Assessment of groundwater salinity risk using kriging methods: A case study in northern Iran

被引:25
作者
Ashrafzadeh, Afshin [1 ]
Roshandel, Fateme [1 ]
Khaledian, Mohammadreza [1 ]
Vazifedoust, Majid [1 ]
Rezaei, Mojtaba [2 ]
机构
[1] Univ Guilan, Dept Water Engn, Fac Agr Sci, Rasht, Iran
[2] Agr Res Educ & Extens Org, Rice Res Inst Iran, Rasht, Iran
关键词
Ordinary kriging; Cokriging; Indicator variables; Guilan Province; MONITORING NETWORK; INTERPOLATION; OPTIMIZATION; ELEVATION; QUALITY;
D O I
10.1016/j.agwat.2016.09.028
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
The suitability of groundwater for paddy field irrigation in the alluvial plains of Guilan Province, northern Iran, was investigated using ordinary kriging and ordinary cokriging of continuous and indicator quality variables. The cross validation values of error measures showed that ordinary cokriging provides more accurate estimates of the quality variables of interest. Maps showing the spatial variability of electrical conductivity (EC) and sum of major cations and anions (SCA) were generated for the years 2010 through 2014, using ordinary cokriging. Based on the estimated values of EC and SCA, four groundwater salinity classes (excellent, good, risky, and unsuitable) were considered and the proportion of the study area covered by each class was obtained. Results showed that the portion of the study area covered by the risky class, in which the groundwater salinity is expected to reduce the rice yield, is located in the eastern part of the study area and has an average value of 25.4% in the period 2010-2014. The results also showed that the western part of the study area has excellent or good groundwater quality for rice irrigation. The probability maps of EC were also obtained using ordinary cokriging of EC indicator variable. Five probability classes were considered and the proportion of the study area covered by each class was obtained. It was observed that the probability that the rice yield is reduced more than 10% is above 0.4 in 6.2% of the study area. The maps generated in this study can be used to identify the regions in the province where groundwater could be allowed to be extracted and utilized by farmers to reduce the bad effects of the scarcity of surface water. Also, in the regions with a risk of rice yield reduction, conjunctive use of groundwater and surface water could be planned and advised to farmers. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:215 / 224
页数:10
相关论文
共 31 条
  • [1] Ahmadpour H., 2013, IRANIAN WATER RES J, V7, P169
  • [2] APHA, 1998, Standard methods for the examination of water and waste water, V20th
  • [3] Spatial and temporal mapping of groundwater salinity using ordinary kriging and indicator kriging: The case of Bafra Plain, Turkey
    Arslan, Hakan
    [J]. AGRICULTURAL WATER MANAGEMENT, 2012, 113 : 57 - 63
  • [4] Bradal A, 2016, J IRRIG DRAIN ENG, V142
  • [5] FIELD-SCALE VARIABILITY OF SOIL PROPERTIES IN CENTRAL IOWA SOILS
    CAMBARDELLA, CA
    MOORMAN, TB
    NOVAK, JM
    PARKIN, TB
    KARLEN, DL
    TURCO, RF
    KONOPKA, AE
    [J]. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 1994, 58 (05) : 1501 - 1511
  • [6] Categorical Indicator Kriging for assessing the risk of groundwater nitrate pollution: The case of Vega de Granada aquifer (SE Spain)
    Chica-Olmo, Mario
    Antonio Luque-Espinar, Juan
    Rodriguez-Galiano, Victor
    Pardo-Iguzquiza, Eulogio
    Chica-Rivas, Lucia
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2014, 470 : 229 - 239
  • [7] Comparison of ordinary kriging and artificial neural network for spatial mapping of arsenic contamination of groundwater
    Chowdhury, Mohammad
    Alouani, Ali
    Hossain, Faisal
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2010, 24 (01) : 1 - 7
  • [8] Spatial Variability of Groundwater Depth and Quality Parameters in the National Capital Territory of Delhi
    Dash, J. P.
    Sarangi, A.
    Singh, D. K.
    [J]. ENVIRONMENTAL MANAGEMENT, 2010, 45 (03) : 640 - 650
  • [9] Davatgar N., 2006, Journal of Science and Technology of Agriculture and Natural Resources, V9, P71
  • [10] Delbari M., 2014, APPL WATER SCI, V9