On the utility of land surface models for agricultural drought monitoring

被引：63

作者：

Crow, W. T. ^{[1
]}

Kumar, S. V. ^{[2
,3
]}

Bolten, J. D. ^{[2
]}

机构：

[1] USDA, Hydrol & Remote Sensing Lab, Beltsville, MD 20705 USA

[2] NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA

[3] Sci Applicat Int Corp, Beltsville, MD USA

来源：

HYDROLOGY AND EARTH SYSTEM SCIENCES | 2012年 / 16卷 / 09期

关键词：

CATCHMENT-BASED APPROACH; SOIL-MOISTURE; VEGETATION; PERFORMANCE; INDEXES; SYSTEM;

D O I：

10.5194/hess-16-3451-2012

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

The lagged rank cross-correlation between model-derived root-zone soil moisture estimates and remotely sensed vegetation indices (VI) is examined between January 2000 and December 2010 to quantify the skill of various soil moisture models for agricultural drought monitoring. Examined modeling strategies range from a simple antecedent precipitation index to the application of modern land surface models (LSMs) based on complex water and energy balance formulations. A quasi-global evaluation of lagged VI/soil moisture cross-correlation suggests, when globally averaged across the entire annual cycle, soil moisture estimates obtained from complex LSMs provide little added skill (<5% in relative terms) in anticipating variations in vegetation condition relative to a simplified water accounting procedure based solely on observed precipitation. However, larger amounts of added skill (5-15% in relative terms) can be identified when focusing exclusively on the extra-tropical growing season and/or utilizing soil moisture values acquired by averaging across a multi-model ensemble.

引用

页码：3451 / 3460

页数：10

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