New Mexico Geological Society
New Mexico Geological Society
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新墨西哥州地质学会
DOI：
10.1007/978-3-030-56901-3_6
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发表时间：
2017
影响因子：
2.2
通讯作者：
Garrett Gamache
中科院分区：
文献类型：
--
作者：
Kaytan;a.;KelKar;John;r.;Giardino;John ViteK;Garrett Gamache
美国西部淡水供应有限，加上农业和城市需求不断增长，迫使城镇严重依赖山区水资源供应国内用水。因此，必须预测天气趋势和变化对水资源的影响，以确保满足当前和未来的用水需求。了解水文响应有关的天气现象在山区，需要一个答案的问题：天气现象减少或转移山地径流制度的时间和体积？时间序列分析和一般最小二乘法（GLS）回归被用来确定是否存在联系的天气现象和时间和流量的Uncompahgre，圣米格尔和阿尼马斯河在西南部科罗拉多。时间序列分析未显示三个流域径流时间的显著（α = 0.05）趋势。与GLS回归，在0.99的显着性水平，选定的变量解释说，56%的方差与春天脉冲的发病日期，84%的方差与峰值流量的时间，和82%的方差与升高的流量结束或消退的日期。我们的研究说明了必要的基础，可用于确定特定地点的径流制度的变化，使关键的水资源管理决策更准确。209
The limited availability of fresh water coupled with growing agricultural and urban demands in the western United States is forcing cities and towns to be heavily dependent on montane water resources for domestic supplies. Thus, predicting the impact of weather trends and variability on water resources is necessary to ensure that current and future demands for water can be met. Understanding the hydrologic response related to weather phenomena in montane regions, requires an answer to the question: Do weather phenomena reduce or shift the timing and volume of montane streamflow regimes? Time-series analysis and General-Least-Squares (GLS) regression were used to determine if a link exists between weather phenomena and the timing and volume of discharge for the Uncompahgre, San Miguel, and Animas Rivers in southwestern Colorado. Time-series analysis did not reveal significant (α = 0.05) trends in the timing of streamflow for the three drainage basins. With GLS regression, at a level of 0.99 significance, the selected variables explained that 56% of the variance was associated with the onset date of the spring-pulse, 84% of the variance was associated with the timing of peak streamflow, and 82% of the variance was associated with the date at which elevated streamflow ends, or subsides. Our research illustrates the necessary foundation that can be used to determine site-specific changes in streamflow regimes to make critical water resource management decisions more accurate. 209