Concentration-discharge (c-Q) plots are routinely used as an integrated signal of watershed response to infer solute sources and travel pathways. However, the interpretation of c-Q data can be difficult unless these data are fitted using statistical models. Such models are frequently applied for geogenic solutes, but it is unclear to what extent they might aid in the investigation of nutrient export patterns, particularly for total dissolved phosphorus (TDP) which is a critical driver of downstream eutrophication problems. The goal of the present study was therefore to statistically model c-Q relations (where c is TDP concentrations) in a set of contrasting watersheds in the Northern Great Plains-ranging in size from 0.2 to 1000+ km 2 -to assess the controls of landscape properties on TDP transport dynamics. Six statistical models were fitted to c-Q data, notably (a) one linear model, (b) one model assuming that c-Q relations are driven by the mixing of end-member waters from different landscape locations (i.e., hydrograph separation), (c) one model relying on a biogeochemical stationarity hypothesis (i.e., power law), (d) one model hypothesizing that c-Q relations change as a function of the solute subsurfacecontact time (i.e., hyperbolic model), and (e) two models assuming that solute fluxes are mostly dependent on reaction rates (i.e., chemical models). Model performance ranged from mediocre (R 2 < 0.2) to very good (R 2 > 0.9), but the hydrograph separation model seemed most universal.No watershed was found to exhibit chemostatic behaviour, but many showed signs of dilution or enrichment behaviour. A tendency toward a multi-model fit and better model performance was observed for watersheds with moderate slope and higher effective drainage area. The relatively poor model performance obtained outside these conditions illustrates the likely importance of controls on TDP concentrations in the region that are independent of flow dynamics.

Studies examining hydrologic response to climatic inputs at hillslope and small catchment scales have shown highly nonlinear runoff behavior (Beven et al., 1988; McDonnell et al., 2007; Sivapalan, 2006; Sivapalan et al., 2002). While these studies have greatly advanced our understanding of runoff generation processes, the "uniqueness of place" (Beven, 2000) inherent to isolated studies has resulted in limited transferability of some findings, making generalization across sites difficult (McDonnell et al., 2007; Scaife & Band, 2017; Sivapalan, 2006). The difficulty in generalizing some process conceptualizations has motivated a shift in focus toward emergent properties, that is, properties that cannot be predicted from individual landscape components but reflect landscape heterogeneity and process complexity (Lehmann et al., 2007; McDonnell et al., 2007). Thresholds in runoff response are one of these properties and are generally defined as critical moments in time or points in space at which runoff behavior rapidly changes (Ali et al., 2013; Phillips, 2006). For critical moments in time, thresholds are typically defined as values of one or multiple meteorological factors that trigger a nonlinear change in hydrologic response characteristics. Thresholds are assessed through the evaluation of scatter plots that compare hydrologic response metrics (y-axis) to meteorological factors (x-axis). To date, threshold-related research has mostly taken place on hillslopes and catchments in temperate or humid environments (e.g.,

Numerous studies have examined the event‐specific hydrologic response of hillslopes and catchments to rainfall. Knowledge gaps, however, remain regarding the relative influence of different meteorological factors on hydrologic response, the predictability of hydrologic response from site characteristics, or even the best metrics to use to effectively capture the temporal variability of hydrologic response. This study aimed to address those knowledge gaps by focusing on 21 sites with contrasting climate, topography, geology, soil properties, and land cover. High‐frequency rainfall and discharge records were analysed, resulting in the delineation of over 1,600 rainfall–runoff events, which were described using a suite of hydrologic response metrics and meteorological factors. Univariate and multivariate statistical techniques were then applied to synthesize the information conveyed by the computed metrics and factors, notably measures of central tendency and variability, variation partitioning, partial correlations, and principal component analysis. Results showed that some response magnitude metrics generally reported in the literature (e.g., runoff ratio and area‐normalized peak discharge) did not vary significantly among sites. The temporal variability in site‐specific hydrologic response was often attributable to the joint influence of storage‐driven (e.g., total event rainfall and antecedent precipitation) and intensity‐driven (e.g., rainfall intensity and antecedent potential evapotranspiration) meteorological factors. Mean annual temperature and potential evapotranspiration at a given site appeared to be good predictors of hydrologic response timing (e.g., response lag and lag to peak). Response timing metrics, particularly those associated with response initiation, were also identified as the metrics most critical for capturing intrasite response variability. This study therefore contributes to the growing knowledge on event‐specific hydrologic response by highlighting the importance of response timing metrics and intensity‐driven meteorological factors, which are infrequently discussed in the literature. As few correlations were found between physiographic variables and response metrics, more data‐driven studies are recommended to further our understanding of landscape–hydrology interactions.

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