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Geostatistical modeling and traditional approaches for streamflow regionalization in a Brazilian Southeast watershed

2021; Elsevier BV; Volume: 108; Linguagem: Inglês

10.1016/j.jsames.2021.103355

1873-0647

Renan Gon Ferreira, Demétrius David da Silva, Abrahão Alexandre Alden Elesbon, Gérson Rodrigues dos Santos, Gustavo Vieira Veloso, Micael de Souza Fraga, Elpı́dio Inácio Fernandes Filho,

Groundwater and Watershed Analysis

Focused on supporting the planning and management of water resources in a watershed domain, this study aimed to assess and compare the performance of multiple approaches for streamflow regionalization. The applied methods were based on linear interpolation, regional regressions (RR), and kriging. The dependent variables used were low-flows of reference (Q7.10, Q95, and Q90) and the long-term mean streamflow (Qmld). The independent variables used by the RR method were drainage area, mean annual precipitation, mean precipitation in the dry and rainy seasons, besides the flow equivalent to the precipitated volume minus the 750 mm abstraction (Peq750). The RR's equations were best fitted using the potential model, and three hydrologically homogeneous regions (RHH) were identified. Meanwhile, the exponential model provided the best fit to the experimental semivariograms in the geostatistical analysis. The methodologies' performance was estimated by the following metrics: mean relative error, percent bias, root mean square error, Nash-Sutcliffe coefficient, and coefficient of determination. The evaluated methodologies had similar performance for the low-flows and long-term mean streamflow, despite the lower accuracy by using the kriging methods for the Q7.10 at the RHH III. All approaches performed better for Qmld, since it is not an extreme variable. Although all methods have shown good results, the adoption of kriging and linear interpolation must always be linked with a careful analysis of factors such as the density and spatial distribution of stream gauge stations in the watershed.