Search for: All records

Abstract Plastic litter is a globally pervasive pollutant. Storms are likely key drivers of plastic transport to oceans, but plastic transport during rising and falling limbs of storm hydrographs is rarely measured. Measurements of plastic movement throughout individual storms will improve watershed models of plastic dynamics. We used cameras to quantify macroplastic movement (i.e., particles > 5 mm) in rivers before, during, and after individual storms (N = 18) at 10 sites within three North American watersheds. Most storms showed no difference in macroplastic transport between rising and falling hydrograph limbs or evidence of hysteresis (transport rate range = 0–236 items/30 min). Total macroplastic exported during storm events was positively related to storm magnitude and was greatest at more urban sites. Thus, macroplastic transport during storms was driven by storm size and land use. The quantitative relationships between macroplastic movement and hydrology will improve discharge‐weighted calculations of macroplastic transport which can benefit modeling, monitoring, and mitigation efforts. Practitioner PointsMacroplastic particles (i.e, > 5 mm) are both retained in urban streams (e.g., in debris dams), and move downstream during baseflow and stormflow conditionsStorm flows are key periods of macroplastic transport: transport rates are higher on both rising and falling limbs of storm hydrographs relative to baseflow.The amount of macroplastics moving during storm flows is positively related to storm intensity.The predictive relationships generated between storm flow and macroplastic transport will improve estimates of annual export, and policies for macroplastic pollution reduction. 

Abstract Regional warming and associated changes in hydrologic systems pose challenges to water supply management in river basins of the western United States and call for improved understanding of the spatial and temporal variability of runoff. We apply a network of total width, subannual width, and delta blue intensity tree-ring chronologies in combination with a monthly water balance model to identify droughts and their associated precipitationPand temperatureTfootprints in the Truckee–Carson River basin (TCRB). Stepwise regression gave reasonably accurate reconstructions, from 1688 to 1999, of seasonalPandT(e.g.,R²= 0.50 for May–SeptemberT). These were disaggregated to monthly values, which were then routed through a water balance model to generate “indirectly” reconstructed runoff. Reconstructed and observed annual runoff correlate highly (r= 0.80) from 1906 to 1999. The extended runoff record shows that twentieth-century droughts are unmatched in severity in a 300-yr context. Our water balance modeling reconstruction advances the conventional regression-based dendrochronological methods as it allows for multiple hydrologic components (evapotranspiration, snowmelt, etc.) to be evaluated. We found that imposed warming (3° and 6°C) generally exacerbated the runoff deficits in past droughts but that impact could be lessened and sometimes even reversed in some years by compensating factors, including changes in snow regime. Our results underscore the value of combining multiproxy tree-ring data with water balance modeling to place past hydrologic droughts in the context of climate change. Significance StatementWe show how water balance modeling in combination with tree-ring data helps place modern droughts in the context of the past few centuries and a warming climate. Seasonal precipitation and temperature were reconstructed from multiproxy tree-ring data for a mountainous location near Lake Tahoe, and these reconstructions were routed through a water balance model to get a record of monthly runoff, snowmelt, and other water balance variables from 1688 to 1999. The resulting extended annual runoff record highlights the unmatched severity of twentieth-century droughts. A warming of 3°C imposed on reconstructed temperature generally exacerbates the runoff anomalies in past droughts, but this effect is sometimes offset by warming-related changes in the snow regime.