A JoH paper on routing

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) ;


A PPP paper on modeling permafrost distr on QTP

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.

Link: http://onlinelibrary.wiley.com/doi/10.1002/ppp.1971/pdf

A paper about choosing a reference period in modeling of change impacts

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.

*corresponding author

zhang et al.-stoten-2018 (PDF)

A land loss Chinese paper

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)


[1] 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)


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.

A paper on evaluation of some simple permafrost models on QTP

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.

PDF available upon request.

三篇IGARSS 2016会议论文:关于多层土壤数据和降水较正

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