Spatial Interpolation on Rainfall Data over Peninsular Malaysia Using Ordinary Kriging

被引:0
|
作者
Jamaludin, Suhaila [1 ]
Suhaimi, Hanisah [1 ]
机构
[1] Univ Teknol Malaysia, Fac Sci, Dept Math, Johor Baharu 81310, Johor, Malaysia
来源
JURNAL TEKNOLOGI | 2013年 / 63卷 / 02期
关键词
Ordinary kriging; spatial interpolation; rainfall; semivariogram rainfall indices;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This study presents the spatial analysis of the rainfall data over Peninsular Malaysia. 70 rainfall stations were utilized in this study. Due to the limited number of rainfall stations, the Ordinary Kriging method which is one of the techniques in Spatial Interpolation was used to estimate the values of the rainfall data and to map their spatial distribution. This spatial analysis was analysed according to the two indices that describe the wet events and another two indices that characterize dry conditions. Large areas at the east experienced high rainfall intensity compared to the areas in the west, northwest and southwest. The small value that has been obtained in Aridity Intensity Index (AII) reflects that the high amount of rainfall in the eastern areas is not contributed by low-intensity events (less than 25th percentile). In terms of number of consecutive dry days, Northwestern areas in Peninsular Malaysia recorded the highest value. This finding explains the occurrence of a large number of floods and soil erosions in the eastern areas.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Genetic Programming-Based Ordinary Kriging for Spatial Interpolation of Rainfall
    Adhikary, Sajal Kumar
    Muttil, Nitin
    Yilmaz, Abdullah Gokhan
    JOURNAL OF HYDROLOGIC ENGINEERING, 2016, 21 (02)
  • [2] Evaluation of spatial interpolation methods and spatiotemporal modeling of rainfall distribution in Peninsular Malaysia
    Fung, Kit Fai
    Chew, Kim Soon
    Huang, Yuk Feng
    Ahmed, Ali Najah
    Teo, Fang Yenn
    Ng, Jing Lin
    Elshafie, Ahmed
    AIN SHAMS ENGINEERING JOURNAL, 2022, 13 (02)
  • [3] A Matlab based ordinary Kriging model developed for rainfall spatial interpolation over macro regions and a case application
    Hu, Q. (hqf_work@163.com), 1600, Editorial Board of Journal of Basic Science and (22):
  • [4] Spatial Interpolation of Bridge Scour Point Cloud Data Using Ordinary Kriging Method
    Shanmugam, Navanit Sri
    Chen, Shen-En
    Tang, Wenwu
    Chavan, Vidya Subhash
    Diemer, John
    Allan, Craig
    Shukla, Tarini
    Chen, Tianyang
    Slocum, Zachery
    Janardhanam, R.
    JOURNAL OF PERFORMANCE OF CONSTRUCTED FACILITIES, 2025, 39 (01)
  • [5] Texture interpolation using ordinary Kriging
    Chandra, S
    Petrou, M
    Piroddi, R
    PATTERN RECOGNITION AND IMAGE ANALYSIS, PT 2, PROCEEDINGS, 2005, 3523 : 183 - 190
  • [6] Analysis of rainfall events over Peninsular Malaysia
    Chin, Ren Jie
    Lai, Sai Hin
    Chang, Kian Boon
    Othman, Faridah
    Jaafar, Wan Zurina Wan
    WEATHER, 2016, 71 (05) : 118 - 123
  • [7] OPTIMAL INTERPOLATION OF RAINFALL DATA BY KRIGING.
    Shamsi, U.M.
    Yoganarasimhan, G.N.
    Journal of the Institution of Engineers (India): Civil Engineering Division, 1986, 67 : 134 - 138
  • [8] Spatial interpolation of water quality index based on Ordinary kriging and Universal kriging
    Khan, Mohsin
    Almazah, Mohammed M. A.
    EIlahi, Asad
    Niaz, Rizwan
    Al-Rezami, A. Y.
    Zaman, Baber
    GEOMATICS NATURAL HAZARDS & RISK, 2023, 14 (01)
  • [9] Optimizing Automated Kriging to Improve Spatial Interpolation of Monthly Rainfall over Complex Terrain
    Lucas, Matthew P.
    Longman, Ryan J.
    Giambelluca, Thomas W.
    Frazier, Abby G.
    McLean, Jared
    Cleveland, Sean B.
    Huang, Yu-Fen
    Lee, Jonghyun
    JOURNAL OF HYDROMETEOROLOGY, 2022, 23 (04) : 561 - 572
  • [10] Strain estimation using ordinary Kriging interpolation
    Ghiasi, Y.
    Nafisi, V.
    SURVEY REVIEW, 2016, 48 (350) : 361 - 366