Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.     

衍射地震CT技术的数值研究

本文首先解决了声波方程的非Born近似的正演计算问题,从而获得理论上不带近似的正演数据;然后,推导了井间（CBP）、垂直地震剖面（VSP）和地面反射（SRP）三种不同的数据采集方式下的衍射CT的重建公式;利用这些重建算法和正演数据,系统地研究了影响到地球物理CT成象质量的三种因素,即:（1）数据采集方式,（2）异常程度和（3）成象区域的尺寸,对重建图象的影响;并比较了衍射地震CT和射线地震CT的成象质量。