Rain-gauge network evaluation and augmentation using geostatistics

Rain-gauge networks are often used to provide estimates of area average rainfall or point rainfalls at ungauged locations. The level of accuracy a network can achieve depends on the total number and locations of gauges in the network. A geostatistical approach for evaluation and augmentation of an e...

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Bibliographic Details
Published in:Hydrological processes Vol. 22; no. 14; pp. 2554 - 2564
Main Authors: Cheng, Ke-Sheng, Lin, Yun-Ching, Liou, Jun-Jih
Format: Journal Article
Language:English
Published: Chichester, UK John Wiley & Sons, Ltd 01.07.2008
Wiley
Subjects:
algorithms
case studies
Earth sciences
Earth, ocean, space
Exact sciences and technology
geostatistics
Hydrology
Hydrology. Hydrogeology
network augmentation
network evaluation
probability
rain
rain gauges
Taiwan
variance
variogram analysis
Far East
Asia
Taiwan
geostatistics
algorithms
rainfall
kriging
probability
variograms
accuracy
rain water
case studies
networks
variogram analysis
network augmentation
contour maps
performances
errors
network evaluation
ISSN:0885-6087, 1099-1085
Online Access:Get full text
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Summary:Rain-gauge networks are often used to provide estimates of area average rainfall or point rainfalls at ungauged locations. The level of accuracy a network can achieve depends on the total number and locations of gauges in the network. A geostatistical approach for evaluation and augmentation of an existing rain-gauge network is proposed in this study. Through variogram analysis, hourly rainfalls are shown to have higher spatial variability than annual rainfalls, with hourly Mei-Yu rainfalls having the highest spatial variability. A criterion using ordinary kriging variance is proposed to assess the accuracy of rainfall estimation using the acceptance probability defined as the probability that estimation error falls within a desired range. Based on the criterion, the percentage of the total area with acceptable accuracy Ap under certain network configuration can be calculated. A sequential algorithm is also proposed to prioritize rain-gauges of the existing network, identify the base network, and relocate non-base gauges. Percentage of the total area with acceptable accuracy is mostly contributed by the base network. In contrast, non-base gauges provide little contribution to Ap and are subject to removal or relocation. Using a case study in northern Taiwan, the proposed approach demonstrates that the identified base network which comprises of approximately two-thirds of the total rain-gauges can achieve almost the same level of performance (expressed in terms of percentage of the total area with acceptable accuracy) as the complete network for hourly Mei-Yu rainfall estimation. The percentage of area with acceptable accuracy can be raised from 56% to 88% using an augmented network. A threshold value for the percentage of area with acceptable accuracy is also recommended to help determine the number of non-base gauges which need to be relocated. Copyright © 2007 John Wiley & Sons, Ltd.
Bibliography:http://dx.doi.org/10.1002/hyp.6851
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ISSN:0885-6087
1099-1085
DOI:10.1002/hyp.6851