Spatial interpolation of precipitation in a dense gauge network for monsoon storm events in the southwestern United States
Author: Matthew Garcia,Christa D. Peters-Lidard, and David C. Goodrich | Size: 900 KB | Format:PDF | Quality:Unspecified | Publisher: Wiley | Year: 2008 | pages: 14
Inaccuracy in spatially distributed precipitation fields can contribute significantly to
the uncertainty of hydrological states and fluxes estimated from land surface models. This
paper examines the results of selected interpolation methods for both convective and
mixed/stratiform events that occurred during the North American monsoon season over a
dense gauge network at the U.S. Department of Agriculture Agricultural Research Service
Walnut Gulch Experimental Watershed in the southwestern United States. The spatial
coefficient of variation for the precipitation field is employed as an indicator of event
morphology, and a gauge clustering factor CF is formulated as a new, scale-independent
measure of network organization. We consider that CF < 0 (a more distributed gauge
network) will produce interpolation errors by reduced resolution of the precipitation field
and that CF > 0 (clustering in the gauge network) will produce errors because of
reduced areal representation of the precipitation field. Spatial interpolation is performed
using both inverse-distance-weighted (IDW) and multiquadric-biharmonic (MQB)
methods. We employ ensembles of randomly selected network subsets for the statistical
evaluation of interpolation errors in comparison with the observed precipitation. The
magnitude of interpolation errors and differences in accuracy between interpolation
methods depend on both the density and the geometrical organization of the gauge
network. Generally, MQB methods outperform IDW methods in terms of interpolation
accuracy under all conditions, but it is found that the order of the IDW method is
important to the results and may, under some conditions, be just as accurate as the
MQB method. In almost all results it is demonstrated that the inverse-distance-squared
method for spatial interpolation, commonly employed in operational analyses and for
engineering assessments, is inferior to the ID-cubed method, which is also more
computationally efficient than the MQB method in studies of large networks.
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Multicriteria design of rain gauge networks for flash flood prediction in semiarid catchments with complex terrain
Author: Till H. M. Volkmann, Steve W. Lyon, Hoshin V. Gupta, and Peter A. Troch | Size: 1.9 MB | Format:PDF | Quality:Unspecified | Publisher: Wiley | Year: 2010 | pages: 16
Despite the availability of weather radar data at high spatial (1 km2) and temporal
(5–15 min) resolution, ground‐based rain gauges continue to be necessary for accurate
estimation of storm rainfall input to catchments during flash flood events, especially in
mountainous catchments. Given economical considerations, a long‐standing problem in
catchment hydrology is to establish optimal placement of a small number of rain gauges to
acquire data on both rainfall depth and spatiotemporal variability of intensity during
extreme storm events. Using weather radar observations and a dense network of 40 tipping
bucket rain gauges, this study examines whether it is possible to determine a reliable “best”
set of rain gauge locations for the Sabino Canyon catchment near Tucson, Arizona, USA,
given its complex topography and dominant storm track pattern. High‐quality rainfall
data are used to evaluate all possible configurations of a “practical” network having from
one to four rain gauges. A multicriteria design strategy is used to guide rain gauge
placement, by simultaneously minimizing the residual percent bias and maximizing the
coefficient of correlation between the estimated and true mean areal rainfall and
minimizing the normalized spatial mean squared error between the estimated and true
spatiotemporal rainfall distribution. The performance of the optimized rain gauge network
was then compared against randomly designed network ensembles by evaluating the
quality of streamflows predicted using the Kinematic Runoff and Erosion (KINEROS2)
event‐based rainfall‐runoff model. Our results indicate that the multicriteria strategy
provided a robust design by which a sparse but accurate network of rain gauges could
be implemented for semiarid basins such as the one studied.
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Geostatistical Analysis of Spatial Variability of Rainfall and Optimal Design of a Rain Gauge Network
Author: DIMITRIS M. PAPAMICHAIL and IRINI G. METAXA | Size: 1.13 MB | Format:PDF | Quality:Unspecified | Publisher: Kluwer Academic Publishers | Year: 1996 | pages: 21
Kriging is a geostatistical estimation technique for regionalized variables that exhibit an
autocorrelation structure. Such a structure can be described by a semivariogram of the observed data.
The punctual&Aging estimate at any point is a weighted average of the data, where the weights are
determined by using the semivariogram and an assumed drift, or lack of drift, in the data. The kriging
algorithm, based on unbiased and minimum-variance estimates, involves a linear system of equations
to calculate the weights. Kriging is applied in an attempt to describe the spatial variability of rainfall
data over a geographical region in northern Greece. Monthly rainfall data of January and June 1987
have been taken from 20 measurement stations throughout the above area. The rainfall data are used
to compute semivariograms for each month. The resulting semivariograms are anisotropic and fitted
by linear and spherical models. Kriging estimates of rainfall and standard deviation were made at
90 locations covering the study area in a rectangular grid and the results used to plot contour maps
of rainfall and contour maps of kriging standard deviation. Verification of the kriging estimates of
rainfall are made by removing known data points and kriging an estimate at the same location. This
verification is known as the jacknifing technique. Kriging errors, a by-product of the calculations,
can then be used to give confidence intervals of the resulting estimates. The acceptable results of the
verification procedure demonstrated that geostatistics can be used to describe the spatial variability
of rainfall. Finally, it is shown how the property of kriging variance depends on the structure and
the geometric configuration of the data points and the point to be estimated can also be used for the
optimal design of the rain gauge network in an area
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Could anyone of you please provide me the articles available in the given link as below:
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SP-273 Further Examples for the Design of Structural Concrete with Strut-and-Tie Models
2010
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Reliable Fundamental Frequencies of Soils and Buildings Down to 0.1 Hz Obtained from Ambient Vibration Recordings with a 4.5‐Hz Sensor
Jean‐Luc Chatelain and Bertrand Guillier
Seismological Research Letters March/April 2013 v. 84 no. 2 p. 199-209
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Computers and Structures, Inc. is pleased to announce the release of CSiXRevit, a link that allows for data exchange between ETABS® v9.7.3/SAP2000 v15.1.0/1 and Autodesk Revit® Structure 2013. CSiXRevit supports true round-tripping, specifically - four different workflows of data interchange:
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