## 2.25.8. Inundated Fraction Prediction[¶](#inundated-fraction-prediction "Permalink to this headline")
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A simplified dynamic representation of spatial inundation based on recent work by [Prigent et al. (2007)](https://escomp.github.io/ctsm-docs/versions/master/html/tech_note/References/CLM50_Tech_Note_References.html#prigentetal2007) is used. [Prigent et al. (2007)](https://escomp.github.io/ctsm-docs/versions/master/html/tech_note/References/CLM50_Tech_Note_References.html#prigentetal2007) described a multi-satellite approach to estimate the global monthly inundated fraction (\\({F}\_{i}\\)) over an equal area grid (0.25 \\(\\circ\\) \\(\\times\\)0.25\\(\\circ\\) at the equator) from 1993 - 2000. They suggested that the IGBP estimate for inundation could be used as a measure of sensitivity of their detection approach at low inundation. We therefore used the sum of their satellite-derived \\({F}\_{i}\\) and the constant IGBP estimate when it was less than 10% to perform a simple inversion for the inundated fraction for methane production (\\({f}\_{s}\\)). The method optimized two parameters (\\({fws}\_{slope}\\) and \\({fws}\_{intercept}\\)) for each grid cell in a simple model based on simulated total water storage (\\({TWS}\\)):

(2.25.20)[¶](#equation-24-20 "Permalink to this equation")\\\[f\_{s} =fws\_{slope} TWS + fws\_{intercept} .\\\]

These parameters were evaluated at the 0.5° resolution, and aggregated for coarser simulations. Ongoing work in the hydrology submodel of CLM may alleviate the need for this crude simplification of inundated fraction in future model versions.