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Development of Comprehensive Monitoring Method for Organic Matter and Nutrients in River Water based on UV-Vis Spectroscopy

Research Project

Project/Area Number 17K06571
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Hydraulic engineering
Research InstitutionTokyo Institute of Technology

Principal Investigator

Kinouchi Tsuyoshi  東京工業大学, 環境・社会理工学院, 教授 (00355835)

Project Period (FY) 2017-04-01 – 2023-03-31
Project Status Completed (Fiscal Year 2022)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2019: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2018: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2017: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Keywords紫外可視分光光度計 / 河川水質 / 栄養塩 / 有機物 / 吸光度スペクトル / 統計回帰モデル / ANNモデル / 浮遊物質 / モニタリング / 水工水理学 / 水資源
Outline of Final Research Achievements

In this study, we examined models to accurately estimate the concentrations of nitrate nitrogen (NO3-N), total nitrogen (TN), chemical oxygen demand (COD), total phosphorus (TP), and suspended solids (SS) using the absorbance spectra obtained from an indoor UV-Vis spectrometer on samples collected from actual rivers. Partial least squares regression (PLSR) using selected wavelengths and principal component regression (PCR) using all wavelengths were found to be suitable for estimating NO3-N and COD, respectively. An ANN model utilizing all wavelengths was suitable for predicting TN. For TP and SS, PLSR and PCR using all wavelengths were effective, respectively. Moreover, we demonstrated the application of these models to the spectra obtained from an in-situ UV-Vis spectrometer in actual rivers, showing that water quality could be reliably estimated with high confidence. The results suggest an efficient approach for water quality monitoring utilizing an in-situ UV-Vis spectrometer.

Academic Significance and Societal Importance of the Research Achievements

現場型の紫外可視吸光光度計は、環境中の水の吸光度スペクトルをリアルタイムで分析して複数の水質項目を監視できる大きな潜在能力を持っているが、流量や水質の変動の大きい河川を対象に吸光度スペクトルから複数水質項目を効率的かつ高い信頼性で推定する手法は確立されていない。本研究では室内の紫外可視吸光光度計で計測される河川水の吸光度スペクトルを用いて構築される最適な水質推定モデルが現場型の吸光光度計で計測される吸光度スペクトルにも適用できることを示しており、モデル構築時に現地でのスペクトル測定を行わずに複数水質の同時モニタリングを可能とするもので、今後の水質モニタリングに新たな道を開くものである。

Report

(7 results)
  • 2022 Annual Research Report   Final Research Report ( PDF )
  • 2021 Research-status Report
  • 2020 Research-status Report
  • 2019 Research-status Report
  • 2018 Research-status Report
  • 2017 Research-status Report
  • Research Products

    (4 results)

All 2019 2018

All Journal Article (1 results) (of which Peer Reviewed: 1 results,  Open Access: 1 results) Presentation (3 results) (of which Int'l Joint Research: 2 results)

  • [Journal Article] Estimation of river water quality using differential ultraviolet-visible spectra based on partial least squares regression2018

    • Author(s)
      Yanping Lyu and Tsuyoshi Kinouchi
    • Journal Title

      Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering)

      Volume: 74

    • NAID

      40021504287

    • Related Report
      2017 Research-status Report
    • Peer Reviewed / Open Access
  • [Presentation] Estimation of nitrogen, phosphorus, COD and suspended solids concentrations by in situ UV-Vis spectroscopy for rivers flowing into Lake Kasumigaura2019

    • Author(s)
      Lyu Yanping, Kinouchi Tsuyoshi, Nagano Tadahiro, Tanaka Shigeo
    • Organizer
      5th International Conference on Water Resource and Environment
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] Estimation of river water quality using in situ UV-Vis spectrometer based on partial least squares regression method2018

    • Author(s)
      Lyu Yanping and Kinouchi Tsuyoshi
    • Organizer
      4th International Conference on Water Resource and Environment
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research
  • [Presentation] Estimation of river water quality using differential ultraviolet-visible spectra based on partial least squares regression2018

    • Author(s)
      Yanping Lyu
    • Organizer
      土木学会水工学講演会
    • Related Report
      2017 Research-status Report

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Published: 2017-04-28   Modified: 2024-01-30  

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