Category Archives: Recent publications

A paper published online on 水文过程

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.

使用了八种时间趋势法调查了气候变化和人类活动对河川径流及成份变化的贡献,均表明在西北典型流域——黑河流域气候变化和人类活动导致河川径流及组分的增加,但不同方法得到明显不同的增幅。其中,不同方法模拟的人类活动对基流变化的贡献可能占到24-92%,气候变化的贡献则占到8-76%。但对于地表径流变化,人类活动的贡献(21-49%)均小于气候变化。我们也对比了时间趋势法与两种Budyko方法在结果上异同,并且分析和讨论了可能存在的问题、不确定性以及未来工作。

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一篇冰川冻土中文论文

植被和土壤参数会较大影响到陆面过程模型的模拟结果,但在青藏高原的相关模拟中,通常并没有对这些参数进行专门的考虑,而相对地其他区域,青藏高原具有植被稀疏和土壤粗颗粒含量高等显著特征,那么这些特点会对多年冻土的模拟结果会有产生多大的影响?我们的研究表明,青藏高原植被土壤特性对Noah模拟结果较大影响。该成果发表在2018年第2期《冰川冻土》。

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.

下载:官网; Baidu;

A paper on an application of GRACE gravity data

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.

Abstract:

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,

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.

Abstract:

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;

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.

Abstract:

结合遥感解译得到多期土地利用类型图,分析1988年~2013年东莞市耕地流失的数量变化特征、流失强度以及与城市扩张之间的流转关系,并结合社会经济统计数据研究东莞耕地流失的影响因素,确定了人口、产业结构、经济发展状况、居民生活水平和交通发展水平五类耕地流失驱动指标。利用相关性检验、主成分分析和逐步回归法进行驱动力分析。研究结果表明:26年间东莞市耕地流失886.52km~2,占研究区总面积的35.96%,耕地以79.16%的净流失率和6.08%的年均强度持续流失,且耕地流失与城市建设用地之间存在显著的线性流转关系;该期间耕地有四个显著的流失阶段,为原始快速流失期、间歇平稳流失期、二次高速流失期和成熟趋缓流失期,分别反映了同时期的国家政策调整及地区战略规划;一、三产业比重、城市化率、职工工资水平及常住人口等12个驱动因子与耕地流失存在显著相关性,其中的户籍非农人口、GDP、固定资产投资、职工工资水平和公路里程分别为五类驱动指标的主成分;第三产业的发展通过提高居民收入水平进而推动城市房地产业的发展,是加速东莞市耕地流失最为核心的动力机制。

hby_dongguan_land_loss-2017 (pdf, 653KB)

基于机器学习模型的青藏高原日降水数据的订正研究

[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.]

选择了5种机器学习模型,即k最近邻方法(KNN)、多元自回归样条方法(MARS)、支持向量机(SVM)、多项对数线性模型(MLM)和人工神经网络(ANN),利用海拔、相对湿度、坡向、植被、风速、气温和坡度等因子订正ITPCAS和CMORPH两种常用的青藏高原日降水数据集。五折交叉验证表明,KNN的订正精度最高。在三个验证站点(唐古拉、西大滩和五道梁)的误差分析,以及对青藏高原年降水量的空间分析均表明,KNN对CMORPH的订正效果显著,对ITPCAS在局部区域有一定订正效果,ITPCAS及其订正值的降水空间分布准确度高于CMORPH的订正值。主成分分析法表明降水订正是气象和环境因子综合作用的结果。

下载:Link 1 (from冰川冻土); precip.machine.learning-wyd-2017 (Local)

一个洪水预报论文

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.

另:对于里面使用不同模型进行不同场次洪水预报我有不同意见,因为我们无法知道下一场次洪水到底适合何种模型,从而不能实际用起来。但使用实测数据,对给定模型参数进行实时率定,从而优化使用该模型的洪水预报精度,是本文主要想传达的。

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.

ABSTRACT

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.

Links: Baidu;