Estimation of permafrost thawing rates in a sub-arctic catchment using recession flow analysis

Permafrost thawing is likely to change the flow pathways taken by water as it moves through arctic and sub-arctic landscapes. The location and distribution of these pathways directly influence the carbon and other biogeochemical cycling in northern latitude catchments. While permafrost thawing due to climate change has been observed in the arctic and sub-arctic, direct observations of permafrost depth are difficult to perform at scales larger than a local scale. Using recession flow analysis, it may be possible to detect and estimate the rate of permafrost thawing based on a long-term streamflow record. We demonstrate the application of this approach to the sub-arctic Abiskojokken catchment in northern Sweden. Based on recession flow analysis, we estimate that permafrost in this catchment may be thawing at an average rate of about 0.9 cm/yr during the past 90 years. This estimated thawing rate is consistent with direct observations of permafrost thawing rates, ranging from 0.7 to 1.3 cm/yr over the past 30 years in the region

Seasonal and regional patterns in performance for a Baltic Sea Drainage Basin hydrologic model

This study evaluates the ability of the Catchment SIMulation (CSIM) hydrologic model to describe seasonal and regional variations in river discharge over the entire Baltic Sea drainage basin (BSDB) based on 31 years of monthly simulation from 1970 through 2000. To date, the model has been successfully applied to simulate annual fluxes of water from the catchments draining into the Baltic Sea. Here, we consider spatiotemporal bias in the distribution of monthly modeling errors across the BSDB since it could potentially reduce the fidelity of predictions and negatively affect the design and implementation of land-management strategies. Within the period considered, the CSIM model accurately reproduced the annual flows across the BSDB; however, it tended to underpredict the proportion of discharge during high-flow periods (i.e., spring months) and overpredict during the summer low flow periods. While the general overpredictions during summer periods are spread across all the subbasins of the BSDB, the underprediction during spring periods is seen largely in the northern regions. By implementing a genetic algorithm calibration procedure and/or seasonal parameterization of subsurface water flows for a subset of the catchments modeled, we demonstrate that it is possible to improve the model performance albeit at the cost of increased parameterization and potential loss of parsimony

Seasonal and regional patterns in performance for a Baltic Sea Drainage Basin hydrologic model

This study evaluates the ability of the Catchment SIMulation (CSIM) hydrologic model to describe seasonal and regional variations in river discharge over the entire Baltic Sea drainage basin (BSDB) based on 31 years of monthly simulation from 1970 through 2000. To date, the model has been successfully applied to simulate annual fluxes of water from the catchments draining into the Baltic Sea. Here, we consider spatiotemporal bias in the distribution of monthly modeling errors across the BSDB since it could potentially reduce the fidelity of predictions and negatively affect the design and implementation of land-management strategies. Within the period considered, the CSIM model accurately reproduced the annual flows across the BSDB; however, it tended to underpredict the proportion of discharge during high-flow periods (i.e., spring months) and overpredict during the summer low flow periods. While the general overpredictions during summer periods are spread across all the subbasins of the BSDB, the underprediction during spring periods is seen largely in the northern regions. By implementing a genetic algorithm calibration procedure and/or seasonal parameterization of subsurface water flows for a subset of the catchments modeled, we demonstrate that it is possible to improve the model performance albeit at the cost of increased parameterization and potential loss of parsimony