Assimilating ASAR Data for Estimating Soil Moisture Profile Using an Ensemble Kalman Filter

Active microwave remote sensing data were used to calculate the near-surface soil moisture in the vegetated areas.In this study,Advanced Synthetic Aperture Radar(ASAR)observations of surface soil moisture content were used in a data assimilation framework to improve the estimation of the soil moisture profile at the middle reaches of the Heihe River Basin,Northwest China.A one-dimensional soil moisture assimilation system based on the ensemble Kalman filter(EnKF),the forward radiative transfer model,crop model,and the Distributed Hydrology-Soil-Vegetation Model(DHSVM)was developed.The crop model,as a semi-empirical model,was used to estimate the surface backscattering of vegetated areas.The DHSVM is a distributed hydrology-vegetation model that explicitly represents the effects of topography and vegetation on water fluxes through the landscape.Numerical experiments were conducted to assimilate the ASAR data into the DHSVM and in situ soil moisture at the middle reaches of the Heihe River Basin from June20 to July 15,2008.The results indicated that EnKF is effective for assimilating ASAR observations into the hydrological model.Compared with the simulation and in situ observations,the assimilated results were significantly improved in the surface layer and root layer,and the soil moisture varied slightly in the deep layer.Additionally,EnKF is an efficient approach to handle the strongly nonlinear problem which is practical and effective for soil moisture estimation by assimilation of remote sensing data.Moreover,to improve the assimilation results,further studies on obtaining more reliable forcing data and model parameters and increasing the efficiency and accuracy of the remote sensing observations are needed,also improving estimation accuracy of model operator is important.

3D Geology Modeling from 2D Prospecting Line Profile Map

Using prospecting line profile map in combination with drilling and other information for 3D reconstruction of geological model is an important method of 3D geological modeling.?This paper?discusses the theory and implementation method of 2D prospecting line map into 3D prospecting line map and then into 3D model. The authors propose that it needs twice upgrading dimension to reconstruction 3D geology model from prospecting line profile map. The first upgrading dimension is to convert profile from 2D into 3D profile,?i.e.?the 2D points in the 2D profile map upgrading dimensional transformation to 3D points in a 3D profile. The second upgrading dimension is that transform 0D point 1D curve and 2D polygon feature into 1D curve, 2D surface and 3D solid feature. The paper reexamines contents and forms in prospecting line map from the two different viewpoints of geology and geographic information science. The process of 3D geology modeling from 2D prospecting map is summarized as follows. Firstly, profile is divided into several sections by beginning, end and drill point of the prospecting line. Next, a 3D folded upright profile frame is built by 2D folded prospecting line on the plan map. Then, 2D points of features on 2D profile are converted into 3D points on 3D profile section by section. And then, adding switch control points for the long line crossover two segments. Lastly, 1D curve features are upgraded to 2D surface.

Regional gravity field modeling based on rectangular harmonic analysis

Regional gravity field modeling with high-precision and high-resolution is one of the most important scientific objectives in geodesy, and can provide fundamental information for geophysics, geodynamics, seismology, and mineral exploration. Rectangular harmonic analysis （RHA） is proposed for regional gravity field modeling in this paper. By solving the Laplace＇s equation of gravitational potential in local Cartesian coordinate system, the rectangular harmonic expansions of disturbing potential, gravity anomaly, gravity disturbance, geoid undulation and deflection of the vertical are derived, and so are the formula for signal degree variance and error degree variance of the rectangular harmonic coefficients （RHC）. We also present the mathematical model and detailed algorithm for the solution of RHC using RHA from gravity observations. In order to reduce the edge effects caused by periodic continuation in RHA, we propose the strategy of extending the size of computation domain. The RHA-based modeling method is validated by conducting numerical experiments based on simulated ground and airborne gravity data that are generated from geopotential model EGM2008 and contaminated by Gauss white noise with standard deviation of 2 mGal. The accuracy of the 2.5＇×2.5＇ geoid undulations computed from ground and airborne gravity data is 1 and 1.4 cm, respectively. The standard error of the gravity disturbances that downward continued from the flight height of 4 km to the geoid is only 3.1 reGal. Numerical results confirm that RHA is able to provide a reliable and accurate regional gravity field model, which may be a new option for the representation of the fine structure of regional gravity field.