| 项目编号: | 1558675
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| 项目名称: | Landscape controls on hydrologic responses to long-term climate oscillations |
| 作者: | Ryan Emanuel
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| 承担单位: | North Carolina State University
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| 批准年: | 2016
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| 开始日期: | 2016-04-01
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| 结束日期: | 2019-03-31
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| 资助金额: | 214952
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| 资助来源: | US-NSF
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| 项目类别: | Standard Grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Geosciences - Earth Sciences
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| 英文关键词: | enso
; hydrologic response
; project
; climate impact
; watershed
; watershed response
; long-term climate change
; el niño-southern oscillation
; long-term climate oscillation
; hydrological response
; multi-year climate oscillation
; precipitation response
; climate-streamflow interaction
; climate condition
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| 英文摘要: | This project seeks to understand and quantify hydrologic responses to long-term climate oscillations, such as the El Niño-Southern Oscillation (ENSO), for 2733 individual watersheds across the conterminous United States. These watersheds represent a wide range of terrain, land cover, land use, and climate conditions, and they include varying degrees of human disturbance. With such an expansive dataset, the project will provide insight as to how and why watersheds respond differently (or not at all) to ENSO. The study will improve scientific knowledge and understanding about climate impacts on the terrestrial water cycle, not only for multi-year climate oscillations but also for long-term climate change, which are both critical for managing water supplies, planning civil infrastructure, and preparing for natural disasters. The project will also provide geospatially-oriented tools to improve hydrology education for K12 and university students while providing postdoctoral training for an emerging hydrologist.
Preliminary analyses suggest that watersheds filter ENSO signals differently, even after accounting for variations in precipitation responses to ENSO across the country. Spatial characteristics associated with internal watershed organization are hypothesized to explain a significant amount of the observed variability in watershed responses to ENSO. This hypothesis is rooted in geomorphological instantaneous unit hydrograph (GIUH) theory, which links the spatial organization of watersheds to their hydrologic responses. This project builds on the GIUH framework and applies it to long-term climate phenomena such as ENSO, using statistical learning methods along with hydrological modeling to test hypotheses. Overall, the work seeks to improve scientific knowledge and understanding about climate impacts on the terrestrial water cycle by bridging the gap between mechanistic, watershed-scale studies of hydrological responses and large-scale studies of climate-streamflow interactions that are predominantly statistical in nature. This work acknowledges the so-called "big data" nature of many geospatial research problems in the hydrologic sciences and brings statistical learning methods, currently under-utilized in the field, to bear on large, publicly available datasets. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/92630
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| Appears in Collections: | 全球变化的国际研究计划
科学计划与规划
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| Recommended Citation: | |
Ryan Emanuel. Landscape controls on hydrologic responses to long-term climate oscillations. 2016-01-01.
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