Ground referencing GRACE satellite estimates of groundwater storage changes in the California Central Valley, USA

International audience[1] There is increasing interest in using Gravity Recovery and Climate Experiment (GRACE) satellite data to remotely monitor groundwater storage variations; however, comparisons with ground-based well data are limited but necessary to validate satellite data processing, especially when the study area is close to or below the GRACE footprint. The Central Valley is a heavily irrigated region with large-scale groundwater depletion during droughts. Here we compare updated estimates of groundwater storage changes in the California Central Valley using GRACE satellites with storage changes from groundwater level data. A new processing approach was applied that optimally uses available GRACE and water balance component data to extract changes in groundwater storage. GRACE satellites show that groundwater depletion totaled $31.0 6 3.0 km 3 for Groupe de Recherche de Geodesie Spatiale (GRGS) satellite data during the drought from October 2006 through March 2010. Groundwater storage changes from GRACE agreed with those from well data for the overlap period (April 2006 through September 2009) (27 km 3 for both). General correspondence between GRACE and groundwater level data validates the methodology and increases confidence in use of GRACE satellites to monitor groundwater storage changes

Fighting Against Human Trade In Michael Apted Amazing Grace Movie (2006): A Sociological Approach

The major problem in this research paper is to explain how fighting against human trade is reflected in Michael Apted Amazing Grace movie. The purposes of this research paper are to analyze Michael Apted Amazing Grace Movie (2006) based on the structural elements of the movie, to describe Fighting against human trade reflected in Michael Apted Amazing Grace Movie (2006) based on sociological approach. The object study is Amazing Grace movie that the screen play is by Michael Apted. It uses sociological approach. In analyzing this study, the writer uses qualitative methodology of research and sociological approach. The Primary data source of this research is the movie Amazing Grace movie that the screen play is Michael Apted. The secondary data sources are the author’s biography, essay, comment, homepage, and website about the movie and other relevant sources. Having analyzed this research paper, the writer presents two conclusions. First, based on the structural analysis it is evident that in this movie the director is giving message that slavery is against humanity. Second, based on the sociological analysis, it appears that this movie is related to the social reality of American society of the end twentieth century

Thomas Torrance\u27s Reformulation of Karl Barth\u27s Christological Rejection of Natural Theology

Karl Barth is widely noted for his antipathy to all forms of natural theology. Indeed, the results of Barth’s Christocentricity have made his name synonymous with the negation of all divine revelation apart from Christ, the one Word of God. if this is so, then the theology of Thomas Torrance, as a highly significant development of Barth’s thought and as vitally concerned with proper natural theology (in dialogue with the physical sciences), becomes a questionable enterprise. This article examines this question and concludes that, while Torrance clearly goes beyond Barth, he is faithful to subthemes in Barth’s theology relating to ‘natural theology’, making explicit and bringing to prominence streams of Barthian thought often left unnoticed

Potential of using remote sensing techniques for global assessment of water footprint of crops

Remote sensing has long been a useful tool in global applications, since it provides physically-based, worldwide, and consistent spatial information. This paper discusses the potential of using these techniques in the research field of water management, particularly for ‘Water Footprint’ (WF) studies. The WF of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage, respectively. In this paper evapotranspiration, precipitation, water storage, runoff and land use are identified as key variables to potentially be estimated by remote sensing and used for WF assessment. A mass water balance is proposed to calculate the volume of irrigation applied, and green and blue WF are obtained from the green and blue evapotranspiration components. The source of remote sensing data is described and a simplified example is included, which uses evapotranspiration estimates from the geostationary satellite Meteosat 9 and precipitation estimates obtained with the Climatic Prediction Center Morphing Technique (CMORPH). The combination of data in this approach brings several limitations with respect to discrepancies in spatial and temporal resolution and data availability, which are discussed in detail. This work provides new tools for global WF assessment and represents an innovative approach to global irrigation mapping, enabling the estimation of green and blue water use

Modeling of GRACE-Derived Groundwater Information in the Colorado River Basin

Groundwater depletion has been one of the major challenges in recent years. Analysis of groundwater levels can be beneficial for groundwater management. The National Aeronautics and Space Administration’s twin satellite, Gravity Recovery and Climate Experiment (GRACE), serves in monitoring terrestrial water storage. Increasing freshwater demand amidst recent drought (2000–2014) posed a significant groundwater level decline within the Colorado River Basin (CRB). In the current study, a non-parametric technique was utilized to analyze historical groundwater variability. Additionally, a stochastic Autoregressive Integrated Moving Average (ARIMA) model was developed and tested to forecast the GRACE-derived groundwater anomalies within the CRB. The ARIMA model was trained with the GRACE data from January 2003 to December of 2013 and validated with GRACE data from January 2014 to December of 2016. Groundwater anomaly from January 2017 to December of 2019 was forecasted with the tested model. Autocorrelation and partial autocorrelation plots were drawn to identify and construct the seasonal ARIMA models. ARIMA order for each grid was evaluated based on Akaike’s and Bayesian information criterion. The error analysis showed the reasonable numerical accuracy of selected seasonal ARIMA models. The proposed models can be used to forecast groundwater variability for sustainable groundwater planning and management

Traceability and AOSD - From Requirements to Aspects

The traceability question is addressed through the development of a framework to go from requirements to aspects using the Design by Contract methodology. It is demonstrated that by starting at the requirements stage, and specifying an early aspect in the same semi-formal language as the system's existing requirements, we have the basis from which to design the aspects at the implementation stage. The language of pre- and post-conditions is shown to match closely that of aspects, in that pre-conditions match the aspect's pointcut, and the post-condition matches the advice part of the aspect. This thus gives us traceability from 'early aspects' to 'late aspects'. This approach will shed some light on the relationship between requirements and their refinements to pre- and post conditions, and the traceability of requirements in the face of reuse over time. The addition of a new crosscutting requirement is investigated in terms of the framework, demonstrating the relationship between early and late aspects and traceability. The framework promises to help with the design of the late aspects. We propose the concept of relevancy: information in a requirement beyond its specification as pre- and post-conditions, as a way of identifying join points