Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach

被引:10
|
作者
Qian, Song S. [1 ]
Kennen, Jonathan G. [2 ]
May, Jason [3 ]
Freeman, Mary C. [4 ]
Cuffney, Thomas F. [5 ]
机构
[1] Univ Toledo, Dept Environm Sci, Toledo, OH 43606 USA
[2] US Geol Survey, West Trenton, NJ 08628 USA
[3] US Geol Survey, Sacramento, CA 95819 USA
[4] US Geol Survey, Eastern Ecol Sci Ctr, Athens, GA 30602 USA
[5] US Geol Survey, Raleigh, NC 27607 USA
关键词
Bayesian network; Climate change; Ecological condition; Regression; Streamflow metrics; Watershed; HYDROLOGIC ALTERATION; PART; MACROINVERTEBRATES; VARIABILITY; RESPONSES; QUALITY;
D O I
10.1016/j.watres.2021.117685
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A continuous-variable Bayesian network (cBN) model is used to link watershed development and climate change to stream ecosystem indicators. A graphical model, reflecting our understanding of the connections between climate change, weather condition, loss of natural land cover, stream flow characteristics, and stream ecosystem indicators is used as the basis for selecting flow metrics for predicting macroinvertebrate-based indicators. Selected flow metrics were then linked to variables representing watershed development and climate change. We fit the model to data from two river basins in southeast US and the resulting model was used to simulate future stream ecological conditions using projected future climate and development scenarios. The three climate models predicted varying ecological condition trajectories, but similar worst-case ecological conditions. The established modeling approach couples mechanistic understanding with field data to develop predictions of management relevant variables across a heterogeneous landscape. We discussed the transferability of the modeling approach.
引用
收藏
页数:11
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