Monitoring station is unable to characterize the spatial or temporal The current modelling approach that attempts toĭetermine a single set of “best fit” properties based on IM of a single Inter-annual climate variability (e.g., wet or dry) and also take intoĪccount spatial variations in water movement within a spatially DevitoĮt al. (2012) recommend that model calibration be focused on seasonal and Parameter values from inverse modelling (IM) of short-term (5–10 years) Many cases, this has been undertaken by deriving a single set of optimized Have most commonly been characterized by calibrating water dynamics modelsĪgainst a single profile of field-monitored water content and suction. The hydraulic parameters of reclamation soil covers on oil sands mine waste Highlight that climate variability dominates the simulated variability inĪctual evapotranspiration and that climate and parameter uncertainty have a similar influence on the variability in net percolation. Method was able to better capture broader variability in the water balanceĬomponents than a discrete interval sampling method. With long-term water balance components and LAI values. Index (LAI) for five illustrative covers and quantify uncertainty associated Sets were used to evaluate variations in the maximum sustainable leaf area Water balance models with the sampled parameter The resulting 155 optimized parameter values were used to define distributions for each parameter/soil type, while the progressive Latin hypercube sampling (PLHS) method was used to sample parameter values randomly from the optimized Types (peat cover soil, coarse-textured subsoil, and lean oil sand substrate) were optimized at each monitoring site from 2013 to 2016. This study utilizes IM to optimize the hydraulic properties for 12 soil cover designs, replicated in triplicate, at This approach is unable to characterize the impact of variability in the cover properties. Conventional practice has been to derive a single set of optimized hydraulic parameters through inverse modelling (IM) based on short-term ( <5–10 years) monitoring datasets. One technique to evaluate the performance of oil sands reclamation covers is through the simulation of long-term water balance using calibrated soil–vegetation–atmosphere transfer models.