Characterising groundwater use by vegetation using a surface energy balance model and satellite observations of land surface temperature |
| |
| Affiliation: | 1. School of Geography, Planning and Environmental Management, University of Queensland, Brisbane Qld 4072, Australia;2. CSIRO, Energy, Christian Laboratory, Black Mountain, Canberra ACT 2601, Australia;3. CSIRO, Land and Water, Christian Laboratory, Black Mountain, Canberra ACT 2601, Australia;1. Department of Civil Engineering, Thiagarajar College of Engineering, Madurai, 625015, Tamilnadu, India;2. Department of Civil Engineering, National Institute of Technology, Trichy, Tamilnadu, India;3. Department of Agricultural Engineering, AC&RI, Madurai, 625104, India;1. State Key Laboratory of Oasis Desert and Ecology, Xinjiang Institute of Ecology and Geography, CAS, Urumqi 830011, China;2. University of Chinese Academy of Sciences, Beijing 100049, China;1. Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, P.O. Box 47, 6700 AA Wageningen, The Netherlands;2. Forest Ecology & Management, Wageningen University, P.O. Box 47, 6700 AA Wageningen, The Netherlands;3. Universidad Austral de Chile, Instituto de Ciencias Ambientales y Evolutivas, Facultad de Ciencias. Valdivia, Chile;1. Institute for Applied Ecology and Collaborative Research Network for Murray-Darling Basin Futures, University of Canberra, ACT 2601, Australia;2. International Centre for Applied Climate Sciences, University of Southern Queensland, Toowoomba QLD 4350, Australia;3. Faculty of Health, Engineering and Sciences, University of Southern Queensland, Toowoomba QLD 4350, Australia;4. Digital Futures CRN, University of Southern Queensland, Toowoomba QLD 4350, Australia;5. National Centre for Engineering in Agriculture, University of Southern Queensland, Toowoomba, QLD 4350, Australia;1. School of Earth and Environmental Sciences, University of Queensland, Brisbane, Qld 4072, Australia;2. CSIRO Energy, GPO Box 1700, Canberra ACT 2601, Australia;3. CSIRO Land and Water, Sandy Bay, Hobart TAS, 7005, Australia;4. CSIRO Land and Water, GPO Box 1700, Canberra ACT 2601, Australia;1. College of Water Conservancy, Shenyang Agricultural University, Shenyang 110866, China;2. Institute of Water Resources and Environment, Jilin University, Changchun 130021, China |
| |
| Abstract: | This study presents a novel ‘model-data’ approach to detect groundwater-dependent vegetation (GDV), through differences in modelled and observed land surface temperatures (LST) in space and time. Vegetation groundwater use is inferred where modelled LST exceeds observed LST by more than a threshold determined from consideration of systematic and random errors in model and observations. Modelled LST was derived from a surface energy balance model and LST observations were obtained from Terra-MODIS thermal imagery. The model-data approach, applied in the Condamine River Catchment, Queensland, Australia, identified GDV coincident to existing mapping. GDV were found to use groundwater up to 48% of the time and for as many as 56 consecutive days. Under driest of conditions, groundwater was estimated to contribute up to 0.2 mm h−1 to total ET for GDV. The ability to both detect the location and water-use dynamics of GDV is a significant advancement on previous remote-sensing GDV methods. |
| |
| Keywords: | Groundwater-dependent vegetation Land surface temperature Surface energy balance modelling Satellite remote sensing |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
