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Assessing the Performance of Two Hydrologic Models for Forecasting Daily Streamflows in the cazones River basin (Mexico)

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Open Journal of Modern Hydrology 2016年第3期6卷 168-181页

作者： Fernando González-Leiva Rodrigo Valdés-Pineda Juan B. Valdés Laura A. Ibáñez-Castillo Posgrado en Ingeniería Agrícola y Uso Integral del Agua Universidad Autónoma Chapingo Chapingo México Department of Hydrology and Water Resources University of Arizona Tucson AZ USA

Floods have caused significant human and economic losses in the cazones River basin, located on the Gulf of Mexico. Despite this knowledge, steps towards the design and implementation of an early warning system for the cazones are still a pending task. In this study we contributed by establishing a hydrological scheme for forecasting mean daily discharges in the cazones basin. For these purposes, we calibrated, validated and compared the HyMod model (HM) which is physics-based, and an autoregressive-based model coupled with the Discrete Kalman Filter (ARX-DKF). The ability of both models to accurately predict discharges proved satisfactory results during the validation period with RMSEHYMOD = 2.77 [mm/day];and RMSEARX-DKF = [2.38 mm/day]. Further analysis based on a Streamflow Assimilation Ratio (SAR) revealed that both models underestimate the discharges in a similar proportion. This evaluation also showed that, under the most common conditions, the simpler stochastic model (ARX-DKF) performs better;however, under extreme hydrological conditions the deterministic HM model reveals a better performance. These results are discussed under the context of future applications and additional requirements needed to implement an early warning hydrologic system for the cazones basin.

关键词： Hydrologic Models cazones basin HyMod Discrete Kalman Filter Hydrologic Uncertainty

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