A database system for querying of river networks : facilitating monitoring and prediction applications
- Author
- Erik Bollen, Brianna Pagán, Bart Kuijpers, Stijn Van Hoey, Nele Desmet, Rik Hendrix, Jef Dams and Piet Seuntjens (UGent)
- Organization
- Abstract
- The increasing availability of real-time in situ measurements and remote sensing observations have the potential to contribute to the optimization of water resources management. Global challenges such as climate change, intensive agriculture and urbanization put a high pressure on our water resources. Due to recent innovations in measuring both water quantity and quality, river systems can now be monitored in real time at an unprecedented spatial and temporal scale. To interpret the sensor measurements and remote sensing observations additional data for example on: the location of the measurement, upstream and downstream catchment characteristics, horizontal ellipsis are required. In this paper, we present a data management system to support flow-path related functionality for decision making and prediction modelling. Adding meta data sets and facilitating (near) real-time processing of sensor data questions are key concepts for the systems. The potential of the database framework for hydrological applications is demonstrated using different applications for the river system of Flanders. In one, the database framework is used to simulate the daily discharge for each segment within a catchment using a simple data-driven approach. The presented system is useful for numerous applications including pollution tracking, alerting and inter-sensor validation in river systems, or related networks.
- Keywords
- data driven modelling, IoT, recursive querying, relational databases, river monitoring, water management, WATERSHED HYDROLOGIC FUNCTIONS, RELATIONAL DATABASE, MODEL, FUTURE
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01GSFWE76Y33R49N4VXKHCJ12N
- MLA
- Bollen, Erik, et al. “A Database System for Querying of River Networks : Facilitating Monitoring and Prediction Applications.” WATER SUPPLY, vol. 22, no. 3, 2022, pp. 2832–46, doi:10.2166/ws.2021.433.
- APA
- Bollen, E., Pagán, B., Kuijpers, B., Van Hoey, S., Desmet, N., Hendrix, R., … Seuntjens, P. (2022). A database system for querying of river networks : facilitating monitoring and prediction applications. WATER SUPPLY, 22(3), 2832–2846. https://doi.org/10.2166/ws.2021.433
- Chicago author-date
- Bollen, Erik, Brianna Pagán, Bart Kuijpers, Stijn Van Hoey, Nele Desmet, Rik Hendrix, Jef Dams, and Piet Seuntjens. 2022. “A Database System for Querying of River Networks : Facilitating Monitoring and Prediction Applications.” WATER SUPPLY 22 (3): 2832–46. https://doi.org/10.2166/ws.2021.433.
- Chicago author-date (all authors)
- Bollen, Erik, Brianna Pagán, Bart Kuijpers, Stijn Van Hoey, Nele Desmet, Rik Hendrix, Jef Dams, and Piet Seuntjens. 2022. “A Database System for Querying of River Networks : Facilitating Monitoring and Prediction Applications.” WATER SUPPLY 22 (3): 2832–2846. doi:10.2166/ws.2021.433.
- Vancouver
- 1.Bollen E, Pagán B, Kuijpers B, Van Hoey S, Desmet N, Hendrix R, et al. A database system for querying of river networks : facilitating monitoring and prediction applications. WATER SUPPLY. 2022;22(3):2832–46.
- IEEE
- [1]E. Bollen et al., “A database system for querying of river networks : facilitating monitoring and prediction applications,” WATER SUPPLY, vol. 22, no. 3, pp. 2832–2846, 2022.
@article{01GSFWE76Y33R49N4VXKHCJ12N,
abstract = {{The increasing availability of real-time in situ measurements and remote sensing observations have the potential to contribute to the optimization of water resources management. Global challenges such as climate change, intensive agriculture and urbanization put a high pressure on our water resources. Due to recent innovations in measuring both water quantity and quality, river systems can now be monitored in real time at an unprecedented spatial and temporal scale. To interpret the sensor measurements and remote sensing observations additional data for example on: the location of the measurement, upstream and downstream catchment characteristics, horizontal ellipsis are required. In this paper, we present a data management system to support flow-path related functionality for decision making and prediction modelling. Adding meta data sets and facilitating (near) real-time processing of sensor data questions are key concepts for the systems. The potential of the database framework for hydrological applications is demonstrated using different applications for the river system of Flanders. In one, the database framework is used to simulate the daily discharge for each segment within a catchment using a simple data-driven approach. The presented system is useful for numerous applications including pollution tracking, alerting and inter-sensor validation in river systems, or related networks.}},
author = {{Bollen, Erik and Pagán, Brianna and Kuijpers, Bart and Van Hoey, Stijn and Desmet, Nele and Hendrix, Rik and Dams, Jef and Seuntjens, Piet}},
issn = {{1606-9749}},
journal = {{WATER SUPPLY}},
keywords = {{data driven modelling,IoT,recursive querying,relational databases,river monitoring,water management,WATERSHED HYDROLOGIC FUNCTIONS,RELATIONAL DATABASE,MODEL,FUTURE}},
language = {{eng}},
number = {{3}},
pages = {{2832--2846}},
title = {{A database system for querying of river networks : facilitating monitoring and prediction applications}},
url = {{http://doi.org/10.2166/ws.2021.433}},
volume = {{22}},
year = {{2022}},
}
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