globalchange  > 全球变化的国际研究计划
DOI: 10.1371/journal.pone.0220457
WOS记录号: WOS:000485033100013
论文题名:
A geospatial method for estimating soil moisture variability in prehistoric agricultural landscapes
作者: Gillreath-Brown, Andrew1; Nagaoka, Lisa2,3; Wolverton, Steve2,3
通讯作者: Gillreath-Brown, Andrew
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2019
卷: 14, 期:8
语种: 英语
WOS关键词: LAND-SURFACE TEMPERATURE ; CLIMATE-CHANGE ; MAIZE PRODUCTIVITY ; EASTERN WOODLANDS ; GREAT-PLAINS ; WATER ; DROUGHT ; SYSTEMS ; MODELS ; TIME
WOS学科分类: Multidisciplinary Sciences
WOS研究方向: Science & Technology - Other Topics
英文摘要:

Prehistoric peoples chose farming locations based on environmental conditions, such as soil moisture, which plays a crucial role in crop production. Ancestral Pueblo communities of the central Mesa Verde region became increasingly reliant on maize agriculture for their subsistence needs by AD 900. Prehistoric agriculturalists (e.g., Ancestral Pueblo farmers) were dependent on having sufficient soil moisture for successful plant growth. To better understand the quality of farmland in terms of soil moisture, this study develops a static geospatial soil moisture model, the Soil Moisture Proxy Model, which uses soil and topographic variables to estimate soil moisture potential across a watershed. The model is applied to the semi-arid region of the Goodman watershed in the central Mesa Verde region of southwestern Colorado. We evaluate the model by comparing the Goodman watershed output to two other watersheds and to soil moisture sensor values. The simple framework can be used in other regions of the world, where water is also an important limiting factor for farming. The general outcome of this research is an improved understanding of potential farmland and human-environmental relationships across the local landscape.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/145669
Appears in Collections:全球变化的国际研究计划

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作者单位: 1.Washington State Univ, Dept Anthropol, Pullman, WA 99164 USA
2.Univ North Texas, Dept Geog & Environm, Denton, TX USA
3.Univ North Texas, Adv Environm Res Inst, Denton, TX USA

Recommended Citation:
Gillreath-Brown, Andrew,Nagaoka, Lisa,Wolverton, Steve. A geospatial method for estimating soil moisture variability in prehistoric agricultural landscapes[J]. PLOS ONE,2019-01-01,14(8)
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