Sensitivity Analysis of Best Management Practices Under Climate Change Scenarios 1

Woznicki, Sean A. and A. Pouyan Nejadhashemi, 2011. Sensitivity Analysis of Best Management Practices Under Climate Change Scenarios. Journal of the American Water Resources Association (JAWRA) 48(1): 90-112. DOI: 10.1111/j.1752-1688.2011.00598.x Abstract:  Understanding the sensitivity of best management practices (BMPs) implementation as climate changes will be important for water resources management. The objective of this study was to determine how the sensitivity of BMPs performance vary due to changes in precipitation, temperature, and CO2 using the Soil and Water Assessment Tool. Sediment, total nitrogen, and total phosphorus loads on an annual and monthly basis were estimated before and after implementation of eight agricultural BMPs for different climate scenarios. Downscaled climate change data were obtained from the National Center for Atmospheric Research Community Climate System Model for the Tuttle Creek Lake watershed in Kansas and Nebraska. Using a relative sensitivity index, native grass, grazing management, and filter strips were determined to be the most sensitive for all climate change scenarios, whereas porous gully plugs, no-tillage, and conservation tillage were the least sensitive on an annual basis. The monthly sensitivity analysis revealed that BMP sensitivity varies largely on a seasonal basis for all climate change scenarios. The results of this research suggest that the majority of agricultural BMPs tested in this study are significantly sensitive to climate change. Therefore, caution should be exercised in the decision-making processes.

[1]  Eike Luedeling,et al.  Climate change sensitivity assessment of a highly agricultural watershed using SWAT , 2009 .

[2]  Thomas M. Isenhart,et al.  Sediment and nutrient removal in an established multi-species riparian buffer. , 2003 .

[3]  V. Chaplot Water and soil resources response to rising levels of atmospheric CO2 concentration and to changes in precipitation and air temperature , 2007 .

[4]  Raghavan Srinivasan,et al.  Simulation of Agricultural Management Alternatives for Watershed Protection , 2010 .

[5]  Sean A. Woznicki,et al.  ASSESSING BEST MANAGEMENT PRACTICE IMPLEMENTATION STRATEGIES UNDER CLIMATE CHANGE SCENARIOS , 2011 .

[6]  M. Jha,et al.  CLIMATE CHHANGE SENSITIVITY ASSESSMENT ON UPPER MISSISSIPPI RIVER BASIN STREAMFLOWS USING SWAT 1 , 2006 .

[7]  Jeffrey G. Arnold,et al.  Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations , 2007 .

[8]  R. Srinivasan,et al.  A global sensitivity analysis tool for the parameters of multi-variable catchment models , 2006 .

[9]  K. Eckhardt,et al.  Potential impacts of climate change on groundwater recharge and streamflow in a central European low mountain range , 2003 .

[10]  Jeffrey G. Arnold,et al.  The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions , 2007 .

[11]  Philip W. Gassman,et al.  Water Quality Modeling for the Raccoon River Watershed Using SWAT , 2006 .

[12]  Richard H. McCuen,et al.  The role of sensitivity analysis in hydrologic modeling , 1973 .

[13]  Hans-Georg Frede,et al.  Comparison of two different approaches of sensitivity analysis , 2002 .

[14]  O. Edenhofer,et al.  Mitigation from a cross-sectoral perspective , 2007 .

[15]  Raghavan Srinivasan,et al.  A modeling approach to evaluate the impacts of water quality management plans implemented in a watershed in Texas , 2006, Environ. Model. Softw..

[16]  Rollin H. Hotchkiss,et al.  Water yield responses to high and low spatial resolution climate change scenarios in the Missouri River Basin , 2003 .

[17]  John R. Williams,et al.  LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT 1 , 1998 .

[18]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[19]  Minghua Zhang,et al.  Management-oriented sensitivity analysis for pesticide transport in watershed-scale water quality modeling using SWAT. , 2009, Environmental pollution.

[20]  John L. Kittle,et al.  BASINS: Better Assessment Science Integrating Point and Nonpoint Sources , 2009 .

[21]  Dennis P. Lettenmaier,et al.  Climate-Change Scenarios for Water Planning Studies: Pilot Applications in the Pacific Northwest , 2003 .

[22]  Eike Luedeling,et al.  Sensitivity of agricultural runoff loads to rising levels of CO2 and climate change in the San Joaquin Valley watershed of California. , 2010, Environmental pollution.

[23]  R. Wilby,et al.  Risks posed by climate change to the delivery of Water Framework Directive objectives in the UK. , 2006, Environment international.

[24]  Mazdak Arabi,et al.  Modeling long-term water quality impact of structural BMPs , 2006 .

[25]  Ralph A. Wurbs,et al.  Scale-dependent soil and climate variability effects on watershed water balance of the SWAT model , 2002 .

[26]  Hayley J. Fowler,et al.  Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling , 2007 .

[27]  M. Arabi,et al.  Representation of agricultural conservation practices with SWAT , 2008 .

[28]  J. Wickham,et al.  Completion of the 2001 National Land Cover Database for the conterminous United States , 2007 .

[29]  Santanu Kumar Behera,et al.  Evaluation of management alternatives for an agricultural watershed in a sub-humid subtropical region using a physical process based model , 2006 .

[30]  Heejun Chang,et al.  The effects of climate change and urbanization on the runoff of the Rock Creek basin in the Portland metropolitan area, Oregon, USA , 2009 .

[31]  Timothy O. Randhir,et al.  Effect of climate change on watershed system: a regional analysis , 2008 .

[32]  Kyle R. Mankin,et al.  Applicability of targeting vegetative filter strips to abate fecal bacteria and sediment yield using SWAT , 2008 .