[1] Field studies in watershed hydrology continue to characterize and catalogue the enormous heterogeneity and complexity of rainfall runoff processes in more and more watersheds, in different hydroclimatic regimes, and at different scales. Nevertheless, the ability to generalize these findings to ungauged regions remains out of reach. In spite of their apparent physical basis and complexity, the current generation of detailed models is process weak. Their representations of the internal states and process dynamics are still at odds with many experimental findings. In order to make continued progress in watershed hydrology and to bring greater coherence to the science, we need to move beyond the status quo of having to explicitly characterize or prescribe landscape heterogeneity in our (highly calibrated) models and in this way reproduce process complexity and instead explore the set of organizing principles that might underlie the heterogeneity and complexity. This commentary addresses a number of related new avenues for research in watershed science, including the use of comparative analysis, classification, optimality principles, and network theory, all with the intent of defining, understanding, and predicting watershed function and enunciating important watershed functional traits.

AimsThe field of ecohydrology is providing new theoretical frameworks and methodological approaches for understanding the complex interactions and feedbacks between vegetation and hydrologic flows at multiple scales. Here we review some of the major scientific and technological advances in ecohydrology as related to understanding the mechanisms by which plant-water relations influence water fluxes at ecosystem, watershed and landscape scales. Important FindingsWe identify several cross-cutting themes related to the role of plantwater relations in the ecohydrological literature, including the contrasting dynamics of water-limited and water-abundant ecosystems, transferring information about water fluxes across scales, understanding spatiotemporal heterogeneity and complexity, ecohydrological triggers associated with threshold behavior and shifts between alternative stable states and the need for long-term data sets at multiple scales. We then show how these themes are embedded within three key research areas where improved understanding of the linkages between plant-water relations and the hydrologic cycle have led to important advances in the field of ecohydrology: upscaling water fluxes from the leaf to the watershed and landscape, effects of plant-soil interactions on soil moisture dynamics and controls exerted by plant water use patterns and mechanisms on streamflow regime. In particular, we highlight several pressing environmental challenges facing society today where ecohydrology can contribute to the scientific knowledge for developing sound management and policy solutions. We conclude by identifying key challenges and opportunities for advancing contributions of plant-water relations research to ecohydrology in the future. Keywords: ecohydrology d plant water use d regime shift d thresholds d scaling d transpiration

[1] Complex hydrological descriptions at the hillslope scale have been difficult to incorporate within a catchment modeling framework because of the disparity between the scale of measurements and the scale of model subunits. As a result, parameters represented in many conceptual models are often not related to physical properties and therefore cannot be established prior to a model calibration. While tolerable for predictions involving water quantity, water quality simulations require additional attention to transport processes, flow path sources, and water age. This paper examines how isotopic estimates of residence time may be used to subsume flow path process complexity and to provide a simple, scalable evaluative data source for water quantity-and quality-based conceptual models. We test a set of simple distributed hydrologic models (from simple to more complex) against measured discharge and residence time and employ a simple Monte Carlo framework to evaluate the identifiability of parameters and how the inclusion of residence time contributes to the evaluative process. Results indicate that of the models evaluated, only the most complex, including an explicit unsaturated zone volume and an effective porosity, successfully reproduced both discharge dynamics and residence time. In addition, the inclusion of residence time in the evaluation of the accepted models results in a reduction of the a posteriori parameter uncertainty. Results from this study support the conclusion that the incorporation of soft data, in this case, isotopically estimated residence times, in model evaluation is a useful mechanism to bring experimental evidence into the process of model evaluation and selection, thereby providing one mechanism to further reconcile hillslope-scale complexity with catchmentscale simplicity.

[1] End member mixing analysis (EMMA) is a commonly applied method to identify and quantify the dominant runoff producing sources of water. It employs tracers to determine the dimensionality of the hydrologic system. Many EMMA studies have been conducted using two to six tracers, with some of the main tracers being Ca, Na, Cl À , water isotopes, and alkalinity. Few studies use larger tracer sets including minor trace elements such as Li, Rb, Sr, and Ba. None of the studies has addressed the question of the tracer set size and composition, despite the fact that these determine which and how many end members (EM) will be identified. We examine how tracer set size and composition affects the conceptual model that results from an EMMA. We developed an automatic procedure that conducts EMMA while iteratively changing tracer set size and composition. We used a set of 14 tracers and 9 EMs. The validity of the resulting conceptual models was investigated under the aspects of dimensionality, EM combinations, and contributions to stream water. From the 16,369 possibilities, 23 delivered plausible results. The resulting conceptual models are highly sensitive to the tracer set size and composition. The moderate reproducibility of EM contributions indicates a still missing EM. It also emphasizes that the major elements are not always the most useful tracers and that larger tracer sets have an enhanced capacity to avoid false conclusions about catchment functioning. The presented approach produces results that may not be apparent from the traditional approach and it is a first step to add the idea of statistical significance to the EMMA approach.