Sally E. Thompson

Panta Rhei-Everything Flows: Change in hydrology and society-The IAHS Scientific Decade 2013-2022

Abstract The new Scientific Decade 2013–2022 of IAHS, entitled “Panta Rhei—Everything Flows”, is dedicated to research activities on change in hydrology and society. The purpose of Panta Rhei is to reach an improved interpretation of the processes governing the water cycle by focusing on their changing dynamics in connection with rapidly changing human systems. The practical aim is to improve our capability to make predictions of water resources dynamics to support sustainable societal development in a changing environment. The concept implies a focus on hydrological systems as a changing interface between environment and society, whose dynamics are essential to determine water security, human safety and development, and to set priorities for environmental management. The Scientific Decade 2013–2022 will devise innovative theoretical blueprints for the representation of processes including change and will focus on advanced monitoring and data analysis techniques. Interdisciplinarity will be sought by increased efforts to connect with the socio-economic sciences and geosciences in general. This paper presents a summary of the Science Plan of Panta Rhei, its targets, research questions and expected outcomes. Editor Z.W. Kundzewicz Citation Montanari, A., Young, G., Savenije, H.H.G., Hughes, D., Wagener, T., Ren, L.L., Koutsoyiannis, D., Cudennec, C., Toth, E., Grimaldi, S., Blöschl, G., Sivapalan, M., Beven, K., Gupta, H., Hipsey, M., Schaefli, B., Arheimer, B., Boegh, E., Schymanski, S.J., Di Baldassarre, G., Yu, B., Hubert, P., Huang, Y., Schumann, A., Post, D., Srinivasan, V., Harman, C., Thompson, S., Rogger, M., Viglione, A., McMillan, H., Characklis, G., Pang, Z., and Belyaev, V., 2013. “Panta Rhei—Everything Flows”: Change in hydrology and society—The IAHS Scientific Decade 2013–2022. Hydrological Sciences Journal. 58 (6) 1256–1275.

Nutrient loads exported from managed catchments reveal emergent biogeochemical stationarity

Complexity of heterogeneous catchments poses challenges in predicting biogeochemical responses to human alterations and stochastic hydro?climatic drivers. Human interferences and climate change may have contributed to the demise of hydrologic stationarity, but our synthesis of a large body of observational data suggests that anthropogenic impacts have also resulted in the emergence of effective biogeochemical stationarity in managed catchments. Long?term monitoring data from the Mississippi?Atchafalaya River Basin (MARB) and the Baltic Sea Drainage Basin (BSDB) reveal that inter?annual variations in loads (LT) for total?N (TN) and total?P (TP), exported from a catchment are dominantly controlled by discharge (QT) leading inevitably to temporal invariance of the annual, flow?weighted concentration, Cf = (LT/QT). Emergence of this consistent pattern across diverse managed catchments is attributed to the anthropogenic legacy of accumulated nutrient sources generating memory, similar to ubiquitously present sources for geogenic constituents that also exhibit a linear LT?QT relationship. These responses are characteristic of transport?limited systems. In contrast, in the absence of legacy sources in less?managed catchments, Cf values were highly variable and supply limited. We offer a theoretical explanation for the observed patterns at the event scale, and extend it to consider the stochastic nature of rainfall/flow patterns at annual scales. Our analysis suggests that: (1) expected inter?annual variations in LT can be robustly predicted given discharge variations arising from hydro?climatic or anthropogenic forcing, and (2) water?quality problems in receiving inland and coastal waters would persist until the accumulated storages of nutrients have been substantially depleted. The finding has notable implications on catchment management to mitigate adverse water?quality impacts, and on acceleration of global biogeochemical cycles.

Comparative hydrology across AmeriFlux sites: The variable roles of climate, vegetation, and groundwater

Watersheds can be characterized as complex space?time filters that transform incoming fluxes of energy, water, and nutrients into variable output signals. The behavior of these filters is driven by climate, geomorphology, and ecology and, accordingly, varies from site to site. We investigated this variation by exploring the behavior of evapotranspiration signals from 14 different AmeriFlux sites. Evapotranspiration is driven by water and energetic forcing and is mediated by ecology and internal redistribution of water and energy. As such, it integrates biological and physical controls, making it an ideal signature to target when investigating watershed filtering. We adopted a paradigmatic approach (referred to as the null model) that couples the Penman?Monteith equation to a soil moisture model and explored the deviations between the predictions of the null model and the observed AmeriFlux data across the sites in order to identify the controls on these deviations and their commonalities and differences across the sites. The null model reproduced evapotranspiration fluxes reasonably well for arid, shallow?rooted systems but overestimated the effects of water limitation and could not reproduce seasonal variation in evapotranspiration at other sites. Accounting for plant access to groundwater (or deep soil moisture) reserves and for the effects of soil temperature on limiting evapotranspiration resolved these discrepancies and greatly improved prediction of evapotranspiration at multiple time scales. The results indicate that site?specific hydrology and climatic factors pose important controls on biosphere?hydrosphere interactions and suggest that plant–water table interactions and early season phenological controls need to be incorporated into even simple models to reproduce the seasonality in evapotranspiration.

Mechanistic models of seed dispersal by wind

Over the past century, various mechanistic models have been developed to estimate the magnitude of seed dispersal by wind, and to elucidate the relative importance of physical and biological factors affecting this passive transport process. The conceptual development has progressed from ballistic models, through models incorporating vertically variable mean horizontal windspeed and turbulent excursions, to models accounting for discrepancies between airflow and seed motion. Over hourly timescales, accounting for turbulent fluctuations in the vertical velocity component generally leads to a power-law dispersal kernel that is censored by an exponential cutoff far from the seed source. The parameters of this kernel vary with the flow field inside the canopy and the seed terminal velocity. Over the timescale of a dispersal season, with mean wind statistics derived from an “extreme-value” distribution, these distribution-tail effects are compounded by turbulent diffusion to yield seed dispersal distances that are two to three orders of magnitude longer than the corresponding ballistic models. These findings from analytic models engendered explicit simulations of the effects of turbulence on seed dispersal using computationally intensive fluid dynamics tools. This development marks a bifurcation in the approaches to wind dispersal, seeking either finer resolution of the dispersal mechanism at the scale of a single dispersal event, or mechanistically derived analytical dispersal kernels needed to resolve long-term and large-scale processes such as meta-population dynamics and range expansion. Because seed dispersal by wind is molded by processes operating over multiple scales, new insights will require novel theoretical tactics that blend these two approaches while preserving the key interactions across scales.

Analytical model for flow duration curves in seasonally dry climates

Flow duration curves (FDC) display streamflow values against their relative exceedance time. They provide critical information for watershed management by representing the variation in the availability and reliability of surface water to supply ecosystem services and satisfy anthropogenic needs. FDCs are particularly revealing in seasonally dry climates, where surface water supplies are highly variable. While useful, the empirical computation of FDCs is data intensive and challenging in sparsely gauged regions, meaning that there is a need for robust, predictive models to evaluate FDCs with simple parameterization. Here, we derive a process-based analytical expression for FDCs in seasonally dry climates. During the wet season, streamflow is modeled as a stochastic variable driven by rainfall, following the stochastic analytical model of Botter et al. (2007a). During the dry season, streamflow is modeled as a deterministic recession with a stochastic initial condition that accounts for the carryover of catchment storage across seasons. The resulting FDC model is applied to 38 catchments in Nepal, coastal California, and Western Australia, where FDCs are successfully modeled using five physically meaningful parameters with minimal calibration. A Monte Carlo analysis revealed that the model is robust to deviations from its assumptions of Poissonian rainfall, exponentially distributed response times and constant seasonal timing. The approach successfully models period-of-record FDCs and allows interannual and intra-annual sources of variations in dry season streamflow to be separated. The resulting median annual FDCs and confidence intervals allow the simulation of the consequences of interannual flow variations for infrastructure projects. We present an example using run-of-river hydropower in Nepal as a case study. Key Points Probabilistic derivation of flow distribution in seasonally dry climate Successfully applied in Nepal, California, and Western Australia Disentangles inter- and intra-annual streamflow variations

Hydrologic refugia, plants, and climate change

Abstract Climate, physical landscapes, and biota interact to generate heterogeneous hydrologic conditions in space and over time, which are reflected in spatial patterns of species distributions. As these species distributions respond to rapid climate change, microrefugia may support local species persistence in the face of deteriorating climatic suitability. Recent focus on temperature as a determinant of microrefugia insufficiently accounts for the importance of hydrologic processes and changing water availability with changing climate. Where water scarcity is a major limitation now or under future climates, hydrologic microrefugia are likely to prove essential for species persistence, particularly for sessile species and plants. Zones of high relative water availability – mesic microenvironments – are generated by a wide array of hydrologic processes, and may be loosely coupled to climatic processes and therefore buffered from climate change. Here, we review the mechanisms that generate mesic microenvironments and their likely robustness in the face of climate change. We argue that mesic microenvironments will act as species‐specific refugia only if the nature and space/time variability in water availability are compatible with the ecological requirements of a target species. We illustrate this argument with case studies drawn from California oak woodland ecosystems. We posit that identification of hydrologic refugia could form a cornerstone of climate‐cognizant conservation strategies, but that this would require improved understanding of climate change effects on key hydrologic processes, including frequently cryptic processes such as groundwater flow. &NA; In warming, drying climates, locally wet sites could form hydrologic microrefugia in which species could persist even as the surrounding landscape becomes unsuitable habitat. A wide variety of physical processes could form locally wet sites, which, if they meet physiological and community‐interaction requirements, could act as microrefugia. Identifying these sites could strengthen climate‐cognizant conservation strategies, but requires improved understanding of hard‐to‐observe hydrologic processes such as groundwater flow. Figure. No caption available.

Water cycle dynamics in a changing environment: Improving predictability through synthesis

All science is the search for unity in hidden likenesses...The progress of science is the discovery at each step of a new order which gives unity to what had long seemed unlike... For order does not display itself of itself; if it can be said to be there at all, it is not there for the mere looking... order must be discovered and, in a deep sense, it must be created. What we see, as we see it, is mere disorder.

Secondary seed dispersal and its role in landscape organization

[1] Mathematical models of banded vegetation patterns predict rapid upslope migration of vegetated patches not realized in field observations, a key point of disagreement between theory and observation. It is shown that the disagreement between model results and field observations can arise from seed dispersal dynamics. Two representations of biomass movement are used to test the hypothesis that secondary seed dispersal in overland flow inhibits band migration. The first is based on coupling down-slope water transport and seed advection. The second uses a kernel-based representation of seed transport where an anisotropic dispersal kernel combines the effects of isotropic primary and downslope secondary seed dispersal, and ensures that conclusions about secondary dispersal are independent of diffusive representations of biomass movement. The analysis demonstrates that secondary seed dispersal can retard upward movement of banded vegetation irrespective of the precise representation of biomass movement as long as the anisotropic effects are accounted for.

Plant Propagation Fronts and Wind Dispersal: An Analytical Model to Upscale from Seconds to Decades Using Superstatistics

Scale separation crossing many orders of magnitude is a consistent challenge in the ecological sciences. Wind dispersal of seed that generates plant propagation fronts is a typical case where timescales range from less than a second for fast turbulent processes to interannual timescales governing plant growth and climatic forcing. We show that the scale separation can be overcome by developing mechanistic and statistical links between processes at the different timescales. A mechanistic model is used to scale up from the turbulent regime to hourly timescales, while a superstatistical approach is used to relate the half‐hourly timescales to annual vegetation migration speeds. We derive a semianalytical model to predict vegetation front movement as a function of wind‐forcing statistics and characteristics of the species being dispersed. This model achieves better than order‐of‐magnitude agreement in a case study of tree dispersal from the early Holocene, a marked improvement over diffusion models. Plant migration is shown to depend nonlinearly on the wind environment forcing the movement but linearly on most physiological parameters. Applications of these analytical results to parameterizing models of plant dispersion and the implications of the superstatistical approach for addressing other ecological problems plagued by similar “dimensionality curses” are outlined.

Rainfall and temperatures changes have confounding impacts on Phytophthora cinnamomi occurrence risk in the southwestern USA under climate change scenarios

Global change will simultaneously impact many aspects of climate, with the potential to exacerbate the risks posed by plant pathogens to agriculture and the natural environment; yet, most studies that explore climate impacts on plant pathogen ranges consider individual climatic factors separately. In this study, we adopt a stochastic modeling approach to address multiple pathways by which climate can constrain the range of the generalist plant pathogen Phytophthora cinnamomi (Pc): through changing winter soil temperatures affecting pathogen survival; spring soil temperatures and thus pathogen metabolic rates; and changing spring soil moisture conditions and thus pathogen growth rates through host root systems. We apply this model to the southwestern USA for contemporary and plausible future climate scenarios and evaluate the changes in the potential range of Pc. The results indicate that the plausible range of this pathogen in the southwestern USA extends over approximately 200,000 km(2) under contemporary conditions. While warming temperatures as projected by the IPCC A2 and B1 emissions scenarios greatly expand the range over which the pathogen can survive winter, projected reductions in spring rainfall reduce its feasible habitat, leading to spatially complex patterns of changing risk. The study demonstrates that temperature and rainfall changes associated with possible climate futures in the southwestern USA have confounding impacts on the range of Pc, suggesting that projections of future pathogen dynamics and ranges should account for multiple pathways of climate-pathogen interaction.