2015
DOI: 10.5194/hess-19-507-2015
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Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data

Abstract: Abstract. The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and not generally accessible. Remote sensing data is a suitable alternative to measure the required input variables. This paper reviews the… Show more

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Cited by 129 publications
(93 citation statements)
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References 206 publications
(97 reference statements)
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“…The variability in this case expresses the accuracy and thus confidence that can be attached to the outputs, because the variability of the input parameter space expresses error in the remotely sensed hydrological variables. The space of input parameters in this MC study is defined by a skewed normal distribution as explained by Karimi and Bastiaanssen (2015). The statistical input data are specified in Table 4.…”
Section: Methodology To Express the Reliability Of The Wa+ Frameworkmentioning
confidence: 99%
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“…The variability in this case expresses the accuracy and thus confidence that can be attached to the outputs, because the variability of the input parameter space expresses error in the remotely sensed hydrological variables. The space of input parameters in this MC study is defined by a skewed normal distribution as explained by Karimi and Bastiaanssen (2015). The statistical input data are specified in Table 4.…”
Section: Methodology To Express the Reliability Of The Wa+ Frameworkmentioning
confidence: 99%
“…A recent literature review by Karimi and Bastiaanssen (2015) showed that the average errors in land use mapping, and annual or seasonal precipitation and evapotranspiration estimates on the basis of multispectral remote sensing data were 14.5, 18.5, and 5.4 %, respectively. These figures are based on a comprehensive literature review in which for each variable several numbers of post-2000 peer-reviewed publications were consulted for reported differences of satellite-based estimates from conventional ground measurements.…”
Section: P Karimi Et Al: Spatial Evapotranspiration Rainfall and Lmentioning
confidence: 99%
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“…These observations are also needed for prognosticating future trends by using modelling approaches that involve calibration and simulation procedures [7]. Additionally, long-term observations of ETa over small watersheds are useful as ground truth for validating remotely sensed products [8].…”
Section: Introductionmentioning
confidence: 99%