Soumya,B.S., Sekhar,m., Riotte,J., Audry,S., Lagane,C. and Braun,J.-J.(2011): Inverse models to analyze the spatiotemporal variations of chemical weathering fluxes in a granito-gneissic watershed: Mule Hole, South India. Geoderma, 165, 12-24.

『花崗岩−片麻岩集水域における化学風化フラックスの時空間変動を解析するためのインバース(逆)モデル:南インドのミュールホール』


Abstract
 Water-rock reactions are driven by the influx of water, which are out of equilibrium with the mineral assemblage in the rock. Here a mass balance approach is adopted to quantify these reactions. Based on field experiments carried out in a granito-gneissic small experimental watershed (SEW), Mule Hole SEW (〜4.5 km2), quartz, oligoclase, sericite, epidote and chlorite are identified as the basic primary minerals while kaolinite, goethite and smectite are identified as the secondary minerals. Observed groundwater chemistry is used to determine the weathering rates, in terms of ‘Mass Transfer Coefficients’ (MTCs), of both primary and secondary minerals.
 Weathering rates for primary and secondary minerals are quantified in two steps. In the first step, top red soil is analyzed considering precipitation chemistry as initial phase and water chemistry of seepage flow as final phase. In the second step, minerals present in the saprolite layer are analyzed considering groundwater chemistry as the output phase. Weathering rates thus obtained are converted into weathering fluxes (Qweathering) using the recharge quantity.
 Spatial variability in the mineralogy observed among the thirteen wells of Mule Hole SEW is observed to be reflected in the MTC results and thus in the weathering fluxes. Weathering rates of the minerals in this silicate system varied from few 10μmol/L (in case of biotite) to 1000 s of micromoles per liter (calcite). Similarly, fluxes of biotite are observed to be least (7±5 mol/ha/yr) while those of calcite are highest (1265±791 mol/ha/yr). Further, the fluxes determined annually for all the minerals are observed to be within the bandwidth of the standard deviation of these fluxes. Variations in these annual fluxes are indicating the variations in the precipitation. Here, the standard deviation indicated the temporal variations in the fluxes, which might be due to the variations in the annual rainfall. Thus, the methodology adopted defines an inverse way of determining weathering fluxes, which mainly contribute to the groundwater concentration.

Keywords: Mass transfer coefficient (MTC); Groundwater chemistry; Mineralogy; Silicate chemical weathering; Regolith; Weathering fluxes』

1. Introduction
2. Field settings
 2.1. Protolith
 2.2.Regolith
 2.3. Hydrology and hydrogeology
3. Methodology
 3.1. Water sampling and analyses
 3.2. Observation well network
 3.3. Theoretical mass balance approach
4. Conceptual inverse models for determining weathering rates and fluxes
 4.1. Models for soil layer (Step 1)
 4.2. Model for saprolite layer (Step 2)
5. Results
6. Discussion - application of inverse models
 6.1. Weathering rates (MTC) of minerals in the topsoil zone and saprolite
 6.2. Weathering fluxes (Qweathering) in the soil and saprolite
  6.2.1. In the soil
  6.2.2. In the saprolite
 6.3. Variability in the weathering fluxes
  6.3.1. Spatial variability
  6.3.2. Temporal variability
7. Conclusions
Acknowledgement
References


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