S. Zanardo

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.

Stochastic modeling of nutrient losses in streams: Interactions of climatic, hydrologic, and biogeochemical controls

We present an analytical, stochastic approach for quantifying intra-annual fluctuations of in-stream nutrient losses induced by naturally variable hydrologic conditions. The relevance of the problem we address lies in the growing concern for the major environmental impacts of increasing nutrient loads from watersheds to freshwater bodies and coastal waters. Here we express the first-order nutrient loss rate constant, k(e), as a function of key biogeochemical and hydrologic controls, in particular the stream depth (h). The stage h modulates the impact of natural streamflow temporal fluctuations (induced by intermittent rainfall forcings) on the underlying biogeochemical processes and thus represents the major driver of at-a-site fluctuations of k(e). Novel expressions for the probability distribution function (pdf) of h and k(e) are derived as a function of a few eco-hydrologic, morphologic and biogeochemical parameters. The shape of such pdfs chiefly depends on the following attributes: (1) the average frequency of streamflow-producing rainfall events, lambda; (2) the inverse of mean catchment residence time, k; and (3) a stream channel shape factor, identified through the discharge rating curve exponent b. For lambda/(kb) > 1, h and k(e) have lower intra-annual variability and lower sensitivity to climatic and morphologic controls, leading to improved predictability and ease of measurement of these attributes. Moment analyses suggest that the variability of k(e), relative to that of h, is attenuated for lambda/(kb) > 1. Thus, the interplay between climate-landscape parameters and the stream shape factor b controls the temporal variability induced by stochastic rainfall forcings on stream stages and nutrient removal rates.

Intra‐annual rainfall variability control on interannual variability of catchment water balance: A stochastic analysis

We evaluate the extent to which within-year rainfall variability controls interannual variability of catchment water balance. To this end, we analytically derive the probability density function of the annual Budyko evaporation index, B (i.e., the ratio of annual actual evapotranspiration to annual precipitation), by accounting for the stochastic nature of intra-annual rainfall fluctuation and neglecting all other sources of variability. We apply our analytical model to 424 catchments located in different climatic regions across the conterminous United States to perform this assessment. In general, we found that the model is capable of explaining mean B but is less accurate in predicting its coefficient of variation. Nonetheless, in a significant number of catchments the model can provide adequate predictions of the probability density function of B. Clear geographic patterns can be distinguished in the residuals between observed and predicted statistics of B. Interannual variability is thus not always associated with random intra-annual rainfall fluctuations. In some regions, other controls, such as seasonality and vegetation adaptations, are possibly more important. A sensitivity analysis of model parameters helped characterize the dominant controls on the distribution of B in terms of three dimensionless ratios that include climatic and soil characteristics. This study represents the first step in a diagnostic, data-driven analysis of the climatic controls on the interannual variability of catchment water balance.

Dominant controls on pesticide transport from tile to catchment scale: Lessons from a minimalist model

This paper proposes a minimalist modeling approach for characterizing pesticide concentrations in runoff from agricultural catchments across spatial scales. The model proposed is of an intermediate level of complexity between traditional chromatographic separation models and the more complex dual-domain models. Parsimony in the model is achieved by assuming stationarity of catchment travel time distributions and by coupling a dual-domain source zone model that describes near-surface pesticide dynamics with the mass response function (MRF) approach, which describes catchment-scale solute transport. The model is evaluated by comparing predicted atrazine concentrations with measured values over a 5 yr period at two spatial scales (tile drain: 3-5 ha; river station : 69 km(2)) within an intensively managed agricultural catchment in Illinois, United States. Pesticide dynamics within the source zone provided the strongest control on leaching. Two parameters were calibrated at the tile scale, Gamma, which describes partitioning in the dual-domain surficial source zone, and k(e), which describes the mass transfer rate constant between the two domains. The initial peak of concentration was found to be sensitive to Gamma, while the later peaks were sensitive to k(e). The calibrated parameters at the tile stations were used to predict atrazine dynamics at the river station. Prediction errors are examined and related to the lack of detailed information about anthropogenic forcings across scales (e. g., land-use or soil/crop management practices).