Contrasting stream water temperature responses to global change in the Mid-Atlantic Region of the United States: A process-based modeling study
Contrasting stream water temperature responses to global change in the Mid-Atlantic Region of the United States: A process-based modeling study
复制标题
美国中大西洋地区溪流水温对全球变化的响应对比:基于过程的建模研究
DOI:
10.1016/j.jhydrol.2021.126633
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发表时间:
2021
影响因子:
6.4
通讯作者:
Li, Ya
中科院分区:
文献类型:
--
作者:
Yao, Yuanzhi;Tian, Hanqin;Kalin, Latif;Pan, Shufen;Friedrichs, Marjorie A.M.;Wang, Jing;Li, Ya
The accurate estimation of stream water temperature is essential for understanding environmental controls on the structure and functioning of aquatic ecosystems. Few studies have coupled soil and stream water temperatures to capture the synergy of thermal balances between terrestrial and riverine systems. As a result, little is known about how multiple environmental stresses have affected water temperature, particularly for different orders of streams. Here we incorporated a new water transport scheme into the Dynamic Land Ecosystem Model (DLEM) to predict water temperature in 1st order and higher-order streams (>1st order). Driven by a 4-km geo-referenced dataset of multiple environmental factors, our new water temperature model was utilized to predict the spatiotemporal variations of water temperature in the U.S. Mid-Atlantic Region during 1900–2015. Results revealed that water temperature during 1970–2015 increased significantly (p< 0.05), and the rate of increase of the 1st order streams 0.32 °C∙decade−1is higher than that of higher-order streams 0.28 °C ∙ decade−1. The buffering effect of groundwater on water temperature in 1st order streams diminished under the context of climate warming. Factorial analysis showed that climate change and variability explain most of the changes (~80%) in stream water temperature since 1900. Land-use conversions (mostly from cropland to forest), CO2fertilization, and land nitrogen management collectively explained a greater percent of change in water temperature in 1st order streams (24%) than higher-order streams (9%), implying that 1st order streams are particularly vulnerable to human activities.
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DOI:
--
发表时间:
2005
期刊:
影响因子:
--
作者:
B. Hassett;M. Palmer;E. Bernhardt;Sean M. C. Smith;J. Carr;D. Hart
通讯作者:
D. Hart
影响因子:
5.4
作者:
BROWN, GW;KRYGIER, JT
通讯作者:
KRYGIER, JT
DOI:
--
发表时间:
2012
期刊:
影响因子:
--
作者:
J. Yearsley
通讯作者:
J. Yearsley
影响因子:
5.4
作者:
Burns, Erick R.;Zhu, Yonghui;Dunham, Jason B.
通讯作者:
Dunham, Jason B.
影响因子:
6.7
作者:
Arismendi, Ivan;Safeeq, Mohammad;Johnson, Sherri L.
通讯作者:
Johnson, Sherri L.