Applying ANN and GIS for estimation of effective parameters in determination of plant pattern (Case Study: Nahavand City)

Subject Areas : environmental management

Hossein Banejad ¹ ( Water Department, Agriculture Faculty, Bu-Ali Sina University. )
Hamid Mohebzadeh ² ( M. Sc. Student Water Department, Agriculture Faculty, Bu-Ali Sina University )
Ehsan Olyaie ³ ( M. Sc. Student Water Department, Agriculture Faculty, Bu-Ali Sina University )

Received: 2009-12-22 Accepted : 2010-07-15 Published : 2013-03-21

Keywords: Artificial Neural Networks, GIS, Planting Pattern, Nahavand,

Abstract :

AbstractOne of the most important issues in irrigated agriculture is determination of optimum plant pattern.Therefore, estimation of effective parameters in quality and quantity of available water is significantand is one of the most important components in adoption of management decisions in development ofsustainable agriculture. In this study, Artificial Neural Networks technique has been used forestimation of piezometer wells water level and also effective factors for water quality used inagriculture (EC, SAR). For this purpose, monthly recorded data for piezometer wells water levelduring a seven year and data related with water quality during a four years period in Nahavand plainwere used. Also, a groundwater level in Nahavand in year of 1385-86 was drawn. Efficiency of modelwas evaluated by statistical criteria including coefficient of determination (R2), root mean square error(RMSE) and mean absolute error (MAE). The derived results showed that R2 value for estimation ofpiezometer wells water level is 0.98 and for SAR and EC is 0.991 and 0.990 respectively. The aboveresults indicated the appropriate ability of Artificial Neural Networks as superior technique forsimulation of effective quality and quantity parameters in determination of plant pattern. Also theresults from spatial drowning of groundwater level by Geographic Information System indicated theshortage of water resource in this region

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