Upper Blue Nile Basin Water Budget from a Multi-Model Perspective.

Area of Science:

• Hydrology
• Climate Science
• Environmental Modeling

Background:

• Understanding the Blue Nile's water balance is critical due to increasing hydroclimatic extremes.
• Land surface models (LSMs) and various datasets are used to estimate water budget variables.
• Intercomparison of LSMs with different forcings and precipitation data can refine hydrological estimates.

Purpose of the Study:

• To evaluate and compare two LSMs, Noah3.3 and CLSMF2.5, coupled with the HyMAP river routing scheme.
• To assess the impact of different meteorological forcing and precipitation datasets on hydrological estimates in the Blue Nile region.
• To identify the most suitable modeling approach for improving water balance representation.

Main Methods:

• Utilized Noah3.3 and CLSMF2.5 LSMs, coupled with the HyMAP river routing scheme.
• Forced models with combinations of MERRA-Land, MERRA-2 meteorological datasets, and CHIRPS, TRMM, MERRA precipitation datasets (16 experiments total).
• Evaluated modeled evapotranspiration (ET), streamflow, and terrestrial water storage against ALEXI, in-situ data, and GRACE products.

Main Results:

• CLSMF2.5 demonstrated superior performance over Noah3.3 in representing water budget variables, indicated by higher Nash-Sutcliffe coefficients.
• Model experiments using observation-based precipitation datasets (CHIRPS, TRMM) yielded better results than those using MERRA-Land and MERRA-2 precipitation.
• CLSMF2.5 coupled with HyMAP showed a better representation of Blue Nile water balance variables.

Conclusions:

• The Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) routing scheme is recommended for improved water balance modeling in the Blue Nile.
• Observation-based precipitation datasets (CHIRPS, TRMM) are more reliable for hydrological modeling in this region than reanalysis precipitation.
• Findings suggest incorporating CLSMF2.5 and HyMAP into systems like the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System for enhanced regional water management.