Water Resources Management

, Volume 31, Issue 12, pp 3953–3974 | Cite as

SWAT Setup with Long-Term Detailed Landuse and Management Records and Modification for a Micro-Watershed Influenced by Freeze-Thaw Cycles

  • Junyu Qi
  • Sheng Li
  • Qi Yang
  • Zisheng Xing
  • Fan-Rui MengEmail author


In the widely used soil and water assessment tool (SWAT), the standard hydrological response units (HRUs) delineation method has low spatial resolution with respect to model inputs and outputs and renders difficulties in using long-term detailed landuse and management records. In addition, the modified universal soil loss equation (MUSLE) uses a constant K-factor which cannot address seasonal variation in soil erodibility caused by freeze-thaw cycles in cold regions. The current study presents a simple method to incorporate detailed landuse and management inputs in SWAT. The method delineates HRUs based on field boundaries and associates each HRU with a particular field. As a result, long-term detailed records can be incorporated into the SWAT management files. In addition, the existing MUSLE in SWAT was modified by introducing a variable K-factor to address effects of freeze-thaw cycles on soil erosion for cold regions. This modified version of SWAT was calibrated and validated for an agricultural micro-watershed, i.e., Black Brook Watershed in New Brunswick, Canada. The results showed that, compared with the standard HRU-delineation method, field-based HRU-delineation method was able to improve landuse and management practice input accuracy for SWAT and save time and effort for long-term simulation, and provide high resolution outputs in the watershed. As a result, the field-based HRU-delineation method can facilitate decision making not only at the subbasin scale but also at the field scale. In addition, results showed that sediment loading simulation accuracy was improved with the modified-MUSLE compared with the original-MUSLE.


Freeze-thaw Best management practices Hydrological response units MUSLE Water quality 



The funding support for this project was provided by Agriculture and Agri-Food Canada (AAFC) through project #1145, entitled “Integrating selected BMPs to maximize environmental and economic benefits at the field and watershed scales for sustainable potato production in New Brunswick”, and Natural Science and Engineering Research Council (NSERC) through Discovery Grants to CPAB and FRM. The research is also partially supported byNASA (NNX17AE66G) and USDA (2017-67003-26485). Authors are thankful to S. Lavoie, J. Monteith, and L. Stevens for their technical support in data collection and sample analyses.


  1. Abbaspour K, Vejdani M, Haghighat S (2007) SWAT-CUP calibration and uncertainty programs for SWAT. In: MODSIM 2007 International congress on Modelling and simulation, Modelling and simulation Society of Australia and new ZealandGoogle Scholar
  2. Ahmad N et al (2011) Modeling sediment and nitrogen export from a rural watershed in eastern Canada using the soil and water assessment tool. Journal of Environmental Quality 40:1182–1194CrossRefGoogle Scholar
  3. Alberts E, Laflen J, Spomer R (1987) Between year variation in soil erodibility determined by rainfall simulation. Transactions of ASAE 30:982–987CrossRefGoogle Scholar
  4. Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment part I: model development. JAWRA Journal of the American Water Resources Association 34:73–89CrossRefGoogle Scholar
  5. Bajracharya R, Lal R (1992) Seasonal soil loss and erodibility variation on a Miamian silt loam soil. Soil Science Society of America Journal 56:1560–1565CrossRefGoogle Scholar
  6. Cao W, Bowden WB, Davie T, Fenemor A (2009) Modelling impacts of land cover change on critical water resources in the Motueka River catchment, New Zealand. Water Resources Management 23:137–151CrossRefGoogle Scholar
  7. Chow T, Rees H (2006) Impacts of intensive potato production on water yield and sediment load Black Brook Experimental Watershed: 1992-2002 Summary. Potato Research Centre, AAFC, Fredericton, New Brunswick, CanadaGoogle Scholar
  8. Chow L, Xing Z, Benoy G, Rees H, Meng F, Jiang Y, Daigle J (2011) Hydrology and water quality across gradients of agricultural intensity in the Little River watershed area, New Brunswick, Canada. Journal of Soil and Water Conservation 66:71–84CrossRefGoogle Scholar
  9. Coote D, Malcolm-McGovern C, Wall G, Dickinson W, Rudra R (1988) Seasonal variation of erodibility indices based on shear strength and aggregate stability in some Ontario soils. Canadian Journal of Soil Science 68:405–416CrossRefGoogle Scholar
  10. Cronshey R, McCuen, R.H., Miller, N., Rawls, W., Robbins, S., Woodward, D. (1986) Urban hydrology for small watersheds. National Resources Conservation Service, USDA, Washington, DC, USAGoogle Scholar
  11. Daggupati P, Douglas-Mankin K, Sheshukov A, Barnes P, Devlin D (2011) Field-level targeting using SWAT: mapping output from HRUs to fields and assessing limitations of GIS input data. Transactions of the ASABE 54:501–514CrossRefGoogle Scholar
  12. Dakhlalla AO, Parajuli PB (2015) Evaluation of the best management practices at the watershed scale to attenuate peak streamflow under climate change scenarios. Water Resources Management 30:963–982CrossRefGoogle Scholar
  13. Debele B, Srinivasan R, Gosain AK (2010) Comparison of process-based and temperature-index snowmelt modeling in SWAT. Water Resources Management 24:1065–1088CrossRefGoogle Scholar
  14. Edwards L (1991) The effect of alternate freezing and thawing on aggregate stability and aggregate size distribution of some Prince Edward Island soils. European Journal of Soil Science 42:193–204CrossRefGoogle Scholar
  15. Gassman PW, Reyes MR, Green CH, Arnold JG (2005) SWAT peer-reviewed literature: a review. In: 3rd International SWAT conference. Zurich, SwitzerlandGoogle Scholar
  16. Ghebremichael L, Veith T, Hamlett J, Gburek W (2008) Precision feeding and forage management effects on phosphorus loss modeled at a watershed scale. Journal of Soil and Water Conservation 63:280–291CrossRefGoogle Scholar
  17. Ghebremichael L, Veith T, Watzin M (2010) Determination of critical source areas for phosphorus loss: Lake Champlain basin. Vermont Trans ASABE 53:1595–1604CrossRefGoogle Scholar
  18. Gitau M, Veith T, Gburek W (2004) Farm-level optimization of BMP placement for cost-effective pollution reduction. Transactions of ASAE 47:1923–1931CrossRefGoogle Scholar
  19. Govers G, Loch R (1993) Effects of initial water content and soil mechanical strength on the runoff erosion resistance of clay soils. Soil Research 31:549–566CrossRefGoogle Scholar
  20. Haan CT, Barfield BJ, Hayes JC (1994) Design hydrology and sedimentology for small catchments. Academic Press, San Diego, California, USAGoogle Scholar
  21. Hosoyamada K (1986) The effects of rainfall and soil properties on farmland conservation. Journal of Irrigation Engineering and Rural Planning 1986:5–14Google Scholar
  22. Jha M, Gassman PW, Secchi S, Gu R, Arnold J (2004) Effect of watershed subdivision on SWAT flow, sediment, and nutrient predictions. JAWRA Journal of the American Water Resources Association 40:811–825CrossRefGoogle Scholar
  23. Kalcic MM, Chaubey I, Frankenberger J (2015) Defining soil and water assessment tool (SWAT) hydrologic response units (HRUs) by field boundaries. International Journal of Agricultural and Biological Engineering 8:69–80Google Scholar
  24. Kirby P, Mehuys G (1987a) Seasonal variation of soil erodibilities in southwestern Quebec. Journal of Soil and Water Conservation 42:211–215Google Scholar
  25. Kirby P, Mehuys G (1987b) The seasonal variation of soil erosion by water in southwestern Quebec. Canadian Journal of Soil Science 67:55–63CrossRefGoogle Scholar
  26. Kok H, McCool D (1990a) Quantifying freeze/thaw-induced variability of soil strength. Transactions of ASAE 33:501–506CrossRefGoogle Scholar
  27. Kok H, McCool DK (1990b) Freeze thaw effects on soil strength. In: Cooley KR (ed.) International symposium on frozen soil impacts on agricultural, range, and forest lands. Special report. U.S. Army Cold Regions Research and Engineering Laboratory, Hanover, NH, pp 90–91Google Scholar
  28. Li Q et al (2014a) An approach for assessing impact of land use and biophysical conditions across landscape on recharge rate and nitrogen loading of groundwater. Agriculture, Ecosystems and Environment 196:114–124CrossRefGoogle Scholar
  29. Li Q, Xing Z, Danielescu S, Li S, Jiang Y, Meng F-R (2014b) Data requirements for using combined conductivity mass balance and recursive digital filter method to estimate groundwater recharge in a small watershed, New Brunswick, Canada. Journal of Hydrology 511:658–664CrossRefGoogle Scholar
  30. Li J, Li G, Zhou S, Chen F (2015) Quantifying the effects of land surface change on annual runoff considering precipitation variability by SWAT. Water Resources Management 30:1071–1084CrossRefGoogle Scholar
  31. Li S, Liang W, Zhang W, Liu Q (2016) Response of soil moisture to hydro-meteorological variables under different precipitation gradients in the Yellow River basin. Water Resources Management 30:1867–1884CrossRefGoogle Scholar
  32. Lobb DA, Li S, McConkey BG (2016) Soil erosion. Agriculture and Agri-Food Canada, Ottawa, ONGoogle Scholar
  33. Maier N, Dietrich J (2016) Using SWAT for strategic planning of basin scale irrigation control policies: a case study from a humid region in northern Germany. Water Resources Management 30:3285–3298CrossRefGoogle Scholar
  34. McConkey B, Nicholaichuk W, Steppuhn H, Reimer C (1997) Sediment yield and seasonal soil erodibility for semiarid cropland in western Canada. Canadian Journal of Soil Science 77:33–40CrossRefGoogle Scholar
  35. Mekonnen BA, Mazurek KA, Putz G (2016) Sediment export modeling in cold-climate prairie watersheds. Journal of Hydrologic Engineering 21:05016005CrossRefGoogle Scholar
  36. Mellerowicz KT (1993) Soils of the Black Brook watershed St. Andre parish, Madawaska County, New Brunswick. [Fredericton]: new Brunswick Department of AgricultureGoogle Scholar
  37. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE 50:885–900CrossRefGoogle Scholar
  38. Mutchler CK, Carter CE (1983) Soil erodibility variation during the year. Transactions of the American Society of Agricultural Engineers 26:1102–1104CrossRefGoogle Scholar
  39. Nagasawa T, Umeda Y, Li L (1993) Control of soil erosion in Hokkaido [Japan], 2: characteristics of soil erosion during snowmelt and thawing periods Transactions of the Japanese Society of Irrigation. Engineering, Drainage and ReclamationGoogle Scholar
  40. Nash J, Sutcliffe J (1970) River flow forecasting through conceptual models part I-A discussion of principles. Journal of Hydrology 10:282–290CrossRefGoogle Scholar
  41. Ning J, Gao Z, Lu Q (2015) Runoff simulation using a modified SWAT model with spatially continuous HRUs. Environmental Earth Sciences 74:5895–5905CrossRefGoogle Scholar
  42. Pai N, Saraswat D, Srinivasan R (2012) Field_SWAT: A tool for mapping SWAT output to field boundaries. Computational Geosciences 40:175–184CrossRefGoogle Scholar
  43. Qi J, Li S, Li Q, Xing Z, Bourque CP-A, Meng F-R (2016a) Assessing an enhanced version of SWAT on water quantity and quality simulation in regions with seasonal snow cover. Water Resources Management 30:5021–5037CrossRefGoogle Scholar
  44. Qi J, Li S, Li Q, Xing Z, Bourque CP-A, Meng F-R (2016b) A new soil-temperature module for SWAT application in regions with seasonal snow cover. Journal of Hydrology 538:863–877CrossRefGoogle Scholar
  45. Qi J, Li S, Jamieson R, Hebb D, Xing Z, Meng F-R (2017) Modifying SWAT with an energy balance module to simulate snowmelt for maritime regions. Environmental Modelling and Software 93:146–160CrossRefGoogle Scholar
  46. Teshager AD, Gassman PW, Secchi S, Schoof JT, Misgna G (2016) Modeling agricultural watersheds with the soil and water assessment tool (SWAT): calibration and validation with a novel procedure for spatially explicit HRUs. Environmental Management 57:894–911CrossRefGoogle Scholar
  47. Ullrich A, Volk M (2009) Application of the soil and water assessment tool (SWAT) to predict the impact of alternative management practices on water quality and quantity. Agricultural Water Management 96:1207–1217CrossRefGoogle Scholar
  48. Uniyal B, Jha MK, Verma AK (2015) Assessing climate change impact on water balance components of a river basin using SWAT model. Water Resources Management 29:4767–4785CrossRefGoogle Scholar
  49. Veith T, Sharpley A, Weld J, Gburek W (2005) Comparison of measured and simulated phosphorus losses with indexed site vulnerability. Transactions of ASAE 48:557–565CrossRefGoogle Scholar
  50. Veith TL, Sharpley AN, Arnold JG (2008) Modeling a small, northeastern watershed with detailed, field-level data. Transactions of the ASABE 51:471–483CrossRefGoogle Scholar
  51. Wall G, Dickinson W, Rudra R, Coote D (1988) Seasonal soil erodibility variation in southwestern Ontario. Canadian Journal of Soil Science 68:417–424CrossRefGoogle Scholar
  52. Wall G, Coote D, Pringle E, Shelton I (2002) Revised universal soil loss wquation for application in Canada: a handbook for estimating soil loss from water erosion in Canada Agriculture and Agri-Food Canada, Research branch, Ottawa, contribution no AAFC/AAC2244EGoogle Scholar
  53. Wilcox BP (1994) Runoff and erosion in intercanopy zones of pinyon-juniper woodlands. Journal of Range Management:285–295Google Scholar
  54. Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses-a guide to conservation planning, agriculture handbook no. 537 U.S. Department of Agriculture, WashingtonGoogle Scholar
  55. Yang Q, Meng F-R, Zhao Z, Chow TL, Benoy G, Rees HW, Bourque CP-A (2009a) Assessing the impacts of flow diversion terraces on stream water and sediment yields at a watershed level using SWAT model. Agriculture, Ecosystems and Environment 132:23–31CrossRefGoogle Scholar
  56. Yang Q, Zhao Z, Chow TL, Rees HW, Bourque CPA, Meng FR (2009b) Using GIS and a digital elevation model to assess the effectiveness of variable grade flow diversion terraces in reducing soil erosion in northwestern New Brunswick, Canada. Hydrological Processes 23:3271–3280CrossRefGoogle Scholar
  57. Yang Q, Zhao Z, Benoy G, Chow TL, Rees HW, Bourque CP-A, Meng F-R (2010a) A watershed-scale assessment of cost-effectiveness of sediment abatement with flow diversion terraces. Journal of Environmental Quality 39:220–227CrossRefGoogle Scholar
  58. Yang W, Wang X, Liu Y, Gabor S, Boychuk L, Badiou P (2010b) Simulated environmental effects of wetland restoration scenarios in a typical Canadian prairie watershed. Wetlands Ecology and Management 18:269–279CrossRefGoogle Scholar
  59. Young R, Mutchler C (1977) Erodibility of some Minnesota soils. Journal of Soil and Water Conservation 32:180–182Google Scholar
  60. Zanchi C (1988) Soil loss and seasonal variation of erodibility in two soils with different texture in the Mugello valley in Central Italy catena. Supplement 12:167–174Google Scholar
  61. Zhang R, Li Q, Chow TL, Li S, Danielescu S (2013) Baseflow separation in a small watershed in New Brunswick, Canada, using a recursive digital filter calibrated with the conductivity mass balance method. Hydrological Processes 27:2659–2665CrossRefGoogle Scholar
  62. Zhao Z, Chow TL, Yang Q, Rees HW, Benoy G, Xing Z, Meng F-R (2008) Model prediction of soil drainage classes based on digital elevation model parameters and soil attributes from coarse resolution soil maps. Canadian Journal of Soil Science 88:787–799CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Junyu Qi
    • 1
  • Sheng Li
    • 1
    • 2
  • Qi Yang
    • 3
    • 4
  • Zisheng Xing
    • 1
    • 2
  • Fan-Rui Meng
    • 1
    Email author
  1. 1.Faculty of Forestry and Environmental ManagementUniversity of New BrunswickFrederictonCanada
  2. 2.Potato Research Centre, Agriculture and Agri-Food CanadaFrederictonCanada
  3. 3.Guangxi Key Laboratory of Forest Ecology and ConservationNanningChina
  4. 4.College of ForestryGuangxi UniversityNanningChina

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