The influence of parameter distribution uncertainty on hydrological and sediment modeling: a case study of SWAT model applied to the Daning watershed of the Three Gorges Reservoir Region, China

Shen, Zhenyao; Lei, Chen; Chen, Tao

doi:10.1007/s00477-012-0579-8

Cited by 36 publications

(19 citation statements)

References 55 publications

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“…But the way of generating new parameter ranges has its limitations. The parameter ranges are proposed to be measured or estimated according to watershed characteristics when data collection is possible (Zhenyao et al 2013). However, with the constraints of experiments, measured data are not available.…”

Section: Discussionmentioning

confidence: 99%

Investigating the uncertainty and transferability of parameters in SWAT model under climate change

Zhu

Zhang

et al. 2016

Hydrological Sciences Journal

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There is an implicit assumption in most work that the parameters calibrated based on observations remain valid for future climatic conditions. However, this might not be true due to parameter instability. This paper investigates the uncertainty and transferability of parameters in a hydrological model under climate change. Parameter transferability is investigated with three parameter sets identified for different climatic conditions, which are: wet, intermediate and dry. A parameter set based on the baseline period is also investigated for comparison. For uncertainty analysis, a k-simulation set approach is proposed instead of employing the traditional optimization method which uses a single best-fit parameter set. The results show that the parameter set from the wet sub-period performs the best when transferred into wet climate condition, while the parameter set from the baseline period is the most appropriate when transferred into dry climate condition. The largest uncertainty of simulated daily high flows for 2011-2040 is from the parameter set trained in the dry sub-period, while that of simulated daily medium and low flows lies in the parameter set from the intermediate calibration sub-period. For annual changes in the future period, the uncertainty with the parameter set from the intermediate sub-period is the largest, followed by the wet sub-period and dry sub-period. Compared with high and medium flows/runoffs, the uncertainty of low flows/runoffs is much smaller for both simulated daily flows and annual runoffs. For seasonal runoffs, the largest uncertainty is from the intermediate sub-period, while the smallest is from the dry sub-period. Apart from that, the largest uncertainty can be observed for spring runoffs and the lowest one for autumn runoffs. Compared with the traditional optimization method, the k-simulation set approach shows many more advantages, particularly being able to provide uncertainty information to decision support for watershed management under climate change. ARTICLE HISTORY

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Section: Discussionmentioning

confidence: 99%

Investigating the uncertainty and transferability of parameters in SWAT model under climate change

Zhu

Zhang

et al. 2016

Hydrological Sciences Journal

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“…Zhenyao et al . () studied the impact of parameter distribution uncertainty on hydrological modelling using SWAT and recommend use of any available knowledge of the watershed to aid selection of realistic parameter ranges to reduce prediction uncertainties. Besides the guidelines by van Griensven et al .…”

Section: Methodsmentioning

confidence: 99%

“…We focused on selection of realistic ranges of the model input parameter values in order to reduce uncertainty in the model outputs (Arnold et al, 2012). Selection of realistic ranges of SWAT input parameters prior to calibration has been shown to reduce model prediction uncertainties (Benaman and Shoemaker, 2004;Zhenyao et al, 2013). We particularly paid special attention to model parameters that govern the water 'loss' from the system e.g.…”

Section: Evaluation Of Model Performancementioning

confidence: 99%

“…Knowledge of the watershed is important in hydrologic modelling as there is no automatic procedure of parameterization and calibration which can substitute for actual physical knowledge (Arnold et al, 2012). Zhenyao et al (2013) studied the impact of parameter distribution uncertainty on hydrological modelling using SWAT and recommend use of any available knowledge of the watershed to aid selection of realistic parameter ranges to reduce prediction uncertainties. Besides the guidelines by van Griensven et al (2012), we used our watershed knowledge as well as knowledge from our past experience of SWAT application in the region (e.g.…”

Section: Evaluation Of Model Performancementioning

confidence: 99%

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Modelling the impact of agroforestry on hydrology of Mara River Basin in East Africa

Mwangi

Jülich

Patil

et al. 2016

Hydrological Processes

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Land‐use change is one of the main drivers of watershed hydrology change. The effect of forestry related land‐use changes (e.g. afforestation, deforestation, agroforestry) on water fluxes depends on climate, watershed characteristics and spatial scale. The Soil and Water Assessment Tool (SWAT) model was calibrated, validated and used to simulate the impact of agroforestry on the water balance in the Mara River Basin (MRB) in East Africa. Model performance was assessed by Nash–Sutcliffe Efficiency (NSE) and Kling–Gupta Efficiency (KGE). The NSE (and KGE) values for calibration and validation were: 0.77 (0.88) and 0.74 (0.85) for the Nyangores sub‐watershed, and 0.78 (0.89) and 0.79 (0.63) for the entire MRB. It was found that agroforestry in the watershed would generally reduce surface runoff, mainly because of enhanced infiltration. However, it would also increase evapotranspiration and consequently reduce baseflow and overall water yield, which was attributed to increased water use by trees. Spatial scale was found to have a significant effect on water balance; the impact of agroforestry was higher at the smaller headwater catchment (Nyangores) than for the larger watershed (entire MRB). However, the rate of change in water yield with an increase in area under agroforestry was different for the two and could be attributed to the spatial variability of climate within the MRB. Our results suggest that direct extrapolation of the findings from a small sub‐catchment to a larger watershed may not always be accurate. These findings could guide watershed managers on the level of trade‐offs that might occur between reduced water yields and other benefits (e.g. soil erosion control, improved soil productivity) offered by agroforestry. Copyright © 2016 John Wiley & Sons, Ltd.

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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%

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 influence of parameter distribution uncertainty on hydrological and sediment modeling: a case study of SWAT model applied to the Daning watershed of the Three Gorges Reservoir Region, China

Cited by 36 publications

References 55 publications

Investigating the uncertainty and transferability of parameters in SWAT model under climate change

Investigating the uncertainty and transferability of parameters in SWAT model under climate change

Modelling the impact of agroforestry on hydrology of Mara River Basin in East Africa

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

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