Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies
Twelve actual evaporation datasets are evaluated for their ability to improve the performance of the fully distributed mesoscale Hydrologic Model (mHM). The datasets consist of satellite-based diagnostic models (MOD16A2, SSEBop, ALEXI, CMRSET, SEBS), satellite-based prognostic models (GLEAM v3.2a, G...
| Autores principales: | , , , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2020
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/108934 |
| _version_ | 1855514377316204544 |
|---|---|
| author | Dembélé, M. Ceperley, N. Zwart, Sander J. Salvadore, E. Mariethoz, G. Schaefli, B. |
| author_browse | Ceperley, N. Dembélé, M. Mariethoz, G. Salvadore, E. Schaefli, B. Zwart, Sander J. |
| author_facet | Dembélé, M. Ceperley, N. Zwart, Sander J. Salvadore, E. Mariethoz, G. Schaefli, B. |
| author_sort | Dembélé, M. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Twelve actual evaporation datasets are evaluated for their ability to improve the performance of the fully distributed mesoscale Hydrologic Model (mHM). The datasets consist of satellite-based diagnostic models (MOD16A2, SSEBop, ALEXI, CMRSET, SEBS), satellite-based prognostic models (GLEAM v3.2a, GLEAM v3.3a, GLEAM v3.2b, GLEAM v3.3b), and reanalysis (ERA5, MERRA-2, JRA-55). Four distinct multivariate calibration strategies (basin-average, pixel-wise, spatial bias-accounting and spatial bias-insensitive) using actual evaporation and streamflow are implemented, resulting in 48 scenarios whose results are compared with a benchmark model calibrated solely with streamflow data. A process-diagnostic approach is adopted to evaluate the model responses with in-situ data of streamflow and independent remotely sensed data of soil moisture from ESA-CCI and terrestrial water storage from GRACE. The method is implemented in the Volta River basin, which is a data scarce region in West Africa, for the period from 2003 to 2012.
Results show that the evaporation datasets have a good potential for improving model calibration, but this is dependent on the calibration strategy. All the multivariate calibration strategies outperform the streamflow-only calibration. The highest improvement in the overall model performance is obtained with the spatial bias-accounting strategy (+29%), followed by the spatial bias-insensitive strategy (+26%) and the pixel-wise strategy (+24%), while the basin-average strategy (+20%) gives the lowest improvement. On average, using evaporation data in addition to streamflow for model calibration decreases the model performance for streamflow (-7%), which is counterbalance by the increase in the performance of the terrestrial water storage (+11%), temporal dynamics of soil moisture (+6%) and spatial patterns of soil moisture (+89%). In general, the top three best performing evaporation datasets are MERRA-2, GLEAM v3.3a and SSEBop, while the bottom three datasets are MOD16A2, SEBS and ERA5. However, performances of the evaporation products diverge according to model responses and across climatic zones. These findings open up avenues for improving process representation of hydrological models and advancing the spatiotemporal prediction of floods and droughts under climate and land use changes. |
| format | Journal Article |
| id | CGSpace108934 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace1089342024-06-26T10:18:04Z Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies Dembélé, M. Ceperley, N. Zwart, Sander J. Salvadore, E. Mariethoz, G. Schaefli, B. hydrology modelling calibration strategies satellites remote sensing evaporation river basins stream flow water storage soil water content climatic zones forecasting datasets performance evaluation spatial distribution Twelve actual evaporation datasets are evaluated for their ability to improve the performance of the fully distributed mesoscale Hydrologic Model (mHM). The datasets consist of satellite-based diagnostic models (MOD16A2, SSEBop, ALEXI, CMRSET, SEBS), satellite-based prognostic models (GLEAM v3.2a, GLEAM v3.3a, GLEAM v3.2b, GLEAM v3.3b), and reanalysis (ERA5, MERRA-2, JRA-55). Four distinct multivariate calibration strategies (basin-average, pixel-wise, spatial bias-accounting and spatial bias-insensitive) using actual evaporation and streamflow are implemented, resulting in 48 scenarios whose results are compared with a benchmark model calibrated solely with streamflow data. A process-diagnostic approach is adopted to evaluate the model responses with in-situ data of streamflow and independent remotely sensed data of soil moisture from ESA-CCI and terrestrial water storage from GRACE. The method is implemented in the Volta River basin, which is a data scarce region in West Africa, for the period from 2003 to 2012. Results show that the evaporation datasets have a good potential for improving model calibration, but this is dependent on the calibration strategy. All the multivariate calibration strategies outperform the streamflow-only calibration. The highest improvement in the overall model performance is obtained with the spatial bias-accounting strategy (+29%), followed by the spatial bias-insensitive strategy (+26%) and the pixel-wise strategy (+24%), while the basin-average strategy (+20%) gives the lowest improvement. On average, using evaporation data in addition to streamflow for model calibration decreases the model performance for streamflow (-7%), which is counterbalance by the increase in the performance of the terrestrial water storage (+11%), temporal dynamics of soil moisture (+6%) and spatial patterns of soil moisture (+89%). In general, the top three best performing evaporation datasets are MERRA-2, GLEAM v3.3a and SSEBop, while the bottom three datasets are MOD16A2, SEBS and ERA5. However, performances of the evaporation products diverge according to model responses and across climatic zones. These findings open up avenues for improving process representation of hydrological models and advancing the spatiotemporal prediction of floods and droughts under climate and land use changes. 2020-09 2020-08-04T05:53:28Z 2020-08-04T05:53:28Z Journal Article https://hdl.handle.net/10568/108934 en Open Access Elsevier Dembele, M.; Ceperley, N.; Zwart, Sander J.; Salvadore, E.; Mariethoz, G.; Schaefli, B. 2020. Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies. Advances in Water Resources, 143:103667. [doi: 10.1016/j.advwatres.2020.103667] |
| spellingShingle | hydrology modelling calibration strategies satellites remote sensing evaporation river basins stream flow water storage soil water content climatic zones forecasting datasets performance evaluation spatial distribution Dembélé, M. Ceperley, N. Zwart, Sander J. Salvadore, E. Mariethoz, G. Schaefli, B. Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies |
| title | Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies |
| title_full | Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies |
| title_fullStr | Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies |
| title_full_unstemmed | Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies |
| title_short | Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies |
| title_sort | potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies |
| topic | hydrology modelling calibration strategies satellites remote sensing evaporation river basins stream flow water storage soil water content climatic zones forecasting datasets performance evaluation spatial distribution |
| url | https://hdl.handle.net/10568/108934 |
| work_keys_str_mv | AT dembelem potentialofsatelliteandreanalysisevaporationdatasetsforhydrologicalmodellingundervariousmodelcalibrationstrategies AT ceperleyn potentialofsatelliteandreanalysisevaporationdatasetsforhydrologicalmodellingundervariousmodelcalibrationstrategies AT zwartsanderj potentialofsatelliteandreanalysisevaporationdatasetsforhydrologicalmodellingundervariousmodelcalibrationstrategies AT salvadoree potentialofsatelliteandreanalysisevaporationdatasetsforhydrologicalmodellingundervariousmodelcalibrationstrategies AT mariethozg potentialofsatelliteandreanalysisevaporationdatasetsforhydrologicalmodellingundervariousmodelcalibrationstrategies AT schaeflib potentialofsatelliteandreanalysisevaporationdatasetsforhydrologicalmodellingundervariousmodelcalibrationstrategies |