Investigating the effective factors on water area changes in Shadegan Wetland using remote sensing technique and factor analysis

Document Type : Original Article


1 Desert Research Department, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran

2 Department of Desert Sciences, Faculty of Natural Resources and Earth Sciences, Kashan University, Kashan, Iran

3 Rangeland Research Department, Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran


Introduction: Water depletion in wetlands, due to both natural and unnatural reasons, leads to the extinction and death of living organisms. After successive droughts, if flooding and rehydration occur, their recovery is highly unlikely. According to the Ramsar Agreement, the area of Shadegan Wetland is 537731 hectares and includes freshwater area, tidal zone, Mousa creek, and marginal lands. The freshwater area of the wetland is about 164 thousand hectares based on the Landsat satellite image during flooding and is equivalent to 28% of the total area of the wetland. This wetland is extremely important due to various functions such as flood control, air conditioning, soil erosion control, plant and animal habitat, and providing livelihood. The purpose of this study is to monitor the trend of changes in the freshwater area of the wetland using satellite images and identify the factors affecting changes in its area.
Material and methods:  Landsat TM, ETM +, and OLI satellite data from 1998 to 2017 were used to monitor the water area of Shadegan Wetland. Various climatic, hydro-climatic, and water management factors were extracted for the study period in the whole watershed. The trend of changes and their relationship with changes in the wetland water area were investigated using the principal component analysis (PCA) method, and the factors that explained the highest variance of water changes were identified and analyzed.
Results and discussion: The trend of changes in the water area of Shadegan Wetland was increasing. Data using KMO and Bartlett statistics showed that the studied elements were suitable for changes in water area based on factor analysis. The results of factor analysis showed that five factors played an important role in changing the water area of Shadegan Wetland. In total, five factors were able to explain 88.9% of the variance of the data; the first factor was the temperature, the area under cultivation, the number of earthen dams and drains entering the sugarcane, which explained approximately 36% of the variance. The second factor was the humidity of the basin which explained 15% of the variance. The third factor was the instant discharge’s drought that explained 14.9% of the total variance. The fourth factor was discharge and precipitation with 11.8%, and the fifth factor was wetland moisture, which explained 11.2% of the variance of water area changes.
Conclusion: Wetlands that are situated at the foothills of watersheds are affected by the factors in the watershed. In total, five factors were able to explain 88.9% of the variance of the changes. In the first factor, apart from temperature, three factors that result from human activities were the most important: the area under cultivation due to the development of large irrigation projects, use of water sources of Jarahi River, which is the source of 90% of water input to the lagoon and numerous dams, dams upstream of the wetland that prevent the arrival of flood and seasonal runoff, and sugarcane drainage as inlet water to the wetland. In order to manage the wetland, reduction of human activities and utilization of water resources in order to provide the natural water of the wetland should be considered so that the wetland can continue as a living ecosystem.


Asghari Poudeh, Z., Ghadirian Baharanchi, O., Nematallahi, S., Fakheran, S. and Pourmanafi, S., 2019. Monitoring and prediction of land use/cover changes in Shadegan international Wetland, Iran. Iranian Journal of Applied Ecology. 8(3), 63-76, (In Persian with English abstract).
Behzadi karimi, H. and Mizafari, G.H.A., 2017. Estimation of groundwater levels in Bayza plain using geostatistical methods. Journal of Geography and Environmental Studies. 6(21), 145-163. (In Persian with English abstract).
Bureau, R.C., 2000. Ramsar Handbooks for the Wise Use of Wetlands. Ramsar Convention Bureau. 3rd edn. (Ramsar Convention Secretariat: Gland, Switzerland), 220 p.
Chen, J., Wang, S.Y. and Mao, Z.P., 2011. Monitoring wetland changes in Yellow River Delta by remote sensing during 1976–2008. Progress in Geography, 5.
Chen, L., Jin, Z., Michishita, R., Cai, J., Yue, T., Chen, B. and Xu, B., 2014. Dynamic monitoring of wetland covers changes using time-series remote sensing imagery. Ecological Informatics. 24, 17-26.
Chovok, J. and Mohseni, M., 2016. Investigating the process of land use change in Parishan Wetland using remote sensing. Journal of Zist Sepehr, 11(2), 11-19. (In Persian with English abstract).
Dargahian, F., Razavizadeh, S. and Lotfi Nasab Asl, S., 2018. The role of water resources management as one of the effective factors in intensifying the activity of the dust center in the south and southeast of Ahvaz. Iranian Journal of Nature, 3(4), pp. 26-.33(In Persian with English abstract).
Dashti, S.S., Sabzghabai, G.h.R., Jafarzadeh, K. and Bazmara Baleshti, M., 2018. Evaluation of Trends in Mesopotamian Coastal Wetland with Land Use Approach. Journal of Wetland Ecobiology. 10(4), 20-5. (In Persian with English abstract).
Deng, H. and Chen, Y., 2017. Influences of recent climate change and human activities on water storage variations in Central Asia. Journal of Hydrology. 544, 46-57.
Ebrahimikhusfi, Z., Khosroshahi, M., Naeimi, M. and Zandifar, S., 2019. Evaluating and monitoring of moisture variations in Meyghan wetland using the remote sensing technique and the relation to the meteorological drought indices. Journal of RS and GIS for Natural Resources. 10(2), 1-14. (In Persian with English abstract).
Ebrahimikhusfi, Z., Vali, A., Khosroshahi, M. and Ghazavi, R., 2017. Investigation of the role of bed dried Gavkhooni wetland on the production of the internal dust using remote sensing and dust storms (Case study: Isfahan province). 24(1), 152-164. (In Persian with English abstract).
Hanasaki, N, Yoshikawa, S, Pokhrel, Y. and Kanae, S., 2018. A global hydrological simulation to specify the sources of water used by humans. Hydrology and Earth System Sciences. 22(1), 789-817.
Javadi, F., Rezayan, S. and Jozi, S., 2020. Evaluating Satellite Indicators in Determining the Level of Aquatic Areas Using Satellite Sensors (Case Study: Zaribar Wetland, Kurdistan Province). Iranian journal of Ecohydrology. 7(2), 539-550. (In Persian with English abstract).
Karami, P. and Mirsanjeri, M., 2018. An Analysis of Destruction of Landform in Hawizi's Great Wetlands Using Remote Sensing. Journal of Wetland Ecobiology. 10(1), 29-54. (In Persian with English abstract).
Kayastha, N., Thomas, V., Galbraith, J. and Banskota, A., 2012. Monitoring wetland change using inter-annual landsat time-series data. Wetlands. 32(6), 1149-1162.
Khangholi, E., Naderi, M., Hadi Pour, M. and Alyi Pourardi, M., 2018. Estimation of Minimum Aquatic Environmental Requirement of the Megan Desert. Journal of Wetland Ecobiology. 10(3), 102-91. (In Persian with English abstract).
Khosravi, R., Hassanzadeh, R., Hossinjanizadeh, M. and Mohammadi, S., 2020. Investigating Water Body Changes Using Remote Sensing Water Indices and Google Earth Engine: Case Study of Poldokhtar Wetlands, Lorestan Province. Iranian journal of Ecohydrology. 7(1), 131-146. doi: 10.22059/ije.2020.295498.1265. (In Persian with English abstract).
Kuleli, T., Guneroglu, A., Karsli, F. and Dihkan, M., 2011. Automatic detection of shoreline changes on coastal Ramsar wetlands of Turkey. Ocean Engineering. 38(10), 1141-1149.
Mitsch, W. and Gosselink, J.G., 2016. Wetlands, Van Nostrand Reinhold .6th edition, New York, 772 p.
Papastergiadou, E.S., Retalis, A., Apostolakis, A. and Georgiadis, T., 2008. Environmental monitoring of spatio-temporal changes using remote sensing and GIS in a Mediterranean wetland of Northern Greece. Water Resources Management. 22(5), 579-594.
Pourkhbaz, H., Yousefi Khaneghah, S.h. and Salehi Pour, F., 2015. Investigation of Land Use Changes and Land Coverage of Shadegan Wetland Using Remote Sensing and GIS and Providing Management Strategies. Journal of Wetland Ecobiology. 7(25), 66-55. (In Persian with English abstract).
Rahimi Blouchi, L., Zarkar, A. and Malekmohammadi, B., 2014. Detecting environmental change of Shadegan international wetland using remote sensing and WRASTIC index (Case study: Shadegan international wetland). Journal of RS and GIS for Natural Resources. 5(2), 61-73. (In Persian with English abstract).
Rashki, A., Kaskaoutis, D.G., Rautenbach, C.D., Eriksson, P.G., Qiang, M. and Gupta, P., 2012. Dust storms and their horizontal dust loading in the Sistan region, Iran. Aeolian Research. 5, 51-62. (In Persian with English abstract).
Shen, G., Yang, X., Jin, Y., Xu, B. and Zhou, Q., 2019. Remote sensing and evaluation of the wetland ecological degradation process of the Zoige Plateau Wetland in China, Ecological Indicators. 104: 48-58.
Singh, S., Bhardwaj, A. and Verma, V.K., 2020. Remote sensing and GIS based analysis of temporal land use/land cover and water quality changes in Harike wetland ecosystem, Punjab, India. Journal of Environmental Management. 262:110355.
Zhang, S., Na, X., Kong, B., Wang, Z., Jiang, H., Yu, H. and Dale, P., 2009. Identifying wetland change in China’s Sanjiang Plain using remote sensing. Wetlands. 29(1), 302
Zhu, C., Zhang, X. and Huang, Q., 2018. Four decades of estuarine wetland changes in the Yellow River delta based on Landsat observations between 1973 and 2013. Water. 10(7), 933.