شماره ركورد :
1255999
عنوان مقاله :
Evaluation of Interpolation Techniques for Estimating Groundwater Level and Groundwater Salinity in the Salman Farsi Sugarcane Plantation
پديد آورندگان :
Sayadi Shahraki ، Atefeh Shahid Chamran University of Ahvaz. Ahvaz - Faculty of Water and Environmental Engineering - Ph.D. of Irrigation and Drainage Department , Boroomand-Nasab ، Saeed Shahid Chamran University of Ahvaz. Ahvaz - Faculty of Water and Environmental Engineering - Professor of Irrigation and Drainage Department , Naseri ، Abd Ali Shahid Chamran University of Ahvaz. Ahvaz - Faculty of Water and Environmental Engineering - Professor of Irrigation and Drainage Department , Soltani Mohammadi ، Amir Shahid Chamran University of Ahvaz - Faculty of Water and Enviromental Engineering - Associate Professor of Irrigation and Drainage Department
از صفحه :
67
تا صفحه :
78
كليدواژه :
IDW , Interpolation , Groundwater level , Groundwater Salinity , Kriging
چكيده فارسي :
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.
عنوان نشريه :
علوم و مهندسي آبياري
عنوان نشريه :
علوم و مهندسي آبياري
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