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A comparison of single- and multi-site calibration and validation: a case study of SWAT in the Miyun Reservoir watershed, China

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Abstract

An essential task in evaluating global water resource and pollution problems is to obtain the optimum set of parameters in hydrological models through calibration and validation. For a large-scale watershed, single-site calibration and validation may ignore spatial heterogeneity and may not meet the needs of the entire watershed. The goal of this study is to apply a multi-site calibration and validation of the Soil andWater Assessment Tool (SWAT), using the observed flow data at three monitoring sites within the Baihe watershed of the Miyun Reservoir watershed, China. Our results indicate that the multi-site calibration parameter values are more reasonable than those obtained from single-site calibrations. These results are mainly due to significant differences in the topographic factors over the large-scale area, human activities and climate variability. The multi-site method involves the division of the large watershed into smaller watersheds, and applying the calibrated parameters of the multi-site calibration to the entire watershed. It was anticipated that this case study could provide experience of multi-site calibration in a large-scale basin, and provide a good foundation for the simulation of other pollutants in followup work in the Miyun Reservoir watershed and other similar large areas.

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References

  • Abbaspour K C (2011). SWAT-CUP4: SWAT Calibration and Uncertainty Programs–A User Manual. Department of Systems Analysis, Integrated Assessment and Modelling (SIAM), Eawag, Swiss Federal Institute of Aquatic Science and Technology, CH, Switzerland

    Google Scholar 

  • Anderton S, Latron J, Gallart F (2002). Sensitivity analysis and multiresponse, multi-criteria evaluation of a physical based distributed model. Hydrol Processes, 16(2): 333–353

    Article  Google Scholar 

  • Arnold J G, Srinivasan R, Muttiah R S, Williams J R (1998). Large area hydrologic modeling and assessment: part I. Model development. J Am Water Resour Assoc, 34(1): 73–89

    Article  Google Scholar 

  • Bai J, Shen Z, Yan T (2016). Effectiveness of vegetative filter strips in abating fecal coliform based on modified soil and water assessment tool. Int J Environ Sci Technol, 13(7): 1723–1730

    Article  Google Scholar 

  • Bao Z, Fu G, Wang G, Jin J, He R, Yan X, Liu C (2012). Hydrological projection for the Miyun Reservoir basin with the impact of climate change and human activity. Quat Int, 282: 96–103

    Article  Google Scholar 

  • Bekele E G, Nicklow J W (2007). Multi-objective automatic calibration of SWAT using NSGA-II. J Hydrol (Amst), 341(3–4): 165–176

    Article  Google Scholar 

  • Cao W, Bowden W B, Davie T, Fenemor A (2006). Multi-variable and multi-site calibration and validation of SWAT in a large mountainous catchment with high spatial variability. Hydrol Processes, 20(5): 1057–1073

    Article  Google Scholar 

  • Cho K H, Pachepsky Y A, Kim J H, Kim J W, Park M H (2012). The modified SWAT model for predicting fecal coliforms in the Wachusett Reservoir Watershed, USA. Water Res, 46(15): 4750–4760

    Article  Google Scholar 

  • Duan Q, Sorooshian S, Gupta V K (1992). Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resour Res, 28(4): 1015–1031

    Article  Google Scholar 

  • Frey S K, Topp E, Edge T, Fall C, Gannon V, Jokinen C, Marti R, Neumann N, Ruecker N, Wilkes G, Lapen D R (2013). Using SWAT, bacteroidales microbial source tracking markers, and fecal indicator bacteria to predict waterborne pathogen occurrence in an agricultural watershed. Water Res, 47(16): 6326–6337

    Article  Google Scholar 

  • Gong Y W, Shen Z Y, Hong Q, Liu R M, Liao Q (2011). Parameter uncertainty analysis in watershed total phosphorus modeling using the GLUE approach. Agric Ecosyst Environ, 142(3–4): 246–255

    Article  Google Scholar 

  • Gong Y W, Shen Z Y, Liu R M, Hong Q, Wu X (2012). A comparison of single- and multi-gauge based calibrations for hydrological modeling of the Upper DaningheWatershed in China’s Three Gorges Reservoir Region. Hydrol Res, 43(6): 822–832

    Article  Google Scholar 

  • Li Z J, Li X B (2008). Impacts of precipitation changes and human activities on annual runoff of Chaohe Basin during past 45 years. Sci Geogr Sin, 28(6): 809–813 (in Chinese)

    Google Scholar 

  • Liu R, Zhang P, Wang X, Chen Y, Shen Z (2013). Assessment of effects of best management practices on agricultural non-point source pollution in Xiangxihe watershed. Agric Water Manage, 117: 9–18

    Article  Google Scholar 

  • Ma H, Yang D, Tan S K, Gao B, Hu Q (2010). Impact of climate variability and human activity on streamflow decrease in Miyun Reservoir catchment. J Hydrol (Amst), 389(3–4): 317–324

    Article  Google Scholar 

  • Méndez M, Araya J A, Sánchez L D (2013). Automated parameter optimization of a water distribution system. J Hydroinform, 15(1): 71–85

    Article  Google Scholar 

  • Moriasi D N, Arnold J G, Van Liew M W, Bingner R L, Harmel R D, Veith T L (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASAE, 50(3): 885–900

    Article  Google Scholar 

  • Nash J, Sutcliffe J (1970). River flow forecasting through conceptual models part I—A discussion of principles. J Hydrol, 10: 282–290

    Article  Google Scholar 

  • Parajuli P B, Mankin K R, Barnes L P (2009). Source specific fecal bacteria modeling using soil and water assessment tool model. Bioresour Technol, 100(2): 953–963

    Article  Google Scholar 

  • Parajuli P B, Mankin K R, Barnes P L (2008). Applicability of targeting vegetative filter strips to abate fecal bacteria and sediment yield using SWAT. Agric Water Manage, 95(10): 1189–1200

    Article  Google Scholar 

  • Rasolomanana S D, Lessard P, Vanrolleghem P A (2012). Singleobjective vs. multi-objective autocalibration in modelling total suspended solids and phosphorus in a small agricultural watershed with SWAT. Water Sci Technol, 65(4): 643–652

    Article  Google Scholar 

  • Shen Z, Chen L, Chen T (2013). 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. Stochcastic Environmental Research and Risk Assessment, 27(1): 235–251

    Article  Google Scholar 

  • Shen Z Y, Chen L, Chen T (2012). Analysis of parameter uncertainty in hydrological and sediment modeling using GLUE method: a case study of SWAT model applied to Three Gorges Reservoir Region, China. Hydrol Earth Syst Sci, 16(1): 121–132

    Article  Google Scholar 

  • Wang G, Xia J, Chen J (2009). Quantification of effects of climate variations and human activities on runoff by a monthly water balance model: a case study of the Chaobaihe basin in northern China. Water Resour Res, 45(7): 206–216

    Google Scholar 

  • Wang G S, Xia J, Wan D H, Ye Z A (2006). A Distributed monthly water balance model for identifying hydrological response to climate changes and human activities. J Nat Res, 21(1): 86–91 (in Chinese)

    Google Scholar 

  • Wang S, Zhang Z, Sun G, Strauss P, Guo J, Tang Y, Yao A (2012). Multi-site calibration, validation, and sensitivity analysis of the MIKE SHE Model for a large watershed in northern China. Hydrol Earth Syst Sci, 16(12): 4621–4632

    Article  Google Scholar 

  • Wang X Y, Qin F L, Ou Y, Xue Y F (2008). SWAT-based simulation on non- point source pollution in the northern watershed of Miyun Reservoir. J Agro-Environ Sci, 27(3): 1098–1105 (in Chinese)

    Google Scholar 

  • Xu Z X, Pang J P, Liu C M, Li J Y (2009). Assessment of runoff and sediment yield in the Miyun Reservoir catchment by using SWAT model. Hydrol Processes, 23(25): 3619–3630

    Article  Google Scholar 

  • Yang J, Reichert P, Abbaspour K C, Xia J, Yang H (2008). Comparing uncertainty analysis techniques for a SWATapplication to the Chaohe Basin in China. J Hydrol (Amst), 358(1–2): 1–23

    Article  Google Scholar 

  • Zhang X, Beeson P, Link R, Manowitz D, Izaurralde R C, Sadeghi A, Thomson A M, Sahajpal R, Srinivasan R, Arnold J G (2013). Efficient multi-objective calibration of a computationally intensive hydrologic model with parallel computing software in Python. Environ Model Softw, 46: 208–218

    Article  Google Scholar 

  • Zhang X, Srinivasan R, Bosch D (2009). Calibration and uncertainty analysis of the SWAT model using Genetic Algorithms and Bayesian Model Averaging. J Hydrol (Amst), 374(3–4): 307–317

    Article  Google Scholar 

  • Zhang X, Srinivasan R, Van Liew M (2008). Multi-site calibration of the SWAT model for hydrologic modeling. Trans ASABE, 51(6): 2039–2049

    Article  Google Scholar 

  • Zhao Y, Yu X, Zheng J, Wu Q (2012). Quantitative effects of climate variations and land-use changes on annual streamflow in Chaobai river basin. Transactions of the Chinese Society of Agricultural Engineering, 28(22): 252–260 (in Chinese)

    Google Scholar 

Download references

Acknowledgements

The research was funded by National Natural Science Foundation of China (Grant No. 51579011), National Science Foundation for Innovative Research Group (No. 51421065) and State Key Program of National Natural Science of China (Grant No. 41530635).

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Correspondence to Zhenyao Shen.

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Bai, J., Shen, Z. & Yan, T. A comparison of single- and multi-site calibration and validation: a case study of SWAT in the Miyun Reservoir watershed, China. Front. Earth Sci. 11, 592–600 (2017). https://doi.org/10.1007/s11707-017-0656-x

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