The Relationship Between Nitrate Distribution in Groundwater and Agricultural Landuse (Case study: Ardabil Plain,Iran)

Document Type : REVIEW PAPER


1 Young Researchers Club, Ardabil Branch, Islamic Azad University, Ardabil Iran

2 Basij Sq., Department of environmental Sciences and Engineering, Ardabil Branch, Islamic Azad University, Ardabil, Iran

3 Department on environmental Sciences, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran



The use of chemical fertilizers in agricultural sector leads to increase of nitrate concentrations in surface and groundwater. The present study determined the vast impacts of agriculture in Ardabil Plain in the northwest of Iran. The study surveyed and measured the amount of nitrate concentration in groundwater sources of 46 wells in the region. Arc GIS software was used to zoning of the area by ordinary kriging function. To match the changes of nitrate concentrations with the land use patterns, images of Landsat Satellite ETM+ in June of 2012 was applied. To determine the relationship of agricultural land use with nitrate distribution in the area SPSS 16 software was used. According to the regression results, the use of agricultural land use and the amount of chemical fertilizer in the region are highly related with nitrate distribution with 95% accuracy. The results showed that the source of nitrate input to the region is the use of artificial nitrate fertilizer in agricultural activities.


Akbari M, Jorge MR, Madanisadat H, 2009, Evaluation of underground water level drop using Geographic Information System (GIS). Case Study: Mashhad Plain Aquifer. Journal of Soil and Water Conservation Research (In persian), 44(4): 144–156.
 Al Sheikh AA, Abdul Qadri Bukani N, Hojjat SA. 2008, Modeling of Groundwater Contamination through Geostatistical Analysis (Case Study: Shiraz City), Geomatics Conference 87, Tehran, Iran Mapping Organization, https: // www.
 Alavipanah SK. 2018, Application Remote Sensing in Land Science (Soil Science), Tehran: University of Tehran, p.496.
 Barca E, Passarella G. 2008, Spatial evaluation of the risk of groundwater quality degradation. A comparison between disjunctive kriging and geostatistical simulation, Environ. Monitoring Assessment, 137: 261–273.
Bradley K, Esser GB, HudsonJean E, MoranHarry R, Beller Tina M, CarlsenBrendan P, Dooher Pa, Krauter WW, Mcnab MDelores RMarko VNathan R. 2011, Nitrate Contamination in California Groundwater: An Integrated Approach to Basin Assessment and Resource Protection, Environmental Science, UCRL-ID-151454 DRAFT, DOI:10.2172/1062757
Fataei E. 2012, Evaluation Ardabil Plain Groundwater wells Quality, Environmental Geology Journal(In Persian), 6(21): 65-76, 2012.
Foody, G.M. 2000, Mapping Land Cover from Remotely Sensed Data with a Softened Feedforward Neural Network Classification. Journal of Intelligent and Robotic Systems 29(4): 433–449.
Rivett MOBuss SRMorgan PSmith JWBemment CD. 2008, Nitrate attenuation in groundwater: a review of biogeochemical controlling processes. 42(16):4215-32. doi: 10.1016/j.watres.2008.07.020.
 Mitra A,  Lohochoudhury B. 2019, Identifying Anthropogenic Factors of Groundwater Pollution through Student’s Opinion in Rural West Bengal, Anthropogenic Pollution Journal, 3 (2): 51-61, DOI: 10.22034/ap.2019.668547
 Nick Qoogh Yand Kabeli AR. 2010, Vulnerability Assessment of Gorgan Plain Across DRASTIC, 4th Specialized Conference on Environmental Engineering, Tehran University, Faculty of Environment, .html
 Sepehry A, Mottaghi MR, 2002. Vegetation Indices for Estimation of Canopy Cover Percentage of Rangeland Vegetation (In Protected Area of Jahan – Nama, Gorgan). Iranian Natural Resources(In persian), 55(2): 1-14.
Shabani M. 2009, Survey Arsanjan plain Groundwater Quality change, Natural Geography Journal(In Persian), 1(3): 71-82.
Suthar S. 2010, Contaminated Drinking Water and  Rural Health Perspective in Rajesthan , India : an Overview  of recent  case studies. Environmental Monitoring and Assessment, 173(1-4):837-849, DOI: 10.1007/s10661-010-1427-2.
Yao L, Huo Z, Feng Sh, Mao X, Kang Sh, Chen J, Xu J, Steenhuis TS. 2013, Evaluation of spatial interpolation methods for groundwater level in an arid inland oasis, northwest China, Environmental Earth Sciences, 71(4): 911–1924, DOI: 10.1007/s12665-013-2595-5
Yuan F, Sawaya KE, Loeffelholz BC, Bauer ME. 2005, Land cover classification and change analysis of the Twin Cities (Minnesota) metropolitan area by multitemporal Landsat remote sensing. Remote Sensing of Environment, 98(2-3), 317-328.
  • Receive Date: 18 December 2019
  • Revise Date: 01 February 2020
  • Accept Date: 11 February 2020
  • First Publish Date: 01 March 2020