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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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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. |
format | Online Article Text |
id | pubmed-10365974 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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