Soil moisture is an important driver of growth in boreal Alaska, but estimating soil hydraulic parameters can be challenging in this data-sparse region. Parameter estimation is further complicated in regions with rapidly warming climate, where there is a need to minimize model error dependence on interannual climate variations. To better identify soil hydraulic parameters and quantify energy and water balance and soil moisture dynamics, we applied the physically based, one-dimensional ecohydrological Simultaneous Heat and Water (SHAW) model, loosely coupled with the Geophysical Institute of Permafrost Laboratory (GIPL) model, to an upland deciduous forest stand in interior Alaska over a 13-year period. Using a Generalized Likelihood Uncertainty Estimation parameterisation, SHAW reproduced interannual and vertical spatial variability of soil moisture during a five-year validation period quite well, with root mean squared error (RMSE) of volumetric water content at 0.5 m as low as 0.020 cm(3)/cm(3). Many parameter sets reproduced reasonable soil moisture dynamics, suggesting considerable equifinality. Model performance generally declined in the eight-year validation period, indicating some overfitting and demonstrating the importance of interannual variability in model evaluation. We compared the performance of parameter sets selected based on traditional performance measures such as the RMSE that minimize error in soil moisture simulation, with one that is designed to minimize the dependence of model error on interannual climate variability using a new diagnostic approach we call CSMP, which stands for Climate Sensitivity of Model Performance. Use of the CSMP approach moderately decreases traditional model performance but may be more suitable for climate change applications, for which it is important that model error is independent from climate variability. These findings illustrate (1) that the SHAW model, coupled with GIPL, can adequately simulate soil moisture dynamics in this boreal deciduous region, (2) the importance of interannual variability in model parameterisation, and (3) a novel objective function for parameter selection to improve applicability in non-stationary climates.

In this study, summer rainfall contributions to streamflow were quantified in the sub-arctic, 30% glacierized Tarfala (21.7km(2)) catchment in northern Sweden for two non-consecutive summer sampling seasons (2004 and 2011). We used two-component hydrograph separation along with isotope ratios (O-18 and D) of rainwater and daily streamwater samplings to estimate relative fraction and uncertainties (because of laboratory instrumentation, temporal variability and spatial gradients) of source water contributions. We hypothesized that the glacier influence on how rainfall becomes runoff is temporally variable and largely dependent on a combination of the timing of decreasing snow cover on glaciers and the relative moisture storage condition within the catchment. The results indicate that the majority of storm runoff was dominated by pre-event water. However, the average event water contribution during storm events differed slightly between both years with 11% reached in 2004 and 22% in 2011. Event water contributions to runoff generally increased over 2011 the sampling season in both the main stream of Tarfala catchment and in the two pro-glacial streams that drain Storglaciaren (the largest glacier in Tarfala catchment covering 2.9km(2)). We credit both the inter-annual and intra-annual differences in event water contributions to large rainfall events late in the summer melt season, low glacier snow cover and elevated soil moisture due to large antecedent precipitation. Together amplification of these two mechanisms under a warming climate might influence the timing and magnitude of floods, the sediment budget and nutrient cycling in glacierized catchments. Copyright (c) 2012 John Wiley & Sons, Ltd.