Cindy T Falcón, Claudio José C Blanco, Diego C Estumano
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Parameter Estimation Using the Inverse Problem Method for Simulating Lateral Inflow and Runoff Depth in a small catchment of Amazon.
The inverse problem method can be applied to determine the properties of hydrological phenomena and estimate the parameters, which cannot be measured directly. This type of inverse focus can facilitate the implementation of the kinematic wave model (direct model-DM), to fill gaps for lateral inflow rate and runoff depth in watersheds. Thus, the goal of the study was the application of the inverse problem method (IP). The lateral inflow rate was generally obtained as a Fourier transform to represent any watersheds. The study was developed using a small catchment in the Amazon where intense rainfall events occur, producing runoff and sediments, which affect rural populations. Lateral inflow rate and runoff depth were derived using precipitation data and parameters estimated through the KINEROS2 (K2)/direct model (DM) model and the ensuing solution methods with MCMC (Markov chains Monte Carlo)/Fourier transform. The developed method was applied to four rainfall-runoff events, leading to a good fit between the observed and predicted data (Nash-Sutcliffe coefficients between 0.76 and 0.85 and RMSE values between 1.80 mm and 6.72 mm).
期刊介绍:
The Brazilian Academy of Sciences (BAS) publishes its journal, Annals of the Brazilian Academy of Sciences (AABC, in its Brazilianportuguese acronym ), every 3 months, being the oldest journal in Brazil with conkinuous distribukion, daking back to 1929. This scienkihic journal aims to publish the advances in scienkihic research from both Brazilian and foreigner scienkists, who work in the main research centers in the whole world, always looking for excellence.
Essenkially a mulkidisciplinary journal, the AABC cover, with both reviews and original researches, the diverse areas represented in the Academy, such as Biology, Physics, Biomedical Sciences, Chemistry, Agrarian Sciences, Engineering, Mathemakics, Social, Health and Earth Sciences.