Synergistic calibration of a hydrological model using discharge and remotely sensed soil moisture in the Paraná river basin

• Autor(a) principal: Fleischmann, Ayan Santos
• Data de Publicação: 2021
• Outros Autores: Oliveira, Aline Meyer, Siqueira, Vinícius Alencar, Colossi, Bibiana Rodrigues, Paiva, Rodrigo Cauduro Dias de, Kerr, Yann, Ruhoff, Anderson Luis, Fan, Fernando Mainardi, Pontes, Paulo Rógenes Monteiro, Collischonn, Walter, Al Bitar, Ahmad
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRGS
• Texto Completo: http://hdl.handle.net/10183/232840
• topic: Modelos hidrológicos; Calibração; Umidade do solo; Sensoriamento remoto; Paraná, Rio, Bacia do; Optimal calibration; SMOS; Soil moisture; South America hydrology; Large-scale hydrology

Hydrological models are useful tools for water resources studies, yet their calibration is still a challenge, especially if aiming at improved estimates of multiple components of the water cycle. This has led the hydrologic community to look for ways to constrain models with multiple variables. Remote sensing estimates of soil moisture are very promising in this sense, especially in large areas for which field observations may be unevenly distributed. However, the use of such data to calibrate hydrological models in a synergistic way is still not well understood, especially in tropical humid areas such as those found in South America. Here, we perform multiple scenarios of multiobjective model optimization with in situ discharge and the SMOS L4 root zone soil moisture product for the Upper Paraná River Basin in South America (drainage area > 900,000 km2), for which discharge data for 136 river gauges are used. An additional scenario is used to compare the relative impacts of using all river gauges and a small subset containing nine gauges only. Across the basin, the joint calibration (CAL-DS) using discharge and soil moisture leads to improved precision and accuracy for both variables. The discharges estimated by CAL-DS (median KGE improvement for discharge was 0.14) are as accurate as those obtained with the calibration with discharge only (median equal to 0.14), while the CAL-DS soil moisture retrieval is practically as accurate (median KGE improvement for soil moisture was 0.11) as that estimated using the calibration with soil moisture only (median equal to 0.13). Nonetheless, the individual calibration with discharge rates is not able to retrieve satisfactory soil moisture estimates, and vice versa. These results show the complementarity between these two variables in the model calibration and highlight the benefits of considering multiple variables in the calibration framework. It is also shown that, by considering only nine gauges inste