Embedded Files
Precipitation and river discharge are key hydrological variables for drought monitoring, water resources management, flood forecasting, and water budget closure. This work evaluates how NGGM and MAGIC missions can improve estimates of these variables compared to GRACE-C, using Equivalent Water Height (EWH) data. Two tasks are addressed: (1) precipitation estimation using SM2RAIN, and (2) runoff and river discharge estimation using STREAM.
Performance is assessed by comparing simulated values from different EWH configurations with “true” values and with in situ discharge. Metrics include bias, correlation (R), RMSE, Kling–Gupta Efficiency (KGE).
Figure: Impact for precipitation - In the cyan and blue areas, we expect an improvement in terms of precipitation estimation by using 5-day NGGM (MAGIC) Equivalent Water Height (EWH) observations with respect to soil moisture (SM) observations from ASCAT
Precipitation: SM2RAIN with ESM-based EWH shows good global performance (median R = 0.78), especially in temperate regions. NGGM and MAGIC outperform GRACE-C, which improves performance in humid tropics like the Amazon and Congo basins. Arid regions remain challenging.
River discharge: STREAM with reference EWH achieves mean KGE = 0.71. Filtered data clearly outperform unfiltered (mean KGE = 0.77 vs. 0.32). NGGM filtered data perform best (KGE = 0.81).
Runoff: Filtered data reduce mean RRMSE to 85% vs. 101% for unfiltered, with the largest improvement for GRACE-C-like data (–53%).
Overall, the 5-day resolution of NGGM and MAGIC enables the first reliable precipitation estimates from gravimetry and significantly improves river discharge estimates at basin scale compared to GRACE-C, especially when combined with post-processing filters.
Report abuse