Predicting riverine dissolved silica fluxes to coastal zones from a hyperactive region and analysis of their first-order controls

Abstract

Silicate weathering and resulting transport of dissolved matter influence the global carbon cycle in two ways. First by the uptake of atmospheric/soil CO 2 and second by providing the oceanic ecosystems via the fluvial systems with the nutrient dissolved silica (DSi). Previous work suggests that regions dominated by volcanics are hyperactive or even ''hot spots'' concerning DSi-mobilization. Here, we present a new approach for predicting DSi-fluxes to coastal zones, emphasizing ''first-order'' controlling factors (lithology, runoff, relief, land cover and temperature). This approach is applied to the Japanese Archipelago, a region characterized by a high percentage of volcanics (29.1% of surface area). The presented DSi-flux model is based on data of 516 catchments, covering approximately 56.7% of the area of the Japanese Archipelago. The spatial distribution of lithology-one of the most important first order controlsis taken from a new high resolution map of Japan. Results show that the Japanese Archipelago is a hyperactive region with a DSi-yield 6.6 times higher than the world average of 3.3 t SiO 2 km -2 a -1, but with large regional variations. Approximately 10% of its area exceeds 10 times the world average DSi-yield. Slope constitutes another important controlling factor on DSi-fluxes besides lithology and runoff, and can exceed the influence of runoff on DSi-yields. Even though the monitored area on the Japanese Archipelago stretches from about 31°to 46°N, temperature is not identified as a significant first-order model variable. This may be due to the fact that slope, runoff and lithology are correlated with temperature due to regional settings of the Archipelago, and temperature information is substituted to a certain extent by these factors. Land cover data also do not improve the prediction model. This may partly be attributed to misinterpreted land cover information from satellite images. Implications of results for Earth System and global carbon cycle modeling are discussed.

The new global lithological map database GLiM: A representation of rock properties at the Earth surface

“…In contrast to the first level py, the second level attribute indicates some occurrences of pyroclastics rather than the dominant rock type of the mapped unit. This subclass is a recognition of the potential importance of the presence of pyroclastics, which was reported to exhibit very high weathering rates when fresh [Dahlgren et al, 1999;Hartmann et al, 2010].…”

“…Lithology is a key variable in many fields, including landscape evolution [de Caritat et al, 2012;Coulthard, 2001;Dürr et al, 2011;McAuliffe, 1994], pathways of water fluxes [Gleeson et al, 2011], river chemical composition [Gibbs, 1967;Hartmann, 2009;Hartmann et al, 2010;Meybeck, 1987], isotope provenance [Bataille and Bowen, 2012;Godfrey et al, 2009;Lacan and Jeandel, 2005], matter supply to ecosystems [Porder et al, 2007] and lateral land ocean matter fluxes [Berner, 1994;Godderis et al, 2009;Hartmann, 2009;Hartmann and Moosdorf, 2011;Meybeck, 1987;Moosdorf et al, 2011]. [3] Lithology is often highly heterogeneous at the regional and local scale, and even small occurrences of certain rock types can provide important information for matter fluxes at the Earth's surface (e.g., carbonate or evaporite occurrence for river chemical compositions) [e.g., Mast et al, 1990].…”

Global spatial distribution of natural riverine silica inputs to the coastal zone

“…Hartmann et al, 2010aHartmann et al, , 2011. In general, the levels of silica concentrations transported from the terrestrial to the fluvial system depend on the relative proportions of minerals in soils and rocks and their weatherability, on temperature, water residence time in soils and rocks, drainage intensity, gradient of slope, land use/cover changes and acids involved in weathering processes, as e.g., carbonic, sulphuric or humic acids (Meybeck, 1979;Wollast and Mackenzie, 1983;Drever, 1994Drever, , 1997Gaillardet et al, 1999;West et al, 2005;Jennerjahn et al, 2006;Conley et al, 2008;Hartmann et al, 2010a;Struyf et al, 2010;Cornelis et al, 2011). The yield of dissolved silica exported by rivers per unit area (t SiO 2 km −2 y −1 ) is first dependant on the river runoff (mm y −1 ), then on the control factors of concentration (Wollast and Mackenzie, 1983;Meybeck, 1994;Hartmann et al, 2010a and b;Cornelis et al, 2011).…”

“…It may even originate from a nearby COSCAT or river where general basin characteristics are similar. This informational clustering is based on lithology, climate, relief, water drainage, and abundance of lakes, which are the main control factors of silica fluxes (Wollast and Mackenzie, 1983;Drever, 1997;Hartmann et al, 2010a). This estimated DSi is then combined to the remaining runoff which can also be different from the one of the documented area (estimated DSi levels are given in Supplement 1 for each COSCAT).…”

“…However, some studies provide evidence that regions characterised by small catchments draining to coastal zones in humid and warm climates (with a specific lithologic characteristic) represent above average specific fluxes (Milliman and Syvitski, 1992;Hartmann et al, 2009Hartmann et al, , 2010a. In particular, the Ring of Fire, surrounding the Pacific Ocean, is characterised by small and steep catchments due to plate tectonics.…”