Estimation of potential evapotranspiration over the Yellow River basin: reference crop evaporation or Shuttleworth–Wallace?

Potential evapotranspiration (PET) is a key input to hydrological models. Its estimation has often been via the Penman–Monteith (P–M) equation, most recently in the form of an estimate of reference evapotranspiration (RET) as recommended by FAO‐56. In this paper the Shuttleworth–Wallace (S–W) model is implemented to estimate PET directly in a form that recognizes vegetation diversity and temporal change without reference to experimental measurements and without calibration. The threshold values of vegetation parameters are drawn from the literature based on the International Geosphere–Biosphere Programme land cover classification. The spatial and temporal variation of the LAI of vegetation is derived from the composite NOAA‐AVHRR normalized difference vegetation index (NDVI) using a method based on the SiB2 model, and the Climate Research Unit database is used to provide the required meteorological data. All these data inputs are publicly and globally available. Consequently, the implementation of the S–W model developed in this study is applicable at the global scale, an essential requirement if it is to be applied in data‐poor or ungauged large basins. A comparison is made between the FAO‐56 method and the S–W model when applied to the Yellow River basin for the whole of the last century. The resulting estimates of RET and PET and their association with vegetation types and leaf area index (LAI) are examined over the whole basin both annual and monthly and at six specific points. The effect of NDVI on the PET estimate is further evaluated by replacing the monthly NDVI product with the 10‐day product. Multiple regression relationships between monthly PET, RET, LAI, and climatic variables are explored for categories of vegetation types. The estimated RET is a good climatic index that adequately reflects the temporal change and spatial distribution of climate over the basin, but the PET estimated using the S–W model not only reflects the changes in climate, but also the vegetation distribution and the development of vegetation in response to climate. Although good statistical relationships can be established between PET, RET and/or climatic variables, applying these relationships likely will result in large errors because of the strong non‐linearity and scatter between the PET and the LAI of vegetation. It is concluded that use of the implementation of the S–W model described in this study results in a physically sound estimate of PET that accounts for changing land surface conditions. Copyright © 2006 John Wiley & Sons, Ltd.     

Influence of Land Use/Cover Change on Storm Runoff— A Case Study of Xitiaoxi River Basin in Upstream of Taihu Lake Watershed

Land use/cover change (LUCC) is one of the main boundary conditions which influence many hydrologic processes. In view of the importance of Taihu Lake Watershed in China and the urgency of discovering the impacts of LUCC on storm runoff, two flood events under five land cover scenarios in the Xitiaoxi River Basin of the upstream of Taihu Lake watershed were simulated by distributed hydrologic modeling system HEC-HMS. The influences of each land cover on storm runoff were discussed. It was concluded that under the same rainstorm the ascending order of runoff coefficient and peak flow produced by the 5 different land covers were woodland, shrub, grassland, arable land, and built-up land; the descending order of swelling time were woodland, shrub, grassland, arable land, and built-up land. Scenario of built-up land was the first to reach peak flow, then arable land, grassland, shrub, and woodland. There were close relationships between the runoff coefficients produced by the 5 different land covers. The degrees of impacts on runoff coefficient of land cover change modes were sorted by descending: woodland to built-up land, shrub to built-up land, grassland to built-up land, arable land to built-up land, woodland to arable land, shrub to arable land, arable land to grassland, shrub to grassland, grassland to arable land, and woodland to shrub. Urbanization will contribute to flood disaster, while forestation will mitigate flood disaster.     

EVIDENCE FOR ABRUPT CLIMATIC CHANGES ONNORTHWESTERN MARGIN OF EAST ASIAN MONSOON REGION DURING LAST DEGLACIATION

Based on investigations of the Zhongwei Nanshan aeolian section situated in the southeastern margin of Tengger Dcsert, carbon-14 and TL (thermoluminescence) dating results and paleoclimatic proxies such as magnetic susceptibility and grain size, we inferred that the northwestern margin of East Asian monsoon region experienced abrupt climatic changes during the last deglaciation. Six oscillation events were identified: Oldest Dryas, Belling, Older Dryas, AllerФd, lntra-AllerФd Cold Period (1ACP) and Younger Dryas (YD). The summer monsoon was weaker during Oldest Dryas and Younger Dryas when the winter monsoon was stronger. However, during the B/A (BФlling/AllerФd) period, the summer monsoon strengthened, reflected by magnetic susceptibility, when the winter monsoon also became strong, which is different from the paleoclimatic pattern established in the East Asian monsoon region. Furthermore,the summer monsoon was nearly in phase with the climate changes inferred from the oxygen isotopic records of Greenland ice cores. It could be speculated that the variations of the sea ice cover in the high latitudes of the North Hemisphere affected the high pressure of Asian continent and the changes of the winter monsoon inland. On the other hand,the sea ice cover variations might have indirectly caused the occurrence of ENSO events that has tightly been related to the summer monsoon in northwest margin of East Asian monsoon region.     

基于HJ-1A高光谱的黄河口碱蓬和柽柳盖度反演模型研究

碱蓬和柽柳是黄河口湿地典型的盐生植物类型,是多种保护珍禽的主要栖息地,具有景观尺度较小、分布广且多混生的特点。应用覆盖黄河口北部潮滩的HJ-1A高光谱遥感影像,基于现场测量的端元光谱和从遥感影像中使用顺序最大角凸锥法(SAMCC)自动提取的端元光谱,应用线性光谱分解法(LSU)、正交子空间投影法(OSP)、匹配滤波法(MF)、最小能量约束法(CEM)和自适应一致估计法(ACE)5种不同光谱解混方法进行混合像元光谱解混,对比两种方法得到的端元光谱分别对碱蓬和柽柳盖度的反演能力,并给出相应的反演模型。结果显示:(1)现场测量端元光谱取得了较好的碱蓬和柽柳盖度反演结果,其中应用LSU方法的光谱解混结果与现场测量盖度的决定系数对于碱蓬和柽柳分别达到了0.88和0.95;(2)两种端元获取方式的光谱解混结果中,LSU和OSP方法均获得了较高的相关性,ACE解混方法的相关性都最低;(3)SAMCC方法提取端元光谱对柽柳的分解结果与现场测量盖度的相关性远高于碱蓬。     

基于GEE的地表覆盖与气候状态关联研究

为探究地表覆盖与气候状态间的关联性,本文选取2019年的Landsat影像数据,结合温度、降水量、PM_2.5浓度3种气候指标,利用GEE平台,结合NDVI、MNDWI、NDBI,采用SVM、RF、CART方法进行地表覆盖分类,探究气候指标与地表覆盖类型分布的关联性;提出了使用3种气候指标构建分类特征进行地表覆盖分类的方法,并通过消融试验分析了气候指标对地表覆盖分类精度的影响。结果表明:①RF有较好的分类结果,总体精度为96.0%;②3种气候指标均能提高地表覆盖分类精度,其中PM_2.5浓度效果最好;③温度与植被、水体关联性较大,PM_2.5浓度与城区、植被关联性较大,降水量与耕地关联性较大。     

大光斑波形数据在土地覆盖分类的适用性分析

针对GLAS地学激光测高系统是冰、云和陆地高程卫星(ICESat)的唯一监测工具,能够记录地表光斑内的地物信息,是否能应用于黄土高原土地覆盖分类的问题进行了研究。利用粒子群和最小二乘法相结合的方法对GLAS波形数据进行高斯分解,获取高斯波个数、波形总能量、波形信号起始和信号结束位置4个波形参数;基于波形自动分类方法对黄土高原水体、森林、城市用地、其他地类(裸地、低矮植被等)进行分类。通过基于覆盖相同研究区域的30 m地表覆盖数据(Globe Land30),验证分类的准确性。结果表明,GLAS大光斑波形数据对黄土高原的4种地类能够很好地进行区分,总分类精度高达87.68%,Kappa系数为65.79%。研究表明,GLAS波形数据可以作为获取土地覆盖信息的有效数据源,为研究黄土高原土地覆盖变化提供更丰富的数据支持。     

刍议《重庆历史地图集》第二卷的编制

以《重庆历史地图集》第二卷编制的具体情况为例,对图集的开本设计、内容结构设计、封面和版式设计、整体设计、创新源,以及图集编制取得的经验进行了论述,为以后类似图集的编制提供参考。     

伴随对流层中低层气温持续下降的雪转雨过程分析

利用欧洲中期天气预报中心（ECMWF）0.25°×0.25°分辨率细网格模式产品、探空观测资料和风廓线雷达等资料,对2014年2月18日浙江嘉兴雨雪天气过程中降水相态先由雨转雪、再由雪转雨的变化条件进行了分析,并对ECMWF细网格模式产品进行了预报性能检验,结果表明：模式形势预报准确,但未能预报出雪转雨过程。在对流层中低层气温持续降低的情况下,水汽凝结高度不同是造成两次相态转换的主要原因。上午垂直运动加强,水汽充沛,降水粒子的凝结高度高,足以形成大的雪花,在较低的零度层高度以下降落时不至于融化;下午垂直运动减弱,水汽集中在低层,尽管这一高度层的气温在-3～-2 ℃,但是不足以凝结成固态降水,同时地面气温受海上暖平流影响而回升,因此降水相态由雪转雨。     

1971-2010年河南省霜期的时空分布及其对气温的响应

利用1971-2010年河南省均匀分布的110个地面气象站霜的观测资料,采用线性倾向率和单相关分析法,对近40 a河南省初霜期、终霜期和无霜期的时空分布特征及其对气温的响应进行研究,利用M-K法分析霜期的突变特征。结果表明：1971-2010年河南省平均无霜期为221.3 d,纬度与初霜期（R=-0.806）和无霜期（R=-0.707）均呈显著负相关,与终霜期（R=0.557）呈显著正相关;初霜期以2.6 d/10 a的速率呈明显推迟（p<0.01）,而终霜期的线性变化趋势不明显,无霜期以4.7 d/10 a的速率呈明显延长（p<0.01）;初霜期、终霜期和无霜期的突变点均在1998年。从各地区看,初霜期在各地区呈明显推迟,豫西地区推迟趋势最大（3.5 d/10 a,p<0.01）;终霜期仅在豫西和豫南地区呈显著提前;除豫东地区外,无霜期在其余5个地区均呈明显延长,豫西地区延长趋势最大（7.7 d/10 a,p<0.01）。从各观测站霜期的变化趋势空间分布来看,初霜期显著推后、终霜期显著提前和无霜期明显延长的站点分布在豫西和豫南地区。河南省初霜期与10月、终霜期与3月气温因子相关性较强;初霜期推迟和终霜期提前主要由气温升高引起的,其中平均最低气温是最重要的影响因素。初霜期推迟和终霜期提前导致无霜期延长。     

Interannual Climate Variability of the Past Millennium from Simulations

The interannual variability of global temperature and precipitation during the last millennium is analyzed using the results of ten coupled climate models participating in the Paleoclimate Modelling Intercomparison Project Phase 3. It is found that large temperature(precipitation) variability is most dominant at high latitudes(tropical monsoon regions), and the seasonal magnitudes are greater than the annual mean. Significant multi-decadal-scale changes exist throughout the whole period for the zonal mean of both temperature and precipitation variability, while their long-term trends are indistinctive. The volcanic forcings correlate well with the temperature variability at midlatitudes, indicating possible leading drivers for the interannual time scale climate change.