A dynamic model for suspended particulate matter (SPM) in rivers
Article first published online: 5 JAN 2006
Global Ecology and Biogeography
Volume 15, Issue 1, pages 93–107, January 2006
How to Cite
Håkanson, L. (2006), A dynamic model for suspended particulate matter (SPM) in rivers. Global Ecology and Biogeography, 15: 93–107. doi: 10.1111/j.1466-822X.2006.00196.x
- Issue published online: 5 JAN 2006
- Article first published online: 5 JAN 2006
- Dynamic model;
- predictive power;
- suspended particulate matter;
Aim To present a general, process-based river model for suspended particulate matter (SPM).
Location General approach based on processes; data from Europe and Israel.
Methods The model has been tested and calibrated using an empirical river model for SPM and validated (blind-tested) using data from seven European sites. This modelling gives mean monthly SPM concentrations in water for defined river sites. The model is based on processes in the entire upstream river stretch (and not for given river segments) and calculates the transport of SPM from land to water, primary production of SPM (within the upstream river stretch), resuspension, mineralization and retention of SPM in the upstream river stretch (but not bed load of friction materials, such as sand). The catchment area is differentiated into inflow (∼ dry land) areas and outflow area (∼ wetland areas dominated by relatively fast horizontal SPM-fluxes). The model is simple to apply in practice as all driving variables may be accessed readily from maps. The driving variables are: latitude, altitude, continentality, catchment area and mean annual precipitation.
Results Modelled values have been compared to independent empirical data from sites covering a relatively wide domain (catchment areas from 93 to 5250 km2, precipitation from 400 to 660 mm year−1, altitudes from −210 to 150 m a.s.l., latitudes from 47 to 59° N and continentalities from 200 to 1000 km from the ocean). When blind-tested, the model predicts annual SPM-fluxes well.
Conclusion When modelled values are compared to empirical data, the slope is almost perfect (1.03) and the r2-value is 0.9996. This is good, given the fact that there are several simplifications in the model structure. It must, however, be stressed that there are only seven validation cases and that this model has not been tested for small catchments.