A comparison of techniques for hydrograph recession analysis

Sujono, Joko; Shikasho, Shiomi; Hiramatsu, Kazuaki

doi:10.1002/hyp.1247

Cited by 87 publications

(89 citation statements)

References 26 publications

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“…Runoff characteristics of forest catchments vary widely depending on the generations and compositions of direct runoff and baseflow [17], and so it is difficult to accurately understand these processes [11]. In other words, the point at which the direct runoff ends and where all runoff is baseflow should be carefully determined.…”

Section: Determination Of Recession Periodmentioning

confidence: 99%

“…However, these methods require lengthy analysis. The matching strip method, in particular, has a disadvantage in that it may lead to different results depending on the researcher despite using the same data because the user's subjectivity is involved in this method [10,11]. Sujono et al [11] noted that several recession constants are obtained when using the matching strip method.…”

Section: Introductionmentioning

confidence: 99%

“…The matching strip method, in particular, has a disadvantage in that it may lead to different results depending on the researcher despite using the same data because the user's subjectivity is involved in this method [10,11]. Sujono et al [11] noted that several recession constants are obtained when using the matching strip method. Negative opinions of this method have been expressed, but some researchers have simultaneously argued that more precise estimations of the recession constants can be derived from the researcher's own judgment [9,11].…”

Section: Introductionmentioning

confidence: 99%

“…Sujono et al [11] noted that several recession constants are obtained when using the matching strip method. Negative opinions of this method have been expressed, but some researchers have simultaneously argued that more precise estimations of the recession constants can be derived from the researcher's own judgment [9,11].…”

Section: Introductionmentioning

confidence: 99%

“…Simultaneously, validation tests of each method are also being studied [15]. In addition, several studies have examined the applicability of these methods [9,11]. However, most of these studies were carried out in relatively large catchments with areas that are larger than 100 ha, with few applications in small forest catchments.…”

Section: Introductionmentioning

confidence: 99%

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Applicability Assessment of Estimation Methods for Baseflow Recession Constants in Small Forest Catchments

Yang

Choi

Lim

2018

Water

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Abstract:In South Korea, since small forest catchments are located upstream of most river basins, the baseflow from these catchments is important for a clean water supply to downstream areas. Baseflow recession analysis is widely recognized as a valuable tool for estimating the baseflow component of the stream hydrograph. However, few studies have applied this tool to small forest catchments. So, this study was conducted to assess the applicability of the recession analysis methods proposed in previous studies. The data used were long-term rainfall-runoff data from 1982 to 2011 in the Gwangneung coniferous (GC) and deciduous (GD) forest catchment in Gyeonggi-do, South Korea. For the applicability assessment, six recession constant estimation methods, which were used by previous studies, were selected. The recession constants of the GC and GD catchments were calculated, and applicability assessments were conducted by comparing the recession predictions and baseflow separations. As a result, the recession constants for GC and GD were 0.8480 and 0.9235, respectively. This clear difference may be due to the different forest cover in each area. The correlation regression line, AR(1) model, and the Vogel and Kroll method showed lower error rates and appropriate baseflow indexes compared with other methods.

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Section: Determination Of Recession Periodmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Applicability Assessment of Estimation Methods for Baseflow Recession Constants in Small Forest Catchments

Yang

Choi

Lim

2018

Water

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Global patterns in base flow index and recession based on streamflow observations from 3394 catchments

et al. 2013

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[1] Numerous previous studies have constructed models to estimate base flow characteristics from climatic and physiographic characteristics of catchments and applied these to ungauged regions. However, these studies generally used streamflow observations from a relatively small number of catchments (<200) located in small, homogeneous study areas, which may have led to less reliable models with limited applicability elsewhere. Here, we use streamflow observations from a highly heterogeneous set of 3394 catchments (<10,000 km 2 ) worldwide to construct reliable, widely applicable models based on 18 climatic and physiographic characteristics to estimate two important base flow characteristics: (1) the base flow index (BFI), defined as the ratio of long-term mean base flow to total streamflow; and (2) the base flow recession constant (k), defined as the rate of base flow decay. Regression analysis results revealed that BFI and k were related to several climatic and physiographic characteristics, notably mean annual potential evaporation, mean snow water equivalent depth, and abundance of surface water bodies. Ensembles of artificial neural networks (ANNs; obtained by subsampling the original set of catchments) were trained to estimate the base flow characteristics from climatic and physiographic data. The catchment-scale estimation of the base flow characteristics demonstrated encouraging performance with R 2 values of 0.82 for BFI and 0.72 for k. The connection weights of the trained ANNs indicated that climatic characteristics were more important for estimating k than BFI. Global maps of estimated BFI and k were obtained using global climatic and physiographic data as input to the derived models. The resulting global maps are available for free download at http://www.hydrology-amsterdam.nl.

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Evaluation of the LISEM soil erosion model in two catchments in the East African Highlands

Hessel¹,

Bosch²,

Vigiak

2005

Earth Surf Processes Landf

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Under increasing population pressure, soil erosion has become a threat in the East African Highlands, and erosion modelling can be useful to quantify this threat. To test its applicability for this region, the LISEM soil erosion model was applied to two small catchments, one in the Usumbara Mountains, Tanzania, and the other on the slopes of Mount Kenya. Input data for the model were collected in both catchments, as were data on runoff and erosion that were used for calibration and validation of the model. LISEM was first calibrated on catchment outlet data, and afterwards simulated spatial patterns of erosion were compared to available erosion data. The results showed that LISEM can, after calibration, give good discharge predictions for some events, but not for all. However, LISEM generally overpredicted soil loss from the catchments. Comparison with observed erosion patterns did not show overprediction, but according to the model, erosion was more widespread than was observed. There are several reasons for these discrepancies. First, it is difficult to obtain enough accurate data to run the model, such as accurate maps, rainfall data and soil and plant characteristics. Second, it is also difficult to obtain accurate data to evaluate the performance of the model, either for the catchment outlet or spatially, therefore observed erosion rates are also uncertain. Third, the model could not deal correctly with complex events, i.e. those having double rainfall peaks, and might also have difficulties with catchment characteristics such as soil type and the complexity of land use. Finally, LISEM could not deal with events in which throughflow or baseflow played a role, which was to be expected since those processes are not simulated by LISEM. Nevertheless, LISEM could be calibrated to give good discharge predictions for some events, and also gave reasonable results when compared to data obtained from erosion plots. Furthermore, only complex, distributed, storm-based models such as LISEM can give spatial predictions for single storms. Therefore, it is concluded that if the aim is spatial prediction on an event basis, there is no alternative to complex erosion models such as LISEM, but if the aim is to predict average annual erosion, the data-demanding, physically based LISEM erosion model may not be the most appropriate model.

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A comparison of techniques for hydrograph recession analysis

Cited by 87 publications

References 26 publications

Applicability Assessment of Estimation Methods for Baseflow Recession Constants in Small Forest Catchments

Applicability Assessment of Estimation Methods for Baseflow Recession Constants in Small Forest Catchments

Global patterns in base flow index and recession based on streamflow observations from 3394 catchments

Evaluation of the LISEM soil erosion model in two catchments in the East African Highlands

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