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Study on Real-Time Forecasting of Hydrological Variables Using Technique of Non-Linear Time Series Analysis

Research Project

Project/Area Number 14560199
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Irrigation, drainage and rural engineering/Rural planning
Research InstitutionOkayama University

Principal Investigator

CHIKAMORI Hidetaka  Okayama University, Faculty of Environmental Science and Technology, Associate Professor, 環境理工学部, 助教授 (40217229)

Co-Investigator(Kenkyū-buntansha) NAGAI Akihiro  Okayama University, Faculty of Environmental Science and Technology, Professor, 環境理工学部, 教授 (80093285)
Project Period (FY) 2002 – 2003
Project Status Completed (Fiscal Year 2003)
Budget Amount *help
¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2003: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2002: ¥500,000 (Direct Cost: ¥500,000)
Keywordsflood forecasting / rainfall forecasting / non-linear time series analysis / chaos / 降雨予測 / 非線形時系列
Research Abstract

For effective flood control, accurate real-time forecasting of flood discharge is very important. For supporting the flood forecasting, accurate real-time forecasting of rainfall is important as well. In this study, we developed new flood and heavy rainfall forecasting system using technique of non-linear time-series analysis, that is, local linear approximation (LL) method, Nearest Neighbor (NN) method and Self-Organizing feature map with Linear Output mapping (SOLO) algorithm, and examined forecasting accuracy of the developed system. First, we applied LL method to real-time flood forecasting for 39 storms records observed at Kuroki Dam Basin located in the northern part of Okayama Prefecture, Japan, during 1979 -2002. It is, as a result, found that forecasting accuracy of flood discharge by the LL method is so high that it is comparative to that by the conventional real-time forecasting system using the Tank Model with Kalman filtering technique. Second, we also applied the SOLO algorithm to real-time flood forecasting at Kuroki Dam Basing and found that the flood forecasting system by the SOLO algorithm achieved a high degree of accuracy in the case of using feature vectors composed of scores of all principal components of past discharge and rainfall data. The accuracy is almost equivalent to that by the LL method. However, when feature vectors are directly composed of discharge and rainfall data, forecasting accuracy became worse particularly during verification duration. Finally we applied the NN method to real-time rainfall forecasting at Okayama using the rainfall data observed at ground rain gauges around Okayama of Automated Meteorological Data Acquisition System (AMeDAS) of Japan. Although forecasting accuracy of rainfall occurrence was so high as over 80%, accuracy of forecasted rainfall depth was insufficient for practical use because it tends to be underestimated.

Report

(3 results)
  • 2003 Annual Research Report   Final Research Report Summary
  • 2002 Annual Research Report
  • Research Products

    (4 results)

All Other

All Publications (4 results)

  • [Publications] 近森秀高, 永井明博: "局所線形近似法を用いた実時間洪水流出予測"水文・水資源学会誌. 15-2. 164-175 (2002)

    • Description
      「研究成果報告書概要(和文)」より
    • Related Report
      2003 Final Research Report Summary
  • [Publications] Chikamori, H., A.Nagai: "Real-Time Flood Forecasting Using Local Linear Approximation Method"Journal of Japan Society of Hydrology and Water Resources. Vol.15,No.2. 164-175 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
    • Related Report
      2003 Final Research Report Summary
  • [Publications] 近森秀高, 永井明博: "局所線形近似法を用いた洪水実時間予測"水文・水資源学会誌. 15・3. 164-175 (2002)

    • Related Report
      2003 Annual Research Report
  • [Publications] 近森秀高, 永井明博: "局所線形近似法を用いた洪水実時間予測"水文・水資源学会誌. 15・3. 164-175 (2002)

    • Related Report
      2002 Annual Research Report

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Published: 2002-04-01   Modified: 2016-04-21  

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