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Monitoring Kikuletwa river levels in northern Tanzania: A data set unlocking insights for effective flood early warning systems

Floods are a recurring natural disaster that pose significant risks to communities and infrastructure. The lack of reliable and accurate data on river systems in developing countries has hindered the development of effective flood early warning systems. This paper presents a data set collected using...

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Autores principales: Mdegela, Lawrence, De Bock, Yorick, Luhanga, Edith, Leo, Judith, Mannens, Erik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10365974/
https://www.ncbi.nlm.nih.gov/pubmed/37496522
http://dx.doi.org/10.1016/j.dib.2023.109395
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author Mdegela, Lawrence
De Bock, Yorick
Luhanga, Edith
Leo, Judith
Mannens, Erik
author_facet Mdegela, Lawrence
De Bock, Yorick
Luhanga, Edith
Leo, Judith
Mannens, Erik
author_sort Mdegela, Lawrence
collection PubMed
description Floods are a recurring natural disaster that pose significant risks to communities and infrastructure. The lack of reliable and accurate data on river systems in developing countries has hindered the development of effective flood early warning systems. This paper presents a data set collected using ultrasonic distance sensors installed at two locations along the Kikuletwa River in the Pangani River Basin, Northern Tanzania. The dataset consists of hourly measurements of river water levels, providing a high-resolution time series that can be used to study trends in water level changes and to develop more accurate flood early warning systems. The Kikuletwa River dataset has significant potential applications for flood management, including the calibration and validation of hydrological models, the identification of critical thresholds for flood warning, and the evaluation of flood forecasting techniques. The dataset can also be used to study the hydrological processes in the basin, such as the relationship between rainfall and river discharge, and to develop more efficient and effective flood management strategies. The ultrasonic distance sensors were configured to record river level data at hourly intervals, providing a continuous time series of river levels. The data was subjected to quality control procedures to ensure accuracy and consistency, and missing or erroneous data was corrected or removed where necessary.
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spelling pubmed-103659742023-07-26 Monitoring Kikuletwa river levels in northern Tanzania: A data set unlocking insights for effective flood early warning systems Mdegela, Lawrence De Bock, Yorick Luhanga, Edith Leo, Judith Mannens, Erik Data Brief Data Article Floods are a recurring natural disaster that pose significant risks to communities and infrastructure. The lack of reliable and accurate data on river systems in developing countries has hindered the development of effective flood early warning systems. This paper presents a data set collected using ultrasonic distance sensors installed at two locations along the Kikuletwa River in the Pangani River Basin, Northern Tanzania. The dataset consists of hourly measurements of river water levels, providing a high-resolution time series that can be used to study trends in water level changes and to develop more accurate flood early warning systems. The Kikuletwa River dataset has significant potential applications for flood management, including the calibration and validation of hydrological models, the identification of critical thresholds for flood warning, and the evaluation of flood forecasting techniques. The dataset can also be used to study the hydrological processes in the basin, such as the relationship between rainfall and river discharge, and to develop more efficient and effective flood management strategies. The ultrasonic distance sensors were configured to record river level data at hourly intervals, providing a continuous time series of river levels. The data was subjected to quality control procedures to ensure accuracy and consistency, and missing or erroneous data was corrected or removed where necessary. Elsevier 2023-07-12 /pmc/articles/PMC10365974/ /pubmed/37496522 http://dx.doi.org/10.1016/j.dib.2023.109395 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Mdegela, Lawrence
De Bock, Yorick
Luhanga, Edith
Leo, Judith
Mannens, Erik
Monitoring Kikuletwa river levels in northern Tanzania: A data set unlocking insights for effective flood early warning systems
title Monitoring Kikuletwa river levels in northern Tanzania: A data set unlocking insights for effective flood early warning systems
title_full Monitoring Kikuletwa river levels in northern Tanzania: A data set unlocking insights for effective flood early warning systems
title_fullStr Monitoring Kikuletwa river levels in northern Tanzania: A data set unlocking insights for effective flood early warning systems
title_full_unstemmed Monitoring Kikuletwa river levels in northern Tanzania: A data set unlocking insights for effective flood early warning systems
title_short Monitoring Kikuletwa river levels in northern Tanzania: A data set unlocking insights for effective flood early warning systems
title_sort monitoring kikuletwa river levels in northern tanzania: a data set unlocking insights for effective flood early warning systems
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10365974/
https://www.ncbi.nlm.nih.gov/pubmed/37496522
http://dx.doi.org/10.1016/j.dib.2023.109395
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