Irrigation Sciences and Engineering

Irrigation Sciences and Engineering

Evaluation of Interpolation Techniques for Estimating Groundwater Level and Groundwater Salinity in the Salman Farsi Sugarcane Plantation

Document Type : Research Paper

Authors
Atefeh Sayadi Shahraki 1
Saeed Boroomand-Nasab 2
Abd Ali Naseri 3
Amir Soltani Mohammadi 4
1 Ph.D. of Irrigation and Drainage Department, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz. Ahvaz, Iran.
2 Professor of Irrigation and Drainage Department, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz. Ahvaz, Iran
3 Professor of Irrigation and Drainage Department, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz. Ahvaz, Iran.
4 Associate Professor of Irrigation and Drainage Department, Faculty of Water and Enviromental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
10.22055/jise.2021.36270.1944
Abstract
Due to the essential role of groundwater resources as useable and depleting water resources, the study and management of groundwater exploitation are of great importance. Proper management of groundwater resources needs knowledge of the spatial variability of groundwater level and groundwater salinity over the study area. To obtain such information, appropriate interpolation and mapping of groundwater level and groundwater salinity based on a limited number of observations is needed. The purpose of the present study is to evaluate Ordinary Kriging and IDW interpolation techniques for estimating groundwater level and groundwater salinity in Salman Farsi Sugarcane Plantation (West of Iran). The results showed that the prediction accuracy of the Ordinary Kriging model for groundwater level and groundwater salinity parameters was higher than the IDW model. To this aim, the Root Mean Square Error (RMSE) value was calculated to simulate the groundwater level in Ordinary Kriging and IDW method by 1.02 and 2.14, respectively, and to simulate the salinity of groundwater by 1.45 and 2.79. Due to the acceptable accuracy of the results of the Kriging model, planners can, by updating the data of this model, use it to predict the quantity and quality of groundwater parameters.
Keywords
IDW
Interpolation
Groundwater level
Groundwater salinity
Kriging
Subjects
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Irrigation Sciences and Engineering
Volume 44, Issue 2
Summer 2021
Pages 67-78

  • Receive Date 03 January 2021
  • Revise Date 28 May 2021
  • Accept Date 31 May 2021
  • Publish Date 22 June 2021