基于模块化建模方法的高寒土壤热状况及水文过程模拟
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摘要
随着全球变暖,冻土活动层深度正在逐渐加深,冻土退化成为近年来寒区环境变化的重要特征之一。除气候变化原因外,区域生态环境因素也可影响冻土活动层的热状况。已有的研究表明,积雪和有机质可影响冻土活动层的变化,然而,其机制和机理还有待于进一步研究。
在当前全球普遍缺少水资源的背景下,准确估计河流上游出山口水资源量是流域水资源合理规划的前提,更是寒区水文过程模拟的一项最重要任务。冰雪、冻土的出现,除单纯考虑降水的分配、汇流过程、入渗、壤中流和地下水径流过程外,还要因为固态水分的相变考虑能量平衡过程,寒区水文过程的模拟也变得更加复杂。如何在未来气候变化情况下,精确估计冰雪水文过程、冻土水文过程,是寒区水文过程模拟的关键。传统的水文模型很少考虑寒区水文过程要素(冰雪和冻土)或者仅作简化处理,模型的模拟结果难以满足实际需要。另外,由于寒区不易接近且工作条件艰苦,寒区数据监测普遍存在不足的情况,这也与水文过程模拟中需要大量的数据相冲突。如何在缺少资料的寒区进行水文过程模拟成为一个重要的科学问题。
基于模块化建模环境设计的模块化建模方法,具有目标和数据驱动的特点,极强的应用灵活性使其构建的模型具有模拟寒区不同过程水热运移的能力。本研究选择中国科学院监测的冰沟站、风火山站和唐古拉站三个野外观测台站,利用模块化建模方法CoupModel和CRHM分别模拟地气间能量运移过程和寒区水文过程,定量分析季节性积雪和有机质土壤对冻土活动层热状况的影响,评估季节性积雪和冻土对寒区水文过程的影响。
1. CoupModel能够模拟精确模拟青藏高原季节性积雪和有机质存在时积雪地气间能量运移过程和活动层温度状况的变化。在风火山流域,在有地表温度输入时,以分层土壤温度为指标,应用贝叶斯算法,率定与地气间能量运移有关的参数,结果显示,模型能够确定有关的水热运移参数。风火山流域CoupModel模型率定期和验证期土壤温度纳什系数NSE的范围分别为0.952～0.984和0.902-967。在季节性积雪存在时,冰沟站CoupModel模型率定期积雪深度和各层土壤温度的NSE值分别为0.76、0.937～0.962；模型验证期各层土壤温度的NSE值在0.915～0.948。在唐古拉站,有机质土壤广泛分布,CoupModel率定期和验证期分层土壤温度的NSE值范围分别为0.914～0.951,0.894～0.951。综合对比风火山站、冰沟站和唐古拉站模型模拟结果,我们发现：模型在风火山站的模拟结果最为出色,模型的效率系数在40cm土壤深度处率定过程中达到了最大值0.984;CoupModel对上层土壤的模拟精度较下层土壤高。
2.积雪由于其低的热传导率、大的融化和升华潜热、表面较裸土高的反照率改变了近地层能量的分配并影响地气间能量运移过程,改变冻土的存在和发育条件,影响其下伏冻土活动层的热状况。研究中通过改变10月至次年5月的降水来控制积雪深度的变化,结果显示：冬季较薄的积雪(0～20cm)覆盖地表,致使到达地面的总辐射量减少,加之由于积雪融化和升华作用导致与积雪底层接触的地表温度降低,促进活动层的冬季冻结过程,活动层温度有降低的趋势,有利于冻土的发育；随着冻结积雪深度从20cm增加至80cm,积雪的热绝缘作用逐渐占据主导地位并减弱地气间的能量运移过程,致使土壤层中储存的热量不能及时释放而阻碍活动层的冻结过程,活动层的变化主要表现在活动层不同深度处开始冻结时间延迟、冻结速率减小和整个冻土活动层温度升高几个方面。总体上,0～20ccm的较浅季节性积雪有利于冻土的发育,更深的积雪出现则不利于冬季冻土活动层的冻结过程。
3.有机质土壤较普通矿物质土壤高的热容量和低的热传导率使其能够对冻土活动层的温度状况产生影响。在CoupModel成功率定的基础上,通过控制唐古拉站土壤剖面中有机质土壤的分布来研究有机质土壤的存在冻土活动层热状况的影响,结果表明：在唐古拉站现有气候背景下,随着有机质土壤分布深度从0cm增加至80cm,冻土活动层的夏季融化深度逐渐从接近280cm减小至100cm,活动层萎缩率超过60%；冻土活动层的温度状况在全年出现了相反的情况,冬季活动层温度出现增加的趋势,而夏季活动层温度则出现了减小的趋势,全年活动层温度的变化幅度减小,活动层温度对空气温度变化的响应不再那么强烈。综合活动层融化深度和温度的状况,我们可以得出,随着有机质土壤的增加,冻土活动层的变化趋于更加稳定,在青藏高原唐古拉现有年均气温低于0℃的情况下有机质土壤的存在有利于冻土的发育。
4.基于模块化建模方法构建的寒区水文模型CRHM具有模拟积雪水文过程的能力。在冰沟积雪小流域,通过模块灵活转换,评估不同模块和算法(度日因子和能量平衡)对积雪累积-消融过程的影响,同时估计不同算法计算的积雪消融过程中积雪的物质/水量平衡,最后,利用CRHM模型来模拟流域出山口的融雪径流过程。结果显示：度日因子模型和能量平衡模型均能够模拟积雪的积累-消融过程,且由能量平衡模型模型模拟的积雪深度更接近实测值,度日因子和能量平衡算法模拟的积雪深度与实测雪深的线性相关系数R2分别为0.64和0.78,纳什系数NSE值为-0.57和0.75；比较度日因子模型和能量平衡模型模拟的积雪物质平衡并结合风速观测数据,得出,在冰沟流域由度日因子模型和能量平衡模型计算的风吹雪引起的升华分别占纵积雪升华量的40%和50%,积雪融化量约占50%,风吹雪引起的积雪损失量较少,为2%左右。鉴于能量平衡模型能够更好模拟积雪的物质平衡过程,选择能量平衡模型模拟冰沟流域出山口处河川径流的日均流量,在未经参数率定的情况下,模型的效率系数NSE值为0.64,模型能够捕获春季由于融雪形成的洪峰过程。
5. CRHM能够模拟冻土活动层冻融过程对水文过程的影响。在青藏高原长江源区风火山冻土流域,冻土作为主要的影响因子来评价CRHM冻土模型的有效性及冻土冻融过程对整个流域水文过程的影响,主要模拟内容包括冻土和未冻土下渗过程和冻土区坡面汇流过程,冻土融化过程中的径流过程和地表、壤中流过程,并定量地表径流和壤中流的量。结果显示：和未包含冻土冻融模块的CRHM模型相比,包含冻土冻融模块的CRHM模型能够成功模拟由冻土融化引起的春季洪水过程,模型的纳什系数NSE值为0.67；分析2007年两个模型模拟结果并结合观测出山口日均流速,发现冻土对春汛的影响最大,而对夏汛的影响最小;模型模拟的径流组分分割情况与同位素和径流场观测结果基本一致,地下径流量占整个河川净流量的70%左右。
综合以上几点,积雪和有机质的存在,从不同方面影响冻土活动层的热状况和冻土发育环境,为气候变暖情况下冻土的保护提供了一定程度的指导。积雪和冻土的存在和改变可引起寒区水文过程发生很大改变,在未来气候变化下准确估计积雪和冻土的变化是寒区水文过程和水资源评价的重要方面。模块化建模方法具有独特的优势,对未来青藏高原气候模式、冻土模型、积雪模型、冰川模型和水文模型的发展有一定借鉴意义。
With global consistent warming, the frozen soil active layer depth has been gradually deepening and it is frozen soil degeneration that is significant feature of cold regions environmental change. Except for climatic change, the diversities of region ecological environment can affect the thermal regime of the soil frozen active layer. Existed researches indicate that snow cover and organic material existed in surface soil can render the change of frozen soil active layer. However, its mechanism is not absolutely transparent to us.
Under the background of widespread water resource absence, accurately estimating water resource quantity of river upstream is not only precondition of basin water resource reasonable programming but also the most important mission of cold region hydrological processes simulation. The cold region hydrological processes simulation is more complex because of ice, snow and frozen soil presence so that the hydrological model must take energy transport in water phase change into account except for precipitation distribution, confluence, infiltration, subsurface flow and ground water flow. How to accurately simulate ice/snow and frozen soil hydrological processes is the key to cold region hydrological processes simulation when the region or global climatic condition changes in the future. The cultural hydrological model seldom considers cold region hydrological processes factor, such as ice, snow and frozen soil, or simplify the processes as one or more parameters. What's more, the lack of monitored data because of hard approach to cold regions and hard work conditions contradicts the abundant data needed by hydrological processes simulation. How to simulate hydrological processes under a limited data condition has become a important science focus in cold region hydrological simulation.
Designed and founded on the basis of modular modelling environment, the modular modelling method, having object and forcing data feature, can be utilized flexibly to stimulate cold region water-thermal transport and hydrological processes. This research objectives are1) to simulate energy transport between space and surface soil and quantitatively analyze the influence of seasonal snow cover and organic existence in surface on the active layer thermal regime by CoupModel,2) to simulate snow hydrological processes and frozen soil hydrological processes and estimate the impact of seasonal snow cover and frozen soil on cold region hydrological processes, used the monitoring datasets in Binggou station, Fenghuoshan station and Tanggula station by Chinese Academy of Sciences (CAS). The following is the main conclusion.
I. CoupModel is able to accurately simulate Qinghai-Tibet Plateau energy transport processes between space and surface soil and active layer temperature state change when the seasonal snow or organic material is present. In the Fenghuoshan basin, surface temperature as model input, soil temperature at different soil layers as verifiable indexes, calibrate parameters relative to energy transport processes utilized Bayesian theory and the result indicates the model can estimate parameters. The Nash coefficient (NSE) values between simulated soil temperature by CoupModel and observed soil temperature in Fenghuoshan basin vary from0.952to0.984in model calibration period and from0.902to0.967in model verification period. In Binggou basin, where the seasonal snow cover is present, the NSE value between simulated and observed snow depth is0.76and the NSE values between simulated soil temperature by CoupModel and observed soil temperature vary from0.937to0.962in model calibration period and from0.915to0.948in model verification period. The NSE values between simulated soil temperature by CoupModel and observed soil temperature vary from0.914to0.951in model calibration period and from0.894to0.951in model verification period at Tanggula station. Comparing soil temperature simulation results at Fenghuoshan station, Binggou Station and Tanggula station, we can conclude that the model displays the best result at Fenghuoshan station and the maximum NSE value is0.984at40cm soil depth in model calibration; moreover, the CoupModel simulated accuracy of upper layer soil is better than subsoil.
2. Energy budget, distribution and transport between space and surface soil are changed by snow cover presence because of its low thermal conductivity, high melting and sublimation latent heat and higher albedo than bare soil and then induce the change of frozen soil existence and development environment, affect the thermal regime of the frozen soil active layer. The snow cover depth is controlled by changing precipitation from October to May of the next year and the result indicates the presence of shallow snow cover from0cm to20cm in winter render decrease of total radiation reaching surface owing to high albedo of snow cover and low temperature of contact surface between snow cover and soil layer because of energy consumed by snow cover melting and sublimation. Therefore, soil freezing is easy to happen and the temperature of whole active layer trend low. The snow cover which depth varies from0cm to20cm avail frozen soil development. Following snow cover depth from20cm to80cm, the snow cover insulation becomes decisive gradually and restrains energy exchange between space and soil layer. The energy stored by soil layer can't release timely so that the freezing process of active layer changes. The variation of active layer mainly displays freezing start time delay and soil temperature rise at whole soil layer and the freezing rate decrease. As a whole, the shallow snow cover varying from0cm to20cm benefits frozen soil development and gradually become opposite with snow cover depth increasing.
3. More soil thermal capacity and lower thermal conductivity than common mineral substance, the organic soil can affect thermal regime of frozen soil active layer. Based on successfully calibrated CoupModel model, research the effect of organic soil on the thermal regime of active layer by controlling the organic soil distribution at whole soil profile. The results indicate that under the background of existing climate system, the melting depth of active layer in summer decreases from about280cm to100cm and reduced proportion is over60%following organic distribution depth from0cm to80cm. The temperature condition of active layer displays adverse trend in cold season and warm season of a year:the temperature rises in winter and the temperature decreases in summer. The temperature amplitude of variation decreases all year and the response of soil temperature to air temperature is not so strong. Comparing active layer melting depth and temperature condition, we can conclude that the change of frozen soil active layer becomes steady with the organic soil increasing. The organic soil presence makes for frozen soil development at Tanggula station under existed climate system, annual average air temperature below0℃.
4. The cold region hydrological model (CRHM) designed and found by modular model platform can simulate snow hydrological processes. At Binggou snow basin, the CRHM can be utilized to estimate the effect of different modules and algorithms including degree day algorithm and energy budget algorithm on snow cover accumulation and ablation, to compute snow cover material balance or water budget by degree day algorithm and energy budget algorithm and to stimulate cold region hydrological processes and discharge through flexible modular transition. The results indicate that both degree day algorithm and energy budget algorithm are able to simulate snow cover accumulation and ablation processes and the energy budget algorithm performance is better that the R2between observed snow cover depth and simulated by degree day algorithm and energy budget algorithm are0.64,0.78, respectively and the NSE values are-0.57and0.75respectively. Comparing snow cover budget simulated by degree day model with by energy budget model and using observed wind speed at the same time, we can conclude that snow cover sublimation caused by blowing snow process calculated by degree day model and energy budget model is40%and50%of total snow sublimation, respectively. The melting snow is about50%of total snow cover. However, the snow loss in blowing snow process is relatively little, about2%. To simulate day average discharge caused by the seasonal snow cover at the basin outlet, choose energy budget algorithm model because of its better performance than degree day algorithm model. The NSE value between simulated and observed discharge is0.64and the model is able to illustrate the flood processes induced by seasonal snow cover melt.
5. CRHM is able to simulate hydrological processes including frozen soil freezing and melting processes. At Fenghuoshan basin of the headwater of Yangtze River in core region of Qinghai-Tibet plateau, the frozen soil is chose to estimate the effectiveness that CRHM simulates frozen soil hydrological processes and the influence of frozen soil on cold region hydrological processes. The main simulated processes include infiltration in frozen soil and unfrozen soil, surface flow, interflow, etc. At last, quantify the amount of surface flow and interflow. The results indicate comparing with simulated discharge variation by CRHM model which the frozen soil module is neglected, the performance of CRHM including frozen soil module is better and the NSE values is0.67. The model can capture flood in spring caused by frozen soil melt. The drastic effect of frozen soil on runoff happens in spring flood process and the slender effect happens in summer flood process by analyzing two simulated results with observed value at2007. The discharge component division by model is fit to isotope and catchment area observation and the ground water flow proportion can reach approximately70%.
All in all, the presence of both seasonal snow cover and organic soil is able to affect the thermal regime of frozen soil active layer and frozen development environment by different ways. The research results will be used to guide frozen soil protection at a certain extent. The existence and change on timing and extent of snow cover and frozen soil can alter tempestuously cold region hydrological processes. Accurately estimating the change of snow cover and frozen soil is first step for cold region hydrological processes simulation and cold region water resource assessment under the background of global climate change in the future. The modular model construction method with particular superiority, can apply to developing climatic model, frozen soil model, snow cover model, glacier model and cold region hydrological model at Qinghai-Tibet plateau.
在当前全球普遍缺少水资源的背景下,准确估计河流上游出山口水资源量是流域水资源合理规划的前提,更是寒区水文过程模拟的一项最重要任务。冰雪、冻土的出现,除单纯考虑降水的分配、汇流过程、入渗、壤中流和地下水径流过程外,还要因为固态水分的相变考虑能量平衡过程,寒区水文过程的模拟也变得更加复杂。如何在未来气候变化情况下,精确估计冰雪水文过程、冻土水文过程,是寒区水文过程模拟的关键。传统的水文模型很少考虑寒区水文过程要素(冰雪和冻土)或者仅作简化处理,模型的模拟结果难以满足实际需要。另外,由于寒区不易接近且工作条件艰苦,寒区数据监测普遍存在不足的情况,这也与水文过程模拟中需要大量的数据相冲突。如何在缺少资料的寒区进行水文过程模拟成为一个重要的科学问题。
基于模块化建模环境设计的模块化建模方法,具有目标和数据驱动的特点,极强的应用灵活性使其构建的模型具有模拟寒区不同过程水热运移的能力。本研究选择中国科学院监测的冰沟站、风火山站和唐古拉站三个野外观测台站,利用模块化建模方法CoupModel和CRHM分别模拟地气间能量运移过程和寒区水文过程,定量分析季节性积雪和有机质土壤对冻土活动层热状况的影响,评估季节性积雪和冻土对寒区水文过程的影响。
1. CoupModel能够模拟精确模拟青藏高原季节性积雪和有机质存在时积雪地气间能量运移过程和活动层温度状况的变化。在风火山流域,在有地表温度输入时,以分层土壤温度为指标,应用贝叶斯算法,率定与地气间能量运移有关的参数,结果显示,模型能够确定有关的水热运移参数。风火山流域CoupModel模型率定期和验证期土壤温度纳什系数NSE的范围分别为0.952～0.984和0.902-967。在季节性积雪存在时,冰沟站CoupModel模型率定期积雪深度和各层土壤温度的NSE值分别为0.76、0.937～0.962；模型验证期各层土壤温度的NSE值在0.915～0.948。在唐古拉站,有机质土壤广泛分布,CoupModel率定期和验证期分层土壤温度的NSE值范围分别为0.914～0.951,0.894～0.951。综合对比风火山站、冰沟站和唐古拉站模型模拟结果,我们发现：模型在风火山站的模拟结果最为出色,模型的效率系数在40cm土壤深度处率定过程中达到了最大值0.984;CoupModel对上层土壤的模拟精度较下层土壤高。
2.积雪由于其低的热传导率、大的融化和升华潜热、表面较裸土高的反照率改变了近地层能量的分配并影响地气间能量运移过程,改变冻土的存在和发育条件,影响其下伏冻土活动层的热状况。研究中通过改变10月至次年5月的降水来控制积雪深度的变化,结果显示：冬季较薄的积雪(0～20cm)覆盖地表,致使到达地面的总辐射量减少,加之由于积雪融化和升华作用导致与积雪底层接触的地表温度降低,促进活动层的冬季冻结过程,活动层温度有降低的趋势,有利于冻土的发育；随着冻结积雪深度从20cm增加至80cm,积雪的热绝缘作用逐渐占据主导地位并减弱地气间的能量运移过程,致使土壤层中储存的热量不能及时释放而阻碍活动层的冻结过程,活动层的变化主要表现在活动层不同深度处开始冻结时间延迟、冻结速率减小和整个冻土活动层温度升高几个方面。总体上,0～20ccm的较浅季节性积雪有利于冻土的发育,更深的积雪出现则不利于冬季冻土活动层的冻结过程。
3.有机质土壤较普通矿物质土壤高的热容量和低的热传导率使其能够对冻土活动层的温度状况产生影响。在CoupModel成功率定的基础上,通过控制唐古拉站土壤剖面中有机质土壤的分布来研究有机质土壤的存在冻土活动层热状况的影响,结果表明：在唐古拉站现有气候背景下,随着有机质土壤分布深度从0cm增加至80cm,冻土活动层的夏季融化深度逐渐从接近280cm减小至100cm,活动层萎缩率超过60%；冻土活动层的温度状况在全年出现了相反的情况,冬季活动层温度出现增加的趋势,而夏季活动层温度则出现了减小的趋势,全年活动层温度的变化幅度减小,活动层温度对空气温度变化的响应不再那么强烈。综合活动层融化深度和温度的状况,我们可以得出,随着有机质土壤的增加,冻土活动层的变化趋于更加稳定,在青藏高原唐古拉现有年均气温低于0℃的情况下有机质土壤的存在有利于冻土的发育。
4.基于模块化建模方法构建的寒区水文模型CRHM具有模拟积雪水文过程的能力。在冰沟积雪小流域,通过模块灵活转换,评估不同模块和算法(度日因子和能量平衡)对积雪累积-消融过程的影响,同时估计不同算法计算的积雪消融过程中积雪的物质/水量平衡,最后,利用CRHM模型来模拟流域出山口的融雪径流过程。结果显示：度日因子模型和能量平衡模型均能够模拟积雪的积累-消融过程,且由能量平衡模型模型模拟的积雪深度更接近实测值,度日因子和能量平衡算法模拟的积雪深度与实测雪深的线性相关系数R2分别为0.64和0.78,纳什系数NSE值为-0.57和0.75；比较度日因子模型和能量平衡模型模拟的积雪物质平衡并结合风速观测数据,得出,在冰沟流域由度日因子模型和能量平衡模型计算的风吹雪引起的升华分别占纵积雪升华量的40%和50%,积雪融化量约占50%,风吹雪引起的积雪损失量较少,为2%左右。鉴于能量平衡模型能够更好模拟积雪的物质平衡过程,选择能量平衡模型模拟冰沟流域出山口处河川径流的日均流量,在未经参数率定的情况下,模型的效率系数NSE值为0.64,模型能够捕获春季由于融雪形成的洪峰过程。
5. CRHM能够模拟冻土活动层冻融过程对水文过程的影响。在青藏高原长江源区风火山冻土流域,冻土作为主要的影响因子来评价CRHM冻土模型的有效性及冻土冻融过程对整个流域水文过程的影响,主要模拟内容包括冻土和未冻土下渗过程和冻土区坡面汇流过程,冻土融化过程中的径流过程和地表、壤中流过程,并定量地表径流和壤中流的量。结果显示：和未包含冻土冻融模块的CRHM模型相比,包含冻土冻融模块的CRHM模型能够成功模拟由冻土融化引起的春季洪水过程,模型的纳什系数NSE值为0.67；分析2007年两个模型模拟结果并结合观测出山口日均流速,发现冻土对春汛的影响最大,而对夏汛的影响最小;模型模拟的径流组分分割情况与同位素和径流场观测结果基本一致,地下径流量占整个河川净流量的70%左右。
综合以上几点,积雪和有机质的存在,从不同方面影响冻土活动层的热状况和冻土发育环境,为气候变暖情况下冻土的保护提供了一定程度的指导。积雪和冻土的存在和改变可引起寒区水文过程发生很大改变,在未来气候变化下准确估计积雪和冻土的变化是寒区水文过程和水资源评价的重要方面。模块化建模方法具有独特的优势,对未来青藏高原气候模式、冻土模型、积雪模型、冰川模型和水文模型的发展有一定借鉴意义。
With global consistent warming, the frozen soil active layer depth has been gradually deepening and it is frozen soil degeneration that is significant feature of cold regions environmental change. Except for climatic change, the diversities of region ecological environment can affect the thermal regime of the soil frozen active layer. Existed researches indicate that snow cover and organic material existed in surface soil can render the change of frozen soil active layer. However, its mechanism is not absolutely transparent to us.
Under the background of widespread water resource absence, accurately estimating water resource quantity of river upstream is not only precondition of basin water resource reasonable programming but also the most important mission of cold region hydrological processes simulation. The cold region hydrological processes simulation is more complex because of ice, snow and frozen soil presence so that the hydrological model must take energy transport in water phase change into account except for precipitation distribution, confluence, infiltration, subsurface flow and ground water flow. How to accurately simulate ice/snow and frozen soil hydrological processes is the key to cold region hydrological processes simulation when the region or global climatic condition changes in the future. The cultural hydrological model seldom considers cold region hydrological processes factor, such as ice, snow and frozen soil, or simplify the processes as one or more parameters. What's more, the lack of monitored data because of hard approach to cold regions and hard work conditions contradicts the abundant data needed by hydrological processes simulation. How to simulate hydrological processes under a limited data condition has become a important science focus in cold region hydrological simulation.
Designed and founded on the basis of modular modelling environment, the modular modelling method, having object and forcing data feature, can be utilized flexibly to stimulate cold region water-thermal transport and hydrological processes. This research objectives are1) to simulate energy transport between space and surface soil and quantitatively analyze the influence of seasonal snow cover and organic existence in surface on the active layer thermal regime by CoupModel,2) to simulate snow hydrological processes and frozen soil hydrological processes and estimate the impact of seasonal snow cover and frozen soil on cold region hydrological processes, used the monitoring datasets in Binggou station, Fenghuoshan station and Tanggula station by Chinese Academy of Sciences (CAS). The following is the main conclusion.
I. CoupModel is able to accurately simulate Qinghai-Tibet Plateau energy transport processes between space and surface soil and active layer temperature state change when the seasonal snow or organic material is present. In the Fenghuoshan basin, surface temperature as model input, soil temperature at different soil layers as verifiable indexes, calibrate parameters relative to energy transport processes utilized Bayesian theory and the result indicates the model can estimate parameters. The Nash coefficient (NSE) values between simulated soil temperature by CoupModel and observed soil temperature in Fenghuoshan basin vary from0.952to0.984in model calibration period and from0.902to0.967in model verification period. In Binggou basin, where the seasonal snow cover is present, the NSE value between simulated and observed snow depth is0.76and the NSE values between simulated soil temperature by CoupModel and observed soil temperature vary from0.937to0.962in model calibration period and from0.915to0.948in model verification period. The NSE values between simulated soil temperature by CoupModel and observed soil temperature vary from0.914to0.951in model calibration period and from0.894to0.951in model verification period at Tanggula station. Comparing soil temperature simulation results at Fenghuoshan station, Binggou Station and Tanggula station, we can conclude that the model displays the best result at Fenghuoshan station and the maximum NSE value is0.984at40cm soil depth in model calibration; moreover, the CoupModel simulated accuracy of upper layer soil is better than subsoil.
2. Energy budget, distribution and transport between space and surface soil are changed by snow cover presence because of its low thermal conductivity, high melting and sublimation latent heat and higher albedo than bare soil and then induce the change of frozen soil existence and development environment, affect the thermal regime of the frozen soil active layer. The snow cover depth is controlled by changing precipitation from October to May of the next year and the result indicates the presence of shallow snow cover from0cm to20cm in winter render decrease of total radiation reaching surface owing to high albedo of snow cover and low temperature of contact surface between snow cover and soil layer because of energy consumed by snow cover melting and sublimation. Therefore, soil freezing is easy to happen and the temperature of whole active layer trend low. The snow cover which depth varies from0cm to20cm avail frozen soil development. Following snow cover depth from20cm to80cm, the snow cover insulation becomes decisive gradually and restrains energy exchange between space and soil layer. The energy stored by soil layer can't release timely so that the freezing process of active layer changes. The variation of active layer mainly displays freezing start time delay and soil temperature rise at whole soil layer and the freezing rate decrease. As a whole, the shallow snow cover varying from0cm to20cm benefits frozen soil development and gradually become opposite with snow cover depth increasing.
3. More soil thermal capacity and lower thermal conductivity than common mineral substance, the organic soil can affect thermal regime of frozen soil active layer. Based on successfully calibrated CoupModel model, research the effect of organic soil on the thermal regime of active layer by controlling the organic soil distribution at whole soil profile. The results indicate that under the background of existing climate system, the melting depth of active layer in summer decreases from about280cm to100cm and reduced proportion is over60%following organic distribution depth from0cm to80cm. The temperature condition of active layer displays adverse trend in cold season and warm season of a year:the temperature rises in winter and the temperature decreases in summer. The temperature amplitude of variation decreases all year and the response of soil temperature to air temperature is not so strong. Comparing active layer melting depth and temperature condition, we can conclude that the change of frozen soil active layer becomes steady with the organic soil increasing. The organic soil presence makes for frozen soil development at Tanggula station under existed climate system, annual average air temperature below0℃.
4. The cold region hydrological model (CRHM) designed and found by modular model platform can simulate snow hydrological processes. At Binggou snow basin, the CRHM can be utilized to estimate the effect of different modules and algorithms including degree day algorithm and energy budget algorithm on snow cover accumulation and ablation, to compute snow cover material balance or water budget by degree day algorithm and energy budget algorithm and to stimulate cold region hydrological processes and discharge through flexible modular transition. The results indicate that both degree day algorithm and energy budget algorithm are able to simulate snow cover accumulation and ablation processes and the energy budget algorithm performance is better that the R2between observed snow cover depth and simulated by degree day algorithm and energy budget algorithm are0.64,0.78, respectively and the NSE values are-0.57and0.75respectively. Comparing snow cover budget simulated by degree day model with by energy budget model and using observed wind speed at the same time, we can conclude that snow cover sublimation caused by blowing snow process calculated by degree day model and energy budget model is40%and50%of total snow sublimation, respectively. The melting snow is about50%of total snow cover. However, the snow loss in blowing snow process is relatively little, about2%. To simulate day average discharge caused by the seasonal snow cover at the basin outlet, choose energy budget algorithm model because of its better performance than degree day algorithm model. The NSE value between simulated and observed discharge is0.64and the model is able to illustrate the flood processes induced by seasonal snow cover melt.
5. CRHM is able to simulate hydrological processes including frozen soil freezing and melting processes. At Fenghuoshan basin of the headwater of Yangtze River in core region of Qinghai-Tibet plateau, the frozen soil is chose to estimate the effectiveness that CRHM simulates frozen soil hydrological processes and the influence of frozen soil on cold region hydrological processes. The main simulated processes include infiltration in frozen soil and unfrozen soil, surface flow, interflow, etc. At last, quantify the amount of surface flow and interflow. The results indicate comparing with simulated discharge variation by CRHM model which the frozen soil module is neglected, the performance of CRHM including frozen soil module is better and the NSE values is0.67. The model can capture flood in spring caused by frozen soil melt. The drastic effect of frozen soil on runoff happens in spring flood process and the slender effect happens in summer flood process by analyzing two simulated results with observed value at2007. The discharge component division by model is fit to isotope and catchment area observation and the ground water flow proportion can reach approximately70%.
All in all, the presence of both seasonal snow cover and organic soil is able to affect the thermal regime of frozen soil active layer and frozen development environment by different ways. The research results will be used to guide frozen soil protection at a certain extent. The existence and change on timing and extent of snow cover and frozen soil can alter tempestuously cold region hydrological processes. Accurately estimating the change of snow cover and frozen soil is first step for cold region hydrological processes simulation and cold region water resource assessment under the background of global climate change in the future. The modular model construction method with particular superiority, can apply to developing climatic model, frozen soil model, snow cover model, glacier model and cold region hydrological model at Qinghai-Tibet plateau.
引文
[1]Adam J C, Hamlet A F, Lettenmaier D P. Implications of global climate change for snowmelt hydrology in the twenty-first century [J]. Hydrological Processes,2009,23:962-972.
[2]Allison I, Barry R G, et al. Climate and Cryosphere (CliC) Project. Science and Co-ordination Plan, Version 1.1., World Climate Research Programme [R]. WCRP-114, WMO/TD No.1053, Geneva,2001, pp.76.
[3]Anderson E A. A point energy and mass balance model of a snow cover, NWS Technical Report 19 [P]. National Oceanic and Atmospheric Administration, Washington, DC, USA, 1976,150 pp.
[4]Andreadis K M, Storck P, et al. Modeling snow accumulation and ablation in forested environments [J]. Water resource research,2009,45:W05429.
[5]Anisimov O A, Shiklomanov N I, et al. Global warming and active-layer thickness:results from transient general circulation models [J]. Global and Planetary Change,1997,15:61-78.
[6]Argent R M, Voinov A, et al. Comparing modelling frameworks-A workshop arrroach[J]. Environmental modelling & software,2006,21:895-910.
[7]Armstrong R L, Brun E. Snow and climate:physical processes, surface energy exchange and modeling [M]. Cambridge University Press,2008.
[8]Bartelt P, Lehning M. A physical SNOWPACK model for Avalanche Warning Services Part I: numerical model [J]. Cold Regions Science and Technology,2002,35:123-145.
[9]Boer M M, Koster E A. Greenhouse-impact on Cold-Climate Ecosystems and Landscapes[J]. Catena Supplement,1992,22:1-151.
[10]Braithwaite R J, Olesen O B. Response of the energy balance on the margin of the Greenland ice sheet to temperature changes [J]. Journal of Glaciology,1990,36 (123):217-221.
[11]Braun L, Aellen M. Modelling discharge of glacierized basins assisted by direct measurements of glacier mass balance [J]. IAHS Publ,1990,193:99-106.
12] Braun L, Grabs W, et al. Application of a conceptual precipitation-runoff model in the Langtang Kfaola Basin, Nepal Himalaya [J]. Snow and glacier hydrology,1992,218: 221-237.
13] Brown J, Nelson F E, et al. The circumpolar active layer monitoring (CALM) program research designs and initial results [J]. Polar Geography,2000,3:165-258.
14] Brun E, Martin E, et al. An energy and mass model of snow cover sidtable for operational avalanche forecasting [J]. Journal of Glaciology,1989,35 (121):333-342.
15] Chen R S, Lu S H, et al. A distributed water-heat coupled model for mountainous watershed of an inland river basin of Northwest China (Ⅰ):model structure and equations [J]. Environmental Geology,2008,53 (6):1299-1309.
16] Cheng Guodong, Wu Tonghua, et al. Responses of permafrost to climate change and their environmental significance, Qinghai-Tibet Plateau [J]. Journal of Geophysical Research,2007, 112;F02S03
17] Cherkauer, K A,& Lettenmaier D P. Simulation of spatial variability in snow and frozen soil [J]. Journal of Geophysical Research,2003,108:D22.
[18]Christiansen H H. Meteorological control on interannual spatial and temporal variations in snow cover and ground thawing in two northeast greenlandic circumpolar-active-layer-monitoring (CALM) sites [J]. Permafrost Periglac,2004,15(2): 155-169.
[19]Christiansen J R, Elberling B, Jansson P E. Modelling water balance and nitrate leaching in temperate Norway spruce and beech forests located on the same soil type with the CoupModel [J]. Forest Ecology and Management,2006,237(1-3):545-556.
[20]Coordinate Energy and Water-cycle Observations Project (CEOP) Strategic Implementation Plan:http://www.ceop.net/2008.
[21]Crawford N. Computer simulation techniques for forecasting snowmelt runoff [J]. The role of snow and ice in hydrology,1973:1062-1072.
[22]Cuffey K M, Paterson W S B. The physics of glaciers(fourth edition) [M]. www, elsevier. com/permissions,2010.
[23]Flerchinger G N, Saxton K E. Simultaneous heat and water model of a freezing snow-residue-soil system I:Theory and development [J]. Transactions of the American Society of Agricultural Engineers,1989,32:565-571.
[24]Fukushima Y, Watanabe O, et al. Estimation of streamflow change by global warming in a glacier-covered high mountain area of the Nepal Himalaya [J].20th General Assembly of the International Union of Geodesy and Geophysics, Vienna,1991, Aust,08/11-24/91: 181-188.
[25]Garnier B J, Ohmura A. The evaluation of surface variations in solar radiation income [J]. Solar Energy,1970,13:21-34.
[26]Gao Q, Shi S. Water resources in the arid zone of northwest China [J]. Journal of Desert Research,1992,124:1-12.
[27]Granger R J, Gray D M, et al. Snowmelt infiltration to frozen prairie soils [J]. Canadian Journal of Earth Sciences,1984,21:669-677.
[28]Granger R J, Gray D M. Evaporation from natural nonsaturated surfaces [J]. Journal of Hydrology,1989,111:21-29.
[29]Gray D M, Landine P G. Albedo model for shallow prairie snow covers [J]. Canadian Journal of Earth Sciences,1987,24:1760-1768.
[30]Gray D M, Landine P G. An energy-budget snowmelt model foor the Canndian Prairies [J]. Can J Earth Sci,1988,25(8):1292-1303.
[31]Hansson K, Simunek J, et al. Water flow and heat transport in frozen soil:Numerical solution and freeze-thaw applications [J]. Vadose Zone J,2004,3 (2):693.
[32]Harlan R. Analysis of coupled heat-fluid transport in partially frozen soil [J]. Water resource research,1973,9(5):1314-1323.
[33]Hollesen J, Elberling B, et al. Modelling subsurface temperatures in a heat producing coal waste rock pile, Svalbard (78°N) [J]. Cold Regions Science and Technology,2009,58(1-2): 68-76.
[34]IPCC. Climate Change and Impact 1990[M]. Cambridge:Cambridge University Pres.1990.
[35]IPCC. Climate Change 1995:Impacts, Adaptation, and Mitigation [M]. Cambridge: Cambridge University Press.1996.
[36]IPCC. Climate Change 2001:Impact, Adaptation, and Vulnerability [M]. Cambridge: Cambridge University Press.2001.
[37]IPCC. IPCC Fourth Assessment Report (AR4) [M]. Cambridge:Cambridge University Press. 2007.
[38]Iwata Y, Nemoto M, et al. Influence of rain, air temperature, and snow cover on subsequent spring-snowmelt infiltration into thin frozen soil layer in northern Japan [J]. Journal of Hydrology,2011,401 (3-4):165-176.
[39]Jansson P E. Simulation model for soil water and heat conditions:Description of the SOIL model [Z]. Division of Agricultural Hydrotechnics Communications 98:2, Department of Soil Sciences, Swedish University of Agricultural Sciences, Uppsala,1998.
[40]Jansson P E, Moon D S. A coupled model of water, heat and mass transfer using object orientation to improve flexibility and functionality [J]. Environmental Modelling & Software, 2001,16(1):37-46.
[41]Johnsson H, Bergstr M L, et al. Simulated nitrogen dynamics and losses in a layered agricultural soil [J]. Agriculture, Ecosystems & Environment,1987,18:333-356.
[42]Jordan R. A one-dimensional temperature model for a snow cover. Technical documentation forSNTHERM.89 [R]. US Army Corps of Engineers Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire,1991,49 pp.
[43]Karlberg L, Ben-Gal A, et al. Modelling transpiration and growth in salinity-stressed tomato under different climatic conditions [J]. Ecological Modelling,2006,190(1-2):15-40.
[44]Konz M, Uhlenbrook S, et al. Implementation of a process-based catchment model in a poorly gauged, highly glacierized Himalayan headwater [J]. Hydrology and Earth System Sciences,2007,11(4):1323-1339.
[45]Lawrence D M, Slater A G. A projection of severe near-surface permafrost degradation during the 21 st century [J]. Geophysical Research Letters,2005,24:L24401.
[46]Leavesley G H, Lichty R W, et al. Precipitation-runoff modelling system:user's manual [R], US Geological Survey, Reston, Virginia, Water-Resources Investigations Report,1983: 83-4238.
[47]Leavesley G H, Restrepo P J, et al. The Modular Modeling System (MMS):User's Manual [R]. Open-File Report, U S Geological Survey,1996,96-151.
[48]Lehning M, Bartelt P B, et al. A physical SNOWPACK model for the Swiss Avalanche Warning Services Part Ⅱ:Snow Microstructure [J]. Cold Regions Science and Technology, 2002a,35:147-167.
[49]Lehning M, Bartelt P B, et al. A physical SNOWPACK model for the Swiss Avalanche Warning Services Part Ⅲ:Meteorological Boundary Conditions, Thin Layer Formation and Evaluation [J]. Cold Regions Science and Technology,2002b,35(3):169-184.
[50]Lehning M, Volksch I, et al. ALPINE3D:a detailed model of mountain surface processes and its application to snow hydrology [J]. Hydrological processes,2006,20 (10):2111-2128.
[51]Lemke P, Ren J W. Observations:Changes in Snow, Ice and Frozen Ground[R]. IPCC.2007: 337-38.
[52]Li Xin, Cheng Guodong, et al. Modeling Chinese cryospheric change by using GIS technology [J]. Cold Regions Science and Technology,2003,36:1-9.
[53]Li Xin, Cheng Guodong, et al. Cryospheric change in China [J]. Global and Planetary Change,2008,62:210-218.
[54]Li X, Koike T. Frozen soil parameterization in SiB2 and its validation with GAME-Tibet observations [J]. Cold Regions Science and Technology,2003,36:165-182.
[55]Liang X, Lettenmaier D P, et al. A Simple hydrologically Based Model of Land Surface Water and Energy Fluxes for GSMs [J]. Journal of Geophysical Research,1994,99(D7): 14415-14428.
[56]Luce C H, Tarboton D G. The application of depletion curves for parameterization of subgrid variability of snow [J]. Hydrological processes,2004,18 (8):1409-1422.
[57]Luo L F, Robock A, et al. Effects of frozen soil on soil temperature, spring infiltration, and runoff:Results from the PILPS 2(d) experiment at Valdai, Russia [J]. Journal of Hydrometeorology,2003,4 (2):334-351.
[58]Marks D, Domingo J, et al. A spatially distributed energy balance snowmelt model for application in mountain basins [J]. Hydrological Process,1999,13(12-13):1935-1959.
[59]Milly P C D. Moisture and heat transport in hysteretic, inhomogeneous porous media:a matric head-based formulation and a numerical model [J]. Water resource research,1982, 18(3):489-498.
[60]Molders N, Romanovsky V E. Long-term evaluation of the hydro-thermodynamic soil-vegetation scheme's frozen ground/permafrost component using observations at Barrow, Alaska [J]. Journal of Geophysical Research,2006,111:D04105.
[61]Nicolsky D J, Romanovsky V E, et al. Improved modeling of permafrost dynamics in Alaska with CLM3[J]. Geophysical Research Letters,2007,34.
[62]Oerlemans J, Fortuin J. Sensitivity of glaciers and small ice caps to greenhouse warming [J]. Science,1992,258(5079):115-117.
[63]Ogden F L, Saghafian B. Green and Ampt infiltration with redistribution [J]. Journal of Irrigation and Drainage Engineering,1997,123(5):386-393.
[64]Osterkamp T E. Characteristics of the recent warming of permafrost in Alaska [J]. Geophysical Research Letters,2007,112:F02S02.
[65]Peduzzi P, Herold C, et al. Assessing high altitude glacier thickness, volume and area changes using field, GIS and remote sensing techniques:the case of Nevado Coropuna (Peru) [J]. Cryosphere,2010,4 (3):313-323.
[66]Philip J, Vries D D. Moisture movement in porous materials under temperature gradients, Trans [J]. Am. Geophys. Union,1957,38 (2):222-232.
[67]Pohl S, Davison B, et al. Modelling spatially distributed snowmelt and meltwater runoff in a small Arctic catchment with a hydrology land-surface scheme (WATCLASS) [J]. Atmos Ocean,2005,43 (3),193-211.
[68]Pomeroy J W, Gray D M, et al. The cold regions hydrological model:a platform for basing process representation and model structure on physical evidence [J]. Hydrological Processes, 2007,21:2650-2667.
[69]Pomeroy J W, Li L. Prairie and arctic areal snow cover mass balance using a blowing snow model [J]. Journal of Geophysical Research,2000,105:26619-26634.
[70]Priestley C H, Taylor R J. On the assessment of surface heat flux and evaporation using large-scale parameters [J]. Monthly Weather Review,1972,100:81-92.
[71]Qin Dahe, Liu Shiyin, et al. Snow cover distribution, variability, and response to climate change in western China [J]. Journal of Climate,2006.19(9):1820-1833.
[72]Rigon R, Bertoldi G, et al. GEOtop:a distributed hydrological model with coupled water and energy budgets [J]. Journal of Hydrometeorology,2006,7:371-388.
[73]Schirmer M, Wirz V, et al. Persistence in intra-annual snow depth distribution:1. Measurements and topographic control [J]. Water resource. Research,2011,47 (9):W09516.
[74]Schuur E A G, Abbott B, et al. High risk of permafrost thaw [J]. Nature,2011,480(7375): 32-33.
[75]Sivapalan M, Takeuchi K, et al. IAHS decade on predictions in ungauged basins (PUB), 2003-2012:shaping an exciting future for the hydrological sciences [J]. Hydrological Sciences Journal,2003,48(6):857-880.
[76]Stendel M, Christensen J H. Impact of global warming on permafrost conditions in a coupled GCM [J]. Geophysical Research Letters,2002,13.
[77]Svensson M, Jansson P E, et al. Bayesian calibration of a model describing carbon, water and heat fluxes for a Swedish boreal forest stand [J]. Ecological modelling,2008,213:331-344.
[78]Tarboton D G, Chowdhury T G, et al. A spatially distributed energy balance snowmelt model [C]. In:Proceedings of symposium on biogeochemistry of seasonally snow-covered catchments, Boulder,1995.
[79]Tian F, Hu H, et al. Extension of the Representative Elementary Watershed approach for cold regions via explicit treatment of energy related processes [J]. Hydrology and Earth System Sciences,2006,10:619-644.
[80]Tynybekov. Glacier Degradation from GIS and Remote Sensing Data [J]. Nato Sci Peace Secur,2009:159-163.
[81]Wang G X, Hu H C, et al. Impacts of changes in vegetation cover on soil water heat coupling in an alpine meadow of the Qinghai-Tibet Plateau, China [J]. Hydrology and earth system sciences,2009,13:327-341.
[82]Wang G X, Hu H C, et al. The influence of freeze-thaw cycles of active soil layer on surface runoff in a permafrost watershed [J]. Journal of Hydrology,2009.375(3-4):438-449.
[83]Wang G X, Wang Y B, et al. Influences of alpine ecosystem responses to climatic change on soil properties on the Qinghai-Tibet Plateau, China [J]. Catena,2007,70:506-514.
[84]Wang L, Koike T, et al. Frozen soil parameterization in a distributed biosphere hydrological model [J]. Hydrology and Earth System Sciences,2010,14 (3):557-571.
[85]Wigmosta M S, Vail L W, et al. A distributed hydrology-vegetation model for complex terrain [J]. Water resource research,1994,30 (6):1665-1680.
[86]Woo M K, Arain M A, et al. A two-directional freeze and thaw algorithm for hydrologic and land surface modelling [J]. Geophysical Research Letters,2004,31:L12501.
[87]Wu Qingbai, Liu Yongzhi. Ground temperature monitoring and its recent change in Qiinghai-Tibet Plateau [J]. Cold regions sciences and technology,2004,38:85-92.
[88]Wu Qingbai, Zhang Tingjun. Changes in active layer thickness over the Qinghai-Tibetan Plateau from 1995 to 2007 [J]. Journal of geophysical research,2010,115:D09107.
[89]Yang Meixue, Nelson F E, et al. Permafrost degradation and its environmental effects on the Tibetan Plateau:A review of recent research [J]. Earth-science reviews,2010,103:31-44.
[90]Yang Zhaoping, Ou Yanghua, et al. Effects of permafrost degradation on ecosystems [J]. Acta Ecologica Sinica,2010,30:33-39.
[91]Yi S H, Woo M K, et al. Impacts of peat and vegetation on permafrost degradation under climate warming [J]. Geophysical research letters,2007,34(16):L16504.
[92]Zhang T J. Influence of the seasonal snow cover on the ground thermal regime:An overview [J]. Reviews of Geophysics,2005,43(4).
[93]Zhang Tingjun, Barry R G, et al. An amplified signal of climatic change in soil temperatures during the last century at Irkutsk, Russia [J]. Climatic Change,2001 b,49:41-76.
[94]Zhang Tingjun, Barry R G, et al. Distribution of seasonally and perennially frozen ground in the Northern Hemisphere [C]. In:Proceedings of the 8th International Conference on Permafrost,2003,21-25, Zurich, Switzerland [Phillips, M, Springman, S M, and Arenson, L U(eds)] Swets and Zeitlinger, Lisse, the Netherlands:1289-1294.
[95]Zhang Tingjun, Barry R G, et al. Statistics and characteristics of permafrost and ground-ice distribution in the Northern Hemisphere [J]. Polar Geography,2008,31(1-2):47-68.
[96]Zhang X, Sun S F, et al. Development and testing of a frozen soil parameterization for cold region studies [J]. Journal of Hydrometeorology,2007,8:690-701.
[97]Zhang Yinsuo, Wang Shusen, et al. Impact of snow cover on soil temperature and its simulation in a boreal aspen forest [J]. Cold Regions Science and Technology,2008,52(3): 355-370.
[98]Zhang Z, Kane D L, et al. Development and application of a spatially-distributed Arctic hydrological and thermal process model (ARHYTHM) [J]. Hydrological Processes,2000,14: 1017-1044.
[99]陈玲.线性模型中参数型经验Bayes估计若干问题研究[D].中国科学技术大学：2010.
[100]程国栋.厚层地下冰的形成机制.中国科学院地学部第二次学部委员会大会文集.北京：科学出版社，1988：191-193.
[101]丁永建,秦大河.冰冻圈变化与全球变暖：我国面临的影响及对策[J].中国基础科学,2009,第3期第五版.
[102]郝振纯,江微娟等.青藏高原河源区气候变化特征分析[J].冰川冻土,2010,32(6)：1130-1135.
[103]何晓波.典型多年冻土能水动态特征研究[D].兰州：中国科学院寒区旱区环境与工程研究所.2008.
[104]何元庆,张忠林等.中国季风温冰川区近代气候变化与冰川动态[J].地理学报,2003,58(4)：550-558.
[105]何元庆,章典.气候变暖是玉龙雪山冰川退缩的主要原因[J].冰川冻土,2004,26(2)：230-231.
[106]胡和平,叶柏生等.考虑冻土的陆面过程模型及其在青藏高原GAME/Tibet试验中的应用[J].中国科学D辑：地球科学,2006,36(8)：755-766.
[107]蒋喜.祁连山七一冰川暖季能量-物质平衡观测与模拟研究[D].兰州：中国科学院寒区早区环境与工程研究所.2008.
[108]金会军,李述训等.气候变化对中国多年冻土和寒区环境的影响[J].地理学报, 2000,55(2)：161-173.
[109]康尔泗.寒区和干旱区水文研究的回顾和展望[J].冰川冻土,1998,23(7)：675-681.
[110]康尔泗,程国栋等.西部干旱区冰雪水资源和出山径流[M].北京：科学出版社.2002.
[111]李弘毅,王建,郝晓华.祁连山区风吹雪对积雪质能过程的影响[J].冰川冻土,2012,34(5)：1084-1090.
[112]李生辰,徐亮等.近34 a青藏高原降水变化及其分区[J].中国沙漠,2007,27(2)：307-314.
[113]李述训,程国栋.冻融土中的水热输运原理.兰州：兰州大学出版社.1995.
[114]李述训,南卓铜等.冻融作用对系统与环境间能量交换的影响[J].冰川冻土,2006,24(2)：109-115.
[115]李帅,谢国辉,等.阿勒泰地区降水量、可降水量及降水转化率分析[J].冰川冻土,2008,30(4)：675-680.
[116]李太兵,王根绪等.长江源多年冻土区典型小流域水文特征分析[J].冰川冻土2009,31(1)：82-88.
[117]李新,程国栋.冻土-气候关系模型评述[J].冰川冻土,2003,24(03)：315-321.
[118]李忠勤,沈永平等.冰川消融对气候变化的响应——以乌鲁木齐河源1号冰川为例[J].冰川冻土,2007,29(3)：333-342.
[119]刘光生.长江源多年冻土区沼泽及高寒草甸水热过程及其对气候变化的响应[D].兰州：兰州大学,2009.
[120]刘光生,王根绪等.三江源区气候及水文变化特征研究[J].长江流域资源与环境,2012,21(3)：302—309.
[121]刘时银,沈永平等.祁连山西段小冰期以来的冰川变化研究[J].冰川冻土,2002,24(3)：227-233.
[122]刘时银,上官冬辉等.20世纪初以来青藏高原东南部岗日嘎布山的冰川变化[J].冰川冻土,2005，27(1)：55-63.
[123]刘时银,丁永建等.中国西部冰川对近期气候变暖的响应[J].第四纪研究,2006,26(5)：762-771.
[124]马虹,胡汝骥.积雪对冻土热状况的影响[J].干旱区地理,1995,18(4)：23-27.
[125]马晓波,胡泽勇.青藏高原40年来降水变化趋势及突变分析[J].中国沙漠,2005,25(1)：137-139.
[126]蒲建辰,姚檀栋等.近百年来青藏高原冰川的进退变化[J].冰川冻土,2004,26(5)：517-522.
[127]秦大河,效存德等.国际冰冻圈研究动态和我国冰冻圈研究的现状和展望[J].应用气象学报.2006,17(6),649-656.
[128]任东兴.基于环境同位素的长江源典型多年冻土小流域水循环规律研究[D].兰州大学,2010.
[129]施雅风,刘时银等.近30a青藏高原气候与冰川变化中的两种特殊现象[J].气候变化研究进展,2006,2(4)：154-160.
[130]孙琳婵,赵林等.西大滩地区积雪对地表反照率及浅层地温的影响[J].山地学报,2010,28(3)：266-273.
[131]王国亚,毛炜峰等.新疆阿勒泰地区积雪变化特征及其对冻土的影响[J].冰川冻土, 2012,34(6)：1293-1300.
[132]王书功.水文模型参数估计方法及参数估计不确定性研究[D].兰州：中国科学院寒区旱区环境与工程研究所.2006.
[133]王叶堂,何勇等.2000-2005年青藏高原积雪时空变化分析[J].冰川冻土,2007,29(6)：855-861.
[134]吴吉春,盛煜等.青藏高原多年冻土退化过程及方式[J].中国科学D辑：地球科学,2009，11：1570-1578.
[135]肖红浪.中国水情-水源、水患、水利[M].开明出版社.2000.
[136]谢自楚,刘潮海.冰川学导论[M].上海：上海科学普及出版社.2010.
[137]徐学祖,邓友生.冻土中水分迁移的实验研究[M].北京：科学出版社.1991
[138]徐学祖,王家澄等.冻土物理学[M].北京：科学传版社.2001.
[139]杨梅学,姚檀栋等.青藏高原唐古拉山北坡夏季风降水特征的初步分析[J].冰川冻土,1999,21(3)：233-236.
[140]姚檀栋,刘时银等.高亚洲冰川的近期退缩及其对西北水资源的影响[J].中国科学(D)辑：地球科学,2004,34(6)：535-543.
[141]赵林,程国栋等.青藏高原五道梁附近多年冻土活动层冻结和融化过程[J].科学通报,2000,45(11)：1205--1211.
[142]赵林,李韧等.唐古拉地区活动层土壤水热特征的模拟研究[J].冰川冻土,2008,30(6)：930-937.
[143]赵勇,崔彩霞等.北疆冬季降水的气候特征分析[J].冰川冻土,2011,33(2)：292-299.
[144]周剑,王根绪等.高寒冻土地区草甸草地生态系统的能量-水分平衡分析[J].冰川冻土,2008,30(3)：398-407.
[145]周幼吾,郭东信等.中国冻土[M].北京：科学出版社.2000.
[2]Allison I, Barry R G, et al. Climate and Cryosphere (CliC) Project. Science and Co-ordination Plan, Version 1.1., World Climate Research Programme [R]. WCRP-114, WMO/TD No.1053, Geneva,2001, pp.76.
[3]Anderson E A. A point energy and mass balance model of a snow cover, NWS Technical Report 19 [P]. National Oceanic and Atmospheric Administration, Washington, DC, USA, 1976,150 pp.
[4]Andreadis K M, Storck P, et al. Modeling snow accumulation and ablation in forested environments [J]. Water resource research,2009,45:W05429.
[5]Anisimov O A, Shiklomanov N I, et al. Global warming and active-layer thickness:results from transient general circulation models [J]. Global and Planetary Change,1997,15:61-78.
[6]Argent R M, Voinov A, et al. Comparing modelling frameworks-A workshop arrroach[J]. Environmental modelling & software,2006,21:895-910.
[7]Armstrong R L, Brun E. Snow and climate:physical processes, surface energy exchange and modeling [M]. Cambridge University Press,2008.
[8]Bartelt P, Lehning M. A physical SNOWPACK model for Avalanche Warning Services Part I: numerical model [J]. Cold Regions Science and Technology,2002,35:123-145.
[9]Boer M M, Koster E A. Greenhouse-impact on Cold-Climate Ecosystems and Landscapes[J]. Catena Supplement,1992,22:1-151.
[10]Braithwaite R J, Olesen O B. Response of the energy balance on the margin of the Greenland ice sheet to temperature changes [J]. Journal of Glaciology,1990,36 (123):217-221.
[11]Braun L, Aellen M. Modelling discharge of glacierized basins assisted by direct measurements of glacier mass balance [J]. IAHS Publ,1990,193:99-106.
12] Braun L, Grabs W, et al. Application of a conceptual precipitation-runoff model in the Langtang Kfaola Basin, Nepal Himalaya [J]. Snow and glacier hydrology,1992,218: 221-237.
13] Brown J, Nelson F E, et al. The circumpolar active layer monitoring (CALM) program research designs and initial results [J]. Polar Geography,2000,3:165-258.
14] Brun E, Martin E, et al. An energy and mass model of snow cover sidtable for operational avalanche forecasting [J]. Journal of Glaciology,1989,35 (121):333-342.
15] Chen R S, Lu S H, et al. A distributed water-heat coupled model for mountainous watershed of an inland river basin of Northwest China (Ⅰ):model structure and equations [J]. Environmental Geology,2008,53 (6):1299-1309.
16] Cheng Guodong, Wu Tonghua, et al. Responses of permafrost to climate change and their environmental significance, Qinghai-Tibet Plateau [J]. Journal of Geophysical Research,2007, 112;F02S03
17] Cherkauer, K A,& Lettenmaier D P. Simulation of spatial variability in snow and frozen soil [J]. Journal of Geophysical Research,2003,108:D22.
[18]Christiansen H H. Meteorological control on interannual spatial and temporal variations in snow cover and ground thawing in two northeast greenlandic circumpolar-active-layer-monitoring (CALM) sites [J]. Permafrost Periglac,2004,15(2): 155-169.
[19]Christiansen J R, Elberling B, Jansson P E. Modelling water balance and nitrate leaching in temperate Norway spruce and beech forests located on the same soil type with the CoupModel [J]. Forest Ecology and Management,2006,237(1-3):545-556.
[20]Coordinate Energy and Water-cycle Observations Project (CEOP) Strategic Implementation Plan:http://www.ceop.net/2008.
[21]Crawford N. Computer simulation techniques for forecasting snowmelt runoff [J]. The role of snow and ice in hydrology,1973:1062-1072.
[22]Cuffey K M, Paterson W S B. The physics of glaciers(fourth edition) [M]. www, elsevier. com/permissions,2010.
[23]Flerchinger G N, Saxton K E. Simultaneous heat and water model of a freezing snow-residue-soil system I:Theory and development [J]. Transactions of the American Society of Agricultural Engineers,1989,32:565-571.
[24]Fukushima Y, Watanabe O, et al. Estimation of streamflow change by global warming in a glacier-covered high mountain area of the Nepal Himalaya [J].20th General Assembly of the International Union of Geodesy and Geophysics, Vienna,1991, Aust,08/11-24/91: 181-188.
[25]Garnier B J, Ohmura A. The evaluation of surface variations in solar radiation income [J]. Solar Energy,1970,13:21-34.
[26]Gao Q, Shi S. Water resources in the arid zone of northwest China [J]. Journal of Desert Research,1992,124:1-12.
[27]Granger R J, Gray D M, et al. Snowmelt infiltration to frozen prairie soils [J]. Canadian Journal of Earth Sciences,1984,21:669-677.
[28]Granger R J, Gray D M. Evaporation from natural nonsaturated surfaces [J]. Journal of Hydrology,1989,111:21-29.
[29]Gray D M, Landine P G. Albedo model for shallow prairie snow covers [J]. Canadian Journal of Earth Sciences,1987,24:1760-1768.
[30]Gray D M, Landine P G. An energy-budget snowmelt model foor the Canndian Prairies [J]. Can J Earth Sci,1988,25(8):1292-1303.
[31]Hansson K, Simunek J, et al. Water flow and heat transport in frozen soil:Numerical solution and freeze-thaw applications [J]. Vadose Zone J,2004,3 (2):693.
[32]Harlan R. Analysis of coupled heat-fluid transport in partially frozen soil [J]. Water resource research,1973,9(5):1314-1323.
[33]Hollesen J, Elberling B, et al. Modelling subsurface temperatures in a heat producing coal waste rock pile, Svalbard (78°N) [J]. Cold Regions Science and Technology,2009,58(1-2): 68-76.
[34]IPCC. Climate Change and Impact 1990[M]. Cambridge:Cambridge University Pres.1990.
[35]IPCC. Climate Change 1995:Impacts, Adaptation, and Mitigation [M]. Cambridge: Cambridge University Press.1996.
[36]IPCC. Climate Change 2001:Impact, Adaptation, and Vulnerability [M]. Cambridge: Cambridge University Press.2001.
[37]IPCC. IPCC Fourth Assessment Report (AR4) [M]. Cambridge:Cambridge University Press. 2007.
[38]Iwata Y, Nemoto M, et al. Influence of rain, air temperature, and snow cover on subsequent spring-snowmelt infiltration into thin frozen soil layer in northern Japan [J]. Journal of Hydrology,2011,401 (3-4):165-176.
[39]Jansson P E. Simulation model for soil water and heat conditions:Description of the SOIL model [Z]. Division of Agricultural Hydrotechnics Communications 98:2, Department of Soil Sciences, Swedish University of Agricultural Sciences, Uppsala,1998.
[40]Jansson P E, Moon D S. A coupled model of water, heat and mass transfer using object orientation to improve flexibility and functionality [J]. Environmental Modelling & Software, 2001,16(1):37-46.
[41]Johnsson H, Bergstr M L, et al. Simulated nitrogen dynamics and losses in a layered agricultural soil [J]. Agriculture, Ecosystems & Environment,1987,18:333-356.
[42]Jordan R. A one-dimensional temperature model for a snow cover. Technical documentation forSNTHERM.89 [R]. US Army Corps of Engineers Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire,1991,49 pp.
[43]Karlberg L, Ben-Gal A, et al. Modelling transpiration and growth in salinity-stressed tomato under different climatic conditions [J]. Ecological Modelling,2006,190(1-2):15-40.
[44]Konz M, Uhlenbrook S, et al. Implementation of a process-based catchment model in a poorly gauged, highly glacierized Himalayan headwater [J]. Hydrology and Earth System Sciences,2007,11(4):1323-1339.
[45]Lawrence D M, Slater A G. A projection of severe near-surface permafrost degradation during the 21 st century [J]. Geophysical Research Letters,2005,24:L24401.
[46]Leavesley G H, Lichty R W, et al. Precipitation-runoff modelling system:user's manual [R], US Geological Survey, Reston, Virginia, Water-Resources Investigations Report,1983: 83-4238.
[47]Leavesley G H, Restrepo P J, et al. The Modular Modeling System (MMS):User's Manual [R]. Open-File Report, U S Geological Survey,1996,96-151.
[48]Lehning M, Bartelt P B, et al. A physical SNOWPACK model for the Swiss Avalanche Warning Services Part Ⅱ:Snow Microstructure [J]. Cold Regions Science and Technology, 2002a,35:147-167.
[49]Lehning M, Bartelt P B, et al. A physical SNOWPACK model for the Swiss Avalanche Warning Services Part Ⅲ:Meteorological Boundary Conditions, Thin Layer Formation and Evaluation [J]. Cold Regions Science and Technology,2002b,35(3):169-184.
[50]Lehning M, Volksch I, et al. ALPINE3D:a detailed model of mountain surface processes and its application to snow hydrology [J]. Hydrological processes,2006,20 (10):2111-2128.
[51]Lemke P, Ren J W. Observations:Changes in Snow, Ice and Frozen Ground[R]. IPCC.2007: 337-38.
[52]Li Xin, Cheng Guodong, et al. Modeling Chinese cryospheric change by using GIS technology [J]. Cold Regions Science and Technology,2003,36:1-9.
[53]Li Xin, Cheng Guodong, et al. Cryospheric change in China [J]. Global and Planetary Change,2008,62:210-218.
[54]Li X, Koike T. Frozen soil parameterization in SiB2 and its validation with GAME-Tibet observations [J]. Cold Regions Science and Technology,2003,36:165-182.
[55]Liang X, Lettenmaier D P, et al. A Simple hydrologically Based Model of Land Surface Water and Energy Fluxes for GSMs [J]. Journal of Geophysical Research,1994,99(D7): 14415-14428.
[56]Luce C H, Tarboton D G. The application of depletion curves for parameterization of subgrid variability of snow [J]. Hydrological processes,2004,18 (8):1409-1422.
[57]Luo L F, Robock A, et al. Effects of frozen soil on soil temperature, spring infiltration, and runoff:Results from the PILPS 2(d) experiment at Valdai, Russia [J]. Journal of Hydrometeorology,2003,4 (2):334-351.
[58]Marks D, Domingo J, et al. A spatially distributed energy balance snowmelt model for application in mountain basins [J]. Hydrological Process,1999,13(12-13):1935-1959.
[59]Milly P C D. Moisture and heat transport in hysteretic, inhomogeneous porous media:a matric head-based formulation and a numerical model [J]. Water resource research,1982, 18(3):489-498.
[60]Molders N, Romanovsky V E. Long-term evaluation of the hydro-thermodynamic soil-vegetation scheme's frozen ground/permafrost component using observations at Barrow, Alaska [J]. Journal of Geophysical Research,2006,111:D04105.
[61]Nicolsky D J, Romanovsky V E, et al. Improved modeling of permafrost dynamics in Alaska with CLM3[J]. Geophysical Research Letters,2007,34.
[62]Oerlemans J, Fortuin J. Sensitivity of glaciers and small ice caps to greenhouse warming [J]. Science,1992,258(5079):115-117.
[63]Ogden F L, Saghafian B. Green and Ampt infiltration with redistribution [J]. Journal of Irrigation and Drainage Engineering,1997,123(5):386-393.
[64]Osterkamp T E. Characteristics of the recent warming of permafrost in Alaska [J]. Geophysical Research Letters,2007,112:F02S02.
[65]Peduzzi P, Herold C, et al. Assessing high altitude glacier thickness, volume and area changes using field, GIS and remote sensing techniques:the case of Nevado Coropuna (Peru) [J]. Cryosphere,2010,4 (3):313-323.
[66]Philip J, Vries D D. Moisture movement in porous materials under temperature gradients, Trans [J]. Am. Geophys. Union,1957,38 (2):222-232.
[67]Pohl S, Davison B, et al. Modelling spatially distributed snowmelt and meltwater runoff in a small Arctic catchment with a hydrology land-surface scheme (WATCLASS) [J]. Atmos Ocean,2005,43 (3),193-211.
[68]Pomeroy J W, Gray D M, et al. The cold regions hydrological model:a platform for basing process representation and model structure on physical evidence [J]. Hydrological Processes, 2007,21:2650-2667.
[69]Pomeroy J W, Li L. Prairie and arctic areal snow cover mass balance using a blowing snow model [J]. Journal of Geophysical Research,2000,105:26619-26634.
[70]Priestley C H, Taylor R J. On the assessment of surface heat flux and evaporation using large-scale parameters [J]. Monthly Weather Review,1972,100:81-92.
[71]Qin Dahe, Liu Shiyin, et al. Snow cover distribution, variability, and response to climate change in western China [J]. Journal of Climate,2006.19(9):1820-1833.
[72]Rigon R, Bertoldi G, et al. GEOtop:a distributed hydrological model with coupled water and energy budgets [J]. Journal of Hydrometeorology,2006,7:371-388.
[73]Schirmer M, Wirz V, et al. Persistence in intra-annual snow depth distribution:1. Measurements and topographic control [J]. Water resource. Research,2011,47 (9):W09516.
[74]Schuur E A G, Abbott B, et al. High risk of permafrost thaw [J]. Nature,2011,480(7375): 32-33.
[75]Sivapalan M, Takeuchi K, et al. IAHS decade on predictions in ungauged basins (PUB), 2003-2012:shaping an exciting future for the hydrological sciences [J]. Hydrological Sciences Journal,2003,48(6):857-880.
[76]Stendel M, Christensen J H. Impact of global warming on permafrost conditions in a coupled GCM [J]. Geophysical Research Letters,2002,13.
[77]Svensson M, Jansson P E, et al. Bayesian calibration of a model describing carbon, water and heat fluxes for a Swedish boreal forest stand [J]. Ecological modelling,2008,213:331-344.
[78]Tarboton D G, Chowdhury T G, et al. A spatially distributed energy balance snowmelt model [C]. In:Proceedings of symposium on biogeochemistry of seasonally snow-covered catchments, Boulder,1995.
[79]Tian F, Hu H, et al. Extension of the Representative Elementary Watershed approach for cold regions via explicit treatment of energy related processes [J]. Hydrology and Earth System Sciences,2006,10:619-644.
[80]Tynybekov. Glacier Degradation from GIS and Remote Sensing Data [J]. Nato Sci Peace Secur,2009:159-163.
[81]Wang G X, Hu H C, et al. Impacts of changes in vegetation cover on soil water heat coupling in an alpine meadow of the Qinghai-Tibet Plateau, China [J]. Hydrology and earth system sciences,2009,13:327-341.
[82]Wang G X, Hu H C, et al. The influence of freeze-thaw cycles of active soil layer on surface runoff in a permafrost watershed [J]. Journal of Hydrology,2009.375(3-4):438-449.
[83]Wang G X, Wang Y B, et al. Influences of alpine ecosystem responses to climatic change on soil properties on the Qinghai-Tibet Plateau, China [J]. Catena,2007,70:506-514.
[84]Wang L, Koike T, et al. Frozen soil parameterization in a distributed biosphere hydrological model [J]. Hydrology and Earth System Sciences,2010,14 (3):557-571.
[85]Wigmosta M S, Vail L W, et al. A distributed hydrology-vegetation model for complex terrain [J]. Water resource research,1994,30 (6):1665-1680.
[86]Woo M K, Arain M A, et al. A two-directional freeze and thaw algorithm for hydrologic and land surface modelling [J]. Geophysical Research Letters,2004,31:L12501.
[87]Wu Qingbai, Liu Yongzhi. Ground temperature monitoring and its recent change in Qiinghai-Tibet Plateau [J]. Cold regions sciences and technology,2004,38:85-92.
[88]Wu Qingbai, Zhang Tingjun. Changes in active layer thickness over the Qinghai-Tibetan Plateau from 1995 to 2007 [J]. Journal of geophysical research,2010,115:D09107.
[89]Yang Meixue, Nelson F E, et al. Permafrost degradation and its environmental effects on the Tibetan Plateau:A review of recent research [J]. Earth-science reviews,2010,103:31-44.
[90]Yang Zhaoping, Ou Yanghua, et al. Effects of permafrost degradation on ecosystems [J]. Acta Ecologica Sinica,2010,30:33-39.
[91]Yi S H, Woo M K, et al. Impacts of peat and vegetation on permafrost degradation under climate warming [J]. Geophysical research letters,2007,34(16):L16504.
[92]Zhang T J. Influence of the seasonal snow cover on the ground thermal regime:An overview [J]. Reviews of Geophysics,2005,43(4).
[93]Zhang Tingjun, Barry R G, et al. An amplified signal of climatic change in soil temperatures during the last century at Irkutsk, Russia [J]. Climatic Change,2001 b,49:41-76.
[94]Zhang Tingjun, Barry R G, et al. Distribution of seasonally and perennially frozen ground in the Northern Hemisphere [C]. In:Proceedings of the 8th International Conference on Permafrost,2003,21-25, Zurich, Switzerland [Phillips, M, Springman, S M, and Arenson, L U(eds)] Swets and Zeitlinger, Lisse, the Netherlands:1289-1294.
[95]Zhang Tingjun, Barry R G, et al. Statistics and characteristics of permafrost and ground-ice distribution in the Northern Hemisphere [J]. Polar Geography,2008,31(1-2):47-68.
[96]Zhang X, Sun S F, et al. Development and testing of a frozen soil parameterization for cold region studies [J]. Journal of Hydrometeorology,2007,8:690-701.
[97]Zhang Yinsuo, Wang Shusen, et al. Impact of snow cover on soil temperature and its simulation in a boreal aspen forest [J]. Cold Regions Science and Technology,2008,52(3): 355-370.
[98]Zhang Z, Kane D L, et al. Development and application of a spatially-distributed Arctic hydrological and thermal process model (ARHYTHM) [J]. Hydrological Processes,2000,14: 1017-1044.
[99]陈玲.线性模型中参数型经验Bayes估计若干问题研究[D].中国科学技术大学：2010.
[100]程国栋.厚层地下冰的形成机制.中国科学院地学部第二次学部委员会大会文集.北京：科学出版社，1988：191-193.
[101]丁永建,秦大河.冰冻圈变化与全球变暖：我国面临的影响及对策[J].中国基础科学,2009,第3期第五版.
[102]郝振纯,江微娟等.青藏高原河源区气候变化特征分析[J].冰川冻土,2010,32(6)：1130-1135.
[103]何晓波.典型多年冻土能水动态特征研究[D].兰州：中国科学院寒区旱区环境与工程研究所.2008.
[104]何元庆,张忠林等.中国季风温冰川区近代气候变化与冰川动态[J].地理学报,2003,58(4)：550-558.
[105]何元庆,章典.气候变暖是玉龙雪山冰川退缩的主要原因[J].冰川冻土,2004,26(2)：230-231.
[106]胡和平,叶柏生等.考虑冻土的陆面过程模型及其在青藏高原GAME/Tibet试验中的应用[J].中国科学D辑：地球科学,2006,36(8)：755-766.
[107]蒋喜.祁连山七一冰川暖季能量-物质平衡观测与模拟研究[D].兰州：中国科学院寒区早区环境与工程研究所.2008.
[108]金会军,李述训等.气候变化对中国多年冻土和寒区环境的影响[J].地理学报, 2000,55(2)：161-173.
[109]康尔泗.寒区和干旱区水文研究的回顾和展望[J].冰川冻土,1998,23(7)：675-681.
[110]康尔泗,程国栋等.西部干旱区冰雪水资源和出山径流[M].北京：科学出版社.2002.
[111]李弘毅,王建,郝晓华.祁连山区风吹雪对积雪质能过程的影响[J].冰川冻土,2012,34(5)：1084-1090.
[112]李生辰,徐亮等.近34 a青藏高原降水变化及其分区[J].中国沙漠,2007,27(2)：307-314.
[113]李述训,程国栋.冻融土中的水热输运原理.兰州：兰州大学出版社.1995.
[114]李述训,南卓铜等.冻融作用对系统与环境间能量交换的影响[J].冰川冻土,2006,24(2)：109-115.
[115]李帅,谢国辉,等.阿勒泰地区降水量、可降水量及降水转化率分析[J].冰川冻土,2008,30(4)：675-680.
[116]李太兵,王根绪等.长江源多年冻土区典型小流域水文特征分析[J].冰川冻土2009,31(1)：82-88.
[117]李新,程国栋.冻土-气候关系模型评述[J].冰川冻土,2003,24(03)：315-321.
[118]李忠勤,沈永平等.冰川消融对气候变化的响应——以乌鲁木齐河源1号冰川为例[J].冰川冻土,2007,29(3)：333-342.
[119]刘光生.长江源多年冻土区沼泽及高寒草甸水热过程及其对气候变化的响应[D].兰州：兰州大学,2009.
[120]刘光生,王根绪等.三江源区气候及水文变化特征研究[J].长江流域资源与环境,2012,21(3)：302—309.
[121]刘时银,沈永平等.祁连山西段小冰期以来的冰川变化研究[J].冰川冻土,2002,24(3)：227-233.
[122]刘时银,上官冬辉等.20世纪初以来青藏高原东南部岗日嘎布山的冰川变化[J].冰川冻土,2005，27(1)：55-63.
[123]刘时银,丁永建等.中国西部冰川对近期气候变暖的响应[J].第四纪研究,2006,26(5)：762-771.
[124]马虹,胡汝骥.积雪对冻土热状况的影响[J].干旱区地理,1995,18(4)：23-27.
[125]马晓波,胡泽勇.青藏高原40年来降水变化趋势及突变分析[J].中国沙漠,2005,25(1)：137-139.
[126]蒲建辰,姚檀栋等.近百年来青藏高原冰川的进退变化[J].冰川冻土,2004,26(5)：517-522.
[127]秦大河,效存德等.国际冰冻圈研究动态和我国冰冻圈研究的现状和展望[J].应用气象学报.2006,17(6),649-656.
[128]任东兴.基于环境同位素的长江源典型多年冻土小流域水循环规律研究[D].兰州大学,2010.
[129]施雅风,刘时银等.近30a青藏高原气候与冰川变化中的两种特殊现象[J].气候变化研究进展,2006,2(4)：154-160.
[130]孙琳婵,赵林等.西大滩地区积雪对地表反照率及浅层地温的影响[J].山地学报,2010,28(3)：266-273.
[131]王国亚,毛炜峰等.新疆阿勒泰地区积雪变化特征及其对冻土的影响[J].冰川冻土, 2012,34(6)：1293-1300.
[132]王书功.水文模型参数估计方法及参数估计不确定性研究[D].兰州：中国科学院寒区旱区环境与工程研究所.2006.
[133]王叶堂,何勇等.2000-2005年青藏高原积雪时空变化分析[J].冰川冻土,2007,29(6)：855-861.
[134]吴吉春,盛煜等.青藏高原多年冻土退化过程及方式[J].中国科学D辑：地球科学,2009，11：1570-1578.
[135]肖红浪.中国水情-水源、水患、水利[M].开明出版社.2000.
[136]谢自楚,刘潮海.冰川学导论[M].上海：上海科学普及出版社.2010.
[137]徐学祖,邓友生.冻土中水分迁移的实验研究[M].北京：科学出版社.1991
[138]徐学祖,王家澄等.冻土物理学[M].北京：科学传版社.2001.
[139]杨梅学,姚檀栋等.青藏高原唐古拉山北坡夏季风降水特征的初步分析[J].冰川冻土,1999,21(3)：233-236.
[140]姚檀栋,刘时银等.高亚洲冰川的近期退缩及其对西北水资源的影响[J].中国科学(D)辑：地球科学,2004,34(6)：535-543.
[141]赵林,程国栋等.青藏高原五道梁附近多年冻土活动层冻结和融化过程[J].科学通报,2000,45(11)：1205--1211.
[142]赵林,李韧等.唐古拉地区活动层土壤水热特征的模拟研究[J].冰川冻土,2008,30(6)：930-937.
[143]赵勇,崔彩霞等.北疆冬季降水的气候特征分析[J].冰川冻土,2011,33(2)：292-299.
[144]周剑,王根绪等.高寒冻土地区草甸草地生态系统的能量-水分平衡分析[J].冰川冻土,2008,30(3)：398-407.
[145]周幼吾,郭东信等.中国冻土[M].北京：科学出版社.2000.