Analytical Solutions

The balanced equation for SCS_C in a single layer (Eq. [3:5.1.2a]) can be combined with Eq. [3:5.1.3a] and Eq. [3:5.1.7] and with a few assumptions allow for an analytical solution to the differential equation. The soil clay content and the C input rate were assumed to be constant and the powers α\alpha and β\beta set to 1, so that the balance equation can be solved explicitly for SCS_C. The time step was considered to be a year and we assumed that residues and manure fully decompose in that time frame so that kR=kM=1k_R=k_M=1. Since the influence of residues and manure on the SCS_C balance is similar we assumed that C inputs are only through residues. With these substitutions Eq. [3:5.1.2a] becomes:

dSCdt=hxRChxRCSxSCkSxSC2\frac{dS_C}{dt}=h_xR_C-\frac{h_xR_C}{S_x}S_C-\frac{k}{S_x}S^2_C 3:5.3.1

The constant k substitutes for kxfEftoolk_xf_Ef_{tool}. This differential equation can be solved analytically, with integration rendering the following solution:

SC(t)=hxRC2k[(ϕeγtSx1ϕeγtSx+1)1+4kSxhxRC1]S_C(t)=\frac{h_xR_C}{2k}[(\frac{\phi e^{\frac{\gamma_t}{S_x}}-1}{\phi e^{\frac{\gamma _t}{S_x}}+1})\sqrt{1+\frac{4kS_x}{h_xR_C}}-1] 3:5.3.2

γ=hxRC1+4kSxhxRC,\gamma=h_xR_C\sqrt{1+\frac{4kS_x}{h_xR_C}},

ϕ=2kSC(t=0)+hxRC+γ2kSC(t=0)+hxRCγ\phi=-\frac{2kS_C(t=0)+h_xR_C+\gamma}{2kS_C(t=0)+h_xR_C-\gamma}

The integration constant ϕ\phi depends on the initial SCS_C. The steady state solution for Eq. 3:5.3.2 is:

SC=hxRC2k1+4kSxhxRC1]S_C=\frac{h_xR_C}{2k}\sqrt{1+\frac{4kS_x}{h_xR_C}}-1] 3:5.3.3

The ratio hxRCk\frac{h_xR_C}{k} is the equilibrium SCS_C that would be obtained if neither hCh_C nor kSk_S had a dependence on SCS_C. As RCR_C increases, the value of the fraction 4kSxhxRC\frac{4kS_x}{h_xR_C} will get smaller. Therefore, the squared root term in Eq. 3:5.3.3 can be approximated as 1+124kSxhxRC1+\frac{1}{2}\frac{4kS_x}{h_xR_C} by preserving just the first two terms of the binomial expansion, from which Eq. 3:5.3.4 can be re-written as:

SC=hxRC2k(1+(12)4kSxhxRC1)=SxS_C=\frac{h_xR_C}{2k}(1+(\frac{1}{2})\frac{4kS_x}{h_xR_C}-1)=S_x 3:5.3.4

Therefore, as RCR_C increases SCS_C approaches SxS_x asymptotically (Figure 1). Taking as a reference a soil layer with SxS_x = 25 Mg C ha1^{-1}, hxh_x = 0.2, and k=0.01k=0.01 y1y^{-1}, it can be seen in Figure 1 that doubling hxh_x and kk have a similar effect but of opposite sign such that the equilibrium SCS_C increases with increasing hxh_x and decreases with increasing kk. In both cases the increase and the decrease in SCS_C are less than proportional to the increase in these two parameters. The equilibrium SCS_C, however, is very sensitive to changes in SxS_x, which makes this variable critical for a correct representation of SCS_C dynamics. This formulation is a mathematical representation of the concept of SCS_C saturation (Hassink and Whitmore, 1997; Six et al., 2002), enhanced with a control of the decomposition rate by SCS_C.

The transient trajectory of SCS_C is controlled by the quotient of the two exponential terms in Eq. [3:5.3.5].

d=1i=1N(OiSi)2i=1N(SiO+OiO)2d=1-\frac{\sum^N_{i=1}(O_i-S_i)^2}{\sum^N_{i=1}(|S_i-\overline O|+|O_i-\overline O|)^2} [3.5.3.5]

For a given SxS_x and initial SCS_C, increasing the inputs (RCR_C) changes the steady state SCS_C with decreasing marginal increments as SCS_C approaches SxS_x, yet the steady state condition is approached faster with higher inputs (Figure 3:5-1). For a given RCR_C, changing SxS_x has a substantial impact on the rate of change of SCS_C when the inputs are medium to high (Figure 3:5-1) but a minor effect if inputs are too low. This formulation strongly suggests that soils with higher carbon storage capacity (higher SxS_x) that are currently depleted of SCS_C should be the primary targets for storing SCS_C, or that soils with low SxS_x may store carbon quickly for a few years but the rate of gains will decrease earlier than in soils with higher SxS_x.

The conditions for which the SCS_C can be modeled analytically as shown here are very restrictive. The numerical solution implemented in the model is more flexible as the constants α\alpha and β\beta are allowed to differ from 1. The model can be expanded to accommodate saturation of different SOM pools, instead of just one uniform pool, as strongly suggested by the results and analysis of Stewart et al. (2008). Yet, this will require a level of parameterization for which we consider there is simply not sufficient information for a realistic implementation in numerical models.

Figure 3:5-1. Equilibrium soil organic carbon (SC, Mg C ha1^{-1}) for the steady state condition (Eq. [3:5.3.3]) with different values for humification (hxh_x, kg kg1^{-1}), SOM apparent turnover rate (kk, yr1^{-1}), and saturation soil organic carbon (SCCS_{CC}, Mg C ha1^{-1}). The line without a symbol in both panels was arbitrarily chosen as a reference. The linear, no asymptotic line in Panel A shows the equilibrium for the case in which hxh_x and kk do not depend on SCS_C so that SCS_C at equilibrium = hxRC/kh_xR_C/k, where RCR_C is the residue carbon input rate (Mg C ha1^{-1} yr1^{-1}). Panel A shows the equilibrium when SCCS_{CC} is doubled and Panel B shows the equilibrium SCS_C when hxh_x or kk is doubled.

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