While climate models project strong future warming, continuous changes in permafrost will have major impact on the Earth system, affecting climate system, water cycle and carbon cycle. There is an urgent need to understand the nature of the change of permafrost dynamics in response to climate change. It is therefore timely for a session to bring together studies that address recent advances in understanding, diagnosis and prediction of past and future changes in permafrost regions in Asia as well as improvements in numerical permafrost modelling. 28 Jun to 4 Jul 2020, Sono Belle Vivaldi Park, Hongcheon.
Zhao Y, Nan Z*, Yu W, Zhang L. Calibrating a hydrological model by stratifying frozen ground types and seasons in a cold alpine basin. Water. 2019, 11(5): 985. DOI:10.3390/w11050985.
Abstract: Frozen ground and precipitation seasonality may strongly affect hydrological processes in a cold alpine basin, but the calibration of a hydrological model rarely considers their impacts on model parameters, likely leading to considerable simulation biases. In this study, we conducted a case study in a typical alpine catchment, the Babao River basin, in Northwest China, using the distributed hydrology–soil–vegetation model (DHSVM), to investigate the impacts of frozen ground type and precipitation seasonality on model parameters. The sensitivity analysis identified seven sensitive parameters in the DHSVM, amid which soil model parameters are found sensitive to the frozen ground type and land cover/vegetation parameters sensitive to dry and wet seasons. A stratified calibration approach that considers the impacts on model parameters of frozen soil types and seasons was then proposed and implemented by the particle swarm optimization method. The results show that the proposed calibration approach can obviously improve simulation accuracy in modeling streamflow in the study basin. The seasonally stratified calibration has an advantage in controlling evapotranspiration and surface flow in rainy periods, while the spatially stratified calibration considering frozen soil type enhances the simulation of base flow. In a typical cold alpine area without sufficient measured parametric values, this approach can outperform conventional calibration approaches in providing more robust parameter values. The underestimation in the April streamflow also highlights the importance of improved physics in a hydrological model, without which the model calibration cannot fully compensate the gap.