Silvia Roxana Mattos Gutierrez

Ms. Silvia Roxana Mattos Gutierrez


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 June 2024 in Remote Sensing
Verified
Journal Article
Open access
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Silvia Roxana Mattos GutierrezSilvia Roxana Mattos Gutierrez
Silvia Roxana Mattos Gutierrez
AFAyele Almaw Fenta
Ayele Almaw Fenta
TMTaye Minichil Meshesha
Taye Minichil Meshesha
ABAshebir Sewale Belay
Ashebir Sewale Belay
This study evaluated the accuracy of two new generation satellite rainfall estimates (SREs): Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and Integrated Multi-satellite Retrieval for GPM (IMERG) over Bolivia’s complex terrain. These SREs were compared against rainfall data from rain gauge measurements on a point-to-pixel basis for the period 2002–2020. The evaluation was performed across three regions with distinct topographical settings: Altiplano (Highland), Valles (Midland), and Llanos (Lowland). IMERG exhibited better accuracy in rainfall detection than CHIRPS, with the highest rainfall detection skills observed in the Highland region. However, IMERG’s higher rainfall detection skill was countered by its higher false alarm ratio. CHIRPS provided a more accurate estimation of rainfall amounts across the three regions, exhibiting low random errors and relative biases below 10%. IMERG tended to overestimate rainfall amounts, with marked overestimation by up to 75% in the Highland region. Bias decomposition revealed that IMERG’s high false rainfall bias contributed to its marked overestimation of rainfall. We showcase the utility of long-term CHIRPS data to investigate spatio-temporal rainfall patterns and meteorological drought occurrence in Bolivia. The findings of this study offer valuable insights for choosing appropriate SREs for informed decision-making, particularly in regions of complex topography lacking reliable gauge data.