ORIGINAL_ARTICLE
Multivariate Flood Analysis Using Vine Copulas in Bazoft Watershed, Iran
In this study, we applied the vine copula structures for multivariate analysis of flood characteristics. For this purpose, the hydrographs of 98 flood events recorded at Landi station in Bazoft watershed, in Chaharmahal va Bakhtiari Province, were selected and the flood characteristics, including peak flood (P), flood volume (V), flood duration (D) and time to peak (T) were extracted. Then, the best fitted distribution on each variable was selected by Kolmogorov-Smirnov test. In the next phase, the C-vine and D-vine structure were created considering three (P,V and T/D) and four variables (P,D,T and V) in changeable orders. In this way, the flood volume and peak were considered in a constant combination, and flood duration or the time to peak were consideredchangeable in tri-variate joints. In the four-variable joints, different combinations of all four variables were used. We used Gumbel, Frank, Joe, Clayton, Gaussian and t-student copula functions to combine these variables. The results obtained from the theoretical joint were compared with the experimental joint of that compound. Results showed that the best permutations of C-vine and D-vine copulas are similar in trivariate models TPV, (NSE=0.913), and the Gumbel and Gaussian copulas have selected as the best-fitted copula at the edges. In four-variate cases, the best C-vine and D-vine structures were PVTD and PTVD, (NSE=0.989) and the Gumbel and Gaussian were the abundant copulas in both of C-vine and D-vine models. The results indicated that the four-variate vine structures have higher concordance with the empirical copula than the tri-variate structures.
https://jrwm.ut.ac.ir/article_80521_878249c415119d9e60614bfae7240281.pdf
2021-02-19
674
690
10.22059/jrwm.2021.314030.1548
Vine structure
Copula
Flood
Four-variate analysis
joint distribution
Sasan
Amini
sasan2005@gmail.com
1
Shahrekord University
AUTHOR
Rafat
Zare Bidaki
zare.rafat@nres.sku.ac.ir
2
استادیار، دانشکدۀمنابع طبیعی و علوم زمین، دانشگاه شهرکرد، ایران.
LEAD_AUTHOR
Rasoul
Mirabbasi
mirabbasi_r@yahoo.com
3
Assistant Professor, Department of Water Engineering, Shahrekord University
AUTHOR
Marym
Shafaei
m.shafaei65@gmail.com
4
Water Resources Allocation Expert in Ministry of Energy, Tehran, Iran.
AUTHOR
[1] Aas, K., Czado, C., Frigessi, A. and Bakken, H. (2009). Pair-copula constructions of multiple dependence. Insurance: Mathematics and Economics, 44(2), 182–198.
1
[2] Ayantobo, O. O., Li, Y. and Song, S. (2019). Multivariate drought frequency analysis using four-variate symmetric and asymmetric Archimedean copula functions. Water Resources Management, 33(1), 103–127.
2
[3] Bedford, T. and Cooke, R. M. (2002). Vines: A new graphical model for dependent random variables. Annals of Statistics, 1031–1068.
3
[4] Dayal, K. S., Deo, R. C. and Apan, A. A. (2019). Development of copula-statistical drought prediction model using the standardized precipitation-evapotranspiration index. In Handbook of Probabilistic Models. Elsevier Inc.
4
[5] Favre, A. C., Adlouni, S. El, Perreault, L., Thiémonge, N. and Bobée, B. (2004). Multivariate hydrological frequency analysis using copulas. Water Resources Research, 40(1), 1–12.
5
[6] Grimaldi, S. and Serinaldi, F. (2006). Asymmetric copula in multivariate flood frequency analysis. Advances in Water Resources, 29(8), 1155–1167.
6
[7] Jiang,C.,Xiong,L.,Yan,L., Dong, J. and Xu, C.Y. (2019). Multivariate hydrologic design methods under nonstationary conditions and application to engineering practice. Hydrology and Earth System Sciences, 23(3), 1683–1704.
7
[8] Joe, H. (1997). Multivariate models and multivariate dependence concepts. CRC Press.
8
[9] Latif, S. and Mustafa, F. (2020). Trivariate distribution modelling of flood characteristics using copula function—A case study for Kelantan River basin in Malaysia. AIMS Geosciences, 6(1), 92–130.
9
[10] Mirabbasi, R., Fakheri-Fard, A. and Dinpashoh, Y. (2012). Bivariate drought frequency analysis using the copula method. Theoretical and Applied Climatology, 108(1–2), 191–206.
10
[11] Nash, J. E. and Sutcliffe, J. V. (1970). ’ L ~ E Empirical or Analytical Approaeb. Journal of Hydrology, 10(3), 282–290.
11
[12] Nguyen-Huy, T., Deo, R. C., An-Vo, D. A., Mushtaq, S. and Khan, S. (2017). Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones. Agricultural Water Management, 191(September), 153–172.
12
[13] Pereira, G. and Veiga, Á. (2018). PAR(p)-vine copula based model for stochastic streamflow scenario generation. Stochastic Environmental Research and Risk Assessment, 32(3), 833–842.
13
[14] Salvadori, G. and De Michele, C. (2006). Statistical characterization of temporal structure of storms. Advances in Water Resources, 29(6), 827–842.
14
[15] Shafaei, M., Fakheri-Fard, A., Dinpashoh, Y., Mirabbasi, R. and De Michele, C. (2017). Modeling flood event characteristics using D-vine structures. Theoretical and Applied Climatology, 130(3–4), 713–724.
15
[16] Sklar, A., SKLAR, A. and Sklar, C. A. (1959). Fonctions de reprtition an dimensions et leursmarges.
16
[17] Snyder, W. M. (1962). Some possibilities for multivariate analysis in hydrologic studies. Journal of Geophysical Research, 67(2): 721–729.
17
[18] Wong, S. T., Gray, D. M. and Hydro-, D. (1958). Mean Annual Flood I N New England ’. 298–311.
18
[19] Vernieuwe, H., Vandenberghe, S., De Baets, B. and Verhoest, N. E. C. (2015). A continuous rainfall model based on vine copulas. Hydrology and Earth System Sciences, 19(6), 2685–2699.
19
[20] Zhang, L. and Singh, V. P. (2007). Trivariate flood frequency analysis using the Gumbel–Hougaard copula. Journal of Hydrologic Engineering, 12(4), 431–439.
20
ORIGINAL_ARTICLE
Evaluation of the Combination of ANFIS Model with Metaheuristic Optimization Algorithms in Predicting Dust Storms of Khuzestan Province
Due to the growing development of meta-models and their combination with optimization algorithms for modeling and predicting meteorological variables, in this research four metaheuristic optimization algorithms of Particle Swarm Optimization (PSO), Genetics Algorithms (GA), Ant Colony Optimization for Continuous Domains (ACOR) and Differential Evolutionary (DE) were combined with the adaptive neural-fuzzy inference system (ANFIS) model. The performance of four combined models developed with ANFIS model to predict the Frequency variables of Dust Stormy Days (FDSD) on a seasonal scale in Khuzestan province in the southwest of Iran was evaluated. For this purpose, hourly dust data and codes of the Word Meteorological Organization were used on a seasonal scale with a statistical period of 40 years (1980-2019) in seven synoptic stations of Khuzestan province. The results of good fit indices in the training and testing phase showed that there is no significant difference between the ANFIS method and other combined models used. R and RMSE values of the best combined model (ANFIS-PSO) from 0.88 to 0.97 and 0.10 to 0.19, respectively, and in the ANFIS model from 0.83 to 0.94 and 0.11 to 21, respectively, were variable. The results also showed that the combination of optimization algorithms used with the ANFIS model does not significantly improve the results of the model compared to the individual ANFIS model.
https://jrwm.ut.ac.ir/article_80529_b999714a122984385f6e167f8eeff5ff.pdf
2021-02-19
691
708
10.22059/jrwm.2020.311676.1540
ANFIS
Artificial Intelligence
Evolutionary algorithms
Genetic Algorithm
modeling
Mohammad
Ansari Ghojghar
m.ansari2014m@gmail.com
1
Ph.D. Candidate, Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.
LEAD_AUTHOR
Masoud
Pourgholam-Amiji
mpourgholam6@ut.ac.ir
2
Ph.D. Candidate, Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.
AUTHOR
Shahab
Araghinejad
araghinejad@ut.ac.ir
3
Associate Professor, Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.
AUTHOR
Banafsheh
Zahraie
bzahraie@ut.ac.ir
4
Associate Professor, School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran.
AUTHOR
Saman
Razavi
saman.razavi@usask.ca
5
Associate Professor, Department of Civil, Geological, and Environmental Engineering, School of Environment and Sustainability, University of Saskatchewan, Saskatoon, Canada.
AUTHOR
Ali
Salajegheh
salajegh@ut.ac.ir
6
Professor, Faculty of Natural Resources, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.
AUTHOR
[1] Abdolshahnejad, M., Khosravi, H., Nazari Samani, A. A., Zehtabian, G. R., & Alambaigi, M. (2020). Determining the Conceptual Framework of Dust Risk Based on Evaluating Resilience (Case Study: Southwest of Iran). Strategic Research Journal of Agricultural Sciences and Natural Resources, 5(1), 33-44. (In Persian)
1
[2] Annaty, M., Eghbalzadeh, A., & Hosseini, S. (2015). Hybrid ANFIS model for predicting scour depth using particle swarm optimization. Indian journal of science and technology, 8(22), 642-649.
2
[3] Ansari Ghojghar, M., Pourgholam-Amiji, M., Bazrafshan, J., Hosseini-Moghari, S. M., Liaghat, A., & Araghinejad, Sh. (2020). Performance Evaluation of Genetic Algorithm and GA-SA Hybrid Method in Forecasting Dust Storms (Case Study: Khuzestan Province). Iranian Journal of Soil and Water Research (Articles in Press). (In Persian)
3
[4] Araghinejad, S. (2013). Data-driven modeling: using MATLAB® in water resources and environmental engineering (Vol. 67). Springer Science & Business Media.
4
[5] Araghinejad, Sh., Ansari Ghojghar, M., Pourgholam-Amiji, M., Liaghat, A., & Bazrafshan, J. (2019). The Effect of Climate Fluctuation on Frequency of Dust Storms in Iran. Desert Ecosystem Engineering Journal, 7(21), 13-32. (In Persian)
5
[6] Azad, A., Karami, H., Farzin, S., Saeedian, A., Kashi, H., & Sayyahi, F. (2018). Prediction of water quality parameters using ANFIS optimized by intelligence algorithms (case study: Gorganrood River). KSCE Journal of Civil Engineering, 22(7), 2206-2213.
6
[7] Cao, R., Jiang, W., Yuan, L., Wang, W., Lv, Z., & Chen, Z. (2014). Inter-annual variations in vegetation and their response to climatic factors in the upper catchments of the Yellow River from 2000 to 2010. Journal of Geographical Sciences, 24(6), 963-979.
7
[8] Davis, L. (1991). Handbook of genetic algorithms.
8
[9] Dorigo, M. (1992). Optimization, learning and natural algorithms. PhD Thesis, Politecnico di Milano.
9
[10] Farajzadeh Asl, M., & Alizadeh, Kh. (2011). Spatial Analysis of Dust storm in Iran. The Journal of Spatial Planning, 15(1), 65-84. (In Persian)
10
[11] Goudie, A. S., & Middleton, N. J. (2006). Desert dust in the global system. Springer Science & Business Media.
11
[12] Hassanzadeh, Y., Abdi Kordani, A., & Fakheri Fard, A. (2012). Drought Forecasting Using Genetic Algorithm and Conjoined Model of Neural Network-Wavelet. Journal of Water and Wastewater, 23(3), 48-59. (In Persian)
12
[13] Jalalkamali, A. (2015). Using of hybrid fuzzy models to predict spatiotemporal groundwater quality parameters. Earth Science Informatics, 8(4), 885-894.
13
[14] Jang, J. S. (1993). ANFIS: adaptive-network-based fuzzy inference system. IEEE transactions on systems, man, and cybernetics, 23(3), 665-685.
14
[15] Mahmoodimahpash, N., & Souri, B. (2020). Detecting origin of dust-fall using ions ratio and morphology of the particles in western Iran. Journal of Natural Environment, 73(2), 355-367. (In Persian)
15
[16] Mehrabi, Sh., Soltani, S., & Jafari, R. (2015). Investigating the Relationship between Climatic Parameters and the Exposure of Greenhouses (Case Study: Khuzestan Province). Journal of Water and Soil Science, 19(71), 69-80. (In Persian)
16
[17] Mehri, Y., Mehri, M., & Soltani, J. (2020). Evaluation of combined Models with Optimization Approach of PSO and GA in ANFIS for Predicting of Dispersion Coefficient in Rivers. Water and Irrigation Management, 10(1), 45-59. (In Persian)
17
[18] Mohammadi Ghaleni, M., & Ebrahimi, K. (2013). Evaluation of direct search and genetic algorithms in optimization of muskingum nonlinear model parameters - a flooding of Karoun river, Iran. Water and Irrigation Management, 2(2), 1-12. (In Persian)
18
[19] Mozafari, Gh. A., Shafie, Sh., & Hemati, H. R.(2016). Predicting monthly precipitation of Kermanshah synoptic station using the hybrid model of neural network and wavelet. Journal of Water and Soil Conservation, 22(6), 135-152. (In Persian)
19
[20] Nabizadeh, M., Mosaedi, A., & Dehghani, A. (2012). Intelligent estimation of stream flow by Adaptive Neuro-Fuzzy Inference System. Water and Irrigation Management, 2(1), 69-80. (In Persian)
20
[21] Nadiri, A. A., Taherkhani, Z., & Sadeghi Aghdam, F. (2017). Prediction of ground water level of Bostan Abad using combining artificial intelligence models. Iran Water Resources Research, 13(3), 43-55. (In Persian)
21
[22] O’Loingsigh, T., McTainsh, G. H., Tews, E. K., Strong, C. L., Leys, J. F., Shinkfield, P., & Tapper, N. J. (2014). The Dust Storm Index (DSI): a method for monitoring broadscale wind erosion using meteorological records. Aeolian Research, 12, 29-40.
22
[23] Prudêncio, R. B., & Ludermir, T. B. (2003). Neural network hybrid learning: genetic algorithms & Levenberg-Marquardt. In Between Data Science and Applied Data Analysis (pp. 464-472). Springer, Berlin, Heidelberg.
23
[24] Rashki, A., Kaskaoutis, D. G., Goudie, A. S., & Kahn, R. A. (2013). Dryness of ephemeral lakes and consequences for dust activity: the case of the Hamoun drainage basin, southeastern Iran. Science of the total environment, 463, 552-564.
24
[25] Sepehri, M, Ildoromi, A. R., Hosseini, S. Z., Nori, H., Mohammadzade, F., & Artimani, M. M. (2018). The combination of neural networks and genetic algorithms is a way to estimate the Peak flood. Iranian Journal of Watershed Management Science and Engineering, 11(39), 23-28. (In Persian)
25
[26] Shafaei, M., Fakheri Fard, A., Darbandi, S., Ghorbani, M. (2014). Prediction Daily Flow of Vanyar Station Using ANN and Wavelet Hybrid Procedure. Irrigation and Water Engineering, 4(2), 113-128. (In Persian)
26
[27] Shi, Y. (2001). Particle swarm optimization: developments, applications and resources. In Proceedings of the 2001 congress on evolutionary computation (IEEE Cat. No. 01TH8546), 1, 81-86.
27
[28] Sobhani, B., Safarian Zengir, V., & faizollahzadeh, S. (2020). Modeling and prediction of dust in western Iran. Physical Geography Research Quarterly, 52(1), 17-35. (In Persian)
28
[29] Socha, K., & Dorigo, M. (2008). Ant colony optimization for continuous domains. European journal of operational research, 185(3), 1155-1173.
29
[30] Sreedhara, B. M., Rao, M., & Mandal, S. (2019). Application of an evolutionary technique (PSO–SVM) and ANFIS in clear-water scour depth prediction around bridge piers. Neural Computing and Applications, 31(11), 7335-7349.
30
[31] Storn, R., & Price, K. (1997). Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces. Journal of global optimization, 11(4), 341-359.
31
[32] Yarmoradi, Z., Nasiri, B., Mohammadi, Gh. H., & Karampour, M. (2018). Trend analysis of dusty day’s frequency in Eastern arts o Iran associated with Climate Fluctuations. Desert Ecosystem Engineering Journal, 7(18), 1-14. (In Persian)
32
Zeinali, B. (2016). Investigation of frequency changes trend of days with dust storms in western half of Iran. Journal of Natural Environment hazards, 5(7), 100-87. (In Persian)
33
ORIGINAL_ARTICLE
Calibration of SWMM Model in North catchment of Tehran
In this study SWMM software has been calibrated with real meteorological and hydrometric data at the North of Tehran basins and simulation parameters have been obtained. For this purpose, five rainfall events and runoff data related to these rainfalls, recorded at the outlet of Zargandeh catchment were used. This model is calibrated with three events and verified with two other events. Also, in this simulation the peaks of flood, outflow hydrographs, runoff volumes and peak flood times is obtained. The root mean square error are obtained for outlet hydrographs for the first to fifth events were 0.05, 0.22, 0.4, 0.37 and 0.16, and the Nash-Sutcliffe coefficient are obtained 0.91, 0.94, 0.93, 0.9 and 0.94, respectively. Also, the percentage of difference of the flood discharge peak modeling and observations for first to fifth events are calculated 7.33%, 9.69%, 5.8%, 5.6% and 9.93% and for runoff volume, this percentage difference are calculated -8.82%, -3.08%, 8.8%, -19.43% and 5.11%, respectively. Based on these results, the performance and application of this model to simulate runoff in this area is acceptable and can be used to manage and control urban runoff.
https://jrwm.ut.ac.ir/article_80530_1f00bb1dda6e7afdc80df84ffad6af2d.pdf
2021-02-19
709
724
10.22059/jrwm.2020.298685.1471
Rainfall-Runoff model
calibration and validation
Urban Catchment
SWMM model
Reza
Badizadegan
rbadizadegan@gmail.com
1
Water Engineering Department, ,Ferdowsi University of Mashhad
AUTHOR
Saeed Reza
Khodashenas
khodashenas@ferdowsi.um.ac.ir
2
Ferdowsi University of Mashhad
LEAD_AUTHOR
Kazem
Esmaili
esmaili@um.ac.ir
3
Water Engineering Department, Ferdowsi University of Mashhad
AUTHOR
[1] ASCE, (1992), Design & Construction of Urban Stormwater Management Systems, New York, NY.
1
[2] Badiezadeh, S., Bagremand, A. and Dehghani, A, A. (2015). Urban flood management by simulation of surface runoff using SWMM model in Gorgan city, Golestan Province- Iran. Journal of Water and Soil Conservatio. 22(4). 155-170.
2
[3] Chow, M. F., Yusop, Z. and Toriman, M. E. (2012). Modelling runoff quantity and quality in tropical urban catchments using Storm Water Management Model. International Journal of Environmental Science and Technology. 9. 737–748.
3
[4] Chow, V, T., Maidment, D, R. and Mays, L, W. (1988). Applied Hydrology. McGraw-Hill Book Company, inc. Publisher.
4
[5] Crawford, N.H. and Linsley, R.K., (1966). Digital Simulation in Hydrology: Stanford Watershed Model IV. Civil Engineering Department, Stanford University. Tech. Report No. 39.
5
[6] Huber, W. and Dickinson, R. (1988) Stormwater Management Model. User´s Manual. U.S. Environmental Research Agency. Office of Research and Development. Ver 4, Part A.
6
[7] Jinkang, D., Shunping, X., Youpeng, X. and Chong-Yu, X. (2007) Development and testing of a simple physically-based distributed rainfall-runoff model for storm runoff simulation in humid forested basins. Journal of Hydrology.336(3). 334-346.
7
[8] Karimi, V., Solaimani, K., Habibnejad, M. and Shahedi, K. (2015). Simulation of Flow in Open & Closed Conduits by EPA-SWMM Model (Case Study: Babolsar Urban Watershed). Journal of Watershed Management Research. 6 (11). 162-170.
8
[9] Khalighi Sigarodi, Sh., Rostami Khalaj, M., Mahdavi, M. and Salajegheh, A. (2015). Calibration and validation SWMM model in order to simulate urban runoff (Case Study: Imam Ali Town in Mashhad). 63(3).487-498.
9
[10] Kornecki, TS., Sabbagh GJ. and Storm DE. (1999) Evaluation of runoff, erosion and phosphorus modeling system-SIMPLE. Journal of the American Water Resources Association. 4. 807 - 820.
10
[11] Koudelak, P. and West, S. (2007). Sewerage network modelling in Latvia, use of InfoWorks CS and Storm Water Management Model 5 in Liepaja city. Water and Environment Journal. 22(2). 81-87.
11
[12] Mahdavi, M. (2005). Applied Hydrology, 4ed Edition, University of Tehran press.
12
[13] McCuen, R. (1996), Hydrology, FHWA-SA-96-067, Federal Highway Administration, Washington, DC.
13
[14] Moradi, M. and Darbandi, S. (2017). Approach for appraising spate risks in urban drainage systems using stormwater management model. Watershed Engineering and Management. 9(3). 276-291.
14
[15] Ovbiebo, T. and SHE, N. (1995) Urban runoff quality modeling in a subbasin of the Duwamish River using XP-SWMM. Proc. Watershed Management Symposium Held in San Antonio, Texas, USA. August 14-19. ASCE, New York. 320-329.
15
[16] Rossman, L. R. (2015). Storm Water Management Model User’s Manual Version 5.1. United States Environmental Protection Agency (EPA).
16
[17] Rostami, M., Mahdavi, M., Khalighi, Sh. and Salajeghe, A. (2012). Sensitivity Analysis of Variables Affecting on Urban Flooding Using SWMM Model. Journal of Watershed Management Research. 3 (5). 81-91.
17
[18] Santhi, C., Arnold, J.G., Williams, J.R., Dugas, W.A., Srinivasan, R. and Hauck, L.M. (2001). Validation of the SWAT model on a large river basin with point and nonpoint sources, Journal of the American Water Resources Association, 37(5). 1169-1188.
18
[19] Sourisseau, S., Basser, A., Perie, F. and Caquet, T. (2008). Calibration, validation and sensitivity analysis of an ecosystem model applied to artificial streams, Water Research, 42(4). 1167-1181.
19
[20] Tehran Engineering & Technical Consulting Org. (2011). Tehran Stormwater Management Master Plan. 2 (1) Meteorology.
20
[21] Tehran Engineering & Technical Consulting Org. (2011). Tehran Stormwater Management Master Plan. 2 (2, 3) Hydrology.
21
[22] Temprano, J. Arango, O. Cagiao, J. Suarez, J. and Tejero, I. (2006) Stormwater quality calibration by SWMM: a case study in northern Spain. Water SA 32(1). 55–63.
22
[23] Tsihrintzis, V. and Hamid, R. )1998(. Runoff quality prediction from small urban catchments using SWMM. Hydrol Process, 12: 2. 311-329.
23
ORIGINAL_ARTICLE
Analysis of Institutional Network of Resilience to Climate Change: Case of Ghezel Ozen Basin
The climate change phenomenon is considered as one of the important environmental challenges in the 21st century. The most impacts of this phenomenon are focused on industries and establishments such as agriculture and fishery that is depended on natural resources. Resilience considered as a practical approach for compatibility of this phenomenon and the creation of sustainable development. Since networks, especially formal networks such as institutional networks, can play a key role in creating and promoting resilience against climate change, the present study is conducted through a network analysis approach and with the aim of fundamental analyses in the field of resilience against climate change. The statistical population of the present study consists of the small beneficiary owners in Tarom County in Zanjan province. Through network analysis, the dominant statistical method of the research considered as the sociometry and extraction of network centrality indices. According to the findings, two agencies namely Agriculture Jihad Organization, and Banks and Credit and Financial Institution play a major role in the educational information network and technical services, respectively. In the financial facilities network, banks and credit and financial institutions, and the Agricultural Jihad Organization rank first and second in providing the financial services and consulting, respectively. The findings demonstrated that many institutions that can play a constructive role in the field of resilience against climate change, such as the insurance organization, have been secluded and marginalized.
https://jrwm.ut.ac.ir/article_80531_8f900043a061568f573cdde3eec5c685.pdf
2021-02-19
725
740
10.22059/jrwm.2021.297966.1469
resilience
climate change
Social network
Formal institutions
Mohammad
Chizari
mchizari@modares.ac.ir
1
Professor, Department of Agricultural Extension and Education, Tarbiat Modares University, Tehran, Iran
LEAD_AUTHOR
seyede somaye
Bathaiy
s.bathaiy@modares.ac.ir
2
Department of Agricultural Extension and Education, Tarbiat Modares University, Tehran, Iran
AUTHOR
Hasan
Sadighi
sadigh_h@modares.ac.ir
3
Department of Agricultural Extension and Education, Tarbiat Modares University, Tehran, Iran
AUTHOR
Amir
Alambeigi
alambaigi@ut.ac.ir
4
Agricultural extension and education, University of Tehran
AUTHOR
[1] Adger, W. N. (2000). Social and ecological resilience: are they related?. Progress in human geography, 24(3), 347-364.
1
[2] Adger, W. N. (2003). Social Capital, Collective Action, and Adaptation to Climate Change. Economic Geography, 79, 387-404.
2
[3] Alambeigi, A.and Malekli, M. (2019). Institutional Analysis of Drought Management in the Ghareh Chay Watershed in Saveh County: An Application of Social Network Analysis. Journal of Range and Watershed Management, 71(4), 1013-1027 .(In Persian)
3
[4] Bandiera, O. and Rasul, I. (2006). Social networks and technology adoption in northern Mozambique. The Economic Journal, 116(514), 869-902.
4
[5] Barnes, M. L., Bodin, Ö., Guerrero, A. M., McAllister, R. R., Alexander, S. M. and Robins, G. (2017). The social structural foundations of adaptation and transformation in social–ecological systems. Ecology and Society, 22(4).
5
[6] Berkes, F. and Ross, H. (2013). Community resilience: toward an integrated approach. Society & Natural Resources, 26(1), 5-20.
6
[7] Biggs, R., Schlüter, M. and Schoon, M. L. (Eds.). (2015). Principles for building resilience: sustaining ecosystem services in social-ecological systems. Cambridge University Press.
7
[8] Bisaro, A., Roggero, M. and Villamayor-Tomas, S. (2018). Institutional analysis in climate change adaptation research: A systematic literature review. Ecological economics, 151, 34-43.
8
[9] Bodin, Ö. And Prell, C. (Eds.). (2011). Social networks and natural resource management: uncovering the social fabric of environmental governance. Cambridge University Press.
9
[10] Bodin, Ö. And Tengö, M. (2012). Disentangling intangible social–ecological systems. Global Environmental Change, 22(2), 430-439.
10
[11] Boyd, E. and Folke, C. (Eds.). (2011). Adapting institutions: governance, complexity and social-ecological resilience. Cambridge University Press, Cambridge, UK.
11
[12] Brown, J., Alvarez, P., Byrd, K., Deswood, H., Elias, E. and Spiegal, S. (2017). Coping with historic drought in california Rangelands: developing a more effective institutional response. Rangelands, 39(2), 73-78.
12
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61
ORIGINAL_ARTICLE
Investigating soil qualitative properties affected by plant patches with different growth forms in Fasa Mianjangal region
Study of important soil properties and vegetation attributes can give us awareness of the potential of rangelands and make it possible to determine their condition. O In this regard, the present study was carried out with the aim of studying the structural and functional attributes of different growth forms on soil surface indices in the Mianjangal Catchment, Fasa. Eleven soil surface indicators were measured along three 100-meter transects using Landscape Function Analysis. The measured factors were classified to assess functional potentials (stability, infiltration, nutrient cycle). Structural attributes including number of patches, length and width of patches, the percentage of patch length to the transect length, patch area index and organization index were investigated. In general, four ecological patches including shrub, bush, grass and forb and the space between the patches (bare and litter) were identified in the study area. The organization index of patch area index were 0.41 and 0.03 in the study area respectively. The results showed that plant patches with different growth forms had different effects on ecosystem function. The growth form shrub had the highest stability, which had a significant difference with other growth forms. In terms of infiltration index in the study area, there were no significant differences between ecological patches with shrub and grass growth forms. Soil nutrient cycle also had a significant difference between ecological patches and also inter-patches. The shrub growth form had the highest amount of nutrient cycle.
https://jrwm.ut.ac.ir/article_80532_a02450beb4d386416cbad6e425bae187.pdf
2021-02-19
741
752
10.22059/jrwm.2020.302307.1505
Landscape function analysis
Plant patch
Water and soil conservation
biological control
Esfandiar
Jahantab
e.jahantab@fasau.ac.ir
1
Department of Range and Watershed Management, Faculty of Agriculture, Fasa University, Fasa, Iran
AUTHOR
Maryam
Zahedifar
mzahedifar@gmail.com
2
Department of Range and Watershed Management, Faculty of Agriculture, Fasa University, Fasa, Iran
AUTHOR
Mohsen
Farzin
m.farzin@yu.ac.ir
3
Department of Range and Watershed Management, Faculty of Agriculture and Natural Recourses, Yasooj University, Yasooj, Iran
LEAD_AUTHOR
[1] Bestelmeyer, BT., Ward, JP., Herrick, JE. and Tugel, A J. (2006). Fragmentation effects on soil aggregate stability in patchy arid grassland. Journal of Rangeland Ecology and Management, 59 (4), 406 - 415.
1
[2] Chamani, A., Heshmati, GhA. and Karimian, V. ( 2015). Evaluating soil surface indicators rangeland in shrubs different patches (Case Study: Gub Gugeh rangeland of Golestan province). Journal of Environmental Erosion Research, 16, 1-11. (In Persian)
2
[3] Forman, R. and Collinge, SK. (1995). The ‘spatial solution’ to conserving biodiversity in landscapes and regions. In Conservation of Faunal Diversity in Forested Landscapes. Edited by R. M. DeGraaf and R.I. Miller. Chapman and Hall, London, 537-568.
3
[4] Ghodsi, M., Mesdaghi, M. and Heshmati, Gh.A. (2012). Effect of different growth forms on soil surface features (Case study: Semi-steppe rangeland, Golestan National Park). Journal of Watershed Management Researches (Pajouhesh & Sazandegi), 93, 63-69. (In Persian)
4
[5] Heshmati, GH., Azimi, MS. and Ashouri, P. (2010). Assessment of Structural Characteristics of Fertilized Patch in Rangeland Ecosystems (Case Study: Ghareh Ghir and Maraveh Tapeh Rangelands of Golestan Province). Journal of Range and Watershed Management, 63 (3), 319-329. (In Persian)
5
[6] Heshmati, GhA. and Karimian, V. (2016). Comparing Ecological Functions of Northern and Southern landscapes of Darehkonari Khashab rangeland, Gachsaran County. Journal of Range and watershed Management, 69 (3), 575-585. (In Persian)
6
[7] Kakembo, V., Ndlela, S. and Cammeraat, E. (2012). Trends in vegetation patchiness loss and implications for landscape function: the case of Pteronia incana invasion in the Eastern Cape Province, South Africa. Journal of Land Degradation & Development, 23 (6), 548-556.
7
[8] Karimian, V. and Heshmati,Gh.A. (2017). Evaluation effects of Tree and shrub species (ziziphus spina cristi, ziziphus numolaria and Astragalus fasciculifolius)on the Soil Surface Indices in Winter Rangelands (case Study: Khashab Stream Rangelands, Southern Kohgiluyeh and Boyerahmad). Iranian Journal of Range and Desert Research, 24 (4), 730-741. (In Persian)
8
[9] Karimian, V. 2018. Studying Soil Surface Quality in Northern and Southern Slopes of Khahkaloon and Ahmadabad Vezg Rangelands, Boyerahmad County. Journal of Rangeland, 11 (4), 511-521. (In Persian)
9
[10] Kavandi Habib, R,. Heshmati, Gh.A. and Siroosi, H. (2014). Comparison of Ecological Patches' Potentials and Functions in Rangeland Ecosystems (Case Study: Qahavand Rangelands, Hamedan Province, Iran). Journal of Rangeland Science, 4 (3), 234-245.
10
[11] Khalasi Ahvazi, L. and Heshmati, Gh.A. (2013). Evaluating different patches, Using LFA method to control wind erosion (Case study: Hanitiyeh rangelands of Ahvaz city). Journal of Research Quarterly On Environmental Erosion Researches, 2 (8), 62-76.
11
[12] Lotfi Anari, P., Heshmati, GA. and Bahremand, A. (2010). The Effect of Different Patches and Interpatch on Infiltration Rate in an Arid Shrub land Ecosystem. Journal of Research of Environmental Sciences, 4, 57-63.
12
[13] Lozano, F.J., Soriano, M., Martnez, S. and Asensio, C. (2013). The influence of blowing soil trapped by shrubs on fertility in Tabernas District (SE Spain). Journal of Land Degradation & Development, 24 (6), 575-581.
13
[14] Ludwig, J., Tongway, D., Freudenberger, D., Noble, D. and Hodginson, D. (1997). Landscape Ecology, Function and Management: Principles from Australia's Rangelands. CSIRO press.
14
[15] Ludwig, J.A., Eager, R.W., Williams, R.J. and Lowe, L.M. (1999). Declines in Vegetation Patches, Plant Diversity, and Grasshopper Diversity Near Cattle Watering-Points in the Victoria River District, Northern Australia, The Rangeland Journal, 21, 135-149.
15
[16] Mohebi, Z. and Heshmati. G.A. (2017). Effects of different patches on qualitative indices of soil surface using Landscape Function Analysis (LFA) (Case study: Faraman Rangeland, Kermanshah). Iranian Journal of Range and Desert Research, 24 (3), 560-569. (In Persian)
16
[17] Pellant, M., Shaver, P., Pyke, D.A. and Herrick, J.E. (2005). Interpreting Indicators of Rangeland Health, Technical Reference 1734-6, Version 4. BLM National Business Center press.
17
[18] Post, D. (2005). Impact on grazing on sediment and nutrient concentrations in streams draining rangelands of the Burdekin catchments, Proc, Australia Water Association: paper t5260, 4 pp.
18
[19] Rahimi Balkanlou., Kh., Ghorbani, M., Jafari, M.and Tavili, A. (2016). Evaluation and comparison of ecological health in three arid rangeland using Landscape Function Analysis (LFA) (Case study: Kalateh Roudbar, Damghan). Journal of Desert Management, 7 (1), 35-45. (In Persian)
19
[20] Rezaei, S.A. and Tongway, D.J. (2005). Assessing rangeland capability in Iran using landscape function indices based on soil surface attributes. Journal of Arid Environment, 65, 460-473.
20
[21] Sallaway, M.M. and Waters, D.K. (1994). Spatial variation in runoff generation in granitic grazing lands. Proceedings of “Water Down Under” hydrology conference, 21-25 November 1994, Adelaide. Institute of Engineers Australia, 485-489.
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[23] Taghipoor, A., Mesdaghi, M., Heshmati, Gh. and Rastegar, Sh. (2008). The effect of environmental factors on distribution range Species on Hezar jarib Behshahr(Case Study: village Sorkhgriveh). Journal of Agricultural and natural resource science, 15 (4), 195-205.
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[24] Tongway, D.J. and Hindley, N.L. (2004). Landscape function analysis: procedures for monitoring and assessing landscapes with special reference to mine sites and rangelands, Version 3.1, CSIRO press.
24
ORIGINAL_ARTICLE
Using k Nearest Neighbor (k-NN) algorithm as a suitable approach to estimate cover-management factor of RUSLE model in Shirin Dareh basin, North Khorasan
Cover-management factor (C) is one of the most important influential factor on soil erosion using the Revised Universal Soil Loss Equation (RUSLE) model. C-factor is challenging to determine based on the proposed procedures due to lack of accurate information. Vegetation cover map can be used to estimate C-factor, but preparing a suitable mapping of vegetation cover is challenging in many situations. Therefore, in this study vegetation cover map was prepared and compared using the k Nearest Neighbor (k-NN) algorithm, linear regression (LR) and linear stepwise regression (LSR) in the study area. In regression methods, 17 vegetation and environmental indices were prepared and their relationships were investigated. The results of comparing the three methods showed that the k-NN method has better results than other regression methods due to its highest overall accuracy (83.3%) and kappa coefficient (75.9%) therefore, it was used to produce C-factor map. Results showed that the k-NN was very promising for mapping vegetation canopy cover in the arid and semi-arid areas. The results showed that among vegetation indices NDVI had the highest correlation (0.82) with percentage vegetation cover. Also, in the k-NN method, the Euclidean distance metrics in k = 9 has better results than the other two Fuzzy and Mahalanobis distances and can be used to estimation of vegetation cover map.
https://jrwm.ut.ac.ir/article_80533_4086c550093a3978d8d34fad0bb46f69.pdf
2021-02-19
753
770
10.22059/jrwm.2021.247783.1199
Soil erosion
Cover-management factor
Vegetation indices
GIS
nonparametric algorithms
K Nearest Neighbor
Emad
Zakeri
ra.zakeri@gmail.com
1
Ph.D. Range Management, Department of Natural Resources and Watershed Management of North Khorasan province, Iran
LEAD_AUTHOR
Hamidreza
karimzadeh
karimzadeh@cc.iut.ac.ir
2
University of Isfahan Tecnology
AUTHOR
Seyed Alireza
Mousavi
sarmousavi@cc.iut.ac.ir
3
Department of Natural Resources Isfahan /University of Technology /]Isfahan/Iran
AUTHOR
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61
ORIGINAL_ARTICLE
Digital mapping of soil aggregate stability and the effectiveness of soil erosion control practices in Behbahan region
Soil aggregate stability and its spatial distribution can be considered as a good indicator for assessing the results of measures conducted for mitigation soil erosion. This study was conducted in two adjacent sites in Chahmari region, Kuzestan province. At one site afforestation and contour furrowing were conducted to control soil erosion and the adjacent site with no controlling measures was considered as control. A total of 150 soil samples were collected from the surface layer (0-5 cm) of two sites and mean weight diameter of aggregates (MWD) were measured using dry and wet sieving (MWDd and MWDw, respectively). Based on digital soil mapping (DSM) approach and to map MWD spatially, several environmental covariates were derived from a Landsat 8 image and a digital elevation model (DEM). Two machine learning algorithms including artificial neural networks (ANN) and regression trees (RT) were used to predict MWD with covariates as inputs. Results indicated a significant difference between MWDd in two sites, but no significant difference was found between MWDw. Correlation analysis revealed no correlation between MWDw and all terrain attributes derived from the DEM, but significant correlations were obtained between MWDd and some terrain attributes. Most covariates derived from Landsat images had significant correlation with both MWDw and MWDd. ANN and TR had relatively high and almost the same accuracy in predicting MWDw, but in predicting MWDd, ANN was superior to RT. In general, the findings showed good performance of DSM techniques in predicting and spatial mapping of MWD.
https://jrwm.ut.ac.ir/article_80534_9479731578b5c3edf3dc7e9ef345ce01.pdf
2021-02-19
771
785
10.22059/jrwm.2020.301998.1499
Artificial Neural Networks
digital soil mapping
Regression tree
Spatial modeling
Manizheh
Razavi Hosain Abad
razavi.mn95@gmail.com
1
Faculty of Natural Resources and Environment, Khatam Al-Anbia University of Technology, Behbahan
AUTHOR
Alireza
Amirian Chekan
amirian.ar@lu.ac.ir
2
Assistant Professor, Department of Soil Science Engineering, Faculty of Agriculture and Natural Resources, Lorestan University
AUTHOR
Mohammad
Faraji
mfaraji31@yahoo.com
3
Assistant Professor, Behbahan Khatam Alanbia University of Technology
LEAD_AUTHOR
Jamal
Mosavian
mosvianjamal@yahoo.com
4
Master of Science of the General Department of Natural Resources and Watershed Management of Khuzestan Province
AUTHOR
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2
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5
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6
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12
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42
ORIGINAL_ARTICLE
The Most Important Factors Influencing the Urmia Rangeland Fire Using DEMATEL
To determine these factors, the DEMATEL was used. To determine the most influential factors, several criteria such as slope, slope direction, height, type of cover, density of cover, percentage of cover, human population, proximity to roads, proximity to residential areas, proximity to agricultural lands, proximity to water resources, The type of employment of the natives and the use of the lands were used. The various steps of the decision evaluation method included forming the mean matrix, calculating the effect matrix of non-scaled direct relationships, calculating the total matrix (total direct and indirect effects matrix), calculating the impact matrix and the impact rate, and determining the order of effectiveness and impact. Based on the obtained results, among various factors, land use factor (3.9308) has the most impact and factor for slope has the least impact (1.0475) on the fire phenomenon. Based on the results of the present study, land use factors and human population have more interaction with other fire factors and the weight of these factors is more on the occurrence of fire phenomenon. Also, based on the results of the communication vector, which represents the certainty of a criterion as an influential criterion, the factors adjacent to the road (1.43) and height (0.6) have the greatest impact .The most important application of this information is the use of this information in the preparation of fire risk maps.
https://jrwm.ut.ac.ir/article_80538_80d27ea669a669f8fd56bfadb57b4ecf.pdf
2021-02-19
786
801
10.22059/jrwm.2020.296573.1455
Fire Prevention
Decision Making Techniques
Fire management
Urmia
mahshid
souri
souri@rifr-ac.ir
1
Assistant Professor, Rangeland Research Division, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran.
LEAD_AUTHOR
payam
najafi
payam_najafi23@yahoo.com
2
M.Sc. Graduate of Range Management, Faculty of Natural Resources, University of Urmia, Iran.
AUTHOR
javad
motamedi
motamedi@rifr-ac.ir
3
Professor associated, Rangeland Research Division, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran
AUTHOR
saeedeh
nateghi
nateghi@rifr-ac.ir
4
Assistant Professor, Rangeland Research Division, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran
AUTHOR
[1] Akinola, O. V. and Adegoke, J. (2018). Assessment of forest fire vulnerability zones in Missouri, United States of America. International Journal of Sustainable Development & World Ecology, 1–7.
1
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[3] Amiri, T. (2019). Determining the location of observation towers in the rapid detection of forest fires using the geographic information system, Journal of Mapping and Spatial Information Engineering, 10(2):1-11.
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[4] Burges, R. (2011). Development of a spatial, dynamic, fuzzy fire risk model for Chitwan District, Nepal. Geo-Information Science and Earth Observation for Enviromental Modeling and Management, 96 p.
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[5] Chavan, M.E., Das, K.K. and Suryawanshi, R.S. (2012). Forest fire risk zonation using Remote Sensing and GIS in Huynial watershed, Tehri Garhwal district, UA. International Journal of Basic and Applied Research, 2: 6-12.
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[6] Chuvieco, E., Aguado, I., Jurdao, S., Pettinari, M.L., Yebra, M., Salas, J., Hantson, S., de la Riva, J., Ibarra, P., Rodrigues, M., Echeverria, M., Azqueta, D., Roman, M.V., Bastarrika, A., Martinez, S., Recondo, C., Zapico, E., and Martinez-Vega, F.J. (2012). Integrating geospatial information into fire risk assessment. International Journal of Wildland Fire, 23(5): 606-619.
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[7] Çolak, E. and Sunar, F. (2020). Evaluation of forest fire risk in the Mediterranean Turkish forests: A case study of Menderes region, Izmir. International Journal of Disaster Risk Reduction, 45, 471-479.
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[10] Gandhi, S., Mangla, S.K., Kumar, P. and Kumar, D. (2015). Evaluation factors in implementation of successful green supply chain management using DEMATEL, A case study: Indian manufacturing company. International Journal of Strategic Management Review, 3(2): 96–109.
10
[11] Gerdzheva, A.A. (2014). A Comparative analysis of different wildfire risk assessment models (a case study for smolyyan distric, Bulgaria). European Journal of Geography, 5(3): 22-36.
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[12] Han, Y. and Deng, Y. (2018). An enhanced fuzzy evidential DEMATEL method with its application to identify critical success factors. Journal of Soft Computing, 22(15), 5073–5090.
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[13] Jaiswal, R.K., Mukherjee, S., Raju, K.D. and Saxena, R. (2002). Forest fire risk zone mapping from satellite imagery and GIS. International Journal of Applied Earth Observation and Geoinformation, 4(1): 1-10.
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[14] Janbaz Ghobadi, GH., 2019. Investigation of forest fire risk areas in Golestan province based on fire risk index Using GIS, Iranian Journal of Space Analysis of Environmental Hazards, 6 (3):89-109.
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[15] Ju, Y., Wang, A. and You, T. (2014). Emergency alternative evaluation and selection based on ANP, DEMATEL, and TL-TOPSIS. Journal of Natural Hazards, 75(52): 347–379.
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[16] Kilic, H. and Yalcin, AS. (2020). Comparison of municipalities considering environmental sustainability via neutrosophic DEMATEL based TOPSIS. Socio-Economic Planning Sciences, Elsevier, 23, 117-128.
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[17] Konkathi, P., Shetty, A., Kolluru, V., Yathish, P. and Pruthviraj, U. (2019). Static Fire Risk Index for the Forest Resources of Karnataka. International Geoscience and Remote Sensing Symposium, 115-117.
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[21] Mohammad Yazdi, A., Nedjati, E. and Zarei, R. (2020). A novel extension of DEMATEL approach for probabilistic safety analysis in process systems. Safety Science journal, 121, 119-136.
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[22] Naghipour, A. (2018). Forecasting the occurrence of fire using modeling of Bavar Lizin network in Chaharmahal and Bakhtiari province, Rangeland Scientific Research Journal, 13 (1): 90-100.
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[23] Sakellariou, S., Tampekis, S., Samara, F., Flannigan, M., Jaeger, D., Christopoulou, O. and Sfougaris, A. 2018. Determination of fire risk to assist fire management for insular areas: the case of a small Greek island Journal of Forestry Research, 13,178-188.
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[24] Sheng-Li, Si., Xiao-Yue, Y., Hu-Chen, L. and Zhang, P. (2018). DEMATEL Technique: A Systematic Review of the State-of-the-Art Literature on Methodologies and Applications. Mathematical Problems in Engineering Journal, 41, 127-136.
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[26] Tseng, M. L. (2009). A causal and effect decision making model of service quality expectation using grey-fuzzy DEMATEL approach. Journal of Expert Systems with Applications, 36, 7738-7748.
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[27] Tzeng, G.H. and Huang, J.J. (2011). Multiple Attribute Decision making methods and application, Taylor and Frncis Group.
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[28] Vadrevu, K.P., Eaturu, A., Badarinath. K. (2010). Fire risk evaluation using multi criteria analysis– a case study. Journal of Environmental Monitoring and Assessment, 166(2): 223–239.
28
[29] Xue-qian, Sh., Moxian, S., Kai, H. and Wen, J. (2019). An improved evidential DEMATEL identify critical success factors under uncertain environment. Journal of Ambient Intelligence and Humanized Computing, 16 (3), 113-121. https://doi.org/10.1007/s12652-019-01546-1.
29
[30] Yang, J.L. and Tzeng, G.H. (2011). An integrated MCDM technique combined with DEMATEL for a novel cluster-weighted with ANP method. Journal of Expert system with applications, 38(2): 1417- 1424.
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[31] Yiliadis, L.S. (2005). A decision support system applying an integrated fuzzy model for long-term forest fire risk estimation. Environmental Modelling and Software, 20(5): 613–621.
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[32] Zarrakar, A., Kazemi Zamani, B., Ghorbani, S., Ashegh Maala, M. and Jafari, HR. (2013). Spatial Distribution Mapping of Forest Fire Risk Using Decision Making Method Multi Criteria and GIS in Three Forest Areas of Guilan Province. Iranian Journal of Forest and Poplar Research, 21 (2): 230- 218.
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[33] Zhou, L., Dai, G., Qin, R., Tang, M. and Qiu, J. (2018). Risk Analysis of Gob Coal Spontaneous Combustion in Methane-Rich, Combustion-Prone Coal Seam Based on Intuitionistic Fuzzy DEMATEL. Journal of Failure Analysis and Prevention, 18(4), 975–987.
33
ORIGINAL_ARTICLE
Evaluation of the effect of seed washing with sulfuric acid and irrigation with salt water on seed germination of Zygophyllum fabago L.
Plant growth and yield in the environment is affected by numerous biotic and abiotic environmental stresses as well as seed dormancy. The aim of the present study was to investigate the effect of seed washing treatments with sulfuric acid and irrigation of seeds with saline water on seed germination of Zygophyllum fabago. According to previous relevant researches, for this purpose, three concentrations of 0, 10 and 20% were prepared for acid washing treatment. For salinity treatment, four levels were considered: 0, 60, 90 and 120 mmol / l. Irrigation with spray water was applied evenly on all pteridia when necessary. Germinated seeds were counted daily and continued until no increase in the number of germinated seeds was observed .Comparison of the mean of the main effect of different levels of acid treatment on the germination percentage of Z. fabago showed that zero and ten percent acid concentration treatments with 59 and 60 percent have a higher value. Regarding the comparison of the mean of the interaction effects of acid and salinity, the results showed that the best treatment combination is zero percent acid and zero salinity of ten and ten millimoles per liter. Therefore, Z. fabago species needs low concentrations of salinity and sulfuric acid for optimal growth. Therefore, it can be used to improve and rehabilitate rangeland ecosystems according to the salinity of the area.
https://jrwm.ut.ac.ir/article_80536_07fd3650b41c0c20a878eb6fe4f0fa1c.pdf
2021-02-19
802
815
10.22059/jrwm.2020.302089.1500
Seed dormancy
Sulfuric acid
salinity
germination
Medicinal plant
Esmaeil
Sheidai Karkaj
e.sheidai@urmia.ac.ir
1
Assistant professor, Department of Range and Watershed Management, Faculty of Agriculture and Natural Resources, Urmia University, Urmia
LEAD_AUTHOR
Esfandiar
Jahantab
esfandiar.jahantab@gmail.com
2
Fasa University
AUTHOR
Zahra
Mahmoodi
zah.mahmudi@yahoo.com
3
Urmia University
AUTHOR
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1
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4
[5] Azimi, R., Borzelabad, M. J., Feizi, H. and Azimi, A. (2014). Interaction of SiO2 nanoparticles with seed prechilling on germination and early seedling growth of tall wheatgrass (Agropyron elongatum L.). Polish Journal of Chemical Technology, 16(3), 25-29.
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11
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[25] Keshavarz Afshar, R., Keykhah, M., Chaeichi, M.R. and Ansari, M. (2013). Effect of different levels of salinity and drought stress on seed germination characteristics and seedling growth of forage turnip (Brassica rapa L.). Iranian Journal of Field Crop Science, 43(4), 661-671. (In Persian)
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[27] Labbafi, M., Mehrafarin, A., Naghdibadi, H., Ghorbani, M. and Tavakoli, M. (2018). Investigating the effect of various chemical and non-chemical treatments break dormancy galbanum seeds Ferula gummosa Boiss. Eco-phytochemical Journal of Medicinal Plants, 6(2), 80-88. (In Persian)
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[29] Lefevre, I., Vogel-Mikus, K., Arcon, I. and Lutts, S. (2016). How do roots of the metalresistant perennial bush Zygophyllum fabago cope with cadmium and zinc toxicities? Plant and Soil, 404 (1-2), 193-207.
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[30] Li, Y. (2008). Effect of salt stress on seed germination and seedling growth of three salinity Plants, Pakistan Journal of Biological Sciences, 11(9), 1268-1272.
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[34] Mojab, M., Hosseini, M., Zamani, Gh.R., Kohansal, A., Ebrahimi, A. (2015). The effect of different methods of seed dormancy breaking and effects of salinity and drought stress on germination characteristics of weed (Prosopis stephaniana willd). Environmental stresses in crop science, 8 (1), 101-108. (In Persian)
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44
ORIGINAL_ARTICLE
The effect of substrate and stimulating hormone on germination characteristics of Salvadora persica
Germination is one of the most important stages of plant growth that may be affected by different stresses in natural environments. This study was kind aimed to investigate the effects of substrate and different levels of gibberellic and indole butyric acid on germination characteristics of Salvadora persica seeds in 2019. Two factors was considered consist of substrate (in four types (1- pit moss, 2 - cocopit and 3 - pit moss 50% + sand 50% 4 - Cocopit 50% + 50% sand), and gibberellic acid (in two levels 250 and 500 ppm) and indole butyric acid (in two levels 250 and 500 ppm). Then, the effect of these two factors and distilled water as the control in three replications on seed germination and seedling growth of Salvadora persica was investigated using a completely randomized factorial design. The results showed that the substrate had a significant effect on germination percentage, root length, shoot length, seedling, fresh root weight, shoot fresh weight and seed vigor index (p < 0.01). Seed pretreatment with gibberellic and indole butyric acid hormones had a significant effect on all studied characteristics. Interaction of substrate type and pretreatment with hormones had a significant effect on germination percentage, root length, shoot length, seedling and seed vigor index (p < 0.01) and had no significant effect on root and shoot fresh weight. The highest germination percentage was obtained in cocopeat and gibberellic acid 250 ppm (73%).
https://jrwm.ut.ac.ir/article_80537_d3cca3bf7378ea89b59f833efb90e6de.pdf
2021-02-19
816
831
10.22059/jrwm.2020.296712.1456
germination
substrate
gibberellic acid
indole butyric acid
Salvadora persica
Morteza
Saberi
m_saberi63@yahoo.com
1
University of Zabol
LEAD_AUTHOR
Soheila
noori
snoori.327@uoz.ac.ir
2
Range and watershed management department, Water and Soil collage, University of Zabol
AUTHOR
Fahimeh
Rashidi
f.rashidi6322@gmail.com
3
MSc student in Range management, Faculty of water and soil, University of Zabol
AUTHOR
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1
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2
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3
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Burley 21 in the floating method. The Tenth Congress of Soil Science, 26/8/2007, Karaj, Iran.
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61
ORIGINAL_ARTICLE
Analysis of the Impact of Ecotourism on Capitals of Rural Livelihoods in the Sustainability Framework (Case Study: Palangan Village of Kurdistan)
Sustainable livelihood approach is one of the new approaches in the field of sustainable rural development, which has been considered for poverty reduction and improving rural living standards, and their factors have a vital importance and role. Therefore, the aim of this study investigate the effect of ecotourism on sustainable rural livelihood in Palangan Village of Kurdistan Province. The statistical population in this study is all persons over 20 year’s old living in the studied village that are 623 peoples. Sampling was done randomly that using the Cochran formula, a total of 238 individuals were selected. A data collection tool was a researcher-made questionnaire that used after confirming the validity by experts' opinion and reliability by Cronbach's alpha coefficient (0.83). Data analysis was performed using SPSS16.0 software. The results of one-sample t-test showed that natural, social and human resources were not in a good condition under the influence of ecotourism in Palangan village. Financial and physical capitals have had a better effects and this effect was only significant in physical livelihood capital. The findings of this study showed that there is a need to improve the tourism situation in the study area in order to achieve sustainable livelihoods and in this regard, principled management, local community participation and the use of ecotourism potentials in Palangan village are necessary.
https://jrwm.ut.ac.ir/article_80539_fa99a04717bf141243e9512b45143538.pdf
2021-02-19
832
842
10.22059/jrwm.2020.299418.1479
Property
Development
Sustainable Livelihood
Local Economy
Palangan Village
Asghar
Farajollahi
asghar.farajolahi@gmail.com
1
Ph.D. Graduate, Combating Desertification, Gorgan University of Agricultural Science and Natural Resources, Golestan,
AUTHOR
Iman
Islami
i.eslami@modares.ac.ir
2
Assistant Professor of Rangeland Management Department, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor , Iran
LEAD_AUTHOR
Abdollahzadeh, Gh.h., Salehi, Kh., Sharifzadeh, M.Sh., & Khajeh Shahkohi, A. (2015). Investigating the impact of tourism on sustainable livelihoods in Golestan Province, Journal of Tourism Planning and Development, 4 (15): 148-169. In Persian.
1
Blake, A., Arbache, J.S., Sinclair, M., & Thea Teles, V. (2008). Tourism and Poverty Relief. Annals of Tourism Research 35(1): 107-126.
2
Carney, D. (1998). Sustainable Rural Livelihoods: What Contribution Can We Make? London: DFID. 213 pages.
3
Croes, R. & Vanegas Sr, Ma. (2008). Co integration and Causality between Tourism and Poverty Reduction. Journal of Travel Research, 47(1): 94-103.
4
DelMar Alonso-Almeida, M. (2013). Environmental management in tourism: students’ perceptions and managerial practice in restaurants from a gender perspective, Journal of Cleaner Production, 60, 201-207.
5
Esazehi, A. (1979). Survey of sustainable livelihoods index of rural households in Saravan County, MA Thesis in Agricultural Extension, Yasuj University. In Persian.
6
Fallahi, H. (2006). Feasibility study of ecotourism development - Ashtarakoh Basin with emphasis on gohar lake, MSc Thesis, Faculty of Earth Sciences, Shahid Beheshti University. In Persian.
7
Ghadami, M. & Aligholi Zadeh Firouzjaie, N. (2012). Evaluation of destination tourism development in the sustainability framework of the Study Sample (Tamashkal District / Tonekabon County), Geographical Research Quarterly, 27 (1): 104-79. In Persian.
8
Gilmon, P. (2008). Environmental Analyze and Zoning for an Urban Park Management Purpose Bralizian Archives of Biology and Technology, 48(4): 647-655.
9
Harilal, V., & Tichaawa, T.M. (2018). Ecotourism and alternative livelihood strategies in Cameroon’s protected areas. Euro Economica, 1(37): 133-148.
10
Islami, I., Ebrahimzadeh Asmin, H., & Ashtari Mehrjadi, A. (2020). Social Network Analysis of Participatory Management and Social Capital among Livestock Beneficiaries in Yazd Province. Journal of Community Development, 12(2): 483-500. In Persian.
11
Luvanga, N., & Shitundu, J. (2003).The Role of Tourism in Poverty Alleviation in Tanzania. Research Report, No. 03.4
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Malek, B. (2014). Designing of tourist complex in Palangan Village (with ecotourism and sustainable architecture), Master of Architecture Thesis, Shahrood University of Technology. In Persian.
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Masoumi, M. (2009). An introduction to approaches in planning local, Urban and Regional Tourism Development, Samira Publications. In Persian.
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Mbaiwaa, J.E. & Stronzab, A. (2010). The effects of tourism development on rural livelihoods in the Okavango Delta, Botswana, Journal of Sustainable Tourism, 18(5): 635-656.
15
Mir Karimi, S. H., Saeedi, S. & Saeedi, S. (2016). Principles and concepts of achieving successful ecotourism, Human and Environmental Quarterly, 14 (2): 13-23. In Persian.
16
Moghaddam, S. (2016). Assessing the role of ecotourism in the sustainable development of local communities of Abhar County, MA Thesis in Geography and Tourism Planning, Zanjan University. In Persian.
17
Moradi, D. (2013). The role of ecotourism in the economic development of wetlands (Case Study: Varzaneh City), Master of Science in Geography and Tourism Planning, University of Science and Culture. In Persian.
18
Motiei Langroodi, H., Ghadiri Masoum, M., Rezvani, M. R., Nazari, A. & Sahneh, B. (2011). The impact of migrants 'return to villages on improving residents' livelihoods (Case Study: Aq Qala City), Human Geography, 78, 67-83. In Persian.
19
Mozumder, M. M. H., Uddin, M. M., Schneider, P., Islam, M. M., & Shamsuzzaman, M. (2018). Fisheries-Based Ecotourism in Bangladesh: Potentials and Challenges. Resources, 7(4), 61 pages.
20
Muladan, B., & Bilharz, S. (2002). Sustainable development indicators, Translated by Haddad Tehrani, Neshat, Moharramnejad, Nasser, EPA Publications. 468 pages. In Persian.
21
National Statistics Portal. (2019). Iran Statistical Center, Results of the general population and housing census of 2016. In Persian.
22
Nazarian, A., Moshiri, S.R. & Aghajani, F. (2006). Feasibility study of tourism industry development in Ardabil City, Geographical Perspective Quarterly, 1(3): 103-117. In Persian.
23
Nyaupane, G.P. (2011). Linkages among biodiversity, livelihood, and tourism, Annuals of Tourism Research, 38(4): 1344-1366.
24
Roe, D., Ashley, C., Page, S.H. & Meyer, D. (2004). Tourism and the poor: Analyzing and interpreting tourism statistics from a poverty perspective. Partnership London.1-29.
25
Samavati, A. (2016). Evaluating the effects of ecotourism on sustainable livelihood components from a perspective experts and tribes of Turkasvand, Master's Degree in Range Management, University of Malayer. In Persian.
26
Sarmad, Z., Bazaragan, A. & Hajazi, A. (2014). Research Methods in Behavioral Sciences, Publication of Agah, 408p.
27
Sarvi sadrabad, H., & Islami, I. (2020). Analysis of the social network and bonding social capital in participatory management of water resources (Case study: Sadrabad Village, Nodoushan catchment, Yazd Province). Journal of Range and Watershed Management. 72(3): 739-753. In Persian.
28
Udayakumara, E.P.N. & Shrestha, R.P. (2011). Assessing livelihood for improvement: Samanalawewa reservoir environs, Sri Lanka, International Journal of Sustainable Development and World Ecology, 18(4): 366-376.
29
Veisi, F., & Nikkhah, C. (2019). Analysis of the role of tourism in sustainable livelihoods of rural households, Case Study: Oraman distrct in Sarvabad County, Geography and Planning, 22(66): 329-348.
30
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31
Yousefi, M. (2016). Ecotourism and Sustainable Livelihoods of Local Communities, Biosphere, 11(2): 35-38. In Persian.
32
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33
ORIGINAL_ARTICLE
Socio-Economic Factors Affecting Rural Households’ Participation in Carbon Sequestration Projects in the Qom Province
The Carbon Sequestration Project has been an important international initiative for natural resources management and climate change reduction measures over the past two decades.It has tried to involve rural households in all stages of the project to achieve environmental, economic,social and human goals. A number of factors can affect relevant stakeholders’ participation in carbon sequestration project activities.This study aimed to investigate the socio-economic factors affecting the participation of rural households in the Qom province, using a survey with a descriptive-correlational approach. A sample of 265 households out of 840 rural households was selected using a simple random sampling method in five villages where this project was implemented.The data were collected using a structured interview technique by a questionnaire and analyzed using the SPSS22 and AMOS software.The results showed that rural people had highly been involved in the less active participation stages, such as expert consultation with council members and village elders, where as they had poor contribution to the projects through collaborative or spontaneous involvements.The most important factors affecting the participation of rural households in the carbon sequestration project were identified to be variables such as social capitals; extension programs; implemented conservation projects; agricultural and non-agricultural diversification initiatives in carbon sequestration projects; the land area of households’ permanent crop; and their agricultural income.Promoting social capital through extension programs, and applying a combination of conservation and livelihood diversification measures can not only strengthen the participation of rural communities in natural resource management projects but also increase the success of these projects.
https://jrwm.ut.ac.ir/article_80540_ca2177056c0f46ea96e867f75c11b193.pdf
2021-02-19
843
863
10.22059/jrwm.2021.303920.1510
participatory natural resources management
Carbon Sequestration Project
Rural Community
socio-economic effects
Qom province
Kobr
Karimi
kkarimi2004@gmail.com
1
University of Zanjan
LEAD_AUTHOR
Esmail
Karamidehkordi
e.karamidehkordi@modares.ac.ir
2
Associate Professor of Agricultural Extension and Rural Development, Tarbiat Modares University, Iran, Associate Professor of Agricultural Extension and Rural Development, University of Zanjan, Iran.
AUTHOR
Matthias
Buchecker
matthias.buchecker@wsl.ch
3
Economics and Social Sciences, Social Sciences in Landscape Research, Swiss Federal Research Institute WSL Zürcherstrasse
AUTHOR
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[4] Bastian, O., Haase, D. and Grunewald, K. (2012). Ecosystem properties, potentials and services – The EPPS conceptual framework and an urban application example. Ecological Indicators, 21, 7-16.
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[5] Bhandari, P., Kc, M., Shrestha, S., Aryal, A. and Shrestha, U. B. (2016). Assessments of ecosystem service indicators and stakeholder's willingness to pay for selected ecosystem services in the Chure region of Nepal. Applied Geography, 69, 25-34.
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[6] Danish, Baloch, M. A., Mahmood, N. and Zhang, J. W. (2019). Effect of natural resources, renewable energy and economic development on CO2 emissions in BRICS countries. Science of The Total Environment, 678, 632-638.
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[15] Karimi, K. (2013). Rural communities’ capacity building and emphasis on stakeholders’ organizational coherence in Zanjan province's natural resources and watershed management projects using the National Development Fund. (MSc), University of Zanjan, Faculty of Agriculture.
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[16] Karimi, K. and Karami Dehkordi, I. (2015). Participation of Rural Users in Pasture Management Plans and the Factors Effective on them in Mahneshan Township. Geography and Development, 45, 181-196.
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[17] Khalili, v., Mahmoudi, J., Gholami, S. and Nazari , M. (2015). Factors affecting the rate of participation of beneficiaries in the implementation Range Management Plan (case study of summer pastures Vazroud area). Journal of Natural Ecosystem of Iran, 5(2), 105-113.
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[18] Kim, D.-H., Suen, Y.-B. and Lin, S.-C. (2019). Carbon dioxide emissions and trade: Evidence from disaggregate trade data. Energy Economics, 78, 13-28.
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[19] Lal, R. (2012). Climate change and soil degradation mitigation by sustainable management of soils and other natural resources. Agricultural Research, 1(3), 199-212.
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[20] Larson, S., De Freitas, D. M. and Hicks, C. C. (2013). Sense of place as a determinant of people's attitudes towards the environment: Implications for natural resources management and planning in the Great Barrier Reef, Australia. Journal of Environmental Management, 117, 226-234.
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[21] Lejano, R. P. and Ingram, H. (2009). Collaborative networks and new ways of knowing. Environmental Science & Policy, 12(6), 653-662.
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[22] Mahmoudi, J. S. and Foroutan, S. K. M. (2018). Factors Affecting the Beneficiaries Participation in the Implementation of Range Manegment Plans in Kiasar Watershed, Sari County. Whatershed Management Research, 31(18), 46-59.
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[23] Mohammadi Golrang, B., See Lai, F. and Sadegh, S. H. R. (2017). Evaluation of variables affecting people's participation in soil pasture and watershed management projects (Case study: Kouskabad Watershedin Khorasan Razavi). Journal of Research & Rural Planning, 6(1), 49-68.
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[24] Mousaei, M. (2015). Factors affecting the non-participation of exploiters in agricultural projects (case study of Fars province). Journal of Promotion and Agricultural Economics, 2(2), 84-69.
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[25] Mousaei, M., Malek Mohammadi, I., Farajollah Hosseini, S. J. and Mirdamadi, S. M. (2010). Factors affecting the participation of operators in watershed management projects from the perspective of experts in promoting natural resources and watershed management in Fars province. Agricultural Science; Crop Ecophysiology, 4(14), 139-151.
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[26] Nejadi, F., Abbasi, E. and Choobchian, S. (2017). The Role of Combating Desertification Projects in Promotion of Local People’s Social Capital the Case of Shahdad Carbon Sequestration Project). Journal of Rural Research, 7(4), 604-617.
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[27] O'Mara, F. P. (2012). The role of grasslands in food security and climate change. Ann. Bot-London,110:1263-1270.
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[29] Pezeshki-Raad, G. and KaramiDehkordi, E. (2012). Social Statistics and Data Analysis of Research on Agricultural Extension, development and Education. Tehran: Tarbiat Modares University Press.
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[30] Poeplau, C., Don, A., Vesterdal, L., Leifeld, J., Basvan, W., Schumacher, J. and Sgensior, A. (2011). Temporal dynamics of soil organic carbon after land-use change in the temperate zone - carbon response functions as a model approach. Global Change Biology, 17(7), 72415–72427.
30
[31] Rahimi, d. and Rahemi, y. (2016). Resources in the Impacts Climate Change on Floods in North of Iran. Geography and Environmental Planning, 27(1), 89-102.
31
[32] Saberi, R., Fal Soleyman, M. and Gheysari, S. (2012). Sustainable Local Development and Attracting Maximum Participation of People Case Study: The Experiences of International Project of Carbon Sequestration in South Khorasan. Geography and Development Iranian Journal, 10(28), 41-54.
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[33] Sene-Harper, A., Matarrita-Cascante, D. and Larson, L. R. (2019). Leveraging local livelihood strategies to support conservation and development in West Africa. Environmental Development, 29, 16-28.
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[34] Shackleton, C. M., Willis, T. J., Brown, K. and Polunin, N. V. C. (2010). Reflecting on the next generation of models for community-based natural resources management. Environmental Conservation, 37(1), 1-4.
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[35] Sil, Â., Fonseca, F., Gonçalves, J., Honrado, J., Marta-Pedroso, C., Alonso, J., . . . Azevedo, J. C. (2017). Analysing carbon sequestration and storage dynamics in a changing mountain landscape in Portugal: insights for management and planning. International Journal of Biodiversity Science, Ecosystem Services & magement, 13(2), 82-104.
35
[36] Soleimanpour, S M., Salehpour Jam, A., Noroozi, A A., Khalili, N. and Keshavarzi ,H. (2020). Experts' Viewpoints on Prioritizing Factors Affecting Lack of Sustainable Participation of Rural Communities in Watershed Management Projects on the Moradabad Watershed, Meymand the Province of Fars, 32(3), 53-62.
36
[37] Tallis, H. and Polasky, S. (2009). Mapping and valuing ecosystem services as an approach for conservation and natural‐resource management. Annals of the New York Academy of Sciences, 1162(1), 265-283.
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[38] Thomas, C. W. and Koontz, T. M. (2011). Research Designs for Evaluating the Impact of Community-Based Management on Natural Resource Conservation. Journal of Natural Resources Policy Research, 3(2), 97-111.
38
[39] Tompkins, E. and Adger, W. N. (2004). Does adaptive management of natural resources enhance resilience to climate change? Ecology and Society, 9(2(,
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[40] Tubiello, F. N., Soussana, J.-F. and Howden, S. M. (2007). Crop and pasture response to climate change. Proceedings of the National Academy of Sciences, 104(50), 19686-19690.
40
[41] Varamesh, S., Hosseini, S. M., Abdi, N. and Akbarinia, M. (2010). Increment of soil carbon sequestration due to forestation and its relation with some physical and chemical factors of soil. Iranian Journal of Forest, 2(1), 25-35.
41
[42] Wang, X., Feng, Y., Liu, J., Lee, H., Li, C., Li, N. and Ren, N. (2010). Sequestration of CO2 discharged from anode by algal cathode in microbial carbon capture cells (MCCs). Biosensors and Bioelectronics, 25(12), 2639-2643.
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[43] Wilmsen, C., Elmendorf, W. F., Fisher, L., Ross, J., Sarathy, B. and Wells, G. (2012). Partnerships for empowerment: participatory research for community-based natural resource management: Routledge.
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[44] Wright, J. H., Hill, N. A. O., Roe, D., Rowcliffe, J. M., Kümpel, N. F., Day, M., . . . Milner-Gulland, E. J. (2016). Reframing the concept of alternative livelihoods. Conservation Biology, 30(1), 7-13.
44
[45] Zamen Rahemi Ardakani, A., Esmaeilpour, Y., Mohammadi, Y. and Gholami, H. (2018). Factor Analysis of obstacles to the Local Communities Participation in the Biological Restoration and Desertification Plans of Carbon Sequestration Project in the Lapui County, Fars Province
45
ORIGINAL_ARTICLE
Evaluation of seed and forage yield of important populations of Fortuynia bongei in Kerman province
This research was aimed to investigate the populations of Fortuynia bongei in a complete blocks design with three replications in field conditions. Treatments included the populations of Fortuynia bongei collected from Sirch, Koohpayeh, Zarand, Bam and Baghin. The traits including vegetation cover, forage yield, and seed yield were recorded. Data were analyzed by SPSS software and mean comparisons were performed by Duncan's Multiple Range Test. The results of ANOVA showed significant differences among the populations of Fortuynia bongei collected in this study. According to the results of mean comparisons, the highest percentage was recorded for the Koohpayeh population and the Bam population had the highest yield and seed production. So, these tow population could be recommended for the range lands rehabilitation projects in this area.
https://jrwm.ut.ac.ir/article_80541_a5d4395691cdd93817038f8722d48213.pdf
2021-02-19
864
875
10.22059/jrwm.2020.252848.1236
Fortuynia bungei
genotype
Forage yield
Seed yield
Ali
Mohebby
tahayashar@gmail.com
1
RIFR
LEAD_AUTHOR
Mahdi
Ramezani
dr.mramezani@yahoo.com
2
teacher
AUTHOR
Naser
Arabzadeh
arabzadeh_r_m@yahoo.com
3
Retired Assistant Professor, South Kerman Agricultural and Natural Resources Research and Education Center
AUTHOR
[1] Abbasi, M.R. (2010). Genetically diversity of Trifolium species in the national Genetic bank of Iran. Journal of Genetics and Forest and Rangelands Plants Rehabilitation. 17. N: 1, 70-87.
1
[2] Abdolrahmani, B., Esfahani, M and Sadeghzadeh, B.( 2013). Assesing the relationship between vigority and yield of rain irrigated accessions of wheat . Journal of Iranian agronomy. 4:14: 308-319.
2
[3] Ashraf Jafari, A. (2003). Determining the biodiversity and genetically distance between 20 accession of Lolium multiflorum by using multivariate statistics, Journal of Pajohesh and Sazandeghi. 64, 78- 83.
3
[4] Babakhanlo, P. (1967). Suitable forage plant with high adaptation for Iran climate, organization of range improvement press.
4
[5] Baniasadi, M., alizadeh, M and Ahmadi, R. ( 2009). Assessment the effect of drought on the yield and palatability of rangelands species in Abbarik- Bam. The first conference of modeling the soil, air and plant.
5
[6] Bhattarai, K., Johnson, D.A., Jones, T.A., Connors, K.J., and Gardner, D.R..( 2008). Physiological and Morphological Characterization of Basalt Milkvetch (Astragalus filipes): Basis for Plant Improvement. Rangeland Ecol Manage 61:444–455.
6
[7] Briggs, K.G.( 1975). Effects of seeding rate and row spacing on agronomic characteristics of Glenlea, pitic 62 and neepawa wheats. Canadian J. of Plant Sci., 55: 363-367.
7
[8] Gulsen, O., Sever-Mutlu, S., Mutlu, N., Tuna, M., Karaguzel, O., Shearman, R.C., Riordan, T. P., and Heng-Moss, T.M. ( 2009). Polyploidy creates higher diversity among Cynodon accessions as assessed by molecular markers. Theor Appl Genet 118:1309–1319.
8
[9] Imani, A.A., Jafari, A.A., Choghan, R., Asghari, A and Darvish, F. ( 2008). Evaluation of quantity and quality in 36 population of Festuca arundinacea for presentation suitable types for range improvement and forage production in highland pasture in Ardabil province, Journal of range and desert research, 15(4):493-507.
9
[10] Majidi, M.M., Asghariniia, P., Amini, F., Ebrahimian, M and Mirlouhi, A.F. ( 2001). Analyzing the intraction between accession and Environment on the yield of Festuca species by using Multivariate statistics. Journal of Genetics and Forest and Rangelands Plants Rehabilitation. 1:19134-152.
10
[11] Mirhaji, T.( 2008). Evaluation of the kind of plants exist in range plant nursery, Final Report of Project, Research Institute of Forests and Rangelands press.
11
[12] Mirhaji, T., Sanadgol, A and A.A. Jafari.( 2013). Evaluation of 16 population of Festuca ovina L. in range plant nursery, Research site of Homand Absard, Journal of range and desert research, 20(1): 11-22.
12
[ 13] Peymanifard, B and A, Tarighi .(1984). Introduction of important forage for Iran rangeland, Issue number 24, Research Institute of Forests and Rangelands press, 79p.
13
[14] Peymanifard, B and B, Malekpour.( 1984).Increasing forage in poor rangeland with Terracing and forage planting. Research Institute of Forests and Rangelands press.
14
[15] Piano, E., Valentini, L., Pecett, P., and Romani M.( 1996). Evaluation of Lucerne germplasm collection in relation to traits conferring grazing tolerance. Euphytica 89: 279-288.
15
[ 16] Riiasat, M., Ashraf Jafari, A., safavi, Y. (2015). Study the yield of lymus pertenuis accessions under the flood and rain irrigation in the Fars province. Journal of Genetics and Forest and Rangelands Plants Rehabilitation. 2:46: 247-258.
16
[ 17] Rybiñski W., B. Szot and R. Rusinek.(2008). Estimation of morphological traits and mechanical properties of grasspea seeds (Lathyrus sativus L.) originating from EU countries. Int. Agrophysics, 2008, 22, 261-275.
17
[18] Rosso, B.S., Pagano, E.M. and Rimieri, P. ( 1966). Evaluation and utilization of tall fescue germplasm collection at Pergamino Inta. Argantina.
18
[19] Sanadgol, A. (1991). Assessing adaptation of forage plant in Marevehtapeh, Chaparghoymeh and Aghghala region, Technical report of Research Institute of Forests and Rangelands.
19
[20] Stacey, T. (2003). Wheat crop establishment: Seeding rate and depth and row spacing .Canada Grains Council Complete Guide to Wheat Management.
20
[21] Total office of Natural resources in Kerman province. ( 2002). The balance between livestock and rangeland project from Kerman province.
21
[22] Vogel K. P., M. R. Schmer and R. B. Mitchell. (2005). Plant Adaptation Regions: Ecological and Climatic Classification of Plant Materials. Rangeland Ecology & Management 58: 315-319.
22
[23] Zahrabi, A., Etminan, A., Safari, H and A.A. Jafari. (2011). Evaluation forage yield stability in hispidus Elymus population with AMMI model and other stability analysis method in two condition of stress and without stress. Journal of rangeland, 2: 209-218.
23
ORIGINAL_ARTICLE
Simulation and numerical analysis of dust emission flux using WRF-Chem model and GOCART wind erosion schema (dust storm : 20 to 22 July 2015)
Today, the phenomenon of dust is known as one of the most important natural disasters in arid and semi-arid regions. The long-term effects of this phenomenon on the human health index are referred to as chronic disease. Therefore, studying and identifying the patterns and centers of this phenomenon seems necessary in these areas. In this study, in order to simulate the dust emission flux to determine the internal and external critical centers in the central plateau of Iran, WRF-Chem model and GOCART wind erosion scheme and storm were used from July 19 to 21, 2015. The results showed that the Arabian deserts in Saudi Arabia, the deserts of Iraq, as well as the Gharegham desert in Turkmenistan and the Helmand region in Afghanistan are among the most important foreign crisis centers affecting Iran's central plateau atmosphere. Also, the Central Desert (Dasht-e Kavir) has been identified as the main source of dust and the southern parts of the Central Loot Basin and the Jazmourian Basin have been identified as the internal sources of dust. The results also showed that in the Central Loot basin, the amount of 6900 micrograms per square meter of dust increases per second due to the erosion conditions.
https://jrwm.ut.ac.ir/article_80542_91037d2b6d030e1c52d5098b119dac85.pdf
2021-02-19
876
882
10.22059/jrwm.2020.301398.1490
Dust Flux
WRF-Chem model
GOCART Scheme
Central Desert and Loot Plain
Central Plateau of Iran
TAYYEBEH
MESBAHZADEH
tmesbah@ut.ac.ir
1
university of tehran
AUTHOR
Ali
Salajegheh
salajegh@ut.ac.ir
2
دانشگاه تهران
AUTHOR
farshad
soleimani sardoo
farshad.soleimani@ut.ac.ir
3
university of jiroft
LEAD_AUTHOR
Gholamreza
Zehtabian
ghzehtab@ut.ac.ir
4
university of Tehran
AUTHOR
Abbas
Ranjbar
aranjbar@gmail.com
5
SS
AUTHOR
Mario
Marcello Miglietta
m.marcello@gmail.com
6
ss
AUTHOR
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31
ORIGINAL_ARTICLE
Clarifying the role and value of awareness of local communities in increasing the participation in rangeland protection
(Case study: Malard County)
This study aims to examine the role and value of local community awareness of the economic value of carbon sequestration as an important rangeland ecosystem services in order to increase the participation of local community for conservation of rangeland. In order to explain the role and value of awareness in increasing the participation of people in both experimental and control groups, Contingent Valuation Method and dichotomous choice – double bounded format was used and willingness of local communities to pay to preserve pastures were measured. The results showed in two separate groups have a significant difference in terms of willingness to pay for conservation of rangeland, that the difference between the willingness to pay represents the exact value of awareness in increasing willingness to pay for conservation of pasture. In the experimental group, the average willingness to pay was 89410.84 Rials and in the control group average, the average willingness to pay was 32560.88 Rials. The difference between the average willingness of people to pay in two groups is the equivalent of 57039.12 Rials. The average willingness of people to pay each year in the village of test and control group respectively is 2587230.6 and 1657100.05 Rials. The proposed knowledge up to local communities in the Malard County of the carbon sequestration process as well as the role and its position in relation to the welfare of local communities, especially with regard to the beginning of the implementation of the International Generalized Carbon Sequestration in the county take priority.
https://jrwm.ut.ac.ir/article_80543_496d9b51628d315da19e46ce455a0c11.pdf
2021-02-19
883
892
10.22059/jrwm.2018.234226.1132
Awareness
Economic Value
Carbon sequestration
Local Community
participation
maede
nasry
maede.nasry@ut.ac.ir
1
M.Sc Student Desert Management, Department of Arid and Mountains Regions Reclamation, Faculty of Natural Resources, University of Tehran, Karaj, Iran
AUTHOR
Mohammad
Jafari
jafary@ut.ac.ir
2
null
AUTHOR
Hossein
Azarnivand
ut@ut.ac.ir
3
null
AUTHOR
Hamed
Rafiee
hamedrafiee@ut.ac.ir
4
null
AUTHOR
[1] Adeli Sardoei, M., Babollah, H. and Pishbahar, E. (2012). Estimating the Willingness to Pay off some JIROFT Households to Protect Wildlife and a Determination of the Factors Affecting It (Case study: Grey Francolin). Iranian Journal of agricultural economic and development research, 2(43), 253-262.
1
[2] Andrade, G. S. and Rhodes, J. R. (2012). Protected areas and local communities: an inevitable partnership toward successful conservation strategies? Ecology and Society, 17(4), 14.
2
[3] Cameron, T. A. and James, M. D. (1987). Estimation Methods for Close-Ended Contingent Valuation Surveys. Review of Economics and Statistics, 69, 269-276.
3
[4] Dixon, R. K., Winjun, J. K., Adrasko, K. J. and Schroeder, P.E. (1994). Integrated Land –use systems: assessment of promising agro forest and alternative land-use practices to enhance carbon conservation and sequestration. Climate Change. 30,1-23.
4
[5] Fatahi, A. and Fathzadeh, A. (2012). Preserving valuation of watershed areas using contingent valuation method (case study: Gomishan wetland). Iranian journal of watershed management science and engineering, 5(17), 47- 52.
5
[6] Forouzeh, M.R., Heshmati, Gh. A., Mesbah, S.H. and Ghanbarian, Gh.A. (2008). Effect of floodwater irrigation on carbon sequestration potential of Helianthemum Lipii (L.) pers., dendrostellera lesserti van tiegh And Artemisia Sieberi besser in the Gareh Bygone plain: a case study. Pajouhesh VA Sazandegi Journal. 21(1), 11-19.
6
[7] Hanemann, M. W. (1984). Welfare evaluation in contingent valuation experiments with discrete responses. American journal of Agricultural Economic, 66, 332-341.
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[8] Kniivila, M. (2006). Users and non-users of conservation areas: Are there differences in WTP, motives and the validity of responses in CVM surveys? Ecological Economics, 59, 530- 539.
8
[9] Lamsad, P., Pant, K. P., Kumar, L. and Atreya, K. (2015). Sustainable livelihoods through conservation of wetland resources: a case of economic benefits from Ghodaghodi Lake, western Nepal. Ecology and Society, 20(1), 10.
9
[10] Lee, C. K. and Han, S. Y. (2002). Estimating the Use and Preservation Values of National Parks Tourism Resources Using A Contingent Valuation Method. Tourism Management, 23, 531-540.
10
[11] Mahmoudi, J., Heidari, Gh. and Mirbozorgi, M. S. (2011). The obstructions of grazing management project from the viewpoint of Natural Resources Experts. Renew. Natural Resource Journal, 2(4), 231-242.
11
[12] Rahman, M. and Asmawi, Z. (2015). Local Residents’ Awareness towards the Issue of Mangrove Degradation in Kuala Selangor, Malaysia. Indonesia, Annual Serial Landmark International Conferences on Quality of Life. Quality of Life in the Bbuilt and Natural Environment 3. Jakarta, April 25-27.
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[13] Triguero, M., Olomi, M., Jha, N., Zorondo, F. and Reyes, V. (2010). Urban and rural perceptions of protected areas: a case study in Dandeli Wildlife Sanctuary, Western Ghats, India. Journal of Environmental Conservation, 36, 208-217.
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[14] Williams, W. D. (2002). Community participation in conserving and managing inland waters. Aquatic Conservation, Marine and Freshwater Ecosystems Journal. 12(3), 315-326.
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[15] Wood, A., Hailu, A., Abbot, P. and Dixon, A. (2002). Sustainable management of wetlands in Ethiopia: local knowledge versus government policy, strategies for wise use of wetlands: best practices in participatory management. Wetlands International Journal. 56, 81-88.
15
[16] Wong, E. (2006). Public participation in environmental planning and the preparation process of local plans. Paper presented at the Fourth Sabah-Sarawak Environmental Convention.
16
[17] Yeganeh, H., Azarnivand, H., Saleh, I., Arzani, H. and Amirnejad, H. (2015). The estimated economic value of gas Regulation functions of rangeland ecosystems in the Taham watershed. Journal of Rangeland. 9(2), 106-119.
17
ORIGINAL_ARTICLE
Investigating land-use changes in Jiroft plain in the present and future period with a look at agricultural land-use suitability
Evaluating of the development of crops based on water needs along with detecting and predicting land use changes will provide a clear picture of changes in water resources and anthropogenic effects of the agricultural sector for environmental planners to plan more consciously in the field of water and soil conservation, Therefore, the current study was conducted with two general objectives. The first goal was to examine land use in the past and predict land use in the future using the Land Change Modeler (LCM) and logistic regression method. Detecting land use changes was performed using Landsat satellite images including sensors of TM (1990), ETM+ (2001) and OLI (2019). The second object of the study was to examine the development trend of agricultural products in terms of water needs in the last three decades, which was examined based on databases of the Agricultural Jihad Organization (AJO). The transition potential modelling was performed based on logistic regression method and variables of digital elevation model (DEM), slope, aspect, geology, the distance from fault, the distance from road, the distance from river, distance from residential lands, NDVI and land use was predicted using Markov chain in future. Also, the trend of changes in the area under cultivation of major crops based on water needs in Jiroft plain was studied based on the data of the last three decades and the data of the National Irrigation Document, which has been less considered by researchers in land use change studies.
https://jrwm.ut.ac.ir/article_80954_aef09c6ce3a128f78670798380b5fcb4.pdf
2021-02-19
893
913
10.22059/jrwm.2020.307198.1522
Land Use Change
Cultivation development
Jiroft plain
Crops
Water requirement
Mohsen
Adeli Sardooei
mohsenwsu@gmail.com
1
Department of agricultural development and management, University of Tehran: ّFaculty member,, University of Jiroft, Jiroft, Iran
AUTHOR
Ali
Asadi
mohsen.adelis@ut.ac.ir
2
Department of agricultural development and management, University of Tehran
LEAD_AUTHOR
Khalil
Khalil
khkallan@ut.ac.ir
3
Dept. Agricultural Management and development, University of Tehran
AUTHOR
Ali Akbar
Barati
abarati@ut.ac.ir
4
Dept. Agricultural Management and development, University of Tehran
AUTHOR
Hassan
Khosravi
hkhosravi@ut.ac.ir
5
Associate Professor, Faculty of Natural Resources, University of Tehran
AUTHOR
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