Evaluating the relative importance of precipitation, temperature and land-cover change in the hydrologic response to extreme meteorological drought conditions over the North American High Plains
Evaluating the relative importance of precipitation, temperature and land-cover change in the hydrologic response to extreme meteorological drought conditions over the North American High Plains
复制标题
评估降水、温度和土地覆盖变化在北美高原极端气象干旱条件水文响应中的相对重要性
DOI：
10.5194/hess-23-1931-2019
复制
发表时间：
2019
影响因子：
6.3
通讯作者：
R. Maxwell
中科院分区：
文献类型：
--
作者：
A. Hein;L. Condon;R. Maxwell
抽象的。干旱是一种自然灾害，
在气候变化的未来。它涉及到温度的变化，
降水和/或土地覆盖，但每一个的相对贡献
这些因素对总体干旱严重程度的影响尚不清楚。在这里，我们应用
高分辨率综合水文模型的高平原探索
这些因素中的每一个的个体重要性以及
他们该模型是使用ParFlow-CLM构建的，
和地下过程的详细物理方程。
进行了扰动植被、降水和
温度分别和组合。结果显示，
降水引起蒸散量，土壤湿度，
河流流量和地下水位比温度升高或
土地覆盖的破坏。然而，这些因素不是线性加和的，
组合应用;多因素运行的一些影响来自
温度、降水和土地覆盖之间的相互作用。空间
规模在确定影响的特征方面很重要，
小尺度的非线性影响聚集成可预测的线性大尺度行为。
Abstract. Drought is a natural disaster that may become more common
in the future under climate change. It involves changes to temperature,
precipitation and/or land cover, but the relative contributions of each of
these factors to overall drought severity is not clear. Here we apply a
high-resolution integrated hydrologic model of the High Plains to explore
the individual importance of each of these factors and the feedbacks between
them. The model was constructed using ParFlow-CLM, which represents surface
and subsurface processes in detail with physically based equations.
Numerical experiments were run to perturb vegetation, precipitation and
temperature separately and in combination. Results show that decreased
precipitation caused larger anomalies in evapotranspiration, soil moisture,
stream flow and water table levels than increased temperature or
disturbed land cover did. However, these factors are not linearly additive when
applied in combination; some effects of multifactor runs came from
interactions between temperature, precipitation and land cover. Spatial
scale was important in characterizing impacts, as unpredictable and
nonlinear impacts at small scales aggregate to predictable, linear large-scale behavior.
影响因子：
4.8
作者：
Gosling, Simon N.;Zaherpour, Jamal;Zhang, Xinxin
通讯作者：
Zhang, Xinxin