1. Assessing the combined effect of Carbon-Water dynamics on hydrological processes in Brazil
- Author
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Brown, Jamie R C and Brown, Jamie R C
- Abstract
Vegetation dynamics optimally adapt to given environmental conditions by maximising their net carbon profit. If we model these processes, can they help us understand hydrological fluxes across different climates? Furthermore, can this optimality modelling further our understanding on the sensitivity of carbon-water mechanisms in vegetation to changes in CO2? This thesis uses a vegetation optimality model across multiple biomes in Brazil to examine the extent to which it can answer these questions. Firstly, we examine the reliability and suitability of five high-resolution meteorological gridded products (ERA5-Land, GLDAS2.0, GLDAS2.1, the BNMD and MSWEPv2.2 (precipitation only)) for seven variables (precipitation, air temperature, wind speed, pressure, specific humidity, and downward shortwave and longwave radiation) against eleven flux towers spanning five biomes across Brazil. At the daily scale analysis showed that MSWEPv2.2 outperformed the others for precipitation whilst ERA5-Land showed the most consistency for all other variables. Secondly, we show that the Vegetation Optimality Model (VOM), is successfully able to reproduce patterns of evapotranspiration (ET) at several sites, with a stronger correlation at more seasonal sites (r values ranging 0.25 – 0.69 across sites). VOM is a developed model that attempts to quantify the physiological processes of a plant growth carbon-capture cost-benefit system through describing carbon-water dynamics. Results show the importance of root dynamics in the success of the model; the minimal calibration needed per site reflects the strong physiological understanding behind it. Finally, we show declines in ET across an increasing atmospheric CO2 gradient, with dampened impacts on hydrological processes through modelling long-term adaptations in vegetation (reductions from 0.7-6.0% over an increase of 77 ppm CO2). Overall, this thesis advances our knowledge in relation to the questions above i
- Published
- 2023