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Remote Sens. 2016, 8(5), 428; doi:10.3390/rs8050428

Advantages of Using Microwave Satellite Soil Moisture over Gridded Precipitation Products and Land Surface Model Output in Assessing Regional Vegetation Water Availability and Growth Dynamics for a Lateral Inflow Receiving Landscape

1
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China
2
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
3
CSIRO Land and Water, GPO Box 1666, Canberra 2601, ACT, Australia
4
Australian Research Council Centre of Excellence for Climate System Science, Sydney, NSW 2052, Australia
5
VanderSat B.V., Huygensstraat 34, Noordwijk 2201 DK, The Netherlands
6
Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia
7
Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor, MI 48109, USA
8
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
9
Department of Earth Sciences, Faculty of Earth and Life Sciences, VU University Amsterdam, Amsterdam 1081 HV, The Netherlands
*
Author to whom correspondence should be addressed.
Academic Editors: Magaly Koch and Prasad S. Thenkabail
Received: 6 March 2016 / Revised: 1 May 2016 / Accepted: 12 May 2016 / Published: 20 May 2016
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Abstract

To improve the understanding of water–vegetation relationships, direct comparative studies assessing the utility of satellite remotely sensed soil moisture, gridded precipitation products, and land surface model output are needed. A case study was investigated for a water-limited, lateral inflow receiving area in northeastern Australia during December 2008 to May 2009. In January 2009, monthly precipitation showed strong positive anomalies, which led to strong positive soil moisture anomalies. The precipitation anomalies disappeared within a month. In contrast, the soil moisture anomalies persisted for months. Positive anomalies of Normalized Difference Vegetation Index (NDVI) appeared in February, in response to water supply, and then persisted for several months. In addition to these temporal characteristics, the spatial patterns of NDVI anomalies were more similar to soil moisture patterns than to those of precipitation and land surface model output. The long memory of soil moisture mainly relates to the presence of clay-rich soils. Modeled soil moisture from four of five global land surface models failed to capture the memory length of soil moisture and all five models failed to present the influence of lateral inflow. This case study indicates that satellite-based soil moisture is a better predictor of vegetation water availability than precipitation in environments having a memory of several months and thus is able to persistently affect vegetation dynamics. These results illustrate the usefulness of satellite remotely sensed soil moisture in ecohydrology studies. This case study has the potential to be used as a benchmark for global land surface model evaluations. The advantages of using satellite remotely sensed soil moisture over gridded precipitation products are mainly expected in lateral-inflow and/or clay-rich regions worldwide. View Full-Text
Keywords: remote sensing; soil moisture; precipitation; NDVI; vegetation remote sensing; soil moisture; precipitation; NDVI; vegetation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Chen, T.; McVicar, T.R.; Wang, G.; Chen, X.; de Jeu, R.A.M.; Liu, Y.Y.; Shen, H.; Zhang, F.; Dolman, A.J. Advantages of Using Microwave Satellite Soil Moisture over Gridded Precipitation Products and Land Surface Model Output in Assessing Regional Vegetation Water Availability and Growth Dynamics for a Lateral Inflow Receiving Landscape. Remote Sens. 2016, 8, 428.

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