THE ASSESSMENT OF KRIGING INTERPOLATION METHODS AND LINEAR REGRESSION BASED ON DIGITAL ELEVATIONAL MODEL (DEM) IN ORDER TO SPECIFY THE SPATIAL DISTRIBUTION OF ANNUAL PRECIPITATION (CASE STUDY: ESFAHAN PROVINCE)

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MEHRSHAHI D.; KHOSRAVI Y.

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Journal: Journal of Spatial Planning Year:2011 | Volume:14 | Issue:4 (68) Page(s): 233-249

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Title

THE ASSESSMENT OF KRIGING INTERPOLATION METHODS AND LINEAR REGRESSION BASED ON DIGITAL ELEVATIONAL MODEL (DEM) IN ORDER TO SPECIFY THE SPATIAL DISTRIBUTION OF ANNUAL PRECIPITATION (CASE STUDY: ESFAHAN PROVINCE)

Author(s)

MEHRSHAHI D. | KHOSRAVI Y. | Issue Writer Certificate

Keywords

KRIGINGQ2

LINEAR REGRESSIONQ2

DEM MODELQ2

GISQ2

ISFAHANQ2

Abstract

One of the most important parameters for computation of water balance and preparation of hydrologic models is to analyse the spatial distribution of precipitation. Therefore, any measurement miscalculation has a direct effect on water resource planning. Furthermore, due to the lack of overlap among the meteorological stations, recording of the precipitation, regional measurements or precipitation estimations within the areas among the stations are necessary. To achieve this, there are several methods including interpolation methods. In this study, KRIGING (simple and normal) as well as LINEAR REGRESSION methods based on digital elevation model were used to evaluate a 20- year annual precipitation data from 23 meteorological stations in ISFAHAN province. For this purpose, as the first step for each model within the KRIGING method, a semivariogram was computed, and by using cross-validation technique, the mapping errors were estimated. As a result, an optimal map was selected from 14basic maps. All steps were carried out using GIS software. At the second step, the precipitation data and the elevations of meteorological stations were recalled using LINEAR REGRESSION model through Curve Expert software. To distinguish an optimal model, the results were processed within 16 models. Eventually, the most significant models from the two methods were compared with each other to determine the precipitation spatial distributions for finalizing the interpolation task. The results indicated that Sinusoidal regression function was the most appropriate model for the interpolation of the ISFAHAN province's precipitation records.

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APA: Copy

MEHRSHAHI, D., & KHOSRAVI, Y.. (2011). THE ASSESSMENT OF KRIGING INTERPOLATION METHODS AND LINEAR REGRESSION BASED ON DIGITAL ELEVATIONAL MODEL (DEM) IN ORDER TO SPECIFY THE SPATIAL DISTRIBUTION OF ANNUAL PRECIPITATION (CASE STUDY: ESFAHAN PROVINCE). SPATIAL PLANNING (MODARES HUMAN SCIENCES), 14(4 (68)), 233-249. SID. https://sid.ir/paper/171902/en

Vancouver: Copy

MEHRSHAHI D., KHOSRAVI Y.. THE ASSESSMENT OF KRIGING INTERPOLATION METHODS AND LINEAR REGRESSION BASED ON DIGITAL ELEVATIONAL MODEL (DEM) IN ORDER TO SPECIFY THE SPATIAL DISTRIBUTION OF ANNUAL PRECIPITATION (CASE STUDY: ESFAHAN PROVINCE). SPATIAL PLANNING (MODARES HUMAN SCIENCES)[Internet]. 2011;14(4 (68)):233-249. Available from: https://sid.ir/paper/171902/en

IEEE: Copy

D. MEHRSHAHI, and Y. KHOSRAVI, “THE ASSESSMENT OF KRIGING INTERPOLATION METHODS AND LINEAR REGRESSION BASED ON DIGITAL ELEVATIONAL MODEL (DEM) IN ORDER TO SPECIFY THE SPATIAL DISTRIBUTION OF ANNUAL PRECIPITATION (CASE STUDY: ESFAHAN PROVINCE),” SPATIAL PLANNING (MODARES HUMAN SCIENCES), vol. 14, no. 4 (68), pp. 233–249, 2011, [Online]. Available: https://sid.ir/paper/171902/en

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