| dc.description.abstract | The study aims to understand when the effort required to run a distributed and detailed water balance model leads to effective better results, when compared with a lumped, data-parsimonious, and easier-to-apply hydrological model. The study compares the results obtained from a lumped hydrological model with the results from soil water assessment tool (SWAT) when used to estimate stream flow values from precipitation and climate data. Both models use the curve number (CN) concept, determined from land use, soil hydrologic group, and antecedent soil moisture conditions, and were run with a daily time step. The lumped model input variables and parameters are considered to be uniformly distributed throughout the watershed, while the SWAT model requires an extensive and detailed spatial data, including weather data (rainfall, temperature, humidity, wind, and solar radiation), physical characteristics of the basin (topography and drainage network), as well as soil and land use data. The effort required to fully understand SWAT formulation, to obtain the needed data and to calibrate the model, is time consuming and does not lead to significant better results, when compared with the lumped model results. The results confirm that in many situations, the simpler lumped model leads to reliable values of hydrological variables, both at a daily and monthly scale. The models’ predictability power is higher at a monthly time step, because both models fail to reproduce the daily flow values fully in a consistent way, although they are able to reproduce the overall variability. Lack of data to describe the precipitation accurately may explain the poorer model performance at the daily time step. The study concludes that when available data fail to represent the spatial distribution of the input variables and model parameters, there is little advantage in using the more complex distributed model. | |
