The Impact of Land Use/Land Cover Changes on Groundwater Resources Using Remote Sensing & GIS (Case Study: Khan-Mirza Plain)

Document Type : Research Paper


1 Dept. of Geographical Sciences and Planning, University of Isfahan, Isfahan, Iran

2 Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Isfahan, Iran


Hydrological status and water table fluctuations are directly related to land use and/or land cover (LULC) changes in each area. In this research, the impact of LULC changes on groundwater quantity and quality of Khan-Mirza Plain, in the northern Karun watersheds, was investigated. For this purpose, Landsat 5, 7 and 8 satellite images and ETM and OLI sensors were employed to prepare the LULC map of Khan-Mirza Plain for 2006 and 2016 using the artificial neural network algorithm. The neural network algorithm with the general accuracy of 90/29 was classified into six use classes (agriculture, rangeland, residential areas, rocky and bare lands, gardens and lowlands). Analysis of changes indicated that agricultural and residential uses were increased, respectively, by 62.5% and 3.5%. The biggest change was in conversion of the rocky and bare lands for the agricultural use. Another change was in the LULC of rocky and bare lands and rangelands: these have been converted into to the residential areas. A few piezometric wells in the plain were also used to investigate the lowering of the groundwater table during the 2006- 2016 period. The quality parameters investigated were calcium, sodium, magnesium, potassium, all soluble solids, electrical conductivity, sulfate, chlorine, bicarbonate, and water acidity (PH). Investigation of the time variation of the groundwater quality parameters further showed that potassium, water acidity, and bicarbonate followed an upward trend during the studied time. Most chemical parameters of water had the highest concentrations in the central plain area. The results, therefore, showed that increase of degradation and growth of human activities in the region had both caused changes in the LULC, subsequently intensifying the quantitative and qualitative loss of groundwater in the Khan-Mirza Plain. Therefore, the areas with irrigated agriculture, dry farming, and undeveloped agriculture have been increased. One of the main reasons for lowering of water table in 2016 was the excessive exploitation of groundwater as a result of the change in agriculture uses.


Ahmed, S., 2007. Application of geostatistics in hydrosciences. In Groundwater, Edited by: Thangarajan, M. 78–111. The Netherlands: Springer.
Beven, K. J., J. Fischer, 1996. Remote sensing and scaling in hydrology. In Scaling up in hydrology using remote sensing. Ed. J. B. Stewart, T. Engman, R. A. Feddes and Y. Kerr, 1-18 New York: John Wiley.
Chen, X.W., 2002. Using remote sensing and GIS to analyses land cover change and its impacts on regional sustainable development. International Journal of Remote Sensing, 23; 107-124.
Karimian et al. / Desert 24-2 (2019) 319-330
Dams, J., S.T. Woldeamlak, O. Beatellan, 2008. Predicting land-use change and its impact on the groundwater system of the Kleine Nete catchment, Belgium. Hydrology and Earth System Sciences, 12; 1369–1385.
Delhomme, J.P., 1974. La cartographie d'une grandeur physique a partir des donnees de differentes qualities. In International Association of Hydro-geologists ed. Proc. of IAH Congress (Montpellier, France) Montpellier; 185–194. France: IAH.
Deutsch, C.V., A.G. Journel, 1992. GSLIB: Geostatistical software library and user's guide, New York: Oxford University Press.
Ekrami, M., Z.A. Sharifi, H. Malekinejad, M.R. Ekhtesasi, 2011. Investigating quantitative and qualitative changes of groundwater resources in Yazd-Ardakan plain over 2000-2009. Toloe Behdasht, 10; 82-91.
Khan, M.N., V.V. Rastoskuev, Y. Sato, S. Shiozawa, 2005. Assessment of hydrosaline land degradation by using a simple approach of remote sensing indicators. Agricultural Water Management, 77; 96-109.
Kitanidis, P.K, 1997. Introduction to geostatistics, Cambridge: Cambridge University Press.
Marengo, E., M.C. Gennaro, E. Robotti, A. Maiocchi, G. Pavese, A. Indaco, A. Rainero, 2007. Statistical Analysis of Groundwater Distribution in Alessandria Province (Piedmont- Italy). Microchemical Journal, 88; 167-177.
Mortezaei, Q., A. Kohandel, 2015. Investigating the impact of land use changes on groundwater resources using satellite images (Case Study: Chaharmahal Bakhtiari). Journal of Watershed Management Sciences and Engineering, 9; 1-9.
Mouser, P.J., 2005. A multivariate statistical approach to spatial representation of groundwater contamination using hydrochemistry and microbial community profiles. Environmental Science and Technology, 39; 7551–7559.
Pijanowski, B.C., D.G. Brown, B.A. Shellito, G.A. Manik, 2002. Using neural networks and GIS to forecast land use changes: A Land Transformation
Model. Computers Environment and Urban Systems, 26; 553-575.
Rahman, M.H., R.M. Habibnejad, L. Gholami, 2017. Evaluation of land use role on groundwater quality changes in Lajan Basin. Natural Ecosystems of Iran, 8; 83-99.
Rahmati, A., N. Mahmoodi, A. Mosaedi, F. Hidari, 2013. Assessing the effect of landuse and lithology on spring water quality in Piranshahr watershed, Iranian Journal of Watershed Management Science, 8; 19-26.
Scanlon, B., R. Reedy, D. Tonestromw, D. Prudicz, K. Dennehy, 2005. Impact of land use and land cover change on groundwater recharge and quality in the southwestern US. Global Change Biology, 11; 1577– 1593.
Shaban, M., 2006. The application of digital data + ETM in mapping land use to improve rangeland management in Mouteh Wildlife Refuge. The first conference, University of Rangeland management.
Shakiba, A., B. Mirbagheri, A. Khairi, 2011. Drought evaluation and its impact on groundwater resources using the SPI Index in East of Kermanshah Province. First National Conference on Drought and Climate Change, Karaj, Dehydration and Drought Research Center in Agriculture and Natural Resources.
Singh, S.K., C.K. Singh, S. Mukherjee, 2010. Impact of land-use and land cover change on groundwater quality in the Lower Shiwalik hills: a remote sensing and GIS based approach. Central European Journal of Geosciences, 2; 124-131.
Tabatabaei, H.R., N. Lalehzari, M. Noormehnad, H. Khazaii, 2010. The effect study of land use changes on ground water quality (Case study: Shahrekoord plain). Journal of Research in Agricultural Science, 6; 37-46.
Yuan, F., K. Sawaya, B. Loeffelholz, M. Bauer, 2005. Land cover classification and change analysis of the Twin Cities (Minnesota) metropolitan area by multi temporal Landsat remote sensing. Remote Sensing of Environment, 98; 317–328