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Rainfall-Runoff Modeling Using the SCS-CN Method and Geographic Information Systems in the Huallaga River Basin, Peru

Author(s): Pablo Quispe Ramos; Eusebio Ingol-Blanco; Abel Mejia Marcacuzco

Linked Author(s): Eusebio Ingol-Blanco

Keywords: Precipitation - Runoff Model; Curve Number Method; Huallaga River Basin

Abstract: Surface runoff is one of the most important processes of the hydrological cycle and it is the main water source for different users in a river basin. However, its dynamics have been substantially influenced by natural variability and probably by climate change. On the other hand, in Peru, one of the fundamental problems related to water is the lack of information on the water availability of many hydrological units located in both coastal and Amazon basins, considering the influence of a changing climate in the next decades. Therefore, this research evaluates the surface runoff in the Huallaga river basin, using the curve number (CN) method coupled to geographic information systems that contributes to decision-making, planning and prediction of direct runoff. In general, the methodology includes the analysis of vegetation cover, soil types, geomorphology, digital elevation model (DEM), consistency analysis and evaluation of historical records in pluviometric and hydrometric stations, analysis of satellite images, development of the model coupled to geographic information systems, calibration and validation model, and daily flow prediction. For the meteorological data analysis, 40 rain gauge stations and records available from Peruvian Interpolated Data of the SENAMHI’s Climatological and hydrological Observations (PISCO) were used. PISCO has a high spatial resolution of 5 km x 5 km. Likewise, daily flow records from 4 hydrometric stations distributed along the Huallaga river were used for calibration and validation model, and a simple method to separate the base flow was used. The results shows that the model provides reasonable estimates of daily direct runoff that can help improve decisions in water resources planning and management in Peru's basins.

DOI: https://doi.org/10.3850/IAHR-39WC252171192022475

Year: 2022

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