Ecohydrological sensitivity to climatic variables: dissecting the water tower of Europe

Abstract

The water balance in mountain regions describes the relations between precipitation, snow accumulation and melt, evapotranspiration and soil moisture and determines the availability of water for runoff in downstream areas. Climate change is affecting the water budget of mountains at a fast pace and it has thus become a priority for hydrologists to quantify the vulnerability of each hydrological component to climate change, in order to assess the availability of water in the near future. However, our incomplete understanding of mountain hydrology implies that our knowledge about the future water supply of billions of people worldwide is limited. In this thesis, I use the ecohydrological model Tethys-Chloris (T&C) to (1) explore the responses of forests to the increasing atmospheric CO2, (2) quantify the major drivers of ecohydrological processes and their vulnerability to climate change across the European Alpine environments, and (3) partition the water budget into blue (hydrological) and green (biological) water fluxes and quantify the sensitivity of each component to temperature and precipitation change at the pan-Alpine scale. The first part of the thesis focuses on vegetation parameterization in ecohydrological models. It is a common practice to apply static vegetation parameters, although recently several studies have questioned this approach, showing that vegetation may adjust to climate change at shorter timescales than previously thought. This implies that traditional model approaches using temporally constant parameters might be biased. Recent evidence suggests that one such example of vegetation plasticity may be related to the increasing atmospheric CO2 concentrations. Through numerical simulations with T&C, I show that plasticity in key vegetation parameters can explain the changes in water and carbon vegetation fluxes in 20 forest sites in the northern Hemisphere; changes that otherwise cannot be explained. In the second part of the thesis, I explore the key drivers of Alpine ecohydrology. Applying T&C on three case studies, I quantified the drivers of ecohydrological fluxes and explored the vulnerability of different Alpine ecosystems to climate change. By correlating the spatial distribution of ecohydrological responses with that of meteorological and topographic attributes, I computed spatially explicit sensitivities of net primary productivity, transpiration, and snow cover to air temperature, radiation, and water availability to evaluate their absolute and relative importance. The results demonstrate the sharp differences between different parts of the Alps, thus highlighting the need for a high-resolution assessment of the Alpine water budget. The third part of the thesis addresses the ecohydrological sensitivity to climatic variables across the Alps. I collected a dataset from meteorological and environmental agencies and universities from six countries and combined it with new distributed products of meteorological forcing, soil properties, vegetation and snow cover to perform and validate large-scale, high-resolution ecohydrological simulations of the entire Alpine region for a period of three years (2001-2003). The focus in these simulations is on the partitioning of the pan-Alpine water budget into runoff and evapotranspiration. These simulations allowed us to quantify the sensitivity of each component of the pan-Alpine water budget to climate change and show that even during major heatwaves, Alpine vegetation keeps high transpiration rates, thus amplifying the decrease in streamflow. These unique simulations permitted vi for the first time a very detailed understanding of water sinks and sources at the scale of the Alps, and a correlation analysis revealed the potential “hot spots” of changes in the water cycle in space and time under climate change. This study also shows that recent advances in ecohydrological modeling, combined with large scale datasets and new computational capabilities, can bridge the gap between coarse-scale Earth system models and detailed catchment analyses, providing more reliable, high-resolution climate change impact assessments in the world’s mountain regions.