Management of uncertainty in hydrologic modeling is related to our ability to (a) select appropriate values for model parameters and (b) assess the extent to which their variation affects a simulated response. We focus on the application of sensitivity and uncertainty analyses to assess the influence of main parameters associated with the widely used distributed watershed model TopModel in estimating surface runoff in the area of the Middle Magdalena Valley, Colombia. We ground our study on the GLUE methodology, as included in the MCAT Toolbox. This methodology is conducive to a Regional Sensitivity Analysis (RSA), rendering global information about the relative importance of given model parameters through an a-posteriori probability function. GLUE is viewed as a first step to undertake a comprehensive global sensitivity analysis based on the statistical moments characterizing the outputs of the simulations. We do so upon relying on (a) the Sobol’ indices, associated with a classical decomposition of variance and (b) recently developed indices quantifying the relative contribution of each uncertain model parameter to the (ensemble) mean, skewness and kurtosis of the model output. Our analyses are grounded on a collection of 150.000 model simulations, each spanning a 12-year temporal window. These are constructed by assuming those model parameters are random and associated with a uniform distribution within a support of width selected on the basis of literature studies and preliminary model calibration against available data. Results of the global sensitivity analysis enable identifying a reduced set of model parameter values, showing that the parameter driving the transmissivity recession curve (associated with an exponential decrease of saturated hydraulic conductivity with depth), the maximum root zone storage deficit, and the initial subsurface flow can be considered as the most sensitive ones. Observed and simulated high values of surface runoff due to the excess of infiltration suggest a high water storage capacity of the soil and dominance of subsurface runoff processes, consistent with the local characteristics of the soils in the region.

Hydrological distributed modeling is a key point for a comprehensive assessment of the feedback between the dynamics of the hydrological cycle, climate conditions, and land use. Such modeling results are markedly relevant in the fields of water resources management. Here TopModel (TOPography based hydrological MODEL) is employed for the hydrological modeling of an area in the Middle Magdalena Valley (MMV), a tropical basin located in Colombia. This study is located in the intertropical convergence zone and is characterized by special meteorological conditions, with fast water fluxes over the year. It has been subject to significant land use changes, as a result of intense economic activities, i.e., agriculture, energy and oil & gas production. The model employees a record of 12 years of: • Daily precipitation database from observed gauges • Daily evapotranspiration database from temperature data • Streamflow database as observed data from calibration Calibration is performed using data from 2000 to 2008, and validation is performed with data from 2009 to 2012. The Nash-Sutcliffe coefficient is used to assess the robustness of our calibration process.(values of this metric being 0.62 and 0.53, respectively for model calibration and validation). The results reveal high water storage capacity in the soil, and a marked subsurface runoff, consistent with the characteristics of the soil types in the regions. The calibrated model provides relevant indications about recharge in the region, which is important to quantify the interaction between surface water and groundwater, especially during the dry season, which is more relevant in climate-change and climate-variability scenarios.