IntroductionThe time water spends travelling subsurface through a catchment to the stream network (i.e. the catchment water transit time) fundamentally describes the storage, flow pathway heterogeneity and sources of water in a catchment. The distribution of transit times reflects how catchments retain and release water and solutes that in turn set biogeochemical conditions and affect contamination release or persistence. Thus, quantifying the transit time distribution provides an important constraint on biogeochemical processes and catchment sensitivity to anthropogenic inputs, contamination and land-use change. Although the assumptions and limitations of past and present transit time modelling approaches have been recently reviewed (McGuire and McDonnell, 2006), there remain many fundamental research challenges for understanding how transit time can be used to quantify catchment flow processes and aid in the development and testing of rainfall-runoff models. In this Commentary study, we summarize what we think are the open research questions in transit time research. These thoughts come from a 3-day workshop in January 2009 at the International Atomic Energy Agency in Vienna. We attempt to lay out a roadmap for this work for the hydrological community over the next 10 years. We do this by first defining what we mean (qualitatively and quantitatively) by transit time and then organize our vision around needs in transit time theory, needs in field studies of transit time and needs in rainfall-runoff modelling. Our goal in presenting this material is to encourage widespread use of transit time information in process studies to provide new insights to catchment function and to inform the structural development and testing of hydrologic models. What is transit time?The terminology on time concepts associated with water movement through catchments can be confusing and a barrier to its use. Water transit time through the system can be defined as:where t w is the elapsed time from the input of water through a system input boundary at time t in to the output of that water through a system output boundary at time t out . In a catchment, the land surface and the catchment outlet may be considered as the main input and output boundaries for most of the water flow through the catchment (Figure 1). However, the land surface constitutes both a water input boundary and an output boundary for water that experiences evapotranspiration (ET). Considering also the subsurface depth dimension of a catchment, groundwater flow into and out of the catchment system is determined by prevailing groundwater divides and hydraulic gradients, which may vary in time and space and differ from the topographically determined catchment boundaries. For general transient flow conditions, water may thus flow into and out from the catchment system through different boundaries that are not all fixed in time and space. By analogy to the water transit time definition and quantification in Equation (1), one can similarly define and quantify the mean age o...

Abstract:Hydrological studies across varied climatic and physiographic regions have observed small changes in the 'states of wetness'; based on average soil moisture, can lead to dramatic changes in the amount of water delivered to the stream channel. This non-linear behaviour of the storm response has been attributed to a critical switching in spatial organization of shallow soil moisture and hydrologic connectivity. However, much of the analysis of the role of soil moisture organization and connectivity has been performed in small rangeland catchments. Therefore, we examined the relationship between hydrologic connectivity and runoff response within a temperate forested watershed of moderate relief. We have undertaken spatial surveys of shallow soil moisture over a sequence of storms with varying antecedent moisture conditions. We analyse each survey for evidence of hydrologic connectivity and we monitor the storm response from the catchment outlet. Our results show evidence of a non-linear response in runoff generation over small changes in measures of antecedent moisture conditions; yet, unlike the previous studies of rangeland catchments, in this forested landscape we do not observe a significant change in geostatistical hydrologic connectivity with variations in antecedent moisture conditions. These results suggest that a priori spatial patterns in shallow soil moisture in forested terrains may not always be a good predictor of critical hydrologic connectivity that leads to threshold change in runoff generation, as has been the case in rangeland catchments.

[1] Current interest in multicatchment hydrologic studies challenges the use of geochemical mixing models across scale, where changes in stream water chemistry from catchment to catchment may indicate (1) changes in the proportional contributions of end-members, (2) changes in the geochemical signatures of end-members in space, or (3) changes in the geochemical signatures of end-members in time. In this study we examine stream water chemistry from a series of eight nested catchments in a 1.47 km 2 temperate forest watershed in southern Quebec for evidence of contributing end-members. We use eigenvector and residual analysis (Hooper, 2003) of the multivariate stream water chemistry records to estimate the dimensionality of the mixing space for each individual catchment, indicating the number of contributing end-members. Using the mixing space of the largest, highest-order catchment (1.47 km 2 ), we evaluate its ability to predict stream water chemistry in the seven upstream catchments, representing progressively smaller areas. We observe significant spatial variation in ionic mixing ratios within the 147 ha watershed. Only spatial testing across catchments allowed us to identify appropriate conservative tracers most compatible with the application of a single mixing model across scale. On the seasonal timescale, groundwater geochemistry changes significantly due to the recharge from spring snowmelt, indicating a mixture of two groundwater end-members of varying age. On the timescale of storm events, shallow perched water and throughfall provide geochemical signatures consistent with physical mixing while unsaturated zone soil water sampled from local pockets of glacial till does not. Our results suggest cautious application of end-member mixing analysis (EMMA) for multicatchment studies.Citation: James, A. L., and N. T. Roulet (2006), Investigating the applicability of end-member mixing analysis (EMMA) across scale: A study of eight small, nested catchments in a temperate forested watershed, Water Resour. Res., 42, W08434,

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The physical dynamics of lake temperature and ice phenology are important in the modelling and management of temperate aquatic ecosystems. One-dimensional hydrothermal lake models have not been well evaluated in terms of how they simulate ice dynamics in particular. We chose four models (Hostetler, Minlake, Simple Ice Model or SIM and General Lake Model) to test and compare their performance modelling water temperature and ice dynamics using 16 years of field data from Harp Lake, an extensively studied inland lake in south-central Ontario. Each model produced satisfactory water temperature profiles over the simulated period, with small differences in the model performance. Model fits for ice phenology and ice thickness were, however, considerably lower than those for water temperature, with Minlake generating the best agreement with observed ice-on and ice-off dates as well as ice thickness, followed by SIM. The responses of lake ice dynamics to future climate scenarios were simulated by running each of the four models for 91 years, from 2010 to 2100. The predicted decrease in ice season length was significantly different among models, varying between 30 and 81 days, with an average of 48 days. Corresponding decreases in ice thickness varied between 0.11 and 0.20 m, averaging 0.17 m. This study demonstrates that uncertainty due to model performance and selection is considerable, and further testing and refinement of hydrothermal lake dynamic models are needed to improve predictive abilities for ice dynamics. Figure 7. Ice phenology (modelled versus observed) for four models: Hostetler (a), Minlake (b), GLM (c) and SIM (d), in terms of three ice features: ice thickness (i), ice-on date (ii) and ice-off date (iii) 4597 COMPARING ICE AND TEMPERATURE SIMULATIONS BY LAKE MODELS

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[1] Recent studies of catchment hydrologic response are incorporating increasingly complex datasets to investigate model representation of spatial and temporal variability. In this paper, catchment rainfall-runoff and stable isotope tracer response were modeled using a lumped conceptual model that integrates the unit hydrograph and isotope hydrograph separation methodologies. The model was applied across eight nested catchments (7 to 147 ha) for four rainstorms collected between summer and fall in 2001-2002, generating a usable 23 rainstorm datasets ranging from 1.2 to 10.3 h in length and spanning variability in environmental conditions related to storm characteristics (size and intensity) and antecedent moisture. Monte Carlo simulations were run for four model structures of varying complexity and evaluated using a Generalized Likelihood Uncertainty Estimation (GLUE) approach. We found that a model of intermediate complexity was adequate to model all catchment-storm pairs. Relationships between the parameters of the best model and catchment and storm characteristics were sought. We found that the fraction of effective rainfall routed as event water was correlated to rainstorm size but insensitive to catchment size, indicating that it is controlled by environmental conditions such as storm intensity and size. The mean transit time of event water decreased with increasing rainstorm size, indicating increased connectivity during larger rainstorms. Finally, a linear relation was found between the mean transit time of event water and catchment size suggesting that the time it takes for event water to be transferred to the stream is directly related to catchment size, particularly for catchments greater than 30 ha.Citation: Segura, C., A. L. James, D. Lazzati, and N. T. Roulet (2012), Scaling relationships for event water contributions and transit times in small-forested catchments in Eastern Quebec, Water Resour. Res., 48, W07502,