A geospatial method for estimating soil moisture variability in prehistoric agricultural landscapes

被引:6
|
作者
Gillreath-Brown, Andrew [1 ]
Nagaoka, Lisa [2 ,3 ]
Wolverton, Steve [2 ,3 ]
机构
[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
来源
PLOS ONE | 2019年 / 14卷 / 08期
基金
美国国家科学基金会;
关键词
LAND-SURFACE TEMPERATURE; CLIMATE-CHANGE; MAIZE PRODUCTIVITY; EASTERN WOODLANDS; GREAT-PLAINS; WATER; DROUGHT; SYSTEMS; MODELS; TIME;
D O I
10.1371/journal.pone.0220457
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
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.
引用
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页数:29
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