Heavy metal transport in large river systems: heavy metal emissions and loads in the Rhine and Elbe river basins

Abstract

Abstract:Pollutant transport and management in the Rhine and Elbe basins is still of international concern, since certain target levels set by the international committees for protection of both rivers have not been reached. The analysis of the chain of emissions of point and diffuse sources to river loads will provide policy makers with a tool for effective management of river basins. The analysis of large river basins such as the Elbe and Rhine requires information on the spatial and temporal characteristics of both emissions and physical information of the entire river basin. In this paper, an analysis has been made of heavy metal emissions from various point and diffuse sources in the Rhine and Elbe drainage areas. Different point and diffuse pathways are considered in the model, such as inputs from industry, wastewater treatment plants, urban areas, erosion, groundwater, atmospheric deposition, tile drainage, and runoff. In most cases the measured heavy metal loads at monitoring stations are lower than the sum of the heavy metal emissions. This behaviour in large river systems can largely be explained by retention processes (e.g. sedimentation) and is dependent on the specific runoff of a catchment. Independent of the method used to estimate emissions, the source apportionment analysis of observed loads was used to determine the share of point and diffuse sources in the heavy metal load at a monitoring station by establishing a discharge dependency. The results from both the emission analysis and the source apportionment analysis of observed loads were compared and gave similar results. Between 51% (for Hg) and 74% (for Pb) of the total transport in the Elbe basin is supplied by inputs from diffuse sources. In the Rhine basin diffuse source inputs dominate the total transport and deliver more than 70% of the total transport. The diffuse hydrological pathways with the highest share are erosion and urban areas.

Storage of sediment‐associated heavy metals along the channelized Odra River, Poland

“…Despite the potential cycling of heavy metals by contaminant leaching during water table fluctuations or the re-working of alluvial sediments during floods, there have been few attempts to assess the pattern of heavy metals stored along heavily modified channels (Vink and Behrendt, 2002). This paper describes an investigation of the Odra River in western Poland, where channelization works preceded an extended period of heavy industrialization and documented riverine pollution.…”

Sediment research, management and policy

“…Diffuse sources (groundwater, urban runoff, soil erosion etc.) on the other hand became relatively more important over time and presently contribute more than 70% of the total load (Vink and Behrendt 2002).…”

Relating hydrogeomorphic properties to stream buffering chemistry in the Neversink River watershed, New York State, USA

“…Differences in baseflow ANC throughout the Neversink are expected to be correlated with the fraction of stream water from deep sources where cations (which contribute to ANC) derived from weathering are likely to be in the highest concentrations. Thus, subsurface contact time and watershed residence time have been proposed as predictors of watershed ANC (Wolock et al, 1997). Residence time estimates using 18 O and 35 S indicate that stream baseflow (¾300 days old) is derived from the mixing of a deeper groundwater system (groundwater springs had residence times of ¾500 days) and faster, shallow flowpaths (Burns et al, 1998a).…”

“…Predicting a watershed's ability to buffer acidity during baseflow is crucial to cost-effective management of water chemistry and biota in the Northeastern US (Peters and Driscoll, 1987;Van Sickle et al, 1997). Regression models for predicting buffering chemistry at baseflow typically relate average water chemistry values to geologic, land cover, topographic, and/or soil properties (Wolock et al, 1997;Clow et al, 2000;Cooper et al, 2004;Sullivan et al, 2007). These spatial properties are used to infer the sources and flowpaths which control baseflow buffering chemistry (Peters and Driscoll, 1987;3760 A.…”