王玉丹，南卓铜，陈浩，吴小波. 基于K最近邻模型的青藏高原CMORPH日降水数据的订正研究. 遥感技术与应用. 2016, 31(3): 607-616.
摘要：
青藏高原的降水数据主要由遥感产品和多源观测数据融合产生,由于青藏高原的观测站点分布稀疏不均,遥感数据误差较大,因此常用的CMORPH(Climate Prediction Center Morphing Technique)等降水数据集精度有限.通过K 最近邻(K-Nearest Neighbor,简称KNN)模型,可以建立环境(海拔、坡度、坡向、植被)、气象因子(气温、湿度、风速)和日降水量的关系,从而订正青藏高原的CMORPH 日降水数据集,提高数据精度.对CMORPH 日降水数据的误差分析表明,采用KNN 模型订正后的CMORPH 降水数据优于原始数据和采用PDF(Probability Density Function Matching Method)法订正的CMORPH 数据,且空间分布较好地符合青藏高原的降水分布特征.
下载 (~11MB, pdf) Link
马启民，黄滢冰，南卓铜*，吴小波. 青藏高原典型多年冻土区的一维水热过程模拟研究. 冰川冻土. 2016, 38(2): 341-350.
摘要：
了解多年冻土内部的水热过程对寒区工程规划和建设的辅助决策具有重要意义。冻土的水分迁移与温度变化密切相关，然而传统的经验模型局限性大，对水热物理过程考虑不足；陆面过程模型所需的驱动数据多且很难准确模拟深层土温，尽管数值模型在工程上应用的比较多，但很少应用到冻土的演化过程中。基于非饱和土壤渗流和热传导理论，实现了冻土水分场与温度场的水热耦合数值模拟。以唐古拉综合观测场为例，将数值模拟结果与观测数据进行对比，验证水热耦合数值模拟的有效性。结果表明：模型对土壤温度模拟效果较好，15 m以上R2在0.88以上，RMSE在1℃以内；水分模拟尚可，但仍存在一定误差，R2在0.7以上，RMSE在7.65%以内。模拟的活动层厚度约3.6 m，年平均地温所在的深度约为15 m，与实测值基本一致。该水热耦合模型可用于研究多年冻土区土壤水热变化规律.
下载 (pdf, ~10.8 MB): mqm.et al. bcdt.2016
Zhang L, Nan Z, Xu Y, Li S. Hydrological Impacts of Land Use Change and Climate Variability in the Headwater Region of the Heihe River Basin, Northwest China. PloS One. 2016, 11(6): e158394. DOI:10.1371/journal.pone.0158394.
ABSTRACT:
Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basin, northwest China, in the recent past (1995–2014) and near future (2015–2024), by combining two land use models (i.e., Markov chain model and Dyna-CLUE) with a hydrological model (i.e., SWAT). The potential impacts in the near future were explored using projected land use patterns and hypothetical climate scenarios established on the basis of analyzing long-term climatic observations. Land use changes in the recent past are dominated by the expansion of grassland and a decrease in farmland; meanwhile the climate develops with a wetting and warming trend. Land use changes in this period induce slight reductions in surface runoff, groundwater discharge and streamflow whereas climate changes produce pronounced increases in them. The joint hydrological impacts are similar to those solely induced by climate changes. Spatially, both the effects of land use change and climate variability vary with the sub-basin. The influences of land use changes are more identifiable in some sub-basins, compared with the basin-wide impacts. In the near future, climate changes tend to affect the hydrological regimes much more prominently than land use changes, leading to significant increases in all hydrological components. Nevertheless, the role of land use change should not be overlooked, especially if the climate becomes drier in the future, as in this case it may magnify the hydrological responses.
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0158394
Yu W, Nan Z*, Wang Z, Chen H, Wu T, Zhao L. An Effective Interpolation Method for MODIS Land Surface Temperature on the Qinghai-Tibet Plateau. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2015, 8(9): 4539-4550. DOI:10.1109/JSTARS.2015.2464094.
Links: Baidu;
Kargel J S, Leonard G J, Shugar D H, Haritashya U K, Bevington A, Fielding E J, Fujita K, Geertsema M, Miles E S, Steiner J, Anderson E, Bajracharya S, Bawden G W, Breashears D F, Byers A, Collins B, Czyzowska-Wisniewski E, Dhital M R, Donnellan A, Evans T L, Geai M L, Glasscoe M T, Green D, Gurung D R, Heijenk R, Hilborn A, Hudnut K, Huyck C, Immerzeel W W, Jiang L, Jibson R, Kääb A, Khanal N R, Kirschbaum D, Kraaijenbrink P D A, Lamsal D, Liu S, Lv M, Mckinney D, Nahirnick N K, Nan Z, Ojha S, Olsenholler J, Painter T H, Pleasants M, Pratima K, Qi Y, Raup B H, Regmi D, Rounce D R, Sakai A, Shangguan D, Shea J M, Shrestha A B, Shukla A, Stumm D, van der Kooij M, Voss K, Wang X, Weihs B, Wolfe D, Wu L, Yao X, Yoder M R, Young N. Geomorphic, Tectonic, and Geologic Controls of Geohazards Induced by Nepal’s 2015 Gorkha Earthquake. Science. 2015, 350. DOI:10.1126/science.aac8353.
Abstract: The Gorkha earthquake (M 7.8) on 25 April 2015 and later aftershocks struck South Asia, killing ~9,000 and damaging a large region. Supported by a large campaign of responsive satellite data acquisitions over the earthquake disaster zone, our team undertook a satellite image survey of the earthquakes’ induced geohazards in Nepal and China and an assessment of the geomorphic, tectonic, and lithologic controls on quake-induced landslides. Timely analysis and communication aided response and recovery and informed decision makers. We mapped 4,312 co-seismic and post-seismic landslides. We also surveyed 491 glacier lakes for earthquake damage, but found only 9 landslide-impacted lakes and no visible satellite evidence of outbursts. Landslide densities correlate with slope, peak ground acceleration, surface downdrop, and specific metamorphic lithologies and large plutonic intrusions.
http://www.sciencemag.org/lookup/doi/10.1126/science.aac8353
科技部基础性工作“青藏高原多年冻土本底调查”的重要成果，已经通过科学出版社出版出来了。
赵林, 盛煜, 南卓铜 et al., 2015. 多年冻土调查手册. 北京: 科学出版社, 198.
Zhang L., Nan Z., Yu W. et al., 2015. Hydrological response to various Land-Use change scenarios under constant and changed climatic conditions. ENVIRON MANAGE, 10.1007/s00267-015-0620-z.
[1] Zhang L, Nan Z*, Yu W, et al. Modeling Land-Use and Land-Cover Change and Hydrological Responses under Consistent Climate Change Scenarios in the Upper and Middle Heihe River Basin, China. Water Resources Management. 2015. DOI:10.1007/s11269-015-1085-9.
[1] Ren Y, Zhao Y, Nan Z. A prototype of online hydrological model service allied to online science data center[J]. Remote Sensing Technology and Application. 2015, 30(3): 547—556.[任彦润，赵彦博，南卓铜. 联合科学数据中心的在线水文模型服务研究[J]. 遥感技术与应用. 2015, 30(3): 547—556.]
下载：从百度云盘
He S., Nan Z., Hou Y., 2015. Accuracy evaluation of two precipitation datasets over upper reach of Heihe River Basin, northwestern China. Sciences in Cold and Arid Regions, 7(2): 157-169.
Get the paper, He et al. 2015. SCAR. Accuracy evaluation two precip datasets – Copy-small (~920KB, pdf)