Xiufeng He

Monitoring Groundwater Variations from Satellite Gravimetry and Hydrological Models: A Comparison with in-situ Measurements in the Mid-Atlantic Region of the United States

Aimed at mapping time variations in the Earth’s gravity field, the Gravity Recovery and Climate Experiment (GRACE) satellite mission is applicable to access terrestrial water storage (TWS), which mainly includes groundwater, soil moisture (SM), and snow. In this study, SM and accumulated snow water equivalent (SWE) are simulated by the Global Land Data Assimilation System (GLDAS) land surface models (LSMs) and then used to isolate groundwater anomalies from GRACE-derived TWS in Pennsylvania and New York States of the Mid-Atlantic region of the United States. The monitoring well water-level records from the U.S. Geological Survey Ground-Water Climate Response Network from January 2005 to December 2011 are used for validation. The groundwater results from different combinations of GRACE products (from three institutions, CSR, GFZ and JPL) and GLDAS LSMs (CLM, NOAH and VIC) are compared and evaluated with in-situ measurements. The intercomparison analysis shows that the solution obtained through removing averaged simulated SM and SWE of the three LSMs from the averaged GRACE-derived TWS of the three centers would be the most robust to reduce the noises, and increase the confidence consequently. Although discrepancy exists, the GRACE-GLDAS estimated groundwater variations generally agree with in-situ observations. For monthly scales, their correlation coefficient reaches 0.70 at 95% confidence level with the RMSE of the differences of 2.6 cm. Two-tailed Mann-Kendall trend test results show that there is no significant groundwater gain or loss in this region over the study period. The GRACE time-variable field solutions and GLDAS simulations provide precise and reliable data sets in illustrating the regional groundwater storage variations, and the application will be meaningful and invaluable when applied to the data-poor regions.

Estimating Total Discharge in the Yangtze River Basin Using Satellite-Based Observations

The measurement of total basin discharge along coastal regions is necessary for understanding the hydrological and oceanographic issues related to the water and energy cycles. However, only the observed streamflow (gauge-based observation) is used to estimate the total fluxes from the river basin to the ocean, neglecting the portion of discharge that infiltrates to underground and directly discharges into the ocean. Hence, the aim of this study is to assess the total discharge of the Yangtze River (Chang Jiang) basin. In this study, we explore the potential response of total discharge to changes in precipitation (from the Tropical Rainfall Measuring Mission—TRMM), evaporation (from four versions of the Global Land Data Assimilation—GLDAS, namely, CLM, Mosaic, Noah and VIC), and water-storage changes (from the Gravity Recovery and Climate Experiment—GRACE) by using the terrestrial water budget method. This method has been validated by comparison with the observed streamflow, and shows an agreement with a root mean square error (RMSE) of 14.30 mm/month for GRACE-based discharge and 20.98 mm/month for that derived from precipitation minus evaporation (P − E). This improvement of approximately 32% indicates that monthly terrestrial water-storage changes, as estimated by GRACE, cannot be considered negligible over Yangtze basin. The results for the proposed method are more accurate than the results previously reported in the literature.

The Influence of Polarimetric Parameters and an Object-Based Approach on Land Cover Classification in Coastal Wetlands

The purpose of this study was to examine how different polarimetric parameters and an object-based approach influence the classification results of various land use/land cover types using fully polarimetric ALOS PALSAR data over coastal wetlands in Yancheng, China. To verify the efficiency of the proposed method, five other classifications (the Wishart supervised classification, the proposed method without polarimetric parameters, the proposed method without an object-based analysis, the proposed method without textural and geometric information and the proposed method using the nearest-neighbor classifier) were applied for comparison. The results indicated that some polarimetric parameters, such as Shannon entropy, Krogager_Kd, Alpha, HAAlpha_T11, VanZyl3_Vol, Derd, Barnes2_T33, polarization fraction, Barnes1_T33, Neuman_delta_mod and entropy, greatly improved the classification results. The shape index was a useful feature in distinguishing fish ponds and rivers. The distance to the sea can be regarded as an important factor in reducing the confusion between herbaceous wetland vegetation and grasslands. Furthermore, the decision tree algorithm increased the overall accuracy by 6.8% compared with the nearest neighbor classifier. This research demonstrated that different polarimetric parameters and the object-based approach significantly improved the performance of land cover classification in coastal wetlands using ALOS PALSAR data.

Calibration and Evaluation of Precipitable Water Vapor From MODIS Infrared Observations at Night

Water vapor is one of the most variable atmospheric constituents. Knowledge of both the spatial and temporal variations of atmospheric water vapor is very important in forecasting regional weather and understanding the global climate system. The Moderate Resolution Imaging Spectroradiometer (MODIS) is the first space instrument to obtain precipitable water vapor (PWV) with near-infrared (nIR) bands and the traditional IR bands, which provides an opportunity to monitor PWV with wide coverage during both daytime and nighttime. However, the accuracy of PWV measurements obtained with IR bands is much lower than that with nIR bands. Moreover, seldom have studies been devoted to the calibrations of MODIS IR PWV. In this paper, the accuracy of MODIS IR water vapor product during the nighttime is assessed by ERA-Interim data, Global Positioning System, and radiosonde observations. Results reveal that the performance of MODIS IR water vapor product is much poorer than that from the other observations, and the MODIS IR PWV needs to be calibrated. As such, we propose a differential linear calibration model (DLCM) to calibrate the MODIS IR water vapor product during the nighttime. Case studies under both dry and moist atmosphere in midlatitude and equatorial regions are used to test and assess the performance of the DLCM. Results show that the DLCM can effectively enhance the accuracy of MODIS IR retrievals at nighttime. Furthermore, while the traditional least square model may over calibrate the MODIS IR PWV measurements occasionally, the DLCM can avoid that defect successfully.

Assessment of InSAR Atmospheric Correction Using Both MODIS Near-Infrared and Infrared Water Vapor Products

Water vapor variations affect the interferometric synthetic aperture radar (InSAR) signal transmission and the accuracy of the InSAR measurements. The Moderate Resolution Imaging Spectroradiometer (MODIS) near infrared (nIR) water vapor product can correct InSAR atmospheric effects effectively, but it only works for the synthetic aperture radar (SAR) images acquired during the daytime. Although the MODIS infrared (IR) water vapor product owns poorer accuracy and spatial resolution than the nIR product, it is available for daytime as well as nighttime. In order to improve the accuracy of water vapor measurements from the MODIS IR product, a differential linear calibration model (DLCM) has been developed in this paper. The calibrated water vapor measurements from the IR product are then used for wet delay map production and nighttime overpass SAR interferogram atmospheric correction. Results show that the accuracy of the MODIS IR product can be improved effectively after calibration with the DLCM, and the derived wet delays are more suitable for InSAR atmospheric correction than original measurements from the IR product. Furthermore, a MODIS altitude-correlated turbulence model (MATM) is incorporated to correct the atmospheric effects from another descending ASAR interferogram. Results show that the MATM can reduce altitude-dependent water vapor artifacts more effectively than the traditional correction method without the need to incorporate the altitude information.

GPS and InSAR Time Series Analysis: Deformation Monitoring Application in a Hydraulic Engineering Resettlement Zone, Southwest China

Booming development of hydropower in China has resulted in increasing concerns about the related resettlement issues. Both global positioning system (GPS) and persistent scatterer interferometric synthetic aperture radar (InSAR) time series analysis are applied to measuring the magnitude and monitoring the spatial and temporal variations of land surface displacement in Hanyuan, a hydraulic engineering resettlement zone, southwest China. The results from the GPS monitoring system established in Hanyuan match well the digital inclinometer results, suggesting that the GPS monitoring system can be employed as a complement to the traditional ground movement monitoring methods. The InSAR time series witness various patterns and magnitudes of deformation in the resettlement zone. Combining the two complementary techniques will overcome the limitations of the single method.

Ocean Wave Separation Using CEEMD-Wavelet in GPS Wave Measurement

Monitoring ocean waves plays a crucial role in, for example, coastal environmental and protection studies. Traditional methods for measuring ocean waves are based on ultrasonic sensors and accelerometers. However, the Global Positioning System (GPS) has been introduced recently and has the advantage of being smaller, less expensive, and not requiring calibration in comparison with the traditional methods. Therefore, for accurately measuring ocean waves using GPS, further research on the separation of the wave signals from the vertical GPS-mounted carrier displacements is still necessary. In order to contribute to this topic, we present a novel method that combines complementary ensemble empirical mode decomposition (CEEMD) with a wavelet threshold denoising model (i.e., CEEMD-Wavelet). This method seeks to extract wave signals with less residual noise and without losing useful information. Compared with the wave parameters derived from the moving average skill, high pass filter and wave gauge, the results show that the accuracy of the wave parameters for the proposed method was improved with errors of about 2 cm and 0.2 s for mean wave height and mean period, respectively, verifying the validity of the proposed method.

Acquiring Three-Dimensional Deformation of Kilauea's South Flank From GPS and DInSAR Integration Based on the Ant Colony Optimization

To acquire a 3-D deformation of Kilaueas south flank, measurements from GPS and differential interferometric synthetic aperture radar (DInSAR) were integrated based on ant colony optimization. Constraints from GPS and DInSAR measurements were used to establish an energy function based on the Gibbs equation. In this letter, projection vectors used in the energy function were refined depending on the elevation and location of each ground pixel. To achieve stable and fast convergence of the algorithm, the proposed method was tested with different parameters. An ant colony size of 80 with 20 generation loops was designed to derive the 3-D deformation by solving the energy function. Both the ascending and descending interferometric pairs, as well as the GPS observations, of Kilauea volcano, Hawaii, were used in this letter. The results show good consistency with the GPS checkpoints. Root mean squares of 1.40, 1.88, and 2.2 cm were achieved in the directions of north-south, east-west, and zenith, respectively. The derived 3-D deformation maps will allow a better understanding of the source geometry associated with volcanic and seismic activities that result in surface deformation.

The performance of bds relative positioning usage with real observation data

With the first phase of COMPASS/BeiDou-2 (BDS) completed, the assessment of positioning performance and the characterization of its system are analyzed and presented. Pseudo-range and carrier phase measurements modulated on B1 and B2 have been collected in Shanghai, from 00:00 to 24:00 on 28 December, 2012. Compared with GPS, visibility and measurement quality of BDS’s GEO, IGSO and MEO satellites are analyzed. DOP during the whole orbital period is also analyzed the results demonstrate that BDS’s HDOP is better than GPS’s one, but VDOP opposite. Furthermore, the result of positioning is also presented and analyzed. Short baselines are estimated by standalone BDS and GPS’s carrier phase measurement, respectively, using 48 segmentations of observations during a whole day (24 hours, each segmentation, is about 30 minutes observation). The analysis of static relative positioning demonstrates that BDS could achieve to millimeter level, corresponding to GPS. Kinematic result is produced by double differenced carrier phase observations with the ambiguities fixed under the constraint of precise short baseline.The result shows that the centimeter accuracy could be achieved. When comparing the results of kinematic baseline solutions, performance of BDS is worse than GPS on North and Up components, but oppositely on the component of East in the kinematic baseline processing.

Remote sensing of atmospheric water vapor from synthetic aperture radar interferometry: case studies in Shanghai, China

Abstract. The estimation of atmospheric water vapor with high resolution is important for operational weather forecasting, climate monitoring, atmospheric research, and numerous other applications. The 40  m×40  m and 30  m×30  m differential precipitable water vapor (ΔPWV) maps are generated with C- and L-band synthetic aperture radar interferometry (InSAR) images over Shanghai, China, respectively. The ΔPWV maps are accessed via comparisons with the spatiotemporally synchronized PWV measurements from the European Centre for Medium-Range Weather Forecasts Interim reanalysis at the finest resolution and global positioning system observations, respectively. Results reveal that the ΔPWV maps can be estimated from both C- and L-band InSAR images with an accuracy of better than 2.0 mm, which, therefore, demonstrates the ability of InSAR observations at both C- and L-band to detect the water vapor distribution with high spatial resolution.