IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v35y2021i11d10.1007_s11269-021-02908-1.html
   My bibliography  Save this article

Deterministic and Stochastic Principles to Convert Discrete Water Quality Data into Continuous Time Series

Author

Listed:
  • Danieli Mara Ferreira

    (Federal University of Parana)

  • Marcelo Coelho

    (Federal University of Parana)

  • Cristovao Vicente Scapulatempo Fernandes

    (Federal University of Parana)

  • Eloy Kaviski

    (Federal University of Parana)

  • Daniel Henrique Marco Detzel

    (Federal University of Parana)

Abstract

Limited water quality data is often responsible for incorrect model descriptions and misleading interpretations in terms of water resources planning and management scenarios. This study compares two hybrid strategies to convert discrete concentration data into continuous daily values for one year in distinct river sections. Model A is based on an autoregressive process, accounting for serial correlation, water quality historical characteristics (mean and standard deviation), and random variability. The second approach (model B) is a regression model based on the relationship between flow and concentrations, and an error term. The generated time series, here referred to as synthetic series, are propagated in time and space by a deterministic model (SihQual) that solves the Saint-Venant and advection-dispersion-reaction equations. The results reveal that both approaches are appropriate to reproduce the variability of biochemical oxygen demand and organic nitrogen concentrations, leading to the conclusion that the combination of deterministic/empirical and stochastic components are compatible. A second outcome arises from comparing the results for distinct time scales, supporting the need for further assessment of statistical characteristics of water quality data - which relies on monitoring strategies development. Nonetheless, the proposed methods are suitable to estimate multiple scenarios of interest for water resources planning and management. Graphical Abstract

Suggested Citation

  • Danieli Mara Ferreira & Marcelo Coelho & Cristovao Vicente Scapulatempo Fernandes & Eloy Kaviski & Daniel Henrique Marco Detzel, 2021. "Deterministic and Stochastic Principles to Convert Discrete Water Quality Data into Continuous Time Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3633-3647, September.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:11:d:10.1007_s11269-021-02908-1
    DOI: 10.1007/s11269-021-02908-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-021-02908-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-021-02908-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ankita P. Dadhich & Rohit Goyal & Pran N. Dadhich, 2021. "Assessment and Prediction of Groundwater using Geospatial and ANN Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(9), pages 2879-2893, July.
    2. Jiping Yao & Guoqiang Wang & Weina Xue & Zhipeng Yao & Baolin Xue, 2019. "Assessing the Adaptability of Water Resources System in Shandong Province, China, Using a Novel Comprehensive Co-evolution Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(2), pages 657-675, January.
    3. Hamed Taherdoost, 2018. "A review of technology acceptance and adoption models and theories," Post-Print hal-03741843, HAL.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bonaiuto, M. & Mosca, O. & Milani, A. & Ariccio, S. & Dessi, F. & Fornara, F., 2024. "Beliefs about technological and contextual features drive biofuels’ social acceptance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    2. O. Oyediran & A. Omoshule & Sanjay Misra & Rytis Maskeliūnas & Robertas Damaševičius, 2019. "Attitude of mobile telecommunication subscribers towards sim card registration in Lagos State, Southwestern Nigeria," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(4), pages 783-791, August.
    3. Mohammadbashir Sedighi & Hamideh Parsaeiyan & Yashar Araghi, 2021. "An Empirical Study of Intention to Continue Using of Digital Ride-hailing Platforms," The Review of Socionetwork Strategies, Springer, vol. 15(2), pages 489-515, November.
    4. Prithvi Roy & Badrinarayan Srirangam Ramaprasad & Manan Chakraborty & Nandan Prabhu & Shreelatha Rao, 2024. "Customer Acceptance of Use of Artificial Intelligence in Hospitality Services: An Indian Hospitality Sector Perspective," Global Business Review, International Management Institute, vol. 25(3), pages 832-851, June.
    5. Maksym Gaiduk & Ralf Seepold & Natividad Martínez Madrid & Juan Antonio Ortega, 2021. "Digital Health and Care Study on Elderly Monitoring," Sustainability, MDPI, vol. 13(23), pages 1-18, December.
    6. Pal, Debajyoti & Zhang, Xiangmin & Siyal, Saeed, 2021. "Prohibitive factors to the acceptance of Internet of Things (IoT) technology in society: A smart-home context using a resistive modelling approach," Technology in Society, Elsevier, vol. 66(C).
    7. Chen, Long & Huang, Jiahui & Jing, Peng & Wang, Bichen & Yu, Xiaozhou & Zha, Ye & Jiang, Chengxi, 2023. "Changing or unchanging Chinese attitudes toward ride-hailing? A social media analytics perspective from 2018 to 2021," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    8. Amiruddin Saleh & Johan David Wetik & Sik Sumaedi, 2023. "Smartphone Apps-Based Health Communication Media Usage among Older Individuals During the COVID-19 Pandemic: The Role of System Quality Factors," SAGE Open, , vol. 13(4), pages 21582440231, November.
    9. Simone Wurster & Rita Schulze, 2020. "Consumers’ Acceptance of a Bio-circular Automotive Economy: Explanatory Model and Influence Factors," Sustainability, MDPI, vol. 12(6), pages 1-22, March.
    10. Grangeia, Carolina & Santos, Luan & Ferreira, Daniel Viana & Guimarães, Raphael & de Magalhães Ozorio, Luiz & Tavares, Arthur, 2023. "Energy transition scenarios in the transportation sector in Brazil: Contributions from the electrical mobility," Energy Policy, Elsevier, vol. 174(C).
    11. Almourad, Mohamed Basel & Alrobai, Amen & Skinner, Tiffany & Hussain, Mohammed & Ali, Raian, 2021. "Digital wellbeing tools through users lens," Technology in Society, Elsevier, vol. 67(C).
    12. Shima Kamali & Keyvan Asghari, 2023. "The Effect of Meteorological and Hydrological Drought on Groundwater Storage Under Climate Change Scenarios," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(8), pages 2925-2943, June.
    13. Rana Saeed Al-Maroof & Khadija Alhumaid & Ahmad Qasim Alhamad & Ahmad Aburayya & Said Salloum, 2021. "User Acceptance of Smart Watch for Medical Purposes: An Empirical Study," Future Internet, MDPI, vol. 13(5), pages 1-19, May.
    14. Muhammad Riaz & Sherani, 2021. "Investigation of information sharing via multiple social media platforms: a comparison of Facebook and WeChat adoption," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(5), pages 1751-1773, October.
    15. Junfang Liu & Baolin Xue & Yuhui Yan, 2020. "The Assessment of Climate Change and Land-Use Influences on the Runoff of a Typical Coastal Basin in Northern China," Sustainability, MDPI, vol. 12(23), pages 1-13, December.
    16. Ho, Manh-Tung & Mantello, Peter & Ghotbi, Nader & Nguyen, Minh-Hoang & Nguyen, Hong-Kong T. & Vuong, Quan-Hoang, 2022. "Rethinking technological acceptance in the age of emotional AI: Surveying Gen Z (Zoomer) attitudes toward non-conscious data collection," Technology in Society, Elsevier, vol. 70(C).
    17. Hamed Taherdoost, 2019. "Importance of Technology Acceptance Assessment for Successful Implementation and Development of New Technologies," Post-Print hal-02557395, HAL.
    18. Hamed Taherdoost, 2021. "Importance of Technology Acceptance Assessment for Successful Implementation and Development of New Technologies," Post-Print hal-03741844, HAL.
    19. Lidia Yadira Perez-Aguilar & Wenseslao Plata-Rocha & Sergio Alberto Monjardin-Armenta & Cuauhtémoc Franco-Ochoa, 2022. "Aridity Analysis Using a Prospective Geospatial Simulation Model in This Mid-Century for the Northwest Region of Mexico," Sustainability, MDPI, vol. 14(22), pages 1-22, November.
    20. Moon, Sungho & Kim, Kyungah & Seung, Hyunchan & Kim, Junghun, 2022. "Strategic analysis on effects of technologies, government policies, and consumer perceptions on diffusion of hydrogen fuel cell vehicles," Energy Economics, Elsevier, vol. 115(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:35:y:2021:i:11:d:10.1007_s11269-021-02908-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.