Surface water and groundwater: unifying conceptualization and quantification of the two “water worlds”

Berkowitz, Brian; Zehe, Erwin

doi:10.5194/hess-24-1831-2020

Cited by 26 publications

(29 citation statements)

References 158 publications

(204 reference statements)

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“…Such an approach would avoid cases in which we unnecessarily underestimate the needed (spatial) model complexity of a hydrological model, which again could lead to limited predictive performances (e.g., Fenicia et al, 2011;Höge et al, 2019;Schoups et al, 2008). However, this procedure may result in a strong increase of uncertainty due to an increased number of model parameters (e.g., Beven, 1989), frequently by an unchanged amount of data for validation (Melsen et al, 2016), lead to a general overestimation of the simulated spatial variability due to error propagations and can drastically increase the number of redundant computations (Clark et al, 2017;Loritz et al, 2018). The issue of increasing computational times due to redundant calculations is thereby reinforced by the fact that physically based simulations of hydrological fluxes rely on relatively short natural length scales in time and space.…”

Section: Spatially Adaptive Modeling -As a Learning Tool To Better Unmentioning

confidence: 99%

The role and value of distributed precipitation data in hydrological models

Loritz

Hrachowitz

Neuper

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. This study investigates the role and value of distributed rainfall for the runoff generation of a mesoscale catchment (20 km2). We compare four hydrological model setups and show that a distributed model setup driven by distributed rainfall only improves the model performances during certain periods. These periods are dominated by convective summer storms that are typically characterized by higher spatiotemporal variabilities compared to stratiform precipitation events that dominate rainfall generation in winter. Motivated by these findings, we develop a spatially adaptive model that is capable of dynamically adjusting its spatial structure during model execution. This spatially adaptive model allows the varying relevance of distributed rainfall to be represented within a hydrological model without losing predictive performance compared to a fully distributed model. Our results highlight that spatially adaptive modeling has the potential to reduce computational times as well as improve our understanding of the varying role and value of distributed precipitation data for hydrological models.

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Section: Spatially Adaptive Modeling -As a Learning Tool To Better Unmentioning

confidence: 99%

The role and value of distributed precipitation data in hydrological models

Loritz

Hrachowitz

Neuper

et al. 2021

Hydrol. Earth Syst. Sci.

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“…The numerical study of Edery et al (2014), for example, revealed that a higher variance in the hydraulic conductivity (K) field coincided with a stronger concentration of solutes within a smaller number of preferential flow paths. If the emergence of preferential flow is indeed manifested self-organization, as argued by Berkowitz and Zehe (2020), this key finding of Edery et al (2014) suggests that macroscale steady states of stronger organization (or higher order) emerge and persist despite a greater https://doi.org/10.5194/hess-2021-254 Preprint. Discussion started: 21 May 2021 c Author(s) 2021.…”

Section: Preferential Flow Phenomenafast Furious and Enigmaticmentioning

confidence: 94%

Preferential Pathways for Fluid and Solutes in Heterogeneous Groundwater Systems: Self-Organization, Entropy, Work

Zehe¹,

Loritz²,

Edery³

et al. 2021

Preprint

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Abstract. Patterns of distinct preferential pathways for fluid flow and solute transport are ubiquitous in heterogeneous, saturated and partially saturated porous media. Yet, the underlying reasons for their emergence, and their characterization and quantification, remain enigmatic. Here we analyze simulations of steady state fluid flow and solute transport in two-dimensional, heterogeneous saturated porous media with a relatively short correlation length. We demonstrate that the downstream concentration of solutes in preferential pathways implies a downstream declining entropy in the transverse distribution of solute transport pathways. This reflects the associated formation and downstream steepening of a concentration gradient transversal to the main flow direction. With an increasing variance of the hydraulic conductivity field, stronger transversal concentration gradients emerge, which is reflected in an even smaller entropy of the transversal distribution of transport pathways. By defining "self-organization" through a reduction in entropy (compared to its maximum), our findings suggest that a higher variance and thus randomness of the hydraulic conductivity coincides with stronger macroscale self-organization of transport pathways. While this finding appears at first sight striking, it can be explained by recognizing that emergence of spatial self-organization requires, in light of the second law of thermodynamics, that work be performed to establish transversal concentration gradients. The emergence of steeper concentration gradients requires that even more work be performed, with an even higher energy input into an open system. Consistently, we find that the energy input necessary to sustain steady-state fluid flow and tracer transport grows with the variance of the hydraulic conductivity field as well. Solute particles prefer to move through pathways of very high power, and these pathways pass through bottlenecks of low hydraulic conductivity. This is because power depends on the squared spatial head gradient, which is in these simulations largest in regions of low hydraulic conductivity.

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“…Although there is evidence for the presence of preferential flow in other components of the system, such as in the groundwater (e.g. Berkowitz and Zehe, 2020), initial model testing suggested that the inclusion of the additional calibration parameters is not warranted by the available data. For simplicity and following the principle of model parsimony we assumed complete mixing for all other outflows from all other storage components (Figure 3; cf.…”

Section: Tracer Transport Modelmentioning

confidence: 99%

Deforestation reduces the vegetation-accessible water storage in the unsaturated soil and affects catchment travel time distributions and young water fractions

Hrachowitz

Stockinger

Coenders-Gerrits

et al. 2020

Preprint

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Abstract. Deforestation can considerably affect transpiration dynamics and magnitudes at the catchment-scale and thereby alter the partitioning between drainage and evaporative water fluxes released from terrestrial hydrological systems. However, it has so far remained problematic to directly link reductions in transpiration to changes in the physical properties of the system and to quantify these changes of system properties at the catchment-scale. As a consequence, it is difficult to quantify the effect of deforestation on parameters of catchment-scale hydrological models. This in turn leads to substantial uncertainties in predictions of the hydrological response after deforestation but also to a poor understanding of how deforestation affects principal descriptors of catchment-scale transport, such as travel time distributions and young water fractions. The objectives of this study are therefore to quantify the effects of deforestation in the Wüstebach experimental catchment on the partitioning of water fluxes and to directly associate these changes to changes in parameters of a hydrological model with integrated tracer routine based on the concept of storage age selection functions. Simultaneously modelling stream flow and stable water isotope dynamics using meaningfully adjusted model parameters both for the pre- and post-deforestation periods, respectively, the model is used to track fluxes through the system and to estimate the effects of deforestation on catchment travel time distributions and young water fractions Fyw. It was found that deforestation led to a significant increase of stream flow, accompanied by corresponding reductions of evaporative fluxes. This is reflected by an increase of the runoff ratio from CR = 0.55 to 0.68 in the post-deforestation period despite similar climatic conditions. This reduction of evaporative fluxes could be linked to a reduction of the catchment-scale water storage volume in the unsaturated soil (SU,max) that is within the reach of active roots and thus accessible for vegetation transpiration from ~ 225 mm in the pre-deforestation period to ~ 90 mm in the post-deforestations period. The hydrological model, reflecting the changes in the parameter SU,max indicated that in the post-deforestation period stream water was characterized by slightly higher mean fractions of young water (Fyw ~ 0.13) than in the pre-deforestation period (Fyw ~ 0.11). In spite of these limited effects on the overall Fyw, considerable changes were found for wet periods, during which post-deforestation fractions of young water increased to values Fyw ~ 0.40 for individual storms. Deforestation also caused a significantly increased sensitivity of young water fractions to discharge under wet conditions from dFyw/dQ = 0.25 to 0.43. Overall, this study demonstrates that deforestation has not only the potential to affect the partitioning between drainage and evaporation as well as the vegetation-accessible storage volumes SU,max, and thus the fundamental hydrological response characteristics of catchments, but also catchment-scale tracer circulation dynamics. In particular for wet conditions, deforestation caused higher proportions of younger water to reach the stream, implying faster routing of stable isotopes and plausibly also solutes through the subsurface.

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Surface water and groundwater: unifying conceptualization and quantification of the two “water worlds”

Cited by 26 publications

References 158 publications

The role and value of distributed precipitation data in hydrological models

The role and value of distributed precipitation data in hydrological models

Preferential Pathways for Fluid and Solutes in Heterogeneous Groundwater Systems: Self-Organization, Entropy, Work

Deforestation reduces the vegetation-accessible water storage in the unsaturated soil and affects catchment travel time distributions and young water fractions

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