Assessment of different interpolation algorithms for daily rainfall spatial distribution in the Var catchment, France

Abstract To have effective water resource management, the distributed hydrological models are commonly applied for supporting the decision‐making processes. Among different inputs, the spatial distributed rainfall plays significant role in those model simulations. Many interpolation methods have been developed for generating distributed rainfall based on measurement samples. However, depending on the catchment characteristics and data availability, the suitable interpolation algorithm is case‐dependent. This paper presents one operational approach for determining the resonable interpolation algorithm in a complex large catchment (Var catchment, France). Based on the daily rainfall data (2008–2014) collected from 16 stations in the Var catchment, six different interpolation approaches including: inverse distance weight (IDW), spline, kriging with linear and spherical semi‐variogram models and geographically weighted regression considering elevation effects and the combined impacts of elevation and distance to the sea were tested. Integrated the results of statistical and modeling assessments, the 400 m resolution distributed rainfall generated by IDW algorithm shows high preference in generating distributed rainfall in the Var catchment. Moreover, the strategy described in the article also shows promising acceptability for other catchments.