Title

Spatio-temporal patterns of evapotranspiration from groundwater-dependent vegetation

Document Type

Journal Article

Publisher

John Wiley & Sons Ltd.

Place of Publication

United Kingdom

School

Centre for Ecosystem Management

RAS ID

23343

Comments

Originally published as: Sommer, B., Boggs, D. A., Boggs, G. S., Dijk, A., & Froend, R. (2016). Spatio‐temporal patterns of evapotranspiration from groundwater‐dependent vegetation. Ecohydrology, 9(8), 1620-1629. Available here.

Abstract

Understanding hydrological processes in water-limited systems requires consideration of temporal and spatial vegetation water use patterns at the landscape scale. We used data derived from the MODerate Resolution Imaging Spectroradiometer (MODIS) satellite instrument and interpolated climate data covering a ten-year period to contrast the spatio-temporal patterns of actual evapotranspiration (AET) from known phreatophytic and non-phreatophytic vegetation overlying a large superficial aquifer. We assessed shallow to deeper groundwater habitats and compared AET responses to seasonal and inter-annual variation in precipitation. Overall, vegetation in shallow groundwater habitats had higher AET rates during the growth season (spring and summer) than vegetation growing in deeper groundwater habitats, suggesting that the former was not physiologically constrained by water deficit. Vegetation in areas of consistently high (ground-)water availability maintained higher AET, reaching a peak of 95 mm in mid-summer. In contrast, plantation maritime pines had the highest AET rates at deep groundwater habitats. Inter-annual variability in AET correlated with rainfall and AET rates peaked two months after the majority of effective rainfall had fallen. During low rainfall years, maximum AET peaked one month earlier relative to higher rainfall years. The results of this study suggest that remote sensing of AET can give a conditional indication of where groundwater is important in supporting vegetation and can be a valuable tool in identifying management focus areas where vegetation is variably sensitive to water deficit. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

DOI

10.1002/eco.1752

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