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Global radiation is a key climate input in process-based models (PBMs) for forests, as it determines photosynthesis, transpiration and the canopy energy balance. While radiation is highly variable at a fine spatial resolution in complex terrain due to shadowing effects, the data required for PBMs that are currently available over large extents are generally at a spatial resolution coarser than ∼9 km. Downscaling large-scale radiation data to the high resolution available from digital elevation models (DEMs) is therefore of potential importance to refine global radiation estimates and improve PBM estimations. In this study, we introduced a new downscaling model that aims to refine sub-daily global radiation data obtained from climate reanalysis data or projections at large scales to the resolution of a given DEM. First, downscaling involves splitting radiation into a direct and diffuse fraction. The influences of surrounding mountains' shade on direct radiation and the "bowl" (deep valley) effect (or sky-view factor) on diffuse radiation are then considered. The model was evaluated by comparing simulated and observed radiation at the Mont Ventoux study site (southeast of France) using the recent ERA5-Land hourly data available at a 9 km resolution as input and downscaled to different spatial resolutions (from 1 km to 30 m resolution) using a DEM. The downscaling algorithm improved the reliability of radiation at the study site, in particular at scales below 150 m. Finally, by using two different PBMs (CASTANEA, a PBM simulating tree growth, and SurEau, a plant hydraulic model simulating hydraulic failure risk), we showed that accounting for fine-resolution radiation can have a great impact on predictions of forest functions. [ABSTRACT FROM AUTHOR]

Flooding is one of the world's most common and costly natural hazards, inflicting billions in damages each year. However, current hydraulic models to support flood mapping are not well suited for large-scale applications or frequent updates, either due to limited accuracy of simple methods or lack of scalability (i.e., large computational requirements) for more sophisticated hydrodynamic models. This results in flood maps being decades out of date or simply nonexistent in some areas. Recent advances in generating flood maps have been made seemingly in parallel between geospatial methods and hydrodynamic models, such as the Height Above Nearest Drainage (HAND) method, hybrid 1D-2D hydrodynamic models and more efficient computing of 2D models. This study presents the Geospatially Augmented Standard Step (GASS) method, which combines a novel improvement to the HAND method, Dynamic Height Above Nearest Drainage (DHAND), with a 1D hydraulic model for rapid flood inundation mapping at large scales while maintaining the accuracy of hydrodynamic models. This method is implemented into a new modelling software package called Blackbird, and is benchmarked in two case studies, including a verification of the code and a benchmark test comparing multiple approaches in the ability to approximate 2D model results. The Blackbird model vastly outperforms the simpler HAND-Manning method and also outperforms a traditional HEC-RAS 1D model when evaluated for accuracy of approximating a 2D model benchmark. This new method is shown to reduce the incidence of falsely predicting flooded areas through improved resolution of landscape connections over HAND-based or 1D hydraulic models. Blackbird also streamlines the model development effort relative to existing 1D or 2D models while maintaining a computational speed that was 10, 000 times less than a comparable 2D model in one case study. The method also allows for future integration of hydraulic structures, ice jams and other features that are unavailable in HAND-based models. Overall, the GASS method provides a viable option for large-scale and real-time fluvial flood mapping applications. [ABSTRACT FROM AUTHOR]

With the recurrence of flooding in African cities, there is growing interest in the development of sufficiently informative tools to help characterize and predict overflow risks. One of the challenges is to develop methods that strike a compromise between the accuracy of simulations, the availability of basic data, and the shortening of calculation times to be compatible with real-time applications. The present study, carried out on the urban outskirts of Dakar, aims to propose a method capable of modeling flows at fine resolution (5 m2), over the entire area, and providing a rapid diagnosis of how the drainage network is operating for rainfall intensities of different return periods, while taking urban conditions into account. Three methodological steps are combined to achieve this objective: i) determination of drainage directions, including modifications induced by buildings, artificial drainage and storage basins, ii) application of a hydrological model for calculating flows at the outlets of elementary catchment, iii) the implementation of a hydraulic model for propagating these flows through the drainage network and a storage model for retention basins. The network overflow points are calculated as the difference between the calculated flows and the network's capacity to evacuate them. Simulation results show that the stormwater drainage network is capable of evacuating runoff volumes generated by rainfall with a low return period (10 years), but seems to overflow for rainfall with a rare frequency (100 years), with overflow rates sometimes exceeding 18 m3/s. The model, built on the ATHYS modelling platform, also provides boundary conditions for applying more complex hydraulic models to determine the local impact of drainage network overflows on limited areas. [ABSTRACT FROM AUTHOR]

The calibration of macroscale hydrological models is often challenged by the lack of adequate observations of river discharge and infrastructure operations. This modeling backdrop creates a number of potential pitfalls for model calibration, potentially affecting the reliability of hydrological models. Here, we introduce a novel numerical framework conceived to explore and overcome these pitfalls. Our framework consists of VIC-Res (a macroscale model setup for the Upper Mekong Basin), which is a novel variant of the Variable Infiltration Capacity (VIC) model that includes a module for representing reservoir operations, and a hydraulic model used to infer discharge time series from satellite data. Using these two models and global sensitivity analysis, we show the existence of a strong relationship between the parameterization of the hydraulic model and the performance of VIC-Res – a codependence that emerges for a variety of performance metrics that we considered. Using the results provided by the sensitivity analysis, we propose an approach for breaking this codependence and informing the hydrological model calibration, which we finally carry out with the aid of a multi-objective optimization algorithm. The approach used in this study could integrate multiple remotely sensed observations and is transferable to other poorly gauged and heavily regulated river basins. [ABSTRACT FROM AUTHOR]

Uncrewed aerial vehicles (UAVs), affordable precise global navigation satellite system hardware, multi-beam echo sounders, open-source 3D hydrodynamic modelling software, and freely available satellite data have opened up opportunities for a robust, affordable, physics-based approach to monitoring river flows. Traditional methods of river discharge estimation are based on point measurements, and heterogeneity of the river geometry is not contemplated. In contrast, a UAV-based system which makes use of geotagged images captured and merged through photogrammetry in order to generate a high-resolution digital elevation model (DEM) provides an alternative. This UAV system can capture the spatial variability in the channel shape for the purposes of input to a hydraulic model and hence probably a more accurate flow discharge. In short, the system can be used to produce the river geometry at greater resolution so as to improve the accuracy in discharge estimations. Three-dimensional hydrodynamic modelling offers a framework to establish relationships between river flow and state variables such as width and depth, while satellite images with surface water detection methods or altimetry records can be used to operationally monitor flows through the established rating curve. Uncertainties in the data acquisition may propagate into uncertainties in the relationships found between discharge and state variables. Variations in acquired geometry emanate from the different ground control point (GCP) densities and distributions used during photogrammetry-based terrain reconstruction. In this study, we develop a rating curve using affordable data collection methods and basic principles of physics. The basic principal involves merging a photogrammetry-based dry bathymetry and wet bathymetry measured using an acoustic Doppler current profiler (ADCP). The output is a seamless bathymetry which is fed into the hydraulic model so as to estimate discharge. The impact of uncertainties in the geometry on discharge estimation is investigated. The impact of uncertainties in satellite observation of depth and width is also analysed. The study shows comparable results between the 3D and traditional river rating discharge estimations. The rating curve derived on the basis of 3D hydraulic modelling was within a 95 % confidence interval of the traditional gauging-based rating curve. The 3D-hydraulic-model-based estimation requires determination of the roughness coefficient within the stable bed and the floodplain using field observation at the end of both the dry and wet season. Furthermore, the study demonstrates that variations in the density of GCPs beyond an optimal number have no significant influence on the resultant rating relationships. Finally, the study observes that which state variable approximation (water level and river width) is more accurate depends on the magnitude of the flow. Combining stage-appropriate proxies (water level when the floodplain is entirely filled and width when the floodplain is filling) in data-limited environments yields more accurate discharge estimations. The study was able to successfully apply advanced UAV and real-time kinematic positioning (RTK) technologies for accurate river monitoring through hydraulic modelling. This system may not be cheaper than in situ monitoring; however, it is notably more affordable than other systems such as crewed aircraft with lidar. In this study the calibration of the hydraulic model is based on surface velocity and the water depth. The validation is based on visual inspection of an RTK-based waterline. In future studies, a larger number of in situ gauge readings may be considered so as to optimize the validation process. [ABSTRACT FROM AUTHOR]

Advances in geodetic altimetry instruments are providing more accurate measurements, thus enabling satellite missions to produce useful data for narrow rivers and streams. Altimetry missions produce spatially dense land and water surface elevation (WSE) measurements in remote areas where in situ data are scarce that can be combined with hydraulic and/or hydrodynamic models to simulate WSE and estimate discharge. In this study, we combine ICESat-2 (Ice, Cloud and land Elevation Satellite) land and water surface elevation measurements with a low-parameterized hydraulic calibration to simulate WSE and discharge without the need for surveyed cross-sectional geometry and a rainfall–runoff model. ICESat-2 provides an opportunity to map river cross-sectional geometry very accurately, with an along-track resolution of 0.7 m, using the ATL03 product. These measurements are combined with the inland water product ATL13 to calibrate a steady-state hydraulic model to retrieve unobserved hydraulic parameters such as river depth or the roughness coefficient. The low-parameterized model, together with the assumption of steady-state hydraulics, enables the application of a global search algorithm for a spatially uniform parameter calibration at a manageable computational cost. The model performance is similar to that reported for highly parameterized models, with a root mean square error (RMSE) of around 0.41 m. With the calibrated model, we can calculate the WSE time series at any chainage point at any time for an available satellite pass within the river reach and estimate discharge from WSE. The discharge estimates are validated with in situ measurements at two available gauging stations. In addition, we use the calibrated parameters in a full hydrodynamic model simulation, resulting in a RMSE of 0.59 m for the entire observation period. [ABSTRACT FROM AUTHOR]

Google's operational flood forecasting system was developed to provide accurate real-time flood warnings to agencies and the public with a focus on riverine floods in large, gauged rivers. It became operational in 2018 and has since expanded geographically. This forecasting system consists of four subsystems: data validation, stage forecasting, inundation modeling, and alert distribution. Machine learning is used for two of the subsystems. Stage forecasting is modeled with the long short-term memory (LSTM) networks and the linear models. Flood inundation is computed with the thresholding and the manifold models, where the former computes inundation extent and the latter computes both inundation extent and depth. The manifold model, presented here for the first time, provides a machine-learning alternative to hydraulic modeling of flood inundation. When evaluated on historical data, all models achieve sufficiently high-performance metrics for operational use. The LSTM showed higher skills than the linear model, while the thresholding and manifold models achieved similar performance metrics for modeling inundation extent. During the 2021 monsoon season, the flood warning system was operational in India and Bangladesh, covering flood-prone regions around rivers with a total area close to 470 000 km 2 , home to more than 350 000 000 people. More than 100 000 000 flood alerts were sent to affected populations, to relevant authorities, and to emergency organizations. Current and future work on the system includes extending coverage to additional flood-prone locations and improving modeling capabilities and accuracy. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs), affordable precise Global Navigation Satellite System hardware, echo sounders, open-source 3D hydrodynamic modelling software, and freely available satellite data have opened up opportunities for a robust, affordable, physics-based approach to monitor river flows. In short, the hardware can be used to produce the geometry. 3D hydrodynamic modelling offers a framework to establish relationships between river flow and state variables such as width and depth, while satellite images with surface water detection methods or altimetry records can be used to operationally monitor flows through the established rating curve. Uncertainties in the data acquisition may propagate into uncertainties in the relationships found between discharge and state variables. Variations in acquired geometry emanate from the different ground control point (GCP) densities and distributions which are used during photogrammetry-based terrain reconstruction. In this study, we develop a rating curve using affordable data collection methods and basic principles of physics. The specific objectives were to: determine how the rating curve based on a 3D hydraulic model compares with conventional methods; investigate the impact of geometry uncertainty on estimated discharge when applied in a hydraulic model; and investigate how uncertainties in continuous observations of depth and width from satellite platforms propagate into uncertainties in river flow estimates using the rating curves obtained. The study shows comparable results between the 3D and traditional river rating discharge estimations. The rating curve derived on the basis of 3D hydraulic modelling was within a 95 % confidence interval of the traditional gauging based rating curve. The physics- based estimation requires determination of the roughness coefficient within the permanent bed and the floodplain using field observation as both the end of dry and wet season. Furthermore, the study demonstrates that variations in the density of GCPs beyond an optimal number (9) has no significant influence on the resultant rating relationships. Finally, the study observes that it depends on the magnitude of the flow which state variable approximation (water level & river width) is most promising to use. Combining stage appropriate proxies (water level when the floodplain is entirely filled, and width when the floodplain is filling) in data limited environments yields more accurate discharge estimations. The study was able to successfully apply low cost technologies for accurate river monitoring through bhydraulic modelling. In future studies, a larger amount of in-situ gauge readings may be considered so as to optimise the validation process. [ABSTRACT FROM AUTHOR]

This contribution presents a novel multi-dimensional (multi-D) hydraulic–hydrological numerical model with variational data assimilation capabilities. It allows multi-scale modeling over large domains, combining in situ observations with high-resolution hydrometeorology and satellite data. The multi-D hydraulic model relies on the 2D shallow-water equations solved with a 1D–2D adapted single finite-volume solver. One-dimensional-like reaches are built through meshing methods that cause the 2D solver to degenerate into 1D. They are connected to 2D portions that act as local zooms, for modeling complex flow zones such as floodplains and confluences, via 1D-like–2D interfaces. An existing parsimonious hydrological model, GR4H, is implemented and coupled to the hydraulic model. The forward-inverse multi-D computational model is successfully validated on virtual and real cases of increasing complexity, including using the second-order scheme version. Assimilating multiple observations of flow signatures leads to accurate inferences of multi-variate and spatially distributed parameters among bathymetry friction, upstream and lateral hydrographs and hydrological model parameters. This notably demonstrates the possibility for information feedback towards upstream hydrological catchments, that is, backward hydrology. A 1D-like model of part of the Garonne River is built and accurately reproduces flow lines and propagations of a 2D reference model. A multi-D model of the complex Adour basin network, with inflow from the semi-distributed hydrological model, is built. High-resolution flow simulations are obtained on a large domain, including fine zooms on floodplains, with a relatively low computational cost since the network contains mostly 1D-like reaches. The current work constitutes an upgrade of the DassFlow computational platform. The adjoint of the whole tool chain is obtained by automatic code differentiation. [ABSTRACT FROM AUTHOR]

Step-pool systems are common bedforms in mountain streams and have been utilized in river restoration projects around the world. Step-pool units exhibit highly nonuniform hydraulic characteristics which have been reported to closely interact with the morphological evolution and stability of step-pool features. However, detailed information on the three-dimensional hydraulics for step-pool morphology has been scarce due to the difficulty of measurement. To fill in this knowledge gap, we established a combined approach based on the technologies of structure from motion (SfM) and computational fluid dynamics (CFD). 3D reconstructions of bed surfaces with an artificial step-pool unit built from natural stones at six flow rates were imported to CFD simulations. The combined approach succeeded in visualizing the high-resolution 3D flow structures for the step-pool unit. The results illustrate the segmentation of flow velocity downstream of the step, i.e., the integral recirculation cell at the water surface, streamwise vortices formed at the step toe, and high-speed flow in between. The highly nonuniform distribution of turbulence energy in the pool has been revealed, and two energy dissipaters of comparable magnitude are found to co-exist in the pool. Pool scour development during flow increase leads to the expansion of recirculation cells in the pool, but this expansion stops for the cell near the water surface when flow approaches the critical value for step-pool failure. The micro-bedforms (grain clusters) developed on the negative slope affect the local hydraulics significantly, but this influence is suppressed at the pool bottom. The drag forces on the step stones increase with discharge (before the highest flow value is reached). In comparison, the lift force consistently has a larger magnitude and a more widely varying range. Our results highlight the feasibility and great potential of the approach combining physical and numerical modeling in investigating the complex flow characteristics of step-pool morphology. [ABSTRACT FROM AUTHOR]

A modelling framework for using regional climate projections to assess flooding hazard has been developed and applied to the Gwydir River (catchment 26 600 km 2 and floodplain 8100 km 2) , NSW, Australia. The model framework uses NSW and ACT Regional Climate Modelling version 1.5 projections combined with computationally efficient hydrologic and hydraulic models. Although it required model management and high-performance computing resources, the modelling framework successfully processed 18 regional climate projections into flood projections. Specifically, a six-member set of climate model combinations simulating a historical period (1951–2005) and a future period (2006–2100) under two global emission pathways (RCP4.5 and RP8.5) were used to predict flood depth and speed. In total, 1470 continuous years were simulated at hourly time steps. These flood (depth and speed) projections were analysed to assess the flood hazard changes under future climate scenarios by estimating changes in the annual probability of occurrence of a range of flood hazard classes. The six-member ensemble indicates that the flood hazard in the Gwydir Valley will decrease in the short, medium and long term. There are also cases within the ensemble, which includes increases in all non-safe flood hazard classifications while decreasing the safe flood hazard classification. [ABSTRACT FROM AUTHOR]

Riparian zones are known to modulate water quality in stream corridors. They can act as buffers for groundwater-borne solutes before they enter the stream at harmful, high concentrations or facilitate solute turnover and attenuation in zones where stream water (SW) and groundwater (GW) mix. This natural attenuation capacity is strongly controlled by the dynamic exchange of water and solutes between the stream and the adjoining aquifer, creating potential for mixing-dependent reactions to take place. Here, we couple a previously calibrated transient and fully integrated 3D surface–subsurface numerical flow model with a hydraulic mixing cell (HMC) method to map the source composition of water along a net losing reach (900 m) of the fourth-order Selke stream and track its spatiotemporal evolution. This allows us to define zones in the aquifer with more balanced fractions of the different water sources per aquifer volume (called mixing hot spots), which have a high potential to facilitate mixing-dependent reactions and, in turn, enhance solute turnover. We further evaluated the HMC results against hydrochemical monitoring data. Our results show that, on average, about 50 % of the water in the alluvial aquifer consists of infiltrating SW. Within about 200 m around the stream, the aquifer is almost entirely made up of infiltrated SW with practically no significant amounts of other water sources mixed in. On average, about 9 % of the model domain could be characterized as mixing hot spots, which were mainly located at the fringe of the geochemical hyporheic zone rather than below or in the immediate vicinity of the streambed. This percentage could rise to values nearly 1.5 times higher following large discharge events. Moreover, event intensity (magnitude of peak flow) was found to be more important for the increase in mixing than event duration. Our modeling results further suggest that discharge events more significantly increase mixing potential at greater distances from the stream. In contrast near and below the stream, the rapid increase in SW influx shifts the ratio between the water fractions to SW, reducing the potential for mixing and the associated reactions. With this easy-to-transfer framework, we seek to show the applicability of the HMC method as a complementary approach for the identification of mixing hot spots in stream corridors, while showing the spatiotemporal controls of the SW–GW mixing process and the implications for riparian biogeochemistry and mixing-dependent turnover processes. [ABSTRACT FROM AUTHOR]

Advances in geodetic altimetry instruments are providing more accurate measurements, enabling satellite missions to hand over useful data in narrow rivers and streams. Altimetry missions produce spatially dense land and water surface elevation measurements in remote areas where in-situ data is scarce, that can be combined with hydraulic/hydrodynamic models to simulate water surface elevation and estimate discharge. In this study, we combine ICESat-2 land and water surface elevation measurements with a low-parametrized hydraulic calibration to simulate water surface elevation and discharge without the need for a rainfall-runoff model. ICESat-2 provides an opportunity to map river cross-section geometry very accurately with an along-track resolution of 0.7 m using the ATL03 product. These measurements are combined with the inland water product ATL13 to calibrate a steady-state hydraulic model to retrieve unobserved hydraulic parameters, such as river depth or roughness coefficient. The low-parametrized model together with the assumption of steady-state hydraulics enables the application of a global search algorithm for parameter calibration at a manageable computational cost. The model performance is similar to that reported for highly parametrized models, with a root mean square error of around 0.41 m. With the calibrated model, we can calculate water surface elevation time series at any chainage point at any time of an available satellite pass within the river reach, and estimate discharge from water surface elevation. The discharge estimates are validated with in-situ measurements at two available gauging stations. In addition, we use the calibrated parameters in a full hydrodynamic model simulation resulting in a RMSE of 0.59 m for the entire observation period. [ABSTRACT FROM AUTHOR]

Assessment of the karst network geometry based on field data is an important challenge in the accurate modeling of karst aquifers. In this study, we propose an integrated approach for the identification of effective three-dimensional (3D) discrete karst conduit networks conditioned on tracer tests and geophysical data. The procedure is threefold: (i) tracer breakthrough curves (BTCs) are processed via a regularized inversion procedure to determine the minimum number of distinct tracer flow paths between injection and monitoring points, (ii) available surface-based geophysical data and borehole-logging measurements are aggregated into a 3D proxy model of aquifer hydraulic properties, and (iii) single or multiple tracer flow paths are identified through the application of an alternative shortest path (SP) algorithm to the 3D proxy model. The capability of the proposed approach to adequately capture the geometrical structure of actual karst conduit systems mainly depends on the sensitivity of geophysical signals to karst features, whereas the relative completeness of the identified conduit network depends on the number and spatial configuration of tracer tests. The applicability of the proposed approach is illustrated through a case study at the Hydrogeological Experimental Site (HES) in Poitiers, France. [ABSTRACT FROM AUTHOR]

River floods, which are one of the most dangerous natural hazards worldwide, have increased in intensity and frequency in recent decades as a result of climate change, and the future scenario is expected to be even worse. Therefore, their knowledge, predictability, and mitigation represent a key challenge for the scientific community in the coming decades, especially in those local areas that are most vulnerable to these extreme events. In this sense, a multiscale analysis is essential to obtain detailed maps of the future evolution of floods. In the multiscale analysis, the historical and future precipitation data from the CORDEX project are used as input in a hydrological model (HEC-HMS) which, in turn, feeds a 2D hydraulic model (Iber+). This integration allows knowing the projected future changes in the flow pattern of the river, as well as analyzing the impact of floods in vulnerable areas through the flood hazard maps obtained with hydraulic simulations. The multiscale analysis is applied to the case of the Miño-Sil basin (NW Spain), specifically to the city of Ourense. The results show a delay in the flood season and an increase in the frequency and intensity of extreme river flows in the Miño-Sil basin, which will cause more situations of flooding in many areas frequented by pedestrians and in important infrastructures of the city of Ourense. In addition, an increase in water depths associated with future floods was also detected, confirming the trend for future floods to be not only more frequent but also more intense. Detailed maps of the future evolution of floods also provide key information to decision-makers to take effective measures in advance in those areas most vulnerable to flooding in the coming decades. Although the methodology presented is applied to a particular area, its strength lies in the fact that its implementation in other basins and cities is simple, also taking into account that all the models used are freely accessible. [ABSTRACT FROM AUTHOR]

Hydro-meteo hazard early warning systems (EWSs) are operating in many regions of the world to mitigate nuisance effects of floods. EWS performances are majorly impacted by the computational burden and complexity affecting flood prediction tools, especially for ungauged catchments that lack adequate river flow gauging stations. Earth observation (EO) systems may integrate the lack of fluvial monitoring systems supporting the setting up of affordable EWSs. But, EO data, constrained by spatial and temporal resolution limitations, are not sufficient alone, especially at medium–small scales. Multiple sources of distributed flood observations need to be used for managing uncertainties of flood models, but this is not a trivial task for EWSs. In this work, a near-real-time flood modelling approach is developed and tested for the simultaneous assimilation of both water level observations and EO-derived flood extents. An integrated physically based flood wave generation and propagation modelling approach, that implements an ensemble Kalman filter, a parsimonious geomorphic rainfall–runoff algorithm (width function instantaneous unit hydrograph, WFIUH) and a quasi-2D hydraulic algorithm, is proposed. An approach for assimilating multiple stage gauge observations is proposed to overcome stability issues related to the updating of the quasi-2D hydraulic model states. Furthermore, a methodology to retrieve distributed observed water depths from satellite images to update 2D hydraulic modelling state variables is implemented. Performances of the proposed approach are tested on a flood event for the Tiber River basin in central Italy. The selected case study shows varying performances depending on whether local and distributed observations are separately or simultaneously assimilated. Results suggest that the injection of multiple data sources into a flexible data assimilation framework constitutes an effective and viable advancement for flood mitigation to tackle EWS uncertainty and numerical stability issues. Specifically, our findings reveal that the simultaneous assimilation of observations from static sensors and satellite images led to an overall improvement of the Nash–Sutcliffe efficiency (NSE) between 5 % and 40 %, the Pearson correlation up to 12 % and bias reduction up to 80 % with respect to the open-loop simulation. Moreover, this combined assimilation allows us to reduce the flood extent uncertainty with respect to the disjoint assimilation simulations for several hours after the satellite image acquisition. [ABSTRACT FROM AUTHOR]

Rapid modern technological advancements have led to significant improvements in river monitoring using unmanned aerial vehicles (UAVs), photogrammetric reconstruction software, and low-cost real-time kinematic Global Navigation Satellite System (RTK GNSS) equipment. UAVs allow for the collection of dry bathymetric data in environments that are difficult to access. Low-cost RTK GNSS equipment facilitates accurate measurement of wet bathymetry when combined with subaqueous measuring tools such as acoustic Doppler current profilers (ADCPs). Hydraulic models may be constructed from these data, which in turn can be used for various applications such as water management, forecasting, early warning and disaster preparedness by responsible water authorities, and construction of river rating curves. We hypothesise that the reconstruction of dry terrain with UAV-based photogrammetry combined with RTK GNSS equipment leads to accurate geometries particularly fit for hydraulic understanding and simulation models. This study sought to (1) compare open-source and commercial photogrammetry packages to verify if water authorities with low resource availability have the option to utilise open-source packages without significant compromise on accuracy; (2) assess the impact of variations in the number of ground control points (GCPs) and the distribution of the GCP markers on the quality of digital elevation models (DEMs), with a particular emphasis on characteristics that impact hydraulics; and (3) investigate the impact of using reconstructions based on different GCP numbers on conveyance and hydraulic slope. A novel method which makes use of a simple RTK tie line along the water edge measured using a low-cost but highly accurate GNSS is presented so as to correct the unwanted effect of lens distortion ("doming effect") and enable the concatenation of geometric data from different sources. Furthermore, we describe how merging of the dry and wet bathymetry can be achieved through gridding based on linear interpolation. We tested our approach over a section of the Luangwa River in Zambia. Results indicate that the open-source software photogrammetry package is capable of producing results that are comparable to commercially available options. We determined that GCPs are essential for vertical accuracy, but also that an increase in the number of GCPs above a limited number of five only moderately increases the accuracy of results, provided the GCPs are well spaced in both the horizontal and vertical dimension. Furthermore, insignificant differences in hydraulic geometries among the various cross sections are observed, corroborating the fact that a limited well-spaced set of GCPs is enough to establish a hydraulically sound reconstruction. However, it appeared necessary to make an additional observation of the hydraulic slope. A slope derived merely from the UAV survey was shown to be prone to considerable errors caused by lens distortion. Combination of the photogrammetry results with the RTK GNSS tie line was shown to be essential to correct the slope and made the reconstruction suitable for hydraulic model setup. [ABSTRACT FROM AUTHOR]

Root water uptake is an important process in the terrestrial water cycle. How this process depends on soil water content, root distributions, and root properties is a soil–root hydraulic problem. We compare different approaches to implement root hydraulics in macroscopic soil water flow and land surface models. By upscaling a three-dimensional hydraulic root architecture model, we derived an exact macroscopic root hydraulic model. The macroscopic model uses the following three characteristics: the root system conductance, Krs , the standard uptake fraction, SUF , which represents the uptake from a soil profile with a uniform hydraulic head, and a compensatory matrix that describes the redistribution of water uptake in a non-uniform hydraulic head profile. The two characteristics, Krs and SUF , are sufficient to describe the total uptake as a function of the collar and soil water potential, and water uptake redistribution does not depend on the total uptake or collar water potential. We compared the exact model with two hydraulic root models that make a priori simplifications of the hydraulic root architecture, i.e., the parallel and big root model. The parallel root model uses only two characteristics, Krs and SUF , which can be calculated directly following a bottom-up approach from the 3D hydraulic root architecture. The big root model uses more parameters than the parallel root model, but these parameters cannot be obtained straightforwardly with a bottom-up approach. The big root model was parameterized using a top-down approach, i.e., directly from root segment hydraulic properties, assuming a priori a single big root architecture. This simplification of the hydraulic root architecture led to less accurate descriptions of root water uptake than by the parallel root model. To compute root water uptake in macroscopic soil water flow and land surface models, we recommend the use of the parallel root model with Krs and SUF computed in a bottom-up approach from a known 3D root hydraulic architecture. [ABSTRACT FROM AUTHOR]

Sorptivity is a parameter of primary importance in the study of unsaturated flow in soils. This hydraulic parameter is required to model water infiltration into vertical soil profiles. Sorptivity can be directly estimated from the soil hydraulic functions (water retention and hydraulic conductivity curves), using the integral formulation of. However, calculating sorptivity in this manner requires the prior determination of the soil hydraulic diffusivity and its numerical integration between initial and final saturation degrees, which may be difficult in some situations (e.g., coarse soil with diffusivity functions that are quasi-infinite close to saturation). In this paper, we present a procedure to compute sorptivity using a scaling parameter, cp , that corresponds to the sorptivity of a unit soil (i.e., unit values for all parameters and zero residual water content) that is utterly dry at the initial state and saturated at the final state. The cp parameter was computed numerically and analytically for five hydraulic models: delta (i.e., Green and Ampt), Brooks and Corey, van Genuchten–Mualem, van Genuchten–Burdine, and Kosugi. Based on the results, we proposed brand new analytical expressions for some of the models and validated previous formulations for the other models. We also tabulated the output values so that they can easily be used to determine the actual sorptivity value for any case. At the same time, our numerical results showed that the relation between cp and the hydraulic shape parameters strongly depends on the chosen model. These results highlight the need for careful selection of the proper model for the description of the water retention and hydraulic conductivity functions when estimating sorptivity. [ABSTRACT FROM AUTHOR]

Plant transpiration downregulation in the presence of soil water stress is a critical mechanism for predicting global water, carbon, and energy cycles. Currently, many terrestrial biosphere models (TBMs) represent this mechanism with an empirical correction function (β) of soil moisture – a convenient approach that can produce large prediction uncertainties. To reduce this uncertainty, TBMs have increasingly incorporated physically based plant hydraulic models (PHMs). However, PHMs introduce additional parameter uncertainty and computational demands. Therefore, understanding why and when PHM and β predictions diverge would usefully inform model selection within TBMs. Here, we use a minimalist PHM to demonstrate that coupling the effects of soil water stress and atmospheric moisture demand leads to a spectrum of transpiration responses controlled by soil–plant hydraulic transport (conductance). Within this transport-limitation spectrum, β emerges as an end-member scenario of PHMs with infinite conductance, completely decoupling the effects of soil water stress and atmospheric moisture demand on transpiration. As a result, PHM and β transpiration predictions diverge most for soil–plant systems with low hydraulic conductance (transport-limited) that experience high variation in atmospheric moisture demand and have moderate soil moisture supply for plants. We test these minimalist model results by using a land surface model at an AmeriFlux site. At this transport-limited site, a PHM downregulation scheme outperforms the β scheme due to its sensitivity to variations in atmospheric moisture demand. Based on this observation, we develop a new "dynamic β " that varies with atmospheric moisture demand – an approach that overcomes existing biases within β schemes and has potential to simplify existing PHM parameterization and implementation. [ABSTRACT FROM AUTHOR]

In the last few years, some regions of the Mediterranean area have witnessed a progressive increase in extreme events, such as urban and flash floods, as a response to the increasingly frequent and severe extreme rainfall events, which are often exacerbated by the ever-growing urbanization. In such a context, the urban drainage systems may not be sufficient to convey the rainwater, thus increasing the risk deriving from the occurrence of such events. This study focuses on a particularly intense urban flood that occurred in Palermo (Italy) on 15 July 2020; it represents a typical pluvial flood due to extreme rainfall on a complex urban area that many cities have experienced in recent years, especially in the Mediterranean region. A conceptual hydrological model and a 2D hydraulic model, particularly suitable for simulations in a very complex urban context, have been used to simulate the event. Results have been qualitatively validated by means of crowdsourced information and satellite images. The experience of Palermo, which has highlighted the urgent need for a shift in the way stormwater in urban settlements is managed, can be assumed to be a paradigm for modeling pluvial floods in complex urban areas under extreme rainfall conditions. Although the approaches and the related policies cannot be identical for all cities, the modeling framework used here to assess the impacts of the event under study and some conclusive remarks could be easily transferred to other, different urban contexts. [ABSTRACT FROM AUTHOR]

Rapid modern technological advancements have led to significant improvements in river monitoring using Unmanned Aerial vehicles (UAVs). These UAVs allow for the collection of flow geometry data in environments that are difficult to access. Hydraulic models may be constructed from these data, which in turn can be used for various applications such as water management, forecasting, early warning and disaster preparedness by responsible water authorities, and construction of river rating curves. We hypothesize that the reconstruction combined with Real Time Kinematic Global Navigation Satellite System (RTK GNSS) equipment leads to accurate geometries particularly fit for hydraulic understanding and simulation models. This study sought to (1) compare open source and commercial photogrammetry packages to verify if water authorities with low resource availability have the option to utilise these without significant compromise on accuracy; (2) assess the impact of variations in the number of Ground Control Points (GCPs) and the distribution of the GCP markers on the quality of Digital Elevation Models (DEMs), with a particular emphasis on characteristics that impact on hydraulics; and (3) investigate the impact of variations in DEMs on flow estimations based on the number of GCPs used. We tested our approach over a section of the Luangwa River in Zambia. We compare performance of two different photogrammetry software packages, one being open-source and one commercial; then compare for one chosen package the performance with different GCP numbers and distributions, and finally, emphasize on the reconstruction of hydraulically important parameters. The first investigation (1) utilises the root mean square error (RMSE) method to determine if open source software performs as well as commercial software. The second task (2) aimed to assess the optimal GCP number and distribution; we generated 10 UAV based elevation models under varying GCP distribution conditions using OpenDroneMap (ODM) software. To benchmark the different DEM reconstructions we assessed the Mean Absolute Error of the elevation using the GCPs that were left out of the reconstruction. Finally (3), in order to investigate the impact of variations in DEMs on flow estimations we performed a comparison of the hydraulic conveyance across each reconstruction, as well as a comparison of the hydraulic slope against an independent estimate using an in-situ RTK GNSS tie line. Results indicate that the open-source software photogrammetry package is capable of producing results that are comparable to commercially available options. We determined that GCPs are essential for vertical accuracy, but also that an increase in the number of GCPs above a limited amount of 5 only moderately increases the accuracy of results, provided the GCPs are well spaced both in horizontal and vertical dimension. Furthermore, insignificant differences in hydraulic geometries among the various cross sections are observed, corroborating the fact that a limited well-spaced set of GCPs is enough to establish a hydraulically sound reconstruction. This is important so that future studies do not invest in procedures that may be costly, but may not contribute significantly to the improvement of desired results. The hydraulic slope was shown to be prone to errors caused by lens distortion. These errors are too large to enable use in a hydraulic model setup. We therefore recommend to combine photogrammetry results with a RTK GNSS tie line when reconstructions are to be used for hydraulic model setup. [ABSTRACT FROM AUTHOR]

Floods are one of the most frequent and damaging natural threats worldwide. Whereas the assessment of direct impacts is well advanced, the evaluation of indirect impacts is less frequently achieved. Indirect impacts are not due to the physical contact with flood water but result, for example, from the reduced performance of infrastructures. Linear critical infrastructures (such as roads and pipes) have an interconnected nature that may lead to failure propagation, so that impacts extend far beyond the inundated areas and/or period. This work presents the risk analysis of two linear infrastructure systems, i.e. the water distribution system (WSS) and the road network system. The evaluation of indirect flood impacts on the two networks is carried out for four flooding scenarios, obtained by a coupled 1D–quasi-2D hydraulic model. Two methods are used for assessing the impacts on the WSS and on the road network: a pressure-driven demand network model and a transport network disruption model respectively. The analysis is focused on the identification of (i) common impact metrics, (ii) vulnerable elements exposed to the flood, (iii) similarities and differences of the methodological aspects for the two networks, and (iv) risks due to systemic interdependency. The study presents an application to the metropolitan area of Florence (Italy). When interdependencies are accounted for, results showed that the risk to the WSS in terms of population equivalent (PE/year) can be reduced by 71.5 % and 41.8 %, if timely repairs to the WSS stations are accomplished by 60 and 120 min respectively; the risk to WSS in terms of pipe length (km yr -1) reduces by 53.1 % and 15.6 %. The study highlights that resilience is enhanced by systemic risk-informed planning, which ensures timely interventions on critical infrastructures; however, for indirect impacts and cascade effects, temporal and spatial scales are difficult to define. Perspective research could further improve this work by applying a system-risk analysis to multiple urban infrastructures. [ABSTRACT FROM AUTHOR]

The study evaluates the hydraulic analysis of water supply distribution network using water GEMS v8i. which used for modeling and Simulation of hydraulic parameters in the distribution networks. The hydraulic parameters which analyzed by using this software were junction pressure, velocity of water in networking system, and nodal demands and the overall result of water supply did not satisfied demand. The water distribution system has been analyzed for steady state and extended period simulation for the present population scenario for intermittent water supply using water Gems v8i. About 14 percent of the total number of nodes analyzed had negative pressures while 68 percent of the nodes had pressures less than the adopted pressure for the analysis. These negative pressures indicate that there is inadequate head within the distribution network for water conveyance to all the sections. In the same manner 85.6 percent of flow velocities in the pipes were within the adopted velocity while around 14.4 percent of the velocities exceeded the adopted velocity. The results in this study revealed that the performance of the water distribution system of under current demand is inefficient. [ABSTRACT FROM AUTHOR]

Plant hydraulic and photosynthetic responses to individual rain pulses are not well understood because field experiments of pulse behavior are sparse. Understanding individual pulse responses would inform how rainfall intermittency impacts terrestrial biogeochemical cycles, especially in drylands, which play a large role in interannual global atmospheric carbon uptake variability. Using satellite-based estimates of predawn plant and soil water content from the Soil Moisture Active Passive (SMAP) satellite, we quantify the timescales of plant water content increases following rainfall pulses, which we expect bear the signature of whole-plant mechanisms. In wetter regions, we find that plant water content increases rapidly and dries along with soil moisture, which we attribute to predawn soil–plant water potential equilibrium. Global drylands, by contrast, show multi-day plant water content increases after rain pulses. Shorter increases are more common following dry initial soil conditions. These are attributed to slow plant rehydration due to high plant resistances using a plant hydraulic model. Longer multi-day dryland plant water content increases are attributed to pulse-driven growth, following larger rain pulses and wetter initial soil conditions. These dryland responses reflect widespread drought recovery rehydration responses and individual pulse-driven growth responses, as supported by previous isolated field experiments. The response dependence on moisture pulse characteristics, especially in drylands, also shows ecosystem sensitivity to intra-annual rainfall intensity and frequency, which are shifting with climate change. [ABSTRACT FROM AUTHOR]

Floods are the most frequent and damaging natural threat worldwide. Whereas the assessment of direct impacts is well advanced, the evaluation of indirect impacts is less frequently achieved. Indirect impacts are not due to the physical contact with flood water but result from the reduced performance of infrastructures. Linear critical infrastructures (such as roads and pipes) have an interconnected nature that may lead to failure propagation, so that impacts extend far beyond the inundated areas and/or period. This work presents the risk analysis of two linear infrastructure systems, i.e. the water distribution system (WSS) and the road network system. The evaluation of indirect flood impacts on the two networks is carried out for four flooding scenarios, obtained by a coupled 1D-quasi 2D hydraulic model. Two methods are used for assessing the impacts on the water distribution system and on the road network, a Pressure-Driven Demand network model and a transport network disruption model respectively. The analysis is focused on the identification of: (i) common impact metrics; (ii) vulnerable elements exposed to the flood; (iii) similarities and differences of the methodological aspects for the two networks; (iv) risks due to systemic interdependency. The study presents an application to the metropolitan area of Florence (Italy). When interdependencies are accounted for, results showed that the risk to the WSS in terms of Population Equivalent (PE/year) can be reduced by 71.5 % and 41.8 %, if timely repairs to the WSS stations are accomplished by 60 and 120 minutes respectively; the risk to WSS in terms of pipes length (km/year) reduces by 53.1 % and 15.6 %. The study highlights that resilience is enhanced by system risk-informed planning, which ensures timely interventions on critical infrastructures; however, temporal and spatial scales are difficult to define for indirect impacts and cascade effects. Perspective research could further improve this work by applying a system-risk analysis to multiple urban infrastructures. [ABSTRACT FROM AUTHOR]

Plant hydraulic and photosynthetic responses to individual rain pulses are not well understood because pulse experiments are sparse. Understanding individual pulse responses would inform how rainfall intermittency impacts terrestrial biogeochemical cycles, especially in drylands which play a large role in global atmospheric carbon uptake interannual variability. Using satellite-based estimates of predawn plant and soil water content from the Soil Moisture Active Passive (SMAP) satellite, we quantify the timescales of plant water content increases following rainfall pulses, which we expect bear the signature of whole-plant mechanisms. In wetter regions, we find that plant water content increases rapidly and dries along with soil moisture, which we attribute to predawn soil-plant water potential equilibrium. Global drylands, by contrast, show multi-day plant water content increases after rain pulses. Shorter increases are more common following dry initial soil conditions. These are attributed to slow plant rehydration due to high plant resistances using a plant hydraulic model. Longer multi-day dryland plant water content increases are attributed to pulse-driven growth, following larger rain pulses and wetter initial soil conditions. These dryland responses reflect widespread drought recovery rehydration responses and individual pulse-driven growth responses, which supports isolated field experiments. The response dependence on moisture pulse characteristics also implies ecosystem sensitivity to intra-annual rainfall intensity and frequency, which are expected to shift in a future climate. [ABSTRACT FROM AUTHOR]

The accuracy of hydraulic models depends on the quality of the bathymetric data they are based on, whatever the scale at which they are applied. The along-stream (longitudinal) and cross-sectional geometry of natural rivers is known to vary at the scale of the hydrographic network (e.g., generally decreasing slope, increasing width in the downstream direction), allowing parameterizations of main cross-sectional parameters with large-scale proxies such as drainage area or bankfull discharge (an approach coined downstream hydraulic geometry, DHG). However, higher-frequency morphological variability (i.e., at river reach scale) is known to occur for many stream types, associated with varying flow conditions along a given reach, such as the alternate bars or the pool–riffle sequences and meanders. To consider this high-frequency variability of the geometry in the hydraulic models, a first step is to design robust methods to characterize the scales at which it occurs. In this paper, we introduce new wavelet analysis tools in the field of geomorphic analysis (namely, wavelet ridge extraction) to identify the pseudo-periodicity of alternating morphological units from a general point of view (focusing on pool–riffle sequences) for six small French rivers. This analysis can be performed on a single variable (univariate case) but also on multiple variables (multivariate case). In this study, we choose a set of four variables describing the flow degrees of freedom: velocity, hydraulic radius, bed shear stress, and a planform descriptor that quantifies the local deviation of the channel from its mean direction. Finally, this method is compared with the bedform differencing technique (BDT), by computing the mean, median, and standard deviation of their longitudinal spacings. The two methods show agreement in the estimation of the wavelength in all reaches except one. The method aims to extract a pseudo-periodicity of the alternating bedforms that allow objective identification of morphological units in a continuous approach with the maintenance of correlations between variables (i.e., at many station hydraulic geometry, AMHG) without the need to define a prior threshold for each variable to characterize the transition from one unit to another. [ABSTRACT FROM AUTHOR]

Drilling fluid infiltration during well drilling induces pore pressure and strain perturbations in neighboured reservoir formations. In this study, we in situ monitored such small strain changes (~20µε) using fiber-optic distributed strain sensing in two observation wells with different distances (approximately 3m and 9m) from a new drilling wellbore in a shallow water aquifer. The results suggest that the drilling induced hydromechanical deformations that occurred at depths of both wells are indicative of the impact zones of fluid invasion and reservoir permeability structure (heterogeneity). A hydraulic diffusion model is used to interpret the strain evolution. The method and data would be useful for understanding reservoir pressure communications, determining the zones for fluid productions or injections (e.g., for CO2 storage), and optimizing reservoir management and utilization. [ABSTRACT FROM AUTHOR]

Identification of flood prone areas is instrumental for a large number of applications, ranging from engineering to climate change studies, and provides essential information for planning effective emergency responses. In this work we describe an integrated hydrological and hydraulic modeling approach for the assessment of flood-prone areas in Italy and we present the first results obtained over the Po river (Northern Italy) at a resolution of 90 m. River discharges are obtained through the hydrological model CHyM driven by GRIPHO, a newly-developed high resolution hourly precipitation dataset. Runoff data is then used to obtain Synthetic Design Hydrographs (SDHs) for different return periods along the river network. Flood hydrographs are subsequently processed by a parallelized version of the CA2D hydraulic model to calculate the flow over an ad hoc re-shaped HydroSHEDS digital elevation model which includes information about the channel geometry. Modeled hydrographs and SDHs are compared with those obtained from observed data for a choice of gauging stations, showing an overall good performance of the CHyM model. The flood hazard maps for return periods of 50, 100, 500 are validated by comparison with the official flood hazard maps produced by the River Po Authority (Adbpo) and with the Joint Research Centre's (JRC) pan-European maps. The results show a good agreement with the available official national flood maps for high return periods. For lower return periods the results and less satisfactory but overall the application suggests strong potential of the proposed approach for future applications. [ABSTRACT FROM AUTHOR]

Flood frequency curves are usually highly uncertain since they are based on short data sets of measured discharges or weather conditions. To decrease the confidence intervals, an efficient bootstrap method is developed in this study. The Rhine river delta is considered as a case study. We use a hydraulic model to normalize historic flood events for anthropogenic and natural changes in the river system. As a result, the data set of measured discharges could be extended by approximately 600 years. The study shows that historic flood events decrease the confidence interval of the flood frequency curve significantly, specifically in the range of large floods. This even applies if the maximum discharges of these historic flood events are highly uncertain themselves. [ABSTRACT FROM AUTHOR]

Extreme water levels generating flooding in estuarine and coastal environments are often driven by compound events, where many individual processes such as waves, storm surge, streamflow, and tides coincide. Despite this, extreme water levels are typically modeled in isolated open-coast or estuarine environments, potentially mischaracterizing the true risk of flooding facing coastal communities. This paper explores the variability of extreme water levels near the tribal community of La Push, within the Quileute Indian Reservation on the Washington state coast, where a river signal is apparent in tide gauge measurements during high-discharge events. To estimate the influence of multiple forcings on high water levels a hybrid modeling framework is developed, where probabilistic simulations of joint still water level and river discharge occurrences are merged with a hydraulic model that simulates along-river water levels. This methodology produces along-river water levels from thousands of combinations of events not necessarily captured in the observational records. We show that the 100-year still water level event and the 100-year discharge event do not always produce the 100-year along-river water level. Furthermore, along specific sections of river, both still water level and discharge are necessary for producing the 100-year along-river water level. Understanding the relative forcing driving extreme water levels along an ocean-to-river gradient will help communities within inlets better understand their risk to the compounding impacts of various environmental forcing, which is important for increasing their resilience to future flooding events. [ABSTRACT FROM AUTHOR]

In global hydrological models, groundwater (GW) is typically represented by a bucket-like linear groundwater reservoir. Reservoir models, however, (1) can only simulate GW discharge to surface water (SW) bodies but not recharge from SW to GW, (2) provide no information on the location of the GW table, and (3) assume that there is no GW flow among grid cells. This may lead, for example, to an underestimation of groundwater resources in semiarid areas where GW is often replenished by SW or to an underestimation of evapotranspiration where the GW table is close to the land surface. To overcome these limitations, it is necessary to replace the reservoir model in global hydrological models with a hydraulic head gradient-based GW flow model. We present G 3 M, a new global gradient-based GW model with a spatial resolution of 5 ′ (arcminutes), which is to be integrated into the 0.5 ∘ WaterGAP Global Hydrology Model (WGHM). The newly developed model framework enables in-memory coupling to WGHM while keeping overall runtime relatively low, which allows sensitivity analyses, calibration, and data assimilation. This paper presents the G 3 M concept and model design decisions that are specific to the large grid size required for a global-scale model. Model results under steady-state naturalized conditions, i.e., neglecting GW abstractions, are shown. Simulated hydraulic heads show better agreement to observations around the world compared to the model output of de Graaf et al. (2015). Locations of simulated SW recharge to GW are found, as is expected, in dry and mountainous regions but areal extent of SW recharge may be underestimated. Globally, GW discharge to rivers is by far the dominant flow component such that lateral GW flows only become a large fraction of total diffuse and focused recharge in the case of losing rivers, some mountainous areas, and some areas with very low GW recharge. A strong sensitivity of simulated hydraulic heads to the spatial resolution of the model and the related choice of the water table elevation of surface water bodies was found. We suggest to investigate how global-scale groundwater modeling at 5 ′ spatial resolution can benefit from more highly resolved land surface elevation data. [ABSTRACT FROM AUTHOR]

Flooding is an imminent natural hazard threatening most river deltas, e.g. the Mekong Delta. An appropriate flood management is thus required for a sustainable development of the often densely populated regions. Recently, the traditional event-based hazard control shifted towards a risk management approach in many regions, driven by intensive research leading to new legal regulation on flood management. However, a large-scale flood risk assessment does not exist for the Mekong Delta. Particularly, flood risk to paddy rice cultivation, the most important economic activity in the delta, has not been performed yet. Therefore, the present study was developed to provide the very first insight into delta-scale flood damages and risks to rice cultivation. The flood hazard was quantified by probabilistic flood hazard maps of the whole delta using a bivariate extreme value statistics, synthetic flood hydrographs, and a large-scale hydraulic model. The flood risk to paddy rice was then quantified considering cropping calendars, rice phenology, and harvest times based on a time series of enhanced vegetation index (EVI) derived from MODIS satellite data, and a published rice flood damage function. The proposed concept provided flood risk maps to paddy rice for the Mekong Delta in terms of expected annual damage. The presented concept can be used as a blueprint for regions facing similar problems due to its generic approach. Furthermore, the changes in flood risk to paddy rice caused by changes in land use currently under discussion in the Mekong Delta were estimated. Two land-use scenarios either intensifying or reducing rice cropping were considered, and the changes in risk were presented in spatially explicit flood risk maps. The basic risk maps could serve as guidance for the authorities to develop spatially explicit flood management and mitigation plans for the delta. The land-use change risk maps could further be used for adaptive risk management plans and as a basis for a cost–benefit of the discussed land-use change scenarios. Additionally, the damage and risks maps may support the recently initiated agricultural insurance programme in Vietnam. [ABSTRACT FROM AUTHOR]

This paper presents a novel methodology for estimating the unknown discharge hydrograph at the entrance of a river reach when no information is available. The methodology couples an optimization procedure based on the Bayesian geostatistical approach (BGA) with a forward self-developed 2-D hydraulic model. In order to accurately describe the flow propagation in real rivers characterized by large floodable areas, the forward model solves the 2-D shallow water equations (SWEs) by means of a finite volume explicit shock-capturing algorithm. The two-dimensional SWE code exploits the computational power of graphics processing units (GPUs), achieving a ratio of physical to computational time of up to 1000. With the aim of enhancing the computational efficiency of the inverse estimation, the Bayesian technique is parallelized, developing a procedure based on the Secure Shell (SSH) protocol that allows one to take advantage of remote high-performance computing clusters (including those available on the Cloud) equipped with GPUs. The capability of the methodology is assessed by estimating irregular and synthetic inflow hydrographs in real river reaches, also taking into account the presence of downstream corrupted observations. Finally, the procedure is applied to reconstruct a real flood wave in a river reach located in northern Italy. [ABSTRACT FROM AUTHOR]

The Iceland-Faroe Ridge (IFR) is considered to be the third-most important passage for dense overflow water from the Nordic Seas feeding into the lower limb of the Atlantic Meridional Overturning Circulation with a volume transport on the order of 1 Sv (106 m3 s-1). The Western Valley, which is the northernmost deep passage across the IFR, has been presumed to supply a strong and persistent overflow (WV-overflow), contributing a large fraction of the total overflow across the IFR. However, prolonged measurements of this transport are so far missing. In order to quantify the flow by direct measurements, three instrumental packages were deployed close to the sill of the Western Valley for 278 days (2016-2017) including an Acoustic Doppler Current Profiler at the expected location of the overflow core. The average volume transport of WV-overflow during this field experiment was found to be less than 0.03 Sv. Aided by the observations and a two-layer hydraulic model, we argue that the reason for this low value is the inflow of warm Atlantic Water to the Norwegian Sea in the upper layers suppressing the deep overflow. The link between deep and surface flows explains an observed relationship between overflow and sea level slope as measured by satellite altimetry. This relationship, combined with historical hydrographic measurements allows us to conclude that the volume transport of WV-overflow most likely has been less than 0.1 Sv on average since the beginning of regular satellite altimetry in 1993. Our new direct measurements do not allow us to present an updated estimate of the total overflow across the IFR, but they indicate that it may well be considerably less than 1 Sv. [ABSTRACT FROM AUTHOR]

In the Vietnamese part of the Mekong Delta (VMD) the areas with three rice crops per year have been expanded rapidly during the last 15 years. Paddy-rice cultivation during the flood season has been made possible by implementing high-dyke flood defenses and flood control structures. However, there are widespread claims that the highdyke system has increased water levels in downstream areas. Our study aims at resolving this issue by attributing observed changes in flood characteristics to high-dyke construction and other possible causes. Maximum water levels and duration above the flood alarm level are analysed for gradual trends and step changes at different discharge gauges. Strong and robust increasing trends of peak water levels and duration downstream of the high-dyke areas are found with a step change in 2000/2001, i.e. immediately after the disastrous flood which initiated the high-dyke development. These changes are in contrast to the negative trends detected at stations upstream of the high-dyke areas. This spatially different behaviour of changes in flood characteristics seems to support the public claims. To separate the impact of the highdyke development from the impact of the other drivers - i.e. changes in the flood hydrograph entering the Mekong Delta, and changes in the tidal dynamics - hydraulic model simulations of the two recent large flood events in 2000 and 2011 are performed. The hydraulic model is run for a set of scenarios whereas the different drivers are interchanged. The simulations reveal that for the central VMD an increase of 9-13 cm in flood peak and 15 days in duration can be attributed to high-dyke development. However, for this area the tidal dynamics have an even larger effect in the range of 19-32 cm. However, the relative contributions of the three drivers of change vary in space across the delta. In summary, our study confirms the claims that the high-dyke development has raised the flood hazard downstream. However, it is not the only and not the most important driver of the observed changes. It has to be noted that changes in tidal levels caused by sea level rise in combination with the widely observed land subsidence and the temporal coincidence of high water levels and spring tides have even larger impacts. It is recommended to develop flood risk management strategies using the high-dyke areas as retention zones to mitigate the flood hazard downstream. [ABSTRACT FROM AUTHOR]

Probabilistic flood inundation mapping is performed and analysed at the ungauged Xerias stream reach, Volos, Greece. The study evaluates the uncertainty introduced by the roughness coefficient values on hydraulic models in flood inundation modelling and mapping. The wellestablished one-dimensional (1-D) hydraulic model, HECRAS is selected and linked to Monte-Carlo simulations of hydraulic roughness. Terrestrial Laser Scanner data have been used to produce a high quality DEM for input data uncertainty minimisation and to improve determination accuracy on stream channel topography required by the hydraulic model. Initial Manning's n roughness coefficient values are based on pebble count field surveys and empirical formulas. Various theoretical probability distributions are fitted and evaluated on their accuracy to represent the estimated roughness values. Finally, Latin Hypercube Sampling has been used for generation of different sets of Manning roughness values and flood inundation probability maps have been created with the use of Monte Carlo simulations. Historical flood extent data, from an extreme historical flash flood event, are used for validation of the method. The calibration process is based on a binary wet-dry reasoning with the use of Median Absolute Percentage Error evaluation metric. The results show that the proposed procedure supports probabilistic flood hazard mapping at ungauged rivers and provides water resources managers with valuable information for planning and implementing flood risk mitigation strategies. [ABSTRACT FROM AUTHOR]

Single satellite synthetic aperture radar (SAR) data are now regularly used to estimate hydraulic model parameters such as channel roughness, depth and water slope. However, despite channel geometry being critical to the application of hydraulic models and poorly known a priori, it is not frequently the object of calibration. This paper presents a unique method to simultaneously calibrate the bankfull channel depth and channel roughness parameters within a 2-D LISFLOOD-FP hydraulic model using an archive of moderate-resolution (150 m) ENVISAT satellite SAR-derived flood extent maps and a binary performance measure for a 30 × 50 km domain covering the confluence of the rivers Severn and Avon in the UK. The unknown channel parameters are located by a novel technique utilising the information content and dynamic identifiability analysis (DYNIA) (Wagener et al., 2003) of single and combinations of SAR flood extent maps to find the optimum satellite images for model calibration. Highest information content is found in those SAR flood maps acquired near the peak of the flood hydrograph, and improves when more images are combined. We found that model sensitivity to variation in channel depth is greater than for channel roughness and a successful calibration for depth could only be obtained when channel roughness values were confined to a plausible range. The calibrated reach-average channel depth was within 0.9m (16% error) of the equivalent value determined from river crosssection survey data, demonstrating that a series of moderateresolution SAR data can be used to successfully calibrate the depth parameters of a 2-D hydraulic model. [ABSTRACT FROM AUTHOR]

The rapid progress of lidar technology has made the acquirement and application of high-resolution digital elevation model (DEM) data increasingly popular, especially in regards to the study of floodplain flow. However, high-resolution DEM data pose several disadvantages for flood-plain modeling studies; e.g., the data sets contain many redundant interpolation points, large numbers of calculations are required to work with data, and the data do not match the size of the computational mesh. Two-dimensional (2-D) hydraulic modeling, which is a popular method for analyzing floodplain flow, offers highly precise elevation parameterization for computational mesh while ignoring much of the micro-topographic information of the DEM data itself. We offer a flood simulation method that integrates 2-D hydraulic model results and high-resolution DEM data, thus enabling the calculation of flood water levels in DEM grid cells through local inverse distance-weighted interpolation. To get rid of the false inundation areas during interpolation, it employs the run-length encoding method to mark the inundated DEM grid cells and determine the real inundation areas through the run-length boundary tracing technique, which solves the complicated problem of connectivity between DEM grid cells. We constructed a 2-D hydraulic model for the Gongshuangcha detention basin, which is a flood storage area of Dongting Lake in China, by using our integrated method to simulate the floodplain flow. The results demonstrate that this method can solve DEM associated problems efficiently and simulate flooding processes with greater accuracy than simulations only with DEM. [ABSTRACT FROM AUTHOR]