Water Resources Research · 2012 · 46 citations · 34 references
AgricultureEarth SciencesSoil SciencesSoil PhysicsSoil ScienceSoil-water RelationsHydraulic ModelingSoil Hydraulic PropertiesSoil MoistureSoil Water DynamicsSoil-water BalanceWater ContentHeterogeneityLayered Soil ProfilesSoil Hydraulic ParameterizationSoil Moisture AssimilationSoil Moisture Data AssimilationSoil Moisture EstimationSoil PropertiesVertical Heterogeneity
We developed a layer‐specific soil‐moisture assimilation scheme using a simulation‐optimization framework, Soil‐Water‐Atmosphere‐Plant model with genetic algorithm (SWAP‐GA). Here, we explored the quantification of the soil hydraulic properties in a layered soil column under various combinations of soil types, vegetation covers, bottom boundary conditions and soil layering using idealized (synthetic) numerical studies and actual field experiments. We demonstrated that soil layers and vertical heterogeneity (layering arrangements) could impact to the uncertainty of quantifying soil hydraulic parameters. We also found that, under layered soil system, when the subsurface flows are dominated by upward fluxes, e.g., from a shallow water table, the solution to the inverse problem appears to be more elusive. However, when the soil profile is predominantly draining, the soil hydraulic parameters could be fairly estimated well across soil layers, corroborating the results of past studies on homogenous soil columns. In the field experiments, the layer‐specific assimilation scheme successfully matched soil moisture estimates with observations at the individual soil layers suggesting that this approach could be applied in real world conditions.
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Genetic algorithms in search, optimization, and machine learning
Choice Reviews Online · 1989 · 49.3K citations