GOCE: The Earth Gravity Field by Space Gradiometry

An artificial satellite, flying in a purely gravitational field is a natural probe, such that, by a very accurate orbit determination, would allow a perfect estimation of the field. A true satellite experiences a number of perturbational, non-gravitational forces acting on the shell of the spacecraft; these can be revealed and accurately measured by a spaceborne accelerometer. If more accelerometers are flown in the same satellite, they naturally eliminate (to some extent) the common perturbational accelerations and their differences are affected by the second derivatives of the gravity fields only (gradiometry). The mission GOCE is based on this principle. Its peculiar dynamical observation equations are reviewed. The possibility of estimating the gravity field up to some harmonic degree (200) is illustrated.     

Signal and noise in S.L.R. data

The problem of judging on model deficiency in S.L.R. data treatment is considered. In particular the correlation analysis of residuals of adjusted orbits is used to show the presence of unmodelled signals. This analysis seems suitable at least for a proper preprocessing of S.L.R. data, in the sense of being an efficient procedure of outliers rejection.     

Evaluating water table response to rainfall events in a shallow aquifer and canal system

Shallow aquifers typically have greater hydrologic connectivity and response to recharge and changes in surface water management practices than deeper aquifers and are therefore often managed to reduce the risk of flooding. Quantification of the water table elevation response under different management scenarios provides valuable information in shallow aquifer systems to assess indirect influences of such modifications. The episodic master recession method was applied to the 15‐min water table elevation and NEXRAD rainfall data for 6 wells to identify water table response and individual rainfall events. The objectives of this study were to evaluate the effects of rainfall, water table elevation, canal stage, site‐specific characteristics, and canal structure modification/water management practice on the fluctuations in water table elevations using multiple/stepwise multiple linear regression techniques. With the modification of canal structure and operation adjustment, significant difference existed in water table response in the southern wells due to its relative downstream position regarding the general groundwater flow direction and the structural modification locations. On average, water table response height and flood risk were lower after than before the structure modification to canals. The effect of rainfall event size on the height of water table response was greater than the effect of antecedent water table elevation and canal stage on the height of water table response. Other factors including leakance of the canal bed sediment, specific yield, and rainfall on i  ? 1 day had significant effects on the height of water table response as well. Antecedent water table elevation and canal stage had greater and more linear effects on the height of water table response after the management changes to canals. Variation in water table response height/rainfall event size ratio was attributed to difference in S _y , antecedent soil water content, hydraulic gradient, rainfall size, and run‐off ratio. After the structure modification, water table response height/rainfall event size ratio demonstrated more linear and proportional relationship with antecedent water table elevation and canal stage.     

Modelling soil water dynamics considering measurement uncertainty

In shallow water table‐controlled environments, surface water management impacts groundwater table levels and soil water dynamics. The study goal was to simulate soil water dynamics in response to canal stage raises considering uncertainty in measured soil water content. Water and Agrochemicals in the soil, crop and Vadose Environment (WAVE) was applied to simulate unsaturated flow above a shallow aquifer. Global sensitivity analysis was performed to identify model input factors with the greatest influence on predicted soil water content. Nash–Sutcliffe increased and Root Mean Square Error reduced when uncertainties in measured data were considered in goodness‐of‐fit calculations using measurement probability distributions and probable asymmetric error boundaries, implying that appropriate model performance evaluation should be carried out using uncertainty ranges instead of single values. Although uncertainty in the experimental measured data limited evaluation of the absolute predictions by the model, WAVE was found a useful exploratory tool for estimating temporal variation in soil water content. Visual analysis of soil water content time series under proposed changes in canal stage management indicated that sites with land surface elevation of less than 2.0‐m NGVD29 were predicted to periodically experience saturated conditions in the root zone and shortening of the growing season if canal stage is raised more than 9 cm and maintained at this level. The models developed could be combined with high‐resolution digital elevation models in future studies to identify areas with the greatest risk of experiencing saturated root zone. The study also highlighted the need to incorporate measurement uncertainty when evaluating performance of unsaturated flow models. Copyright © 2014 John Wiley & Sons, Ltd.     

Impact of time-scale of the calibration objective function on the performance of watershed models

Many of the continuous watershed models perform all their computations on a daily time step, yet they are often calibrated at an annual or monthly time-scale that may not guarantee good simulation performance on a daily time step. The major objective of this paper is to evaluate the impact of the calibration time-scale on model predictive ability. This study considered the Soil and Water Assessment Tool for the analyses, and it has been calibrated at two time-scales, viz. monthly and daily for the War Eagle Creek watershed in the USA. The results demonstrate that the model's performance at the smaller time-scale (such as daily) cannot be ensured by calibrating them at a larger time-scale (such as monthly). It is observed that, even though the calibrated model possesses satisfactory ‘goodness of fit’ statistics, the simulation residuals failed to confirm the assumption of their homoscedasticity and independence. The results imply that evaluation of models should be conducted considering their behavior in various aspects of simulation, such as predictive uncertainty, hydrograph characteristics, ability to preserve statistical properties of the historic flow series, etc. The study enlightens the scope for improving/developing effective autocalibration procedures at the daily time step for watershed models. Copyright © 2007 John Wiley & Sons, Ltd.     

Data gaps in finite-dimensional boundary value problems for satellite gradiometry

 In the framework of a boundary value problem (BVP), when areas on the boundary are void of data the solution of the problem becomes undetermined and clearly more difficult. Physically, this could be the situation in which a gradiometer on a satellite on a perfectly circular orbit covers a sphere with measured second radial derivatives: if the satellite orbit is not polar, there are caps at satellite altitude which are not covered by data. A solution is presented based on an iterative algorithm, under the hypothesis of using a finite-dimensional model as is usually done in the time-wise approach. The convergence of the iterative solution is proved and a numerical example is shown to confirm the theoretical result. Received: 14 August 2000 / Accepted: 12 April 2001     

First GOCE gravity field models derived by three different approaches

Three gravity field models, parameterized in terms of spherical harmonic coefficients, have been computed from 71 days of GOCE (Gravity field and steady-state Ocean Circulation Explorer) orbit and gradiometer data by applying independent gravity field processing methods. These gravity models are one major output of the European Space Agency (ESA) project GOCE High-level Processing Facility (HPF). The processing philosophies and architectures of these three complementary methods are presented and discussed, emphasizing the specific features of the three approaches. The resulting GOCE gravity field models, representing the first models containing the novel measurement type of gravity gradiometry ever computed, are analysed and assessed in detail. Together with the coefficient estimates, full variance-covariance matrices provide error information about the coefficient solutions. A comparison with state-of-the-art GRACE and combined gravity field models reveals the additional contribution of GOCE based on only 71 days of data. Compared with combined gravity field models, large deviations appear in regions where the terrestrial gravity data are known to be of low accuracy. The GOCE performance, assessed against the GRACE-only model ITG-Grace2010s, becomes superior at degree 150, and beyond. GOCE provides significant additional information of the global Earth gravity field, with an accuracy of the 2-month GOCE gravity field models of 10?cm in terms of geoid heights, and 3?mGal in terms of gravity anomalies, globally at a resolution of 100?km (degree/order 200).     

Estimation of urban subtropical bahiagrass (Paspalum notatum) evapotranspiration using crop coefficients and the eddy covariance method

Eddy covariance (EC) and micro‐meteorological data were collected from May 2010 to January 2013 from urban, non‐irrigated bahiagrass (Paspalum notatum) in subtropical south Florida. The objectives were to determine monthly crop coefficients (K_c) for non‐irrigated bahiagrass by using EC evapotranspiration (ET) data and the Food and Agriculture Organization 56 Penman–Monteith reference evapotranspiration equation; compare crop ET (ET_c) calculated with new K_c values to ET_c obtained using K_c values available in the literature; and compare results and methodologies for statistical differences. New K_c values ranged from 0.62 to 0.92 and were different from K_c values found in the scientific literature for bahiagrass. Resulting ET_c calculated using literature K_c values were significantly different from EC ET data, whereas ET_c using the new K_c values was not. Specifically, literature K_c values were temporally biased to miscalculate the timing of convergence between potential and actual ET, assuming that our new K_c values calculated with EC methods were most accurate. As a consequence, ET_c calculated using the literature K_c values was either too large or too small. However, one set of literature K_c values from a similar climate and water table depth were closer to our new K_c values, indicating that climate should be considered when selecting urban non‐irrigated K_c from the literature to estimate ET. Results also indicated that more than 1 year of EC ET data was needed when establishing monthly K_c values because of annual variability in factors controlling ET, such as water availability. The new K_c values reported herein could be used as an estimate for urban non‐irrigated bahiagrass within similar climates. Copyright © 2013 John Wiley & Sons, Ltd.     

Knab Sampling Window for InSAR Data Interpolation

Interferometric synthetic aperture radar processing requires interpolating a slave image onto a master one. Since the signals requiring interpolation are limited in both time and bandwidth, the Knab sampling window provides an almost optimal and viable interpolation kernel. Its performance in terms of coherence preservation and interferometric phase error as a function of the number of retained samples and oversampling factor are shown.