Assessing the Relationship between the Shadgan Wetland Fluctuation levels and Water EC in Time Duration, Using Satellite Images and Geostatistical Methods
Subject Areas : Water resources managementBahman Yargholi 1 , Yasaman Samaei 2
1 - Assistant Professor, Agricultural Engineering Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Alborz, Iran.
2 - M.Sc. Graduate, Department of Water Engineering, Imam Khomeini International University, Qazvin, Iran
Keywords: geostatistical methods, Satellite Images, Shadeghan wetland, water salinity, water area,
Abstract :
Introduction: Wetlands are highly beneficial to human societies due to their positive environmental functions, direct and indirect functions, as well as their value as an asset. It has led to an increase in the attention given to their restoration and maintenance in different societies. Shadgan Wetland contains fresh-salty, and brackish water, and approximately 900 million cubic meters of Jarahi water resources enter Shadgean every year. The wetland is at risk of serious harm as a result of the developmental activities occurring around it, which are causing pollutants to enter the wetland and reducing the quantity of fresh water coming in. A number of factors contribute to the destruction of this wetland, including over-exploitation from its water resources, the discharge of urban waste within its limits, the fragmentation of the wetland as a result of road construction, the construction of stations to increase the pressure on electricity, gas and oil pipelines, as well as effluents from industries such as bread making, alcohol production, sugarcane cultivation and industry. The economic value of wetlands and climate regulation, flood prevention, protection of plant and animal diversity, beauty and inherent visual attractions of wetlands, tourist attractions, as well as creating an opportunity for migratory birds to nest and a place for scientific research are among the most important considerations in the design of a wetlands. The development of water resources schemes and the regulation of river flows are often recognized as the most serious threats to the ecological sustainability of rivers and wetlands. Method: This study attempts to determine the change in water salinity of Shadegan wetland in the last five decades using the electrical conductivity index due to the importance of Shadegan wetland in various ways. Finally, a relationship has been established between the area and the salinity of this significant wetland. Also, by using electrical conductivity data from 23 stations in the lagoon and with the help of satellite images and remote sensing techniques and interpolation methods (IDW), the changes of this index in the mentioned period were investigated, leading to a mathematical relationship. Results and Discussion: According to the research results, upstream human activities, especially dam constructions and agricultural development projects, have had a great impact on the quantity and quality of the wetland. With climate change and drought, these effects have intensified, resulting in a reduction of the wetland level as well as an increase in the salinity of the wetland water. These changes can be observed both in terms of their temporal and spatial dimensions. Consequently, the results show the trend of increasing salinity from the southern parts to the north and also the greater manifestation of the increase in salinity in the southern parts due to the decrease in the incoming fresh water flow (more than twice). According to the results, there are three salinity levels in the wetland: saline, brackish water, and super salinity, and a salinity increase is observed in all three zones The present results and equations are used as an achievement by water and environment managers and they can estimate the EC of water in key and indicator stations and finally at the level of the wetland by measuring the size of the wetland using different technologies. So over time, the levels and zones of saline and super salinity have expanded, and the levels of brackish water have decreased. It is expected that this process will continue over time, resulting in the sea salt water advancing towards the wetland and increasing the amount of salinity within it. Conclusions: According to this study, based on the relationship between salinity and the level of the wetland, as well as the water area of the wetland, it is possible to estimate its salinity in three zones. By measuring the salinity of water at several key stations within each of the three zones, the wetland's water level can be estimated. In monitoring, managing, and qualitatively protecting the wetland and consequently its species, this equation and its relationships can play an important role.
Bayat, R. & Jafari, S. (2016). Qarmishcheshmeh, B. Charkhabi, A. Study of the effect of fine dust on vegetation changes (Case study: Shadegan Wetland, Khuzestan). Remote Sensing and GIS in Natural Resources (Application of Remote Sensing and GIS in Natural Resources Science). 7 (2), 17-32. [In Persian]
Behzadi Karimi, H. & Omidvar, K. (2017). Spatial analysis of chemical parameters affecting groundwater quality using factor analysis techniques and geostatistical models (Case study: Beiza-Zarghan plain). Remote Sensing and GIS in Natural Resources (Application of Remote Sensing and GIS in Natural Resources Science). 8 (4 (29 in a row)), 17-35.
Chuck, J. & Mohseni, M. (2016). Investigating the trend of land use changes in Parishan Wetland using remote sensing. Zist Sepehr Student Journal. 11 (2), 11-19.
Dargahian, F. and Khosroshahi, M. (2020). Lotfi Nasab Asl, S. . Investigation of changes in water area of Shadegan wetland and its relationship with hydrological drought and sugarcane drainage. Environmental Science. 46 (2), 225-240. [In Persian]
Dashti, S. Sabzqabai, G. Jafarzadeh, K., Bazm Arabalshti, M. (2018). Evaluating the trend of changes in Miankaleh coastal wetland with land management approach. Wetland Ecobiology .5-20. [In Persian]
Dastranj, H., Tavakoli, F. & Sultanpour, A. (2017). Investigating the water level and volume variations of Lake Urmia using satellite images and satellite altimetry. Journal of Geographical Data (SEPEHR). 27(107), 149-163. doi: 10.22131/sepehr.2018.33569. [In Persian]
Hasanlu, M. Jamshidi, M. Sattari, M. (2018). Preparation of salinity map of Urmia Lake using support vector regression and Landsat-8 images. Hydrogeomorphology. 4 (14), 43-56. [In Persian]
Hosseini, S. M. & Qahramani, B. (2013). Asgari, H. Estimation of electrical conductivity and sulfate in groundwater of Mashhad using kriging method, 6th International Conference on Civil Engineering, Isfahan.
Hosseini, S., Nabavi, S., Rajabzadeh Qatarami, A. & Omidvar, V. (2010). Comparison of changes in the conservation values of Shadegan wetland by IMO, IUCN and (Salm and Price) method during the 60s to 80s. Ecology of wetlands (wetlands). 1 (4), 21-37. [In Persian]
Khalifa Nil Saz, m. (2016). Ecological monitoring of Shadgan lagoon, published by the Iranian fisheries science research institute. [In Persian]
Karami, P. Mirsanjari, M. (2018). Analysis of land degradation in Hoveyzeh large wetland using remote sensing. Wetland Ecobiology (Wetland). 10 (1 (35 consecutive)). 39-54.
Maqami,Y. Ghazavi, R., Vali, A. & Sharafi, S. (2010). Evaluation of different interpolation methods for water quality zoning using GIS (Case study: Abadeh city). Geography and Environmental Planning. Journal of Humanities Research, University of Isfahan. 22 (2 (42 consecutive)).171-182. [In Persian]
Martínez-López, J., Carre˜no, M. F., Palazón-Ferrando, J. A., Martínez-Fernández, J. & Esteve, M.A. (2014). Remote sensing of plant communities as a tool for assessing the condition of semiarid Mediterranean saline wetlands in agricultural catchments. International Journal of Applied Earth Observation and Geo-information. 26 (1): 193-204. [In Persian]
Mehrpooyan, M. Jami, M. & Pourkermani, M. (2013). Investigating the annual and seasonal changes of Jazmourian Lake in the years 1972-2012 with the help of satellite images and GIS software, Fifth International Conference on Comprehensive Management of Natural Crises, Tehran. [In Persian]
Mohammadi Roozbahani M, Rasekh A, & Jaafar Aghaei H. (2013). Biological assessment with use of HFBI index in Shadegan wetland. Wetland Ecobiology. 5 (3) :73-85. URL: http://jweb.ahvaz.iau.ir/article-1-176-fa.html. [In Persian]
Nilsaz, Kh. Ismaili, F. Sabzali, S. Eskandari, Ghar. Ansari, H. & Albouid, P. (2016). Ecological monitoring of Shadegan wetland. Fisheries Science Research Institute. [In Persian]
PoorKhabaz, H. & Yousefi Khanghah, SH. (2015).Salehipoor, F. Investigation of Land Use Change and Land Cover Shadegan Wetland Using Remote Gauge and GIS and Providing Management Solutions. Wetland Ecobiology Quarterly. 7 (25), 55-66.
Rafiei, A. Danehkar, A. & Zand Basiri, M. (2020). Bagherzadeh Karimi, M. Application of linear programming in measuring the feasibility of Shadegan wetland index according to the criteria of Ramsar Convention. Environmental Science. 46 (3), 421-436. [In Persian]
Rahimi Balochi, L. & MalekMohamady, B. (2013). Assessment of environmental risks of Shadegan. International Wetland based on ecological performance indicators. 39 (65), 112-101.
Ranjbar (1388).
Salehi, H. Motamedi, M. & Mafi, E. (2020). Validation of summer temperature interpolation methods in northeastern Iran, Quarterly. Journal of Applied Research in Geographical Sciences. 21 (61), 351-369.
Shang, S. (2015). A general multi-objective programming model for minimum ecological flow or water level of inland water bodies. Journal of Arid Land, 7 (2): 166-176.
Sima, S. & Tajrishi, M. (2006). Environmental Water Needs Assessment of Shadegan Wetland, 7th International Congress of Civil Engineering, Tehran.
Sun, X., Xiong, S., Zhu, X., Zhu, X., Li, Y. & Li, B. L. J. E. m. (2015). A new indices system for evaluating ecological economic-social performances of wetland restorations and its application to Taihu Lake Basin, China. Ecological modelling, 295: 216-226.
Tavakoli,M. Amini, D. & Faramarzi, M. (2020). Investigating the relationship between soil salinity change, land use and climatic factors (Case study: Shadegan, Khuzestan). Environmental science and technology, 22 (9): 43-58. [In Persian]
Xu, Y., Wang, Y., Li, S., Huang, G. & Dai, C. (2018). Stochastic optimization model for water allocation on a watershed scale considering wetland’s ecological water requirement. Ecological Indicators, 92: 330-341.