Selecting the appropriate hydraulic model structure using low-resolution satellite imagery

This study aims at investigating the value added by an explicit representation of floodplain processes in hydraulic models, by comparing the results of a pure 1D model to the ones of an integrated 1D-2D model. The analysis is performed on a 96 km reach of the River Po (Italy). For this test site, two different model structures (1D and 1D-2D) are implemented and compared. The models are first calibrated using high water marks of a high magnitude event and then validated by means of a coarse resolution space-borne flood extent map of a low-magnitude event. The explicit inclusion of 2D features strongly improves the performance of the model, both in terms of accuracy and robustness. The possible causes of this behaviour are investigated and some statements are drawn based on the analysis of the features of the two flood events. Some general conclusions on the effect of the choice between 1D and 2D models arise from the analysis of the calibration-validation procedure. In this context a new measure of fit is proposed, to be used if binary (wet/dry) observations are available and is proven to be able to better distinguish among different sets of model parameters. Lastly, the study also shows the ability of timely low resolution satellite imagery to assist the selection of the most appropriate hydraulic model structure.     

Secular perturbations of fictitious satellites of uranus

Secular perturbations of fictitious satellites that are initially circular and in the equatorial plane of Uranus are discussed. Satellites located in the region where the solar perturbation is dominant become highly eccentric and inclined with respect to the equator, and have a possibility to collide with Uranus. Satellites located in the region where the oblateness perturbation is dominant keep the original eccentricity and the inclination. A scenario of a possible extinction of outer satellites of Uranus is also discussed.     

Ocean wind fields retrieved from the advanced synthetic aperture radar aboard ENVISAT

In this paper an algorithm is presented which enables high-resolution ocean surface wind fields to be retrieved from the advanced synthetic aperture radar (ASAR) data acquired by the European remote sensing satellite ENVISAT. Wind directions are extracted from wind-induced streaks that are visible in ASAR images at scales above 200 m and that are approximately in line with the mean surface wind direction. Wind speeds are derived from the normalized radar cross section (NRCS) and image geometry of the calibrated ASAR images, together with the local ASAR-retrieved wind direction. Therefore the empirical C-band model CMOD4, which describes the dependency of the NRCS on wind and image geometry, is used. CMOD4 is a semi-empirical model, which was originally developed for the scatterometer of the European remote sensing satellites ERS-1 and 2 operating at C-band with vertical polarization. Consequently, CMOD4 requires modification when applied to ASAR images that were acquired with horizontal polarization in transmitting and receiving. This is performed by considering the polarization ratio of the NRCS. To demonstrate the applicability of the algorithm, wind fields were computed from several ENVISAT ASAR images of the North Sea and compared to atmospheric model results of the German weather service.Acknowledgements The authors were supported by the German Bundesministerium für Bildung und Forschung (BMBF) in the framework of the project. A new perspective of the Ocean ENVISAT Oceanography (ENVOC). The ENVISAT ASAR data were kindly made available by the European Space Agency in the framework of the ENVISAT Project AO-ID 220, Biological and geophysical parameters from synthetic aperture radar over the ocean (BIGPASO).     

Monitoring the water balance of Lake Victoria, East Africa, from space

Using satellite gravimetric and altimetric data, we examine trends in water storage and lake levels of multiple lakes in the Great Rift Valley region of East Africa for the years 2003–2008. GRACE total water storage estimates reveal that water storage declined in much of East Africa, by as much as , while altimetric data show that lake levels in some large lakes dropped by as much as 1–2 m. The largest declines occurred in Lake Victoria, the Earth’s second largest freshwater body. Because the discharge from the outlet of Lake Victoria is used to generate hydroelectric power, the role of human management in the lake’s decline has been questioned. By comparing catchment water storage trends to lake level trends, we confirm that climatic forcing explains only about 50decline. This analysis provides an independent means of assessing the relative impacts of climate and human management on the water balance of Lake Victoria that does not depend on observations of dam discharge, which may not be publically available. In the second part of the study, the individual components of the lake water balance are estimated. Satellite estimates of changes in lake level, precipitation, and evaporation are used with observed lake discharge to develop a parameterization for estimating subsurface inflows due to changes in groundwater storage estimated from satellite gravimetry. At seasonal timescales, this approach provides closure to Lake Victoria’s water balance to within . The third part of this study uses the water balance of a downstream water body, Lake Kyoga, to estimate the outflow from Lake Victoria remotely. Because Lake Kyoga is roughly 20 times smaller in area than Lake Victoria, its water balance is strongly influenced by inflow from Lake Victoria. Lake Kyoga has been shown to act as a linear reservoir, where its outflow is proportional to the height of the lake. This model can be used with satellite altimetric lake levels to estimate a time series of Lake Victoria discharge with an rms error of about .     

广东数字遥测地震台网运行维护管理的探索

介绍广东数字遥测地震台网自投入正式观测运行以来,在进行台网系统运行维护、台网规范管理和开展地震科研工作等方面所做的一些探索和取得的一些经验。     

Flood and landslide applications of near real-time satellite rainfall products

Floods and associated landslides account for the largest number of natural disasters and affect more people than any other type of natural disaster. With the availability of satellite rainfall analyses at fine time and space resolution, it has also become possible to mitigate such hazards on a near-global basis. In this article, a framework to detect floods and landslides related to heavy rain events in near-real-time is proposed. Key components of the framework are: a fine resolution precipitation acquisition system; a comprehensive land surface database; a hydrological modeling component; and landslide and debris flow model components. A key precipitation input dataset for the integrated applications is the NASA TRMM-based multi-satellite precipitation estimates. This dataset provides near real-time precipitation at a spatial-temporal resolution of 3 h and 0.25° × 0.25°. In combination with global land surface datasets it is now possible to expand regional hazard modeling components into a global identification/monitoring system for flood/landslide disaster preparedness and mitigation.     

Spatio-temporal modeling of PM2.5 concentrations with missing data problem: a case study in Beijing,China

ABSTRACT

One of the major challenges in conducting epidemiological studies of air pollution and health is the difficulty of estimating the degree of exposure accurately. Fine particulate matter (PM_2.5) concentrations vary in space and time, which are difficult to estimate in rural, suburban and smaller urban areas due to the sparsity of the ground monitoring network. Satellite retrieved aerosol optical depth (AOD) has been increasingly used as a proxy of ground PM_2.5 observations, although it suffers from non-trivial missing data problems. To address these issues, we developed a multi-stage statistical model in which daily PM_2.5 concentrations can be obtained with complete spatial coverage. The model consists of three stages – an inverse probability weighting scheme to correct non-random missing patterns of AOD values, a spatio-temporal linear mixed effect model to account for the spatially and temporally varying PM_2.5-AOD relationships, and a gap-filling model based on the integrated nested Laplace approximation-stochastic partial differential equations (INLA-SPDE). Good model performance was achieved from out-of-sample validation as shown in R² of 0.93 and root mean square error of 9.64 μg/m³. The results indicated that the multi-stage PM_2.5 prediction model proposed in the present study yielded highly accurate predictions, while gaining computational efficiency from the INLA-SPDE.     

建立省域C级GPS控制网与大地水准面精化

地质、矿产、交通、国土、测绘等众多行业都与空间数据密切相关.空间数据基准框架决定了空间数据的准确性、统一性和实用性.本文从国内外发展现状出发,简述了我国目前大地坐标框架存在的问题,论述了建立省域C级GPS网并精化似大地水准面的作用和意义,并提出了建立省域C级GPS网并精化似大地水准面的技术方案和相关问题.     

卫星大地测量用于东亚大陆地球动力学与地震学研究回顾

王仁先生是中国地球动力学研究的开创者,他所引领的有关潮汐和板块运动造成的地壳应力场演化研究使得有关活动构造、断层形变和地震危险性的研究从定性走向定量,并在过去半个世纪中不断丰富发展.卫星大地测量方法从20世纪80年代开始用于精密定位和运动测量,为地球动力学和地震学研究提供了不可缺少的观测资料,极大促进了相关学科的发展.本文结合本人研究经历回顾卫星大地测量方法用于东亚大陆地球动力学、地震构造学和地震物理过程研究带来的一些重要发现,作为对王仁先生在相关领域开创性贡献的纪念.

     

赣南遥测数字地震台网监测能力估算

估算台网监测能力的方法有多种,本文采用目前最常用的根据近震震级公式,通过确定振幅比,用量规函数反推单台控制距离的方法。依据4台以上定位原则,确定各台控制距离相交部分为数字遥测地震台网给定震级下限的监测范围。并绘制出赣南数字遥测地震台网的监测能力图,为江西省地震速报范围为速报震级的确定提供了理论依据。