Abstract
Abstract. The objective of the present study is application of the land surface model SWAP to project climate change impact on northern Russian river runoff up to 2100 using meteorological projections from the atmosphere–ocean global climate model INMCM4.0. The study was performed for the Northern Dvina River and the Kolyma River characterized by different climatic conditions. The ability of both models to reproduce the observed river runoff was investigated. To apply SWAP for hydrological projections, the robustness of the model was evaluated. The river runoff projections up to 2100 were calculated for two greenhouse gas emission scenarios: RCP8.5 and RCP4.5 prepared for the phase five of the Coupled Model Intercomparison Project (CMIP5). For each scenario, several runoff projections were obtained using different models (INMCM4.0 and SWAP) and different post-processing techniques for correcting biases in meteorological forcing data. Differences among the runoff projections obtained for the same emission scenario and the same period illustrate uncertainties resulted from application of different models and bias-correcting techniques.
Highlights
Nowadays atmosphere–ocean global climate models (AOGCMs) represent the main tool for physically based assessments of future climate change which can be used for hydrological projections
In order to make sure that model parameter values, obtained for the current conditions, remain valid in projection periods, SWAP model transposability in time under contracted climate conditions was analyzed before its application for hydrological projections
As to SWAP, application of optimal parameter values obtained for real meteorology does not provide a good accuracy of streamflow simulation when meteorological outputs from AOGCM drive the model
Summary
Nowadays atmosphere–ocean global climate models (AOGCMs) represent the main tool for physically based assessments of future climate change which can be used for hydrological projections. The hydrological projections can be done directly by AOGCMs coupled with river routing models to obtain streamflow at a river basin outlet. This is widely used for evaluating the performance of GCMs and for studying the climate change impact on water resources of large river basins The major reasons seem to be a coarse spatial scale of GCMs and large errors in modelling precipitation and partitioning precipitation between evapotranspiration and runoff. For a large river basin or catchment, meteorological outputs can be used directly, while for smaller ones spatial downscaling and disaggregation techniques are used (Arora and Boer, 2001)
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