Calibration and Uncertainty Analysis for modeling Runoff of the Tambo
River Basin, Perú, using Sequential Uncertainty Fitting (SUFI-2)
algorithm.
Abstract
Basin scale simulation is essential to understand the hydrological
cycle, specify essential information for water management, for this
reason the applicability of the Soil and Water Assessment Tool (SWAT)
model is evaluated to simulate runoff in the semiarid basin of the River
Tambo (Peru), due to the most economic activities are driven by
available water. To achieve the objective of the study, SWAT model was
configured using the basin properties such as soil type, digital
reduction model, land use, meteorological information such as
temperature, temperature of the network of meteorological stations
(SENAMHI). The SWAT model was calibrated using the SUFI-2 algorithm for
the periods from 1994 to 2001, with 3 years of warming and validated
from 2002 to 2016 using daily river discharges. The results during the
daily and monthly calibration period had Nash-Sutcliffe Simulation
Efficiency (NSE) of 0.69 and 0.86, Determination Coefficient (R2) of
0.70 and 0.87, Percent bias (PBIAS) of -14.4 and Ratio of standard
deviation of the observation of the root mean square error (RSR) of the
root of 0.55 and 0.37, respectively. For the daily and monthly
validation period, they had NSE of 0.52 and 0.70, R2 of 0.67 and 0.87,
PBIAS of -6.1 and RSR of 0.69 and 0.55, respectively. These results
indicate that the SWAT model has the ability to predict current flows
within the river basin of the Tambo Valley in southern Peru, being a
useful tool for a more detailed analysis of the effects of climate
change, change of land use, water quality analysis and sediment
performance analysis.