Zoning hydraulic conductivity using different geostatistical methods (Case study Shavoor)

Subject Areas : Irrigation and Drainage

محمد سلاخ پور ¹ (اهواز -موسسه جهاد نصر)
عباس ملکی ² (گروه مهندسی آب، دانشگاه لرستان، لرستان، ایران.)
علی مختاران ³ (آبیاری و زهکشی – موسسه جهاد نصر.)

Received: 2015-07-05 Accepted : 2015-11-15 Published : 2015-10-01

Keywords: Hydraulic conductivity, Geostatistics, زمین آمار, spatial interpolation, ordinary kriging, درونیابی فضایی, کریجینگ معمولی و هدایت هیدرولیکی,

Abstract :

In studies of irrigation and drainage projects for drainage, it is necessary to extend the data from the sampling point to the network. Therefore, based on available data from observational wells, estimating the state of hydraulic conductivity (K) in the surrounding area. The estimation process values for locations where there is no information for them based on viewing areas called wells spatial interpolation. In this study, based on data from 49 observational wells were constructed in the plains Shavoor in Khuzestan province, was generalized point data as well (Ernst), to the network. Then the accuracy of different interpolation methods were compared using scientific methods include a variety of kriging method, Thiessen and interpolation weight. Due to the geographical position coordinates observational wells, hydraulic conductivity was prepared digital map of the study area, using Civil 3D software. Spatial modeling software environment was then the Arc Gis and ArcMap. Statistical methods were used to compare with other software GS +. By drawing statistical methods and software GS + and ArcGIS ArcMAP, had the lowest error ordinary kriging process shift mode. Therefore, in this study, were used for zoning and expansion of hydraulic conductivity of ordinary Kriging interpolation method. Finally, in the research area of study in 11,500 hectares by Krynjyng conventional zoning were the three areas hydraulic conductivity with ranges 2,300 hectares less than 2 meters per day, 7900 between 2 and 3 meters per day and 1,300 hectares more 3 meters per day.According to the results, estimation of subsurface drainage Shdmhasbh are planted in three areas 50.70 and 80 m. As can be seen, if the estimate for hydraulic conductivity within the Project area, the method is invalid and an error, Perhaps increased costs due to estimation error in the drainage network designs are to be laid underground drains.

References:

حسنی پاک، ع. (1390). زمین آمار، انتشارات دانشگاه تهران، 314 ص.

عالمی، ک. و آذری، ک.(1390). کریجینگ و مدل سازی‌های تک متغیری یک داده مرتبط، تکنولوژی خاک، ص 6.

مدنی، ح. (1390). مبانی زمین آمار، انتشارات دانشگاه صنعتی امیرکبیر.548 ص.

Bhatti, A. U. A. Bakhsh, M and Gurmaniو, A. H. (2000). Spatial variability of Analysis. .pp: 30.

Delhomme, J. P . (2009). Kriging in the hydrosciences. Adv. Water Resources, 1.

Gallichand, J. and Marcotte, D. (2006). Mapping clay content for subsurface drainage in the nile delta.Geoderma. p: 165.

Hosseini M. (2010). Effect of Landuse Changes on Water Balance and Suspended Sediment Yield of Taleghan Catchment, Iran. PhD Thesis, University Putra Malaysia.

Robertson, M. P., Peter, C.I and Villet, M. H. (2004). Comparing Models for Predicting Species, Potential Distribution, A case Study Using Correlative and Mechanistic Predictive Modeling Techniques, Ecol.Model,164.