Abstract
Study region:
This research is carried out in the Kabompo Basin, a headwater catchment of the Zambezi Basin which has an area of 67,261 km2. Kabompo River originates in North-Western Province of Zambia between the Zambezi and Congo River Basins.
Study focus:
This study focuses on error propagation of the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center-MORPHing (CMORPH) rainfall product on simulated streamflow. Assessments are based on automated multi-objective calibration of the Representative Elementary Watershed (REW) model (2006–2012). Parameters of the model were optimized using the ɛ-NSGAII algorithm. Assessments on error propagation targeted streamflow modelling for hydrograph shape and volume, specific hydrograph characteristics, and water balance composition.
New hydrological insights for the region:
By use of multiple objective functions, this study shows that uncorrected CMORPH results in substantial augmentation of rainfall error to streamflow simulation mismatch whereas bias corrected estimates result in attenuation of error. Analysis for water balance composition has great potential to improve application of satellite precipitation products in water management and decision making in the Zambezi basin. This study advises optimization of model parameters for each respective rainfall input data source so to identify outcomes and effects of respective rainfall data sources on the simulated water balance composition and closure.
This research is carried out in the Kabompo Basin, a headwater catchment of the Zambezi Basin which has an area of 67,261 km2. Kabompo River originates in North-Western Province of Zambia between the Zambezi and Congo River Basins.
Study focus:
This study focuses on error propagation of the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center-MORPHing (CMORPH) rainfall product on simulated streamflow. Assessments are based on automated multi-objective calibration of the Representative Elementary Watershed (REW) model (2006–2012). Parameters of the model were optimized using the ɛ-NSGAII algorithm. Assessments on error propagation targeted streamflow modelling for hydrograph shape and volume, specific hydrograph characteristics, and water balance composition.
New hydrological insights for the region:
By use of multiple objective functions, this study shows that uncorrected CMORPH results in substantial augmentation of rainfall error to streamflow simulation mismatch whereas bias corrected estimates result in attenuation of error. Analysis for water balance composition has great potential to improve application of satellite precipitation products in water management and decision making in the Zambezi basin. This study advises optimization of model parameters for each respective rainfall input data source so to identify outcomes and effects of respective rainfall data sources on the simulated water balance composition and closure.
| Original language | English |
|---|---|
| Article number | 100966 |
| Pages (from-to) | 1-14 |
| Number of pages | 14 |
| Journal | Journal of Hydrology: Regional Studies |
| Volume | 38 |
| Early online date | 27 Nov 2021 |
| DOIs | |
| Publication status | Published - 1 Dec 2021 |
Keywords
- ITC-ISI-JOURNAL-ARTICLE
- ITC-GOLD
- UT-Gold-D
