Abstract

Successful streamflow forecasts depend on an adequate performance evaluation of the hydrological model. In this study, the hydrological responses were compared using two hydrological models, physic-based and semi-distributed, Soil and Water Assessment Tool (SWAT) and Variable Infiltration Capacity (VIC), using input data from the Verde River Watershed, located in the Minas Gerais state in southern Brazil. This is a study of one of the most important headwater watershed regions of Brazil (Mantiqueira Range). Both models were suitable for streamflow simulation, with values of R2 (determination coefficient) and NSE (Nash-Sutcliffe) higher than 0.8, NSELog higher than 0.35 (Nash–Sutcliffe Efficiency of the logarithmic values of discharge) and PBIAS (percentage deviation) less than 25%. The integration of SWAT and VIC models can be useful in different water-resource assessment studies. Therefore, based upon this study further investigations should be conducted using various hydrological models and climate, land-use and land-cover changes scenarios in the region.

Highlights

  • Hydrological models have been increasingly used because they help understand the impact of future changes in water balance associated with climate and land-use changes (Alvarenga et al, 2018; Louzada and Ribeiro, 2019)

  • The Verde River Watershed is located in the south of Minas Gerais state, southeastern Brazil (Minas Gerais-MG, Espírito Santo-ES, São Paulo-SP and Rio de Janeiro-RJ states), and is inserted in the Atlantic Forest biome, with springs in the Serra da Mantiqueira

  • Evapotranspiration presented values that ranged from 57.9 to 65.7% of the rainfall. These percentages show reasonable performance of the Variable Infiltration Capacity (VIC) and Soil and Water Assessment Tool (SWAT) for estimating evapotranspiration and, its capability of simulating streamflow in the Verde River Watershed. These results suggest that SWAT and VIC can be useful for simulations focusing on the long-term trend

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Summary

Introduction

Hydrological models have been increasingly used because they help understand the impact of future changes in water balance associated with climate and land-use changes (Alvarenga et al, 2018; Louzada and Ribeiro, 2019). More complex parameters to be quantified must be refined during the calibration phase of a model (Du et al, 2014). The available data in a simulation should represent the input variables and parameter distributions of the hydrological model to recommend the use of more complex distributed models (Santos et al, 2018). The performance of a model can vary with hydrological variables and conditions assessed, such as droughts or floods. The greater complexity of a hydrological model cannot guarantee improvements in its performance. Based and distributed models can be useful for detailed surface overland flow assessments and water balance studies. To assess the impacts of climate change, a simple conceptual model can be appropriate (Singh and Marcy, 2017; Orth et al, 2015)

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