Most existing studies provide coarse spatial resolution mappings(typically 1 km or more),which fail to capture local-scale heterogeneity of permafrost distribution in the permafrost boundary region.This study employed...Most existing studies provide coarse spatial resolution mappings(typically 1 km or more),which fail to capture local-scale heterogeneity of permafrost distribution in the permafrost boundary region.This study employed 298 ground-truth samples to evaluate six machine learning(ML)algorithms for simulating permafrost distribution in the Genhe River Basin(GRB)of the Greater Khingan Mountains(GKM)based on our detailed investigation(e.g.,16 boreholes)in this region conducted in 2023-2024,while identifying key environmental drivers through Shapley Additive Explanations(SHAP)analysis.Results show that the random forest(RF)model achieved the best performance,with a classification accuracy of 0.83 and a Kappa coefficient of 0.66.The RF-based permafrost map at a 30 m resolution reveals a total permafrost area of approximately 8248.5 km2,accounting for 52.0%of the GRB.The most influential predictors of permafrost distribution are slope(SLO),topographic wetness index(TWI),and degree of topographic relief(DTR),contributing 13.6%,11.1%,and 9.4%,respectively.Other important factors include normalized difference water index(NDWI,6.8%)and land surface temperature(LST,6.1%).Permafrost is mainly distributed in valley bottoms,toe slopes,and gently sloping areas in the upper and middle reaches of the basin.These zones are closely associated with vegetation types such as wetlands,shrubs,and larch forests.Conversely,permafrost is rarely found in croplands or on steep slopes.These findings improve the understanding of permafrost distribution patterns in the transitional zone of Northeast China,and offer critical data and methodological support for high-resolution permafrost mapping across the region.展开更多
气候变暖对北极多年冻土和植被产生了重要的影响。CLM(Community Land Model)是应用最广泛的陆面过程模式之一,但其中复杂的边界条件和参数化过程导致模式模拟结果存在一定的不确定性。本研究评估了CLM5.0对阿拉斯加多年冻土区表层土壤...气候变暖对北极多年冻土和植被产生了重要的影响。CLM(Community Land Model)是应用最广泛的陆面过程模式之一,但其中复杂的边界条件和参数化过程导致模式模拟结果存在一定的不确定性。本研究评估了CLM5.0对阿拉斯加多年冻土区表层土壤温度和碳循环的模拟能力,结果表明,CLM5.0可以捕捉到表层土壤温度的季节变化。在苔原和针叶林站点,CLM5.0在日尺度和月尺度都可以很好地模拟出总初级生产力(GPP)随时间的变化,但对净生态系统碳交换(NEE)的模拟结果存在一定的不确定性。CLM5.0可以较为合理地模拟高纬度多年冻土区的土壤温度季节变化,在未来的研究中可能还需要从结构、参数化方案等过程进行改进,从而进一步提升高纬度多年冻土区碳循环的模拟精度。展开更多
基金financially supported by the Science and Technology Fundamental Resources Investigation Program of China(2022FY100704)the National Natural Science Foundation of China(42376254,42322608)+1 种基金the program of the Key Laboratory of Cryospheric Science and Frozen Soil Engineering,CAS(CSFSE-ZZ-2408)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(2022430).
文摘Most existing studies provide coarse spatial resolution mappings(typically 1 km or more),which fail to capture local-scale heterogeneity of permafrost distribution in the permafrost boundary region.This study employed 298 ground-truth samples to evaluate six machine learning(ML)algorithms for simulating permafrost distribution in the Genhe River Basin(GRB)of the Greater Khingan Mountains(GKM)based on our detailed investigation(e.g.,16 boreholes)in this region conducted in 2023-2024,while identifying key environmental drivers through Shapley Additive Explanations(SHAP)analysis.Results show that the random forest(RF)model achieved the best performance,with a classification accuracy of 0.83 and a Kappa coefficient of 0.66.The RF-based permafrost map at a 30 m resolution reveals a total permafrost area of approximately 8248.5 km2,accounting for 52.0%of the GRB.The most influential predictors of permafrost distribution are slope(SLO),topographic wetness index(TWI),and degree of topographic relief(DTR),contributing 13.6%,11.1%,and 9.4%,respectively.Other important factors include normalized difference water index(NDWI,6.8%)and land surface temperature(LST,6.1%).Permafrost is mainly distributed in valley bottoms,toe slopes,and gently sloping areas in the upper and middle reaches of the basin.These zones are closely associated with vegetation types such as wetlands,shrubs,and larch forests.Conversely,permafrost is rarely found in croplands or on steep slopes.These findings improve the understanding of permafrost distribution patterns in the transitional zone of Northeast China,and offer critical data and methodological support for high-resolution permafrost mapping across the region.
文摘气候变暖对北极多年冻土和植被产生了重要的影响。CLM(Community Land Model)是应用最广泛的陆面过程模式之一,但其中复杂的边界条件和参数化过程导致模式模拟结果存在一定的不确定性。本研究评估了CLM5.0对阿拉斯加多年冻土区表层土壤温度和碳循环的模拟能力,结果表明,CLM5.0可以捕捉到表层土壤温度的季节变化。在苔原和针叶林站点,CLM5.0在日尺度和月尺度都可以很好地模拟出总初级生产力(GPP)随时间的变化,但对净生态系统碳交换(NEE)的模拟结果存在一定的不确定性。CLM5.0可以较为合理地模拟高纬度多年冻土区的土壤温度季节变化,在未来的研究中可能还需要从结构、参数化方案等过程进行改进,从而进一步提升高纬度多年冻土区碳循环的模拟精度。
