Evaluation of WRF model rainfall forecast using citizen science in a data-scarce urban catchment: Addis Ababa, Ethiopia

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dc.creatorTedla, H. Z.
dc.creatorTaye, E. F.
dc.creatorWalker, D. W.
dc.creatorHaile, Alemseged Tamiru
dc.date2022-12
dc.date2022-12-31T23:48:54Z
dc.date2022-12-31T23:48:54Z
dc.date.accessioned2026-06-27T18:24:39Z
dc.descriptionStudy region: The Akaki catchment is found in the Upper Awash River Basin in Ethiopia. Study focus: Understanding the accuracy of rainfall forecasts in the data-scarce urban catchment has a multitude of benefits given the increased urban flood risk caused by climate change and urbanization. In this study, accuracy of the weather research and forecasting (WRF) model rainfall forecast was evaluated using citizen science data. Categorical and continuous accuracy evaluation metrics were used beside gauge representativeness effect. New hydrological insights for the region: The rainfall forecasts performance accuracy is high for 1–3- days lead-time but deteriorates for 4–5-days lead-time. The WRF model captured the temporal dynamics and the rainfall amount according to the estimated KGE values. The model has relatively higher detection performance for no rain and light rain events (< 6 mm/day), but it has lower performance for moderate and heavy rain events (> 6 mm/day). Use of data from a single rain gauge misrepresents the accuracy level of the rainfall forecast in the study area. The gauge representativeness error contributed a variance of 28.08–83.33 % to the variance of WRF-gauge rainfall difference. Thus, the use of citizen science rainfall monitoring program is an essential alternative source of information where in-situ rainfall monitoring is limited that can be used to understand the “true” accuracy of WRF rainfall forecasts.
dc.identifierhttps://hdl.handle.net/10568/126410
dc.identifier.urihttp://hdl.handle.net/123456789/154963
dc.languageen
dc.publisherElsevier
dc.rightsOpen Access
dc.sourceTedla, H. Z.; Taye, E. F.; Walker, D. W.; Haile, Alemseged Tamiru. 2022. Evaluation of WRF model rainfall forecast using citizen science in a data-scarce urban catchment: Addis Ababa, Ethiopia. Journal of Hydrology: Regional Studies, 44:101273. [doi: https://doi.org/10.1016/j.ejrh.2022.101273]
dc.subjectrain
dc.subjectweather forecasting
dc.subjectmodels
dc.subjectcitizen science
dc.subjecturban areas
dc.subjectcatchment areas
dc.subjectweather data
dc.subjectmonitoring
dc.titleEvaluation of WRF model rainfall forecast using citizen science in a data-scarce urban catchment: Addis Ababa, Ethiopia
dc.typeJournal Article

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