, J. Hydrol, 348, PP. 40–58.
17
Pandey, G.R. and Nguyen, V.T.V. (1999) A comparative study of regression based methods in regional flood frequency analysis. Journal of Hydrology, 225: PP. 92 – 101.
18
Saf, B. (2008) Application of index procedures to flood frequency analysis in Turkey. Journal of the American Water Resources Association, 44 (1): PP. 37 – 47.
19
Sheikh, Z., Dehvari, A. and Farsadnia, F. (2014) Comparison Canonical Kriging and Linear Moments Methods for Regiona Flood Frequency Analysis in Mazandaran Province. Iran-Watershed Management Science & Engineering, Vol. 8, No. 25. PP. 25-38. (In Farsi).
20
Shu, C. and Ouarda, T. B. M. J. (2007) Flood frequency analysis at ungauged sites using artificial neural networks in canonical co-relation analysis physiographic space, Water Resour. Re., 43, W07438,doi:10.1029/2006WR005142.
21
Stedinger, J.R. and Lu, L.H. (1995) Appraisal of regional and index flood quantile estimators. Stochastic Hydrolics and Hydraulics 9(1): PP. 49 – 75.
22
Tukey, J.W. (1974) Mathematics and the picturing of data, Vol. 2, Proceedings of the International Congress of Mathematicians, Van-couver, B.C., 1974, Canad. Math. Congress, Montreal, Quebec, PP. 523–531,
23
Verhulst, P. F. (1938) Notice sur la loique la population pursuit dans son accroissement, Correspondance Math´ematiqueet Physique, 10, PP. 113–121.
24
Wazneh, H.Chebana, F. and Ouarda, T. B. M. J. (2013a) Optimal depth-based regional frequency analysis.Hydrol. Earth Syst. Sci., 17, PP. 2281–2296.
25
Wazneh, H., Chebana, F. and Ouarda, T. B. M. J. (2013b) Depth-based regional index-flood model.WATER RESOURCES RESEARCH, VOL. 49, PP. 7957–7972.
26
ORIGINAL_ARTICLE
The Study of Kinetics of Potassium Release by Ammonium acetate and Sodium tetraphenylborate Extractants from Selected Micaceous Minerals
The objectives of this study were to compare the capability of ammonium acetate (NH4OAc) and sodium tetraphenylborate (NaBPh4) in the release of potassium from micaceous minerals including biotite, phlogopite and muscovite. Non-linear regression of pseudo second-order, power function, Elovich and parabolic diffusion equations models inspected to describe potassium release from those minerals in a period of 5 to 11520 minute. The results indicated that the amount of NaBPh4-extractable K was s higher than NH4OAc-extractable K. NaBPh4 extractant released 56.15, 60.14 and 10.78% of total potassium from phlogopite, biotite and muscovite respectively, while those values were 0.81, 0.84 and 0.62% for NH4OAc extractant. The results also showed that the potassium released from minerals in two different phases. The rapid phase occurred at the beginning of experiment and the second phase with lower rate release happened until to the end of experiment. Parabolic diffusion and exponential function equations reasonability described the potassium release from micaceous minerals very well according to R2 and SE indexes. Kinetics of potassium release from biotite and phlogopite minerals were described very well by power function equation (R2=0.98-0.99 and SE=1.20-2.43). The best-fitted kinetic models for the phlogopite (R2=0.98 and SE=2.23) and muscovite (R2=0.87 and SE=1.26) minerals were Elovich and parabolic diffusion equations respectively. Therefore, it may be concluded that the release of potassium is controlled by diffusion process from the surface of the studied minerals.
https://ijswr.ut.ac.ir/article_58342_258882200c696360a53961368f26de78.pdf
2016-07-22
377
386
10.22059/ijswr.2016.58342
Available potassium
biotite
Phlogopite
Kinetic equations
Muscovite
Hadis
Hatami
hatami.ha@stu-mail.um.ac.ir
1
Ferdowsi University of Mashhad
AUTHOR
Alireza
Karimi
karimi-a@um.ac.ir
2
Ferdowsi University of Mashhad
LEAD_AUTHOR
Amir
Fotovat
afotovat@um.ac.ir
3
Ferdowsi University of Mashhad
AUTHOR
Amir
Lakzian
alakzian@yahoo.com
4
Ferdowsi University of Mashhad
AUTHOR
Barber, S.A. (1995). Soil Nutrient Bioavailability: A Mechanistic Approach. (2th ed.). New York: Wiley.
1
Bertsch, P.M. and Thomas, G.W. (1985). Potassium status of temperate region soils. In R.D Munson. (Ed.) Potassium in Agriculture. (pp. 131-162) Am. Soc. Agron., Crop Sci. Soc. Am. and Soil Sci. Soc. Am., Madison, Wisconsin, USA.
2
Carey, P.L. and Metherell, A.K. (2003). Rates of release of non-exchangeable potassium in New Zealand soils measured by a modified sodium tetraphenyl-boron method. New Zealand Journal of Agricultural Research, 46, 185-197.
3
Cassman, K.G., Bryant, D.C. and Roberts. B.A. (1990). Comparison of soil test methods for predicting cotton response to soil and fertilizer potassium on potassium fixing soils. Communications in Soil Science and Plant Analysis, 21, 1727–1743.
4
Cox, A. E., Joern, B. C. and Roth. C. B. (1996). Nonexchangeable ammonium and potassium in soils with a modified sodium tetraphenylboron method. Soil Science Society of America Journal, 60, 114-120.
5
Cox, A.E. and Joern, B.C. (1997). Release kinetics of nonexchangeable potassium by sodium tetraphenylboron in midwestern soils. Soil Science, 162, 588–598.
6
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7
Darunsontaya, T., Suddhiprakarn, A., Kheoruenromne, I. and Gilkes, R.J. (2010). The kinetics of potassium release to sodium tetraphenylboron solution from the clay fraction of highly weathered soils. Applied Clay Science, 50, 376-385.
8
Dhillon, S.K. and Dhillon, K.S. (1990). Kinetics of release of non-exchangeable potassium by cation-saturated resins from red (Alfisols), black (Vertisols) and Alluvial (Inceptisols) soils of India. Geoderma, 47, 283–300.
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Dhillon, S.K. and Dhillon, K.S. (1992). Kinetics of release of potassium by sodium tetraphenylboron from some top soil samples of Red (Alfisols), Black (Vertisols) and Alluvial (Inceptisols and Entisols) soils of India. Nutrition Cycling in Agroecosystems, 32, 135–138.
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14
Hosseinpur, A.R. (2004). Evaluation of the capability of extractants in determining garlic available K for Certain Soils in Hamadan. Journal of Science and Technology of Agriculture and Natural Resources, Water and Soil Science, 8, 45-56. In Farsi.
15
Hosseinpur, A.R. and Motaghian, H.R. (2013). Application of kinetic models in describing Soil potassium release characteristics and their correlations with potassium extracted by chemical method. Pedosphere, 23, 482–492.
16
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18
Martin, H.W. and Sparks, D. L. (1985). On the behavior of nonexchangeable potassium in soils. Communications in Soil Science and Plant Analysis, 1, 133–162.
19
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20
Mehta, S.C., Meel, P.K., Grewal, K.S. and Mahendra, S. (1995). Release of non-exchangeable potassium in entisols. Journal of Indian Society Soil Science, 43, 351-356.
21
Mengel, K., and Uhlenbecker, K. (1993).Determination of available interlayer potassium and its uptake by ryegrass. Soil Science Society of America Journal, 57, 561–566.
22
Norouzi, S. and Khademi, H. (2009). Potassium release from muscovite and phlogopite as influenced by selected organic acids. Journal of Water and Soil, 23(1), 263-273. In Farsi.
23
Pal, D.K., Srivastava, P., Durge, S.L. and Bhattacharyya, T. (2001). Role of weathering of fine-grained micas in potassium management of Indian soils. Applied Clay Science, 20, 39-52.
24
Paknnejad, A., Salimpour, S. and Sobhan Ardakani, M. (2005). Kinetic release of nonexchangeable potassium in calcareous soils using revised NaBPh4 method. In: Proceedings of 9th Soil Science Congress of Iran, 6-8 Aug., Tehran, pp. 452- 454.
25
Portela, E. A. C. (1993). Potassium supplying capacity of northeastern Portugese soils. Plant Soil, 154:13–20.
26
Reed, M. G. and Scott, A. D. (1962). Kinetics of Potassium release from biotite and muscovite in sodiumtetraphenylboron solution. Soil Science Society of America. Proceedings, 25, 437-444.
27
Scott, A.D. and Reed, M.G. 1962. Chemical extraction of potassium from soils and micaceous minerals with solution containing sodium tetraphenylboron. II. Biotite. Soil Science Society of America Proceedings, 26: 41-45.
28
Shahbazi, K. and Bazargan, K. (2010). Kinetics of nonexchangeable potassium release from soils by sodium tetra phenyl boron method. Journal of Soil and Water Research, 41, 1-10. In Farsi.
29
Singh, M., Singh, V.P. and Damodar Reddy, D. (2002). Potassium balance and release kinetics under continuous rice–wheat cropping system in Vertisol. Field Crops Research, 77, 81-91.
30
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Sparks, D.L. 1980. Chemistry of soil potassium in Atlantic coastal plain soils. A review. Communications in Soil Science and Plant Analysis, 11, 435-449.
32
Sparks, D.L. (1987). Potassium dynamics in soils. Advanced in Soil Science, 6, 1-63.
33
Tofighi, H. (1999). Comparison of four chemical extractants for estimation of available potassium in paddy soil of north of Iran. Iranian Journal of Agriculture Science, 30(2), 631-648. In Farsi.
34
Wang, H.Y., Sun, H.X., Zhou, J.M., Cheng, W., Du, C.W. and Chen, X.Q. (2010). Evaluating plant-available potassium in different soils using a modified sodium tetraphenylboron method. Soil Science, 175, 544-551.
35
ORIGINAL_ARTICLE
The application of social network analysis in assessment of the capacity
of local communities for the establishment of water resources co-management
(Case study: Sarab-e Shah Hossein village, Razin watershed, Kermanshah)
Increasing demand on water resources has led to the challenges related to increased water stress and exacerbate conflicts, disputes and lack of collaboration between the various stakeholders there. The social evaluation of local beneficiaries according to the method network analysis to identify the challenges and opportunities that advance planning and sustainable management of water resources is required. The social capital of local beneficiaries using social network analysis approach is examined in Sarab-e Shah Hossein Village of the Razin watershed located in Kermanshah province. The results indicate a high level of social capital based on trust and Participation relations and cohesion and stability of the network is very strong in against of tensions and crises are evaluated. Also the high degree of unity and Solidarity among the people will cause cost and time of implementation of cooperative water resources to be reduced. It can be argued that, based on high levels of trust, collaboration, cohesion and social capital among the people of the village, a successful water resources co-management is expected to be operating. Moreover, successful water resources in the local level is impossible without the social monitoring of stakeholders and this method is effective in achieving successful water resources co-management at the local level.
https://ijswr.ut.ac.ir/article_58343_3633a7c9eb618eef72c5d8fa5baf3c77.pdf
2016-07-22
387
395
10.22059/ijswr.2016.58343
Social capital
trust
Collaboration
Social solidarity
Sustainable management of water resources
Fatemeh
Salari
fatemehsalari@ut.ac.ir
1
Faculty of Natural Resources, University of Tehran.
AUTHOR
Mehdi
Ghorbani
mehghorbani@ut.ac.ir
2
Faculty of Natural Resources, University of Tehran.
LEAD_AUTHOR
Arash
Malekian
malekian@ut.ac.ir
3
Faculty of Natural Resources, University of Tehran
AUTHOR
Hedayat
Fahmi
hedayat_fahmi@yahoo.com
4
Faculty Member, of Water and Waste Water Macro Planning Bureau of Ministry of Energy
AUTHOR
Barnes-Mauthe, M., Allen, S. D., Gray, S. A. and Leung, P. S. (2013). The influence of ethnic diversity on social network structure in a common-pool resource system: implications for collaborative management. Ecology and Society 18(1): 23.
1
Bastani, S. and Raeisi, M. (2012). Social Network Analysis as a Method: Using Whole Network Approach for Studying FOSS Communities, Journal of Iranian Social Studies, 14 (2). (In Farsi).
2
Berkes, F. (2010). Devolution of environment and resources governance: trends and future. Environ. Conserv. 37, 489e500.
3
Bhagavatula, S., Elfring, T., Tilburg, A., Gerhard, G. and Bunt, V. (2010). How Social and Human Capital Influence Opportunity Recognition and Resource Mobilization in India's Hand loom Industry, Journal of Business Venturing, 25(3) 245-260.
4
Bodin, O. and Prell, C. (2011). Social network in natural resources management. Cambridge University Press.
5
Borgatti, S. P., Everett, M.G. and Freeman, L. C. (2002). UCINET for Windows: Software for Social Network Analysis, Harvard, MA: Analytic Technologies.
6
Braga, B., Chartres, C., Cosgrove,W. J., da Cunha, L.V., Gleick, P.H., Kabat, P., Ait Kadi, M., Loucks, D.P., Lundqvist, J., Narain, S. and Xia, J. (2014). Water and the Future of Humanity. Calouste Gulbenkian Foundation Avenida de Berna 45A. 1067-001 Lisbon , Portugal.
7
Burt, R. 2003. The social capital of structural holes. Pages 148-189 in M. F. Guillen, R. Collins, P. England, and M. Meyer, editors. The new economic sociology: developments in an emerging field. Russell Sage Foundation, New York, New York,USA.
8
Caniato, M., Vaccari, M., Visvanathan, Ch. and Zurbrügg, Christian. (2014). Using social network and stakeholder analysis to help evaluate infectious waste management: A step towards a holistic assessment. Waste Management.34(5), Pages 938-951.
9
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10
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11
Ebrahimi Azarkharan, F., Ghorbani, M., Salajegheh, A. and Mohseni Saravi, M. (2014). Social Network Analysis of Local Stakeholders in Action Plan for Water Resources Co-Management (Case study: Jajrood River in Latian watershed, Darbandsar village). Iran- Watershed management science Engineering. 8(25). 47-56.(In Farsi).
12
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13
Gaotri, H. (1986). Popular Participation in Development, Paris: Unesco.
14
Ghorbani, M. (2012). The role of social networks in operation mechanisms of Rangeland (Case Study: Taleghan area), Ph.D. Dissertation, Department of Natural Resources, Tehran University, 430 pages. (In Farsi).
15
Ghorbani, M. (2014). network analysis; modeling, policy-making and planning of natural resources co-management. University of Tehran and the Department of Forest, Rangeland and Watershed Management. (In farsi).
16
Ghorbani, M. (2015a). Monitoring and Evaluation Toolkit of Social and Policy Networks aimed at empowerment local communities and land management. 1-18. (In Farsi).
17
Ghorbani, M. (2015b). Analysis and Assessment of the Social-Policy Networks of Grassroots Association, Institutions and Sustainable Development Funds (Sarayan District- South Khorasan- RFLDL project).298p. (In Farsi).
18
Hahn, T., Olsson, P., Folke, C. and Johnsson, k. (2006). Trust – building, Knowledge Generation and Organization Innovations: The Role of a Bridging Organization for Adaptive Co-Management of a Wetland Landscape around Kristianstad, Sweden. Human Ecology. 34(4). 573-592.
19
Hanneman, R.A. and Riddle, M. (2005). Introduction to social network methods, University of California Riverside, California.
20
Hatala, J. P. (2006). Social Network Analysis in Human Resource Development: A New Methodology. Human Resource Development Review. 5(1).45-71.
21
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22
Khanh, H.L.P. (2011). The Role of Social Capital to Access Rural Credit: A case study at Dinh Cu and Van Quat Dong village in coastal of Thua Thien Hue province- Vietnam, Department of Urban and Rural Development, Swedish University of Agricultural sciences, Master Thesis No 56.
23
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24
Lienert, J., Schnetzer, F..and Ingold, K. (2013). Stakeholder analysis combined with social network analysis provides fine-grained insights into water infrastructure planning processes. Journal of Environmental Management 125. 134-148
25
Ming’ate, F.L. M., Rennieb, H. G. and Memonc, A. (2014). landusepol Potential for co-management approaches to strengthen livelihoods of forest dependent communities: A Kenyan case. Land Use Policy 41, 304-312.
26
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27
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28
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31
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32
Pretty, J. and Ward, H. (2001). Social Capital and the Environment. Journal of World Development, 29(2), 209–227.
33
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34
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35
Salari, F., Ghorbani, M. Malekiam, A. (2015a). Social Monitoring in Local Stakeholders Network to Water Resources Local Governance (Case Study: Razin Watershed, Kermanshah City). Rangeland and Watershed management. 68(2). 287-305.(In Farsi).
36
Salari, F., Ghorbani, M., Malekiam, A. Fahmi, H. (2015b). Social Network Analysis of Local Beneficiaries and Social Capital in Water Resources Co-Management (Case study: watershed Razin of Kermanshah city). Iran- Watershed management science Engineering. 8(29). 35-46. (In Farsi).
37
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38
UNDP (2007). Water Governance Facility. http://www.watergovernance.org
39
Vignola, R., McDaniels, T.L. and Scholz, R.W. (2013). Governance structures for ecosystem-based adaptation: Using policy network analysis to identify key organizations for bridging information across scales and policy areas. Enviromental sciens & policy, 31.71-84.
40
Wasserman, S. and Faust, F. (1994). Social Network Analysis: Methods and applications, Cambridge, MA: Cambridge University Press. 358 p.
41
Woolcock, M. (2011).What Distinctive Contribution Can Social Cohesion Make to Development Theory, Research and Policy. World Bank, OECD Conference, Paris.
42
ORIGINAL_ARTICLE
Evaluate of subsurface drainage performance at second crop of paddy field (Case study: Triticale in physical model scale)
In order to evaluate the performance of subsurface drainage, a study at physical model scale in condition of second crop paddy fields was done. In the physical model, drains were installed in two depths 40 (D40) and 60 (D60) cm at two separate boxes and triticale was cultivated after rice harvest. In the time of rain, drainage sample parameters include EC, SAR, pH and TSS were measured in the laboratory. The water table was read by piezometer. The results showed that with increase in drainage depth, EC was increase and SAR value declined. Trend of EC was decreasing throughout the experiment, so that EC value at the end of experiment period for two drainages D40 and D60 decreased with a rate of 53% and 8% compared to the start of period. TSS values and trend throughout the experiment demonstrates the use of geotextile at the roles of its cover. It was found that the drainage installed at a depth of 40 cm can be more successful in the control of soil drainage and prevent waterlogging.
https://ijswr.ut.ac.ir/article_58344_43bbb6ef91a402bb2d0b2cde8158fe56.pdf
2016-07-22
397
405
10.22059/ijswr.2016.58344
Environmental effect
drainage performance index
salinity
drainage response factor
sodium adsorption ratio
Seyed Mohammad Rasoul
Moazeni
s.rasool7@yahoo.com
1
دانشجوی کارشناسی ارشد آبیاری و زهکشی گروه مهندسی آب دانشکده علوم کشاورزی دانشگاه گیلان
AUTHOR
Maryam
Navabian
navabian@guilan.ac.ir
2
هیات علمی / دانشگاه گیلان- دانشکده علوم کشاورزی گروه مهندسی آب
LEAD_AUTHOR
Mahdi
Esmaeili Varaki
esmaeili@guilan.ac.ir
3
استادیار گروه مهندسی آب دانشکده علوم کشاورزی دانشگاه گیلان
AUTHOR
Aslani, F., Nazemi, A., Sadreddini, A., Fakherifard, A. and Ghorbani, M.A. (2010). Underground drainage depth and distance estimates based on drainage water quality. Journal of Soil and Water Research, 41(2), 139-146. (In Farsi).
1
Bahceci, I., Dinc, N., Tari, A. F., Agar, A. I. and Sonmez, B. (2006). Water and salt balance studies, using SaltMod, to improve subsurface drainage design in the Konya-Cumra Plain, Turkey. Agricultural Water Management, 85(3), 261-271.
2
Hornbuckle, J.W., Christen, E,W., and Faulkner, R.D. (2007). Evaluating a multi-level subsurface drainage system for improved drainage water quality. Journal of Agricultural water management, 89(3), 208-216.
3
Karimipashaky, Sh., Mirhadi, S. M. J., Shahdi, A. and Rabiiee, M. (2012). A Study on the Effects of Nitrogen and Phosphorus Fertilizers levels on the Morphological Characteristics, Qualitative and Quantitative Yield of Triticale in Rasht, Iran. Crop Production In Environmental Stress, 4(3), 13-25. (In Farsi).
4
Lelley, T. (2006). Triticale: A Low-input Cereal with Untapped Potential. p. 398-430. In Singh, J. R. (Ed.) Genetic Resources Choromosome Engineering and Crop Improvement. CRC Taylor.
5
Masoudi, S. A. and Liaghat, A. (2013). Feasibility of using rice husk instead of drain pipe and envelope material. Water and Irrigation Management, 3(1), 111-119. (In Farsi).
6
Naseri, A. and Arvahi, A. (2010). A Performance Evaluation of Subsurface Drainage System and Its Comparison with Traditional Drainage (Tide) in Date Palm Gardens of Abadan. Iranian Journal of Soil and Water Research, 40(1), 7-15. (In Farsi).
7
Nazari, B., Liaghat, A., Parsinezhad, M. and Naseri, A. (2008). Optimization the installation of subsurface drainage depth with economic and environmental considerations. In: 5th technical workshop on drainage and environment, 7 Nov., Tehran, Iran, pp. 107-123. (In Farsi).
8
Nozari, H., Azadi, S. and Ebrahimi, R. (2011). Assessment effect of distance and depth of drain on quantity and quality of drainage water output, using system dynamics analysis. In: 3rd National Conference of Irrigation and Drainage Networks, 1-3 Mar., Shahid chamran University, Ahvaz, Iran, pp. 1-10. (In Farsi).
9
Razi, F., Sotoodehnia, A., Daneshkar Arasteh, P. and Akram, M. (2012). A Laboratory Test on the Effect of Drain Installation Depth on Drain Water Salinity (from a Clay-Loam Soil Profile). Iranian Journal of Soil and Water Research, 43(3), 281-288. (In Farsi).
10
Rhoades, J. D. (1968). Mineral-weathering correction for estimating the sodium hazard of irrigation waters. Soil Science Society of America Journal, 32(5), 648-652.
11
Ritzema, H.P., Satyanarayana, T. V., Raman, S. and Boonstra. J. (2008). Subsurface drainage to combat waterlogging and salinity in irrigated lands in India: Lessons learned in farmers’fields. Agricultural Water Management, 95(3), 179-189.
12
Soltani, Sh. M., Hanafi, M. M., Karbalaei, M. T. and Khayambashi, B. (2013). Qualitative Land Suitability Evaluation for the Growth of Rice and off-seasons Crops as Rice Based Cropping System on Paddy Fields of Central Guilan, Iran. Indian Journal of Science and Technology, 6(10), 5395-5403.
13
Snakin V.V., Prisyazhanaya A.A., and Kovasc-Lang E. (2001). Soil liquid phase composition. Elsevier Science B. V., Amsterdam, the Netherlands. 88P.
14
Suarez, D. L. (1981). Relation between pHc and Sodium Adsorption Ratio (SAR) and on alternative method of estimating SAR of soil or Drainage water. Soil Science Society of America Journal, 45(3), 469-475.
15
Unger, I.M., Motavalli, P.P.,and Muzika, R.M. (2009). Changes in soil chemical properties with flooding: A field laboratory approach. Agriculture, Ecosystems & Environment, 131(1-2), 105-110.
16
ORIGINAL_ARTICLE
Evaluation of the Efficiency of Microbial Induced Carbonate Precipitation For Loose Sand Dunes Fixation
Wind erosion is one of the main factors in soil and environment degradations and air pollution in arid and semi-arid areas. Existing methods of soil erosion control, including oil and chemical soil stabilizers, are too costly and they introduce toxic materials into the soil with significant environmental impact. Therefore, this research was conducted to determine the effectiveness of microbial induced calcite precipitation (MICP) as a biological and environmentally friendly method to improve the erosion resistance of loose sand dunes. For this purpose, the erosion of biocemented soil samples was measured experimentally in a wind tunnel under the wind velocities ranging from 10 to 55 kmh-1at a height of 10 cm above the tunnel floor. Results demonstrated that the weight loss of MICP-treated samples relative to the weight loss of control treatment was significantly decreased at all velocities. The effect of biological treatment on wind erosion control was even superior at the higher velocities. Erosion rate of MICP-treated samples was 2.13 against 240 kgm-2h-1 at the velocity of 55 km.h-1. The penetration resistance of the MICP-treated soil samples was observed up to three times higher than from control treatment, indicating a significant improvement of surface resistance in biologically treated samples. The result of SEM and XRD analysis shows that CaCO3 was mainly precipitated as vaterite crystals forming point-to-point contacts between the sand particles and improving surface resistance against wind shear velocity.
https://ijswr.ut.ac.ir/article_58345_da605402bce66f7371e37e3490bbabd0.pdf
2016-07-22
407
415
10.22059/ijswr.2016.58345
Biocement
MICP
Wind erosion control
penetration resistance
Mahdi
Maleki-Kakelar
k.mahdi.maleki@gmail.com
1
دانشجوی دکتری گروه مهندسی شیمی دانشگاه صنعتی سهند
AUTHOR
Sirous
Ebrahimi
sirous.ebrahimi@epfl.ch
2
رئیس مرکز تحقیقات بیوتکنولوژی دانشگاه صنعتی سهند
LEAD_AUTHOR
Farrokh
Asadzadeh
farrokhasadzadeh@gmail.com
3
استادیار گروه علوم خاک دانشگاه ارومیه
AUTHOR
Mehrdad
Emami Tarbizi
m.emami@sut.ac.ir
4
استادیار مهندسی عمران، مرکز تحقیقات ژئوتکنیک، دانشکده مهندسی عمران، دانشگاه صنعتی سهند تبریز
AUTHOR
Armbrust, D., and Dickerson, J. (1971). Temporary wind erosion control: cost and effectiveness of 34 commercial materials. Journal of soil and water conservation 26, 154-157.
1
Armbrust, D., and Lyles, L. (1975) Soil stabilizers to control wind erosion. In W.R. Gardner and W.C. Moldenhauer (Eds.), Soil Conditioners (pp. 77-82). Soil Science Society of America Special Publication. No.7. Madison, WI.
2
Bang, S. C., Min, S. H., Bang, S. S. (2011). KGS Awards Lectures: Application of Microbiologically Induced Soil Stabilization Technique for Dust Suppression. International Journal of Geo-Engineering 3, 27-37.
3
De Muynck, W., Debrouwer, D., De Belie, N., and Verstraete, W. (2008). Bacterial carbonate precipitation improves the durability of cementitious materials. Cement and concrete Research 38, 1005-1014.
4
DeJong, J. T., Mortensen, B. M., Martinez, B. C., and Nelson, D. C. (2010). Bio-mediated soil improvement. Ecological Engineering 36, 197-210.
5
Diouf, B., Skidmore, E., Layton, J., and Hagen, L. (1990). Stabilizing fine sand by adding clay: laboratory wind tunnel study. Soil technology 3, 21-31.
6
Fryrear, D. W., and Skidmore, E. (1985). Methods for controlling wind erosion. In R. F. Follett and B. A. Stewart (Eds.) Soil Erosion and Crop Productivity (pp.443-57). Madison: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America.
7
Fujita, Y., Taylor, J. L., Wendt, L. M., Reed, D. W., and Smith, R. W. (2010). Evaluating the potential of native ureolytic microbes to remediate a 90Sr contaminated environment. Environmental science & technology 44, 7652-7658.
8
Gillette, D. A., Adams, J., Endo, A., Smith, D., and Kihl, R. (1980). Threshold velocities for input of soil particles into the air by desert soils. Journal of Geophysical Research: Oceans (1978–2012) 85, 5621-5630.
9
Gillette, D. A., Adams, J., Muhs, D., and Kihl, R. (1982). Threshold friction velocities and rupture moduli for crusted desert soils for the input of soil particles into the air. Journal of Geophysical Research: Oceans (1978–2012) 87, 9003-9015.
10
Goudie, A. S., and Middleton, N. J. (2006). Dust Storm Control. In A. Goudie and N. J. Middleton (Eds. ), Desert Dust in the Global System (Chapter 8). (pp. 193-199). Springer Science & Business Media.
11
Hammes, F., Seka, A., Van Hege, K., Van de Wiele, T., Vanderdeelen, J., Siciliano, S. D., and Verstraete, W. (2003). Calcium removal from industrial wastewater by bio‐catalytic CaCO3 precipitation. Journal of Chemical Technology and Biotechnology 78, 670-677.
12
Hammes, F., and Verstraete, W. (2002). Key roles of pH and calcium metabolism in microbial carbonate precipitation. Reviews in environmental science and biotechnology 1, 3-7.
13
Hazirei, F., and Zare Ernani, M. (2013). Investigation of Effect of Clay-Lime Mulch forSand Dunes Fixation. Journal of Water and Soil 27, 373-380.
14
He J.-J., Cai, Q.-G., and Tang, Z.-J. (2008). Wind tunnel experimental study on the effect of PAM on soil wind erosion control. Environmental monitoring and assessment 145, 185-193.
15
Lian, B., Hu, Q., Chen, J., Ji, J., and Teng, H. H. (2006). Carbonate biomineralization induced by soil bacterium Bacillus megaterium. Geochimica et Cosmochimica Acta 70, 5522-5535.
16
Lyles, L., Schrandt, R., and Schmeidler, N. (1974). Commercial soil stabilizers for temporary wind-erosion control. Trans. ASAE 17, 1015-1019.
17
Majdi, H., Karimian-Eghbal, M., Karimzadeh, H., and Jalalian, A. (2006). Effect of Different Clay Mulches on the Amount of Wind Eroded Materials. JWSS-Isfahan University of Technology 10, 137-149.
18
Meyer, F., Bang, S., Min, S., Stetler, L., and Bang, S. (2011). Microbiologically-Induced Soil Stabilization: Application of Sporosarcina pasteurii for Fugitive Dust Control. In proceedings of Geo-Frontiers 2011@ sAdvances in Geotechnical Engineering, pp. 4002-4011. ASCE.
19
Movahedan, M., Abbasi, N., and Keramati, M. (2012). Wind erosion control of soils using polymeric materials. Eurasian Journal of Soil Science 1 (2) 81 –86.
20
Shulga, G., and Betkers, T. (2011). Lignin-based dust suppressant and its effect on the properties of light soil. In "Proceedings of the 8th International Conference „Environmental Engineering", pp. 19-20.
21
Tiano, P., Biagiotti, L., and Mastromei, G. (1999). Bacterial bio-mediated calcite precipitation for monumental stones conservation: methods of evaluation. Journal of microbiological methods 36, 139-145.
22
van Paassen, L. A., Ghose, R., van der Linden, T. J., van der Star, W. R., and van Loosdrecht, M. C. (2010). Quantifying biomediated ground improvement by ureolysis: large-scale biogrout experiment. Journal of Geotechnical and Geoenvironmental Engineering 136, 1721-1728.
23
Van Pelt, R., and Zobeck, T. (2004). Effects of Polyacrylamide, Cover Crops, and Crop Residue Management on Wind Erosion. In proceedings of 13th International Soil Conservation Organisation Conference (ISCO), July 2004. Brisbane, Australia, pp. 1-4.
24
Whiffin, V. S., van Paassen, L. A., and Harkes, M. P. (2007). Microbial carbonate precipitation as a soil improvement technique. Geomicrobiology Journal 24, 417-423.
25
Wiktor, V., and Jonkers, H. M. (2011). Quantification of crack-healing in novel bacteria-based self-healing concrete. Cement and Concrete Composites 33, 763-770.
26
ORIGINAL_ARTICLE
Effect of thermal and washing methods on remediation of a clay soil contaminated with gasoline
In this work, remediation of a contaminated clay soil with gasoline was studied through experimental tests by thermal and washing methods. A natural clay soil was contaminated artificially by different percent of (5% and 10%) gasoline. The contaminated soil was remitted at different temperatures (50, 100 and 1500 C). In addition, washing method was conducted on contaminated samples by using two kinds of surfactants (SDS and Tween 80). Experimental tests were including gradation, Atterberg limits, compaction and uniaxial compression tests which were performed on samples of natural, contaminated and remediation soil. Experimental results showed that adding gasoline to natural soil cause changes in physical and mechanical properties of soil and these changes are functions of gasoline percent. The results also showed that both thermal and washing techniques are effective in remediation of soil particularly for soil contaminated with 5% gasoline but the effect of them, and particularly surfactants, is reduced by increasing the percent of gasoline.
https://ijswr.ut.ac.ir/article_58346_4ac54927d5fd5d73845cb5c9086e0e51.pdf
2016-07-22
417
425
10.22059/ijswr.2016.58346
Gasoline
Clay Soil
remediation
Thermal
washing
Mahmoud
Babalar
babalar@ut.ac.ir
1
University of Tehran
LEAD_AUTHOR
Ali
Raeesi Estabragh
raeesi@ut.ac.ir
2
Tehran university of agriculture and natural resources
AUTHOR
Jamal
Abdolahi Alibaik
jaabaik@ut.ac.ir
3
Tehran university of agriculture and natural resources
AUTHOR
gholam ali
Vakili
ghvakili5@ut.ac.ir
4
Tehran university of agriculture and natural resources
AUTHOR
Chu, W., and Kwan, C.Y. (2003), Remediation of Contaminated soil by a Solvent/Surfactant System. Chemosphere. 53, 9-15.
1
Eliss, W.D., Payne, J.R., Tatuni, A.N. and Freestone, F.J. (1984). The Development of Chemical Countermeasures for Hazardous Waste Contaminated soil. Preceding of the hazardous materials spills conference. pp.116-125.
2
EPA (1988). Must for USTs, A summary of the New Regulations for the Underground Storage Tank System. EPA, 530, UST-88,008. Office of underground storage tanks, U.S environmental protection agency, Washington, DC.
3
EPA (1985). Remedial Action at Waste Disposal Site. EPA-625, 6-85,006, Office of Research and Development, Handbook, EPA Hazardous Waste Engineering Research Laboratory, Cincinnati, OH.
4
Estabragh, A.R, Beytolahpour, I., Moradi, M.and Javadi, A.A. (2014). Consolidation Behavior of Two Fine-Grained Soils Contaminated by Glycerol and Ethanol. Engineering Geology. 178. 102-108.
5
Fang, M.Y. (1997). Introduction to Environmental Geotechnology, CRC press, FL.USA.
6
Fent, K., (2003). Ecotoxicological Problems Associated with Contaminated Sites. Toxicol. Lett. 140 (141), 353-365.
7
Golshan,M., Naseri, S.,Farzadkia, M., Esrafili, A.,Rezaei Kalantari, R. and Karimi Takanlu, L,. (2014) Performance Assessment of rhamnolipid MR01biosurfactant and Triton X-100 Chemical Surfactant in Removalof Phenanthrene from soil. Iranian Journal of Health and Environment. 7.(2), 143-156 .
8
Khosravi, E., Ghasemzadeh, H., Sabour, M.R.and Yazdani, H. (2013). Geotechnical Properties of Gas Oil-Contaminated Kaolinite. Engineering Geology. 166, 11-16.
9
Kiem, R., Knicker, H., Ligouis, B.and Kogel-knabner, I., (2003). Airborne Contaminants in the Refractory Organic Carbon Fraction of Arable Soils in Highly Industrialized Areas. Geoderma. 114, 109-137.
10
Meegoda, N.J. and Ratnaweera, P., (1995). Treatment of Oil Contaminated Soils for Identification and Classification. Geotechnical Testing Journal. 18, 41-49.
11
Mehrasebi, M., Baziar, M., Naddafi, K.,Mohammadian Fazli, M., and Assadi. A., (2013). Efficiency of Brij35 and Tween 80 Surfactants for Treatment of Gasoline Contaminated Soil. Iranian Journal of Health and Environment. 6(2), 211-220.
12
Moore, C.A.and Mitchell, J.K.(1974). Electromagnetic Forces and Soil Strength. Geotechnique. 24.(4), 627-640.
13
Mulligan, C.N., Yong, R.N.and Gibbs, B.F. (2001). Surfactant-Enhanced Remediation of Contaminated Soil: Review. Engineering Geology, 60,.371-380.
14
Pincus, H.J., Meegoda, N.J., and Ratnaweera, P.(1995). Treatment of Oil Contaminated Soil for Identification and Classification. Geotechnical Testing Journal. 1.18 (1), 41-49.
15
Ratnaweera, P.and Meegoda, J.N, (2005). Shear Strength and Stress-Strain Behaivior of Contaminated soil. Geotechnical Testing Journal. 22 (2), 1-8.
16
Schwarzenbach, A.R., Gschwend, P.M.and Imboden, D.M.(2003). Environmental Organic Chemistry. Second ed. J. Wiley and sons, New York.
17
Seyed Razavi., S.N., Khodadadi, A. and GanjiDoust., H.(2011).Treatment of Soil Contaminated with Crude-Oil using Biosurfactants. Journal of Environmental Studies. 37 (60), 107-116.
18
Singh, S.K., Srivastava, R.K. and Siby, J.(2009). Studies on Soil Contamination due to Used Motor Oil and its Remediation. Canadian Geotechnical Journal, 46, 1077-1083.
19
Sridharan, A.and Rao, G.(1979).Shear Strength of Saturated Clays and the Role of the Effective Stress Concept. Géotechnique. 2,177-193.
20
Wang, M.C., Benway, J.M., and Aray ssi, A.M. (1990). The Effect of Heating on Engineering Properties of Clays. Physico-Chemical Aspects of Soil and Related Materials. ASTM STP 1095, (139-158).
21
ORIGINAL_ARTICLE
Evaluation of Some Extraction for Determination of Corn Available Iron in Some Soils of East Azerbaijan Province
This research was conducted to evaluation of extraction methods for determining the available iron (Fe) and active Fe in corn plant (Zea mays L.) at 21 calcareous surface soil samples in the East Azerbaijan province. In a greenhouse experiment, corn plant single cross 704 cultivar has been cultivated with 3 replications. After 60 days, the plant growth parameters were measured. According to the results, DTPA and AB-DTPA had the highest linear correlation coefficient with growth indices of corn such as active Fe concentration, chlorophyll index, Fe content, fresh weight and shoot dry weight as well as with some physical and chemical properties of soils. AB-DTPA due to a correlation coefficient greater than DTPA and simultaneous extraction of multiple nutrients was chosen as the best extractant. On the average, rapid ammonium oxalate and AC-EDTA extracted the maximum and minimum amounts of Fe, respectively. The both of 1.5% o-phenanthroline and 1N HCl methods were suitable for measuring corn active Fe concentration. Significant correlation (r=0.66 ,p<0.01) was observed between the active Fe measured by o-phenanthroline and HCl , but o-phenanthroline method compared to HCl due to better correlation with growth indices and the extractable-Fe by DTPA and AB-DTPA methods was found to be superior.
https://ijswr.ut.ac.ir/article_58347_38f2398cef8cd0aa21e85c797d3383ec.pdf
2016-07-22
427
437
10.22059/ijswr.2016.58347
AB-DTPA
Corn
Calcareous soils
DTPA
Kamal
Khalkhal
kamal_soil_ms@yahoo.com
1
دانشجوی سابق کارشناسی ارشد
AUTHOR
Adel
Reyhanitabar
areyhani@tabrizu.ac.ir
2
دانشیار گروه علوم و مهندسی خاک دانشگاه تبریز
LEAD_AUTHOR
Nosratollah
Najafi
nanajafi@yahoo.com
3
دانشیار گروه علوم و مهندسی خاک دانشگاه تبریز
AUTHOR
Abadia, J., Millan, E., Montanes, L. and Heras, L. (1980). DTPA and NH4HCO3-DTPA extractable Fe, Mn and Zn levels in the Ebro Valley. Anales de la Estacion Experimental de Aula Dei, 15(1-2): 181-193.
1
Abadía, J., Monge, E., Montañés, L., and Heras, L. (1984). Extraction of iron from plant leaves by Fe (II) chelators. Journal of Plant Nutrition, 7(1-5): 777-784. [A1]
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Adiloglu, A. (2002). Determination of suitable chemical extraction methods for available iron content of the soils from Edirne province in Turkey. Journal of Central European Agriculture, 3 (3): 255-262.
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4
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7
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8
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9
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Jones, B. J. Jr. )2001(. Laboratory guide for conducting soil tests and plant analysis, (1th ed.). New York: CRC press.
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ORIGINAL_ARTICLE
Abstract
https://ijswr.ut.ac.ir/article_61925_c4f4721e349eeadfd2616881aa832e0c.pdf
2016-07-22
1
20
10.22059/ijswr.2016.61925