Hydrological modeling in a basin of the Brazilian Cerrado biome

Rodrigues, Jéssica Assaid Martins; Andrade, Alberto Carlos de Oliveira; Viola, Marcelo Ribeiro; Ferreira, Danton Diego; Mello, Carlos Rogério de; Thebaldi, Michael Silveira

doi:10.4136/ambi-agua.2639

Cited by 8 publications

(6 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Rodrigues et al (2020), which applied the SWAT model to monthly streamflow simulation near the SRB outlet with a control section in Porto Real (drainage area of 45,042 km²), identified 11 sensitive parameters, of which seven are coincident with this study: ESCO, CN2, ALPHA_BF, CANMX, CH_N2, GW_REVAP, and CH_K2. Similar results were also found in Rodrigues et al (2021), which applied the SWAT model for the simulation of daily streamflow in Manuel Alves da Natividade River Basin (MRB) (drainage area of 14,344 km²), adjacent to the SRB. The authors identified 14 sensitive parameters, of which eleven are coincident with this study, and the GWQMN did not show sensitivity in the MRB.…”

Section: Sensitivity Analysissupporting

confidence: 76%

“…Martins et al (2020) applied the SWAT model for monthly streamflow simulation in the Ribeirão do Pinhal watershed, Limeira -São Paulo, and obtained NSE of 0.64 and 0.58 and PBIAS of 15.2 and -2.8%, respectively, for calibration and validation periods. Rodrigues et al (2021) evaluated the performance of the SWAT model in daily streamflow simulation in the Manuel Alves da Natividade River Basin (MRB), adjacent to the SRB, and obtained NSE values of 0.67 and 0.61, respectively, for calibration and validation periods.…”

Section: Swat Calibration and Validationmentioning

confidence: 99%

See 1 more Smart Citation

Hydrological modeling in the Sono river basin, environmental protection region of the Jalapão, Brazilian savanna

Rodrigues

Junqueira

Amorim

et al. 2021

Rev. Bras. Geog. Fis.

Self Cite

View full text Add to dashboard Cite

The Sono river basin (SRB) is an important ecological area located at the Cerrado biome, which encompasses several environmental protection units, highlighting the Jalapão State Parque. In order to assist the water resource management, this paper developed a hydrological simulation of the SRB, delineated at the Jatobá station (drainage area of 16,862 km²), using the SWAT model, and determined the spatial distribution of the mean, maximum, and minimum specific yields (REmlt, REmin, and REmax) in the basin. The performance of the model was evaluated using Nash-Sutcliffe efficiency (NSE) and percentage bias (PBIAS). For the monthly calibration and validation periods, respectively, NSE values of 0.55 and 0.56 and PBIAS values of 8.2% and -10.2% were obtained. For daily calibration and validation periods, respectively, NSE values of 0.40 and 0.41 and PBIAS values of 8.2% and -11.2% were obtained. These results indicate that the SWAT was able to model the monthly and daily streamflows of the SRB. In addition, the REmlt, REmin and REmax maps showed that the environmental protection areas are the biggest water producers compared with the other parts of the basin. Therefore, the results achieved in this study are fundamental tools for the water resources management at this important ecological region. Keywords: soil and water assessment tool; Cerrado biome; Tocantins-Araguaia river basin. Modelagem hidrológica na bacia do rio Sono, região de proteção ambiental do Jalapão, savana brasileira R E S U M OA bacia do rio Sono (SRB) é uma importante área ecológica localizada no Cerrado, a qual engloba diversas unidades de proteção ambiental, com destaque para o Parque Estadual do Jalapão. Visando auxiliar a gestão dos recursos hídricos, este trabalho desenvolveu uma simulação hidrológica da SRB, delineada na estação Jatobá (área de drenagem de 16.862 km²), utilizando o modelo SWAT, e determinou a distribuição espacial dos rendimentos específicos médio, máximo e mínimo (REmlt, REmin e REmax) na bacia. O desempenho do modelo foi avaliado por meio do coeficiente de Nash-Sutcliffe (NSE) e do percentual de viés (PBIAS). Para os períodos mensais de calibração e validação, respectivamente, foram obtidos valores de NSE de 0,55 e 0,56 e valores de PBIAS de 8,2% e -10,2%. Para os períodos diários de calibração e validação, respectivamente, foram obtidos valores de NSE de 0,40 e 0,41 e valores de PBIAS de 8,2% e -11,2%. Esses resultados indicam que o SWAT foi capaz de modelar as vazões mensais e diárias da SRB. Além disso, os mapas REmlt, REmin e REmax mostraram que as áreas de proteção ambiental são as maiores produtoras de água em comparação com as demais partes da bacia. Portanto, os resultados alcançados neste estudo são ferramentas fundamentais para a gestão dos recursos hídricos nesta importante região ecológica. Palavras-chave: soil and water assessment tool; bioma Cerrado; bacia hidrográfica dos rios Tocantins-Araguaia.

show abstract

Section: Sensitivity Analysissupporting

confidence: 76%

Section: Swat Calibration and Validationmentioning

confidence: 99%

Hydrological modeling in the Sono river basin, environmental protection region of the Jalapão, Brazilian savanna

Rodrigues

Junqueira

Amorim

et al. 2021

Rev. Bras. Geog. Fis.

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, the lack of adequate hydrological monitoring in this region has led to problems in the management of water resources, which may further compromise the sustainability of this important biome. Thus, improving the knowledge base on streamflow in the Cerrado biome is essential for water management in Brazil and for ensuring water security and economic development (Rodrigues et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Hydrological regionalization of streamflows for the Tocantins River Basin in Brazilian Cerrado biome

Rodrigues¹,

Viola²,

Mello³

et al. 2021

Rev. ambiente água

Self Cite

View full text Add to dashboard Cite

The Brazilian Cerrado biome is the largest and richest tropical savanna in the world and is among the 25 biodiversity hotspots identified worldwide. However, the lack of adequate hydrological monitoring in this region has led to problems in the management of water resources. In order to provide tools for the adequate management of water resources in the Brazilian Cerrado biome region, this paper develops the regionalization of maximum, mean and minimum streamflows in the Tocantins River Basin (287,405.5 km2), fully located in the Brazilian Cerrado biome. The streamflow records of 32 gauging stations in the Tocantins River Basin are examined using the Mann-Kendall test and the hydrological homogeneity non-parametric index-flood method. One homogeneous region was identified for the estimate of the streamflows Qltm (long-term mean streamflow), Q90% (streamflow with 90% of exceeding time), Q95% (streamflow with 95% of exceeding time) and Q7,10 (minimum annual streamflow over 7 days and return period of 10 years). Two homogeneous regions were identified for maximum annual streamflow estimation and the Generalized Extreme Value distribution is found to describe the distribution of maximus events appropriately within the both regions. Regional models were developed for each streamflow of each region and evaluated by cross-validation. These models can be used for the estimation of maximum, mean and minimum streamflows in ungauged basins within the Tocantins River Basin within the area boundaries identified. Therefore, the results provided in this paper are valuable tools for practicing water-resource managers in the Brazilian Cerrado biome. Keywords: l-moments, statistical hydrology, water use rights concessions.

show abstract

“…Good adherence of the forecasted hydrographs to those observed can be seen, mainly in the periods of streamflow recession. According to Rodrigues et al (2021), the best models for these periods should be based on the relationship between the groundwater flow, which is predominant in the recession periods, and the discharge from the aquifer. Peak flows were underestimated by the models, mainly due to the difficulty in capturing the many variables involved in the streamflow process, the difficult representation of the spatial variability of rainfall over the basin due to the low density of rain-gauge stations in the basins, and even errors from the extrapolation of the stage-curve of the river (Viola et al 2009;Silva Neto et al 2020).…”

Section: Resultsmentioning

confidence: 99%

Streamflow forecasting in Tocantins river basins using machine learning

et al. 2022

View full text Add to dashboard Cite

Understanding the behavior of the river regime in watersheds is fundamental for water resources planning and management. Empirical hydrological models are powerful tools for this purpose, with the selection of input variables as one of the main steps of the modeling. Therefore, the objectives of this study were to select the best input variables using the genetic, recursive feature elimination, and vsurf algorithms, and to evaluate the performance of the random forest, artificial neural networks, support vector regression, and M5 model tree models in forecasting daily streamflow in Sono (SRB), Manuel Alves da Natividade (MRB), and Palma (PRB) River basins. Based on several performance indexes, the best model in all basins was the M5 model tree, which showed the best performances in SRB and PRB using the variables selected by the recursive feature elimination algorithm. The good performance of the evaluated models allows using them to assist different demands faced by the water resources management in the studied river basins, especially the M5 model tree model using streamflow lags, average rainfall, and evapotranspiration as inputs.

show abstract

Hydrological modeling in a basin of the Brazilian Cerrado biome

Cited by 8 publications

References 39 publications

Hydrological modeling in the Sono river basin, environmental protection region of the Jalapão, Brazilian savanna

Hydrological modeling in the Sono river basin, environmental protection region of the Jalapão, Brazilian savanna

Hydrological regionalization of streamflows for the Tocantins River Basin in Brazilian Cerrado biome

Streamflow forecasting in Tocantins river basins using machine learning

Contact Info

Product

Resources

About