Assessment of the different sources of uncertainty in a SWAT model of the River Senne (Belgium)

Leta, Olkeba Tolessa; Nossent, Jiri; Vélez, C.A.; Shrestha, Narayan Kumar; Griensven, Ann van; Bauwens, Willy

doi:10.1016/j.envsoft.2015.02.010

Cited by 73 publications

(51 citation statements)

References 64 publications

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“…The SWAT model as developed by Leta (Leta, 2013;Leta et al, 2015) for the River Zenne (Belgium) is used in this study.…”

Section: Software /Data Availabilitymentioning

confidence: 99%

“…Even when some of these parameters can be fixed a priori, calibration of SWAT remains quite challenging given the relatively large number of parameters (26 in our case) that are typically left to be varied simultaneously. Therefore, GSA is often applied prior to the calibration process to identify the most influential parameters and the non-influential ones (Cibin et al, 2010;Nossent et al, 2011;Leta et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Comparison of variance-based and moment-independent global sensitivity analysis approaches by application to the SWAT model

Zadeh

Nossent

Sarrazin

et al. 2017

Environmental Modelling & Software

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116

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Link to publication record in Explore Bristol Research PDF-document This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Elsevier at http://www.sciencedirect.com/science/article/pii/S1364815217301159. Please refer to any applicable terms of use of the publisher. University of Bristol -Explore Bristol Research General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms AbstractGlobal Sensitivity Analysis (GSA) is an essential technique to support the calibration of environmental models by identifying the influential parameters (screening) and ranking them.In this paper, the widely-used variance-based method (Sobol') and the recently proposed moment-independent PAWN method for GSA are applied to the Soil and Water Assessment Tool (SWAT), and compared in terms of ranking and screening results of 26 SWAT parameters. In order to set a threshold for parameter screening, we propose the use of a "dummy parameter", which has no influence on the model output. The sensitivity index of the dummy parameter is calculated from sampled data, without changing the model equations. We find that Sobol' and PAWN identify the same 12 influential parameters but rank them differently, and discuss how this result may be related to the limitations of the Sobol' method when the output distribution is asymmetric.

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“…The SWAT model as developed by Leta (Leta, 2013;Leta et al, 2015) for the River Zenne (Belgium) is used in this study.…”

Section: Software /Data Availabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison of variance-based and moment-independent global sensitivity analysis approaches by application to the SWAT model

Zadeh

Nossent

Sarrazin

et al. 2017

Environmental Modelling & Software

Self Cite

116

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“…Parameterization is a critical part of any modeling analysis and has received considerable attention in the literature (Abbaspour et al, 2004;Romanowicz et al, 2005;Sexton et al, 2011;Zhenyao et al, 2013;Migliaccio and Chaubey, 2008;Cibin et al, 2010;Gitau and Chaubey, 2010;Du et al, 2013;Malone et al, 2015;Zhang et al, 2016). In this analysis, we investigated two parameterization designs:…”

Section: Parameterizationmentioning

confidence: 99%

“…It builds on the 12 parameters of the reduced parameterization by adding unique multiplier parameters on the HRU scale for each of the 12 parameters in Table 1, and also includes many other model inputs that are not typically adjusted, although they are still uncertain, such as soil properties, and inputs that govern the simulation of plant growth, such as leaf area index (LAI) variables. The full parameterization also includes annual quartile precipitation multipliers to account for uncertainty and potential bias in precipitation estimates (Leta et al, 2015;Renard et al, 2011;Kavetski et al, 2006;Kuczera et al, 2006). See Table S1 of the Supplement for a summary of the full parameterization and the associated data release (White et al, 2017) for a complete description of the full parameterization.…”

Section: Parameterizationmentioning

confidence: 99%

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

White

Stengel

Rendon

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. Computer models of hydrologic systems are frequently used to investigate the hydrologic response of landcover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of landcover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km 2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as "behavioral" in that they reproduce daily mean streamflow acceptably well according to NashSutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.

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“…The SWAT (Soil and Water Assessment Tool) Model is a process-based distributed parameter model applied to simulate long-term hydrological process in different scale basins [38][39][40]. In the SWAT model, a watershed is divided into sub-basins and further into a series of uniform hydrological response units (HRUs) as the combination of single land use, soil and the management.…”

Section: Swat Model and Swat Cupmentioning

confidence: 99%

Impact of Land Use on Frequency of Floods in Yongding River Basin, China

Zhang

Zhao

Wang

et al. 2016

Water

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Abstract:As the debates surrounding the negative influences of flood control using dams or reservoirs on the eco-environment become fierce, non-structural flood control measures like land use change gain more attention. This study researched the effect of integrated and single land use changes on three floods at small, medium and large scales, respectively, in Yongding River basin. A SWAT (Soil and Water Assessment Tool) model was used to simulate the effect of integrated and single land use changes on floods of different scales. The single land uses were set as S1, S2, S3 to represent the agricultural, grass and construction land changes. The results showed that: (1) the integrated land use changes reduced the small flood, the medium flood and the large flood by 14%, 13% and 5%; (2) the land use management functioned most effectively on medium-scale floods and least effectively on large-scale floods; (3) S1 decreased the medium floods optimally by 24% with a 7-day maximum runoff volume as the indicator and by 29% with a 1-day maximum flood discharge; (4) S2 reduced the medium floods optimally by 21% with runoff depth volume as the indicator; (5) S3 increased the medium floods optimally by 15% with a 1-day maximum flood discharge as the indicator.

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Assessment of the different sources of uncertainty in a SWAT model of the River Senne (Belgium)

Cited by 73 publications

References 64 publications

Comparison of variance-based and moment-independent global sensitivity analysis approaches by application to the SWAT model

Comparison of variance-based and moment-independent global sensitivity analysis approaches by application to the SWAT model

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

Impact of Land Use on Frequency of Floods in Yongding River Basin, China

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