Abstract
In this paper the question of how interpolation of precipitation in space by using various spatial gauge densities affects the rainfall-runoff model discharge if all other input variables are kept constant is investigated. This was done using a physically-based model as the reference with a reconstructed spatially variable precipitation and a conceptual model calibrated to match the reference model output. Both models were run with distributed and lumped inputs. Results showed that all considered interpolation methods resulted in underestimation of the total precipitation volume and that the underestimation was directly proportional to the amount. The underestimation was very severe for low observation densities and disappeared only for very high density precipitation observation networks. This result was confirmed by using observed precipitation with different observation densities. Model runoffs showed worse performance for their highest discharges. Using lumped inputs for the models showed deteriorating performance for peak flows as well even when using simulated precipitation.
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