In the context of global warming,the cryosphere is the second largest climate system in the world,and its changing characteristics and impacts are attracting more and more attention. In the past decade or more,the cryosphere has been shrinking all over the world. As a major part of the cryosphere,the change of snow cov-er will have a significant impact on climate change,ecological environment,agriculture and animal husbandry development and water resources balance. It will also affect the ecological environment,the development of ag-riculture and animal husbandry and the balance of water resources. The snow resources in the southern border ar-ea are extremely rich. Global warming accelerates the melting of snow and glaciers in Xizang,resulting in fre-quent snow and ice disasters such as avalanches,glacial lake outburst and glacial debris flow. It has a great im-pact on local production and residents' lives. Therefore,accurate simulation of snow depth is of great signifi-cance for hydrological processes,climate change,and ecological environment in cold regions. At present,the methods for simulating and monitoring snow depth mainly include ground snow depth observation,inversion of snow depth based on microwave remote sensing,measurement of snow depth based on satellite altimetry technol-ogy,and simulation of snow depth using snow accumulation process models. The snow accumulation process model is based on strict physical meaning and can quantitatively simulate the influence of physical environment on snow parameters,quantitatively simulating regional snow depth from a physical sense. The snow accumula-tion process model mainly includes single-layer snow accumulation model,medium complexity snow accumula-tion model,and detailed snow accumulation model. The model used in this paper is a detailed snow cover mod-el,which is based on the layering of snow physical properties and can describe the evolution of snow microstruc-ture over time. However,the current snow accumulation process model simulation has problems such as com-plex parameter settings and high uncertainty. Therefore,it is necessary to find the most suitable parameter com-bination for the region through parameter calibration,in order to complete the localization of model parameters. This paper innovatively applies the Crocus model for daily snow depth simulation over three years (2019—2021) at Nyalam Station,Purang Station,and Pagri Station in Xizang. Using UQ-Pyl software for model param-eter sensitivity analysis and calibration,the paper constructs localized Crocus models for the aforementioned sta-tions. The applicability of the Crocus model at Nyalam Station,Purang Station,and Pagri Station is comprehen-sively evaluated through correlation coefficients(R),ratios of standard deviation (SDC),Nash efficiency coeffi-cients (NSE),mean differences (BLAS) and root mean square error (RMSE). The results show:the main sen-sitive parameters for the Crocus model are 20 at Nyalam Station,15 at Purang Station,and 13 at Pagri Station;the best snow depth simulation effect of the Crocus model is achieved at Nyalam Station (correlation coefficient of 0.989,ratios of standard deviation of 0.990,Nash efficiency coefficient of 0.978,mean difference of 0.276,root mean square error of 4.280),followed by Purang Station and Pagri Station;among these,the snow settlement,accumulation,and melting processes at Nyalam Station are well simulated,and Purang Station shows superior simulation effects when snow is thick,while Pagri Station overestimates snow depth in March-April each year,but the trend is generally consistent. The daily snow depth simulation results of three stations basically reflect the daily variation process of snow depth. The localization of the Crocus model in this paper is a useful supplement to the snow process simulation research. This paper hopes to provide scientific basis and infor-mation for understanding and revealing the snow process in Xizang Autonomous Region,and also provide strong support for improving the regional climate prediction level,effective management of water resources,disaster prevention and response.
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维普
