青海北川河流域径流变化的机理研究——基于模型和统计两种方法

气候变化和下垫面变化是影响河道径流的两大驱动力,研究两者对径流的影响有利于深入理解流域水文过程,为水资源管理提供科学依据。鉴于利用不同方法获得的结果存在一定程度的差异,有必要使用多种方法进行交叉验证。论文基于Budyko水量平衡法和新增水库模块的分布式水文模型(DHSVM)法量化了气候变化和下垫面变化对青海省北川河流域径流变化的贡献。结果表明：① 自1960年以来流域出口流量以每年0.037 m³/s的趋势下降,突变年份发生在1969年。② 2种方法的分析结果均表明,年代际尺度上,气候变化对径流影响的贡献率由高到低依次为：1990—1999年>2000—2009年>1970—1979年>1980—1989年=2010—2019年,且下垫面变化是1970—2019年流域出口径流变化的主导因素,对应的贡献率分别为94.58% (Budyko法)和65.68% (DHSVM法)。③ Budyko方法只能揭示流域整体的变化,而DHSVM方法能够体现水文过程变化的时空差异,模型结果表明上中游、下游地区的年平均径流变化分别受气候变化、下垫面变化主导;流域出口处月径流变化则对下垫面条件中的水库调节更敏感。此外,文中就2种方法量化结果差异的原因也展开了讨论。     

Characteristics and progress of land use/cover change research during 1990–2018

Journal of Geographical Sciences - Land use/cover change (LUCC) is the foundation and frontier for integrating multiple land surface processes. This paper aims to systematically review LUCC...     

一次华北气旋造成北京特大暴雪天气过程分析

利用北京延庆站和海淀站风廓线产品、微波辐射计产品、北京市雷达产品(南郊和车道沟)、北京市58个称重雨量站观测资料、FY-2E卫星云图、常规气象资料综合分析2012年11月3到4日北京暴雪天气过程。分析表明：降水相态(雨、雪)由华北气旋的锋面性质和锋面位置决定;过程雨雪量由气旋的强度、持续时间和水汽通道维持时间决定;风廓线和微波辐射计产品资料在雨雪开始时间、雨雪相态转换方面有明显的指示性作用。     

利用 Landsat 8影像制作解译样本点辅助高分影像分类可行性的研究

地理国情普查项目使用的高分影像质量的良莠不齐给地表覆盖数据生产带来了巨大障碍。本文剖析了目前收集到的高分影像资料的主要缺陷,如多分辨率、多传感器、多年份和跨季节,给地表覆盖数据解译带来极大的局限性;阐述了Landsat 8影像自身的特点,如像幅面积大、获取周期短、波段信息丰富,同时提出利用Landsat 8影像辅助解译的思路,并通过试验验证这种方法的可行性。     

结合 DEM 的地表覆盖自相关性分析

地表覆盖的空间变化可以反映人类的生存环境,其空间数据的相关性也反映着一些重要信息。在维多利亚州中,耕地一直占着比较大的比重,本文根据landsat TM影像分类得到地表覆盖数据,发现各地表覆盖间类型间的关系,并结合DEM数据研究耕地在维多利亚州的空间分布特点。     

地理国情（市情）普查外业信息采集

地理国情监测不仅扩大了测绘行业的内涵,更重要的是,对我国总体布局和规划提供了可靠的依据。目前,在全国范围内逐步开展地理国情普查工作,我分院按照安排,以厦门市为试点,对其进行了外业的调查与核查工作。结合实地作业情况来看,可以在地理国情普查内容与指标基本不变的前提下,依据地域的不同增加分类或修改部分类别的内涵。为今后全面普查工作的顺利开展,对现有的作业方式和作业内容都应有一定的规范。     

Lake Ladoga ice phenology: Mean condition and extremes during the last 65 years

Winter conditions play an important role for the largest lake in Europe—Lake Ladoga. The ice cover lasts for 171 ± 3 days on average from the early November until the mid‐May. We investigated the ice regime of Lake Ladoga using a constructed ice database of aircraft surveys and satellite images. More than 1250 surveys of the lake's ice cover from 1943 to 2010 were collected and analysed to determine mean and extreme ice conditions for winters of different types of severity. The time series of ice cover percentage over the lake was plotted. On average, 18 observational ice charts were made every winter. Individual ice phenology records show considerable year‐to‐year variation. For this reason, records typically have been combined and analysed as groups (categories). Extremely cold winters were determined as winters with complete ice cover that lasts more than three months which is approximately 90% quartiles from all winters with complete ice cover. The lake surface was completely covered with ice for more than three months during 5 seasons. Extremely warm winters when the maximum ice cover was less than 70% of the lake area occurred during 5 seasons as well. A basic relationship between the winter severity as winter maximum of accumulated freezing degree‐days (AFDD) and the earlier derived Relative Ice Cover Index (RICI) was established. We have used teleconnection indices such as North Atlantic Oscillations (NAO) and Arctic Oscillation (AO) for the period from October to May for estimation of different types of Lake Ladoga's ice conditions. The AO index in winter months and local winter maximum of AFDD explained much of the interannual variation in ice cover. Copyright © 2011 John Wiley & Sons, Ltd.     

A generalized additive model for the spatial distribution of snowpack in the Spanish Pyrenees

A generalized additive model (GAM) was used to model the spatial distribution of snow depth in the central Spanish Pyrenees. Statistically significant non‐linear relationships were found between distinct location and topographical variables and the average depth of the April snowpack at 76 snow poles from 1985 to 2000. The joint effect of the predictor variables explained more than 73% of the variance of the dependent variable. The performance of the model was assessed by applying a number of quantitative approaches to the residuals from a cross‐validation test. The relatively low estimated errors and the possibility of understanding the processes that control snow accumulation, through the response curves of each independent variable, indicate that GAMs may be a useful tool for interpolating local snow depth or other climate parameters. Copyright © 2005 John Wiley & Sons, Ltd.     

Improvement of distributed snowmelt energy balance modeling with MODIS‐based NDSI‐derived fractional snow‐covered area data

Describing the spatial variability of heterogeneous snowpacks at a watershed or mountain‐front scale is important for improvements in large‐scale snowmelt modelling. Snowmelt depletion curves, which relate fractional decreases in snow‐covered area (SCA) against normalized decreases in snow water equivalent (SWE), are a common approach to scale‐up snowmelt models. Unfortunately, the kinds of ground‐based observations that are used to develop depletion curves are expensive to gather and impractical for large areas. We describe an approach incorporating remotely sensed fractional SCA (FSCA) data with coinciding daily snowmelt SWE outputs during ablation to quantify the shape of a depletion curve. We joined melt estimates from the Utah Energy Balance Snow Accumulation and Melt Model (UEB) with FSCA data calculated from a normalized difference snow index snow algorithm using NASA's moderate resolution imaging spectroradiometer (MODIS) visible (0·545–0·565 µm) and shortwave infrared (1·628–1·652 µm) reflectance data. We tested the approach at three 500 m² study sites, one in central Idaho and the other two on the North Slope in the Alaskan arctic. The UEB‐MODIS‐derived depletion curves were evaluated against depletion curves derived from ground‐based snow surveys. Comparisons showed strong agreement between the independent estimates. Copyright © 2010 John Wiley & Sons, Ltd.     

Low‐cost monitoring of snow height and thermal properties with inexpensive temperature sensors

Small, self‐recording temperature sensors were installed at several heights along a metal rod at five locations in a case study catchment. For each sensor, the presence or absence of snow cover was determined on the basis of its insulating effect and the resulting reduction of the diurnal temperature oscillations. Sensor coverage was then converted into a time series of snow height for each location. Additionally, cold content was calculated. Snow height and cold content provide valuable information for spring flood prediction. Good agreement of estimated snow heights with reference measurements was achieved and increased discharge in the study catchment coincided with low cold content of the snow cover. The results of the proposed distributed assessment of snow cover and snow state show great potential for (i) flood warning, (ii) assimilation of snow state data and (iii) modelling snowmelt process. Copyright © 2010 John Wiley & Sons, Ltd.