期刊
HYDROLOGICAL PROCESSES
卷 29, 期 10, 页码 2331-2345出版社
WILEY
DOI: 10.1002/hyp.10363
关键词
stream temperature prediction; urban hydrology; land use change; riparian shading
资金
- US Environmental Protection Agency Science [R835195]
- EPA [150179, R835195] Funding Source: Federal RePORTER
Stream temperatures in urban watersheds are influenced to a high degree by changes in landscape and climate, which can occur at small temporal and spatial scales. Here, we describe a modelling system that integrates the distributed hydrologic soil vegetation model with the semi-Lagrangian stream temperature model RBM. It has the capability to simulate spatially distributed hydrology and water temperature over the entire network at high time and space resolutions, as well as to represent riparian shading effects on stream temperatures. We demonstrate the modelling system through application to the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The results suggest that the model was able to produce realistic streamflow and water temperature predictions that are consistent with observations. We use the modelling construct to characterize impacts of land use change and near-stream vegetation change on stream temperatures and explore the sensitivity of stream temperature to changes in land use and riparian vegetation. The results suggest that, notwithstanding general warming as a result of climate change over the last century, there have been concurrent increases in low flows as a result of urbanization and deforestation, which more or less offset the effects of a warmer climate on stream temperatures. On the other hand, loss of riparian vegetation plays a more important role in modulating water temperatures, in particular, on annual maximum temperature (around 4 degrees C), which could be mostly reversed by restoring riparian vegetation in a fairly narrow corridor - a finding that has important implications for management of the riparian corridor. Copyright (c) 2014 John Wiley & Sons, Ltd.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据