Filtered smoothed minima baseflow separation method

Aksoy, Hafzullah; Kurt, Ilker; Eriş, Ebru

doi:10.1016/j.jhydrol.2009.03.037

Cited by 94 publications

(71 citation statements)

References 29 publications

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“…Several techniques -such as graphical separation, rainfallrunoff models, and baseflow filters -have arisen to estimate baseflow fluxes from discharge records (e.g. Nathan and McMahon, 1990;Dye and Croke, 2003;Eckhardt, 2005Eckhardt, , 2008Brodie et al, 2007;Aksoy et al, 2009). Automated graphical baseflow separation algorithms such as fixed block, sliding block, or local minimum methods define baseflow as the minimum discharge over a given period of time, the duration of which is governed by catchment size (e.g.…”

Section: Cartwright Et Al: Contrasts Between Estimates Of Baseflowmentioning

confidence: 99%

“…Automated graphical baseflow separation algorithms such as fixed block, sliding block, or local minimum methods define baseflow as the minimum discharge over a given period of time, the duration of which is governed by catchment size (e.g. Sloto and Crouse, 1996;Aksoy et al, 2009). Digital filtering techniques assume that baseflow has a longer wavelength response than quickflow and may be estimated by passing a low-pass digital filter across the river hydrograph (e.g.…”

Section: Cartwright Et Al: Contrasts Between Estimates Of Baseflowmentioning

confidence: 99%

“…The data available in the Barwon catchment are similar to those in many catchments globally, and the adopted techniques have been applied individually or in combination elsewhere (e.g. Nathan and McMahon, 1990;Yu and Schwartz, 1999;Eckhardt, 2005;Stewart et al, 2007;Gonzalez et al, 2009;Aksoy et al, 2009;Sanford et al, 2012;Zabaleta and Antiguedad, 2013). For management purposes, it is important to understand the water balance in medium or larger catchments, recognising that they will rarely have the data density of small heavily instrumented catchments.…”

Section: Objectivesmentioning

confidence: 99%

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Contrasts between estimates of baseflow help discern multiple sources of water contributing to rivers

Cartwright

Gilfedder

Hofmann

2014

Hydrol. Earth Syst. Sci.

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Abstract. This study compares baseflow estimates using chemical mass balance, local minimum methods, and recursive digital filters in the upper reaches of the Barwon River, southeast Australia. During the early stages of highdischarge events, the chemical mass balance overestimates groundwater inflows, probably due to flushing of saline water from wetlands and marshes, soils, or the unsaturated zone. Overall, however, estimates of baseflow from the local minimum and recursive digital filters are higher than those based on chemical mass balance using Cl calculated from continuous electrical conductivity measurements. Between 2001 and 2011, the baseflow contribution to the upper Barwon River calculated using chemical mass balance is between 12 and 25 % of the annual discharge with a net baseflow contribution of 16 % of total discharge. Recursive digital filters predict higher baseflow contributions of 19 to 52 % of discharge annually with a net baseflow contribution between 2001 and 2011 of 35 % of total discharge. These estimates are similar to those from the local minimum method (16 to 45 % of annual discharge and 26 % of total discharge). These differences most probably reflect how the different techniques characterise baseflow. The local minimum and recursive digital filters probably aggregate much of the water from delayed sources as baseflow. However, as many delayed transient water stores (such as bank return flow, floodplain storage, or interflow) are likely to be geochemically similar to surface runoff, chemical mass balance calculations aggregate them with the surface runoff component. The difference between the estimates is greatest following periods of high discharge in winter, implying that these transient stores of water feed the river for several weeks to months at that time. Cl vs. discharge variations during individual flow events also demonstrate that inflows of high-salinity older water occurs on the rising limbs of hydrographs followed by inflows of low-salinity water from the transient stores as discharge falls. The joint use of complementary techniques allows a better understanding of the different components of water that contribute to river flow, which is important for the management and protection of water resources.

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Section: Cartwright Et Al: Contrasts Between Estimates Of Baseflowmentioning

confidence: 99%

Section: Cartwright Et Al: Contrasts Between Estimates Of Baseflowmentioning

confidence: 99%

Section: Objectivesmentioning

confidence: 99%

See 1 more Smart Citation

Contrasts between estimates of baseflow help discern multiple sources of water contributing to rivers

Cartwright

Gilfedder

Hofmann

2014

Hydrol. Earth Syst. Sci.

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“…number of elements of these groups was shown with N and was determined as five. A data series was formed within group with minimums in the groups (y i , i = 1, 2, 3, 4, …) and turning points were determined by comparison with equation (3) (Institute of Hydrology, 1980;Tallaksen, 1987;Hisdal et al, 2003;Aksoy et al, 2009). …”

Section: United Kingdom Institute Of Hydrology Methods (Ukih)mentioning

confidence: 99%

“…(4) (Aksoy et al, 2009;nejadhashemi et al, 2009;Koskelo et al, 2012). For the obtained results mean absolute error (MAE) and root mean square error (RMSE) were calculated, and linear regression method (R 2 ) was applied (eqs.…”

Section: United Kingdom Institute Of Hydrology Methods (Ukih)mentioning

confidence: 99%

The examination of the performances of methods used in separating the total stream flow in different rivers

Şengörür¹,

Dede²,

Doğan³

2014

Geofizika

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In this study, the performances of methods of flow separation into the surface flow and base flow of the total stream flow in rivers with different hydraulic features have been examined. For this purpose, daily mean stream flow data of Büyük Melen and Aksu Rivers which are in the same watershed but with different features (average flow value, catchment area, mean elevation) have been separated as surface flow and base flow with the use of Digital Filtering Method (DFM) and United Kingdom Institute of Hydrology Method (UKIH). The recession coefficient in DFM has been used as α = 0.830; and the number of elements for the groups formed to determine the turning points of flow data in UKIH has been used as N = 5. The study has revealed that the results of surface and base flows obtained by both flow separation methods show similarity in all rivers in an acceptable level; and the surface flow values agree better (R 2 > 0,76) compared to base flow values (R 2 > 0.63). However, it has been seen that as long as the total flow values decrease, the surface flow results for both methods come closer to each other; but the results of base flow get differentiated. This situation has been clearly seen in the results of surface (R 2 > 0.89) and base (R 2 > 0.63) flows belonging to Aksu River which has lower values of flow when compared to the ones of Büyük Melen River.

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Evaluation of streamflow simulation results of land surface models in GLDAS on the Tibetan plateau

et al. 2016

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The Global Land Data Assimilation System (GLDAS) project estimates long‐term runoff based on land surface models (LSMs) and provides a potential way to solve the issue of nonexistent streamflow data in gauge‐sparse regions such as the Tibetan Plateau (TP). However, the reliability of GLDAS runoff data must be validated before being practically applied. In this study, the streamflows simulated by four LSMs (CLM, Noah, VIC, and Mosaic) in GLDAS coupled with a river routing model are evaluated against observed streamflows in five river basins on the TP. The evaluation criteria include four aspects: monthly streamflow value, seasonal cycle of streamflow, annual streamflow trend, and streamflow component partitioning. The four LSMs display varying degrees of biases in monthly streamflow simulations: systematic overestimations are found in the Noah (1.74 ≤ bias ≤ 2.75) and CLM (1.22 ≤ bias ≤ 2.53) models, whereas systematic underestimations are observed in the VIC (0.36 ≤ bias ≤ 0.85) and Mosaic (0.34 ≤ bias ≤ 0.66) models. The Noah model shows the best performance in capturing the temporal variation in monthly streamflow and the seasonal cycle of streamflow, while the VIC model performs the best in terms of bias statistics. The Mosaic model provides the best performance in modeling annual runoff trends and runoff component partitioning. The possible reasons for the different performances of the LSMs are discussed in detail. In order to achieve more accurate streamflow simulations from the LSMs in GLDAS, suggestions are made to further improve the accuracy of the forcing data and parameterization schemes in all models.

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Filtered smoothed minima baseflow separation method

Cited by 94 publications

References 29 publications

Contrasts between estimates of baseflow help discern multiple sources of water contributing to rivers

Contrasts between estimates of baseflow help discern multiple sources of water contributing to rivers

The examination of the performances of methods used in separating the total stream flow in different rivers

Evaluation of streamflow simulation results of land surface models in GLDAS on the Tibetan plateau

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