Modellierung des hydrologischen Kreislaufs und der Interaktion mit Vegetation im Zusammenhang mit dem Klimawandel

There is a growing interest to extend climate change predictions to smaller, catchment-size scales and identify their implications on hydrological and ecological processes. This thesis presents a blueprint methodology for studying climate change impacts on eco-hydrological dynamics at the plot and catchment scales. A weather generator, AWE-GEN, is developed to produce input meteorological variables to eco-hydrological models. The weather generator is also used for the simulation of future climate scenarios, as inferred from climate models. Using a Bayesian technique, a stochastic downscaling procedure derives the distributions of factors of change for several climate statistics from a multi-model ensemble of outputs of General Circulation Models. The factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. The time series obtained for present and future climates serve as input to a newly developed eco-hydrological model Tethys-Chloris. The methodology is applied to simulate the present (1961-2000) and future (2081-2100) hydrological regimes for the area of Tucson (AZ, U.S.A.). A general reduction of precipitation and a significant increase of air temperature are inferred with the downscaling procedure. The eco-hydrological model is successively used to detect changes in the surface water partition and vegetation dynamics for a desert shrub ecosystem, typical of the semi-arid climate of southern Arizona. An appreciable effect of climate change can be observed in metrics of vegetation performance. The negative impact on vegetation due to amplification of water stress in a warmer and dryer climate is partially offset by the effect of the augment of carbon dioxide concentration. Additionally, an increase of runoff and a depletion of soil moisture with consequence in deep recharge are detected. Such an outcome might affect water availability and risk management in semi-arid systems.Es besteht derzeit ein wachsendes wissenschaftliches Interesse daran, Vorhersagen zum Klimawandel auch auf eine kleinere Skala zu übertragen. Diese Arbeit präsentiert eine Vorgehensweise um Einflüsse des Klimawandels auf ökologisch-hydrologische Dynamiken auf der Einzugsgebietskala nachzuvollziehen. Dazu wurde ein Wettergenerator, AWEGEN, entwickelt, der meteorologische Variablen ausgibt. Der Wettergenerator wird darüber hinaus für die Simulation zukünftiger Klimaszenarien genutzt, die aus den Klimamodellen hervorgehen. Mittels einer Bayes-Technik werden stochastische Downscaling-Prozeduren zur Verteilung der Wechselfaktoren für verschiedene Klimastatistiken aus einem Multimodell-Ensemble ermittelt, die auf Daten des Globalen Klimamodells beruhen. Die Wechselfaktoren werden danach auf die aus Beobachtungen erhaltenen Statistiken angewendet, um die Parameter des Wettergenerators zu überprüfen. Die Zeitreihen dienen als Ausgangsdaten für das neu entwickelte öko-hydrologische Modell Tethys-Chloris. Diese Methode wird angewendet, um die momentanen (1961-2000) sowie zukünftigen (2081-2100) hydrologischen Regime im Gebiet von Tucson (Arizona, U.S.A.) zu simulieren. Dabei ließen sich eine generelle Reduzierung des Niederschlags und eine Zunahme der Lufttemperatur feststellen. Das öko-hydrologische Modell wurde im Anschluss genutzt, um Änderungen in der Verteilung der Oberflächengewässer und der Vegetationsdynamik für ein Wüsten-Buschland Ökosystems nachzuweisen, wie es für das semi-aride Klima typisch ist. Ein nennenswerter Effekt des Klimawandels kann in den Metriken der Vegetationsleistung beobachtet werden. Der negative Einfluss auf die Vegetation aufgrund von Wassermangel in einem wärmeren und trockeneren Klima wird teilweise ausgeglichen durch den Effekt einer verbesserten Kohlendioxidversorgung. Zusätzlich wird eine Erhöhung des (Oberflächen-)Abflusses beobachtet. Diese Ergebnisse beeinflussen die Wasserverfügbarkeit und das Risikomanagement im semi-ariden System

Investigating Interannual Variability of Precipitation at the Global Scale: Is There a Connection with Seasonality?

Abstract Interannual variability of precipitation can directly or indirectly affect many hydrological, ecological, and biogeochemical processes that, in turn, influence climate. Despite the significant importance of the phenomenon, few studies have attempted to elucidate spatial patterns of this variability at the global scale. This study uses land gauge precipitation records of the Global Historical Climatology Network, version 2, as well as reanalysis data to provide an assessment of the spatial organization of characteristics of precipitation interannual variability. The coefficient of variation, skewness, and short- and long-range dependence of the precipitation variability are analyzed. Among the major inferences is that the coefficient of variation of annual precipitation shows a significant correlation with intra-annual seasonality. Specifically, subyearly precipitation anomalies occurring in locations with pronounced seasonality affect the total yearly amount, imposing a higher variability in the annual precipitation fluctuations. Furthermore, the study illustrates that a positive skewness of the distribution of annual precipitation is a robust property worldwide and its magnitude is related to the coefficient of variation. Additionally, annual precipitation exhibits very weak small-lag autocorrelation. Conversely, the intensity of long-memory–long-range dependence is significantly larger than zero, hinting that organized long-term variations are an important feature of the interannual variability of precipitation

Temperature effects on the spatial structure of heavy rainfall modify catchment hydro-morphological response

Heavy rainfall is expected to intensify with increasing temperatures, which will likely affect rainfall spatial characteristics. The spatial variability of rainfall can affect streamflow and sediment transport volumes and peaks. Yet, the effect of climate change on the small-scale spatial structure of heavy rainfall and subsequent impacts on hydrology and geomorphology remain largely unexplored. In this study, the sensitivity of the hydro-morphological response to heavy rainfall at the small-scale resolution of minutes and hundreds of metres was investigated. A numerical experiment was conducted in which synthetic rainfall fields representing heavy rainfall events of two types, stratiform and convective, were simulated using a space-time rainfall generator model. The rainfall fields were modified to follow different spatial rainfall scenarios associated with increasing temperatures and used as inputs into a landscape evolution model. The experiment was conducted over a complex topography, a medium-sized (477 km2) Alpine catchment in central Switzerland. It was found that the responses of the streamflow and sediment yields are highly sensitive to changes in total rainfall volume and to a lesser extent to changes in local peak rainfall intensities. The results highlight that the morphological components are more sensitive to changes in rainfall spatial structure in comparison to the hydrological components. The hydro-morphological features were found to respond more to convective rainfall than stratiform rainfall because of localized runoff and erosion production. It is further shown that assuming heavy rainfall to intensify with increasing temperatures without introducing changes in the rainfall spatial structure might lead to overestimation of future climate impacts on basin hydro-morphology

Impacts of fertilization on grassland productivity and water quality across the European Alps under current and warming climate: Insights from a mechanistic model

Alpine grasslands sustain local economy by providing fodder for livestock. Intensive fertilization is common to enhance their yields, thus creating negative externalities on water quality that are difficult to evaluate without reliable estimates of nutrient fluxes. We apply a mechanistic ecosystem model, seamlessly integrating land-surface energy balance, soil hydrology, vegetation dynamics, and soil biogeochemistry, aiming at assessing the grassland response to fertilization. We simulate the major water, carbon, nutrient, and energy fluxes of nine grassland plots across the broad European Alpine region. We provide an interdisciplinary model evaluation by confirming its performance against observed variables from different datasets. Subsequently, we apply the model to test the influence of fertilization practices on grassland yields and nitrate (NO$_{3}$$^{-}$) losses through leaching under both current and modified climate scenarios. Despite the generally low NO$_{3}$$^{-}$ concentration in groundwater recharge, the variability across sites is remarkable, which is mostly (but not exclusively) dictated by elevation. In high-Alpine sites, short growing seasons lead to less efficient nitrogen (N) uptake for biomass production. This combined with lower evapotranspiration rates results in higher amounts of drainage and NO$_{3}$$^{-}$ leaching to groundwater. Scenarios with increased temperature lead to a longer growing season characterized by higher biomass production and, consequently, to a reduction of water leakage and N leaching. While the intersite variability is maintained, climate change impacts are stronger on sites at higher elevations. The local soil hydrology has a crucial role in driving the NO$_{3}$$^{-}$ use efficiency. The commonly applied fixed threshold limit on fertilizer N input is suboptimal. We suggest that major hydrological and soil property differences across sites should be considered in the delineation of best practices or regulations for management. Using distributed maps informed with key soil and climatic attributes or systematically implementing integrated ecosystem models as shown here can contribute to achieving more sustainable practices

An ecohydrological journey of 4500 years reveals a stable but threatened precipitation–groundwater recharge relation around Jerusalem

Groundwater is a key water resource in semiarid and seasonally dry regions around the world, which is replenished by intermittent precipitation events and mediated by vegetation, soil, and regolith properties. Here, a climate reconstruction of 4500 years for the Jerusalem region was used to determine the relation between climate, vegetation, and groundwater recharge. Despite changes in air temperature and vegetation characteristics, simulated recharge remained linearly related to precipitation over the entire analyzed period, with drier decades having lower rates of recharge for a given annual precipitation due to soil memory effects. We show that in recent decades, the lack of changes in the precipitation–groundwater recharge relation results from the compensating responses of vegetation to increasing CO(2), i.e., increased leaf area and reduced stomatal conductance. This multicentury relation is expected to be modified by climate change, with changes up to −20% in recharge for unchanged precipitation, potentially jeopardizing water resource availability

Uncertainty in high‐resolution hydrological projections: Partitioning the influence of climate models and natural climate variability

A major challenge in assessing the impacts of climate change on hydrological processes lies in dealing with large degrees of uncertainty in the future climate projections. Part of the uncertainty is owed to the intrinsic randomness of climate phenomena, which is considered irreducible. Additionally, modelling the response of hydrological processes to the changing climate requires the use of a chain of numerical models, each of which contributes some degree of uncertainty to the final outputs. As a result, hydrological projections, despite the progressive increase in the accuracy of the models along the chain, still display high levels of uncertainty, especially at small temporal and spatial scales. In this work, we present a framework to quantify and partition the uncertainty of hydrological processes emerging from climate models and internal variability, across a broad range of scales. Using the example of two mountainous catchments in Switzerland, we produced high-resolution ensembles of climate and hydrological data using a two-dimensional weather generator (AWE-GEN- 2d) and a distributed hydrological model (TOPKAPI-ETH). We quantified the uncertainty in hydrological projections towards the end of the century through the estimation of the values of signal-to-noise ratios (STNR). We found small STNR absolute values (<1) in the projection of annual streamflow for most sub-catchments in both study sites that are dominated by the large natural variability of precipitation (explains ~70% of total uncertainty). Furthermore, we investigated in detail specific hydrological components that are critical in the model chain. For example, snowmelt and liquid precipitation exhibit robust change signals, which translates into high STNR values for streamflow during warm seasons and at higher elevations, together with a larger contribution of climate model uncertainty. In contrast, projections of extreme high flows show low STNR values due to large internal climate variability across all elevations, which limits the potential for narrowing their estimation uncertainty.ISSN:0885-6087ISSN:1099-108

Matching ecohydrological processes and scales of banded vegetation patterns in semi-arid catchments

While the claim that water-carbon interactions result in spatially coherent vegetation patterning is rarely disputed in many arid and semi-arid regions, the significance of the detailed water pathways and other high frequency variability remain an open question. How the short temporal scale meteorological fluctuations form the long term spatial variability of available soil water in complex terrains due to the various hydrological, land surface and vegetation dynamic feedbacks, frames the scope of the work here. Knowledge of the detailed mechanistic feedbacks between soil, plants and the atmosphere will lead to advances in our understanding of plant water availability in arid and semi-arid ecosystems and will provide insights for future model development concerning vegetation pattern formation. In this study, quantitative estimates of water fluxes and vegetation productivity are provided for a semi-arid ecosystem with established vegetation bands on hillslopes using numerical simulations. A state-of-the-science process based ecohydrological model is used, which resolves hydrological and plant physiological processes at the relevant space and time scales, for relatively small periods (e.g. decades) of mature ecosystems (i.e. spatially static vegetation distribution). To unfold the mechanisms that shape the spatial distribution of soil moisture, plant productivity and the relevant surface/subsurface and atmospheric water fluxes, idealized hillslope numerical experiments are constructed, where the effects of soil-type, slope steepness and overland flow accumulation area are quantified. Those mechanisms are also simulated in the presence of complex topography features on landscapes. The main results are: (a) Short temporal scale meteorological variability and accurate representation of the scales at which each ecohydrological process operates are crucial for the estimation of the spatial variability of soil water availability to the plant root zone; (b) Water fluxes such as evapotranspiration, infiltration, runoff-runon and subsurface soil water movement have a dynamic short temporal scale behavior that determines the long term spatial organization of plant soil water availability in ecosystems with established vegetation patterns; (c) Hypotheses concerning the hydrological responses that can lead to vegetation pattern formation have to accommodate realistic and physically based representations of the fast dynamics of key ecohydrological fluxes

Consistent responses of vegetation gas exchange to elevated atmospheric CO2 emerge from heuristic and optimization models

Elevated atmospheric CO2 concentration is expected to increase leaf CO(2)assimilation rates, thus promoting plant growth and increasing leaf area. It also decreases stomatal conductance, allowing water savings, which have been hypothesized to drive large-scale greening, in particular in arid and semiarid climates. However, the increase in leaf area could reduce the benefits of elevated CO2 concentration through soil water depletion. The net effect of elevated CO2 on leaf- and canopy-level gas exchange remains uncertain. To address this question, we compare the outcomes of a heuristic model based on the Partitioning of Equilibrium Transpiration and Assimilation (PETA) hypothesis and three model variants based on stomatal optimization theory. Predicted relative changes in leaf- and canopy-level gas exchange rates are used as a metric of plant responses to changes in atmospheric CO2 concentration. Both model approaches predict reductions in leaf-level transpiration rate due to decreased stomatal conductance under elevated CO2, but negligible (PETA) or no (optimization) changes in canopy-level transpiration due to the compensatory effect of increased leaf area. Leaf- and canopy-level CO2 assimilation is predicted to increase, with an amplification of the CO2 fertilization effect at the canopy level due to the enhanced leaf area. The expected increase in vapour pressure deficit (VPD) under warmer conditions is generally predicted to decrease the sensitivity of gas exchange to atmospheric CO2 concentration in both models. The consistent predictions by different models that canopylevel transpiration varies little under elevated CO2 due to combined stomatal conductance reduction and leaf area increase highlight the coordination of physiological and morphological characteristics in vegetation to maximize resource use (here water) under altered climatic conditions

Partitioning direct and indirect effects reveals the response of water-limited ecosystems to elevated CO2

Increasing concentrations of atmospheric carbon dioxide are expected to affect carbon assimilation and evapotranspiration (ET), ultimately driving changes in plant growth, hydrology and the global carbon balance. Direct leaf biochemical effects have been widely investigated, while indirect effects, although documented, elude explicit quantification in experiments. Here, we used a mechanistic model to investigate the relative contributions of direct (through carbon assimilation) and indirect (via soil moisture savings due to stomatal closure, and changes in leaf area index, LAI) effects of elevated CO2 across a variety of ecosystems. We specifically determined which ecosystems and climatic conditions maximise the indirect effects of elevated CO2. The simulations suggest that the indirect effects of elevated CO2 on net primary productivity are large and variable, ranging from less than 10% to more than 100% of the size of direct effects. For ET, indirect effects were on average 65% of the size of direct effects. Indirect effects tended to be considerably larger in water-limited ecosystems. As a consequence, the total CO2 effect had a significant, inverse relationship with the wetness index and was directly related to vapor pressure deficit. These results have major implications for our understanding of the CO2-response of ecosystems and for global projections of CO2 fertilization because, while direct effects are typically understood and easily reproducible in models, simulations of indirect effects are far more challenging and difficult to constrain. Our findings also provide an explanation for the discrepancies between experiments in the total CO2 effect on net primary productivity

Ecohydrological changes after tropical forest conversion to oil palm

Given their ability to provide food, raw material and alleviate poverty, oil palm (OP) plantations are driving significant losses of biodiversity-rich tropical forests, fuelling a heated debate on ecosystem degradation and conservation. However, while OP-induced carbon emissions and biodiversity losses have received significant attention, OP water requirements have been marginalized and little is known on the ecohydrological changes (water and surface energy fluxes) occurring from forest clearing to plantation maturity. Numerical simulations supported by field observations from seven sites in Southeast Asia (five OP plantations and two tropical forests) are used here to illustrate the temporal evolution of OP actual evapotranspiration (ET), infiltration/runoff, gross primary productivity (GPP) and surface temperature as well as their changes relative to tropical forests. Model results from large-scale commercial plantations show that young OP plantations decrease ecosystem ET, causing hotter and drier climatic conditions, but mature plantations (age > 8−9 yr) have higher GPP and transpire more water (up to +7.7%) than the forests they have replaced. This is the result of physiological constraints on water use efficiency and the extremely high yield of OP (six to ten times higher than other oil crops). Hence, the land use efficiency of mature OP, i.e. the high productivity per unit of land area, comes at the expense of water consumption in a trade of water for carbon that may jeopardize local water resources. Sequential replanting and herbaceous ground cover can reduce the severity of such ecohydrological changes and support local water/climate regulation.This study was supported by the Swiss National Science Foundation grant no. 152019 (r4d - Ecosystems) ‘Oil Palm Adaptive Landscapes’. AM and AK were supported by the Deutsche Forschungsgemeinschaft (DFG) in the framework of the collaborative German- Indonesian research project CRC990 - EFForTS. The authors confirm that they have no interest or relationship, financial, or otherwise that might be perceived as influencing objectivity with respect to this work