Landscape structure, regimes, and the co-evolution of hydrologic systems

In this dissertation I discuss approaches to building hydrologic understanding in a changing world that go beyond the construction of models of ever-greater complexity. These approaches aim to develop insight into the relationship between catchment properties and hydrologic dynamics using reduced-complexity models, and by looking for patterns that reveal emergent relationships between hydrologic systems and the landscapes they are embedded in. The dissertation proposes a framework for thinking about hydrologic systems in a changing world based on seeking a synthesis between the search for mechanistic descriptions of landscape processes, and the search for explanations for emergent landscape patterns. The dissertation is divided into two parts. The first describes a series of studies considering controls on the propagation of hydrologic variability through the landscape. One discusses the propagation of water and solutes through the vadose zone, another the lateral movement of water through a hillslope, and the third the accumulated effect of many hillslopes on the recession of flows at a watershed outlet. Each case builds on parsimonious representations of hydrologic processes to distill analytical results in terms of landscape and climate properties. These analytical results are used to define `regimes' of hydrologic behavior in which particular properties play decisive roles in the hydrologic system. The studies demonstrate that the regime framework yields insight into controls on the aggregate behavior of hydrologic system that can be used to develop `closure relations' capable of representing the effects of unresolved landscape structure on hydrologic fluxes without resolving them explicitly. The second part of the dissertation is concerned with how the landscape structure controlling the hydrologic dynamics has come to be the way it is, and the role that hydrologic variability plays in its evolution. This question is pursued at a range of scales, using modeling and data analysis. Inter-annual water balance variability across the climates and geologies of the continental US are examined for patterns in the dynamics of co-evolved landscapes. A simple model is then used to illustrate how catchment water-balance is affected by feedbacks between the lateral redistribution of water and the spatial organization of vegetation along the network. This work illustrates how insights into why and how landscape hydrology varies from place to place and through time can be built through a focus on the behavior that emerges from small-scale dynamics, conditioned by the over-arching climate, geology and the contingencies of history. These insights point the way to a new paradigm for hydrology that treats hydrologic systems as integrated wholes that have evolved through time, and will continue to change in the future

Перспективи інформаційної економіки

Метою доповіді є дослідження впливу інформаційних технологій на розвиток таких категорій сучасності як перехід сучасної економіки до інформаційного етапу, а також становлення інформаційного суспільства на основі сучасного пост промислового суспільства споживання

The importance of hydraulic groundwater theory in catchment hydrology: The legacy of Wilfried Brutsaert and Jean-Yves Parlange

Based on a literature overview, this paper summarizes the impact and legacy of the contributions of Wilfried Brutsaert and Jean-Yves Parlange (Cornell University) with respect to the current state-of-the-art understanding in hydraulic groundwater theory. Forming the basis of many applications in catchment hydrology, ranging from drought flow analysis to surface water-groundwater interactions, hydraulic groundwater theory simplifies the description of water flow in unconfined riparian and perched aquifers through assumptions attributed to Dupuit and Forchheimer. Boussinesq (1877) derived a general equation to study flow dynamics of unconfined aquifers in uniformly sloping hillslopes, resulting in a remarkably accurate and applicable family of results, though often challenging to solve due to its nonlinear form. Under certain conditions, the Boussinesq equation can be solved analytically allowing compact representation of soil and geomorphological controls on unconfined aquifer storage and release dynamics. The Boussinesq equation has been extended to account for flow divergence/convergence as well as for nonuniform bedrock slope (concave/convex). The extended Boussinesq equation has been favorably compared to numerical solutions of the three-dimensional Richards equation, confirming its validity under certain geometric conditions. Analytical solutions of the linearized original and extended Boussinesq equations led to the formulation of similarity indices for baseflow recession analysis, including scaling rules, to predict the moments of baseflow response. Validation of theoretical recession parameters on real-world streamflow data is complicated due to limited measurement accuracy, changing boundary conditions, and the strong coupling between the saturated aquifer with the overlying unsaturated zone. However, recent advances are shown to have mitigated several of these issues. The extended Boussinesq equation has been successfully applied to represent baseflow dynamics in catchment-scale hydrological models, and it is currently considered to represent lateral redistribution of groundwater in land surface schemes applied in global circulation models. From the review, it is clear that Wilfried Brutsaert and Jean-Yves Parlange stimulated a body of research that has led to several fundamental discoveries and practical applications with important contributions in hydrological modeling.Keywords: Parlange, hillslope, catchment, groundwater, Brutsaert, Boussines

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological Change

Understanding the process interactions and feedbacks among water, porous geological media, microbes, and vascular plants is crucial for improving predictions of the response of Earth’s critical zone to future climatic conditions. However, the integrated coevolution of landscapes under change is notoriously difficult to investigate. Laboratory studies are limited in spatial and temporal scale, while field studies lack observational density and control. To bridge the gap between controlled laboratory and uncontrollable field studies, the University of Arizona built a macrocosm experiment of unprecedented scale: the Landscape Evolution Observatory (LEO). LEO comprises three replicated, heavily instrumented, hillslope-scale model landscapes within the environmentally controlled Biosphere 2 facility. The model landscapes were designed to initially be simple and purely abiotic, enabling scientists to observe each step in the landscapes’ evolution as they undergo physical, chemical, and biological changes over many years. This chapter describes the model systems and associated research facilities and illustrates how LEO allows for tracking of multiscale matter and energy fluxes at a level of detail impossible in field experiments. Initial sensor, sampler, and soil coring data are already providing insights into the tight linkages between water flow, weathering, and microbial community development. These interacting processes are anticipated to drive the model systems to increasingly complex states and will be impacted by the introduction of vascular plants and changes in climatic regimes over the years to come. By intensively monitoring the evolutionary trajectory, integrating data with mathematical models, and fostering community-wide collaborations, we envision that emergent landscape structures and functions can be linked, and significant progress can be made toward predicting the coupled hydro-biogeochemical and ecological responses to global change

Evaluation of statistical methods for quantifying fractal scaling in water-quality time series with irregular sampling

River water-quality time series often exhibit fractal scaling, which here refers to autocorrelation that decays as a power law over some range of scales. Fractal scaling presents challenges to the identification of deterministic trends because (1) fractal scaling has the potential to lead to false inference about the statistical significance of trends and (2) the abundance of irregularly spaced data in water-quality monitoring networks complicates efforts to quantify fractal scaling. Traditional methods for estimating fractal scaling – in the form of spectral slope (β) or other equivalent scaling parameters (e.g., Hurst exponent) – are generally inapplicable to irregularly sampled data. Here we consider two types of estimation approaches for irregularly sampled data and evaluate their performance using synthetic time series. These time series were generated such that (1) they exhibit a wide range of prescribed fractal scaling behaviors, ranging from white noise (β  =  0) to Brown noise (β  =  2) and (2) their sampling gap intervals mimic the sampling irregularity (as quantified by both the skewness and mean of gap-interval lengths) in real water-quality data. The results suggest that none of the existing methods fully account for the effects of sampling irregularity on β estimation. First, the results illustrate the danger of using interpolation for gap filling when examining autocorrelation, as the interpolation methods consistently underestimate or overestimate β under a wide range of prescribed β values and gap distributions. Second, the widely used Lomb–Scargle spectral method also consistently underestimates β. A previously published modified form, using only the lowest 5 % of the frequencies for spectral slope estimation, has very poor precision, although the overall bias is small. Third, a recent wavelet-based method, coupled with an aliasing filter, generally has the smallest bias and root-mean-squared error among all methods for a wide range of prescribed β values and gap distributions. The aliasing method, however, does not itself account for sampling irregularity, and this introduces some bias in the result. Nonetheless, the wavelet method is recommended for estimating β in irregular time series until improved methods are developed. Finally, all methods' performances depend strongly on the sampling irregularity, highlighting that the accuracy and precision of each method are data specific. Accurately quantifying the strength of fractal scaling in irregular water-quality time series remains an unresolved challenge for the hydrologic community and for other disciplines that must grapple with irregular sampling.ISSN:1027-5606ISSN:1607-793

HESS Opinions: Hydrologic predictions in a changing environment: behavioral modeling

Most hydrological models are valid at most only in a few places and cannot be reasonably transferred to other places or to far distant time periods. Transfer in space is difficult because the models are conditioned on past observations at particular places to define parameter values and unobservable processes that are needed to fully characterize the structure and functioning of the landscape. Transfer in time has to deal with the likely temporal changes to both parameters and processes under future changed conditions. This remains an important obstacle to addressing some of the most urgent prediction questions in hydrology, such as prediction in ungauged basins and prediction under global change. In this paper, we propose a new approach to catchment hydrological modeling, based on universal principles that do not change in time and that remain valid across many places. The key to this framework, which we call behavioral modeling, is to assume that there are universal and time-invariant organizing principles that can be used to identify the most appropriate model structure (including parameter values) and responses for a given ecosystem at a given moment in time. These organizing principles may be derived from fundamental physical or biological laws, or from empirical laws that have been demonstrated to be time-invariant and to hold at many places and scales. Much fundamental research remains to be undertaken to help discover these organizing principles on the basis of exploration of observed patterns of landscape structure and hydrological behavior and their interpretation as legacy effects of past co-evolution of climate, soils, topography, vegetation and humans. Our hope is that the new behavioral modeling framework will be a step forward towards a new vision for hydrology where models are capable of more confidently predicting the behavior of catchments beyond what has been observed or experienced before.ISSN:1027-5606ISSN:1607-793

Hydrologic predictions in a changing environment: behavioral modeling

Most hydrological models are valid at most only in a few places and cannot be rea-sonably transferred to other places or to far distant time periods. Transfer in space isdifficult because the models are conditioned on past observations at particular placesto define parameter values and unobservable processes that are needed to fully characterize the structure and functioning of the landscape. Transfer in time has to deal withthe likely temporal changes to both parameters and processes under future changedconditions. This remains an important obstacle to addressing some of the most urgentprediction questions in hydrology, such as prediction in ungauged basins and predictionunder global change. In this paper, we propose a new approach to catchment hydrological modeling, based on universal principles that do not change in time and that remainvalid across many places. The key to this framework, which we call behavioral mod-eling, is to assume that these universal and time-invariant organizing principles canbe used to identify the most appropriate model structure (including parameter values)and responses for a given ecosystem at a given moment in time. The organizing principles may be derived from fundamental physical or biological laws, or from empiricallaws that have been demonstrated to be time-invariant and to hold at many places andscales. Much fundamental research remains to be undertaken to help discover theseorganizing principles on the basis of exploration of observed patterns of landscapestructure and hydrological behavior and their interpretation as legacy effects of past co-evolution of climate, soils, topography, vegetation and humans. Our hope is thatthe new behavioral modeling framework will be a step forward towards a new visionfor hydrology where models are capable of more confidently predicting the behavior ofcatchments beyond what has been observed or experienced beforeISSN:1812-2116ISSN:1812-210

Fill‐and‐spill: a process description of runoff generation at the scale of the beholder

Descriptions of runoff generation processes continue to grow, helping to reveal complexities and hydrologic behavior across a wide range of environments and scales. But to date, there has been little grouping of these process facts. Here, we discuss how the “fill-and-spill” concept can provide a framework to group event-based runoff generation processes. The fill-and-spill concept describes where vertical and lateral additions of water to a landscape unit are placed into storage (the fill)—and only when this storage reaches a critical level (the spill), and other storages are filled and become connected, does a previously infeasible (but subsequently important) outflow pathway become activated. We show that fill-and-spill can be observed at a range of scales and propose that future fieldwork should first define the scale of interest and then evaluate what is filling-and-spilling at that scale. Such an approach may be helpful for those instrumenting and modeling new hillslopes or catchments because it provides a structured way to develop perceptual models for runoff generation and to group behaviors at different sites and scales

Spatial scale dependence of ecohydrologically mediated water balance partitioning: A synthesis framework for catchment ecohydrology

The difficulties in predicting whole catchment water balance from observations at patch scales motivate a search for theories that can account for the complexity of interactions in catchments. In this paper we suggest that the spatial patterns of vegetation may offer a lens through which to investigate scale dependence of hydrology within catchments. Vegetation patterns are attractive because they are observable drivers of evapotranspiration, often a dominant component in catchment water balance, and because the spatial distribution of vegetation is often driven by patterns of water availability. We propose that nontrivial, scale‐dependent spatial patterns in both vegetation distribution and catchment water balance are generated by the presence of a convergent network of flow paths and a two‐way feedback between vegetation as a driver of evapotranspiration and vegetation distribution as a signature of water availability. Implementing this hypothesis via a simple network model demonstrated that such organization was controlled by catchment properties related to aridity, the network topology, the sensitivity of the vegetation response to water availability, and the point‐scale controls on partitioning between evapotranspiration and lateral drainage. The resulting self‐organization generated spatial dependence in areally averaged hydrologic variables, water balance, and parameters describing hydrological partitioning. This spatial scale dependence provides a theoretical approach to connect water balance at patch and catchment scales. Theoretical and empirical studies for understanding the controls of vegetation spatial distribution, point‐scale hydrological partitioning, and the implications of complex flow network topologies on the spatial scale dependence of catchment water balance are proposed as a research agenda for catchment ecohydrology