9th International Symposium on Integrated Water Resources Management (IWRM) | 14th International Workshop on Statistical Hydrology (STAHY) | I EBHE - Encontro Brasileiro de Hidrologia Estatística

Data: 04/11/2024 à 07/11/2024
Local: Florianópolis-SC
Mais informações: https://www.abrhidro.org.br/iebhe

Assessment of a downscaling using quantiles mapping with MIROC model and satellite based precipitation in Guadalquivir basin, Bolivia

Código

I-EBHE0190

Autores

Oliver Saavedra

Tema

WG 1.01: REHYDRATE - REtrieve historical HYDRologic dATa & Estimates

Resumo

In this study daily combined satellite based precipitation products were generated and assessed versus climate change scenarios at Guadalquivir basin in southern Bolivia. The aim of this study was to evaluate areal precipitation and the downscaling procedure using Quantiles Downscaling Mapping (QDM). These schemes are based in statistical analysis where precipitation and temperature are adjusted using observed datasets. Moreover, simulated river discharge was obtained using HYDROBID tool. It was identified underestimation of combined satellite based precipitation product derived from GSMaP as well as simulated river discharge. Three climate change scenarios from MIROC CORDEX were used namely: RCP2.6, RCP4.5 and RCP8.5. The precipitation and temperature analyses were performed at daily time step. The results of QDM application showed more efficiency with RCP 8.5 and combined precipitation product for the 230 sub- basins. The hydrological model forced with perturbed climate change using combined precipitation product with lower values against rain gauges. In this sense, precipitation and river discharge were underestimated. Temperature showed the best performance at all cases. Finally, river discharge values were integrated into volumes, where a decrease in water availability at the basins was noted as for near and far future. It is recommended to use perturbed scenarios with combined precipitation product since it is the most critical and takes into account the spatial variability.

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