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• W2529300035 abstract "Abstract What is the best resolution of annual water balance maps for a correct balance between the basic spatial signal in the observations of precipitation, actual evapotranspiration and runoff across a larger drainage basin and the error in estimates for grid cells in the map to avoid giving a false impression of accuracy? To answer this question an approach based a signal to noise ratio is proposed, which allows finding the optimal resolution maximizing the signal in the map. The approach is demonstrated on gauge data in the Huai River Basin, China. Stochastic interpolation methods were applied to create grid maps of long-term mean values, as well as for estimating variances of the three water balance components in a range of scales from 5 × 5 km to 200 × 200 km 2 grid cells. Interpolation algorithms using covariances of long-term means of data with different spatial support were developed. The identified optimal resolutions by the signal to noise ratio appeared to be very different – 10 × 10, 50 × 50, and 30 × 30 km 2 for precipitation, actual evapotranspiration, and runoff, respectively. These values are directly linked to the observation network densities. The magnitude of the signal to noise ratio shows similar strong differences with values 34, 3.7, and 5.4, respectively. It gives a direct indication of the reliability of the map, which can be considered as satisfactory only for precipitation for the data available for the present study. The critical factors for this magnitude are parameters characterising the spatial covariance in data and the network density." @default.
• W2529300035 created "2016-10-14" @default.
• W2529300035 creator A5015914970 @default.
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• W2529300035 date "2016-12-01" @default.
• W2529300035 modified "2023-09-24" @default.
• W2529300035 title "Signal to noise ratio in water balance maps with different resolution" @default.
• W2529300035 cites W1669376583 @default.
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• W2529300035 doi "https://doi.org/10.1016/j.jhydrol.2016.09.065" @default.
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