Calibration and uncertainty analysis for modelling runoff in the tambo river basin, Peru, using sequential uncertainty fitting ver-2 (SUFI-2) algorithm

Descripción del Articulo

Basin-scale simulation is fundamental to understand the hydrological cycle, and in identifying information essential for water management. Accordingly, the Soil and Water Assessment Tool (SWAT) model is applied to simulate runoff in the semi-arid Tambo River Basin in southern Peru, where economic ac...

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Detalles Bibliográficos
Autores: Chavez Alcazar, Tamar Anaharat, Carlos Mendoza, Juan Adriel
Formato: tesis de grado
Fecha de Publicación:2021
Institución:Universidad Nacional de San Agustín
Repositorio:UNSA-Institucional
Lenguaje:español
OAI Identifier:oai:repositorio.unsa.edu.pe:20.500.12773/13211
Enlace del recurso:http://hdl.handle.net/20.500.12773/13211
Nivel de acceso:acceso abierto
Materia:SWAT model
runoff simulation
Sequential Uncertainty Fitting Ver-2
Nash-Sutcliffe simulation efficiency
Tambo river
semi-arid river basin
https://purl.org/pe-repo/ocde/ford#1.05.11
Descripción
Sumario:Basin-scale simulation is fundamental to understand the hydrological cycle, and in identifying information essential for water management. Accordingly, the Soil and Water Assessment Tool (SWAT) model is applied to simulate runoff in the semi-arid Tambo River Basin in southern Peru, where economic activities are driven by the availability of water. The SWAT model was calibrated using the Sequential Uncertainty Fitting Ver-2 (SUFI-2) algorithm and two objective functions namely the Nash-Sutcliffe simulation efficiency (NSE), and coefficient of determination (R2) for the period 1994 to 2001 which includes an initial warm-up period of 3 years; it was then validated for 2002 to 2016 using daily river discharge values. The best results were obtained using the objective function R2; a comparison of results of the daily and monthly performance evaluation between the calibration period and validation period showed close correspondence in the values for NSE and R2, and those for percent bias (PBIAS) and ratio of standard deviation of the observation to the root mean square error (RSR). The results thus show that the SWAT model can effectively predict runoff within the Tambo River basin. The model can also serve as a guideline for hydrology modellers, acting as a reliable tool
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