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Evaluating Agricultural BMP Effectiveness in Improving Freshwater Provisioning Under Changing Climate

  • Ping Li
  • Rebecca L. Muenich
  • Indrajeet Chaubey
  • Xiaomei Wei
Article
  • 75 Downloads

Abstract

Freshwater provisioning (FWP) is a critical ecosystem service that is highly affected by climate change/variability as well as land use/land management. Agricultural best management practices (BMPs) are implemented to mitigate the adverse impacts of intensive agricultural production on flow and water quality, thus can potentially protect and improve FWP services. Many studies have assessed BMP effectiveness for improving hydrology/water quality, however the impact of climate changes on BMP effectiveness for protecting FWP is poorly understood. In this study, changes in FWP under 5 BMPs and 6 projected climate change/variability scenarios, were quantified. The Soil and Water Assessment Tool was used to quantify FWP services for baseline (1975–2004) and future climates (2021–2050). We then assessed the climate change impacts on BMP effectiveness for 13 watersheds in the Upper Mississippi River Basin. The results indicated that all 5 BMP scenarios behaved similarly under the historical and future climates, generally resulting in improved FWP services compared to the baseline agricultural management. The combined BMPs was the most effective way to enhance FWP. No-tillage and cover crops performed well in improving FWP in agriculturally-dominated watersheds, while filter strips and grassed waterways had high effectiveness in non-agriculturally dominated watersheds. Results for the climate scenarios indicate that 5 BMPs under future climate were still effective compared to baseline. The increased precipitation and rising temperatures generally improved BMP effectiveness in maintaining and improving FWP services, due to increased freshwater availability under the projected future climate.

Keywords

Ecosystem service Streamflow Water quality SWAT 

Notes

Acknowledgements

This study was funded by China Postdoctoral Science Foundation (Award No. 043206018), the U.S. Department of Energy (Award No. DE-EE0004396) and the USDA-NIFA (Award No. S1063). Great appreciation to Hendrik Rathjens for his technical help on bias correction of climate projection data. The authors also would like to thank anonymous reviewers for their comments and suggestions to improve the manuscript.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

References

  1. Abbaspour KC, Rouholahnejad E, Vaghefi S et al (2015) A continental-scale hydrology and water quality model for Europe: calibration and uncertainty of a high-resolution large-scale SWAT model. J Hydrol 524:733–752.  https://doi.org/10.1016/j.jhydrol.2015.03.027 CrossRefGoogle Scholar
  2. Alexander RB, Smith RA, Schwarz GE (2000) Effect of stream channel size on the delivery of nitrogen to the Gulf of Mexico. Nature 403:758–761CrossRefGoogle Scholar
  3. Arabi M, Frankenberger JR, Engel BA, Arnold JG (2008) Representation of agricultural conservation practices with SWAT. Hydrol Process 22:3042–3055.  https://doi.org/10.1002/hyp.6890 CrossRefGoogle Scholar
  4. Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment part I: model development. J Am Water Resour Assoc 34:73–89CrossRefGoogle Scholar
  5. Bhattarai R, Kalita PK, Patel MK (2009) Nutrient transport through a vegetative filter strip with subsurface drainage. J Environ Manag 90:1868–1876.  https://doi.org/10.1016/j.jenvman.2008.12.010 CrossRefGoogle Scholar
  6. Bosch NS, Allan JD, Selegean JP, Scavia D (2013) Scenario-testing of agricultural best management practices in Lake Erie watersheds. J Great Lakes Res 39:429–436.  https://doi.org/10.1016/j.jglr.2013.06.004 CrossRefGoogle Scholar
  7. Bosch NS, Evans MA, Scavia D, Allan JD (2014) Interacting effects of climate change and agricultural BMPs on nutrient runoff entering Lake Erie. J Great Lakes Res 40:581–589.  https://doi.org/10.1016/j.jglr.2014.04.011 CrossRefGoogle Scholar
  8. Chaubey I, Chiang L, Gitau MW, Mohamed S (2010) Effectiveness of best management practices in improving water quality in a pasture-dominated watershed. J Soil Water Conserv 65:424–437.  https://doi.org/10.2489/jswc.65.6.424 CrossRefGoogle Scholar
  9. Christensen JH, Boberg F, Christensen OB, Lucas-Picher P (2008) On the need for bias correction of regional climate change projections of temperature and precipitation. Geophys Res Lett 35:L20709.  https://doi.org/10.1029/2008GL035694 CrossRefGoogle Scholar
  10. Conservation Effects Assessment Project (CEAP) (2012) Assessment of the Effects of conservation practices on cultivated cropland in the Upper Mississippi River Basin. United States Department of Agriculture (USDA), Natural Resources Conservation Service (NRCS), USAGoogle Scholar
  11. Dakhlalla AO, Parajuli PB (2016) Evaluation of the best management practices at the watershed scale to attenuate peak streamflow under climate change scenarios. Water Resour Manag 30:963–982.  https://doi.org/10.1007/s11269-015-1202-9 CrossRefGoogle Scholar
  12. Delong MD (2005) 8 - upper Mississippi River basin A2 - Benke, Arthur C. In: Cushing CE (ed) Rivers of North America. Academic Press, Burlington, pp 326–373CrossRefGoogle Scholar
  13. Demissie Y, Yan E, Wu M (2012) Assessing regional hydrology and water quality implications of large-scale biofuel feedstock production in the upper Mississippi River basin. Environ Sci Technol 46:9174–9182.  https://doi.org/10.1021/es300769k CrossRefGoogle Scholar
  14. Gassman PW, Sadeghi AM, Srinivasan R (2014) Applications of the SWAT model special section: overview and insights. J Environ Qual 43:1.  https://doi.org/10.2134/jeq2013.11.0466 CrossRefGoogle Scholar
  15. IPCC (2013) Climate Change 2013: The Physical Science Basis. Working Group I Contribution to the fifth assessment report of the International Panel on Climate Change. Cambridge University Press, Cambridge, and New York. https://www.ipcc.ch/report/ar5/wg1/. Accessed 3 Nov 2017
  16. Jayakody P, Parajuli PB, Cathcart TP (2014) Impacts of climate variability on water quality with best management practices in sub-tropical climate of USA. Hydrol Process 28:5776–5790.  https://doi.org/10.1002/hyp.10088 CrossRefGoogle Scholar
  17. Kaini P, Artita K, Nicklow JW (2012) Optimizing structural best management practices using SWAT and genetic algorithm to improve water quality goals. Water Resour Manag 26:1827–1845.  https://doi.org/10.1007/s11269-012-9989-0 CrossRefGoogle Scholar
  18. Kalcic MM, Frankenberger J, Chaubey I (2015) Spatial optimization of six conservation practices using Swat in tile-drained agricultural watersheds. J Am Water Resour Assoc 51:956–972.  https://doi.org/10.1111/1752-1688.12338 CrossRefGoogle Scholar
  19. Kaspar TC, Jaynes DB, Parkin TB et al (2012) Effectiveness of oat and rye cover crops in reducing nitrate losses in drainage water. Agric Water Manag 110:25–33.  https://doi.org/10.1016/j.agwat.2012.03.010 CrossRefGoogle Scholar
  20. Li P, Chaubey I, Muenich RL, Wei X (2016) Evaluation of freshwater provisioning for different ecosystem services in the Upper Mississippi River Basin: current status and drivers. Water 8:288.  https://doi.org/10.3390/w8070288 CrossRefGoogle Scholar
  21. Li P, Omani N, Chaubey I, Wei X (2017) Evaluation of drought implications on ecosystem services: freshwater provisioning and food provisioning in the upper Mississippi River basin. Int J Environ Res Public Health 14:496.  https://doi.org/10.3390/ijerph14050496 CrossRefGoogle Scholar
  22. Logsdon RA, Chaubey I (2013) A quantitative approach to evaluating ecosystem services. Ecol Model 257:57–65.  https://doi.org/10.1016/j.ecolmodel.2013.02.009 CrossRefGoogle Scholar
  23. Millennium Ecosystem Assessment (MEA) (2005) Ecosystem services and human well-being: synthesis. Island Press, WashingtonGoogle Scholar
  24. Moriasi DN, Arnold JG, Van Liew MW et al (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50:885–900CrossRefGoogle Scholar
  25. Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2009) Soil and water assessment tool theoretical documentation version 2009. Texas Water Resources Institute Technical Report No. 406. College Station, TX, USA. 2011:1–618Google Scholar
  26. Panagopoulos Y, Gassman PW, Arritt RW et al (2014) Surface water quality and cropping systems sustainability under a changing climate in the upper Mississippi River basin. J Soil Water Conserv 69:483–494.  https://doi.org/10.2489/jswc.69.6.483 CrossRefGoogle Scholar
  27. Russo S, Marchese AF, Sillmann J, Immé G (2016) When will unusual heat waves become normal in a warming Africa? Environ Res Lett 11:054016.  https://doi.org/10.1088/1748-9326/11/5/054016 CrossRefGoogle Scholar
  28. Secchi S, Gassman PW, Jha M et al (2011) Potential water quality changes due to corn expansion in the upper Mississippi River basin. Ecol Appl 21:1068–1084.  https://doi.org/10.1890/09-0619.1 CrossRefGoogle Scholar
  29. Srinivasan R, Zhang X, Arnold J (2010) SWAT ungauged: hydrological budget and crop yield predictions in the upper Mississippi River basin. Trans ASABE 53:1533–1546CrossRefGoogle Scholar
  30. Strock JS, Porter PM, Russelle MP (2004) Cover cropping to reduce nitrate loss through subsurface drainage in the northern U.S. Corn Belt. J Environ Qual 33:1010–1016CrossRefGoogle Scholar
  31. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498.  https://doi.org/10.1175/BAMS-D-11-00094.1 CrossRefGoogle Scholar
  32. Terrado M, Acuña V, Ennaanay D et al (2014) Impact of climate extremes on hydrological ecosystem services in a heavily humanized Mediterranean basin. Ecol Indic 37:199–209.  https://doi.org/10.1016/j.ecolind.2013.01.016 CrossRefGoogle Scholar
  33. Teutschbein C, Seibert J (2012) Bias correction of regional climate model simulations for hydrological climate-change impact studies: review and evaluation of different methods. J Hydrol 456–457:12–29.  https://doi.org/10.1016/j.jhydrol.2012.05.052 CrossRefGoogle Scholar
  34. USDA-NRCS (2013) Soil Web Portal http://soildatamart.nrcs.usda.gov/. Accessed 27 July 2015
  35. Villarreal EL, Semadeni-Davies A, Bengtsson L (2004) Inner city stormwater control using a combination of best management practices. Ecol Eng 22:279–298.  https://doi.org/10.1016/j.ecoleng.2004.06.007 CrossRefGoogle Scholar
  36. Vörösmarty CJ, Bos R, Balvanera P (2005) Fresh water. Ecosyst Hum Well- Curr State Trends Find Cond Trends Work Group 1:165Google Scholar
  37. Waidler D, White M, Steglich E, Wang S, Williams J, Jones CA, Srinivasan R (2009) Conservation practice modeling guide for SWAT and APEX. Texas Water Resources Institute Technical Report No. 399, Texas A&M University System College Station, Texas p 77843–2118Google Scholar
  38. Willaarts BA, Volk M, Aguilera PA (2012) Assessing the ecosystem services supplied by freshwater flows in Mediterranean agroecosystems. Agric Water Manag 105:21–31.  https://doi.org/10.1016/j.agwat.2011.12.019 CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • Ping Li
    • 1
    • 2
  • Rebecca L. Muenich
    • 3
  • Indrajeet Chaubey
    • 4
    • 5
  • Xiaomei Wei
    • 1
  1. 1.College of Water Resources and Architectural EngineeringNorthwest A&F UniversityYanglingChina
  2. 2.Department of Hydraulic EngineeringTsinghua UniversityBeijingChina
  3. 3.School of Sustainable Engineering and the Built EnvironmentArizona State UniversityTempeUSA
  4. 4.Department of Earth, Atmospheric, and Planetary SciencesPurdue UniversityWest LafayetteUSA
  5. 5.Department of Agricultural and Biological EngineeringPurdue UniversityWest LafayetteUSA

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