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.
Keywords: parameter calibration; cold alpine basin; frozen ground; precipitation seasonality; sensitivity analysis; distributed hydrology–soil–vegetation model
赵奕，南卓铜*，李祥飞，徐毅，张凌. 分布式水文模型DHSVM在西北高寒山区流域的适用性研究. 冰川冻土. 2019, 41(1): 147-157.
分布式水文－土壤－植被模型（Distributed Hydrology Soil Vegetation Model, DHSVM）是基于栅格离散的分布式水文模型，对地表水热循环的各个过程能进行很精细地刻画，被广泛应用于世界各地很多类型的流域的高时空分辨率的水文模拟，然而它在高寒山区的适用性并不清楚。基于300ｍ数字高程模型，应用DHSVM 模型对典型的高寒山区流域八宝河流域2001-2009年的水文过程展开模拟，并采用流域出口祁连站的水文实测数据对模型进行了精度评价。参数敏感性分析表明，土壤横向导水率、田间持水量和植被反照率等是该区域主要的敏感性参数。模型默认参数会高估高寒山区流域的潜在蒸散发量，导致夏季径流量远小于观测值。通过参数率定，模型校准期（2001-2004）的模拟日径流和月径流Nash 效率系数分别达到0.72 和0.87；而模型验证期（2005-2009）分别为0.60 和0.74 。结果表明，DHSVM 模型基本具备了模拟高寒山区流域降水－径流过程的能力。然而，由于DHSVM 模型缺少对高寒山区流域土壤的冻融过程的刻画，春季径流的模拟精度明显受到影响，需要在将来重点改进。
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引用：吴小波，南卓铜*，王维真，赵林. 基于Noah陆面过程模型模拟青藏高原植被和土壤特征对多年冻土影响的模拟. 冰川冻土. 2018, 40(2): 279-287.
Wu X, Nan Z*, Zhao S, Zhao L, Cheng G. Spatial modelling of permafrost distribution and properties on the Qinghai-Tibet Plateau. Permafrost and Periglacial Processes. 2018,(1-14). DOI:10.1002/ppp.1971.
下载: Baidu Cloud
强德霞，赵彦博，南卓铜*，吴小波. 基于参数实时优化的洪水预报系统研究：以黑河干流洪水为例. 水利水电技术. 2017, 48(4): 13-17.
Full text available upon request.
Zhao S, Nan Z*, Huang Y, Zhao L. The application and evaluation of simple permafrost distribution models on the Qinghai-Tibet Plateau. Permafrost and Periglacial Processes. 2017, 28(2): 391-404. DOI:10.1002/ppp.1939.
The performance of simple permafrost distribution models widely used on the Qinghai–Tibet Plateau (QTP) has not been fully evaluated. In this study, two empirical models (the elevation model and mean annual ground temperature model) and three semi-physical models (the surface frost number model, the temperature at the top of permafrost model and the Kudryavtsev model) were investigated. The simulation results from the models were compared to each other and validated against existing permafrost maps of the entire QTP and in three representative areas investigated in the field. The models generally overestimated permafrost distribution in the investigated areas, but they captured the broad characteristics of permafrost distribution on the entire QTP, and performed best in areas with colder, continuous permafrost. Large variations in performance occurred at elevations of 3800–4500 m asl and in areas with thermally unstable permafrost. The two empirical models performed best in areas where permafrost is strongly controlled by elevation, such as eastern QTP. In contrast, the three semi-physical models were better in southern island permafrost areas with relatively flat terrain, where local factors considerably impact the distribution of permafrost. Model performance could be enhanced by explicitly considering the effects of elevation zones and regional conditions.