Hydrological Model Performance in the Verde River Basin, Minas Gerais, Brazil

Author:

de Oliveira Conceição de M. M.12ORCID,Alvarenga Lívia A.1,Beskow Samuel3ORCID,da Cunha Zandra Almeida3ORCID,Vargas Marcelle Martins3ORCID,Melo Pâmela A.1ORCID,Tomasella Javier4ORCID,Santos Ana Carolina N.4,Carvalho Vinicius S. O.5,Silva Vinicius Oliveira1ORCID

Affiliation:

1. Department of Water Resources, Federal University of Lavras, Lavras 37200-000, Brazil

2. Department of Agricultural Engineering, State University of Maranhão, Cidade Universitária Paulo VI., São Luis 65055-310, Brazil

3. Center for Technological Development/Water Resources Engineering, Federal University of Pelotas, Pelotas 96010-610, Brazil

4. National Institute for Space Research (INPE), National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), Postal Code 01, Cachoeira Paulista 12630-970, Brazil

5. Institute of Natural Resources, Federal University of Itajubá, Itajubá 37500-903, Brazil

Abstract

In hydrological modelling, it is important to consider the uncertainties related to a model’s structures and parameters when different hydrological models are used to represent a system. Therefore, an adequate analysis of daily discharge forecasts that takes into account the performance of hydrological models can assist in identifying the best extreme discharge forecasts. In this context, this study aims to evaluate the performance of three hydrological models—Lavras Simulation of Hydrology (LASH), Variable Infiltration Capacity (VIC), and Distributed Hydrological Model (MHD-INPE) in the Verde River basin. The results demonstrate that LASH and MHD can accurately simulate discharges, thereby establishing them as crucial tools for managing water resources in the study region’s basins. Moreover, these findings could serve as a cornerstone for future studies focusing on food and water security, particularly when examining their connection to climate change scenarios.

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Nature and Landscape Conservation

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