Testing the incorporation of ecohydrological separation into Hydrus-1D using isotopic tagging
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Hydrologic models often assume precipitation entering the bulk soil matrix is integrated into one well mixed soil moisture reservoir. The soil reservoir can then be used by plants or discharged to the stream. However, ecohydrologic separations between root and stream water exist and indicate distinct soil water pools within the bulk soil matrix. This separation has been explained by the presence of mobile and immobile regions within the soil column, which are reflections of the temporal variation in isotopic compositions of precipitation events. The objective was to test if the hydrologic model Hydrus-1D and its dual porosity function could recreate observed isotopic patterns in soil using stable water isotope (delta2H, delta18O) datasets from the H.J. Andrews Experimental Forest. We used observed precipitation isotope samples to generate an ensemble of synthetic isotope time series capturing precipitation amount effects and site-specific statistical relationships. The Hydrus-1D dual porosity function enabled partitioning of the soil column into different mobile and immobile regions, each with their own respective set of soil hydraulic parameters. Precipitation events were ‘isotopically tagged’ and isotope signatures were modeled in time and space within the mobile and immobile soil regions distinctly. An ensemble of modeled hydrologic partitions and mass transfer rates (ω) between the mobile and immobile regions was compared with observed isotope signatures. Soil moisture and isotopic composition of the modeled mobile and immobile regions were heavily influenced by the fraction of bulk soil in the immobile region and ω. The bulk isotope composition exhibited greater variability with larger immobile fractions and larger ω. Our results indicate incorporating heterogeneous soil water storage within hydrologic modeling frameworks can improve the representation of subsurface chemical transport and plant water uptake. This work advances the general understanding and representation of land-surface processes influencing the climate from local to regional to global scales.