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

TLDR: In this article, the authors investigated the impact of network density at two temporal scales, i.e. for the estimation of total annual precipitation and for the estimate of daily precipitation during specific rain events.

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 (Qu´ ebec, 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. Copyright  2003 John Wiley & Sons, Ltd.