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  • 1
    Publication Date: 2022-05-25
    Description: © 2009 The Authors. This article is distributed under the terms of the Creative Commons Attribution (3.0) License. The definitive version was published in Sensors 9 (2009): 404-429, doi:10.3390/s90100404.
    Description: An instrument has been built to carry out continuous in-situ measurement of small differences in water pressure, conductivity and temperature, in natural surface water and groundwater systems. A low-cost data telemetry system provides data on shore in real time if desired. The immediate purpose of measurements by this device is to continuously infer fluxes of water across the sediment-water interface in a complex estuarine system; however, direct application to assessment of sediment-water fluxes in rivers, lakes, and other systems is also possible. Key objectives of the design include both low cost, and accuracy of the order of ±0.5 mm H2O in measured head difference between the instrument’s two pressure ports. These objectives have been met, although a revision to the design of one component was found to be necessary. Deployments of up to nine months, and wireless range in excess of 300 m have been demonstrated.
    Keywords: Pressure sensor ; Wireless ; Hydrology ; Data logger ; Oceanographic instrumentation
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 2
  • 3
    Publication Date: 2008-10-01
    Description: Estimates of the net convergence of atmospheric moisture flux over the Amazon Basin, [C], derived using data products from three global reanalyses, the NCEP–NCAR reanalysis (NCEP-1), the NCEP/Department of Energy reanalysis (NCEP-2), and the 40-yr ECMWF Re-Analysis (ERA-40), are compared. Two types of uncertainty in these [C] estimates are distinguished and quantified: “model-associated uncertainty,” which necessarily arises from imperfections in the numerical weather models or data assimilation algorithms, and “postprocessing uncertainty” introduced by operations performed on the original reanalysis data products to compute [C], particularly the finite-difference approximation of divergence. Model-associated uncertainty is found to overwhelm the postprocessing error. A closer look at the time series of this field extending over the period 1980–2001, and their comparison to basin-averaged precipitation and runoff data, reveals the signatures of two potential sources of model-associated errors. 1) ERA-40 estimates of [C] exhibit an artificial shift in 1987, possibly produced by the start of assimilation of Special Sensor Microwave Imager (SSM/I) data. The estimates preceding 1988 are negatively biased relative to the remaining time series, and hence subsequent analysis is limited to the 14-yr period 1988–2001. 2) NCEP-1 and NCEP-2 estimates of [C] show a negative bias over the period 1992–98, which likely originates in biased Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) data assimilated by these reanalyses. A measure of the random error in the [C] time series produced by each reanalysis, computed using river discharge data as reference, indicates that ERA-40 gives the most accurate estimates of net atmospheric moisture flux convergence for the aforementioned 14-yr period.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 4
    Publication Date: 2008-10-01
    Description: Spatially averaged evapotranspiration [ET] over the Amazon Basin is computed as the residual of the basin’s atmospheric water balance equation, at the monthly time scale and for the period 1988–2001. Basin-averaged rainfall [P] is obtained from the Global Precipitation Climatology Project (GPCP) dataset, and alternative estimates of the net convergence of atmospheric water vapor flux over the basin [C] are derived from three global reanalyses: the NCEP–NCAR and NCEP–Department of Energy (DOE) reanalyses and the 40-yr ECMWF Re-Analysis (ERA-40). Additionally, a best estimate of [C] is obtained by taking a weighted average of data from these three sources, in which the weight factors are based on the random error attributed to each reanalysis’ [C] estimates by comparison to river discharge data. The resulting time series is dominated by ERA-40’s contribution, which was found to be the most accurate over the study period. Data products from the three reanalyses are also employed to compute the monthly tendencies of total precipitable water over the basin. While the seasonal signature of this “accumulation term” provides important insight into the Amazon Basin’s hydrological cycle, its magnitude is found to be negligible relative to the other components of the water budget. The value of mean annual [ET] presented in this work is significantly lower than other published estimates that are based on simulations by various land surface models. Furthermore, when the best estimate of [C] is used, the resulting [ET] time series exhibits a seasonal cycle that is in phase with that of basin-averaged surface net radiation, suggesting that Amazonian evapotranspiration is prevalently limited by energy availability. In contrast, most land surface models, including that of the NCEP–NCAR reanalysis, simulate water-limited evapotranspiration in the Amazon Basin. The analysis presented here supports the hypothesis that most Amazonian trees sustain elevated evapotranspiration rates during the dry season through deep roots, which tap into large reservoirs of soil water that are replenished during the following wet season.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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