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Highlights • Soil samples were taken from field under different fertilizations for 175 years. • Soil permeability was calculated using X-ray tomography and pore-scale simulation. • Soil was more isotropic and homogenous at aggregate scale than at core scale. • Soil permeability at core scale increased exponentially with soil carbon. • Soil permeability at aggregate scale increased asymptotically with soil carbon., Soil structure is an indicator of soil quality and its alterations following cropping system conversion or fertilization change evolve slowly. How such alterations vary with scale remains elusive. We investigated this based on the Rothamsted long-term wheat experiment (since 1843) in the UK. Triplicate cores 7 cm high and 10 cm in diameter were taken from plots that have been under different fertilizations or returned to natural woodland for more than one century for imaging using X-ray computed tomography with the voxel size being 40 µm. We then broke each core and sampled three aggregates from it to scan with the voxel size being 1.5 µm. For each core and aggregate sample, we calculated its pore size distribution, permeability and tortuosity. The results showed that the fertilization change >170 years ago reshaped the soil structure differently between the core scale and the aggregate scale. Macro-porosity of the pores (>40 µm) in the cores unfertilized or fertilized with inorganic fertilizers was low and the pores were poorly connected in the top 10 cm of soil, compared to those given farmyard manure or in the woodland. In all treatments, the pores in the core images were hydraulically anisotropic with their permeability in the horizontal direction being higher than that in the vertical direction, whereas the aggregates were comparatively isotropic. The fertilization affected image porosity and permeability at core scale more significantly than at aggregate scale, and the aggregates fertilized with farmyard manure and in the woodland were more permeable than the aggregates in other treatments. It was also found that compared to no-fertilization or fertilization with complete fertilizers, fertilizing without phosphorus over the past 20 years increased the porosity and permeability of the aggregates but not of the cores. Fertilization with inorganic fertilizers increased the tortuosity of the macropores in the cores but not of the intra-aggregate pores, compared to no-fertilization. Porosity-permeability relationship for aggregates unfertilized or fertilized with inorganic fertilisers followed a power law with R2 > 0.8. In contrast, the permeability of the aggregates in farmyard manure and in the woodland trended differently as their porosity increased. The results also revealed that the transport ability of the aggregates and cores responded differently to carbon in that with soil carbon increasing, the permeability of the aggregates increased asymptotically while the permeability of the cores, especially its horizontal component, increased exponentially.

Highlights • The effects of lakes and reservoirs on global daily streamflow are evaluated. • Reservoirs affect model performance substantially in the global domain. • Lakes’ effects on model performance are limited to few catchments. • Lakes and reservoirs reduce return levels discharge thresholds globally. • Reservoir parameters contribute to uncertainty of model performance metrics., Lakes and reservoirs affect the timing and magnitude of streamflow, and are therefore essential hydrological model components, especially in the context of global flood forecasting. However, the parameterization of lake and reservoir routines on a global scale is subject to considerable uncertainty due to lack of information on lake hydrographic characteristics and reservoir operating rules. In this study we estimated the effect of lakes and reservoirs on global daily streamflow simulations of a spatially-distributed LISFLOOD hydrological model. We applied state-of-the-art global sensitivity and uncertainty analyses for selected catchments to examine the effect of uncertain lake and reservoir parameterization on model performance. Streamflow observations from 390 catchments around the globe and multiple performance measures were used to assess model performance. Results indicate a considerable geographical variability in the lake and reservoir effects on the streamflow simulation. Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) metrics improved for 65% and 38% of catchments respectively, with median skill score values of 0.16 and 0.2 while scores deteriorated for 28% and 52% of the catchments, with median values −0.09 and −0.16, respectively. The effect of reservoirs on extreme high flows was substantial and widespread in the global domain, while the effect of lakes was spatially limited to a few catchments. As indicated by global sensitivity analysis, parameter uncertainty substantially affected uncertainty of model performance. Reservoir parameters often contributed to this uncertainty, although the effect varied widely among catchments. The effect of reservoir parameters on model performance diminished with distance downstream of reservoirs in favor of other parameters, notably groundwater-related parameters and channel Manning’s roughness coefficient. This study underscores the importance of accounting for lakes and, especially, reservoirs and using appropriate parameterization in large-scale hydrological simulations.

Summary Reusing culture medium of Arthrospira platensis is quite important in large scale production because its inappropriate disposal could exacerbate problems of environmental pollution. This study evaluates the suitability of using different quantities of exhausted Schlosser medium after continuous treatment using granular activated carbon (GAC) with a residence time ( T ) of 2 h for A. platensis growth in continuous cultivation. A tubular photobioreactor (PBR) and urea as cheap nitrogen source were used, taking as response variables kinetic parameters and biomass composition. The removal of both organic matter and pigment ( OMR and PgR , respectively) was measured to evaluate the efficiency of the treatment process. This treatment process yielded high values of OMR (73.7 ± 0.1%) and PgR (52.4 ± 0.4%) using 75% treated medium, thereby A. platensis biomass with high protein content (42.0 ± 0.6%), 1568 ± 15 mg/L cell concentration under steady-state conditions and 941 mg/L d cell productivity. This alternative to simultaneous treatment with GAC for reuse of Schlosser medium in continuous cultivation could ensure no diminution in either cell productivity or protein content in A. platensis cultivation using tubular PBR with 65% reduction in medium culture costs.

Funding Information: We would like to thank Dr Maria Kämäri, MSc Franziska Wolff, MSc Mariana Verdonen, MSc Tiia Tarsa and MSc Marko Kärkkäinen from the University of Eastern Finland, William Speirs from the University of Queensland (Brisbane, Australia), Dr Carlos Gonzales-Inca and MSc Jouni Salmela from the University of Turku and Dr Nikita Tananaev (Melnikov Permafrost Institute [MPI] at Yakutsk, Russia) for their valuable fieldwork assistance in 2016–2021. We also thank Marko Kärkkäinen for analysing the bedload transport amounts and grain sizes and processing the orthomosaic image from the aerial photos of February 2021. It would not have been possible to conduct the fieldwork without the drilling assistance of Ilkka Syvänperä and Esa Karpoff from the Kevo Subarctic Research Institute of University of Turku during 2016–2021. The authors have no conflicts of interest to declare. The ice-covered flow measurements were initiated under the post-doctoral research project of Dr Lotsari, funded by the Academy of Finland (ExRIVER: grant number 267345). The work for this paper was also supported financially by four other Academy of Finland funded projects (DefrostingRivers: 338480; HYDRO-RDI-Network: 337394 and 337279; InfraRiver: 296090; Green-Digi-Basin 347701). Funding was received from the Maj and Tor Nessling Foundation (ExRIVER, grant numbers: 201300067 and 201500046; Influence of river ice and fluvial processes on river environments now and in the future, grant number: 201600042) and Strategic Research Council at the Academy of Finland (Competence-Based Growth Through Integrated Disruptive Technologies of 3D Digitalization, RobotiCS, Geospatial Information and Image Processing/Computing – Point Cloud Ecosystem, grant number: 293389). The Department of Geographical and Historical Studies, University of Eastern Finland, supported the work financially. Funding was also received from the British Society for Geomorphology (research project title ʻDefrosting sedimentary systems: the impacts on the evolution and material transport of high-latitude riversʼ [registered charity number: 1054260]). Funding Information: The ice-covered flow measurements were initiated under the post-doctoral research project of Dr Lotsari, funded by the Academy of Finland (ExRIVER: grant number 267345). The work for this paper was also supported financially by four other Academy of Finland funded projects (DefrostingRivers: 338480; HYDRO-RDI-Network: 337394 and 337279; InfraRiver: 296090; Green-Digi-Basin 347701). Funding was received from the Maj and Tor Nessling Foundation (ExRIVER, grant numbers: 201300067 and 201500046; Influence of river ice and fluvial processes on river environments now and in the future, grant number: 201600042) and Strategic Research Council at the Academy of Finland (Competence-Based Growth Through Integrated Disruptive Technologies of 3D Digitalization, RobotiCS, Geospatial Information and Image Processing/Computing – Point Cloud Ecosystem, grant number: 293389). The Department of Geographical and Historical Studies, University of Eastern Finland, supported the work financially. Funding was also received from the British Society for Geomorphology (research project title ʻDefrosting sedimentary systems: the impacts on the evolution and material transport of high-latitude riversʼ [registered charity number: 1054260]). Publisher Copyright: © 2022 The Authors Global climate change has been projected to affect hydrology, the ice-covered flow period and river morphology (including changed sediment transport conditions) in northern high-latitude regions. To understand the impact of the expected shortening of the ice-covered period on bedload transport, one needs to understand the present sediment transport in these high-latitude rivers with annually occurring ice cover. Thus, the aims are (1) to define the impacts of ice cover on near-bed flow characteristics during hydrologically varying years, and (2) to analyse the impacts of these mid-winter flow characteristics on the bed sediment transport potential. The analyses are based on Acoustic Doppler Current Profiler (ADCP: 2016–21) and Acoustic Doppler Velocimeter (ADV: 2020–21) measurements performed in mid-winter ice-covered conditions of the sandy and small (circa 20 m wide) Pulmanki River in northern Finnish Lapland. Despite the ice-covered river conditions in winter, sediment transport occurs even during these harshest mid-winter conditions. The critical velocities and shear velocities of mid-winter conditions were exceeded in winters 2016–2021, and bedload transport occurred according to bedload measurements. Three different situations occurred regarding the bed sediment transport and near-bed velocity conditions: (1) high measured mid-winter discharges indicate high velocities throughout the meander bend; (2) low measured mid-winter discharges cause low near-bed velocities throughout the meander bend; (3) winters having intermediate discharges indicate near-bed velocities and sediment transport potential being higher at the upstream inlet and apex sections of the meander bend but clearly lower downstream of the apex. The confinement by the river ice cover, i.e. bottom-fast ice, explains the velocity variation. The near-bed velocities were the highest at the upstream inlet section of a symmetrical meander bend, where the measurement cross-sections were narrower and shallower. The velocities were the lowest downstream of the apex, where the channel changed from relatively narrow to wider and deeper.

Due to rapid urbanization, population growth and economic drivers, megacities and metropolises around the world face increasing water challenges, such as water scarcity, degradation of water resources and water-related risks such as flooding. Climate change is expected to put additional stress on already strained metropolitan water management systems. Although there is considerable research on river basin management and on urban water management, there is hardly any on metropolitan water management. Similarly, as urban water generally emerges from and returns to river basins, it is surprising how little literature there is that explicitly connects these two spheres of governance. Hence this review paper addresses the: What does a review of the literature tell us about the overlap and reconciliation between the concepts of Integrated Water Resources/River Basin Management and Metropolitan/Urban Water Management, particularly in relation to megacities? Based on an extensive literature review, this paper concludes that the key differences between the two are in relation to their overarching framework, scope, inputs and outputs of water and in relation to dealing with extreme weather events. The literature review reveals how sustainable and integrated urban water management increasingly adopt principles and rhetoric from integrated water resource management, this has yet to translate into significant changing practices on the ground. Urban water management still often occurs independently of river basin issues. Achieving coherence between river basin management and sustainable/integrated urban water management is even more difficult in metropolises and megacities, because the latter consists of multiple political-administrative units. The article concludes that the scalar mismatch between river basin management and metropolitan/megacity water governance deserves much greater attention than it currently receives in the academic and policy debates.

In the United States, fluvial flood risk is managed by the National Flood Insurance Program (NFIP), which delineates areas that have a 1% chance of flooding each year (i.e. the 100-year floodplain). Development within and adjacent to riverine floodplains exacerbates flood losses by increasing peak discharge and runoff volume, shortening the time to peak, and altering the extent of the floodplain. This paper improves understanding of how future development can alter the 100-year floodplain in a watershed in Houston, TX through land use projection, hydrologic and hydraulic modeling, and implements a novel method for considering the impact of both regional trends in development and site-scale development policies on runoff response. The methodology presented in this paper integrates future development scenarios from a machine learning land use projection model with distributed hydrologic modeling and coupled 1D/2D unsteady hydraulic modeling to produce future floodplain estimates. Current site-scale detention requirements are represented within the hydrologic model to evaluate the regional effectiveness of these policies under future development conditions in 2050. Results indicate that the 100-year floodplain can expand by up to 12.5% across the watershed as a result of projected development in 2050 using current stormwater mitigation policies, and the number of parcels within the floodplain can increase by up to 18.8%. This study demonstrates how incremental land use changes can significantly alter the reality of flood risk in urbanizing watersheds, and how existing land use policies may be insufficient to mitigate impacts from future development.

Water diplomacy may be understood broadly as the measures that may be taken to prevent or peacefully resolve conflicts over water resources concerning their availability, allocation or use between and within states. The concept is preventive in nature as well as offering an approach for conflict resolution. Instruments of international water law, among them notably conventions and soft law developed on that basis – which promote equitable and reasonable use of transboundary waters and prevention of transboundary impact – can serve as tools for water diplomacy. The obligation to establish agreements on shared waters and joint bodies to govern them has contributed to gathering important experience, and some of this has been synthesized into the Principles for Effective Joint Bodies which were adopted by the Meeting of the Parties to the UNECE Water Convention in 2015. The Principles are intended as a resource to increase the effectiveness of joint bodies in transboundary water cooperation. This paper analyses Finland’s cooperation arrangements in the light of the Principles and assesses the extent to which Finland’s transboundary water commissions reflect the good practices specified in the Principles. Taking a wider perspective, the paper also examines the elements of the principles and their practical realisation with a view to understanding better their promotion of water diplomacy. Relevant features include, inter alia, the competency and representation of the joint institution, its accountability and the extent to which public participation is permitted, and the cooperative mechanisms in place. Naturally the underlying transboundary water agreements specify the framework for cooperation between the riparian states to a great extent, but the established joint bodies often play a significant role, specifically in the equitable use and management of the shared water resources, but even beyond, in the prevention and settling of conflicts, and in the general promotion of cooperation and security at a regional level.

Selection of suitable urban stormwater harvesting sites and associated project planning are often complex due to spatial, temporal, economic, environmental and social factors, and related various other variables. This paper is aimed at developing a comprehensive methodology framework for evaluating of stormwater harvesting sites in urban areas using Multi Criteria Decision Analysis (MCDA). At the first phase, framework selects potential stormwater harvesting (SWH) sites using spatial characteristics in a GIS environment. In second phase, MCDA methodology is used for evaluating and ranking of SWH sites in multi-objective and multi-stakeholder environment. The paper briefly describes first phase of framework and focuses chiefly on the second phase of framework. The application of the methodology is also demonstrated over a case study comprising of the local government area, City of Melbourne (CoM), Australia for the benefit of wider water professionals engaged in this area. Nine performance measures (PMs) were identified to characterise the objectives and system performance related to the eight alternative SWH sites for the demonstration of the application of developed methodology. To reflect the stakeholder interests in the current study, four stakeholder participant groups were identified, namely, water authorities (WA), academics (AC), consultants (CS), and councils (CL). The decision analysis methodology broadly consisted of deriving PROMETHEE II rankings of eight alternative SWH sites in the CoM case study, under two distinct group decision making scenarios. The major innovation of this work is the development and application of comprehensive methodology framework that assists in the selection of potential sites for SWH, and facilitates the ranking in multi-objective and multi-stakeholder environment. It is expected that the proposed methodology will assist the water professionals and managers with better knowledge that will reduce the subjectivity in the selection and evaluation of SWH sites.

Relative permeability controls the flow of multiphase fluids in porous media. The estimation of relative permeability is generally solved by Levenberg-Marquardt method with finite difference Jacobian approximation (LM-FD). However, the method can hardly be used in large-scale reservoirs because of unbearably huge computational cost. To eliminate this problem, the paper introduces the idea of simultaneous perturbation to simplify the generation of the Jacobian matrix needed in the Levenberg-Marquardt procedure and denotes the improved method as LM-SP. It is verified by numerical experiments and then applied to laboratory experiments and a real commercial oilfield. Numerical experiment indicates that LM-SP uses only 16.1% computational cost to obtain similar estimation of relative permeability and prediction of production performance compared with LM-FD. Laboratory experiment also shows the LM-SP has a 60.4% decrease in simulation cost while a 68.5% increase in estimation accuracy compared with the earlier published results. This is mainly because LM-FD needs 2n (n is the number of controlling knots) simulations to approximate Jacobian in each iteration, while only 2 simulations are enough in basic LM-SP. The convergence rate and estimation accuracy of LM-SP can be improved by averaging several simultaneous perturbation Jacobian approximations but the computational cost of each iteration may be increased. Considering the estimation accuracy and computational cost, averaging two Jacobian approximations is recommended in this paper. As the number of unknown controlling knots increases from 7 to 15, the saved simulation runs by LM-SP than LM-FD increases from 114 to 1164. This indicates LM-SP is more suitable than LM-FD for multivariate problems. Field application further proves the applicability of LM-SP on large real field as well as small laboratory problems.

The use of radar measurements for the space time estimation of precipitation has for many decades been a central topic in hydro-meteorology. In this paper we are interested specifically in daily and sub-daily extreme values of precipitation at gauged or ungauged locations which are important for design. The purpose of the paper is to develop a methodology to combine daily precipitation observations and radar measurements to estimate sub-daily extremes at point locations. Radar data corrected using precipitation-reflectivity relationships lead to biased estimations of extremes. Different possibilities of correcting systematic errors using the daily observations are investigated. Observed gauged daily amounts are interpolated to unsampled points and subsequently disaggregated using the sub-daily values obtained by the radar. Different corrections based on the spatial variability and the subdaily entropy of scaled rainfall distributions are used to provide unbiased corrections of short duration extremes. Additionally a statistical procedure not based on a matching day by day correction is tested. In this last procedure as we are only interested in rare extremes, low to medium values of rainfall depth were neglected leaving a small number of L days of ranked daily maxima in each set per year, whose sum typically comprises about 50% of each annual rainfall total. The sum of these L day maxima is first iterpolated using a Kriging procedure. Subsequently this sum is disaggregated to daily values using a nearest neighbour procedure. The daily sums are then disaggregated by using the relative values of the biggest L radar based days. Of course, the timings of radar and gauge maxima can be different, so the method presented here uses radar for disaggregating daily gauge totals down to 15 min intervals in order to extract the maxima of sub-hourly through to daily rainfall. The methodologies were tested in South Africa, where an S-band radar operated relatively continuously at Bethlehem from 1998 to 2003, whose scan at 1.5 km above ground [CAPPI] overlapped a dense (10 km spacing) set of 45 pluviometers recording in the same 6-year period. This valuable set of data was obtained from each of 37 selected radar pixels [1 km square in plan] which contained a pluviometer not masked out by the radar foot-print. The pluviometer data were also aggregated to daily totals, for the same purpose. The extremes obtained using disaggregation methods were compared to the observed extremes in a cross validation procedure. The unusual and novel goal was not to obtain the reproduction of the precipitation matching in space and time, but to obtain frequency distributions of the point extremes, which we found to be stable.

International audience; Surface runoff is the hydrological process at the origin of phenomena such as soil erosion, floods out of rivers, mudflows, debris flows and can generate major damage. This paper presents a method to create maps of surface runoff susceptibility. The method, called IRIP (Indicator of Intense Pluvial Runoff, French acronym), uses a combination of landscape factors to create three maps representing the susceptibility (1) to generate, (2) to transfer, and (3) to accumulate surface runoff. The method input data are the topography, the land use and the soil type. The method aims to be simple to implement and robust for any type of study area, with no requirement for calibration or specific input format. In a second part, the paper focuses on the evaluation of the surface runoff susceptibility maps. The method is applied in the Lézarde catchment (210 km², northern France) and the susceptibility maps are evaluated by comparison with two risk regulatory zonings of surface runoff and soil erosion, and two databases of surface runoff impacts on roads and railways. Comparison tests are performed using a standard verification method for dichotomous forecasting along with five verification indicators: accuracy, bias, success ratio, probability of detection, and false alarm ratio. The evaluation shows that the susceptibility map of surface runoff accumulation is able to identify the concentrated surface runoff flows and that the susceptibility map of transfer is able to identify areas that are susceptible to soil erosion. Concerning the ability of the IRIP method to detect sections of the transportation network susceptible to be impacted by surface runoff, the evaluation tests show promising probabilities of detection (73-90%) but also high false alarm ratios (77-92%). However, a qualitative analysis of the local configuration of the infrastructure shows that taking into account the transportation network vulnerability can explain numerous false alarms. This paper shows that the IRIP method can be a valuable tool to facilitate field analysis and perform surface runoff zonings and opens interesting prospects for the use of the IRIP method in a context of risk management.

This paper describes a Bayesian statistical model for estimating flood frequency by combining uncertain annual maximum (AMAX) data from a river gauge with estimates of flood peak discharge from various historic sources that predate the period of instrument records. Such historic flood records promise to expand the time series data needed for reducing the uncertainty in return period estimates for extreme events, but the heterogeneity and uncertainty of historic records make them difficult to use alongside Flood Estimation Handbook and other standard methods for generating flood frequency curves from gauge data. Using the flow of the River Eden in Carlisle, Cumbria, UK as a case study, this paper develops a Bayesian model for combining historic flood estimates since 1800 with gauge data since 1967 to estimate the probability of low frequency flood events for the area taking account of uncertainty in the discharge estimates. Results show a reduction in 95% confidence intervals of roughly 50% for annual exceedance probabilities of less than 0.0133 (return periods over 75 years) compared to standard flood frequency estimation methods using solely systematic data. Sensitivity analysis shows the model is sensitive to 2 model parameters both of which are concerned with the historic (pre-systematic) period of the time series. This highlights the importance of adequate consideration of historic channel and floodplain changes or possible bias in estimates of historic flood discharges. The next steps required to roll out this Bayesian approach for operational flood frequency estimation at other sites is also discussed.

In this paper, a method based on Approximate Empirical likelihood ratio and a Deviance function combined with bootstrapping (AED-BP) is proposed to construct a confidence curve for the location of a change point. The method is compared with a method based on parametric Profile Likelihood and a Deviance function combined with Monte Carlo simulation (PLD-MC). A confidence curve provides a representation of the uncertainty in the outcome of the change point analysis. To evaluate the practical usability of confidence curves constructed by AED-BP, its properties were examined and its performance was compared to that of PLD-MC. The methods were applied to both synthetic and real data. Synthetic data were generated from three parametric distributions: Frechet with a constant shape parameter, log-normal, and gamma distributions. The real data are the hydrometeorological data analysed in other studies. The change points found in the original publications are used as a reference in this present paper. The results show that AED-BP has a performance that is similar to PLD-MC, but has an advantage in that it is not necessary to select a distribution family for the data. The AED-BP results on the Annual Maximum Runoff series for the stations Yichang and Hankou along the Yangtze river are among the first that show a possible effect of the presence of the Three Gorges dam.

Summary Mulched drip irrigation for cotton field is an effective measure for the utilization of saline water, and the regulation of soil water and salt. However, the reasonable methods for quantifying actual evapotranspiration (ET) and deep percolation of recharge to groundwater are still not very well understood, which restricts the accurate regulation of soil water and salt for cotton growth in oasis. In this paper, a set of experiments of mulched drip irrigation with brackish water were conducted in a typical arid region of Tarim basin in southern Xinjiang, China. The irrigation events were recorded, and ET and fluctuations of groundwater table were carefully measured for two consecutive irrigation periods of flowering and bolling stages. A group of upscaling conversion methods were used to quantify the ET, in which canopy structure was considered to estimate the transpiration from leaf scale to a unit of field scale. The groundwater table had a significant response to the irrigation events, thus the deep percolation was estimated using water-table fluctuation method (WTF). Results showed that during the two irrigation events of flowering and bolling stages, the total ET was 31.1 mm with the soil surface evaporation of only 0.4 mm. The total percolation of recharge to groundwater was 48.2 mm which contributed to the groundwater run-off of 22.1 mm. Transpiration of 30.7 mm accounted for 98.6% of the total ET of 31.1 mm and 34.3% of the irrigation water of 90.6 mm. Compared with transpiration, the deep percolation accounted for 53.2% of irrigation water, indicating a serious excessive irrigation that recharged to groundwater. Soil salt budget showed that the salt leached into groundwater was 1.56 times of the input from brackish irrigation water and fertilization during the two irrigation periods. Even for the irrigation practice with brackish water, the accumulated salt of soil profile could also be leached out under large amount of irrigation water (e.g. 90.6 mm for the two irrigation periods, 10 days). However, the waste of enormous water which for instance occupied 53.2% of the irrigation water in this study was not conducive to the sustainable utilization of water resources in the arid oasis. Furthermore, the methods introduced in this paper for ET and deep percolation calculation of cotton filed could be used to quantify the oasis hydrologic cycle of micro-irrigation, to gain a better understanding of the ecological process.

The transboundary nature of water dividing Mexico and the United States (U.S.) transforms the entire border region into an instrument of cooperation, a source of conflict, a national security issue, and an environmental concern. Reasonable data collection and research analysis have been conducted for surface waters by joint governmental institutions and non-governmental bodies. However, with the exception of the U.S. Transboundary Assessment Act Program (TAAP) (focusing on the Hueco Bolson, Mesilla Bolson, San Pedro and Santa Cruz aquifers), there is no comparable research, institutional development, or assessment of transboundary groundwater issues on the frontier. Moreover, data collection and methodologies vary between the two countries, there is no broadly accepted definition of the transboundary nature of an aquifer, and available legal and policy frameworks are constrained by non-hydrological considerations. Hence, there is a conceptual and institutional void regarding transboundary groundwater resources between Mexico and the U.S. The purpose of this paper is to bridge this void and characterize transboundary aquifers on the Mexico–US border. It reviews existing international frameworks for identifying hydrological and social criteria that characterize an aquifer as transboundary. It then assesses data from both countries to propose where and which aquifers could be considered transboundary. Finally, the paper proposes an agenda for assessing Mexico–US transboundary aquifers as a means for improving groundwater management in the border region.

Summary This paper presents the modelling results of several tracer-tests performed in the cave system of Han-sur-Lesse (South Belgium). In Han-sur-Lesse, solute flows along accessible underground river stretches and through flooded areas that are rather unknown in terms of geometry. This paper focus on the impact of those flooded areas on solute transport and their dimensioning. The program used (One-dimensional Transport with Inflow and Storage: OTIS) is based on the two-region non equilibrium model that supposes the existence of an immobile water zone along the main flow zone in which solute can be caught. The simulations aim to replicate experimental breakthrough curves (BTCs) by adapting the main transport and geometric parameters that govern solute transport in karst conduits. Furthermore, OTIS allows a discretization of the investigated system, which is particularly interesting in systems presenting heterogeneous geometries. Simulation results show that transient storage is a major process in flooded areas and that the crossing of these has a major effect on the BTCs shape. This influence is however rather complex and very dependent of the flooded areas geometry and transport parameters. Sensibility tests performed in this paper aim to validate the model and show the impact of the parametrization on the BTCs shape. Those tests demonstrate that transient storage is not necessarily transformed in retardation. Indeed, significant tailing effect is only observed in specific conditions (depending on the system geometry and/or the flow) that allow residence time in the storage area to be longer than restitution time. This study ends with a comparison of solute transport in river stretches and in flooded areas.

Stochastic Storm Transposition (SST) involves resampling and random geospatial shifting (i.e. transposition) of observed storm events to generate hypothetical but realistic rainstorms. Though developed as a probabilistic alternative to probable maximum precipitation (PMP) and sharing PMP’s storm transposition characteristic, SST can also be used in more typical rainfall frequency analysis (RFA) and flood frequency analysis (FFA) applications. This paper explains the method, discusses its origins and linkages to both PMP and RFA/FFA, and reviews the development of SST research over the past six decades. Discussion topics includes: the relevance of recent advances in precipitation remote sensing to frequency analysis, numerical weather prediction, and distributed rainfall-runoff modeling; uncertainty and boundedness in rainfall and floods; the flood frequency challenges posed by climatic and land use change; and the concept of multi-scale flood frequency. Recent literature has shown that process-based multiscale FFA, in which the joint distributions of flood-producing meteorological and hydrological processes are synthesized and resolved using distributed physics-based rainfall-runoff models, provides a useful framework for translating nonstationary hydroclimatic conditions into flood frequency estimates. SST pairs well with the process-based approaches. This pairing is promising because it can leverage advances from other branches of hydrology and hydrometeorology that appear to be difficult to integrate into better-known RFA and FFA approaches. The paper closes with several recommendations for future SST research and applications.

This paper presents a new framework for quantitatively identifying, characterizing and analyzing systematic hydrological cycles resulting from streamflow variability in a way that integrates water supply and water demand. The hydrological cycles in question are measures of the most severe drought and pluvial events in a historical record of streamflow, along with their respective durations. The metrics developed here to quantify such episodes are based on an extended sequent peak algorithm that tracks the dynamic shifts in hydrological behavior of streamflow by accounting for water supply and demand with respect to streamflow. In the interest of being able to analyze the largest possible scope of hydrological cycles and behavior, we apply the quantitative methods developed in this paper to streamflow reconstructions in the Upper Missouri River Basin (UMRB) as a case study. We find that the duration of dry periods increase conspicuously as a function of increasing demand levels, the duration of pluvial events decrease as a function of increasing demand levels, and that the general tendency is for streamflow gauges on or near the main stem of the river to have shorter dry spell durations and typically lower drought severity. On the other hand, being on or near the main stem tends to result in longer-duration pluvial events, though these pluvials are typically less severe than those off the main stem. Persistence and spatial variability of streamflow reconstructions were also analyzed to shed further light on the spatial patterns identified earlier, and to see if this variability and persistence may have an influence on the behavior of the streamflow as quantified by the metrics defined in this paper. Finally, it was found that there is a stochastic dependence between the length of a drought and the time to recovery from that drought, and this dependence is used to create simple conditional probability curves to help water managers prepare for future extreme events.

[EN] An increase in water demands, exacerbated by climate change and the tightening of environmental requirements, leads to a reduction in available water resources for economic uses. This situation poses challenges for water resource planning and management. Water accounting has emerged as an appropriate tool to improve transparency and control in water management. There are multiple water accounting approaches, but they generally involve a very exhaustive list of accounted concepts. According to our findings in this research, one of the best water accounting methodologies is the Australian Water Accounting Standard. However, its implementation for integrated water resource planning and management purposes calls into questioning the amount of information and level of detail necessary for the users of water accounts. In this paper, we present a different method of applying the Australian Water Accounting Standard in relation to water resource management, which improves its utility. In order to compare the original approach and that proposed here, we present and discuss an application to the Júcar Water Resource System, in eastern Spain. 2014 Elsevier B.V. All rights reserved., Authors would like to thank Universitat Politecnica de Valencia for its Support Programme for Research and Development, and the Spanish Ministry of Economy and Competitiveness for its financial support through the projects SCARCE (Consolider-Ingenio 2010 CSD2009-00065) and NUTEGES (CGL2012-34978). We also value the support provided by the European Community's Seventh Framework Program in financing the projects SIRIUS (FP7-SPACE-2010-1, 262902), DROUGHT-R&SPI (FP7-ENV-2011, 282769) and ENHANCE (FP7-ENV-2012, 308438). We would also like to express our gratitude to the Jucar River Basin District Agency (Spanish Ministry of Environment) for the data provided to develop this study. Finally, thanks to the Commonwealth Scientific and Industrial Research Organisation in Adelaide, Australia, for hosting one of the authors for a research stay. This paper reflects only the authors' viewpoints and the mentioned institutions are not liable for any use that may be made of the information herein contained.

[Departement_IRSTEA]Eaux [TR1_IRSTEA]GEUSI; International audience; Water governance is a complex process to manage and improve due to the large numbers of competing scales and levels inherent within it. Effectively supporting any water governance process does not just rely on hydrological knowledge of a water system, but much broader trans‐disciplinary understanding of a whole socialhydrological system. In this paper we show how there are commonly up to eight or more competing scales—spatial, temporal, administrative, institutional, management, network, knowledge/information and stakes/issues—present in any water governance situation. Processes in one scale can then create flows or externalities that produce multi‐level, cross‐scale or rescaling effects. A typology of six types of externalities orflows is provided—physical or material flows (e.g. water and solute movement), information and knowledge, political and social control, financial flows, human flows, and an irreversibility effect (e.g. flows, such as that of time passing, which lead to cumulative effects that are difficult or impossible to reverse)—and used to study the examples provided in the 15 papers of this special issue. From these insights, conclusions are drawn on how conflicts across competing scales are currently being managed, the mechanisms involved in bridging scales, and to what extent currently privileged scales and/or governance structures are appropriate for effectively managing water and land. The two general trends observed for multi‐level and cross‐scale management remain the need for collaborative governance processes and facilitators of these interactions, as well as the development of savvy coalitions for water governance change who understand and can effectively navigate these complex multi‐level and multi‐scalar systems. There is also a need to recognise that water basins or watersheds are social constructions and not always the most effective arenas for water governance. Problemsheds based on conceptssuch as the French “territoire” (territory), may in fact prove more pertinent in many cases (e.g. highly engineered systems) due to the unequivocal social nature of their construction and ability to delineate a range of agreed upon social‐hydrological systems for management.

Summary The effects of climate change on water resources have been studied extensively throughout the world through the use of hydrologic models coupled with General Circulation Model (GCM) output or climate sensitivity scenarios. This paper examines the effects of hydrologic model parameterization uncertainty or equifinality, where multiple unique hydrologic model parameter sets can result in adequate calibration metrics, on hydrologic projections from downscaled GCMs for three snowmelt-dependent watersheds (upper reaches of the Clearwater, Gunnison, and Sacramento River watersheds) in the western United States. The hydrologic model used in this study is the Soil and Water Assessment Tool (SWAT) and is calibrated for discharge at the watershed outlet in each watershed. Despite achieving similar calibration metrics, a majority of hydrologic projections of average annual streamflow during the 2080s were statistically different, with differences in magnitude and direction (increase or decrease) compared to historical annual streamflows. At the average monthly time-scale, a majority of the hydrologic projections varied in peak streamflow timing, peak streamflow magnitude, summer streamflows, as well as overall increases or decreases compared to the historical monthly streamflows. Snowmelt projections from the SWAT model also widely varied, both in depth and snowmelt peak timing, for all watersheds. Since a large portion of the runoff-producing regions in the western United States is snowmelt-dependent, this has large implications for the prediction of the amount and timing of streamflow in the coming century. This paper shows that hydrologic model parameterizations that give similar adequate calibration metrics can lead to statistically significant differences in hydrologic projections under climate change. Therefore, researchers and water resource managers should account for this uncertainty by assembling ensemble projections from both multiple parameter sets and GCMs.

In the Lower Limestone Coast, South Australia, a unique water allocation plan has been under consideration for several years. This plan is the first in Australia to consider forestry as a water affecting activity. Indeed, forestry plantations have a twofold impact on water-rainfall or aquifer recharge interception and direct extraction of groundwater in shallow water table areas-and alter the available water for irrigation as a result of the previous water budget. This paper examines how water is allocated across the competing requirements for water but also across the competing legal, economic and administrative scales embodied by the competing water users; and thus it also details the pre-judicial mechanism used to resolve the conflict over these competing scales. Qualitative and quantitative content analysis in Nvivo was applied to: (i) 180 local newspaper articles on the planning process, (ii) 65 submission forms filled in by the community during a public consultation on the draft water plan and (iii) 20 face-to-face interviews of keys stakeholders involved in the planning process. The social sustainability perspective taken in this study establishes the legal, economic and administrative competitive scales at stake in the conflict regarding water between forestry and irrigation. It also evidences the special feature of this paper, which is that to overcome these competitions and resolve the local conflict before judicial process, the water governance moved up in the administrative scale, from local/regional to State level. Initiated and initially prepared at regional level through the local Natural Resources Management Board, the water planning process was taken up to State level through the formation of an Interdepartmental Committee and the establishment of a Taskforce in charge of developing a policy. These were supported by an amendment of a State legislation on Natural Resources Management to manage the water impacts of forestry plantations. Refereed/Peer-reviewed

summary This paper considers the impact of tidal forcing on regional groundwater flow in an unconfined coastal aquifer. Numerical models are used to quantify this impact for a wide range of hydrogeological conditions. Both a shallow and a deep aquifer are investigated with regard to three dimensionless parameter groups that determine the groundwater flow to a large extent. Analytical expressions are presented that allow for a quick estimate of the regional scale effect of tidal forcing under the same conditions as used in the numerical models. Quantitatively, the results in this paper are complementary to previous studies by taking into account variable density groundwater flow, dispersive salt transport and a seepage face in the intertidal area. Qualitatively, the results are in line with previous investigations. The time-averaged hydraulic head at the high tide mark increases upon a decrease of each of the three considered dimensionless parameter groups: R (including the ratio of the hydraulic conductivity and the precipitation excess), a (the slope of the intertidal area) and AL (the ratio of the width of the fresh water lens and the tidal amplitude). The relative change of the location and the hydraulic head of the groundwater divide, which together characterize regional groundwater flow, increase as a and AL decrease, but decrease as R decreases. The difference between the analytical solutions and numerical results is small. Therefore, the presented analytical solutions can be used to estimate the bias that is introduced in a numerical model if tidal forcing is neglected. The results should be used with caution in case of significant wave forcing, as this was not considered.

Optical remote sensing images are a common data sources for surface water monitoring, while they are easily contaminated by clouds, cloud shadows, terrain shadows, etc., resulting in spatial gaps in surface water images. This paper proposes a surface water gap-filling method based on Naive Bayes classification. It uses the historical cloud-free binary (water, non-water) surface water images as prior data and the uncontaminated pixels in the partially contaminated ternary (water, non-water, contaminated pixels) surface water image as evidence to identify the category of gap pixels to achieve the purpose of gap-filling. This method considers the relationship between disconnected water bodies and does not depend on terrain data. When the image is heavily covered by clouds, this method can also reconstruct the complete water extent accurately. Five study areas with different scenarios including rivers, lakes or reservoirs, are selected to evaluate the method. Results show that the average gap-filling accuracy in all five study areas is over 90 %. After gap-filling, the time series of surface water area presents a good correlation with the time series of water level (e.g., the coefficient of determinationR2 = 0.95 in the Dartmouth reservoir). The proposed method is proved effective in filling gaps caused by clouds, cloud shadows and terrain shadows in surface water image, and it would be suitable for high-frequency surface water monitoring and near real-time surface water mapping.

The economic literature has extensively researched water markets, finding that this instrument can deliver superior resource allocations under growing scarcity. However, these assessments typically ignore the information, bargaining, and enforcement costs that occur in trades, known as transaction costs, which can be particularly relevant in emerging markets such as those for water. This paper presents a multi-agent cellular automata model that couples a positive multi-attribute utility programming (PMAUP) model with an agent-based model (ABM) to elicit the information transaction costs of water trading under alternative market and climate scenarios. A first experiment evaluates an ideal water market with no transaction costs, which is then compared to alternative decentralized spot market setups representing different degrees of information availability that are modeled using the coupled PMAUP-ABM. The difference between the economic surplus under the ideal market and that achieved under alternative market setups with information constraints is used as a proxy value of information transaction costs. Methods are illustrated with an application to the Douro River Basin in central Spain. Results show that information transaction costs can reduce the economic surplus between 0.6% and 45% depending on the scenario.

Model Predictive Control (MPC) of combined sewer systems can reduce environmental degradation caused by uncontrolled overflows. However, practical uncertainties are often neglected when assessing the potential of MPC strategies. This paper aims to understand the risks associated with using a non-perfect internal MPC-model, real precipitation forecast, and realistic dynamic system capacity fluctuations. An MPC with the objective to reduce the total combined sewer overflow (CSO) volume was implemented in the case study of Eindhoven in the Netherlands where highly sensitive waterways receive the sewer overflows. Two types of risks were identified: relative system performance loss and operative deterioration. The former entails a practical decrease in efficacy of controlling CSO spills compared to the theoretical situation, whereas the latter describes the aggravation of environmental pollution compared to a static form of system operation. The results obtained demonstrate that precipitation forecast uncertainty is associated with a small relative system performance loss. Opposite to this, significant performance loss was observed as a consequence of uncertainties in the internal MPC model and the actual sewer system capacity available. The latter caused additional combined sewer overflows compared to a statically optimised control for smaller precipitation events.

The random walk path method (RWP) is a stochastic model that transforms the solution of the unsteady open channel flow equations into a probability problem. In this paper, this method is introduced to solve the discretized Saint-Venant equations, with probabilistic representation of the water levels at junctions. Different boundary conditions, which specify either water levels or discharge hydrographs, can be implemented by specifying how walkers react when arriving at the boundaries. The pointwise solution at river junctions can be obtained via random walk simulations. The efficacy of the model was verified against the following test cases: (1) a real-world looped channel example documented in the manual of the software Hec-Ras and (2) a hypothetical channel system consisting of dendritic and divergent networks. The number of random simulations is an important aspect of the RWP method and needs to be chosen by considering the trade-off between precision and computational efficiency. The impact of the boundary water level or discharge on the water levels at internal nodes can be quantitatively evaluated by adopting the terminal weights, which present a distinct advantage of the RWP method. This assessment of water levels can serve as a guide in the operation of hydraulic controls, such as dams, sluices and pumps, to effectively regulate the flow in mitigating flood risks.

Tropical regions have experienced the fastest Land Use Land Cover Change (LULCC) in the last decades, coupled with climate change (CC) this has affected the hydrological and geomorphological processes of river systems. With the increased demand for land, the general trend has been the loss of forest land to agriculture and settlements. These changes have altered the water balance components through enhanced or reduced evaporation, peak flow, flooding, and river morphology. The aim of this review paper is to provide a meta-analysis on the effects of spatiotemporal changes in climate and LULC on river hydro-morphology in the tropics. Following a systematic search, 60 case studies were identified, of which the majority (68%) experienced forest loss due to agricultural and urban expansion, resulting in increased streamflow, surface flow, and total water yield and decreased ET and groundwater recharge. 12% of the case studies showed the impacts of LULCC on channel morphology features through sediment transport and riverbank erosion. Results from this study show limited correlation between LULCC and hydrological variables, indicating that there are likely other factors controlling hydrological processes. Catchment heterogeneity including soil and topography play an important role. Based on studies that project these changes into the future, similar trends are expected over the next decades, with differences based on LU and climate scenarios. There are still limited studies on river hydro-morphology responses to LULCC and CC in the tropics despite the major changes taking place there. In light of future changes, more studies are needed to improve our understanding.

Model-based polarimetric decomposition can separate to some extent the backscattered radar signals from the vegetation canopy and the underlying ground, hence enabling a strategy for soil moisture retrieval in vegetated agricultural fields. However, the volume scattering models used in previous studies are only applicable to specific cases, making it difficult to completely remove the volume component induced by the vegetation layer. In this paper, three generalized volume scattering models (i.e., generalized volume scattering model (GVSM), simplified adaptive volume scattering model (SAVSM), and simplified Neumann volume scattering model (SNVSM)) are incorporated in the decomposition and evaluated for soil moisture retrieval. Considering the complexity and descriptive ability of the available physical models, a modified two-component model-based decomposition is proposed as the basic decomposition framework. This decomposition is also based on the physical constraint of the dielectric constants included in the model. The employed models combine an X-Bragg surface scattering model with three continuous generalized volume scattering models. The analytic solution of the parameters is obtained, and the minimum power criterion is used to determine the optimal solution to fit the model. By using the proposed model-based decomposition framework, the performance of the three models to simulate the canopy scattering and, as a result, to later estimate soil moisture under agricultural vegetation is evaluated. Fully polarimetric RADARSAT-2 C-band images acquired on eight dates in 2013 and 2015 over fields covered by two crops (wheat and soybean) were employed for validation. Results show that the proposed decomposition method, using any of the three volume scattering models, can provide promising inversion results of soil moisture, with RMSEs ranging from 2.89 to 7.43 [vol.%]. Compared with the other two models, the SNVSM simulates the vegetation contribution more accurately in this framework, and it provides a stable soil moisture inversion performance at different crop phenological stages, with an optimal overall accuracy of RMSE=4.99 [vol.%] and a correlation coefficient of R=0.78. This work was supported in part by the National Natural Science Foundation of China (Grant No. 41820104005, 42171387, 41804004, 42101400), the Canadian Space Agency SOAR-E Program (Grant No. SOAR-E-5489), and the Spanish Ministry of Science and Innovation (AEI Grant No. PID2020-117303GB-C22).

This paper is concerned with the formulation of an adequate likelihood function in the application of Bayesian epistemology to uncertainty quantification of hydrologic models. We focus our attention on a special class of likelihood functions (hereinafter referred to as distribution-adaptive likelihood functions), which do not require prior assumptions about the expected distribution of the residuals, rather inference takes place over the hypotheses (model parameters) and space of distribution functions. Our goals are threefold. First, we present theory of a revised implementation of the generalized likelihood (GL) function of Schoups and Vrugt (2010) wherein residual standardization precedes the treatment of serial correlation. This so-called GL+ function, enjoys a solid statistical underpinning and guarantees a more robust joint inference of the autoregressive coefficients and residual properties. Then, as secondary goal, we present a further generalization of the GL+ function, coined the universal likelihood (UL) function, which extends applicability to highly asymmetrical lepto- and platy-kurtic residual distributions. The UL function builds on the 5-parameter skewed generalized Student’s 𝑡 distribution of Theodossiou (2015) which makes up a large family of continuous probability distributions including (but not limited to) symmetric and skewed forms of the generalized normal, generalized 𝑡, Laplace, normal, Student’s 𝑡, and Cauchy-Lorentz distributions. As our third and last goal, we present the use of strictly proper scoring rules to evaluate, compare and rank likelihood functions. These scoring rules condense the accuracy of a distribution forecast to a single value while retaining attractive statistical properties. The GL+ and UL functions are illustrated using data of a simple autoregressive scheme and benchmarked against the GL function, Student 𝑡 likelihood (SL) of Scharnagl et al. (2015) and normal likelihood (NL) for a conceptual hydrologic model using measured streamflow data. Our results show that, (i) the GL+ function is superior to the GL function, (ii) the active set of nuisance variables exerts a large control on the performance of the GL+, SL and UL functions, (iii) the treatment of autocorrelation deteriorates the scoring rules and performance metrics of the forecast distribution, (iv) a leptokurtic distribution is favored for discharge residuals, (v) scoring rules are indispensable in our search for the true forecast distribution, and (vi) the use of multiple strictly proper scoring rules turns the selection of an adequate likelihood function into a multi-criteria problem.

Mud flows represent one of the major causes of natural hazards in mountain regions. Similarly to debris flows, they consist of a hyper-concentrated mixture of water and sediments flowing down a slope and may cause serious damages to people and structures. The present paper investigates the force produced by a dam-break wave of mud impacting against a rigid wall. A power-law shear-thinning model is used to describe the rheology of the hyper-concentrated mixture. A one-dimensional shallow water model is adopted and a second-order Finite Volume scheme is employed to numerically solve the governing equations. The results indicate that depending on the fluid rheological parameters and on the bottom slope, there exists a minimum value of the wall distance above which the peak force does not exceed the asymptotic value of the hydrostatic final condition. For two different values of the channel slope, the dimensionless value of this lower bound is individuated for several values of the power-law exponent and of a dimensionless Basal Drag coefficient. An estimation of the maximum peak force for wall distance smaller than the minimum value is also provided.

Naturally fractured reservoirs (NFRs) are among major oil and gas producing reservoirs that are commonly targeted for various enhanced oil recovery (EOR) techniques, particularly water-alternating-gas (WAG) injection. Production from NFRs is complicated due to the flow communication between the matrix and fractures in such porous media. The implementation of WAG injection in NFRs features inherent complexities not only related to the three-phase flow, saturation history, and cycle-dependent hysteresis of the individual phases, but also the fracture-matrix communication, fingering, and early breakthrough of the injected phases particularly during gas injection processes. This paper provides the key results on the computational fluid dynamics (CFD) simulation of WAG injection in a fractured system. We evaluate the impacts of hysteresis, fracture characteristics (aperture, orientation, and fracture density in the network), and the three-phase relative permeability of available phases during the WAG injection. The CFD model simulates an immiscible WAG injection and the CFD results are compared to the experimental data in a strong water-wet sand-pack. Similar to the experiments, we simulate Maroon crude as the oil phase, and synthetic brine, and pure CO2 at 100 oC and atmospheric outlet pressure. The CFD results are in excellent agreement with the experimental data. The absolute relative error is less than 12 % for predicting the ultimate oil recovery factors (RFs) in water flooding (WF) and gas injection (GI) cycles. Including the three-phase hysteresis significantly increases the accuracy of the WAG process simulation while excluding hysteresis underestimates the instantaneous RFs at each cycle (especially GI cycles) and the ultimate RF by 4%. We also analyze the fracture pattern and configuration; adding fractures to the system increases the system effective permeability, leading to more contact between the injecting fluid and trapped oil, and consequently higher oil recovery. Connecting a vertical fracture to the horizontal fracture enhances the recovery through strong connections between vertical and horizontal blocks. An increase in the fracture aperture from 0.5 to 3 mm increases the RF from 50 % to 59%. The fracture inclination angle from 30o to 90o increased the ultimate RF by only 2 %. Including the gravity forces in vertical model orientation results in overall improvement in RF through engaging both matrix and fracture media in all cycles. As the permeability contrast between the matrix and fracture media decreases, the flow communication between the two regions increases which improves the recovery performance of the WAG process. Our simulation results can help to further understand the effect of various parameters and operational conditions on WAG injection performance in fractured reservoirs. Post-print / Final draft

Inaccurate description of uncertainty in the error models can cause biases in parameter estimation. When the parameters of the deterministic model and the error model are inferred jointly from the observations, the posterior converges to regions that reflect the processes in both high and low flows. If the nature of errors in low and high flows is different to the extent that the same error description cannot be used for both, biases in inference are introduced. In such cases, the parameter posterior will adjust to the region of the hydrograph with longer proportionate presence in the calibration time series. In this paper we demonstrate that the autoregressive order 1 (AR1) description of errors can lead to sub-optimally performing predictive models if the calibration period has substantial sections of inadequately modelled flows. Inference is performed within the Bayesian framework. We show this for a synthetic example as well as a case study. We also see that the predictive uncertainty bands that we get using the AR1 description can be overconfident and also admit negative values. To mitigate this, we analyze an alternative to additive error models. We use a distribution with a non-negative support, gamma in this study, reflecting the uncertainty in the system response at every time step. The gamma distribution is conditioned on the deterministic model output, which determines its mode and standard deviation. We capture autocorrelation in time using copulas. Given that copulas can capture dependence between different marginals, we use different specifications of the marginal distribution for high and low flows. The results show that 1) biases in parameter estimation can be reduced if a representative error description is attained using the flexibility of a copula-based likelihood. 2) The non-negative support allows to make more realistic uncertainty intervals for low flows. 3) However, the autocorrelation parameter in copulas severely interacts with the model and heteroscedasticity parameters. 4) While the formulation, in principle, should be of added value for parameter inference, in case of less informative priors, the flexibility of this description can produce non-robust inference.

Stormwater detentions basins are designed to capture stormwater to reduce and delay peak flows and to improve water quality. A novel technology proposed to improve basin performance is real-time, active control of the basin outflow, in so-called “smart” stormwater systems. Existing studies demonstrate the performance of active controls that respond in real-time to basin water level, detention time, and rainfall forecast for one or a small number of rainfall events. We hypothesize that the performance of these active controls can be improved by incorporating real-time water quality data into the control algorithm. In addition, we hypothesize that active control performance depends on hydrologic variability, specifically the frequency and intensity of runoff inputs. In this paper, we test these hypotheses using a numerical modeling framework for systems-level reliability analysis of active and passive stormwater basin outflow control using a Monte Carlo method. The analysis is performed using the urban hydrology model EPA-SWMM driven by stochastic rainfall time-series generated from the Modified Bartlett-Lewis Rectangular Pulses Model. Water quality-informed real-time active control algorithms are developed, tested, and shown to display an improvement over traditional, passive (no control) systems and other storage-based active controls for water and pollutant capture. Seasonal and duration curve analysis showed that water level- and water quality- informed control performance varied for different storm return periods and this variability could partly be attributed to the fraction of time the valve is closed. In addition, control performance was sensitive to rainfall variability, generally decreasing as storms become less frequent and more intense. Therefore, control system performance may depend on seasonal and longer time-scale variability in climate and rainfall-runoff processes. We anticipate this study to be a starting point to incorporate theories of reliability to assess detention basin and conveyance network performance under more complex real-time control algorithms and failure modes.

International audience; With an ever-growing population of around 10 million inhabitants (officially 7.9 in 2013), Ho Chi Minh City (HCMC) is set to become one of the largest cities in South East Asia and already occupies a major economic role in the area. To accommodate the increasing population, the megacity now stretches out in an urban continuum covering more than 800 square kilometers and is currently growing at a rate of 3.2% per year. If the neighboring provinces around HCMC are included, the total population reaches nearly 18 million people.This paper attempts to describe the interplay between HCMC and flood-related risks and offer some guidelines to deal with inundations. The potential risks of flooding by rain, tsunami and/or dam failure upstream of the city are evaluated and contextualized within the perspective of climate and human-induced environmental changes. The region is highly vulnerable to the combined effects of subsidence and rising sea levels and has already led to serious flooding that may extend spatially before the end of the century. We propose possible preventative solutions to urban flooding using a multi-pronged approach to issues regarding urban development and suggest a redevelopment strategy for major infrastructure projects.

International audience; This paper emphasizes the importance of integrating outlet discharge and observed internal variables in the evaluation of distributed hydrological models outputs. It proposes a general methodology for a diagnostic evaluation of a complex distributed hydrological model, based on discharge data at the outlet and additional distributed information such as water level and surface soil moisture data. The proposed methodology is illustrated using the PUMMA model in the Mercier sub-catchment (6.6 km 2 ). Model parameters are specified according to field data and a previous study performed in a neighbouring catchment (Jankowfsky et al., 2014), without calibration. The distributed water level and soil moisture network of sensors were useful in the model evaluation process. Thus, model parameters are specified either using in situ information or results from previous studies. A stepwise approach is used for model evaluation. It includes standard water balance assessment as well as comparison of observed and simulated outlet discharge, whether on annual or event timescales. Soil moisture sensors are used to assess the ability of the model to simulate seasonal water storage dynamics based on a normalized index. The water level sensors network is used on two timescales: on a seasonal timescale, sensors network is used to assess the model's ability to simulate intermittency; whereas on event timescales, sensors network is used in determining the model's ability to reproduce observed reaction as well as response times. Event timescales do also focus on the correlation between hydrological response and either rainfall event or antecedent soil moisture variables. Results show that the non-calibrated model is quite effective at capturing water flow and soil water-storage dynamics, but it fails to reproduce observed runoff volume during events. There is strong indication of a deficiency in the characterization of catchment storage and upstream flowpath description. The soil water content and a network of water level sensors provide interesting information about soil moisture and river flow dynamics. They however fail to provide quantitative information about catchment storage. This study opens interesting perspectives for the evaluation of distributed hydrological models using hydrological signatures. Furthermore, it highlights the requirement of quantitative as well as qualitative signatures for improving such models.

Distributed physically based models (DPMs) have become the standard tool for urban drainage modelling. However, high computational demands limit these in applications where fast or multiple simulations are needed. This paper presents simple fit-for-purpose cheaper-to-run surrogate models (SMs) for pipe network simulations which are validated against a DPM. The SMs are set up by lumping the DPM network into compartments in which the volume of water is governed by mass balances. Outgoing discharges to downstream compartment(s) and surcharging are computed from unambiguous volume-discharge curves. The SMs are applied on a 45 km2 catchment, Elster Creek in Melbourne, Australia. The number of simulated states and simulation times are reduced by approximately 3 and 6 orders of magnitude, respectively. Different SM complexities are examined. The simplest SM using steady state training data performed well with NSE of 0.98 for volume in the most upstream compartment. When emulating the aggregated surcharge from that compartment, the SM captured all surcharge events correctly. NSE improved from 0.35 to 0.84 when subdividing the compartment into 17 subcompartments. Uncertainty of SM parameters was examined using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. Two different sampling methods were applied. Limits of acceptability for real-time control, warning and planning, resulted in many accepted models upstream and few to none in downstream backwater-prone areas. All applications showed SM uncertainty bands within expected uncertainty bands for DPM, supporting the use of a simpler conceptual model in fit-for-purpose modelling in urban water systems when computational demands of DPMs are prohibitive.

Water Sensitive Urban Design (WSUD) stormwater systems, also known as Low Impact Development (LID) systems or Nature Based Solutions (NBS), are currently implemented based on the underlying assumption of statistical stationarity of rainfall, which threatens to become outdated under climatic uncertainty. This paper applies a new downscaling method to examine the implications of climate change on future rainfall and evaluate the reliability of WSUD stormwater infrastructure in pollution reduction, flow frequency mitigation and reliability as an alternative water supply. A variety of future atmospheric scenarios are considered as part of this comprehensive assessment by analysing an ensemble of eight different downscaled General Circulation Models (GCMs). High resolution catchment-scale rainfall projections for Melbourne, Australia were generated using a scheme called High-resolution Downscaling of Rainfall Using STEPS (HiDRUS) at a fine 1 km and 6-min scale for more precise analysis with uncertainty estimates. Statistical analyses show that, in general, the climate models predict a drier future with fewer rainfall events and longer dry periods when comparing the simulated near future (2040–2049) periods against the base-line period (1995–2004). The difference simulated between historical and future rainfall projections show minimum difference of WSUD performance in pollution removal and flow frequency reduction, with slightly lower harvesting reliability (

Hydrologic models are important for effective water resources management. They vary in complexity from parsimonious, spatially lumped, to physically-based, fully distributed models, which are generally expected to outperform the former. Wide applications of complex models are limited due to high data and computational demands. Therefore, a new approach based on well-balanced model complexity is needed to obtain reasonable simulation results with low data requirements. This paper presents a novel 3DNet-Catch hydrologic model, developed to represent key processes in sloped catchments under a temperate climate with modest data requirements. 3DNet-Catch includes runoff simulations within computational units by employing the interception, snow and soil routines, as well as runoff and channel routing. The soil routine, which is the key model feature, combines the SCS-CN method, an analytically integrated nonlinear outflow equation and the Brooks-Corey relation for unsaturated conductivity in an innovative manner. To advance runoff routing in 3DNet-Catch, an approach for analytical integration of the linear and nonlinear outflow equations is implemented. Most model parameters are physically meaningful, thus facilitating model calibration. The model structure can be adjusted according to soil and groundwater flow data, and it can include hydraulic structures, thereby providing adaptability to local conditions. A comprehensive hydrologic evaluation framework is established and conducted to examine whether 3DNet-Catch is adequately parameterised and can accurately reproduce catchment hydrologic response. The model parameterisation is evaluated by sensitivity, identifiability and correlation analyses. Model efficiency is quantified in terms of performance measures, hydrologic signatures and plausibility of the simulated hydrological processes. The results show high sensitivity of the hydrologic variables and performance measures to the model parameters, particularly to those of the soil routine. The parameters are uncorrelated and generally well identifiable. The model performs equally well in the calibration and evaluation periods. High efficiency in the hydrological signatures related to the soil routine indicates its robustness. The results, therefore, suggest that 3DNet-Catch is a comprehensively parameterised, versatile hydrologic model. It realistically reproduces observed hydrographs with modest data requirements, thus being appropriate for both engineering applications and investigative catchment dynamics studies. This is the peer-reviewed version of the article: Todorović, A., Stanić, M., Vasilić, Ž., Plavšić, J., 2019. The 3DNet-Catch hydrologic model: Development and evaluation. Journal of Hydrology 568, 26–45. [https://doi.org/10.1016/j.jhydrol.2018.10.040]

Recent riverbed sand mining activities have modified estuarine morphology and sedimentation patterns in many Southeast Asian deltas. The Soai Rap Estuary along the Dong Nai River (one of the largest rivers in Southern Vietnam) is one of the most intensively mined areas in the region, where large-scale sand mining activities have started since the 1990′s. In this paper, we used hydrodynamic modelling (TELEMAC-2D) to investigate the estuarine morphological changes and sediment dynamics related to the intensive riverbed mining in the Soai Rap Estuary. After the hydraulic calibration and validation of the model, we simulate four scenarios: two with dredging, one with sand excavation, and a baseline condition. Our results show that dredging substantially changed the hydraulic regimes, morphological and sediment dynamics of the estuary. Compared to the baseline, dredging substantially influences flow velocity and tidal amplitude. These activities reduce the amount of sediment accumulating upstream by 18% to 36%, while increasing sediment deposition in the Soai Rap Estuary by 6% to 13%. Furthermore, sediment accumulation in the Ganh Rai Bay area decrease by 5% to 10% due to increased sediment transport from the sea to the estuary. Our modelled results also show that the mining pits (pockmarks) created by sand extractions efficiently trap sediment, causing discontinuities in the longitudinal transport of sediment and resulting morphological patterns. We conclude that the morphology and sediment transport regime of the Soai Rap estuary has been significantly altered by the river sand dredging. As such, we recommend that the local government put in place measures to ensure that sand extraction is carried out sustainably in the future, to minimise further alterations to the natural sedimentation patterns and geomorphology of this estuary. Ministry of Education (MOE) Nanyang Technological University This study is funded by University of Natural Resources and Envi-ronment, Ho Chi Minh City, Vietnam under the grant number CS.2022.11. It is also funded by the Nanyang Technological University (#SUG-NAP EP3/19) and Ministry of Education of Singapore (#Tier1 RT06/19, #Tier1 2021-T1-001-056 and #Tier2MOE-T2EP402A20-0001).