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This paper investigates the influence of multi-decadal climatic variability on the temporal evolution of root zone storage capacities (Sr,max) and its implications for streamflow predictions in the Meuse basin. Through a comprehensive analysis of 286 catchments across Europe and the US that are hydro-climatically comparable to the Meuse basin, we construct inter-decadal distributions of past deviations in evaporative ratios (IE) from expected values based on catchment aridity (IA). These distributions of ΔIE were then used to estimate inter-decadal changes in Sr,max and to quantify the associated consequences for streamflow predictions in the Meuse basin. Our findings reveal that, while catchments do not strictly adhere to their specific parametric Budyko curves over time, the deviations in IE are generally very minor, with an average ΔIE=0.01 and an interquartile range (IQR) of -0.01 to 0.03. Consequently, these minor deviations lead to limited inter-decadal changes in Sr,max , mostly ranging between -10 and +21 mm (-5 % to +10 %). When these changes (ΔSr,max) are accounted for in hydrological models, the impact on streamflow predictions in the Meuse basin is found to be marginal, with the most significant shifts in monthly evaporation and streamflow not exceeding 4 % and 12 %, respectively. Our study underscores the utility of parametric Budyko-style equations for first-order estimates of future Sr,max in hydrological models, even in the face of climate change and variability. This research contributes to a more nuanced understanding of hydrological responses to changing climatic conditions and offers valuable insights for future climate impact studies in hydrology. [ABSTRACT FROM AUTHOR]

This paper investigates the influence of multi-decadal climatic variability on the temporal evolution of root zone storage capacities (Sr,max) and its implications for streamflow predictions at the catchment scale. Through a comprehensive analysis of 286 catchments across Europe and the US, we analyse the deviations in evaporative ratios (IE) from expected values based on catchment aridity (IA) and their subsequent impact on Sr,max predictions. Our findings reveal that while catchments do not strictly adhere to their specific parametric Budyko curves over time, the deviations in IE are generally very minor, with an average ΔIE = 0.01 and an interquartile range IQR= -0.01 to 0.03. Consequently, these minor deviations lead to limited changes in predictions of Sr,max, mostly ranging between -10.5 and +21.5 mm (-5.1 % to +9.9 %). When these uncertainties in Sr,max are incorporated into hydrological models, the impact on streamflow predictions is found to be marginal, with the most significant shifts in monthly evaporation and streamflow not exceeding 4 % and 12 %, respectively. Our study underscores the utility of parametric Budyko-style equations for first order estimates of future Sr,max in hydrological models, even in the face of climate change and variability. This research contributes to a more nuanced understanding of hydrological responses to changing climatic conditions and offers valuable insights for future climate impact studies in hydrology. [ABSTRACT FROM AUTHOR]

Future hydrological behavior in a changing world is typically predicted based on models that are calibrated on past observations, disregarding that hydrological systems and, therefore, model parameters may change as well. In reality, hydrological systems experience almost continuous change over a wide spectrum of temporal and spatial scales. In particular, there is growing evidence that vegetation adapts to changing climatic conditions by adjusting its root zone storage capacity, which is the key parameter of any terrestrial hydrological system. In addition, other species may become dominant, both under natural and anthropogenic influence. In this study, we test the sensitivity of hydrological model predictions to changes in vegetation parameters that reflect ecosystem adaptation to climate and potential land use changes. We propose a top-down approach, which directly uses projected climate data to estimate how vegetation adapts its root zone storage capacity at the catchment scale in response to changes in the magnitude and seasonality of hydro-climatic variables. Additionally, long-term water balance characteristics of different dominant ecosystems are used to predict the hydrological behavior of potential future land use change in a space-for-time exchange. We hypothesize that changes in the predicted hydrological response as a result of 2 K global warming are more pronounced when explicitly considering changes in the subsurface system properties induced by vegetation adaptation to changing environmental conditions. We test our hypothesis in the Meuse basin in four scenarios designed to predict the hydrological response to 2 K global warming in comparison to current-day conditions, using a process-based hydrological model with (a) a stationary system, i.e., no assumed changes in the root zone storage capacity of vegetation and historical land use, (b) an adapted root zone storage capacity in response to a changing climate but with historical land use and (c, d) an adapted root zone storage capacity considering two hypothetical changes in land use. We found that the larger root zone storage capacities (+ 34 %) in response to a more pronounced climatic seasonality with warmer summers under 2 K global warming result in strong seasonal changes in the hydrological response. More specifically, streamflow and groundwater storage are up to - 15 % and - 10 % lower in autumn, respectively, due to an up to + 14 % higher summer evaporation in the non-stationary scenarios compared to the stationary benchmark scenario. By integrating a time-dynamic representation of changing vegetation properties in hydrological models, we make a potential step towards more reliable hydrological predictions under change. [ABSTRACT FROM AUTHOR]

To predict future hydrological behavior in a changing world, often use is made of models calibrated on past observations, disregarding that hydrological systems, hence model parameters, will change as well. Yet, ecosystems likely adjust their root-zone storage capacity, which is the key parameter of any hydrological system, in response to climate change. In addition, other species might become dominant, both under natural and anthropogenic influence. In this study, we propose a top-down approach, which directly uses projected climate data to estimate how vegetation adapts its root-zone storage capacity at the catchment scale in response to changes in magnitude and seasonality of hydro-climatic variables. Additionally, the Budyko characteristics of different dominant ecosystems in sub-catchments are used to simulate the hydrological behavior of potential future land-use change, in a space-for-time exchange. We hypothesize that changes in the predicted hydrological response as a result of 2K global warming are more pronounced when explicitly considering changes in the sub-surface system properties induced by vegetation adaptation to changing environmental conditions. We test our hypothesis in the Meuse basin in four scenarios designed to predict the hydrological response to 2K global warming in comparison to current-day conditions using a process-based hydrological model with (a) a stationary system, i.e. no changes in the root-zone storage capacity of vegetation and historical land use, (b) an adapted root-zone storage capacity in response to a changing climate but with historical land use, and (c,d) an adapted root-zone storage capacity considering two hypothetical changes in land use from coniferous plantations/agriculture towards broadleaved forest and vice-versa. We found that the larger root-zone storage capacities (+34%) in response to a more pronounced seasonality with drier summers under 2K global warming strongly alter seasonal patterns of the hydrological response, with an overall increase in mean annual evaporation (+4%), a decrease in recharge (-6%) and a decrease in streamflow (-7%), compared to predictions with a stationary system. By integrating a time-dynamic representation of changing vegetation properties in hydrological models, we make a potential step towards more reliable hydrological predictions under change. [ABSTRACT FROM AUTHOR]

Streamflow is often the only variable used to evaluate hydrological models. In a previous international comparison study, eight research groups followed an identical protocol to calibrate 12 hydrological models using observed streamflow of catchments within the Meuse basin. In the current study, we quantify the differences in five states and fluxes of these 12 process-based models with similar streamflow performance, in a systematic and comprehensive way. Next, we assess model behavior plausibility by ranking the models for a set of criteria using streamflow and remote-sensing data of evaporation, snow cover, soil moisture and total storage anomalies. We found substantial dissimilarities between models for annual interception and seasonal evaporation rates, the annual number of days with water stored as snow, the mean annual maximum snow storage and the size of the root-zone storage capacity. These differences in internal process representation imply that these models cannot all simultaneously be close to reality. Modeled annual evaporation rates are consistent with Global Land Evaporation Amsterdam Model (GLEAM) estimates. However, there is a large uncertainty in modeled and remote-sensing annual interception. Substantial differences are also found between Moderate Resolution Imaging Spectroradiometer (MODIS) and modeled number of days with snow storage. Models with relatively small root-zone storage capacities and without root water uptake reduction under dry conditions tend to have an empty root-zone storage for several days each summer, while this is not suggested by remote-sensing data of evaporation, soil moisture and vegetation indices. On the other hand, models with relatively large root-zone storage capacities tend to overestimate very dry total storage anomalies of the Gravity Recovery and Climate Experiment (GRACE). None of the models is systematically consistent with the information available from all different (remote-sensing) data sources. Yet we did not reject models given the uncertainties in these data sources and their changing relevance for the system under investigation. [ABSTRACT FROM AUTHOR]

Streamflow is often the only variable used to constrain hydrological models. In a previous international comparison study, eight research groups followed an identical protocol to calibrate a total of twelve hydrological models using observed streamflow of catchments within the Meuse basin. In the current study, we hypothesize that these twelve process-based models with similar streamflow performance have similar representations of internal states and fluxes. We test our hypothesis by comparing internal states and fluxes between models and we assess their plausibility using remotely-sensed products of evaporation, snow cover, soil moisture and total storage anomalies. Our results indicate that models with similar streamflow performance represent internal states and fluxes differently. Substantial dissimilarities between models are found for annual and seasonal evaporation and interception rates, the number of days per year with water stored as snow, the mean annual maximum snow storage and the size of the root-zone storage capacity. Relatively small root-zone storage capacities for several models lead to drying-out of the root-zone storage and significant reduction of evaporative fluxes each summer, which is not suggested by remotely-sensed estimates of evaporation and root-zone soil moisture. These differences in internal process representation imply that these models cannot all simultaneously be close to reality. Using remotely-sensed products, we could evaluate the plausibility of model representations only to some extent, as many of these internal variables remain unknown, highlighting the need for experimental research. We also encourage modelers to rely on multi-model and multi-parameter studies to reveal to decision-makers the uncertainties inherent to the heterogeneity of catchments and the lack of evaluation data. [ABSTRACT FROM AUTHOR]

The spatiotemporal dynamics of water volumes stored in the unsaturated root zone are a key control on the response of terrestrial hydrological systems. Robust, catchment-scale root-zone soil moisture estimates are thus critical for reliable predictions of river flow, groundwater recharge, or evaporation. Satellites provide estimates of near-surface soil moisture that can be used to approximate the moisture content in the entire unsaturated root zone through the SoilWater Index (SWI). The characteristic time length (T, in days), as only parameter in the SWI approach, characterizes the temporal variability of soil moisture. The factors controlling T are typically assumed to be related to soil properties and climate; however, no clear link has so far been established. In this study, we hypothesize that optimal T values (Topt) are linked to the interplay of precipitation and evaporation during dry periods, thus to catchment-scale vegetation accessible water storage capacities in the unsaturated root zone. We identify Topt by matching modeled time series of root-zone soil moisture from a calibrated process-based hydrological model to SWI from several satellite-based near-surface soil moisture products in 16 contrasting catchments in the Meuse river basin. Topt values are strongly and positively correlated with vegetation accessible water volumes that can be stored in the root zone, here estimated for each study catchment both as model calibration parameter and from a water-balance approach. Differences in Topt across catchments are also explained by land cover (% agriculture), soil texture (% silt), and runoff signatures (flashiness index). [ABSTRACT FROM AUTHOR]

Intercatchment groundwater flows (IGFs), defined as groundwater flows across topographic divides, can occur as regional groundwater flows that bypass headwater streams and only drain into the channel further downstream or directly to the sea. However, groundwater flows can also be diverted to adjacent river basins due to geological features (e.g., faults, dipping beds and highly permeable conduits). Even though intercatchment groundwater flows can be a significant part of the water balance, they are often not considered in hydrological studies. Yet, assuming this process to be negligible may introduce misrepresentation of the natural system in hydrological models, for example in regions with complex geological features. The presence of limestone formations in France and Belgium potentially further exacerbates the importance of intercatchment groundwater flows, and thus brings into question the validity of neglecting intercatchment groundwater flows in the Meuse basin. To isolate and quantify the potential relevance of net intercatchment groundwater flows in this study, we propose a three-step approach that relies on the comparison and analysis of (1) observed water balance data within the Budyko framework, (2) results from a suite of different conceptual hydrological models and (3) remote-sensing-based estimates of actual evaporation. The data of 58 catchments in the Meuse basin provide evidence of the likely presence of significant net intercatchment groundwater flows occurring mainly in small headwater catchments underlain by fractured aquifers. The data suggest that the relative importance of net intercatchment groundwater flows is reduced at the scale of the Meuse basin, as regional groundwater flows are mostly expected to be self-contained in large basins. The analysis further suggests that net intercatchment groundwater flow processes vary over the year and that at the scale of the headwaters, net intercatchment groundwater flows can make up a relatively large proportion of the water balance (on average 10 % of mean annual precipitation) and should be accounted for to prevent overestimating actual evaporation rates. [ABSTRACT FROM AUTHOR]