Kriging in the design of streamflow sampling networks

Villeneuve, Jean‐Pierre; Morin, Guy; Bobée, Bernard; LeBlanc, Denis R.; Delhomme, J.P.

doi:10.1029/wr015i006p01833

Cited by 29 publications

(15 citation statements)

References 8 publications

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“…The estimation of spatial covariance can also be used for network extension (Guttorp et al, 1992). Kriging, which is discussed in the next section, has also been used to rationalize and to assess the possibility of enhancing water quality and meteorological station networks (Villeneuve et al, 1979;PardoIguzquiza, 1998;Huang and Yang, 1998). The main problem associated with this type of approach is that it usually underestimates the variability within the network.…”

Section: Overview Of Statistical Methods To Evaluate the Appropriatenmentioning

confidence: 98%

Assessment of the impact of meteorological network density on the estimation of basin precipitation and runoff: a case study

St‐Hilaire

Ouarda

Lachance

et al. 2003

Hydrological Processes

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Abstract:In recent years in North America, a number of government agencies and industries have begun to reinvest in meteorological networks. This investment must be based on sound scientific advice. Increased meteorological station network density can be beneficial for a number of purposes, including flood forecasting. This study aimed at investigating the impact of network density at two temporal scales, i.e. for the estimation of total annual precipitation and for the estimation of daily precipitation during specific rain events. This was done using kriging as a means to estimate the spatial distribution and variance of rainfall. Kriged precipitation from two network scenarios (sparse and dense) were used as input into the HSAMI hydrological model and simulations were compared on five drainage basins in the Mauricie area (Québec, Canada).A comparison of the distribution of total annual precipitation interpolated from the two network scenarios showed that adding stations changed the distribution and magnitude of rainfall in the study area. High precipitation cells were better defined with the denser network, and decreases in the relative spatial variance were observed. Similarly, kriged daily precipitation provided a more defined spatial distribution of rainfall during important rain events of 1999, and variance was also reduced when the denser network was used.Finally, simulations performed with the HSAMI model were generally improved when the precipitation inputs were estimated using a denser station network for most drainage basins studied, as expressed by increased Nash coefficients and a decreased root-mean-square error. Peak flows during important summer flood events were generally better simulated when a denser network was used to calculate the mean daily precipitation used as input. Total cumulated volume estimations during the rain events were also generally improved with a denser network.This study showed that the estimation of variance remains an important tool for rain gauge network design. Moreover, network density was shown to have an important impact on the quality of flow simulations, even when a lumped model is used.

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Section: Overview Of Statistical Methods To Evaluate the Appropriatenmentioning

confidence: 98%

Assessment of the impact of meteorological network density on the estimation of basin precipitation and runoff: a case study

St‐Hilaire

Ouarda

Lachance

et al. 2003

Hydrological Processes

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“…The method has been used widely in geology for ore reserve estimation (David 1977) but also in other fields of Earth science (e.g. Delhomme 1979;Villeneuve et al 1979;Streit 1981;Jensen et al 1997;Flowers and Clarke 1999). Kriging is an exact interpolator, i.e.…”

Section: Kriging Interpolationmentioning

confidence: 99%

Application of Kriging Interpolation for Glacier Mass Balance Computations

Hock¹,

Jensen²

1999

Geografiska Annaler A

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In order to compute the specific mass balance of a glacier, point measurements of mass balance need to be integrated and thus interpolated over the entire glacier. In this study kriging was applied as interpolation technique to mass balance data of Storglaciären, a 3 km 2 valley glacier, focusing on the sensitivity of results to the choice of some kriging parameters. Although the spatial means varied only little in most cases, the spatial distribution of the mass balance quantities was sensitive to the assumption on kriging parameters, suggesting that the kriging parameters need to be carefully optimized for each case if the spatial distribution is of interest.

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“…In order to avoid the uncertainty caused by hydrological models, hydrologists start to pay attention to interpolating runoff in special random field with geo-statistical method, which has already been used for interpolating precipitation and evaporation (Villeneuve et al, 1979;Gottschalk, 1993a, b;Huang and Yang, 1998;Gottschalk and Krasovskaia, 1998;Merz and Blöschl, 2005). Three key points need to be taken into account: First, consideration of the fact that runoff data refer to the area of drainage basins (the support); second, definition of distances between basins; third, water balance between the upstream and downstream.…”

Section: Introductionmentioning

confidence: 99%

Mapping runoff based on hydro-stochastic approach for the Huaihe River Basin, China

2011

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Theoretical difficulties for mapping and for estimating river regime characteristics in a large-scale basin remain because of the nature of the variable under study: river flows are related to a specific area, i.e. the drainage basin, and are hierarchically organized in space through the river network with upstream-downstream dependencies. Another limitation is there are not enough gauge stations in developing countries. This presentation aims at developing the hydro-stochastic approach for producing choropleth maps of average annual runoff and computing mean discharge along the main river network for a large-scale basin. The approach applied to mean annual runoff is based on geostatistical interpolation procedures coupled with water balance and data uncertainty analyses. It is proved by an application in the upstream at Bengbu in the Huaihe River Basin, a typical large-scale basin in China. Hydro-stochasitic approach in a first step interpolates to a regular grid net and in a second step the grid values are integrated along rivers. The interpolation scheme includes a constraint to be able to account for the lateral water balance along the rivers. Grid runoff map with 10 km × 10 km resolution and the discharge map along the river with the 1 km basic length unit are the main results in this study. This kind of statistic approach can be widely used because it avoids the complexity of hydrological models and does not depend on the meteorological data.

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Kriging in the design of streamflow sampling networks

Cited by 29 publications

References 8 publications

Assessment of the impact of meteorological network density on the estimation of basin precipitation and runoff: a case study

Assessment of the impact of meteorological network density on the estimation of basin precipitation and runoff: a case study

Application of Kriging Interpolation for Glacier Mass Balance Computations

Mapping runoff based on hydro-stochastic approach for the Huaihe River Basin, China

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