Hydrological modeling allows us to make a comprehensive assessment of the interaction between dynamics of the hydrological cycle, climate conditions, and land use. These modeling results are relevant in water resources management field. We use TopModel (TOPography based hydrological MODEL for the hydrological modeling of an area of 17 000 km2 in the Middle Magdalena Valley (MMV), a tropical basin located in Colombia. This study is located in the intertropical convergence zone (ITCZ) which is characterized by special meteorological conditions and fast water fluxes over the year. This area has been subjected to significant land use changes, as a result of intense economic activities, e.g., agriculture, hydropower energy and oil & gas production (Avellaneda, 2003). The proposed model is based on a record of 12 years of: i.) daily precipitation data from observed gauges, ii.) daily evapotranspiration data from temperature data and iii.) daily streamflow data as observed data. A calibration process was performed using data from 2000 to 2008, and a validation was performed with data from 2009 to 2012. The Nash-Sutcliffe coefficient was used as an objective function to assess the quality of these processes (values of this metric are between 0.74 and 0.73 respectively, for model calibration and validation). The results show us an adequate performance of the model in areas of the tropical region and allow us to analyze the relationship between water storage capacity in the soils of the area with subsurface runoff. This conclusion is consistent with the characteristics of the region. The calibrated model provides an idea about the hydrological functioning of the basin and estimates an approximation of the groundwater recharge in the region. The estimation of the recharge is important to quantify the interaction of surface water and groundwater, especially during the dry season, due to its importance in the analysis of scenarios with climate variability.

Hydrological modeling is commonly crossed by the solution of inverse problems and the estimation for non-linear parameters techniques. Despite this common scenario, the use of these guidelines is limited to the proper sampling of in-field data. This sampling involves a variety of data that generally have little availability, especially in regions where geographical and climatic variability does not allow a constant measurement. In this article, we present the analysis of a regional underground flow model using two techniques: pilot points (PP) and constant zones (CZ). This methodologies allow identifying properly if there are any biased parameters and heterogeneity of hydraulic properties. For this purpose, we developed a numerical variable density model that is limited with reinterpreted data from real measurements. For the CZ technique, the initial parameters are assigned according to its layer, and every layer is considered constant for parameter values; in contrast for PP technique, the initial parameters are assigned according to interpolations using in-situ point measurements. The developed model was applied in an area under the influence of the ITCZ, located in the middle valley of Magdalena (MMV). This area is important on the development of the country due to its contribution to GDP and has been subject to significant changes in land use, as a result of intense economic activities, for example, agriculture, hydroelectric power, and production of oil and gas. The established model shows a scarce link with the observed state variable (hydraulic head -K), this proves the importance of spatial heterogeneity in K. The model is calibrated in order to establish K (as an anisotropic variable that varies spatially), the porosity (η) and the specific storage capacity (Ss) in the PP and CZ, reducing a “mean square” error of state variable dependable on the observation points. The results show that the PP system approach provides a better heterogeneity representation and shows that each parameter is sensitive, and does not depend on other parameters, giving to the parameter evaluation results factual independence and authenticity. This research compiles a methodology to assertively restrict a highly parameterized inverse model with field data to estimate aquifer parameters that vary spatially at a regional scale

Hydrological cycle dynamics can be simulated through continuous numerical modelling in order to estimate a water budget at different time and spatial scales, taking a specific importance when considering climate change effects on the various processes that take place on a basin. With the purpose of estimating potential impacts of climate change on the basin water balance, the present study takes place on the catchment area of the Carare-Minero river, a basin located in the Middle Magdalena Valley (Colombia), a zone in which important economic activities unfold such as stockbreeding and agriculture, where regional climate change scenarios were made for the precipitation and temperature variables, along with a continuous hydrological modeling of the basin using the HEC-HMS software. The regional scenarios for the precipitation and temperature were developed through statistical downscaling based on General Circulation Models (GCM) of the sixth phase of the Coupled Intercomparison Project (CMIP6), with projections to 2100 for seven of the new set of CO2 emission scenarios, the Shared Socioeconomic Pathways (SSP), that take into account different socioeconomic assumptions for climate policies, with a baseline of 25 years between 1990 and 2014; the emission scenarios evaluated from lowest to highest CO2 emission were SSP1-1.9, SSP1-2.6, SSP4-3.4, SSP2-4.5, SSP4-6.0, SSP3-7.0 and SSP5-8.5. The obtained data were used as an input for the model of the basin in HEC-HMS obtaining a new water balance for each scenario comparing the results with the baseline case for current conditions, resulting in an evapotranspiration increase due to higher temperatures that, alongside changes in precipitation, produces lower flows for the higher SSP’s of SSP5-8.5 and SSP3-7.0, in contrast with the low emission scenarios of SSP1-1.9 and SSP1-2.6 were the changes in temperature and precipitation are less drastic generating minor alterations in the hydrological balance.Key words: Hydrological modeling, Middle Magdalena Valley, regional climate change scenarios, water balance.

Water resources management must be in all cases, effective, efficient and sustainable, especially when considering the effects of climate change and variability effects. The challenge tackled in this research was to build a hydro-economic optimization model, which can be used as a decision-making tool for water assignment between several users in a tropical region. The model has been developed by integrating hydrological aspects (surface water and groundwater) in an economical optimization framework for water allocation and water quality management.We study a basin of 17 000 km2 located in the Colombian Middle Magdalena Valley (MMV), a central area with important economic activities, as oil and gas exploration and production (O&G), agriculture and livestock.A regional optimization model that integrates multiple water supplies and demands were designed.  The main purpose of the model is to maximize the value of water consumption. Consequently, the hydro-economic model was solved through a lineal optimization process, that links all available water resources and all water demands under the limitations of: (i) demand rising, (ii) water quality variance and (ii) offer decrease.The system considers the monthly water demand from each user and a penalty for no satisfy it. For hydro-economic analysis, the model contemplates four main study scenarios: (i) current mean condition (ESC1), (ii) at thirty years (ESC2), (iii) at fifty years (ESC3) and, (iv) at hundred years (ESC4). These scenarios show fluctuation in water demand, and water supply based on the population increase. The results show significant differences between the user's allocation regimes. This has been identified between domestic and agricultural sectors, but not between commercial activities. According to the later, it is important to include variable rates for each sector according to its productivity, in the general analysis.The defined objective function maximizes the profit in the MMV basin during a planning period of a year.  It is important to highlight that the whole system was optimized under an equitable distribution in allocation and costs, and thus, the resulting profits would improve results to satisfy all economic sectors.

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.

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.