Altimetry-derived surface water data assimilation over the Nile Basin
Global hydrological models facilitate studying of water resources and their variations over time. The accuracies of these models are enhanced when combined with ever-increasing satellite remotely sensed data. Traditionally, these combinations are done via data assimilation approach, which permits th...
| Main Authors: | , |
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| Format: | Journal Article |
| Language: | English |
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ELSEVIER
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/86609 |
| _version_ | 1848764843737219072 |
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| author | Khaki, M. Awange, Joseph |
| author_facet | Khaki, M. Awange, Joseph |
| author_sort | Khaki, M. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Global hydrological models facilitate studying of water resources and their variations over time. The accuracies of these models are enhanced when combined with ever-increasing satellite remotely sensed data. Traditionally, these combinations are done via data assimilation approach, which permits the use of improved hydrological outputs to study regions with limited in-situ measurements such as the Nile Basin. This study aims at using the state-of-art satellite radar altimetry data to enhance a land-based hydrological model for studying water storage changes over the Nile Basin. Altimetry-derived surface water storage, for the first time, is assimilated into the model using the ensemble Kalman filter (EnKF) for the period of 2003 to 2016. Multiple datasets from ground measurements, as well as space observations, are used to evaluate the performance of the assimilated satellite altimetry data. Results indicate that the assimilation successfully improves model outputs, especially the surface water component. The process increases the correlation between surface water storage changes and water level variations from satellite radar altimetry by 0.44 and reduces the surface water discharge root-mean-square errors (RMSE) by approximately 33%. |
| first_indexed | 2025-11-14T11:25:48Z |
| format | Journal Article |
| id | curtin-20.500.11937-86609 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:25:48Z |
| publishDate | 2020 |
| publisher | ELSEVIER |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-866092021-12-06T03:13:53Z Altimetry-derived surface water data assimilation over the Nile Basin Khaki, M. Awange, Joseph Science & Technology Life Sciences & Biomedicine Environmental Sciences Environmental Sciences & Ecology SATELLITE RADAR ALTIMETRY SEQUENTIAL DATA ASSIMILATION WAVE-FORM RETRACKING STORAGE CHANGES MODEL GRACE EVAPOTRANSPIRATION PREDICTABILITY TEMPERATURE LIMITATIONS Global hydrological models facilitate studying of water resources and their variations over time. The accuracies of these models are enhanced when combined with ever-increasing satellite remotely sensed data. Traditionally, these combinations are done via data assimilation approach, which permits the use of improved hydrological outputs to study regions with limited in-situ measurements such as the Nile Basin. This study aims at using the state-of-art satellite radar altimetry data to enhance a land-based hydrological model for studying water storage changes over the Nile Basin. Altimetry-derived surface water storage, for the first time, is assimilated into the model using the ensemble Kalman filter (EnKF) for the period of 2003 to 2016. Multiple datasets from ground measurements, as well as space observations, are used to evaluate the performance of the assimilated satellite altimetry data. Results indicate that the assimilation successfully improves model outputs, especially the surface water component. The process increases the correlation between surface water storage changes and water level variations from satellite radar altimetry by 0.44 and reduces the surface water discharge root-mean-square errors (RMSE) by approximately 33%. 2020 Journal Article http://hdl.handle.net/20.500.11937/86609 10.1016/j.scitotenv.2020.139008 English ELSEVIER restricted |
| spellingShingle | Science & Technology Life Sciences & Biomedicine Environmental Sciences Environmental Sciences & Ecology SATELLITE RADAR ALTIMETRY SEQUENTIAL DATA ASSIMILATION WAVE-FORM RETRACKING STORAGE CHANGES MODEL GRACE EVAPOTRANSPIRATION PREDICTABILITY TEMPERATURE LIMITATIONS Khaki, M. Awange, Joseph Altimetry-derived surface water data assimilation over the Nile Basin |
| title | Altimetry-derived surface water data assimilation over the Nile Basin |
| title_full | Altimetry-derived surface water data assimilation over the Nile Basin |
| title_fullStr | Altimetry-derived surface water data assimilation over the Nile Basin |
| title_full_unstemmed | Altimetry-derived surface water data assimilation over the Nile Basin |
| title_short | Altimetry-derived surface water data assimilation over the Nile Basin |
| title_sort | altimetry-derived surface water data assimilation over the nile basin |
| topic | Science & Technology Life Sciences & Biomedicine Environmental Sciences Environmental Sciences & Ecology SATELLITE RADAR ALTIMETRY SEQUENTIAL DATA ASSIMILATION WAVE-FORM RETRACKING STORAGE CHANGES MODEL GRACE EVAPOTRANSPIRATION PREDICTABILITY TEMPERATURE LIMITATIONS |
| url | http://hdl.handle.net/20.500.11937/86609 |