Evaluation of WRF model rainfall forecast using citizen science in a data-scarce urban catchment: Addis Ababa, Ethiopia
Study 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...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Journal of Hydrology: Regional Studies |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581822002865 |
| _version_ | 1797987159361191936 |
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| author | Hailay Zeray Tedla Estefanos Fikadu Taye David W. Walker Alemseged Tamiru Haile |
| author_facet | Hailay Zeray Tedla Estefanos Fikadu Taye David W. Walker Alemseged Tamiru Haile |
| author_sort | Hailay Zeray Tedla |
| collection | DOAJ |
| description | Study 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. |
| first_indexed | 2024-04-11T07:44:14Z |
| format | Article |
| id | doaj.art-b85e120ab21242c7b4230aa6b4f6f450 |
| institution | Directory Open Access Journal |
| issn | 2214-5818 |
| language | English |
| last_indexed | 2024-04-11T07:44:14Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology: Regional Studies |
| spelling | doaj.art-b85e120ab21242c7b4230aa6b4f6f4502022-12-22T04:36:23ZengElsevierJournal of Hydrology: Regional Studies2214-58182022-12-0144101273Evaluation of WRF model rainfall forecast using citizen science in a data-scarce urban catchment: Addis Ababa, EthiopiaHailay Zeray Tedla0Estefanos Fikadu Taye1David W. Walker2Alemseged Tamiru Haile3Africa Centre of Excellence for Water Management (ACEWM), Addis Ababa University, Addis Ababa, Ethiopia; Addis Ababa Science and Technology University (AASTU), Addis Ababa, Ethiopia; Corresponding author at: Africa Centre of Excellence for Water Management (ACEWM), Addis Ababa University, Addis Ababa, Ethiopia.Ethiopian Meteorology Institute (EMI), Addis Ababa, EthiopiaWater Resources Management Group, Wageningen University, the NetherlandsInternational Water Management Institute, P. O. Box 5689, Addis Ababa, EthiopiaStudy 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.http://www.sciencedirect.com/science/article/pii/S2214581822002865WRF rainfall forecastCitizen scienceRainfall dataAccuracy evaluationAddis ababaAkaki catchment, Ethiopia |
| spellingShingle | Hailay Zeray Tedla Estefanos Fikadu Taye David W. Walker Alemseged Tamiru Haile Evaluation of WRF model rainfall forecast using citizen science in a data-scarce urban catchment: Addis Ababa, Ethiopia Journal of Hydrology: Regional Studies WRF rainfall forecast Citizen science Rainfall data Accuracy evaluation Addis ababa Akaki catchment, Ethiopia |
| title | Evaluation of WRF model rainfall forecast using citizen science in a data-scarce urban catchment: Addis Ababa, Ethiopia |
| title_full | Evaluation of WRF model rainfall forecast using citizen science in a data-scarce urban catchment: Addis Ababa, Ethiopia |
| title_fullStr | Evaluation of WRF model rainfall forecast using citizen science in a data-scarce urban catchment: Addis Ababa, Ethiopia |
| title_full_unstemmed | Evaluation of WRF model rainfall forecast using citizen science in a data-scarce urban catchment: Addis Ababa, Ethiopia |
| title_short | Evaluation of WRF model rainfall forecast using citizen science in a data-scarce urban catchment: Addis Ababa, Ethiopia |
| title_sort | evaluation of wrf model rainfall forecast using citizen science in a data scarce urban catchment addis ababa ethiopia |
| topic | WRF rainfall forecast Citizen science Rainfall data Accuracy evaluation Addis ababa Akaki catchment, Ethiopia |
| url | http://www.sciencedirect.com/science/article/pii/S2214581822002865 |
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