search query: @supervisor Kummu, Matti / total: 5
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| Author: | Bloch, Samuel |
| Title: | Calculating evapotranspiration: towards an operational Global Ecosystem Restoration Index (GERI) |
| Publication type: | Master's thesis |
| Publication year: | 2016 |
| Pages: | 23 s. + liitt. 6 Language: eng |
| Department/School: | Insinööritieteiden korkeakoulu |
| Main subject: | Water and Environmental Engineering (R3005) |
| Supervisor: | Kummu, Matti |
| Instructor: | |
| Electronic version URL: | http://urn.fi/URN:NBN:fi:aalto-201612226262 |
| Location: | P1 Ark Aalto 6437 | Archive |
| Keywords: | evapotranspiration biodiversity land degradation remote-sensing |
| Abstract (eng): | The current decline in biodiversity prompted researchers to find indicators that would help them monitor and counter this trend. The Global Ecosystem Restoration Index (GERI) is such an indicator; it is dedicated to fight land degradation and restore 15% of degraded land by the end of the decade, a biodiversity target set in Aichi in 2010 by the members of the Convention on Biological Diversity. In this context, this study focuses on the computation of evapotranspiration to develop an indicator, the Evapotranspiration Ratio (ER), which would allow researchers to detect degradation hotspots in a given area, through the analysis of temporal trends. Based on the Penman-Monteith equation, the model was adapted from a previous study and improved; meteorological data from the global reanalysis ERA-Interim were included, and a workflow was designed so that future users would have few manual manipulations to do before obtaining their results. Validation was performed using field data from Coussoul, in the south of France; it returned mixed results, with meteorological data behaving very well while other variables showed rather bad correlation with physical measurements. In the end, simulations in the period 2003-2015 were performed and correlation between time and ER was calculated, with significant points (p<0.05, r2>0.8) labelled as potentially degraded. |
| ED: | 2017-01-08 |
INSSI record number: 55300
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