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Information Journal Paper

Title

THE SPATIAL ANALYSIS AND OPTIMIZATION OF RAIN GAUGING STATION NETWORK IN KURDISTAN PROVINCE USING THE KRIGING ERROR VARIANCE

Pages

  17-18

Abstract

 Introduction: The prediction of the occurrence of floods and the reduction of damages caused by it is strongly influenced by the modeling of physical phenomena and the spatial-temporal distribution of precipitation. The purpose of the research was to optimize the rainfall gauging network in KURDISTAN PROVINCE using Kriging estimation variance and taking into account the topography of the area. In this study, to optimize the RAIN GAUGING NETWORK in KURDISTAN PROVINCE, rainfall data of the rain gauging, synoptic, and climatology stations were used. In order to reduce the costs, stations close to each other that are located in the same height range and also have the same ERROR VARIANCE, were removed from the existing network. In order to reduce the maintenance cost of the stations, after clustering of the area, 8 stations whose removal had little impact on the accuracy of the data, were identified in the province. Then. In order to strengthen the network, the OPTIMIZATION of new stations was put on the agenda and 28 points were set as the proposed stations....

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    APA: Copy

    ZAND KARIMI, ARASH, MOKHTARI, DAVOOD, & ZANDKARIMI, SHEIDA. (2018). THE SPATIAL ANALYSIS AND OPTIMIZATION OF RAIN GAUGING STATION NETWORK IN KURDISTAN PROVINCE USING THE KRIGING ERROR VARIANCE. GEOGRAPHICAL DATA, 27(105 ), 17-18. SID. https://sid.ir/paper/394455/en

    Vancouver: Copy

    ZAND KARIMI ARASH, MOKHTARI DAVOOD, ZANDKARIMI SHEIDA. THE SPATIAL ANALYSIS AND OPTIMIZATION OF RAIN GAUGING STATION NETWORK IN KURDISTAN PROVINCE USING THE KRIGING ERROR VARIANCE. GEOGRAPHICAL DATA[Internet]. 2018;27(105 ):17-18. Available from: https://sid.ir/paper/394455/en

    IEEE: Copy

    ARASH ZAND KARIMI, DAVOOD MOKHTARI, and SHEIDA ZANDKARIMI, “THE SPATIAL ANALYSIS AND OPTIMIZATION OF RAIN GAUGING STATION NETWORK IN KURDISTAN PROVINCE USING THE KRIGING ERROR VARIANCE,” GEOGRAPHICAL DATA, vol. 27, no. 105 , pp. 17–18, 2018, [Online]. Available: https://sid.ir/paper/394455/en

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