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Paper Information

Journal:   JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES)   WINTER 2017 , Volume 69 , Number 4; Page(s) 1043 To 1062.
 
Paper: 

NUMERICAL ANALYSIS OF APPLYING QUANTITATIVE AND QUALITATIVE SCENARIOS ON KHEZEL AQUIFER IN HAMEDAN PROVINCE WITH MODFLOW AND MT3DMS MODELS

 
 
Author(s):  GHOBADIAN R., BAHRAMI Z.*
 
* FACULTY OF AGRICULTURE SCIENCE, RAZI UNIVERSITY, KERMANSHAH, I. R. IRAN
 
Abstract: 

Increased exploitation of groundwater besides recent periods of drought caused a negative balance in Khezel aquifer located in Hamedan province, Iran. From 2000 to 2010, groundwater surface drop was estimated 5.8 meters. With regard to high potential of GMS in using GIS and careful stratification of the aquifer, GMS was used in present study to investigate and predict the groundwater table fluctuations in Khezel aquifer. Thus, Quantitative modeling was performed using MODFLOW model. The model was calibrated (using trial and error method) in two conditions: steady state (in september 2009) and transient state (from October 2009 to July 2010). Also, the quantitative model validated for August 2010. The impact of groundwater artificial recharge (within 31 injection wells for 5 months from October to March) was evaluated by calibrated model. Results showed maximum rise of water level was 19 cm in April. Next, in the same flow simulation stress periods, qualitative modeling was carried out by MT3DMS model. Optimum values of longitudinal dispersion and distribution coefficient were achieved by trial and error method and the qualitative model was calibrated. Statistical results of qualitative modeling are as follow: R2=0.98, slope of regresion line (y=1.0079x), mean error (ME=4.56 ppm) and RMSE=3.36%. Finally, dispersion of point source pollution (leaching pit) was investigated as a scenario. The result indicated that the radius of influence of leaching pits varies from 150 to 200 m in different areas.

 
Keyword(s): GROUNDWATER, QUANTITATIVE AND QUALITATIVE SIMULATION, MODFLOW, MT3DMS
 
References: 
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  Persian Abstract Yearly Visit 102
 
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