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https://hdl.handle.net/1959.11/57252
Title: | Extracting Pasture Evapotranspiration Parameters from Proximal Sensing and Mathematical Modelling |
Contributor(s): | Alam, Muhammad Shahinur (author); Lamb, David (supervisor) ; Mccarthy, Cheryl (supervisor); Rahman, Muhammad (supervisor) ; Warwick, Nigel William (supervisor) |
Conferred Date: | 2020-02-07 |
Copyright Date: | 2019-10 |
Thesis Restriction Date until: | 2120-02-07 |
Handle Link: | https://hdl.handle.net/1959.11/57252 |
Related DOI: | 10.1016/j.compag.2018.02.008 10.1016/j.agwat.2018.10.042 |
Related Research Outputs: | https://hdl.handle.net/1959.11/57253 |
Abstract: | | Knowledge of crop evapotranspiration is crucial for irrigation decision making. An appropriate, user-friendly and time-efficient means of inferring such information is therefore essential. In this study, a closed hemispherical chamber was instrumented, calibrated and deployed in the field for measuring actual evapotranspiration of a vital pasture species, Tall Fescue (Festuca arundinacea). The pasture crop coefficient (Kc) was calculated from the measured instantaneous evapotranspiration and reference crop evapotranspiration (ETo) for a range of growth stages. Also the relationship between Kc and Normalized Difference Vegetation Index (NDVI) as measured using an active optical sensor was established. Using the FAO dual crop coefficient approach and the hemispherical chamber, a technique for partitioning evapotranspiration components was developed. The components of evapotranspiration in terms of basal crop coefficient (Kcb) and soil evaporation coefficient (Ke) were expressed relative to canopy NDVI and Leaf Area Index (LAI). A theoretical model for estimating transpiration was also developed by scaling up stomatal conductance to canopy level in a controlled glasshouse environment. The model was validated against the measured transpiration.
Publication Type: | Thesis Doctoral |
Fields of Research (FoR) 2020: | 300206 Agricultural spatial analysis and modelling 300405 Crop and pasture biomass and bioproducts 460306 Image processing |
Socio-Economic Objective (SEO) 2020: | 100503 Native and residual pastures 100505 Sown pastures (excl. lucerne) 180601 Assessment and management of terrestrial ecosystems |
HERDC Category Description: | T2 Thesis - Doctorate by Research |
Description: | | Please contact rune@une.edu.au if you require access to this thesis for the purpose of research or study.
Awarded the Chancellor's Doctoral Research Medal
Appears in Collections: | School of Environmental and Rural Science School of Science and Technology Thesis Doctoral
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