野外科学观测研究台站（网络）和科学数据中心建设发展

中国科学院地理科学与资源研究所成立80年来,十分重视野外台站（网络）和科学数据中心的建设,取得了辉煌成就。研究所建立了4个野外观测研究网络,引领了中国生态系统研究网络的建设与发展;成立了2个国家级科学数据中心,1个中国科学院数据中心,1个数据出版系统并于2016年加入了世界数据系统;拥有2个国家级野外观测研究站,1个中国科学院野外研究站,形成了独具特色的野外观测研究平台和数据共享服务平台。本文回顾了中国生态系统研究网络、国家生态系统观测研究网络、中国通量观测研究网络、中国物候观测网和禹城站、拉萨站、千烟洲站以及地球系统科学数据中心、生态科学数据中心、资源环境科学数据中心和全球变化科学研究数据出版系统的发展历程。地理资源所台站（网络）从无到有,不断发展壮大,引领了中国野外观测研究事业的发展,支撑了地理学、生态学等重要科学成果产出,科技支撑能力和示范能力大幅提升,有力支撑了华北平原、青藏高原以及南方山地丘陵区的生态文明建设;成为中国地球系统科学、野外台站、资源环境等学科和领域最大的科学数据汇聚中心,数据共享服务成效显著,在国内外具有广泛影响力。在未来发展中,地理资源所将充分发挥野外台站（网络）综合中心作用,强化生态系统、碳水通量、物候等观测研究网络的能力建设,稳步提升野外观测研究站条件保障能力和科学数据中心的数据汇聚能力、分析挖掘能力以及共享服务能力,持续推动和引领中国科学数据的共享,在科学研究和支撑国家需求等方面做出更大贡献。     

A review of fully coupled atmosphere-hydrology simulations

Journal of Geographical Sciences - The terrestrial hydrological process is an essential but weak link in global/regional climate models. In this paper, the development status, research hotspots and...     

基于DEM的数字流域特征提取研究进展

数字高程模型(DEM)是地表形态高程属性的数字化表达,利用流域DEM数据构建数字水系模型并提取流域水文特征,是分布式水文过程模拟的重要基础。DEM中闭合洼地和平坦区域的处理、流向的确定以及DEM分辨率的大小都直接影响着流域水系特征提取的质量与效率。针对当前基于DEM提取河网与流域特征的诸多问题,阐述了DEM数据提取流域水系特征的原理,回顾了数字水系模型与流域特征提取方法,评述了洼地和平地的处理方法及水流方向的确定方法的研究进展,介绍了当前基于不同DEM数据类型的提取方法研究,探讨了DEM尺度和分辨率对提取流域特征的影响,总结了平缓区域数字水系和河网提取的研究进展。     

大尺度水循环模拟系统不确定性研究进展(英文)

The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects:uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.     

Discrete wavelet transform-based investigation into the variability of standardized precipitation index in Northwest China during 1960–2014

This study analyses spatio-temporal trends in precipitation, temperature, and river discharge in the northeast of Iran during recent decades (1953–2013). The Pettitt, SNHT, Buishand, Box-Pierce, Ljung-Box, and McLeod-Li methods were applied to examine homogeneity in time series studied. The nonparametric Mann-Kendall and Sen’s slope estimator tests were used to detect possible significant (p < 0.05) temporal trends in hydrometeorological time series and their magnitude, respectively. For time series with autocorrelation, the trend-free pre-whitening (TFPW) method was used to determine significant trends. To explore spatial distributions of trends, their magnitudes were interpolated by the inverse distance whitening (IDW) method. Trend analysis shows that for daily, monthly, and annual precipitation time series, 12.5, 19, and 12.5 % of the stations revealed significant increasing trends, respectively. For mean temperature, warming trends were found at 38, 23, and 31 % of the stations on daily, monthly, and annual timescales, in turn. Daily and monthly river discharge decreased at 80 and 40 % of the stations. Overall, these results indicate significant increases in precipitation and temperature but decreases in river discharge during recent decades. Hence, it can be concluded that decreasing trends in river discharge time series over the northeast of Iran during 1953–2013 are in response to warming temperatures, which increase the rate of evapotranspiration. Differences between the results of our comprehensive large-scale study and those of previous researches confirm the necessity for more model-based local studies on climatic and environmental changes across the northeast of Iran.     

黔桂喀斯特山区年NDVI变化的影响因素研究

喀斯特山区是中国典型的生态脆弱区,区内的植被极易发生退化,且退化后难以恢复。论文采用逐步多元回归、相关性分析和残差分析等方法,探讨了黔桂喀斯特山区气候变化特征及其NDVI变化的影响因素。结果表明：2002—2015年研究区气候变化呈现暖湿化趋势,但变化并不显著,年降水量和年均温变化分别介于-15.6~25.6 mm/a和-0.08~0.06 ℃/a之间,年均增速分别为7.9 mm/a和0.000 35 ℃/a。过去14 a内,气候变化是影响NDVI变化的关键因素(贡献率约95%),其中降水对植被NDVI的影响大于气温。残差分析表明,近14 a来黔桂喀斯特山区NDVI残差和NDVI残差趋势的均值分别为0.03和0.0007/a,说明人类活动的正效应呈上升趋势。城市化的进程使得大量耕地、林地被建设用地占用,在毕节、安顺、贵阳以及河池、柳州、百色一带,人类活动对植被NDVI变化呈较明显的负效应,但是在六盘水、黔西南自治州、遵义和来宾,由于一系列生态还林工程的实施,人类活动则表现为正向影响。     

Remote sensing monitoring on regional crop water productivity in the Haihe River Basin

Crop water productivity （CWP） agricultural development in water scarcity is one of the important indicators for sustainable area. There is serious conflict between water sup- ply and requirement in the Haihe River Basin. CWP of winter wheat and summer maize from 2003 to 2007 in the Haihe River Basin is estimated based on large-scale evapotranspiration （ET） and crop yield obtained by remote sensing technology. Spatial and temporal distribution of CWP of winter wheat and summer maize is investigated in this study. Results show that CWP of winter wheat in most parts of the study area varies from 1.02 kg/m3 to 1.53 kg/m3, and CWP of summer maize varies from 1.31 kg/m3 to 2.03 kg/m3. Multi-year averaged CWP of winter wheat and summer maize in the study area is about 1.19 kg/m3 and 1.59 kg/m3. CWP results show certain promotion potential to alleviate the water shortage in the Haihe River Basin. Correlation analysis of CWP, crop yield and ET shows that there is great potential for crop yield promotion without the growth in irrigation water. Large-scale CWP estimated by remote sensing technology in this study shows spatial distribution features, which could be used to real-time agricultural water resource management combined with crop yield and ET.     

Quantifying the effects of climate change and human activities on runoff in the water source area of Beijing,China

Abstract

Quantitative assessment of the effects of climate change and human activities on runoff is very important for regional sustainable water resources adaptive management. In this study, the non-parametric Mann-Kendall test is used to identify the trends in and change points of the annual runoff with the aim of analysing the changing characteristics of the hydrological cycle. The study presents the analytical derivation of a method which combines six Budyko hypothesis-based water–energy balance equations with the Penman-Monteith equation to separate the effects of climate change and human activities. The method takes several climate variables into consideration. Results based on data from the Yongding River basin, China, show that climate change is estimated to account for 10.5–12.6% of the reduction in annual runoff and human activities contribute to 87.4–89.5% of the runoff decline. The results indicate that human activities are the main driving factors for the reduction in runoff.

Editor Z.W. Kundzewicz; Associate editor C.Y. Xu     

Coupling of a Regional Climate Model with a Crop Development Model and Evaluation of the Coupled Model across China

In this study, the CERES(Crop Estimation through Resource and Environment Synthesis) crop model was coupled with CLM3.5, the land module of the regional climate model RegCM4. The new coupled model was named RegCM4_CERES; and in this model, crop type was further divided into winter wheat, spring wheat, spring maize, summer maize, early rice, late rice,single rice, and other crop types based on each distribution fraction. The development of each crop sub-type was simulated by the corresponding crop model separately, with each planting and harvesting date. A simulation test using RegCM4_CERES was conducted across China from 1999 to 2008; a control test was also performed using the original RegCM4. Data on crop LAI(leaf area index), soil moisture at 10 cm depth, precipitation, and 2 m air temperature were collected to evaluate the performance of RegCM4_CERES. The evaluation provided comparison of single-station time series, regional distributions,seasonal variations, and statistical indices for RegCM4_CERES. The results revealed that the coupled model had an excellent ability to simulate the phonological changes and spatial variations in crops. The consideration of dynamic crop development in RegCM4_CERES corrected the wet bias of the original RegCM4 over North China and the cold bias over South China.However, the degree of improvement was minimal and the statistical indices for RegCM4_CERES were roughly the same as the original RegCM4.     

基于水文模型的蒸散发数据同化研究进展

本文系统综述了基于水文模型的蒸散发数据同化研究,阐述了蒸散发作为非状态变量构建数据同化演算关系的难点和瓶颈,并系统分析了利用当前各种通用水文模型进行蒸散发同化的可行性.基于此,尝试提出了一种易于操作且具有水循环物理机制的蒸散发同化新方案,该方案利用具有蒸散发—土壤湿度非线性时间响应关系的分布式时变增益模型(DTVGM),并进一步完善DTVGM蒸散发机理,构建基于DTVGM水文模型的蒸散发数据同化系统.该新方案将为区域蒸散发精确模拟提供新的思路和借鉴.