Spectral analysis of base flow separation with digital filters

Spongberg, Mary

doi:10.1029/1999wr900303

Cited by 60 publications

(55 citation statements)

References 16 publications

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“…This filter limits the maximum ratio of baseflow to streamflow. Eckhardt (2005) describes this as potentially beneficial following the demonstration of Spongberg (2000) that runoff has a non-negligible low-frequency component. The equation for this filter is given by (Eckhardt, 2005):…”

Section: Baseflow Separation Using Automated Methodsmentioning

confidence: 99%

Evaluation of outputs from automated baseflow separation methods against simulated baseflow from a physically based, surface water-groundwater flow model

Partington

Brunner

Simmons

et al. 2012

Journal of Hydrology

141

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s u m m a r yBaseflow is often considered to be the groundwater discharge component of streamflow. It is commonly estimated using conceptual models, recursive filters or a combination of the two. However, it is difficult to validate these methods due to the current challenges of measuring baseflow in the field. In this study, simulation of a synthetic catchment's response to rainfall is carried out using a fully integrated surface water-groundwater flow model. A series of rainfall events with differing recovery periods and varied antecedent moisture conditions is considered to span a range of different streamflow generation dynamics. Baseflow is estimated for the outlet hydrograph of the synthetic catchment using a selection of commonly used automated baseflow separation methods. These estimates are compared to the baseflow signal obtained from the numerical model, which serves as the control experiment. Results from these comparisons show that depending on the method used, automated baseflow separation underestimates the simulated baseflow by as much as 28%, or overestimates it by up to 74%, during rainfall events. No separation method is found to be clearly superior to the others, as the performance of the various methods varies with different soil types, antecedent moisture conditions and rainfall events. The differences between the various approaches clearly demonstrate that the baseflow separation methods investigated are not universally applicable.

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Section: Baseflow Separation Using Automated Methodsmentioning

confidence: 99%

Evaluation of outputs from automated baseflow separation methods against simulated baseflow from a physically based, surface water-groundwater flow model

Partington

Brunner

Simmons

et al. 2012

Journal of Hydrology

141

View full text Add to dashboard Cite

show abstract

“…The FFT is an algorithm that computes the discrete Fourier transform (DFT) of time series data, and it converts time domain data to frequency domain data and vice versa [46]. The LPF technique extracts signals with frequencies lower than a certain target cut-off frequency.…”

Section: Removal Of Noise From Groundwater Level Data With Lpfmentioning

confidence: 99%

“…The LPF technique extracts signals with frequencies lower than a certain target cut-off frequency. For certain time series data of V, the FFT as written by Walker [46,47] is…”

Section: Removal Of Noise From Groundwater Level Data With Lpfmentioning

confidence: 99%

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Characterizing the Impact of River Barrage Construction on Stream-Aquifer Interactions, Korea

Hamm

et al. 2016

Water

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This study investigated changes in stream-aquifer interactions during the period shortly after the construction of the Changnyeong-Haman River barrage (CHRB) on the Nakdong River in South Korea. The hydraulic diffusivity (α) and river resistance (R) values at the semipervious stream-aquifer interface were estimated by using a one-dimensional (1-D) analytical solution with Fourier transform (FT). Prior to the application of the 1-D analytical solution, the noise effects on the groundwater levels were removed by using fast Fourier transform and low-pass filtering techniques. Sinusoidal variation of the river stages was applied to the 1-D analytical solution. For the study period, the R values showed a decreasing trend, while the α values showed an increasing trend, and results showed that the average of the median values of flood duration times (t d ) and flood amplitudes were reduced to 78% and 59%, respectively. Moreover, the ratio of flood peak time to t d demonstrated a decreasing tendency after the construction of the CHRB. Hence, it is concluded that the dredging and increase of river-water storage due to CHRB construction enhanced stream-aquifer interactions during the period shortly after the construction of the CHRB.

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“…Mostly the studies have concentrated on using either the statistical techniques or soft decomposing techniques for data decomposition [3]. Studies include automated base flow separation and recession analysis [4], spectral analysis [5], wavelet transforms and runoff time series analysis [6][7][8][9], modular neural network (MNN) [10], self-organizing map (SOM) classifier [11,12] and self organizing linear output map (SOLO) [13]. Most of these studies conclude that the decomposition and partitioning of data resulted in better model performance.…”

Section: Introductionmentioning

confidence: 99%

Streamflow Decomposition Based Integrated ANN Model

Bhatia¹,

Sharma²,

Srivastava³

et al. 2013

OJMH

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The prediction of riverflows requires the understanding of rainfall-runoff process which is highly nonlinear, dynamic and complex in nature. In this research streamflow decomposition based integrated ANN (SD-ANN) model is developed to improve the efficacy rather than using a single ANN model for the flow hydrograph. The streamflows are decomposed into two states namely 1) the rise state and 2) the fall state. The rainfall-runoff data obtained from the Kolar River basin is used to test the efficacy of the proposed model when compared to feed-forward ANN model (FF-ANN). The results obtained in this study indicate that the proposed SD-ANN model outperforms the single ANN model in terms of both the statistical indices and the prediction of high flows.

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Spectral analysis of base flow separation with digital filters

Cited by 60 publications

References 16 publications

Evaluation of outputs from automated baseflow separation methods against simulated baseflow from a physically based, surface water-groundwater flow model

Evaluation of outputs from automated baseflow separation methods against simulated baseflow from a physically based, surface water-groundwater flow model

Characterizing the Impact of River Barrage Construction on Stream-Aquifer Interactions, Korea

Streamflow Decomposition Based Integrated ANN Model

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