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Spatial‐temporal analysis of the climatic and anthropogenic influences on runoff in the Jucu River Basin, Southeastern Brazil
Author(s) -
Delmonte Oliveira Kenny,
Tomasella Javier,
Del'Arco Sanches Leda
Publication year - 2019
Publication title -
land degradation and development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 81
eISSN - 1099-145X
pISSN - 1085-3278
DOI - 10.1002/ldr.3403
Subject(s) - surface runoff , environmental science , structural basin , hydrology (agriculture) , drainage basin , climate change , runoff curve number , spatial variability , physical geography , ecology , geography , statistics , mathematics , geology , cartography , biology , geotechnical engineering , paleontology
Isolating and quantifying the impacts of climate change and human influences on runoff in basins is one of the main challenges of hydrology due to nonstationarity and nonlinear character of the processes. As a result, new hydrological approaches have been proposed, leading to many assumptions for their implementation. Among these, it is worth mentioning the subjectivity in the choice of causal variables that compose climatic and anthropogenic factors and the definition of breakpoints that allows the conjoint analysis of the contribution of these factors on runoff. In this study, the quantification of the influence of climatic and anthropogenic factors on runoff in the Jucu River basin was performed using a decompositional method based on the Budyko hypothesis with time‐varying parameters. For the parameterization of the equations, we considered a combination of 16 variables of a historical series of 47 years (1970–2017). The runoff at sub‐basins of different scales, climatic types, and soil uses was similarly affected by the influences factors. Changes on runoff were mainly due to anthropogenic factors with −18.6 mm (80.5%), followed by climatic factors with −4.5 mm (19.5%) for the whole period. Among all the land use variables considered, agriculture, forest, and pasture were predominantly responsible for the changes. In addition, graphical analysis of the time‐variation of the variables of the Budyko curve proved to be an efficient and low subjectivity approach to identify breakpoints in the conjoint analysis of hydrological variables.