<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml">The objective of this paper is to simulate flow frequency distribution curves for Amazon catchments with the aim of scaling power generation from small hydroelectric power plants. Thus, a simple nonlinear rainfall-runoff model was developed with sigmoid-variable gain factor due to the moisture status of the catchment, which depends on infiltration, and is considered a factor responsible for the nonlinearity of the rainfall-runoff process. Data for a catchment in the Amazon was used to calibrate and validate the model. The performance criteria adopted were the Nash-Sutcliffe coefficient (R2), the RMS, the <italic>Q</italic>95% frequencyc flow percentage error, and the mean percentage errors ranging from <italic>Q</italic>5% to <italic>Q</italic>95%.. Calibration and validation showed that the model satisfactorily simulates the flow frequency distribution curves. In order to find the shortest period of rainfall-runoff data, which is required for applying the model, a sensitivity analysis was performed whereby rainfall and runoff data was successively reduced by 1 year until a 1.5-year model application minimum period was found. This corresponds to one hydrological year plus the 6-month long "memory". This analysis evaluates field work in the ungauged sites of the region.</abstract>

The objective of this paper is to simulate flow frequency distribution curves for Amazon catchments with the aim of scaling power generation from small hydroelectric power plants. Thus, a simple nonlinear rainfall-runoff model was developed with sigmoid-variable gain factor due to the moisture status of the catchment, which depends on infiltration, and is considered a factor responsible for the nonlinearity of the rainfall-runoff process. Data for a catchment in the Amazon was used to calibrate and validate the model. The performance criteria adopted were the Nash-Sutcliffe coefficient (R2), the RMS, the Q95% frequencyc flow percentage error, and the mean percentage errors ranging from Q5% to Q95%.. Calibration and validation showed that the model satisfactorily simulates the flow frequency distribution curves. In order to find the shortest period of rainfall-runoff data, which is required for applying the model, a sensitivity analysis was performed whereby rainfall and runoff data was successively reduced by 1 year until a 1.5-year model application minimum period was found. This corresponds to one hydrological year plus the 6-month long "memory". This analysis evaluates field work in the ungauged sites of the region.

A Non-Linear Rainfall-Runoff Model with a Sigmoid Gain Factor to Simulate Flow Frequency Distribution Curves for Amazon Catchments

Natural Resources Engineering, University of Pará, Rua Augusto Corrěa, 01, 66075-110, Belém-Pará-Brazil

Journal of Hydrology and Hydromechanics

The objective of this paper is to simulate flow frequency distribution curves for Amazon catchments with the aim of scaling power generation from small...

A Non-Linear Rainfall-Runoff Model with a Sigmoid Gain Factor to Simulate Flow Frequency Distribution Curves for Amazon Catchments

Data publikacji: 21 wrz 2011

Zakres stron: 145 - 156

DOI: https://doi.org/10.2478/v10098-011-0012-x

Słowa kluczowe
hydrologické modelovanie, čiara rozdelenia prietokov, malé povodia riekyAmazonka

This content is open access.

A Non-Linear Rainfall-Runoff Model with a Sigmoid Gain Factor to Simulate Flow Frequency Distribution Curves for Amazon Catchments

Data publikacji: 21 wrz 2011

Zakres stron: 145 - 156

DOI: https://doi.org/10.2478/v10098-011-0012-x

Słowa kluczowehydrologické modelovanie, čiara rozdelenia prietokov, malé povodia riekyAmazonka

This content is open access.

Słowa kluczowe
hydrologické modelovanie, čiara rozdelenia prietokov, malé povodia riekyAmazonka