title: Application and evaluation of kriging and cokriging methods on groundwater depth mapping.
abstract: Groundwater and water resources management play a key role in conserving the sustainable conditions in arid and semi-arid regions. Applying some techniques that can reveal the critical and hot conditions of water resources seem necessary. In this study, kriging and cokriging methods were evaluated for mapping the groundwater depth across a plain in which has experienced different climatic conditions (dry, wet, and normal) and consequently high variations in groundwater depth in a 12 year led in maximum, minimum, and mean depths. During this period groundwater depth has considerable fluctuations. Results obtained from geostatistical analysis showed that groundwater depth varies spatially in different climatic conditions. Furthermore, the calculated RMSE showed that cokriging approach was more accurate than kriging in mapping the groundwater depth though there was not a distinct difference. As a whole, kriging underestimated the real groundwater depth for dry, wet, and normal conditions by 5.5, 2.2, and 5.3%, while cokriging underestimations were 3.3, 2, and 2.2%, respectively; which showed the unbiasedness in estimations. Results implied that in the study area farming and cultivation in dry conditions needs more attention due to higher variability in groundwater depth in short distances compared to the other climate conditions. It is believed that geostatistical approaches are reliable tools for water resources managers and water authorities to allocate groundwater resources in different environmental conditions.
authors.affiliation: Agricultural Research and Education Organization, Agricultural Engineering Research Institute, P.O. Box 73415-111, Zarghan, Iran. seyedhamid.ahmadi@gmail.com
authors.forename: Seyed Hamid
authors.initials: SH
authors.lastname: Ahmadi
authors.forename: Abbas
authors.initials: A
authors.lastname: Sedghamiz
mesh_terms: D003247:Conservation of Natural Resources; D003627:Data Interpretation, Statistical; D007492:Iran; D014881:Water Supply / Q000706:statistics & numerical data*