Innovative Sensor Networks in Ghana

Innovative Sensor Networks in Ghana: Operating and validating sensor networks for river discharge in Ghana during the wet season

Hiemstra, Jolijn (TU Delft Civil Engineering & Geosciences)
Streefkerk, Luuk (TU Delft Civil Engineering & Geosciences)
Okkerman, Jorrit (TU Delft Civil Engineering & Geosciences)
Rijsenbrij, Annabel (TU Delft Civil Engineering & Geosciences)
van Leeuwen, Jesse (TU Delft Civil Engineering & Geosciences)
Linnebach, Jonathan (TU Delft Civil Engineering & Geosciences)

van de Giesen, N.C. (mentor)

Delft University of Technology

Civil Engineering

2023-11-28

In a Ghana project, field measurements at the Black Volta aimed to enhance hydrological predictions for the Bui power dam. Validating devices and exploring floodplain contributions, such as with GNSS reflectometry and cameras, provides crucial insights for dam management and model improvement.

In this multidisciplinary project, conducted at the Black Volta in western Ghana, the focus is on addressing challenges related to data scarcity in hydrological predictions, particularly for the Bui power dam. The dam has faced issues during flood events, leading to spillages and subsequent damages. To enhance predictions, field measurements were carried out, employing innovative methods for remote areas within the TEMBO Africa project. The project aimed to validate devices measuring river parameters and improve the understanding of floodplain contributions to river discharge. Key methods included GNSS reflectometry for water level measurement and a camera-based approach for discharge determination. The GNSS-reflectometry device was successfully tested, validated, and installed at the Black Volta, automating water level measurements. The camera-based method demonstrated success on smaller streams but faced challenges on wider rivers. Despite this, it was installed at the Black Volta for daily discharge measurements, promising a reduction in rating curve uncertainty when combined with water level measurements. Field observations were utilized to enhance an existing hydraulic model, refining the floodplain's representation. The study also delved into determining the floodplain's roughness coefficient, involving manual measurements and attempts at automation using remote sensing techniques. The roughness coefficients were implemented into the Delft3D model, showing contributions of floodplains to river discharge. Despite challenges, including equipment installation timing and location disruptions due to bridge construction, the project provides valuable insights for improving hydrological models and preventing dam spillages in the future.

River
Discharge
DELFT3D
sensor network
floodplain
Roughness coefficient
GNSS-reflectometry
openrivercam
rating curve

http://resolver.tudelft.nl/uuid:a1f9159d-a11d-439e-8ee0-fdeff7136e05

Student theses

student report

© 2023 Jolijn Hiemstra, Luuk Streefkerk, Jorrit Okkerman, Annabel Rijsenbrij, Jesse van Leeuwen, Jonathan Linnebach