Comparison of daily and sub-daily SWAT models for daily streamflow simulation in the Upper Huai River Basin of China

Abstract

Despite the significant role of precipitation in the hydrological cycle, few studies have been conducted to evaluate the impacts of the temporal resolution of rainfall inputs on the performance of SWAT (soil and water assessment tool) models in large-sized river basins. In this study, both daily and hourly rainfall observations at 28 rainfall stations were used as inputs to SWAT for daily streamflow simulation in the Upper Huai River Basin. Study results have demonstrated that the SWAT model with hourly rainfall inputs performed better than the model with daily rainfall inputs in daily streamflow simulation, primarily due to its better capability of simulating peak flows during the flood season. The sub-daily SWAT model estimated that 58 % of streamflow was contributed by baseflow compared to 34 % estimated by the daily model. Using the future daily and 3-h precipitation projections under the RCP (Representative Concentration Pathways) 4.5 scenario as inputs, the sub-daily SWAT model predicted a larger amount of monthly maximum daily flow during the wet years than the daily model. The differences between the daily and sub-daily SWAT model simulation results indicated that temporal rainfall resolution could have much impact on the simulation of hydrological process, streamflow, and consequently pollutant transport by SWAT models. There is an imperative need for more studies to examine the effects of temporal rainfall resolution on the simulation of hydrological and water pollutant transport processes by SWAT in river basins of different environmental conditions.

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References

  1. Abbaspour KC (2011) SWAT-CUP4: SWAT calibration and uncertainty programs—a user manual. Swiss Federal Institute of Aquatic Science and Technology, Eawag

    Google Scholar 

  2. Abbaspour KC, Johnson CA, van Genuchten MT (2004) Estimating uncertain flow and transport parameters using a sequential uncertainty fitting procedure. Vadose Zone J 3:1340–1352

    Article  Google Scholar 

  3. Akhavan S, Abedi-Koupai J, Mousavi S-F, Afyuni M, Eslamian S-S, Abbaspour KC (2010) Application of SWAT model to investigate nitrate leaching in Hamadan-Bahar watershed, Iran. Agri Ecosys Environ 139:675–688

    Article  CAS  Google Scholar 

  4. Arnold JG, Allen PM (1999) Automated methods for estimating baseflow and ground water recharge from streamflow records. J Am Water Resour Assoc 35(2):411–424

    Article  Google Scholar 

  5. Arnold JG, Moriasi DN, Gassman PW, Abbaspour KC, White MJ, Srinivasan R, Santhi C, Harmel RD, Griensven Av, Liew MWV, Kannan N, Jha MK (2014) SWAT: model use, calibration, and validation. Trans ASABE 55(4):1491–1508

    Article  Google Scholar 

  6. Bekele EG, Knapp HV (2010) Watershed modeling to assessing impacts of potential climate change on water supply availability. Water Resour Manag 24(13):3299–3320

    Article  Google Scholar 

  7. Cerro I, Antiguedad I, Srinavasan R, Sauvage S, Volk M, Sanchez-Perez JM (2014) Simulating land management options to reduce nitrate pollution in an agricultural watershed dominated by an alluvial aquifer. J Environ Qual 43(1):67–74

    Article  Google Scholar 

  8. Davies TM, Cullen JP, Malcolm AJ, Mawson MH, Staniforth A, White AA, Wood N (2005) A new dynamical core for the met office’s global and regional modeling of the atmosphere. Quart J Roy Meteor Soc 131:1759–1782

    Article  Google Scholar 

  9. Dessu SB, Melesse AM (2013) Impact and uncertainties of climate change on the hydrology of the Mara river basin, Kenya/Tanzania. Hydrol Process 27(20):2973–2986

    Google Scholar 

  10. Du H, Xia J, Zeng S, She D, Liu J (2014) Variations and statistical probability characteristic analysis of extreme precipitation events under climate change in Haihe River Basin, China. Hydrol Process 28:913–925

    Article  Google Scholar 

  11. Duan K, Mei Y (2014) Comparison of meteorological, hydrological and agricultural drought responses to climate change and uncertainty assessment. Water Resour Manag 28:5039–5054

    Article  Google Scholar 

  12. Fohrer N, Dietrich A, Kolychalow O, Ulrich U (2014) Assessment of the environmental fate of the herbicides flufenacet and metazachlor with the SWAT model. J Environ Qual 43(1):75–85

    Article  Google Scholar 

  13. Gao C, Zhang Z, Chen S, Liu Q (2014) The high-resolution simulation of climate change model under RCP4.5 scenarios in the Huaihe River Basin. Geogr Res 33(3):467–477 (Chinese)

    Google Scholar 

  14. Gassman PW, Reyes MR, Green CH, Arnold JG (2007) The soil and water assessment tool: historical development, applications, and future research directions. Trans ASABE 50(4):1211–1250

    Article  CAS  Google Scholar 

  15. Gassman PW, Sadeghi AM, Srinivasan R (2014) Applications of the SWAT model special section: overview and insights. J Environ Qual 43:1–8

    Article  CAS  Google Scholar 

  16. Geza M, McCray JE (2008) Effects of soil data resolution on SWAT model stream flow and water quality predictions. J Environ Manag 88(3):393–406

    Article  CAS  Google Scholar 

  17. Glavan M, White S, Holman IP (2011) Evaluation of river water quality simulations at a daily time step—experience with swat in the Axe catchment, UK. Clean-Soil Air Water 39(1):43–54

    Article  CAS  Google Scholar 

  18. Gong YW, Shen ZY, Liu RM, Hong Q, Wu X (2012) A comparison of single- and multi-gauge based calibrations for hydrological modeling of the Upper Daning River watershed in China’s three gorges reservoir region. Hydrol Res 43(6):822–832

    Article  Google Scholar 

  19. Henan Province Soil Survey Office (1995) Atlas of the soils in Henan Province. Chinese Agriculture Press, Beijing

    Google Scholar 

  20. Hu Y, Liu Y, Tang H, Xu Y, Pan J (2014) Contribution of drought to potential crop yield reduction in a wheat-maize rotation region in the North China Plain. J Integr Agr 13(7):1509–1519

    Article  Google Scholar 

  21. Jeong J, Kannan N, Arnold JG, Glick R, Gosselink L, Srinivasan R, Harmel RD (2011) Development of sub-daily erosion and sediment transport algorithms for SWAT. Trans ASABE 54(5):1685–1691

    Article  Google Scholar 

  22. Jha MK, Gassman PW (2014) Changes in hydrology and streamflow as predicted by a modelling experiment forced with climate models. Hydrol Process 28(5):2772–2781

    Article  Google Scholar 

  23. Kannan N, White SM, Worrall F, Whelan MJ (2007) Sensitivity analysis and identification of the best evapotranspiration and runoff options for hydrological modelling in SWAT-2000. J Hydrol 332(3–4):456–466

    Article  Google Scholar 

  24. Krause P, Boyle DP, Base F (2005) Comparison of different efficiency criteria for hydrological model assessment. Adv Geosci 5:89–97

    Article  Google Scholar 

  25. Li FP, Xu ZX, Liu WF, Zhang YQ (2014) The impact of climate change on runoff in the Yarlung Tsangpo River basin in the Tibetan plateau. Stoch Environ Res Risk Assess 28(3):517–526

    Article  Google Scholar 

  26. Lu GH, Xiao H, Wu ZY, Zhang SL, Li Y (2013) Assessing the Impacts of future climate change on hydrology in Huang-Huai-Hai Region in China using the PRECIS and VIC Models. J Hydrol Eng 18:1077–1087

    Article  Google Scholar 

  27. Lv M, Hu T, Dan L (2014) Daily streamflow simulation in a small-scale farmland catchment using modified SWAT model. Trans ASABE 57(1):31–41

    Google Scholar 

  28. Maharjan GR, Park YS, Kim NW, Shin DS, Choi JW, Hyun GW, Jeon J-H, Ok YS, Lim KJ (2013) Evaluation of SWAT sub-daily runoff estimation at small agricultural watershed in Korea. Front Environ Sci Eng 7(1):109–119

    Article  Google Scholar 

  29. Martin GM, Ringer MA, Pope VD, Jones A, Dearden C, Hinton TJ (2006) The physical properties of the atmosphere in the new hadley centre global environmental model (HADGEM1). Part I: model description and global climatology. J Clim 19:1274–1302

    Article  Google Scholar 

  30. Masih I, Maskey S, Uhlenbrook S, Smakhtin V (2011) Assessing the impact of areal precipitation input on streamflow simulations using the SWAT model. J Am Water Resour Assoc 47:179–195

    Article  Google Scholar 

  31. Mishra A, Kar S (2012) Modeling hydrologic processes and nps pollution in a small watershed in subhumid subtropics using SWAT. J Hydrol Eng 17(3):445–454

    Article  Google Scholar 

  32. Moriasi DN, Starks PJ (2010) Effects of the resolution of soil dataset and precipitation dataset on SWAT2005 streamflow calibration parameters and simulation accuracy. J Soil Water Conserv 65(2):63–78

    Article  Google Scholar 

  33. Oeurng C, Sauvage S, Sanchez-Perez JM (2011) Assessment of hydrology, sediment and particulate organic carbon yield in a large agricultural catchment using the SWAT model. J Hydrol 401(3–4):145–153

    Article  CAS  Google Scholar 

  34. Oliver CW, Radcliffe DE, Risse LM, Habteselassie M, Mukundan R, Jeong J, Hoghooghi N (2014) Quantifying the contribution of on-site wastewater treatment systems to stream discharge using the SWAT model. J Environ Qual 43(2):539–548

    Article  CAS  Google Scholar 

  35. Paschalis A, Fatichi S, Molnar P, Rimkus S, Burlando P (2014) On the effects of small scale space-time variability of rainfall on basin flood response. J Hydrol 514:313–327

    Article  Google Scholar 

  36. Praskievicz S, Bartlein P (2014) Hydrologic modeling using elevationally adjusted NARR and NARCCAP regional climate-model simulations: Tucannon River, Washington. J Hydrol 517:803–814

    Article  Google Scholar 

  37. Prescott JA (1940) Evaporation from water surface in relation to solar radiation. Trans R Soc S Aust 40:114–118

    Google Scholar 

  38. Rouhani H, Willems P, Wyseure G, Feyen J (2007) Parameter estimation in semi-distributed hydrological catchment modelling using a multi-criteria objective function. Hydrol Process 21(22):2998–3008

    Article  Google Scholar 

  39. Saha PP, Zeleke K, Hafeez M (2014) Streamflow modeling in a fluctuant climate using SWAT: Yass river catchment in Southeastern Australia. Environ Earth Sci 71(12):5241–5254

    Article  Google Scholar 

  40. Saxton KE, Willey PH (2005) The SPAW model for agricultural field and pond hydrologic simulation. In: Singh VP, Frevert D (eds) Mathematical modeling of watershed hydrology. CRC Press LLC, USA

    Google Scholar 

  41. Shi P, Ma XX, Hou YB, Li QF, Zhang ZC, Qu SM, Chen C, Cai T, Fang XQ (2013) Effects of land-use and climate change on hydrological processes in the upstream of Huai River. China. Water Resour Manag 27(5):1263–1278

    Article  Google Scholar 

  42. Shi XZ, Yu DS, Warner ED, Pan XZ, Petersen GW, Gong ZG, Weindorf DC (2004) Soil database of 1:1,000,000 digital soil survey and reference system of the Chinese genetic soil classification system. Soil Survey Horizons 45(4):129–136

    Article  Google Scholar 

  43. Shi XZ, Yu DS, Xu SX, Warner ED, Wang HJ, Sun WX, Zhao YC, Gong ZT (2010) Cross-reference for relating genetic soil classification of china with WRB at different scales. Geoderma 155(3–4):344–350

    Article  Google Scholar 

  44. Wagner PD, Fiener P, Wilken F, Kumar S, Schneider K (2012) Comparison and evaluation of spatial interpolation schemes for daily rainfall in data scarce regions. J Hydrol 464:388–400

    Article  Google Scholar 

  45. Wang G, Xia J (2010) Improvement of swat2000 modelling to assess the impact of dams and sluices on streamflow in the huai river basin of China. Hydrol Process 24:1455–1471

    Article  Google Scholar 

  46. Wang HL, Wu ZN, Hu CH (2015) A comprehensive study of the effect of input data on hydrology and non-point source pollution modeling. Water Resour Manag 29:1505–1521

    Article  Google Scholar 

  47. Wu H, Chen B (2015) Evaluating uncertainty estimates in distributed hydrological modeling for the Wenjing River watershed in China by GLUE, SUFI-2, and ParaSol methods. Ecol Eng 76:110–121

    Article  Google Scholar 

  48. Yang J, Abbaspour KC, Reichert P, Yang H (2008) Comparing uncertainty analysis techniques for a SWAT application to Chaohe Basin in China. J Hydrol 358(1–2):1–23

    Article  Google Scholar 

  49. Yoon S, Jeong C, Lee T (2014) Flood flow simulation using CMAX radar rainfall estimates in orographic basins. Meteorol Appl 21:596–604

    Article  Google Scholar 

  50. Yu DS, Shi XZ, Wang HJ, Sun WX, Liu QH, Zhao YC (2007a) Regional patterns of soil organic carbon storages in China. J Environ Manag 85:680–689

    Article  CAS  Google Scholar 

  51. Yu DS, Shi XZ, Wang HJ, Sun WX, Warner ED, Liu QH (2007b) National scale analysis of soil organic carbon storage in china based on Chinese soil taxonomy. Pedosphere 17(1):11–18

    Article  CAS  Google Scholar 

  52. Zhang X, Srinivasan R, Hao F (2007) Predicting hydrologic response to climate change in the Luohe river basin using the SWAT model. Trans ASABE 50(3):901–910

    Article  Google Scholar 

  53. Zhang Y, Xia J, Shao Q, Zhai X (2013) Water quantity and quality simulation by improved swat in highly regulated Huai River basin of China. Stoch Environ Res Risk Assess 27:11–27

    Article  CAS  Google Scholar 

  54. Zhou J, Liu Y, Guo H, He D (2014) Combining the SWAT model with sequential uncertainty fitting algorithm for streamflow prediction and uncertainty analysis for the Lake Dianchi Basin, China. Hydrol. Process 28:521–533

    Article  Google Scholar 

  55. Zuo D, Wang Y, Chen J (1963) Regional spatial patterns of solar radiation in China. ACTA Metero SINICA 33(1):78–95 (Chinese)

    Google Scholar 

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Acknowledgments

The authors gratefully acknowledge the financial support provided by Chinese Natural Science Foundation (41201191), Chinese Ministry of Education New Faculty Fund (20120071120034), Fudan University Tyndall Center Project (FTC98503B04), and Chinese Natural Science Foundation (41201394). We also acknowledge the CORDEX-East Asia Databank, which is responsible for the CORDEX dataset, and we thank the National Institute of Meteorological Research (NIMR), three universities in the Republic of Korea (Seoul National University, Yonsei University, Kongju National University) and other cooperative research institutes in East Asia region for producing and making available their model output.

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Correspondence to Xiaoying Yang or Xiaoxiang Zhang.

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Yang, X., Liu, Q., He, Y. et al. Comparison of daily and sub-daily SWAT models for daily streamflow simulation in the Upper Huai River Basin of China. Stoch Environ Res Risk Assess 30, 959–972 (2016). https://doi.org/10.1007/s00477-015-1099-0

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Keywords

  • Daily streamflow
  • Hourly rainfall
  • Regional downscaling
  • Huai River
  • SWAT