Qquenta, J.; Rau, P.; Bourrel, L.; Frappart, F.; Lavado-Casimiro, W. Assessment of Bottom-Up Satellite Precipitation Products on River Streamflow Estimations in the Peruvian Pacific Drainage. Remote Sens.2024, 16, 11.
Qquenta, J.; Rau, P.; Bourrel, L.; Frappart, F.; Lavado-Casimiro, W. Assessment of Bottom-Up Satellite Precipitation Products on River Streamflow Estimations in the Peruvian Pacific Drainage. Remote Sens. 2024, 16, 11.
Qquenta, J.; Rau, P.; Bourrel, L.; Frappart, F.; Lavado-Casimiro, W. Assessment of Bottom-Up Satellite Precipitation Products on River Streamflow Estimations in the Peruvian Pacific Drainage. Remote Sens.2024, 16, 11.
Qquenta, J.; Rau, P.; Bourrel, L.; Frappart, F.; Lavado-Casimiro, W. Assessment of Bottom-Up Satellite Precipitation Products on River Streamflow Estimations in the Peruvian Pacific Drainage. Remote Sens. 2024, 16, 11.
Abstract
In regions with limited precipitation information like Peru, many studies rely on precipitation data derived from satellite products (SPPs) and reanalysis products. These products provide near-real-time information and offer global spatial coverage, making them attractive for various applications. However, it is essential to consider their uncertainties when conducting hydrological simulations, especially in a key region like the Pacific drainage (Pd), where 56% of Peruvian population resides (including the capital Lima).
This study evaluates the performance of three precipitation products: Reanalysis, ERA5-Land (top down approach), and two SPPs: GPM+SM2RAIN and SM2RAIN-ASCAT (bottom-up approaches). Hydrological modeling was conducted on 30 basins distributed across the Pd, which were grouped into five regions (I-V, ordered from south to north). The results showed that SM2RAIN-ASCAT performed well in regions I-III-IV, ERA5-Land in region II, and GPM+SM2RAIN in region V. The hydrological model GR4J was tested, and better efficiency criteria were obtained with SM2RAIN-ASCAT and GPM+SM2RAIN when comparing simulated versus observed streamflows. The hydrological modeling with SM2RAIN-ASCAT and GPM+SM2RAIN demonstrated satisfactory efficiency metrics (KGE > 0.75; NSE > 0.65). Additionally, ten hydrological signatures were quantified to assess the variability of simulated streamflows in each basin, with metrics such as Mean Flow (Q mean), 5th Quantile Flow (Q5), and 95th Quantile Flow (Q95) showing overall better performance.
Finally, the results of this study demonstrate the reliability of using bottom-up satellite products in Pd basins.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
