Zhang L, Nan Z, Wang W, Ren D, Zhao Y, Wu X. Separating climate change and human contributions to variations in streamflow and its components using eight time-trend methods. Hydrological Processes. 2018, Online. DOI:10.1002/hyp.13331.
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.
Cao Y, Nan Z, Cheng G, Zhang L. Hydrological variability in the arid lands of northwest China during 2002-2013. Advances in Meteorology. 2018, 2018(1502472): 1-13. DOI:10.1155/2018/1502472.
The arid region of Northwest China (ANC) has a distinct and fragile inland water cycle. This study examined the hydrological variations in ANC and its three subregions from August 2002 to December 2013 by integrating terrestrial water storage (TWS) anomaly data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite, soil moisture data modeled by the Global Land Data Assimilation System, and passive microwave snow water equivalent data. The results show that the TWS in ANC increased at a rate of 1.7mm/a over the past decade, which consisted of an increasing trend of precipitation (0.12mm/a). Spatially, in the northern ANC, TWS exhibited a significant decreasing trend of −3.64 mm/a ( < 0.05) as a result of reduced rainfall, increased glacial meltwater draining away from the mountains, and intensified human activities. The TWS in southern and eastern ANC increased at a rate of 2.14 ( = 0.10) and 1.63 ( < 0.01)mm/a, respectively. In addition to increasing precipitation and temperature, decreasing potential evapotranspiration in Southern Xinjiang and expanding human activities in Hexi-Alashan together led to an overall increase in TWS. Increased glacier meltwater and permafrost degradation in response to climate warming may also affect the regional TWS balance. The variations in soil moisture, groundwater, and surface water accounted for the majority of the TWS anomalies in southern and easternANC.The proposed remote sensing approach combiningmultiple data sources proved applicable and useful to understand the spatiotemporal characteristics of hydrological variability in a large area of arid land without the need for field observations.
Links: Baidu, Official,
Zhang L, Nan Z*, Liang X*, Xu Y, Hernandez F, Li L. Application of the MacCormack Scheme to Overland Flow Routing for High-spatial Resolution Distributed Hydrological Model. Journal of Hydrology. 2018, 558: 421-431.
Although process-based distributed hydrological models (PDHMs) are evolving rapidly over the last few decades, their extensive applications are still challenged by the computational expenses. This study attempted, for the first time, to apply the numerically efficient MacCormack algorithm to overland flow routing in a representative high-spatial resolution PDHM, i.e., distributed hydrology-soil-vegetation model (DHSVM), in order to improve its computational efficiency. The analytical verification indicates that both the semi and full versions of the MacCormack schemes exhibit robust numerical stability and are more computationally efficient than the conventional explicit linear scheme. The full-version outperforms the semi-version in terms of simulation accuracy when a same time step is adopted. The semi-MacCormack scheme was implemented into DHSVM (version 3.1.2) to solve the kinematic wave equations for overland flow routing. The performance and practicality of the enhanced DHSVM-MacCormack model were assessed by performing two groups of modeling experiments in the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The experiments show that DHSVM-MacCormack can considerably improve the computational efficiency without compromising the simulation accuracy of the original DHSVM model. More specifically, with the same computational environment and model settings, the computational time required by DHSVM-MacCormack can be reduced to several dozen minutes for a simulation period of three months (in contrast with one day and a half by the original DHSVM model) without noticeable sacrifice of the accuracy. The MacCormack scheme proves to be applicable to overland flow routing in DHSVM, which implies that it can be coupled into other PHDMs for watershed routing to either significantly improve their computational efficiency or to make the kinematic wave routing for high resolution modeling computational feasible.
Keywords: MacCormack Scheme; Overland Flow Routing; DHSVM; Kinematic Wave; Computational Efficiency
Links: Link1 (Elesvier, 50day’s free access since Feb 4, 2018) ; Baidu;
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
Zhang L, Nan Z*, Yu W, Zhao Y, Xu Y. Comparison of baseline period choices for separating climate and land use/land cover change impacts on watershed hydrology using distributed hydrological models. Science of the Total Environment. 2018, 622-623: 1016-1028.
Article in PDF
黄滢冰，南卓铜*，徐启恒，赵克飞. 珠三角典型地区耕地流失特征及机制分析——以1988年～2013年快速城市化的东莞市为例. 世界地理研究. 2017, 26(05): 44-55.
hby_dongguan_land_loss-2017 (pdf, 653KB)
 H Chen, C Ning, Z Nan, et al. Correction of Daily Precipitation Data over the Qinghai-Tibetan Plateau with Machine Learning Models[J]. 2017, 39(3): 583—592.[陈浩，宁忱，南卓铜，等. 基于机器学习模型的青藏高原日降水数据的订正研究[J]. 冰川冻土. 2017, 39(3): 583—592.]
下载：Link 1 (from冰川冻土); precip.machine.learning-wyd-2017 (Local)
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.
1. Wu X, Nan Z.A multilayer soil texture dataset for permafrost modeling over Qinghai-Tibetan Plateau.In Proceeding of 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS),2016. 4917-4920. (wu et al. 2016, igarss )
2. Wang Y, Nan Z*, Chen H, Wu X.Correction of daily precipitation data of ITPCAS dataset over the Qinghai-Tibetan Plateau with KNN model.In Proceeding of 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS),2016. 593-596. (wang et al. 2016, igarss)
3. Ning C, Wang Y, Nan Z*, Chen H, Liu C.Study on correction of daily precipitation data of the Qinghai-Tibetan plateau with machine learning models.In Proceeding of 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS),2016. 517-520. (ning et al. 2016, igarss)