Imaging Land Subsidence Induced by Groundwater Extraction in Beijing (China) Using Satellite Radar Interferometry

Beijing is one of the most water-stressed cities in the world. Due to over-exploitation of groundwater, the Beijing region has been suffering from land subsidence since 1935. In this study, the Small Baseline InSAR technique has been employed to process Envisat ASAR images acquired between 2003 and 2010 and TerraSAR-X stripmap images collected from 2010 to 2011 to investigate land subsidence in the Beijing region. The maximum subsidence is seen in the eastern part of Beijing with a rate greater than 100 mm/year. Comparisons between InSAR and GPS derived subsidence rates show an RMS difference of 2.94 mm/year with a mean of 2.41 ± 1.84 mm/year. In addition, a high correlation was observed between InSAR subsidence rate maps derived from two different datasets (i.e., Envisat and TerraSAR-X). These demonstrate once again that InSAR is a powerful tool for monitoring land subsidence. InSAR derived subsidence rate maps have allowed for a comprehensive spatio-temporal analysis to identify the main triggering factors of land subsidence. Some interesting relationships in terms of land subsidence were found with groundwater level, active faults, accumulated soft soil thickness and different aquifer types. Furthermore, a relationship with the distances to pumping wells was also recognized in this work.

Central Asia on New Delhi's Geostrategic Radar. EUCAM Commentary No. 18, October 2011

Central Asia today holds much strategic interest for India as an emerging 21st Century regional and global power. Despite being a latecomer in what some see as a new ‘Great Game’, New Delhi is keen to reconstruct the ‘Silk Route’. While Indo-Central Asian relations go back to antiquity when cultural, commercial and political ties thrived, post-independence India was physically cut off from Afghanistan and West Asia. It remained embroiled in domestic preoccupations and the insurgency in Jammu and Kashmir, all of which led to a limited foreign policy until the early nineties and a belated rediscovery of the region.

A daily rainfall erosivity model for Western Amazonia

Rainfall erosivities as defined by the R factor from the universal soil loss equation were determined for all events during a two-year period at the station La Cuenca in western Amazonia. Three methods based on a power relationship between rainfall amount and erosivity were then applied to estimate event and daily rainfall erosivities from the respective rainfall amounts. A test of the resulting regression equations against an independent data set proved all three methods equally adequate in predicting rainfall erosivity from daily rainfall amount. We recommend the Richardson model for testing in the Amazon Basin, and its use with the coefficient from La Cuenca in western Amazonia.

Simulation of nutrient loss from soils due to rainfall acidity /

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Mode of access: Internet.