114 research outputs found

    Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites

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    International audienceProliferation of evapotranspiration (ET) products warrants comparison of these products. The study objective was to assess uncertainty in ET output from four land surface models (LSMs), Noah, Mosaic, VIC, and SAC in NLDAS-2, two remote sensing-based products, MODIS and AVHRR, and GRACE-inferred ET from a water budget with precipitation from PRISM, monitored runoff, and total water storage change (TWSC) from GRACE satellites. The three cornered hat method, which does not require a priori knowledge of the true ET value, was used to estimate ET uncertainties. In addition, TWSC or total water storage anomaly (TWSA) from GRACE was compared with water budget estimates of TWSC from a flux-based approach or TWSA from a storage-based approach. The analyses were conducted using data from three regions (humid-arid) in the South Central United States as case studies. Uncertainties in ET are lowest in LSM ET ( 5 mm/mo), moderate in MODIS or AVHRR-based ET (10-15 mm/mo), and highest in GRACEinferred ET (20-30 mm/month). There is a trade-off between spatial resolution and uncertainty, with lower uncertainty in the coarser-resolution LSM ET ( 14 km) relative to higher uncertainty in the finer-resolution ( 1-8 km) RS ET. Root-mean-square (RMS) of uncertainties in water budget estimates of TWSC is about half of RMS of uncertainties in GRACE-derived TWSC for each of the regions. Future ET estimation should consider a hybrid approach that integrates strengths of LSMs and satellite-based products to constrain uncertainties

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

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    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

    Investigation of Pollution in a Karst Aquifer Utilizing Optical Brightener

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    Optical brightener is an additive to laundry detergents and is found contaminating groundwater. Its concentration may rapidly and inexpensively be determined by fluorescence techniques, and because its source is human wastewater, its presence in groundwater serves as a direct indication of pollution from septic tanks, sewer leaks, and landfills. A total of 105 wells and springs in an area within the Inner Bluegrass Karst Region near Lexington, Kentucky, were described and sampled. Analyses were made for optical brightener (430 samples), total coliform (91), fecal coliform (93), and fecal streptococci (90). As many as 20 optical brightener and 4 bacterial samples were analyzed from a single site during the period from May 20, 1984 to June 17, 1985. Data were also collected on spring discharges, well water.levels, and other site characteristics. Statistical analysis of the relationship between optical brightener and the bacterial indices showed low correlations for both springs and wells, in ·contrast to an earlier study. Although time constraints have precluded a thorough analysis of the data, the difference between the results of the two studies appear to be related to differing site populations and analytic and statistical procedures. The data further suggest that the low correlations between optical brightener and the bacterial indices may be a result of bacterial contamination being largely derived from animal waste and other non-human sources, and that optical brightener may be a more reliable indicator of human contamination
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