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Monitoring water level changes is necessary to manage, conserve and restore natural, and anthropogenic lake systems. However, the in-situ monitoring of lake systems is unfeasible due to limitations of costs and access. Furthermore, current remote sensing methods are restricted to large lakes and low spatial resolutions. We develop a novel approach using subsequential pixel-wise observations of the Sentinel-1B sensor based on interferometric synthetic aperture radar to detect water level changes in small lakes. We used 24 small ungauged lakes of the Cajas Massif lake system in Ecuador for development and validation. We found Differential Interferometric Synthetic Aperture Radar (DInSAR)-derived water level changes across lakes to be consistent with precipitation, capturing the peak of the wet seasons. Furthermore, accumulated water level changes could be explained by differences in lake area among lakes. Although with limitations, this study shows the underutilized potential of DInSAR to understand water level changes in small lakes with current radar data availability.

The Data-Based Mechanistic (DBM) model was used in conjunction with the Kalman filter (as a data assimilation technique), to predict the discharge from a sub-catchment located in the upper part of the Paute basin. The results showed that this conjunctive use of the DBM model and the Kalman filter produced better predictions of the discharge in the study site, as compared to the solely use of the DBM model; indeed, the use of the Kalman filter provided an estimate of the uncertainty associated to the use of the DBM model for forecasting purposes. These results not only motivate the future use of data mining techniques for discharge forecasting, but also encourage the use of the current tool for both, prediction as well as forecasting extreme events on Andean catchments.

The surface and groundwater hydrology of a karst catchment located in Belgium was modelled using the distributed physically based code MIKE SHE. The calibration and validation processes were carried out through a common split-sample (i.e., temporal) analysis as well as through a more specialised multi-site (i.e., spatial) analysis. Further, a sensitivity analysis was run varying the calibrated parameters beyond their calibration values, which showed that the most sensitive parameter for the simulation of both surface as well groundwater flows, is the horizontal hydraulic conductivity of the karst layer, in congruence to what has been observed in situ. Both, the surface and groundwater model predictions can be regarded as being satisfactory

HYDRUS-1D, a one dimensional water movement and solute transport model, was applied to analyze a border irrigation event in an alfalfa plot located in the irrigation district of "La Violada" (Spain). The research encompassed monitoring of the irrigation event, the setting-up of the numerical model, model calibration and evaluation, and sensitivity analysis of the van Genuchten-Mualem parameters. Both the model predictions and field measurements clearly indicated that the soil water content was high during and following the irrigation event. The model even predicted a small evapotranspiration decrease induced by water logging and a significant contribution of capillary rise subsequently the water table rise in the adjacent plot caused by an irrigation event prior to the monitored event in the study plot. The research revealed the need for (i) the improvement of the schematization of the soil profile and the better experimental definition of key model parameters; and (ii) the derivation of more accurate data series for respectively the upper and lower boundary conditions

A Data-Based Mechanistic (DBM) model and the Nedbor-Afstromnings Model (NAM) were applied to simulate the rainfall-runoff relationship of two Andean basins, different in size, located in southern Ecuador. This article provides a comparative analysis of both modeling approaches, with emphasis on the evaluation of the model performance. The study revealed that the DBM model better mimics the rainfall-runoff system than the NAM model representing the river basin by a structure composed of three linear reservoirs.

The hydrologic and nitrate (NO3-N) leaching dynamics of a maize field were respectively modelled with DRAINMOD and DRAINMOD-N. Experimental data of a 3-year period were available for model calibration and evaluation. Data from the first two years were used for model calibration whilst data from the remaining year were used for an initial evaluation. Data collected before the 3-year experiment, during a 23-year period, were used for further “backward” (in time) evaluation. The hydrologic module was calibrated through a trial and error approach. The NO3-N leaching module was calibrated and evaluated with a Monte Carlo simulations based approach. Nine parameters describing the leaching process were studied. In total, 10,000 parameter sets were tried out. The analysis revealed an acceptable prediction of the observed drainage and NO3-N leaching time series throughout both the 3-year experimental period as well as the prior 23-year “backward” evaluation period. Nevertheless, the analysis revealed that no single set of optimal parameter values could be identified. It was found that the model performance is only sensitive to the rate of denitrification. Narrow NO3-N prediction intervals were obtained, even in the longer 23-year (“backward”) evaluation period. Apparently, the behavioural DRAINMOD-N simulations were able to acceptably reproduce the limited to moderate NO3-N leaching fluctuations that occur in the modelled system.

To better handle landscape heterogeneities in distributed hydrological modeling, an earlier work proposed a discretization based on nested levels, which leads to fully unstructured modeling meshes. Upon such a discretization, traditional numerical solutions must be adapted, especially to describe lateral flow between the unstructured mesh elements. In this paper, we illustrated the feasibility of the numeric solution of the diffusion equation, representing groundwater flow, using unstructured meshes. Thus, a two-dimensional (2D) groundwater model (BOUSS2D), adapted to convex unstructured and irregular meshes was developed. It is based on the approximation of the 2D Boussinesq equation using numeric techniques suitable for nonorthogonal grids. The handling of vertical and horizontal aquifer heterogeneities is also addressed. The fluxes through the interfaces among joined mesh elements are estimated by the finite volume method and the gradient approximation method. Comparisons between the BOUSS2D predictions and analytical solutions or predictions from existing codes suggest the acceptable performance of the BOUSS2D model. These results therefore encourage the further development of hydrological models using unstructured meshes that are capable of better representing the landscape heterogeneities.

To better handle landscape heterogeneities in distributed hydrological modeling, an earlier work proposed a discretization based on nested levels, which leads to fully unstructured modeling meshes. Upon such a discretization, traditional numerical solutions must be adapted, especially to describe lateral flow between the unstructured mesh elements. In this paper, we illustrated the feasibility of the numeric solution of the diffusion equation, representing groundwater flow, using unstructured meshes. Thus, a two-dimensional 2D groundwater model BOUSS2D, adapted to convex unstructured and irregular meshes was developed. It is based on the approximation of the 2D Boussinesq equation using numeric techniques suitable for nonorthogonal grids. The handling of vertical and horizontal aquifer heterogeneities is also addressed. The fluxes through the interfaces among joined mesh elements are estimated by the finite volume method and the gradient approximation method. Comparisons between the BOUSS2D predictions and analytical solutions or predictions from existing codes suggest the acceptable performance of the BOUSS2D model. These results therefore encourage the further development of hydrological models using unstructured meshes that are capable of better representing the landscape heterogeneities.

A distributed model was used to simulate the main hydrological processes in the Ourthe catchment, situated in the southern hilly part of Belgium. The study revealed important uncertainties associated with the current modelling, particularly with regard to the data of the groundwater system. These are likely to influence the global performance of the numerical model and as such a joint deterministic-stochastic protocol based on Monte Carlo simulations was used to calibrate the model and to assess its current prediction limits. Despite the lack of appropriate time series of observations of the groundwater system, the model performance was assessed not only on the overall simulation of streamflow but also on the prediction of hydrograph subflows for which a digital recursive filter was developed and used. The subflow estimates revealed the importance of the groundwater system as a main contributor to the streamflow. Correspondingly, the deterministic–stochastic analysis showed that the sensitivity of predictions to the horizontal saturated hydraulic conductivity of the modelled groundwater system is highest. In general, broad prediction limits were obtained. The model had some difficulties to mimic well the low flows as well as flows above 60 m3 s−1. These are believed to be the consequence of the significant data uncertainties and errors in boundary conditions, among other aspects. Nevertheless, the study revealed that considering the subflow estimates for evaluating model performance constitutes a tougher evaluation condition offering the potential of enhancing specificity in the assessment of the model prediction limits.

[ES] Se modeló la hidrología superficial y subterránea de una cuenca media con el código MIKE SHE. Se llevó a cabo un Análisis de Sensibilidad (AS) variando datos de topografía y evapotranspiración (ET), variables importantes para modelar el balance hídrico de una cuenca. Se generaron tres Modelos de Elevación Digital (MED) para preparar igual número de modelos hidrológicos difiriendo sólo en términos de la topografía. Se investigó, mediante la calibración independiente de los modelos hidrológicos, los efectos de los MED en las predicciones y en los parámetros de los modelos. En general, se observó una diferencia razonable entre los datos disponibles de elevación y los MED. Sin embargo, en particular, uno de los métodos de interpolación indujo la presencia significativa de depresiones y vías de desagüe artificiales. Paradójicamente, las predicciones del modelo hidrológico correspondiente resultaron ser las más aceptables. El análisis indicó una dependencia significativa de las predicciones