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[Abstract:] On 9–13 February 2023 an intense flood event took place in the province of Maputo (Mozambique), resulting in severe damage to agricultural lands and transport infrastructure and with serious consequences for the population. In the district of Boane, located a few kilometres downstream of the Pequenos Libombos dam, the flood destroyed many food crops as well as two bridges linking the district to Maputo, thus affecting the food security of the population. These events are quite frequent in this region, making the delineation of improved flood hazard maps and the development of new flood risk management plans necessary. We reproduce this flood event with a high-resolution integrated hydrologic-hydraulic model fed with freely available global data sources, using a methodology that can be easily reproduced in other data-scarce regions. The model results are validated with observed estimations of the inflow to the Pequenos Libombos reservoir, with water marks left by the flood in the district of Boane, and with a Sentinel-1 image taken during the recession of the flood. We analyse the effect of the Pequenos Libombos reservoir on the flood hazard, which was subject to debate among the affected population and in the media. The results obtained show that integrated hydrologic–hydraulic models based on two-dimensional shallow-water equations, combined with global databases, are currently able to reasonably reproduce the extent and peak discharge of extreme flood events in data-scarce basins and are therefore very useful tools for the development of flood management plans in these regions.

[Abstract:] Numerical models are currently the main tool used to simulate the effects of urban flooding. The validation of these models requires thorough and accurate observed data in order to test their performance. The current study presents a series of laboratory experiments in a large-scale urban drainage physical facility of approximately 100 m2 that includes roofs, streets, inlets, manholes and sewers. The facility is equipped with a rainfall simulator as well as a surface runoff and pipe inflows generators. The experiments were divided in two sets. In Set 1 the surface runoff was generated exclusively by the rainfall input, while in Set 2 the rainfall simulator was used in combination with the runoff generators. In all the tests the water discharge was measured at points on the inlets, roofs, and outfall. The water depth at different locations of the facility was also measured. The experimental tests were replicated numerically using the urban drainage model Iber-SWMM. Experimental results show that, even in a relatively small catchment the peaks in the hydrographs generated at each element of the facility during intermittent rainfalls are significantly attenuated at the catchment outlet. The agreement between the experimental and numerical results show that there are some differences in the hydrographs generated at each element, but that these differences compensate each other and disappear at the outfall. The results generated provide the research community with a thorough and high-resolution dataset obtained under controlled laboratory conditions in a large-scale urban drainage facility, something which has not previously been available.

[Abstract:] Badlands are often the source of a significant fraction of the sediment reaching the river network due to the exposure of the bare soil to the impact of rain drops and to the bed shear stress generated by the surface runoff. Hence, a correct understanding of the soil erosion and sediment transport processes inside badlands can help to a better characterisation of the suspended sediment production at the catchment scale. In this work we study the suitability of a two-dimensional (2D) physically-based event-scale erosion model as a tool to represent soil erosion and sediment transport in badlands at a seasonal scale. The model solves the 2D shallow water equations, including infiltration and rainfall, in order to compute the generation and routing of surface runoff within the badland. Coupled to the hydrodynamic equations, the model solves a 2D suspended sediment transport equation with source terms that account for rainfall- and runoff-driven erosion and sediment deposition. Based on this model, an overall procedure was developed and tested considering, as case study, a badland located in El Soto catchment (central Pyrenees, Iberian Peninsula). For the analysed badland, several high-resolution topography surveys were available, which allowed for the estimation of the soil loss and the spatial distribution of erosion patterns for periods of 3-4 months over two years. These data sets were used to calibrate and validate the proposed modelling approach, and to analyse its capabilities and limitations for the assessment of soil erosion at the seasonal scale.

[Abstract:] Floods in Villahermosa are events that have occurred frequently over the centuries, due to the city’s location at the mouth of two of the most powerful rivers in Mexico. Flooding effects on residents have become increasingly damaging over the years as a consequence of the increase in frequency and intensity of extreme weather phenomena, in addition to poor land-use planning policies. The increase in population and consequent urban expansion are certainly causes of the problem, which are reflected in poor urban planning policy and in an almost absent perception of risk. In this work, we present a methodology for the construction of flood risk maps based on a hydraulic study, analysis of social vulnerability indexes, calculation of severity indexes and construction of hazard maps. The results of the hydraulic simulations show that relatively frequent rainfall causes floods of the order of 2 m, in agreement with annual observations conducted in Villahermosa. More extreme rainfall can lead to flooding greater than 4 m in marginalized areas of the city. The areas at greatest risk are sections close to the rivers that cross the city, and the estimated economic damage is greater than USD 14 million. Risk maps presented here constitute the first effort of an integrated study to couple flood analysis with the calculation of economic damage in the city of Villahermosa, and provide important tools to conscientize populations in their perception of risk, but also create the basis for a conscious urbanization policy.

[Abstract:] Study Region: The present study was conducted in 24 watersheds located in the region of Galicia, in the northwest of Spain, covering an extension of approximately 13,000 km. Study focus: This study is focused on the application and evaluation of different schemes for streamflow Prediction in Ungauged Basins (PUB). The MHIA model (Spanish acronym for Modelo HIdrológico Agregado), is first used to reproduce the observed time series of discharge in several gauged basins. Then, six different regionalisation schemes are applied to transfer the hydrological model parameters to ungauged catchments. For that purpose, we explore and compare two physical similarity, two spatial proximity and two regression-based regionalisation schemes. Output averaging (also known as ensemble modelling) as well as parameter averaging implementations of the physical similarity and spatial proximity methods are analysed. New hydrological insights: The most efficient methods are those based on output averaging, with acceptable success rates (SR) in 88% of the cases. On the other hand, the parameter averaging-based methods have the lowest SR. The methods based on spatial proximity output averaging provide the best performance when the receptor basin has a sufficient number of nearby donor basins. On the other hand, the methods based on physical similarity output averaging show a better performance in areas where there is a low density of donor catchments. The regression-based methods showed the lowest performance in all cases. The existence of correlations between the performance of the regionalisation schemes and the area of the receptor catchments was observed, with higher performances in large basins than in small basins.

[Resumen:] La consideración del efecto laminador de los embalses en la evaluación de caudales de avenida es un aspecto fundamental en aquellas cuencas donde la hidrología está condicionada por la presencia de presas. En este trabajo se presenta la implementación de embalses y presas en el módulo hidrológico del modelo Iber, el cual resuelve las ecuaciones de aguas someras bidimensionales a escala de toda una cuenca. Para la modelización del caudal de salida del embalse se incluyen aliviaderos con y sin compuerta, desagües de fondo y la posibilidad de definir una curva de desagüe ad hoc que relacione el caudal de salida con el nivel del embalse. Como caso de estudio se modeló el efecto del embalse de Iznájar en la hidrología de la cuenca del río Genil, en España. Se consideraron tres hipótesis de cálculo con el fin de comparar el efecto de los diferentes órganos de desagüe definidos en esta nueva implementación en Iber. La metodología definida demuestra ser capaz de representar numéricamente los órganos de gestión del embalse y resolver así una limitación fundamental en el modelado de grandes cuencas con Iber., [Abstract:] Accounting for the flood routing effect of reservoirs in the assessment of flood discharges is essential in basins where the hydrology is conditioned by the presence of one or more dams. This paper presents the implementation of reservoirs and dams in the hydrological module of the software Iber, which solves the two-dimensional shallow water equations at the scale of an entire basin. Spillways with and without gates, low level outlets, and the possibility to define an ad hoc outflow curve relating the flow rate to the reservoir level are included. As a case study, the effect of the Iznájar reservoir on the hydrology of the Genil basin in Spain was modelled. Three scenarios were considered to compare the effect of the different outflow structures included in this new implementation in Iber. The defined methodology proves to be able to represent numerically the outflow structures, addressing a fundamental limitation in the modelling of large basins with Iber.

[Abstract:] Ensemble modelling is a numerical technique used to combine the results of a number of different individual models in order to obtain more robust, better-fitting predictions. The main drawback of ensemble modeling is the identification of the individual models that can be efficiently combined. The present study proposes a strategy based on the Random-Restart Hill-Climbing algorithm to efficiently build ANN-based hydrological ensemble models. The proposed technique is applied in a case study, using three different criteria for identifying the model combinations, different number of individual models to build the ensemble, and two different ANN training algorithms. The results show that model combinations based on the Pearson coefficient produce the best ensembles, outperforming the best individual model in 100% of the cases, and reaching NSE values up to 0.91 in the validation period. Furthermore, the Levenberg-Marquardt training algorithm showed a much lower computational cost than the Bayesian regularisation algorithm, with no significant differences in terms of accuracy.

[Abstract:] The backwater effect generated by bridges can significantly increase the risk of flooding. In this work we compare two different methods to include the effect of bridges in two-dimensional (2D) shallow water models. The first method is based on empirical discharge equations that are implemented as internal conditions. The second method is the recently proposed 2D extension of the two-component pressure approach, which accounts for the vertical confinement of the flow. Both approaches are tested and compared using a new set of experimental data obtained in 32 laboratory tests, including four different bridge geometries under different flow conditions. The results show that both methods can reproduce the observed bridge afflux for a wide range of flow conditions, but the two-component pressure approach is less dependent on model calibration. On the other hand, both methods fail to correctly reproduce the 2D water depth patterns observed around the bridge.

[Abstract:] Numerical models based on the two-dimensional shallow water equations (2D-SWE) are routinely used in flood risk management and inundation studies. However, most of these models do not adequately account for vertically confined flow conditions that can appear during inundations, due to the presence of hydraulic structures such as bridges, culverts, or underground river reaches. In this article we propose a new mathematical modification of the standard 2D-SWE, inspired by the two-component pressure approach for 1D flows, to address the issue of transient vertically confined flows including transitions between free surface and pressurized conditions. A finite volume discretization to solve the proposed system of equations is proposed and analyzed. Various test cases are used to show the numerical stability and accuracy of the discretization, and to validate the proposed formulation. Results show that the proposed method is numerically stable, accurate, mass conservative, and preserves the C-property. It can also handle subcritical, supercritical, and transcritical flows under free surface or vertically confined conditions.

[Abstract:] Hydrological models are widely used tools in water resources management. Their successful application requires an efficient calibration of the model parameters. Nowadays, there are very powerful global search methods applied to this end, but they have the disadvantage of presenting a high computational cost, because the numerical model to be calibrated needs to be evaluated a large number of times with different parameter sets. In this context, surrogate models can reduce significantly the run time of hydrological models, easing the total computational burden of global search methods. In the present work, we propose and explore the combination of a swarm intelligence-based optimization method, the artificial bee colony algorithm, with a surrogate model based on artificial neural networks in order to calibrate hydrological models. The proposed approach (ABC-ANN) is applied to the calibration and validation of a nine-parameter continuous hydrological model in two basins located in the northwest of Spain. Several aspects of the algorithm are evaluated, including its capability to calibrate the model parameters and its efficiency in terms of CPU time compared to a standard implementation of the ABC algorithm. Results show that the ABC-ANN algorithm is able to identify the location of suitable parameter sets with an accuracy rate within 89 and 99 %, and a reduction in CPU time of more than three orders of magnitude when compared to a sequential implementation. In addition, the frequency distribution of the parameter sets identified gives valuable information about the sensitivity of model output to the input parameters.

[Abstract:] Global warming is changing the magnitude and frequency of extreme precipitation events. This requires updating local rainfall intensity-duration-frequency (IDF) curves and flood hazard maps according to the future climate scenarios. This is, however, far from straightforward, given our limited ability to model the effects of climate change on the temporal and spatial variability of rainfall at small scales. In this study, we develop a robust method to update local IDF relations for sub-daily rainfall extremes using Global Climate Model (GCM) data, and we apply it to a coastal town in NW Spain. First, the relationship between large-scale atmospheric circulation, described by means of Lamb Circulation Type classification (LCT), and rainfall events with potential for flood generation is analyzed. A broad ensemble set of GCM runs is used to identify frequency changes in LCTs, and to assess the occurrence of flood generating events in the future. In a parallel way, we use this Weather Type (WT) classification and climate-flood linkages to downscale rainfall from GCMs, and to determine the IDF curves for the future climate scenarios. A hydrological-hydraulic modeling chain is then used to quantify the changes in flood maps induced by the IDF changes. The results point to a future increase in rainfall intensity for all rainfall durations, which consequently results in an increased flood hazard in the urban area. While acknowledging the uncertainty in the GCM projections, the results show the need to update IDF standards and flood hazard maps to reflect potential changes in future extreme rainfall intensities.

[Abstract:] Droughts are one of the most damaging and complex natural disasters in the world, and they frequently affect agricultural production. Drought monitoring is essential for decision-makers seeking to minimize the socio-economic impacts related to drought events. In this study, we propose a methodology to identify the most suitable drought indices and data sources for monitoring the impact of drought on crops. Mozambique is used as a case study, as it represents a challenging example because of its poor hydroclimatic monitoring network and a lack of disaggregated data for agricultural production. A total of seven standardized drought indicators (SPI, SPEI, SSI, SVCI, STCI, SVHI, and STWS) at different scales (1, 3, 6, and 12 months) were obtained from global databases and evaluated as possible predictors of the annual variability of agricultural yields at the national level. A statistical model of crop yields based on time series was used to measure the explanatory capacity of each index. SPEI and SSI were the most effective at detecting the country's historical drought records regardless of whether nationally averaged values or the percentages of area affected by drought (PAA) were used. However, PAA was found to be a more accurate predictor of variability in crop yields. The variability of most cereals (maize, millet and sorghum) was adequately explained by the PAA of SPEI-3, with that of other crops (cashew nuts, cassava, potatoes, tea, tobacco and vegetables) being explained by the PAA of SSI-12. Specific indicators were proposed for monitoring wheat and sugar cane. These results can directly support managers and decision makers in developing drought contingency plans in Mozambique. To further demonstrate the potential of this methodology, it should be tested in other regions with a greater availability of agricultural data, including spatial disaggregation.

[Abstract:] This study presents MERLIN, an innovative flood hazard forecasting system for predicting discharges and water levels at flood prone areas of coastal catchments. Discharge forecasts are preceded by a hindcast stage. During this stage, the hydrological models assimilate soil moisture and hydro-meteorological observations to evaluate soil infiltration capacities at the beginning of the discharge forecast. Predicted discharges are converted to water-level forecasts using the hydraulic model Iber+, a GPU-parallelized bidimensional flow model. Hydraulic models also assimilate tidal-level forecasts in order to define the boundary conditions of the models. The performance of MERLIN was evaluated over 4 months at three coastal catchments of 4.95, 16.96, and 83.9 km2. Forecasted discharges and water levels presented a good fit to observed values, especially at the larger catchments, which confirmed the potential utility of the presented system.

[Abstract:] This paper analyses the effect of rain data uncertainty on the performance of two hydrological models with different spatial structures: a semidistributed and a fully distributed model. The study is performed on a small catchment of 19.6 km2 located in the north-west of Spain, where the arrival of low pressure fronts from the Atlantic Ocean causes highly variable rainfall events. The rainfall fields in this catchment during a series of storm events are estimated using rainfall point measurements. The uncertainty of the estimated fields is quantified using a conditional simulation technique. Discharge and rain data, including the uncertainty of the estimated rainfall fields, are then used to calibrate and validate both hydrological models following the generalized likelihood uncertainty estimation (GLUE) methodology. In the storm events analysed, the two models show similar performance. In all cases, results show that the calibrated distribution of the input parameters narrows when the rain uncertainty is included in the analysis. Otherwise, when rain uncertainty is not considered, the calibration of the input parameters must account for all uncertainty in the rainfall–runoff transformation process. Also, in both models, the uncertainty of the predicted discharges increase in similar magnitude when the uncertainty of rainfall input increase.

[Abstract:] Flooding in coastal river reaches is the result of complex interactions between coastal and inland drivers. Flood hazard assessments need to consider how these drivers interact in space and time, for which a standard method is currently lacking. A complex hydrodynamic model is required to reproduce the physics of the combined forcings and, at the same time, to fully explore the combinations of drivers that can occur in order to determine extreme flood frequencies. In this work, we explore the individual role of astronomical tide, storm surge and river discharge and their correlations in the extreme flood levels of a coastal river reach. We apply a computationally efficient surrogate model of a 2D shallow water model based on least squares support vector machines regression to reconstruct 10,000 years-long time series of water levels in the reach. As input to the model, we consider an ensemble of synthetic time series of the flood drivers, which differ in the number of variables considered and in their correlations. Probabilities of exceedance of water levels are then computed and compared. The proposed methodology can give a better understanding of the flooding processes in a multivariable environment, as low-lying coastal urban areas typically are, and can provide guidance on where to focus modelling efforts when developing flood hazard assessments in such areas.

[Abstract:] Two-dimensional shallow water models are widely used tools for flood inundation mapping. However, even if High Performance Computing techniques have greatly decreased the computational time needed to run a 2D inundation model, this approach remains unsuitable for applications that require results in a very short time or a large number of model runs. In this paper we test a non-parametric regression model based on least squares support vector machines as a computationally efficient surrogate of the 2D shallow water equations for flood inundation mapping. The methodology is initially applied to a synthetic case study consisting of a straight river reach flowing towards the sea. A coastal urban area is then used as a real test case. Discharge in three streams and tide levels are used as predictor variables to estimate the spatial distribution of maximum water depth and velocity in the study area. The suitability of this regression model for the spatial prediction of flood hazard is evaluated. The results show the potential of the proposed regression technique for fast and accurate computation of flood extent and hazard maps.

[Abstract:] Deep slot fishways (DSF) are similar to vertical slot fishways (VSF) except that a sill has been placed at the base of the slot, and thus require a lower discharge to operate. The conversion of a VSF to a DSF, which requires minimal design modifications, can make for a more flexible design in inflow management, maintaining the correct operation of the fishway in periods of limited water availability. It is, however, crucial to understand the new flow conditions that will be created inside the fishway, and their implications for fish passage. In this paper, the hydrodynamics of DSF were studied for two different pool configurations and five sill heights. The investigation comprised the analysis of the water surface configuration, the velocity and turbulence fields, as well as the definition of the equations that related discharges to depths in the pools. The DSF designs compared well in terms of water surface patterns and maximum velocities with VSFs, but resulted in a more complex three-dimensional flow pattern and increased turbulence levels. Further testing with fish is needed to analyze whether the benefits of retrofitting a VSF by adding a sill during low flows are cancelled out by increased fish passage difficulty.

[Abstract:] Considering the joint probability of occurrence of high sea levels and river discharges, as well as the interactions between these sources of flooding, is of major importance to produce realistic inundation maps in river reaches affected by the sea level. In this paper, we propose a continuous simulation method for the estimation of extreme inundation in coastal river reaches. The methodology combines the generation of synthetic long-term daily time series of river discharge and sea level, the downscaling of daily values to a time resolution of a few minutes, the computation of inundation levels with an unsteady high-resolution two-dimensional model and the use of interpolation techniques to reconstruct long-term time series of water surface from a limited number of characteristic cases. The method is especially suitable for small catchments with times of concentration of a few hours, since it considers the intradiurnal variation of river discharge and sea level. The methodology was applied to the coastal town of Betanzos (NW of Spain), located at a river confluence strongly affected by the sea level. Depending on the return period and on the control point considered, the results obtained with the proposed methodology show differences up to 50 cm when compared with the standard methodology used in this region for the elaboration of flood hazard maps in accordance with the requirements of the European Directives. These results indicate the need for adaption of the standard methodology in order to produce more realistic results and a more efficient evaluation of flood hazard mitigation measures.

[Abstract:] Rainfall-runoff models are frequently used for the prediction of flood discharges from extreme rainfall data in poorly gauged basins. However, the conventional methods used to estimate the frequency of flood discharges from precipitation data do not incorporate a realistic representation of the spatial and temporal structure of rainfall at the study site nor of the antecedent soil moisture content. Temporally and spatially idealized rainfall patterns that do not represent properly the intraevent variability of rainfall are in general assumed. In this paper, we propose a methodology for flood frequency analysis based on the hydrological simulation of potentially hazardous real storm events. The aim of the proposed method is to incorporate the impact of the spatial and temporal intraevent variability of rainfall on flood discharge estimates without making strong assumptions about the spatial and temporal patterns of storms. It also includes a calibrated relation between the antecedent rainfall depth and the soil infiltration capacity, in order to consider the combined effect of antecedent soil moisture content and rainfall intensity. The flood frequency estimates obtained with the proposed methodology are compared to those estimated with a conventional method based on the definition of synthetic design hyetographs from local intensity-duration-frequency curves. The analysis is presented in two watersheds of 84 and 353 km2 located in the NW of Spain. Results highlight the role of the antecedent soil moisture in flood frequency analysis and show that the conventional methodology tends to overestimate the flood discharges when compared to the proposed approach.

[Resumen:] Las desembocaduras, estuarios y tramos de ríos costeros son elementos hidrodinámicamente complejos debido a la interacción de varias dinámicas generadoras de inundación como la marea astronómica, la marea meteorológica, el oleaje y el caudal del río, entre otras. La marea astronómica es una onda larga que se propaga aguas arriba llegando a afectar a tramos de río situados a decenas de kilómetros de la costa. En estos tramos de río, el mismo nivel del agua puede ser el resultado de diferentes combinaciones de las dinámicas mencionadas. Los estudios de peligrosidad y riesgo de inundación en tramos de ríos afectados por la marea se han basado hasta ahora en la aplicación de una condición de contorno de nivel de marea fijada de forma más o menos arbitraria. En España, la Guía metodológica para el desarrollo del Sistema Nacional de Cartografía de Zonas Inundables (Ministerio de Medio Ambiente y Medio Rural y Marino, 2011), consciente de la complejidad de los procesos y en aras de simplificar, aconseja aplicar una condición de contorno de nivel correspondiente al mismo periodo de retorno que el de la avenida que se esté modelizando. Esta forma de proceder no tiene en cuenta la probabilidad de ocurrencia de varios eventos extremos al mismo tiempo. En este artículo se propone una metodología híbrida de simulación continua que combina la generación de series sintéticas a largo plazo de las variables implicadas, un modelado hidrodinámico bidimensional de alta resolución espacial de la zona de estudio, y técnicas estadísticas de muestreo de datos e interpolación de resultados. La metodología propuesta se ha aplicado a la ciudad costera de Betanzos (noroeste de España), localizada en la confluencia de dos ríos y en la cola de un estuario. Históricamente Betanzos ha tenido problemas de inundación por lo que está catalogada como un Área de Riesgo Potencial Significativo de Inundación (ARPSI) fluvial y costera. Los resultados se han comparado con los obtenidos aplicando, [Abstract:] The hydrodynamics of coastal river reaches is complex due to the interaction of several sources of flooding as the astronomical tide, surge, wave set-up and river discharge. The tidal level might affect several km of river reach. In those reaches, the same inundation water level can result from different combinations of the sea level ad river discharge. At the present time, most flood inundation studies in tidal river reaches are based in the application of an arbitrary sea level at the downstream river boundary, without considering the interaction and possible correlations between sea level and river discharge. In Spain, the Guía Metodológica para el Desarrollo del Sistema Nacional de Cartografía de Zonas Inundables (Ministerio de Medio Ambiente y Medio Rural y Marino, 2011), recommends to consider the simultaneous occurrence of a sea level and river discharge associated to the same return period. This approach does not consider the probability of simultaneous occurrence of extreme sea level and river discharge. In order to improve this excessively simple and conservative approach, in this paper we propose a continuous simulation methodology that combines the generation of synthetic long-term time series of river discharge and sea level, 2D inundation modelling at a high spatial resolution and statistical sampling and interpolation techniques. The proposed methodology is applied to the coastal town of Betanzos (NW of Spain), which is classified as a high potential flood risk area by the regional authorities. The town is located at the confluence of two river reaches, in the inner part of Betanzos estuary. The inundation levels obtained with the proposed methodology are compared to those obtained with the standard methodology recommended by the Guía Metodológica para el Desarrollo del Sistema Nacional de Cartografía de Zonas Inundables (Ministerio de Medio Ambiente y Medio Rural y Marino, 2011). Results show that the standard methodology overestimates in

[Abstract:] Inflow discharge and outflow stage estimates for hydraulic flood models are generally derived from river gauge data. Uncertainties in the measured inflow data and the neglect of rainfall-runoff contributions to the modeled domain downstream of the gauging locations can have a significant impact on these estimated “whole reach” inflows and consequently on flood predictions. In this study, a method to incorporate rating curve uncertainty and local rainfall-runoff dynamics into the predictions of a reach-scale flood model is proposed. The methodology is applied to the July 2007 floods of the River Severn in UK. Discharge uncertainty bounds are generated applying a nonparametric local weighted regression approach to stage-discharge measurements for two gauging stations. Measured rainfall downstream from these locations is used as input to a series of subcatchment regional hydrological model to quantify additional local inflows along the main channel. A regional simplified-physics hydraulic model is then applied to combine these contributions and generate an ensemble of discharge and water elevation time series at the boundaries of a local-scale high complexity hydraulic model. Finally, the effect of these rainfall dynamics and uncertain boundary conditions are evaluated on the local-scale model. Accurate prediction of the flood peak was obtained with the proposed method, which was only possible by resolving the additional complexity of the extreme rainfall contributions over the modeled area. The findings highlight the importance of estimating boundary condition uncertainty and local rainfall contributions for accurate prediction of river flows and inundation at regional scales.

[Abstract:] In this paper, we analyse how the performance and calibration of a distributed event-based soil erosion model at the hillslope scale is affected by different simplifications on the parameterizations used to compute the production of suspended sediment by rainfall and runoff. Six modelling scenarios of different complexity are used to evaluate the temporal variability of the sedimentograph at the outlet of a 60 m long cultivated hillslope. The six scenarios are calibrated within the generalized likelihood uncertainty estimation framework in order to account for parameter uncertainty, and their performance is evaluated against experimental data registered during five storm events. The Nash–Sutcliffe efficiency, percent bias and coverage performance ratios show that the sedimentary response of the hillslope in terms of mass flux of eroded soil can be efficiently captured by a model structure including only two soil erodibility parameters, which control the rainfall and runoff production of suspended sediment. Increasing the number of parameters makes the calibration process more complex without increasing in a noticeable manner the predictive capability of the model.

[Abstract:] This paper presents a new freeware simulation tool (IberWQ) for 2D water quality modelling in rivers and non-stratified estuaries. The model computes the spatial and temporal evolution of several species and variables which are relevant for the evaluation of the environmental status of rivers and estuaries, including: Escherichia coli, dissolved oxygen, carbonaceous biochemical oxygen demand, organic nitrogen, ammoniacal nitrogen, nitrate–nitrite nitrogen, water temperature and salinity. A depth-averaged transport equation is solved for each variable with a mass conservative unstructured finite volume solver. IberWQ is fully coupled to the hydrodynamic module of the software Iber, a freeware simulation tool for solving the 2D shallow water equations. Both models are integrated in the same windows graphical environment, including several tools which allow the user to generate unstructured meshes adapted to the site topography, define spatially variable input parameters and visualize model outputs. We present four application examples to illustrate the possibilities of the software for the dynamic simulation of water quality in rivers and estuaries.

[Resumen:] La modelización numérica del flujo de agua en ríos es una herramienta que ayuda a dar respuesta a la legislación vigente europea y española referida a riesgo de inundación. Los modelos numéricos disponibles actualmente se encuentran en constante evolución. Mientras hace una década la modelización unidimensional era prácticamente la única alternativa, en el presente se han generalizado los modelos bidimensionales y se empiezan a utilizar los tridimensionales. Gracias a las actuales herramientas SIG, los resultados de la modelización numérica se pueden combinar con datos georreferenciados para realizar una cuantificación sistemática del riesgo de inundación. En este proceso existen aún una serie de desafíos como la consideración de los caudales sólidos y sus efectos en la morfología del cauce, una correcta descripción del flujo en puentes y estructuras, la integración de modelos hidrológicos con los modelos hidráulicos para una mejor consideración de las condiciones de contorno, y finalmente la optimización de las herramientas para disminuir los tiempos de cálculo actuales., [Abstract:] At the present time there is a strong demand from policy makers for reliable predictions of the effects of climate and land use changes on inundation risk, in order to meet the targets specified in the EU Water Framework Directive. Numerical models are a valuable predictive tool to support decision-making related to the implementation of water and flood risk management strategies. While a decade ago one-dimensional modelling was the most commonly used tool in inundation studies, at the present time the application of two-dimensional models to river inundation modelling is generalized. Combined with GIS tools, the water depth and velocity results of a 2D model can be efficiently combined with land use data in order to quantify the potential damages caused by a certain inundation. Nevertheless, in order to improve the reliability of the numerical predictions, a number of challenges should be addressed in current models, as: modelling the interaction between hydrodynamics, solid loads, and morphologic changes during extreme flood events; a correct characterisation of head losses and flow through bridges with complex geometries; the integration of hydrological and hydraulic models for a better consideration of boundary conditions; and the implementation of efficient parallelization techniques in order to reduce the computational time and increase the scale of the problems which can be addressed with 2D and 3D models.