IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0112725.html
   My bibliography  Save this article

Evaluation of Gridded Precipitation Data for Driving SWAT Model in Area Upstream of Three Gorges Reservoir

Author

Listed:
  • Yan Yang
  • Guoqiang Wang
  • Lijing Wang
  • Jingshan Yu
  • Zongxue Xu

Abstract

Gridded precipitation data are becoming an important source for driving hydrologic models to achieve stable and valid simulation results in different regions. Thus, evaluating different sources of precipitation data is important for improving the applicability of gridded data. In this study, we used three gridded rainfall datasets: 1) National Centers for Environmental Prediction - Climate Forecast System Reanalysis (NCEP-CFSR); 2) Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE); and 3) China trend - surface reanalysis (trend surface) data. These are compared with monitoring precipitation data for driving the Soil and Water Assessment Tool in two basins upstream of Three Gorges Reservoir (TGR) in China. The results of one test basin with significant topographic influence indicates that all the gridded data have poor abilities in reproducing hydrologic processes with the topographic influence on precipitation quantity and distribution. However, in a relatively flat test basin, the APHRODITE and trend surface data can give stable and desirable results. The results of this study suggest that precipitation data for future applications should be considered comprehensively in the TGR area, including the influence of data density and topography.

Suggested Citation

  • Yan Yang & Guoqiang Wang & Lijing Wang & Jingshan Yu & Zongxue Xu, 2014. "Evaluation of Gridded Precipitation Data for Driving SWAT Model in Area Upstream of Three Gorges Reservoir," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-15, November.
    • Handle: RePEc:plo:pone00:0112725
    DOI: 10.1371/journal.pone.0112725
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0112725
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0112725&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0112725?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Shen, Z.Y. & Gong, Y.W. & Li, Y.H. & Hong, Q. & Xu, L. & Liu, R.M., 2009. "A comparison of WEPP and SWAT for modeling soil erosion of the Zhangjiachong Watershed in the Three Gorges Reservoir Area," Agricultural Water Management, Elsevier, vol. 96(10), pages 1435-1442, October.
    2. Ronald L. Iman & Jon C. Helton, 1988. "An Investigation of Uncertainty and Sensitivity Analysis Techniques for Computer Models," Risk Analysis, John Wiley & Sons, vol. 8(1), pages 71-90, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fida Ali & Chatchawin Srisuwan & Kuaanan Techato & Adul Bennui & Tanita Suepa & Damrongrit Niammuad, 2020. "Theoretical Hydrokinetic Power Potential Assessment of the U-Tapao River Basin Using GIS," Energies, MDPI, vol. 13(7), pages 1-13, April.
    2. Vinit Sehgal & Venkataramana Sridhar & Luke Juran & Jactone Arogo Ogejo, 2018. "Integrating Climate Forecasts with the Soil and Water Assessment Tool (SWAT) for High-Resolution Hydrologic Simulations and Forecasts in the Southeastern U.S," Sustainability, MDPI, vol. 10(9), pages 1-27, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. S. Cucurachi & E. Borgonovo & R. Heijungs, 2016. "A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 357-377, February.
    2. Bruno Gianmarco Carra & Giuseppe Bombino & Manuel Esteban Lucas-Borja & Pietro Denisi & Pedro Antonio Plaza-Álvarez & Demetrio Antonio Zema, 2021. "Modelling the Event-Based Hydrological Response of Mediterranean Forests to Prescribed Fire and Soil Mulching with Fern Using the Curve Number, Horton and USLE-Family (Universal Soil Loss Equation) Mo," Land, MDPI, vol. 10(11), pages 1-31, October.
    3. Shifa Chen & Xuan Zha, 2016. "Evaluation of soil erosion vulnerability in the Zhuxi watershed, Fujian Province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(3), pages 1589-1607, July.
    4. Lee, Sang-Hee & Park, Cheol-Min, 2022. "The effect of hunter-wild boar interactions and landscape heterogeneity on wild boar population size: A simulation study," Ecological Modelling, Elsevier, vol. 464(C).
    5. Shabbir Ahmed Osmani & Foysol Mahmud, 2021. "An integrated approach of machine algorithms with multi-objective optimization in performance analysis of event detection," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(2), pages 1976-1993, February.
    6. Emanuele Borgonovo & Gordon B. Hazen & Elmar Plischke, 2016. "A Common Rationale for Global Sensitivity Measures and Their Estimation," Risk Analysis, John Wiley & Sons, vol. 36(10), pages 1871-1895, October.
    7. Nicolas A. Menzies & Brian W. Allwood & Anna S. Dean & Pete J. Dodd & Rein M. G. J. Houben & Lyndon P. James & Gwenan M. Knight & Jamilah Meghji & Linh N. Nguyen & Andrea Rachow & Samuel G. Schumacher, 2023. "Global burden of disease due to rifampicin-resistant tuberculosis: a mathematical modeling analysis," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    8. Paschalis Koutalakis & Georgios Gkiatas & Michael Xinogalos & Valasia Iakovoglou & Iordanis Kasapidis & Georgios Pagonis & Anastasia Savvopoulou & Konstantinos Krikopoulos & Theodoros Klepousniotis & , 2024. "Estimating Stream Bank and Bed Erosion and Deposition with Innovative and Traditional Methods," Land, MDPI, vol. 13(2), pages 1-29, February.
    9. Alan H. Stern, 1993. "Re‐evaluation of the Reference Dose for Methylmercury and Assessment of Current Exposure Levels," Risk Analysis, John Wiley & Sons, vol. 13(3), pages 355-364, June.
    10. Wout Slob, 1994. "Uncertainty Analysis in Multiplicative Models," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 571-576, August.
    11. James K. Hammitt, 1990. "Subjective‐Probability‐Based Scenarios for Uncertain Input Parameters: Stratospheric Ozone Depletion," Risk Analysis, John Wiley & Sons, vol. 10(1), pages 93-102, March.
    12. Yizhen Wang & Menglei Cui & Jiong Guo & Han Zhang & Yingjie Wu & Fu Li, 2023. "Decay Branch Ratio Sampling Method with Dirichlet Distribution," Energies, MDPI, vol. 16(4), pages 1-17, February.
    13. Gorka Merino & Hilario Murua & Josu Santiago & Haritz Arrizabalaga & Victor Restrepo, 2020. "Characterization, Communication, and Management of Uncertainty in Tuna Fisheries," Sustainability, MDPI, vol. 12(19), pages 1-22, October.
    14. Messan, Komi & Rodriguez Messan, Marisabel & Chen, Jun & DeGrandi-Hoffman, Gloria & Kang, Yun, 2021. "Population dynamics of Varroa mite and honeybee: Effects of parasitism with age structure and seasonality," Ecological Modelling, Elsevier, vol. 440(C).
    15. Ronald L. Iman & Mark E. Johnson & Charles C. Watson, 2005. "Uncertainty Analysis for Computer Model Projections of Hurricane Losses," Risk Analysis, John Wiley & Sons, vol. 25(5), pages 1299-1312, October.
    16. M. Kadohira & M. A. Stevenson & H. R. Høgåsen & A. de Koeijer, 2012. "A Quantitative Risk Assessment for Bovine Spongiform Encephalopathy in Japan," Risk Analysis, John Wiley & Sons, vol. 32(12), pages 2198-2208, December.
    17. Liu, Zicheng & Lesselier, Dominique & Sudret, Bruno & Wiart, Joe, 2020. "Surrogate modeling based on resampled polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    18. John H. Miller, 1996. "Active Nonlinear Tests (ANTs) of Complex Simulation Models," Working Papers 96-03-011, Santa Fe Institute.
    19. Pang, Zhihong & O'Neill, Zheng, 2018. "Uncertainty quantification and sensitivity analysis of the domestic hot water usage in hotels," Applied Energy, Elsevier, vol. 232(C), pages 424-442.
    20. Victor R. Vasquez & Wallace B. Whiting, 2005. "Accounting for Both Random Errors and Systematic Errors in Uncertainty Propagation Analysis of Computer Models Involving Experimental Measurements with Monte Carlo Methods," Risk Analysis, John Wiley & Sons, vol. 25(6), pages 1669-1681, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0112725. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.