globalchange  > 气候减缓与适应
DOI: 10.1007/s00267-018-01133-8
WOS记录号: WOS:000458423900002
论文题名:
Meeting Water Quality Goals by Spatial Targeting of Best Management Practices under Climate Change
作者: Xu, Yuelu1; Bosch, Darrell J.1; Wagena, Moges B.2; Collick, Amy S.3; Easton, Zachary M.2
通讯作者: Bosch, Darrell J.
刊名: ENVIRONMENTAL MANAGEMENT
ISSN: 0364-152X
EISSN: 1432-1009
出版年: 2019
卷: 63, 期:2, 页码:173-184
语种: 英语
英文关键词: Spatial targeting ; Climate change ; Mathematical programming ; Economic optimization ; SWAT-VSA
WOS关键词: SWAT MODEL ; LAND-USE ; IMPACT
WOS学科分类: Environmental Sciences
WOS研究方向: Environmental Sciences & Ecology
英文摘要:

Agricultural production is a major source of nonpoint source pollution contributing 44% of total nitrogen (N) discharged to the Chesapeake Bay. The United States Environmental Protection Agency (US EPA) established the Total Maximum Daily Load (TMDL) program to control this problem. For the Chesapeake Bay watershed, the TMDL program requires that nitrogen loadings be reduced by 25% by 2025. Climate change may affect the cost of achieving such reductions. Thus, it is necessary to develop cost-effective strategies to meet water quality goals under climate change. We investigate landscape targeting of best management practices (BMPs) based on topographic index (TI) to determine how targeting would affect costs of meeting N loading goals for Mahantango watershed, PA. We use the results from two climate models, CRCM and WRFG, and the mean of the ensemble of seven climate models (Ensemble Mean) to estimate expected climate changes and the Soil and Water Assessment Tool-Variable Source Area (SWAT-VSA) model to predict crop yields and N export. Costs of targeting and uniform placement of BMPs across the entire study area (423ha) were compared under historical and future climate scenarios. Targeting BMP placement based on TI classes reduces costs for achieving water quality goals relative to uniform placement strategies under historical and future conditions. Compared with uniform placement, targeting methods reduce costs by 30, 34, and 27% under historical climate as estimated by the Ensemble Mean, CRCM and WRFG, respectively, and by 37, 43, and 33% under the corresponding estimates of future climate scenarios.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/129396
Appears in Collections:气候减缓与适应

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作者单位: 1.Virginia Tech, Dept Agr & Appl Econ, Blacksburg, VA 24061 USA
2.Virginia Tech, Dept Biol Syst Engn, Blacksburg, VA 24061 USA
3.Univ Maryland Eastern Shore, Dept Agr Food & Resource Sci, Princess Anne, MD 21853 USA

Recommended Citation:
Xu, Yuelu,Bosch, Darrell J.,Wagena, Moges B.,et al. Meeting Water Quality Goals by Spatial Targeting of Best Management Practices under Climate Change[J]. ENVIRONMENTAL MANAGEMENT,2019-01-01,63(2):173-184
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