Separation of blended data by iterative estimation and subtraction of interference noise

Conventional data acquisition practice dictates the existence of sufficient time intervals between the firing of successive sources in the field. However, much attention has been drawn recently to the possibility of shooting in an overlapping fash- ion. Numerous publications have addressed the issue from dif- ferent scopes (denoising, compressing, blind signal separation etc.) while others have defined the theoretical background. The term ‘blending’ was introduced to describe this new trend in acquisition designs, the time-overlapping data acquisition. In turn, the term ‘deblending’ refers to an algorithm that re- covers the data as if they were shot in the conventional way. Such an algorithm is presented in this chapter for application on both impulsive and vibrating sources. This algorithm is based on iterative interference estimation and subtraction and is applied to field data.GeotechnologyCivil Engineering and Geoscience

Signature of Arctic first-year ice melt pond fraction in X-band SAR imagery

In this paper we investigate the potential of melt pond fraction retrieval from X-band polarimetric synthetic aperture radar (SAR) on drifting first-year sea ice. Melt pond fractions retrieved from a helicopter-borne camera system were compared to polarimetric features extracted from four dual-polarimetric X-band SAR scenes, revealing significant relationships. The correlations were strongly dependent on wind speed and SAR incidence angle. Co-polarisation ratio was found to be the most promising SAR feature for melt pond fraction estimation at intermediate wind speeds (6. 2 m s−1), with a Spearman's correlation coefficient of 0. 46. At low wind speeds (0. 6 m s−1), this relation disappeared due to low backscatter from the melt ponds, and backscatter VV-polarisation intensity had the strongest relationship to melt pond fraction with a correlation coefficient of −0. 53. To further investigate these relations, regression fits were made both for the intermediate (R2fit = 0. 21) and low (R2fit = 0. 26) wind case, and the fits were tested on the satellite scenes in the study. The regression fits gave good estimates of mean melt pond fraction for the full satellite scenes, with less than 4 % from a similar statistics derived from analysis of low-altitude imagery captured during helicopter ice-survey flights in the study area. A smoothing window of 51 × 51 pixels gave the best reproduction of the width of the melt pond fraction distribution. A considerable part of the backscatter signal was below the noise floor at SAR incidence angles above  ∼  40°, restricting the information gain from polarimetric features above this threshold. Compared to previous studies in C-band, limitations concerning wind speed and noise floor set stricter constraints on melt pond fraction retrieval in X-band. Despite this, our findings suggest new possibilities in melt pond fraction estimation from X-band SAR, opening for expanded monitoring of melt ponds during melt season in the future

Systems analysis approach to the design of efficient water pricing policies under the EU Water Framework Directive

Economic theory suggests that water pricing can contribute to efficient management of water scarcity. The European Union (EU) Water Framework Directive (WFD) is a major legislative effort to introduce the use of economic instruments to encourage efficient water use and achieve environmental management objectives. However, the design and implementation of economic instruments for water management, including water pricing, has emerged as a challenging aspect of WFD implementation. This study demonstrates the use of a systems analysis approach to designing and comparing two economic approaches to efficient management of groundwater and surface water given EU WFD ecological flow requirements. Under the first approach, all wholesale water users in a river basin face the same volumetric price for water. This water price does not vary in space or in time, and surface water and groundwater are priced at the same rate. Under the second approach, surface water is priced using a volumetric price, while groundwater use is controlled through adjustments to the price of energy, which is assumed to control the cost of groundwater pumping. For both pricing policies, optimization is used to identify optimal prices, with the objective of maximizing welfare while reducing human water use in order to meet constraints associated with EU WFD ecological and groundwater sustainability objectives. The systems analysis approach demonstrates the successful integration of economic, hydrologic, and environmental components into an integrated framework for the design and testing of water pricing policies. In comparison to the first pricing policy, the second pricing policy, in which the energy price is used as a surrogate for a groundwater price, shifts a portion of costs imposed by higher water prices from low-value crops to high-value crops and from small urban/domestic locations to larger locations. Because growers of low-value crops will suffer the most from water price increases, the use of energy costs to control groundwater use offers the advantage of reducing this burden.The authors would like to thank the Danish Research School of Water Resources (FIVA) for financial support. Three anonymous reviewers made helpful suggestions that were incorporated into the revised version.Riegels, N.; Pulido-Velazquez, M.; Doulgeris, C.; Sturm, V.; Jensen, R.; Moller, F.; Bauer-Gottwein, P. (2013). Systems analysis approach to the design of efficient water pricing policies under the EU Water Framework Directive. Journal of Water Resources Planning and Management. 139(5):574-582. doi:10.1061/(ASCE)WR.1943-5452.0000284S574582139

Leads in Arctic pack ice enable early phytoplankton blooms below snow-covered sea ice

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 7 (2017): 40850, doi:10.1038/srep40850.The Arctic icescape is rapidly transforming from a thicker multiyear ice cover to a thinner and largely seasonal first-year ice cover with significant consequences for Arctic primary production. One critical challenge is to understand how productivity will change within the next decades. Recent studies have reported extensive phytoplankton blooms beneath ponded sea ice during summer, indicating that satellite-based Arctic annual primary production estimates may be significantly underestimated. Here we present a unique time-series of a phytoplankton spring bloom observed beneath snow-covered Arctic pack ice. The bloom, dominated by the haptophyte algae Phaeocystis pouchetii, caused near depletion of the surface nitrate inventory and a decline in dissolved inorganic carbon by 16 ± 6 g C m−2. Ocean circulation characteristics in the area indicated that the bloom developed in situ despite the snow-covered sea ice. Leads in the dynamic ice cover provided added sunlight necessary to initiate and sustain the bloom. Phytoplankton blooms beneath snow-covered ice might become more common and widespread in the future Arctic Ocean with frequent lead formation due to thinner and more dynamic sea ice despite projected increases in high-Arctic snowfall. This could alter productivity, marine food webs and carbon sequestration in the Arctic Ocean.This study was supported by the Centre for Ice, Climate and Ecosystems (ICE) at the Norwegian Polar Institute, the Ministry of Climate and Environment, Norway, the Research Council of Norway (projects Boom or Bust no. 244646, STASIS no. 221961, CORESAT no. 222681, CIRFA no. 237906 and AMOS CeO no. 223254), and the Ministry of Foreign Affairs, Norway (project ID Arctic), the ICE-ARC program of the European Union 7th Framework Program (grant number 603887), the Polish-Norwegian Research Program operated by the National Centre for Research and Development under the Norwegian Financial Mechanism 2009–2014 in the frame of Project Contract Pol-Nor/197511/40/2013, CDOM-HEAT, and the Ocean Acidification Flagship program within the FRAM- High North Research Centre for Climate and the Environment, Norway

Leads in Arctic pack ice enable early phytoplankton blooms below snow-covered sea ic

publishedVersio

Evaluation of Analytical Methods to Study Aquifer Properties with Pumping Tests in Coastal Aquifers with Numerical Modelling (Motril-Salobreña Aquifer)

Two pumping tests were performed in the unconfined Motril-Salobreña detrital aquifer in a 250 m-deep well 300 m from the coastline containing both freshwater and saltwater. It is an artesian well as it is in the discharge zone of this coastal aquifer. The two observation wells where the drawdowns are measured record the influence of tidal fluctuations, and the well lithological columns reveal high vertical heterogeneity in the aquifer. The Theis and Cooper-Jacob approaches give average transmissivity (T) and storage coefficient (S) values of 1460 m2 /d and 0.027, respectively. Other analytical solutions, modified to be more accurate in the boundary conditions found in coastal aquifers, provide similar T values to those found with the Theis and Cooper-Jacob methods, but give very different S values or could not estimate them. Numerical modelling in a synthetic model was applied to analyse the sensitivity of the Theis and Cooper-Jacob approaches to the usual boundary conditions in coastal aquifers. The T and S values calculated from the numerical modelling drawdowns indicate that the regional flow, variable pumping flows, and tidal effect produce an error of under 10 % compared to results obtained with classic methods. Fluids of different density (freshwater and saltwater) cause an error of 20 % in estimating T and of over 100 % in calculating S. The factor most affecting T and S results in the pumping test interpretation is vertical heterogeneity in sediments, which can produce errors of over 100 % in both parameters.This research has been financed by Project CGL2012-32892 (Ministerio de Economía y Competitividad of Spain) and by the Research Group Sedimentary Geology and Groundwater (RNM-369) of the Junta de Andalucía

Inversion methods for the separation of blended data

The recording and storage capacity of modern seismic acquisition systems is continuously growing, enabling denser sampling and the acquisition of better-quality data. One big hurdle is survey time, since the duration of a survey is directly proportional to the number of sources fired. The proposed way forward is to deploy nearly simultaneous sources. Then, the acquired data are blended, i.e., the response to multiple sources is recorded in a single shot record. The objective of this thesis is to provide a method for the separation of blended data with a specific focus on the marine case. The result of this method will contain the response to only one source in every shot record, hence, the subsequent processing steps will not suffer from the interference noise caused by blending. In order to address this challenge, a firm mathematical formulation is required. Based on this formulation, the problem of separating blended data can be cast as a constrained optimisation problem. A constraint reflects the prior knowledge about the solution, in this case the separated data. The fundamental property of coherency is chosen as constraint and the problem can be solved with the aid of an iterative algorithm. A comparison of this algorithm with similar algorithms currently developed in the industry reveals that there are small but important theoretical and implementational differences. The leakage subspace, a mathematical notion inspired by the convergence analysis of this iterative algorithm, contains data that cannot be separated uniquely. This subspace can be computed prior to the acquisition of the data and establishes the link between acquisition parameters and separation efficiency. The separation method has been successfully applied to one of the few real 3D blended datasets currently available. Moreover, numerically blended datasets have been created based on unblended field data and then have been efficiently separated. Numerical blending gives us the freedom to utilize and study the method under different blending conditions. A well-known challenge in the processing of marine seismic data is the presence of strong surface-related multiples, i.e., up going energy from the subsurface that has been reflected at the surface and travels back into the subsurface. A field-data example showed that the separation algorithm, equipped with a surface-multiple prediction term, is able to suppress the surface-multiples while separating the blended data. Another approach is the use of a sparse inversion scheme for the same objective. This algorithm utilizes prior knowledge in terms of travel-time operators and provided excellent results when tested on simple numerical data. This thesis proposes a solution to the challenge of separating blended data. The added business value of such separation algorithms is significant for any exploration company since it can lead to a substantial reduction of the data acquisition cost.Geoscience & EngineeringCivil Engineering and Geoscience

Scale Mixture of Gaussian Modelling of Polarimetric SAR Data

This paper describes a flexible non-Gaussian statistical method used to model polarimetric synthetic aperture radar (POLSAR) data. We outline the theoretical basis of the well-know product model as described by the class of Scale Mixture models and discuss their appropriateness for modelling radar data. The statistical distributions of several Scale mixture models are then described, including the commonly used Gaussian model, and techniques for model parameter estimation are given. Real data evaluations are made using airborne fully polarimetric SAR studies for several distinct land cover types. Generic scale mixture of Gaussian features is extracted from the model parameters and a simple clustering example presented