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APEX model simulation of runoff and sediment losses for grazed pasture watersheds with agroforestry buffers

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Abstract

Buffers have been found to reduce non-point source pollution (NPSP) from watersheds. Hydrologic simulation models assist in predicting the effects of buffers on runoff and sediment losses from small watersheds. The objective of this study was to calibrate, validate and simulate runoff and sediment losses and compare buffer effects on NPSP losses relative to control watersheds (no buffer) for seven years. The experimental design consists of four watersheds under pasture management which were monitored from 2002 through 2008; two with agroforestry buffers (AgB 100 and AgB 300) and two control watersheds (CW 400 and CW 600). Pasture areas included red clover (Trifolium pretense L.) and lespedeza (Kummerowia stipulacea Maxim.) planted into fescue (Festuca arundinacea Schreb.) while the agroforestry buffer area included Eastern cottonwood trees (Populus deltoids Bortr. ex Marsh.) planted into fescue. The APEX model was calibrated from 2002 to 2005 and was validated from 2006 to 2008. The r 2 and NSE values for the calibration and validation periods of the runoff varied from 0.52 to 0.78 and 0.50 to 0.74, respectively. The model did not predict sediment loss very well probably due to insufficient number of measured events and low measured sediment loss. The measured runoff was 57% higher for CW watersheds compared to AgB watersheds. The measured sediment loss was 95% higher for CW watersheds compared to AgB watersheds. After calibrating and validating the model, it was run for long-term scenario analyses for 10 years from 1999 to 2008. Simulated buffer width had a significant influence on runoff. Simulated runoff decreased by 24% when the buffer width was doubled compared to losses associated with the measured buffer width. Simulated runoff from the CW watersheds was 11% higher with double stocking density (relative to measured density) compared to AgB watersheds with double stocking density. With half stocking density (relative to measured density), the AgB watershed had 18% lower runoff compared to CW. Results from this study imply that establishment of agroforestry buffers on grazed pasture watersheds reduce runoff and sediment losses compared to control watersheds without buffers.

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References

  • Abu-Zreig M, Rudra RP, Whitely HR, Lalonde MN, Kaushik NK (2003) Phosphorus removal in vegetated filter strips. J Environ Qual 32:613–619

    Article  PubMed  CAS  Google Scholar 

  • Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment—pt1: model development. J Am Water Res Assoc 34:73–89

    Article  CAS  Google Scholar 

  • Baker JL, Mickelson SK, Arora K, Misra AK (2000) The potential of vegetated filter strips to reduce pesticide transport. In: Steinheimer TR et al (eds) Agrochemical movement: perspective and scale. American Chemical Society, Washington, DC, pp 272–287

    Chapter  Google Scholar 

  • Daniels RB, Gilliam JW (1996) Sediment and chemical load reduction by grass and riparian filters. Soil Sci Soc Am J 60:246–251

    Article  CAS  Google Scholar 

  • De la Cruz RE, Vergara NT (1987) Protective and ameliorative roles of agroforestry: an overview. In: Vergara NT, Briones ND (eds) Agroforestry in the humid tropics. Environment and Policy Institute Southeast Asian Regional Center for Graduate Study, Honolulu, Hawaii, pp 3–30

    Google Scholar 

  • FAPRI (2002) Food and agricultural policy research institute college of agriculture food and natural resources. University of Missouri, Columbia, MO

  • Farrand DT, Udawatta RP, Garrett HE (2002) Predicting environmental benefits of Agroforestry practices in northern Missouri using APEX. Agronomy abstracts. In: Annual meetings Indianapolis, Indiana. American Society of agronomy, Madison, Wisconsin, 10–14 Nov 2002

  • Gassman PW, Williams JR, Benson VW, Izaurralde RC, Hauck LM, Jones CA, Atwood JD, Kiniry JR, Flowers JD (2005) Historical development and applications of the EPIC and APEX models working paper 05-WP 397. Centre for agricultural and rural development, Iowa State University, Ames, Iowa

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

    CAS  Google Scholar 

  • Gilliam JW (1994) Riparian wetlands and water quality. J Environ Qual 23:896–900

    Article  Google Scholar 

  • Hargreaves GH, Samani ZA (1985) Reference crop evapotranspiration from temperature. Appl Eng Agric 1:96–99

    Google Scholar 

  • Harman WL, Wang E, Williams JR (2004) Reducing atrazine losses: water quality implications of alternative runoff control practices. J Environ Qual 33:7–12

    Article  PubMed  CAS  Google Scholar 

  • Izaurralde RC, Williams JR, McGill WB, Rosenberg NJ (2006) Simulating soil C dynamics with EPIC: model description and testing against long-term data. Ecol Model 192(3–4):362–384

    Article  Google Scholar 

  • Kiniry JR, Blanchet R, Williams JR, Texier V, Jones CA, Cabelguenne M (1992) Sunflower simulation using EPIC and ALMANAC models. Field Crops Res 30:403–423

    Article  Google Scholar 

  • Knisel WG (1980) CREAMS: a field scale model for chemical runoff and erosion from agricultural management systems: conservation research report no 26. US Department of Agriculture, Washington, DC, 640 pp

  • Kumar S, Anderson SH, Bricknell LG, Udawatta RP, Gantzer CJ (2008) Soil hydraulic properties influenced by agroforestry and grass buffers for grazed pasture systems. J Soil Water Conserv 63:224–232

    Article  Google Scholar 

  • Kumar S, Anderson SH, Udawatta RP (2010) Agroforestry and grass buffer influences on CT-measured macropores under grazed pasture systems. Soil Sci Soc Am J 74:1–10

    Article  Google Scholar 

  • Lee KH, Isenhart TM, Schultz RC (2003) Sediment and nutrient removal in an established multi-species riparian buffer. J Soil Water Conserv 58(1):1–8

    Google Scholar 

  • Leonard RA, Knisel WG, Still DA (1987) GLEAMS: groundwater loading effects of agricultural management system. Trans ASAE 30(5):1403–1418

    Google Scholar 

  • Line DE, Harman WA, Jennings GD, Thompson EJ, Osmond DL (2000) Nonpoint-source pollutant load reductions associated with livestock exclusion. J Environ Qual 29:1882–1890

    Article  CAS  Google Scholar 

  • Lovell ST, Sullivan WC (2006) Environmental benefits of conservation buffers in the United States: evidence promise and open questions. Agr Ecosyst Environ 112:249–260

    Article  Google Scholar 

  • Lowrance R, Crow SR (2002) Implementation of riparian buffer systems for landscape management. In: Ryszkowski L (ed) Landscape ecology in agroecosystems management. CRC Press, Washington, DC, pp 145–158

    Google Scholar 

  • 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. Trans ASABE 50(3):885–900

    Google Scholar 

  • Mudgal A, Baffaut C, Anderson SH, Sadler EJ, Thompson AL (2010) APEX model assessment of variable landscapes on runoff and dissolved herbicides. Trans ASABE 53:1047–1058

    Google Scholar 

  • Muschler RG, Bonnemann A (1997) Potentials and limitations of agroforestry for changing land-use in the tropics: experiences from Central America. For Ecol Manage 91:61–73

    Article  Google Scholar 

  • Nash JE, Sutcliffe JE (1970) River flow forecasting through conceptual models: part 1. A discussion of principles. J Hydrol 10(3):282–290

    Article  Google Scholar 

  • Parton WJ, Scurlock JMO, Ojima DS, Gilmanov TG, Scholes RJ, Schimel DS, Kirchner T, Menaut JC, Seastedt T, Garcia E, Kamnalrut MA, Kinyamario JI (1993) Observations and modeling of biomass and soil organic matter dynamics for the grassland biome worldwide. Global Biogeochem Cycles 7:785–809

    Article  CAS  Google Scholar 

  • Parton WJ, Ojima DS, Cole CV, Schimel DS (1994) A general model for soil organic matter dynamics: sensitivity to litter chemistry texture and management. In: Quantitative modeling of soil forming processes, SSSA Spec public no 39, Madison, WI, pp 147–167

  • SAS Institute (1999) SAS user’s guide statistics. SAS Inst, Cary, NC

    Google Scholar 

  • Singh VP, Frevert DK (2006) Watershed Models. CRC Press, Taylor and Francis, Boca Raton, FL

    Google Scholar 

  • Udawatta RP, Krstansky JJ, Henderson GS, Garrett HE (2002) Agroforestry practices runoff and nutrient loss: a paired watershed comparison. J Environ Qual 31:1214–1225

    Article  PubMed  CAS  Google Scholar 

  • Udawatta RP, Garrett HE, Kallenbach RL (2010) Agroforestry and grass buffer effects on water quality in grazed pastures. Agro Syst 79:81–87

    Article  Google Scholar 

  • Wang E, Xin C, Williams JR, Xu C (2006) Predicting soil erosion for alternative land uses. J Environ Qual 35:459–467

    Article  PubMed  Google Scholar 

  • Wang X, Gassman PW, Williams JR, Potter S, Kemanian AR (2008) Modeling the impacts of soil management practices on runoff sediment yield maize productivity and soil organic carbon using APEX. Soil Till Res 101:78–88

    Article  Google Scholar 

  • Williams JR (1990) The erosion productivity impact calculator (EPIC) model: a case history. Phil Trans R Soc Lond 329:421–428

    Article  Google Scholar 

  • Williams JR, Izaurralde RC (2005) The APEX model. BRC Rep (2005)-02, Blackland Res Center, Texas, A&M University, Temple, TX

  • Williams JR, Sharpley AN (1989) EPIC-erosion/productivity impact calculator: 1. Model documentation technical bulletin no 1768. USDA Agricultural Research Service, Washington DC

  • Williams JR, Wang E, Meinardus A, Harman WL, Siemers M, Atwood JD (2006a) APEX users guide v2110. Texas A&M University, Texas Agricultural Extension Service, Texas Agricultural Experiment Station, Blacklands Research Center, Temple, TX

  • Williams JR, Harman WL, Magre M, Kizil U, Lindley JA, Padmanabhan G, Wang E (2006b) APEX feedlot water quality simulation. Trans ASABE 49:61–73

    CAS  Google Scholar 

  • Williams JR, Izaurralde RC, Steglich EM (2008) Agricultural policy/environmental eXtender model: theoretical documentation version 0604 (draft). BREC report # 2008-17. Texas AgriLIFE Research, Texas A&M University, Temple, TX

Download references

Acknowledgments

This work was funded through the University of Missouri Center for Agroforestry under cooperative agreements 58-6227-1-004 with the USDA-ARS. Any opinions, findings, conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the U.S. Department of Agriculture.

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Correspondence to Sandeep Kumar.

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Kumar, S., Udawatta, R.P., Anderson, S.H. et al. APEX model simulation of runoff and sediment losses for grazed pasture watersheds with agroforestry buffers. Agroforest Syst 83, 51–62 (2011). https://doi.org/10.1007/s10457-010-9350-7

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  • DOI: https://doi.org/10.1007/s10457-010-9350-7

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