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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. Plain Language Summary: Lakes are essential elements of the hydrological cycle, and changes in lakes water availability affect their aquatic and terrestrial ecosystems and their associated watersheds. Monitoring water level changes is necessary to manage lake systems worldwide; however, monitoring remote and small lakes is unfeasible due to limitations of costs and access. We develop a novel approach that combines satellite remote sensing radar imagery to detect water level changes in small lakes. We used 24 small and high‐altitude unmonitored lakes in Ecuador for development and validation. We found the water level changes across lakes to be consistent with precipitation in the region. Furthermore, accumulated water level changes could be explained by differences in lake area among lakes. Our methodology underpins the underutilized potential of satellite radar observations to understand water level changes in small lakes. It also has considerable potential for the near real‐time monitoring of lake systems worldwide from space observations. Key Points: We demonstrated the utility of synthetic aperture radar interferometry to track water level changes in small ungauged lakes simultaneouslyRegional precipitation and area of lakes conditioned the spatiotemporal patterns of changes in water levelIrregular topography and surrounding elements on the lake shores were crucial for the use of radar interferometry [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The generalised likelihood uncertainty estimation (GLUE) approach was applied to assess the performance of a distributed catchment model and to estimate prediction limits after conditioning based on observed catchment-wide streamflow. Prediction limits were derived not only for daily streamflow but also for piezometric levels and for extreme events. The latter analysis was carried out considering independent partial duration time series (PDS) obtained from the observed daily streamflow hydrograph. Important data uncertainties were identified. For streamflow the stage-discharge data analysis led to estimate an average data uncertainty of about 3 m³ s-1. For piezometric levels, data errors were estimated to be in the order of 5 m in average and 10 m at most. The GLUE analysis showed that most of the inspected parameters are insensitive to model performance, except the horizontal and vertical components of the hydraulic conductivity of one of the geological layers that have the most influence on the streamflow model performance in the application catchment. The study revealed a considerable uncertainty attached to the simulation of both high flows and low flows (i.e., in average terms 5 m³ s-1 before the Bayesian updating of the prediction limits). Similarly, wide prediction intervals were obtained for the piezometric levels in relevant wells, in the order of 3.3 and 1.5 m before and after the Bayesian updating of the prediction limits, respectively. Consequently, the results suggest that, in average terms, the model of the catchment predicts overall outputs within the limitations of the errors in the input variables. [ABSTRACT FROM AUTHOR]

The article offers information on a multi-criteria protocol for evaluating the predictions of hydrologic models during calibration and evaluation stages. The protocol includes different statistical, analytical and visual criteria such as analysis of peak and low flows, cumulative volumes, performance statistics. It is cited that the protocol assesses the physical consistency of model predictions by filtering the total observed hydrograph into different flow-components. It is shown that application of the suggested protocol enhances the physical consistency of model predictions.

To support a sensitivity analysis in the framework of catchment modeling, three potential evapotranspiration (ET[sub p]) scenarios were generated by means of two Food and Agriculture Organization (FAO) approaches, namely, the FAO-24 and the FAO-56 approaches. The crop ET[sub p] was estimated as a function of the reference evapotranspiration (ET[sub o]) by means of the k[sub c]-ET[sub o] approach. Scenario A was generated with the standard FAO-24 approach; Scenario B considered also the FAO-24 approach, but with some nonstandard parameters. Scenario C considered the standard FAO-56 approach. The ET[sub o] data were compared to point-scale ET[sub o] constraints. The annual cumulative value of ET[sub o] from Scenario A was on average approximately 200 mm larger than the values from Scenarios B and C. The research revealed similar ET[sub o] estimates for Scenarios B and C. The research also assessed the performance of the angstrom approach for estimating incoming solar radiation (R[sub s]). In this context, a set of angstrom coefficients was derived by means of an optimization process that considered available R[sub s] data. [ABSTRACT FROM AUTHOR]