Over recent decades, climatic changes and significant variations in all key components of the hydrological cycle have been observed in many regions worldwide, profoundly altering water availability, river flow regimes, and the concentration of nutrients and pollutants. Ecosystem is a key component of the terrestrial hydrological cycle as it shapes the hy drological functioning of catchments by regulating the long-term average partitioning of water into drainage and evaporative fluxes (i.e. latent heat). In response to a changing environment, ecosystems continuously adapt to allow the most efficient use of available energy and resources. However, direct quantification of how ecosystems adapts to climatic variability over long time periods and the mechanistic drivers thereof at the catchment scale is missing so far. As a consequence, it remains unclear how climatic variability, such as precipitation regime or canopy water demand, influences the partitioning of water fluxes, the hydrological response, and hydrological processes and transport mechanisms at the catchment-scale. Therefore, the overarching objective of this thesis is to address the follow ing main research question: How does climatic variability affect the hydrological response and transport mechanisms in a temperate-humid basin over multiple decades? All analysis in this thesis is carried out in a large river basin, the Neckar basin, Germany. A unique long-term dataset is used for this basin, consisting of 70 years of hydrometeorological and tracer data. Hydrological and transport processes in the basin are quantified using a state-of-the-art semi-distributed hydrological model that (i) includes spa tial heterogeneity in topography, vegetation and precipitation, (ii) accounts for ecosystem adaptation to climate variability via a time-varying root zone water storage capacity, and (iii) uses StorAge Selection (SAS) functions to account for mixing of tracers and to estimate time-varying water age distributions at catchment scale. Multi-objective calibration of the hydrological model using the long-term hydrometeorological and tracer dataset pro vides the basis for investigating how climatic variability affects hydrological and physical transport processes in the Neckar basin. The first research question focuses on ecosystem adaptation to climate variability via changes in root zone storage capacity. The root zone storage capacity is a critical factor reg ulating latent heat fluxes and thus the moisture exchange between land and atmosphere as well as the hydrological response and biogeochemical processes in terrestrial hydrological systems. To be survive, root systems of vegetation and the associated vegetation-accessible water storage capacity respond to the ever-changing conditions of its environment. How ever, as these changes occur at landscape scale and are mostly reflected by changes in the composition of plant species present in a specific spatial domain, fluctuations in root zone storage capacity occur largely at time-scales that reflect the life-cycles of individual plants. However, it remains unclear whether root zone storage capacity adapts to climatic variability and evolves over time, thereby reflecting ecosystem adaptation to changing conditions. The thesis investigates this for the Neckar basin by quantifying long-term changes in root zone storage capacity using two different methods, i.e. hydrological model calibration and an independent water balance estimation method. The analysis provides quantitative mechanistic evidence that root zone storage capacity significantly changes over multiple decades reflecting ecosystem adaptation to climatic variability. However, the analysis also suggests that accounting for temporal evolution of root zone storage capacity with a time-variable formulation of that parameter in a hydrological model does not sig nificantly improve its ability to reproduce the hydrological response and may therefore be of minor importance to predict the effects of a changing climate on the hydrological response. The second research question investigates the use of different isotopic tracers to estimate water age distributions, i.e. age distributions of water fluxes (“transit time distri butions”, TTD) and water stored in catchments (“residence time distributions”, RTD) as fundamental descriptors of hydrological functioning and catchment storage. These distri butions provide a way to quantitatively describe the physical link between the hydrological response of catchments and physical transport processes of conservative solutes. However, water age distributions cannot be directly observed, and instead have to be estimated with tracer-aided models. Stable isotopes (𝛿18O) and tritium (3H) are frequently used as tracers in environmental sciences to estimate age distributions of water. It has previously been argued that seasonally variable tracers, such as 𝛿18O, generally and systematically fail to detect the tails of water age distributions and therefore substantially underestimate water ages as compared to radioactive tracers, such as 3H. Early approaches often relied on simple lumped sine-wave or lumped parameter convolution integral models under the assumption that water storage in catchments is at steady state. Here, these methods are compared with the more realistic StorAge Selection (SAS) functions embedded in the dynamic hydrological model used in this thesis. By comparing water age distributions inferred from 𝛿18O and 3H with several different transport model implementations, this thesis demonstrates that previously reported underestimations of water ages are most likely not a result of the use of 𝛿18O or other seasonally variable tracers. Instead, these underestimations can be largely attributed to choices of model approaches and complexity. It is therefore strongly advocated to avoid the use of steady-state model types in combination with seasonally variable tracers and to instead adopt SAS-based or other time-variant model formulations that allow for the representation of transient conditions. The third and final research question investigates the effects of temporal variability of the hydrological response on physical transport processes over a spectrum of time scales from daily to multiple decades. Due to limited availability of tracer records over longer durations in many catchments, most previous studies focused on daily time scales to analyse temporal variability of water ages as metric of physical transport and the underlying drivers. To improve understanding of long-term transport dynamics, this thesis quantifies the variability in water ages, identifies the associated dominant controls from daily to multi-decadal time scales, and analyses the associated temporal evolution of water ages of streamflow and evaporation. It is shown that there are no major long term dynamics in water ages, driven by either internal processes or external transport variability. Consequently, the physical transport dynamics in the upper Neckar basin, and potentially in other basins with similar water age characteristics, are inferred to exhibit near-stationarity over multiple decades. Concluding, this thesis provides sufficient evidence that long-term varying root zone storage capacity significantly reflects ecosystem adaptation to climatic variability. However, the temporal evolution of root zone storage capacity does not control variation in the partitioning of water fluxes and has no significant effects on fundamental hydrological response characteristics of the studied semi-humid river basin in the near future under a changing climatic condition. In addition, the thesis suggests physical transport processes can be assumed to be near-stationary and predictable across multiple decades under either internal (i.e., time-variant root zone storage capacity) or external transport variability (i.e., climatic variability), which contrasts with the frequently reported fractal pattern in stream water solute dynamics. This finding is crucial for management of subsurface water quality and the design of restoration interventions for groundwater affected by legacy contamination such as nitrate.@en

Climatic variability can considerably affect catchment-scale root zone storage capacity (S _umax), which is a critical factor regulating latent heat fluxes and thus the moisture exchange between land and atmosphere as well as the hydrological response and biogeochemical processes in terrestrial hydrological systems. However, direct quantification of changes in S _umax over long time periods and the mechanistic drivers thereof at the catchment scale are missing so far. As a consequence, it remains unclear how climatic variability, such as precipitation regime or canopy water demand, affects S _umax and how fluctuations in S _umax may influence the partitioning of water fluxes and therefore also affect the hydrological response at the catchment scale. Based on long-term daily hydrological records (1953-2022) in the upper Neckar River basin in Germany, we found that variability in hydro-climatic conditions, with an aridity index I _A (i.e. E _P/P) ranging between ∼ 0.9 and 1.1 over multiple consecutive 20-year periods, was accompanied by deviations ΔI _E between -0.02 and 0.01 from the expected I _E inferred from the long-term parametric Budyko curve. Similarly, fluctuations in S _umax, ranging between ∼ 95 and 115 mm or ∼ 20 %, were observed over the same time period. While uncorrelated with long-term mean precipitation and potential evaporation, it was shown that the magnitude of S _umax is controlled by the ratio of winter precipitation to summer precipitation (p < 0.05). In other words, S _umax in the study region does not depend on the overall wetness condition as for example expressed by I _A, but rather on how water supply by precipitation is distributed over the year. However, fluctuations in S _umax were found to be uncorrelated with observed changes in ΔIE. Consequently, replacing a long-term average, time-invariant estimate of S _umax with a time-variable, dynamically changing formulation of that parameter in a hydrological model did not result in an improved representation of the long-term partitioning of water fluxes, as expressed by I _E (and fluctuations ΔIE thereof), or in an improved representation of the shorter-term response dynamics. Overall, this study provides quantitative mechanistic evidence that S _umax changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of S _umax cannot explain long-term fluctuations in the partitioning of water (and thus latent heat) fluxes as expressed by deviations ΔIE from the parametric Budyko curve over multiple time periods with different climatic conditions. Similarly, it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment. This further suggests that accounting for the temporal evolution of S _umax with a time-variable formulation of that parameter in a hydrological model does not improve its ability to reproduce the hydrological response and may therefore be of minor importance for predicting the effects of a changing climate on the hydrological response in the study region over the next decades to come.

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Stable isotopes (I18O) and tritium (3H) are frequently used as tracers in environmental sciences to estimate age distributions of water. However, it has previously been argued that seasonally variable tracers, such as I18O, generally and systematically fail to detect the tails of water age distributions and therefore substantially underestimate water ages as compared to radioactive tracers such as 3H. In this study for the Neckar River basin in central Europe and based on a >20-year record of hydrological, I18O and 3H data, we systematically scrutinized the above postulate together with the potential role of spatial aggregation effects in exacerbating the underestimation of water ages. This was done by comparing water age distributions inferred from I18O and 3H with a total of 21 different model implementations, including time-invariant, lumped-parameter sine-wave (SW) and convolution integral (CO) models as well as StorAge Selection (SAS)-function models (P-SAS) and integrated hydrological models in combination with SAS functions (IM-SAS). We found that, indeed, water ages inferred from I18O with commonly used SW and CO models are with mean transit times (MTTs) of g1/4g1-2 years substantially lower than those obtained from 3H with the same models, reaching MTTs of g1/410 years. In contrast, several implementations of P-SAS and IM-SAS models not only allowed simultaneous representations of storage variations and streamflow as well as I18O and 3H stream signals, but water ages inferred from I18O with these models were, with MTTs of g1/4g11-17 years, also much higher and similar to those inferred from 3H, which suggested MTTs of g1/4g11-13 years. Characterized by similar parameter posterior distributions, in particular for parameters that control water age, P-SAS and IM-SAS model implementations individually constrained with I18O or 3H observations exhibited only limited differences in the magnitudes of water ages in different parts of the models and in the temporal variability of transit time distributions (TTDs) in response to changing wetness conditions. This suggests that both tracers lead to comparable descriptions of how water is routed through the system. These findings provide evidence that allowed us to reject the hypothesis that I18O as a tracer generally and systematically "cannot see water older than about 4 years"and that it truncates the corresponding tails in water age distributions, leading to underestimations of water ages. Instead, our results provide evidence for a broad equivalence of I18O and 3H as age tracers for systems characterized by MTTs of at least 15-20 years. The question to which degree aggregation of spatial heterogeneity can further adversely affect estimates of water ages remains unresolved as the lumped and distributed implementations of the IM-SAS model provided inconclusive results. Overall, this study demonstrates that previously reported underestimations of water ages are most likely not a result of the use of I18O or other seasonally variable tracers per se. Rather, these underestimations can largely be attributed to choices of model approaches and complexity not considering transient hydrological conditions next to tracer aspects. Given the additional vulnerability of time-invariant, lumped SW and CO model approaches in combination with I18O to substantially underestimate water ages due to spatial aggregation and potentially other still unknown effects, we therefore advocate avoiding the use of this model type in combination with seasonally variable tracers if possible and instead adopting SAS-based models or time-variant formulations of CO models.

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