Applications of satellite-based rainfall estimates in flood inundation modeling: a case study in Mundeni Aru River Basin, Sri Lanka
The performance of Satellite Rainfall Estimate (SRE) products applied to flood inundation modelling was tested for the Mundeni Aru River Basin in eastern Sri Lanka. Three SREs (PERSIANN, TRMM, and GSMaP) were tested, with the Rainfall-Runoff-Inundation (RRI) model used as the flood inundation model....
| Main Authors: | , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
MDPI
2017
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/89283 |
| _version_ | 1855527897704431616 |
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| author | Yoshimoto, Shuhei Amarnath, Giriraj |
| author_browse | Amarnath, Giriraj Yoshimoto, Shuhei |
| author_facet | Yoshimoto, Shuhei Amarnath, Giriraj |
| author_sort | Yoshimoto, Shuhei |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The performance of Satellite Rainfall Estimate (SRE) products applied to flood inundation modelling was tested for the Mundeni Aru River Basin in eastern Sri Lanka. Three SREs (PERSIANN, TRMM, and GSMaP) were tested, with the Rainfall-Runoff-Inundation (RRI) model used as the flood inundation model. All the SREs were found to be suitable for applying to the RRI model. The simulations created by applying the SREs were generally accurate, although there were some discrepancies in discharge due to differing precipitation volumes. The volumes of precipitation of the SREs tended to be smaller than those of the gauged data, but using a scale factor to correct this improved the simulations. In particular, the SRE, i.e., the GSMaP yielding the best simulation that correlated most closely with the flood inundation extent from the satellite data, was considered the most appropriate to apply to the model calculation. The application procedures and suggestions shown in this study could help authorities to make better-informed decisions when giving early flood warnings and making rapid flood forecasts, especially in areas where in-situ observations are limited. |
| format | Journal Article |
| id | CGSpace89283 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | CGSpace892832025-03-11T09:50:20Z Applications of satellite-based rainfall estimates in flood inundation modeling: a case study in Mundeni Aru River Basin, Sri Lanka Yoshimoto, Shuhei Amarnath, Giriraj satellite observation rainfall patterns flooding monitoring rainfall-runoff relationships models river basins precipitation forecasting case studies The performance of Satellite Rainfall Estimate (SRE) products applied to flood inundation modelling was tested for the Mundeni Aru River Basin in eastern Sri Lanka. Three SREs (PERSIANN, TRMM, and GSMaP) were tested, with the Rainfall-Runoff-Inundation (RRI) model used as the flood inundation model. All the SREs were found to be suitable for applying to the RRI model. The simulations created by applying the SREs were generally accurate, although there were some discrepancies in discharge due to differing precipitation volumes. The volumes of precipitation of the SREs tended to be smaller than those of the gauged data, but using a scale factor to correct this improved the simulations. In particular, the SRE, i.e., the GSMaP yielding the best simulation that correlated most closely with the flood inundation extent from the satellite data, was considered the most appropriate to apply to the model calculation. The application procedures and suggestions shown in this study could help authorities to make better-informed decisions when giving early flood warnings and making rapid flood forecasts, especially in areas where in-situ observations are limited. 2017-09-27 2017-11-09T08:09:37Z 2017-11-09T08:09:37Z Journal Article https://hdl.handle.net/10568/89283 en Open Access MDPI Yoshimoto, Shuhei; Amarnath, Giriraj. 2017. Applications of satellite-based rainfall estimates in flood inundation modeling: a case study in Mundeni Aru River Basin, Sri Lanka. Remote Sensing, 9(10):1-16. doi: 10.3390/rs9100998 |
| spellingShingle | satellite observation rainfall patterns flooding monitoring rainfall-runoff relationships models river basins precipitation forecasting case studies Yoshimoto, Shuhei Amarnath, Giriraj Applications of satellite-based rainfall estimates in flood inundation modeling: a case study in Mundeni Aru River Basin, Sri Lanka |
| title | Applications of satellite-based rainfall estimates in flood inundation modeling: a case study in Mundeni Aru River Basin, Sri Lanka |
| title_full | Applications of satellite-based rainfall estimates in flood inundation modeling: a case study in Mundeni Aru River Basin, Sri Lanka |
| title_fullStr | Applications of satellite-based rainfall estimates in flood inundation modeling: a case study in Mundeni Aru River Basin, Sri Lanka |
| title_full_unstemmed | Applications of satellite-based rainfall estimates in flood inundation modeling: a case study in Mundeni Aru River Basin, Sri Lanka |
| title_short | Applications of satellite-based rainfall estimates in flood inundation modeling: a case study in Mundeni Aru River Basin, Sri Lanka |
| title_sort | applications of satellite based rainfall estimates in flood inundation modeling a case study in mundeni aru river basin sri lanka |
| topic | satellite observation rainfall patterns flooding monitoring rainfall-runoff relationships models river basins precipitation forecasting case studies |
| url | https://hdl.handle.net/10568/89283 |
| work_keys_str_mv | AT yoshimotoshuhei applicationsofsatellitebasedrainfallestimatesinfloodinundationmodelingacasestudyinmundeniaruriverbasinsrilanka AT amarnathgiriraj applicationsofsatellitebasedrainfallestimatesinfloodinundationmodelingacasestudyinmundeniaruriverbasinsrilanka |