https://orcid.org/0000-0002-8547-4736
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ABSTRACT
It has been proposed that linear regression curves can be used to estimate monthly climate variables from observed precipitation. This approach was explored by applying the MGB hydrological model to the Paraná Basin (Brazil). Linear regressions were obtained for 54 climate gauges, and most of them showed at least six months of significant correlation between monthly climate variables (sunlight hours and relative humidity) and precipitation. The regression equations were applied to 5201 raingauges to estimate monthly climate variables and evapotranspiration, and the results were compared with a scenario using long-term climate averages only. The main differences occurred in wetter periods, where negative correlations between monthly precipitation and evapotranspiration were obtained when using precipitation as a proxy. Long-term changes in the hydrological regime were assessed and showed that the effect of precipitation on relative humidity and sunlight hours seems to have a minor effect on the alterations observed in river discharge in the Paraná Basin.
Editor R. Woods; Associate editor H. Kreibich
Editor R. Woods; Associate editor H. Kreibich
Disclosure statement
No potential conflict of interest was reported by the authors.