EAR-Climate: Forest, Frost, and Flow: Snow Dydrology of spatially Heterogeneous and Hydrologically Connected Peatland Catchments
EAR-Climate: Forest, Frost, and Flow: Snow Dydrology of spatially Heterogeneous and Hydrologically Connected Peatland Catchments
批准号:
2153802
负责人:
Xue Feng
金额:
$50.52万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-07-15 至 2025-06-30
中文摘要
虽然泥炭地只覆盖了全球陆地表面的约3%,但它们储存了大约三分之一到一半的地球土壤碳。这一大型碳源的稳定性受到水的流动和储存的强烈调节。然而,由于泥炭地的空间复杂性和季节变化,尤其是在春季积雪驱动水通量的关键时期,泥炭地中的水的流动和储存仍然很难理解。该项目旨在更好地了解雪如何控制泥炭地集水区的水储存和移动,并改进它们在地球系统模型中的表现。这是通过收集新的现场数据、分析现有的长期数据并将这些数据集成到建模框架中来实现的。该项目将培养多名研究生和本科生进行跨学科研究。森林工作者、水资源管理人员和广大公众将通过实地考察,强调雪和霜冻在调节春季溪流中的重要性,以及通过公共活动庆祝许多明尼苏达州人与雪的文化联系,从而受益。北部泥炭地景观由高地和泥炭地森林、沼泽和开阔水域组成,这使得它们的水文学变得复杂。尤其是在冬季-春季过渡期,这一时期的地形是水文最活跃的,补给率和径流量都很高。该项目将调查森林、积雪和土壤霜冻之间的反馈,因为它们影响着复杂泥炭地系统中积雪、融雪的产生和浅层地下水的补给。具体地说,将收集新的实地数据,以(1)研究森林覆盖在控制积雪大小和持续时间方面的作用;(2)研究土壤霜冻在控制雪进入土壤或土壤表面的渗透方面的作用;以及(3)监测森林和泥炭地沼泽之间的水分运动。该项目团队将使用来自明尼苏达州北部马塞尔实验森林的新数据和现有的长期数据来模拟低地形泥炭地系统的水文学。由于该田地位于泥炭地分布的南缘,这项研究有可能为全球其他北部泥炭地提供一扇“未来之窗”。这些努力尤其及时,因为气候系统接近临界点,泥炭地内的碳水反馈可能会进一步加速这一点。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Although peatlands cover only ~3% of global land surfaces, they store around one-third to one-half of Earth’s soil carbon. The stability of this large carbon source is strongly regulated by the flow and storage of water. However, the flow and storage of water within peatlands remains difficult to understand due to their spatial complexity and seasonal variations, especially during a critical period in the spring when water fluxes are driven by snowmelt. This project aims to better understand how snow controls water storage and movement in peatland catchments and improve their representation within Earth System Models. This is done through collecting new field data, analyzing existing long-term data, and integrating these data into a modeling framework. This project will train multiple graduate students and undergraduate students in interdisciplinary research. Foresters, water resource managers, and the public at large will benefit through field tours highlighting the importance of snow and frost in regulating spring streamflow, as well as through public events celebrating the cultural connections that many Minnesotans have with snow. Northern peatland landscapes consist of a mix of upland and peatland forests, bogs, and open water, which complicates their hydrology. This is especially the case during the winter-spring transition period when the landscape is the most hydrologically active, with high recharge and streamflow rates. This project will investigate the feedbacks between forests, snowpack, and soil frost as they influence snow accumulation, snowmelt generation, and recharge of shallow groundwater in complex peatland systems. Specifically, new field data will be collected to (1) examine the role of forest cover in controlling snowpack size and duration; (2) study the role of soil frost in controlling the infiltration of snow into soils or over the soil surface; and (3) monitor the movement of water between forests and peatland bogs. The project team will use the new data and existing long-term data from the Marcell Experimental Forest in northern Minnesota to model the hydrology of low-relief, peatland systems. With the field site situated at the southern edge of peatland distributions, this study has the potential to provide a “window into the future” for other northern peatlands across the globe. These efforts are especially timely as the climate system approaches tipping points that may be further accelerated by carbon-water feedbacks within peatlands.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
CAREER: A cross-scale, data-efficient approach to understanding plant hydraulic regulation using optimization and maximum entropy
-
批准号:2045610
-
项目类别:Continuing Grant
-
资助金额:$67.63万
-
财政年份:2021
-
负责人:Xue Feng
-
依托单位:
SBIR Phase II: A Non-invasive Image-based Skeletal Muscle Analytics Tool
-
批准号:1556135
-
项目类别:Standard Grant
-
资助金额:$74.76万
-
财政年份:2016
-
负责人:Xue Feng
-
依托单位:
STTR Phase I: A Non-invasive Image‐based Skeletal Muscle Analytics Tool
-
批准号:1417208
-
项目类别:Standard Grant
-
资助金额:$22.5万
-
财政年份:2014
-
负责人:Xue Feng
-
依托单位:
海外基金