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The Unazuki Reservoir is located on the Kurobe River, which is influenced by a catchment with one of the highest sediment yields in Japan. Due to a sufficiently available discharge during flood events, annual sediment flushing with full water-level drawdown (i.e., free-flow sediment flushing) is conducted to preserve the effective storage capacity of the reservoir. Nevertheless, the upstream half of the reservoir (i.e., study segment) suffers from the excessive deposition of coarser sediments. Remobilization of these coarser materials and their transportation further downstream of the reservoir is a priority of reservoir owners for sustainable reservoir functions, such as flood-risk management and hydroelectric energy generation. In this paper, an already conducted sediment-flushing operation in the Unazuki Reservoir is simulated, and its effects on sediment scouring from the study segment of the reservoir together with changes in bed morphodynamics are presented. A fully 3D numerical model using the finite volume approach in combination with a wetting/drying algorithm was utilized to reproduce the hydrodynamics and bed changes using the available onsite data. Afterwards, the effects of discharge adjustment on the morphological bed changes and flushing efficiency were analysed in the study segment using an additional single-discharge pulse supplied from upstream reservoirs. Simulation results showed that an approximately 75% increase in the average discharge during the free-flow stage changed the dominant morphological process from deposition into an erosive mode in the study segment. If the increase in discharge reaches up to 100%, the flushed volume of sediments from the target segment can increase 2.9 times compared with the initiation of the erosive mode., Ministry of Education, Culture, Sports, Science, and Technology of Japan (MEXT)

The radius of maximum wind (Rmax) in a tropical cyclone governs the footprint of hazards, including damaging wind, surge, and rainfall. However, Rmax is an inconstant quantity that is difficult to observe directly and is poorly resolved in reanalyses and climate models. In contrast, outer wind radii are much less sensitive to such issues. Here we present a simple empirical model for predicting Rmax from the radius of 34-kt (1 kt ≈ 0.51 m s−1) wind (R17.5 ms). The model only requires as input quantities that are routinely estimated operationally: maximum wind speed, R17.5 ms, and latitude. The form of the empirical model takes advantage of our physical understanding of tropical cyclone radial structure and is trained on the Extended Best Track database from the North Atlantic 2004–20. Results are similar for the TC-OBS database. The physics reduces the relationship between the two radii to a dependence on two physical parameters, while the observational data enables an optimal estimate of the quantitative dependence on those parameters. The model performs substantially better than existing operational methods for estimating Rmax. The model reproduces the observed statistical increase in Rmax with latitude and demonstrates that this increase is driven by the increase in R17.5 ms with latitude. Overall, the model offers a simple and fast first-order prediction of Rmax that can be used operationally and in risk models. Significance Statement If we can better predict the area of strong winds in a tropical cyclone, we can better prepare for its potential impacts. This work develops a simple model to predict the radius where the strongest winds in a tropical cyclone are located. The model is simple and fast and more accurate than existing models, and it also helps us to understand what causes this radius to vary in time, from storm to storm, and at different latitudes. It can be used in both operational forecasting and models of tropical cyclone hazard risk.

We investigate the effect of variable marine biogeochemical light absorption on Indian Ocean sea surface temperature (SST) and how this affects the South Asian climate. In twin experiments with a regional Earth system model, we found that the average SST is lower over most of the domain when variable marine biogeochemical light absorption is taken into account, compared to the reference experiment with a constant light attenuation coefficient equal to 0.06 m−1. The most significant deviations (more than 1 ∘C) in SST are observed in the monsoon season. A considerable cooling of subsurface layers occurs, and the thermocline shifts upward in the experiment with the activated biogeochemical impact. Also, the phytoplankton primary production becomes higher, especially during periods of winter and summer phytoplankton blooms. The effect of altered SST variability on climate was investigated by coupling the ocean models to a regional atmosphere model. We find the largest effects on the amount of precipitation, particularly during the monsoon season. In the Arabian Sea, the reduction of the transport of humidity across the Equator leads to a reduction of the large-scale precipitation in the eastern part of the basin, reinforcing the reduction of the convective precipitation. In the Bay of Bengal, it increases the large-scale precipitation, countering convective precipitation decline. Thus, the key impacts of including the full biogeochemical coupling with corresponding light attenuation, which in turn depends on variable chlorophyll a concentration, include the enhanced phytoplankton primary production, a shallower thermocline, and decreased SST and water temperature in subsurface layers, with cascading effects upon the model ocean physics which further translates into altered atmosphere dynamics.

International audience

The stability of soil organic carbon (SOC), as it relates to resistance to decomposition, is important for greenhouse gas emission and climate change. However, the SOC stabilization and its related influencing factors subjected to water erosion remain uncertain. The objective of the current study was to determine the SOC stability under long-term water erosion and to investigate the link between SOC stability and edaphic factors. Soil samples from eroded, depositional, and control sites in a closed watershed in subtropical China were collected. The SOC concentration, carbon functional groups, soil physicochemical properties, and thermal stability of SOC were determined. The study results showed that the primary component of the SOC functional groups was O-alkyl carbon (reached 40%), and its proportion has no significant difference among different sites. The TG-T50 (the temperature at which 50% of the soil organic matter is lost) values indicated that the SOC thermal stability in the eroded topsoil was higher than that of the deposited topsoil. The carbon functional groups were lack of relation with SOC thermal stability (p > 0.05). However, the TG-T50 was significantly positively correlated with the cation exchange capacity and silt, but remarkably negatively correlated with SOC, dissolved organic carbon, total nitrogen, sand, clay, pH, aluminum, specific surface area, and iron oxides. These results indicated that the edaphic factors, which were strongly affected by micro-environment, are the main factors affecting thermal stability of organic carbon. The SOC stabilization under the effects of long-term water erosion should be addressed from the perspective of the ecosystem.

Land use and land cover (LULC) changes strongly affect local hydrology and sediment yields. The current study focused on a basin in the Brazilian Amazon and had the following three objectives: (1) to perform an effective diagnosis of flow and sediment yield, (2) to evaluate the impacts of LULC changes over the last 40 years on the hydro-sedimentological variables, and (3) to investigate the impacts of the possible trends or breaking points in the flow, surface runoff, and sediment yield series. The Soil and Water Assessment Tool (SWAT) model validation showed that the simulated results were consistent with the data measured in the dynamic reproduction of flow seasonality. Furthermore, changes in LULC altered surface runoff, sediment yield, and flow according to the Mann-Kendall and Pettitt non-parametric tests. It was also observed that the sub-basins in which pastureland is predominant are more susceptible to increased surface runoff and sediment yield. According to trend and homogeneity tests, these sub-basins had break points in the time series of these variables. On the other hand, in the sub-basins whose land cover is predominantly forest, the time series is homogeneous and trendless. The current study highlighted the impacts that 40 years of LULC changes in an Amazonian basin had on hydro-sedimentological variables, which, in turn, can play an important role in changing the hydrological cycle, consequently these changes can also impact diverse human activities in the region, such as agribusiness, livestock, energy production, food security, and public water supply. Thus, it is concluded that the SWAT model is a good estimator of hydro-sedimentological processes in Amazonian basins and can be used by decision makers in the management of water and environmental resources.

Quantifying incipient sediment motion in vegetated open channel flow is pivotal for estimating bed load transport and the aquatic ecological environment in rivers. A new formula is developed to predict the critical flow velocity for incipient sediment motion in the presence of emergent vegetation, by incorporating the influence of vegetation drag that characterizes the effects of mean flow and turbulence on sediment movement. The proposed formula is shown to agree with existing experimental data. Moreover, the proposed formula is extended to scenarios with submerged vegetation, suggesting that the vegetation drag may be the inherent impact factor for incipient sediment motion in vegetated open channel flow.

This study performed a bridge pier collar comparison for the purpose of reducing scour, while introducing a new collar design. The new collar, referred to as Collar Prototype Number 3, was designed based on an equilibrium scour hole and provides a method of controlling the horseshoe vortex. Numerical modelling was utilized to show the flow field and bed shear stress as a result of using Collar Prototype Number 3. A prototype model of Collar Prototype Number 3 and a flat plate collar were constructed for the purpose of comparing both experimentally under different flow conditions. Collar Prototype Number 3 proved to be an effective device as it reduced scour in terms of the maximum depth downstream of the pier and overall volume, in some instances, by up to 69.7% and 75.7%, respectively. Furthermore, Collar Prototype Number 3 outperformed the flat plate collar, especially because, unlike the flat plate collar, Collar Prototype Number 3 did not experience undermining.

The Regional Ocean Modeling System (ROMS), including an ice shelf component, has been applied on a circum-Antarctic domain to derive estimates of ice shelf basal melting. Significant improvements made compared to previous models of this scale are the inclusion of tides and a horizontal spatial resolution of 2 km, which is sufficient to resolve on-shelf heat transport by bathymetric troughs and eddy-scale circulation. We run the model with ocean–atmosphere–sea ice conditions from the year 2007 to represent nominal present-day climate. We force the ocean surface with buoyancy fluxes derived from sea ice concentration observations and wind stress from ERA-Interim atmospheric reanalysis. Boundary conditions are derived from the ECCO2 ocean state estimate; tides are incorporated as sea surface height and barotropic currents at the open boundary. We evaluate model results using satellite-derived estimates of ice shelf melting and established compilations of ocean hydrography. The Whole Antarctic Ocean Model (WAOM v1.0) qualitatively captures the broad scale difference between warm and cold regimes as well as many of the known characteristics of regional ice–ocean interaction. We identify a cold bias for some warm-water ice shelves and a lack of high-salinity shelf water (HSSW) formation. We conclude that further calibration and development of our approach are justified. At its current state, the model is ideal for addressing specific, process-oriented questions, e.g. related to tide-driven ice shelf melting at large scales.

Air pollution is a global challenge, and especially urban areas are particularly affected by acute episodes. Traditional approaches used to mitigate air pollution primarily consider the technical aspects of the problem but not the role of citizen behaviour and day-to-day practices. ClairCity, a Horizon 2020 funded project, created an impact assessment framework considering the role of citizen behaviour to create future scenarios, aiming to improve urban environments and the wellbeing and health of its inhabitants. This framework was applied to six pilot cases: Bristol, Amsterdam, Ljubljana, Sosnowiec, Aveiro Region and Liguria Region, considering three-time horizons: 2025, 2035 and 2050. The scenarios approach includes the Business As Usual (BAU) scenario and a Final Unified Policy Scenarios (FUPS) established by citizens, decision-makers, local planners and stakeholders based on data collected through a citizen and stakeholder co-creation process. Therefore, this paper aims to present the ClairCity outcomes, analysing the quantified impacts of selected measures in terms of emissions, air quality, population exposure, and health. Each case study has established a particular set of measures with different levels of ambition, therefore different levels of success were achieved towards the control and mitigation of their specific air pollution problems. The transport sector was the most addressed by the measures showing substantial improvements for NO2, already with the BAU scenarios, and overall, even better results when applying the citizen-led FUPS scenarios. In some cases, due to a lack of ambition for the residential and commercial sector, the results were not sufficient to fulfil the WHO guidelines. Overall, it was found in all cities that the co-created scenarios would lead to environmental improvements in terms of air quality and citizens’ health compared to the baseline year of 2015. However, in some cases, the health impacts were lower than air quality due to the implementation of the measures not affecting the most densely populated areas. Benefits from the FUPS comparing to the BAU scenario were found to be highest in Amsterdam and Bristol, with further NO2 and PM10 emission reductions around 10%–16% by 2025 and 19%–28% by 2050, compared to BAU.

The aim of multispectral (MS) and panchromatic (PAN) image fusion is to obtain an MS image that has high resolution in both spectral and spatial domains. During the fusion process, there are two important issues, i.e., spectral information preservation and spatial information enhancement. In this article, we propose a dual-collaborative fusion model that considers not only the spectral correlation collaboration but also the spatial-spectral collaboration. First, the features of PAN and MS images are extracted by a shared feature embedding network. Then, in order to enhance the spatial details, the PAN features are decomposed into four subbands, and the collaborative relationships among subbands are fully explored to refine the features. After the refinement of the subbands, the high-frequency components are directly taken as the inputs of the reconstruction network, while the low-frequency components are transformed by the guidance generation network to accomplish the spatial-spectral collaboration and also make preparations for the spectral adjustment. To explore the spectral correlation collaboration, a novel graph convolutional network is designed for the modulation of intraspectral relationships. Finally, the adjusted MS features are combined with the high-frequency components of PAN features to reconstruct the high-resolution MS image. Experimental results show that the proposed method outperforms traditional state-of-the-art pan-sharpening methods as well as the available deep learning-based ones.

A new model is presented for multisite statistical downscaling of temperature and precipitation using convolutional conditional neural processes (convCNPs). ConvCNPs are a recently developed class of models that allow deep learning techniques to be applied to off-the-grid spatio-temporal data. This model has a substantial advantage over existing downscaling methods in that the trained model can be used to generate multisite predictions at an arbitrary set of locations, regardless of the availability of training data. The convCNP model is shown to outperform an ensemble of existing downscaling techniques over Europe for both temperature and precipitation taken from the VALUE intercomparison project. The model also outperforms an approach that uses Gaussian processes to interpolate single-site downscaling models at unseen locations. Importantly, substantial improvement is seen in the representation of extreme precipitation events. These results indicate that the convCNP is a robust downscaling model suitable for generating localised projections for use in climate impact studies, and motivates further research into applications of deep learning techniques in statistical downscaling., 26 pages, 12 figures

River flood season segmentation is a significant measure for flood prevention. This study aims to carry out theoretical analysis on flood season segmentation methods and put forward a framework for proper flood season segmentation through comparison between different segmentation methods. The studied framework consists of a Fisher optimal partition method for determining the optimum numbers of the sub-seasons, an ensemble approach for segmenting a defined flood season, and a nonparametric bootstrap combined with a fuzzy optimum selection method (NPB-FOS) for testing the rationality of the flood season staging schemes. The present research findings show that different methods could result in different staging schemes. It is proved through rational analysis that the staging scheme obtained by probability change point (PCP) is superior to others. The flood season of the downstream reach of the Yellow River can be segmented into three sub-seasons, i.e. early flood season (01 June–20 July), main flood season (21 July–28 September), and late flood season (29 September–08 November). The segmentation results of the flood season should play an active role in flood prevention. HIGHLIGHTS The conjunctive use of Fisher optimal partition, ensemble approach, nonparametric bootstrap, and fuzzy optimum selection method applied to flood season segmentation.; The rational methods segment a flood season into several sub-seasons.; An optimal framework for reasonable flood season segmentation was proposed.; A case study in the Yellow River was carried out and reasonable results were obtained.

Five mainland SEA countries (Cambodia, Laos, Myanmar, Vietnam, and Thailand) are threatened by climate change. Here, the latest 18 Coupled Model Intercomparison Project Phase 6 (CMIP6) is employed to examine future climate change in this region under two SSP-RCP (shared socioeconomic pathway-representative concentration pathway) scenarios (SSP2-4.5 and SSP5-8.5). The bias-corrected multi-model ensemble (MME) projects a warming (wetting) over Cambodia, Laos, Myanmar, Vietnam, and Thailand by 1.88–3.89, 2.04–4.22, 1.88–4.09, 2.03–4.25, and 1.90–3.96 °C (8.76–20.47, 12.69–21.10, 9.54–21.10, 13.47–22.12, and 7.03–15.17%) in the 21st century with larger values found under SSP5-8.5 than SSP2-4.5. The MME model displays approximately triple the current rainfall during the boreal summer. Overall, there are robust increases in rainfall during the Southwest Monsoon (3.41–3.44, 8.44–9.53, and 10.89–17.59%) and the Northeast Monsoon (−2.58 to 0.78, −0.43 to 2.81, and 2.32 to 5.45%). The effectiveness of anticipated climate change mitigation and adaptation strategies under SSP2-4.5 results in slowing down the warming trends and decreasing precipitation trends after 2050. All these findings imply that member countries of mainland SEA need to prepare for appropriate adaptation measures in response to the changing climate. HIGHLIGHTS There is a robust increase in SWMR rainfall while the NEMR displays smaller increases.; The temperature changes among CLMVT countries do not show any significant differences. However, there are significant precipitation changes.

Comments from S. Joseph Munchak and Robert Meneghini of NASA Goddard Space Flight Center, Charles (Chip) Helms of Universities Space Research Association, Liang Liao of Morgan State University are highly appreciated. Discussions with Norm Wood of University of Wisconsin-Madison on PIP data processing was very helpful. Leo Pio D’Adderio of National Research Council of Italy provided Figure 1 of this study. Thanks to the National Weather Service in Marquette, Michigan for hosting and maintaining the suite of instruments used in this work and sharing meteorological data. Thanks to the National Aeronautics and Space Administration Goddard Space Flight Center Wallops Flight Facility and the Global Precipitation Measurement (GPM) program for providing the PIP, Pluvio, and Parsivel instruments used in this work. Acknowledgments extend to three anonymous reviewers for their constructive comments. This study is partially supported by the NASA award (80NCCS19M0139) under Patrick N. Gatlin of NASA Marshall Space Flight Center, Principal Investigator. The instrument deployment and data processing for the observations from the Marquette, Michigan snowfall suite are supported by NASA grant number 80NSSC18K0701 and NOAA grant number NA15NES4320001. Claire Pettersen’s efforts on this work are supported by NASA grant number 80NSSC19K0712 and Mark Kulie’s efforts are supported by NASA PMM grant 80NSSC20K0982. Annakaisa von Lerber is funded by the Academy of Finland postdoctoral scholarship (333901). The scientific results and conclusions, as well as any views or opinions expressed herein, are those of the authors and do not necessarily reflect those of NOAA or the Department of Commerce.

In high altitude, scarcely gauged basins, climate change impact assessment on river discharge is important for sustainable management of water resources. These basins are sources for irrigation and hydropower generation in the region. Expected changes in precipitation and temperature can affect the basin's hydrological regime which will have consequential impacts on the dependent sectors. For quantifying the impacts of major climatic variables on hydrological processes, this paper examined bias-corrected GCM outputs coupled with a hydrological model – HBV for Chenab basin. Trend analysis shows that precipitation would decrease after the short-term period and temperature is expected to increase throughout the century. Simulated river discharge is expected to increase throughout the 21st century under both RCP 4.5 and RCP 8.5 scenarios. It is also observed that there would be a shift in seasonal discharge patterns with increased pre- and post-monsoon contributions. Increase in snow and ice melt contribution to the overall discharge is also expected and would range between 50 and 59% until 2100. This study concluded that expected increase in discharge volume coupled with shift in seasonal discharge pattern would impact the basin water management and thus it is important to consider the impact of climate change on the hydrological regimes of basins. HIGHLIGHTS Paper deals with the ungauged basin originating from the Himalayas and assesses shifts in seasonal discharge patterns which highlights increased pre- and post- monsoon contributions in annual discharge.; Output from the study is important for the data scarce Himalayan region and for better planning and management of water resources.

As a critical infrastructure of urban water systems, sewer networks suffer from serious corrosion and odor problems, which can be controlled by chemical dosing. It is a challenging task to optimize chemical distribution in such a hybrid system with continuous hydraulic flow, discrete pump operations, and dynamic constraints. In this article, we study real-time control of multiple pumps to achieve the desired chemical distribution in a sewer network. A novel hybrid optimization approach is developed, which involves an event-triggered scheme triggered by predicting proper pumping events at uncontrolled pumping stations, and an improved nature-inspired elephant herding optimization (iEHO) algorithm for scheduling pumping at controllable pumping stations. The proposed method is validated through simulation studies of a real-life sewer network using real measured data. Our strategy significantly improves chemical distribution with reduced costs, despite an astronomic searching space. The iEHO algorithm outperforms the genetic algorithm in terms of the quality of solutions and convergence efficiency.

Temporal and spatial changes of green water (GW) security due to climate and land-use/land-cover (LULC) changes can be used to make the best decisions for sustainable GW management. In this study, simultaneous effects of climate and LULC changes on water resources in Kashafrood Basin were evaluated using the Soil and Water Assessment Tool (SWAT). A land change modeler was set up to monitor LULC, assess changes and make predictions. The MIROC-ESM model derived from Coupled Model Intercomparison Project Phase 5 under two representative concentration pathway (RCP) emission scenarios RCP2.6 and RCP8.5 was applied to evaluate the effects of climate change. Two indices of GW-Scarcity and GW-Vulnerability, representing GW-Security, were quantified using the GW-Footprint concept in Kashafrood Basin. The results show that the annual average of blue water was predicted to increase by 142–350%, and GW storage and the annual averages of GW flow were predicted to decrease by 12–65 and 8–20%, respectively, depending on emission scenarios and time. The GW-Security estimates in the entire basin suggest a better condition in the future by indicating 24–45 and 16–52% decreases in GW-Scarcity and GW-Vulnerability, respectively, depending on emission scenarios and time. HIGHLIGHTS Land change modeler predicts a decline in agricultural area and a growth in urban and pasture areas.; Blue water rises by 142–350% under the effect of climate and land-use changes.; Green water (GW) storage and GW flow decrease by 12–65 and 8–20%, respectively.; The condition of the basin in terms of GW-Security would improve in the future.; GW-Scarcity and GW-Vulnerability escalate in southern and some western subbasins.

WOMBAT (the WOllongong Methodology for Bayesian Assimilation of Trace-gases) is a fully Bayesian hierarchical statistical framework for flux inversion of trace gases from flask, in situ, and remotely sensed data. WOMBAT extends the conventional Bayesian-synthesis framework through the consideration of a correlated error term, the capacity for online bias correction, and the provision of uncertainty quantification on all unknowns that appear in the Bayesian statistical model. We show, in an observing system simulation experiment (OSSE), that these extensions are crucial when the data are indeed biased and have errors that are spatio-temporally correlated. Using the GEOS-Chem atmospheric transport model, we show that WOMBAT is able to obtain posterior means and variances on non-fossil-fuel CO2 fluxes from Orbiting Carbon Observatory-2 (OCO-2) data that are comparable to those from the Model Intercomparison Project (MIP) reported in Crowell et al. (2019, Atmos. Chem. Phys., vol. 19). We also find that WOMBAT's predictions of out-of-sample retrievals obtained from the Total Column Carbon Observing Network are, for the most part, more accurate than those made by the MIP participants.

In ancient times it was believed that the eye radiated a cone of visual flux which mixed with visible objects in the world to create a sensation in the observer – like the sense of touch, but at a distance – this is the extromission theory. Today we consider that light from an illuminant falls on the scene, some of which is reflected into the eye of the observer to create a perception about that scene. The light that reaches the eye, or the camera, is a function of the illumination impinging on the scene and the material property known as reflectivity.

The decline in snowpack across the western United States is one of the most pressing threats posed by climate change to regional economies and livelihoods. Earth system models are important tools for exploring past and future snowpack variability, yet their coarse spatial resolutions distort local topography and bias spatial patterns of accumulation and ablation. Here, we explore pattern-based statistical downscaling for spatially-continuous interannual snowpack estimates. We find that a few leading patterns capture the majority of snowpack variability across the western US in observations, reanalyses, and free-running simulations. Pattern-based downscaling methods yield accurate, high resolution maps that correct mean and variance biases in domain-wide simulated snowpack. Methods that use large-scale patterns as both predictors and predictands perform better than those that do not and all are superior to an interpolation-based “delta change” approach. These findings suggest that pattern-based methods are appropriate for downscaling interannual snowpack variability and that using physically meaningful large-scale patterns is more important than the details of any particular downscaling method.

The goal of this research was to identify functional groups that determine rates of micropollutant (MP) biotransformations performed by wastewater microbial communities. To meet this goal, we performed a series of incubation experiments seeded with four independent wastewater microbial communities and spiked them with a mixture of 40 structurally diverse MPs. We collected samples over time and used high-resolution mass spectrometry to estimate biotransformation rate constants for each MP in each experiment and to propose structures of 46 biotransformation products. We then developed random forest models to classify the biotransformation rate constants based on the presence of specific functional groups or observed biotransformations. We extracted classification importance metrics from each random forest model and compared them across wastewater microbial communities. Our analysis revealed 30 functional groups that we define as either biotransformation promoters, biotransformation inhibitors, structural features that can be biotransformed based on uncharacterized features of the wastewater microbial community, or structural features that are not rate-determining. Our experimental data and analysis provide novel insights into MP biotransformations that can be used to more accurately predict MP biotransformations or to inform the design of new chemical products that may be more readily biodegradable during wastewater treatment.

While interactions between groundwater and lake-water influence water chemistry, water balance, aquatic organisms, biochemical cycles and contamination levels, they remain a poorly studied component of lake hydrology. Identifying the controls of groundwater and lake-water interactions at the landscape level and classifying lakes into categories based on their degree of interaction with the groundwater can provide insights into a lake's sensitivity and vulnerability to environmental stressors. Such information can also provide baseline conditions for comparison to future changes that are important for water management and conservation. To this end, water chemistry and water isotopic composition were investigated in a set of 50 boreal lakes located at different elevations in an esker system near Timmins, Ontario. Analyses focused on stable isotopic ratios of hydrogen and oxygen and specific conductance as indicators of the position of a lake with respect to the influence of groundwater. Both isotopic composition and specific conductance distinguished higher-elevation groundwater-recharge lakes from lower-elevation groundwater-discharge lakes. Groundwater-recharge lakes were high-elevation lakes characterized by enriched isotopic values and low values of specific conductance. In contrast, groundwater-discharge lakes were isotopically depleted and had higher values of specific conductance and occurred at lower elevations. An intermediate group of lakes was also defined (termed seepage lakes) and had intermediate isotopic and water-chemistry characteristics compared to recharge and discharge lakes. Differences in water geochemistry between field campaigns revealed that upland groundwater-recharge lakes showed evidence of evaporative drawdown, indicating sensitivity to short-term changes in climate, whereas the lower-elevation groundwater-discharge lakes showed little variation between seasonal samples and consequently would likely be affected only by hydroclimatological changes of greater duration and magnitude.

International audience; Small reservoirs have traditionally been used worldwide to store surface water, but are complex to manage. Accounting for a water resource scattered across thousands of water bodies remains challenging. Images acquired using unmanned aerial vehicles (UAV), which are already used in different ways in hydrology, could provide additional support. We evaluated the use of UAVs as an alternative way to derive bathymetric data from the topography of a small reservoir. Digital elevation models (DEMs, 58) were produced from UAV imagery and in-situ Differential Global Positioning System (DGPS) points using standard structure from motion (SfM) and interpolation methods. Image processing was able to produce DEMs with 10 times the vertical accuracy of DGPS-point interpolation methods for similar accuracy in determining the relationships between the water height, surface area, and reservoir volume. These results suggest that the SfM photogrammetry can be used to derive bathymetry data from UAV images.; Les petits barrages sont, dans le monde entier, traditionnellement utilisés pour stocker les eaux de surface. Leur gestion demeure complexe du fait de la difficulté à comptabiliser une ressource en eau dispersée parmi des milliers de petits plans d'eau. Une aide non négligeable pourrait provenir des images aériennes basse altitude acquises à l'aide de véhicules aériens sans pilote (UAV), par ailleurs déjà très utilisées en hydrologie. Nous proposons donc d’évaluer l'utilisation des drones comme moyen alternatif pour obtenir des données bathymétriques à partir de la topographie d'un petit barrage. Des modèles numériques de terrain (MNT, 58 au total) ont été produits à partir d'images acquises par un drone commercial et à partir de points mesurés au DGPS (Differential Global Positioning System) en utilisant des méthodes de Structure from Motion (SfM) et des méthodes d'interpolation standards. Le traitement d'images a permis de produire des MNT avec une précision verticale 10 fois supérieure à celle des méthodes d'interpolation des points DGPS pour une précision similaire dans la détermination des relations entre la hauteur d'eau, la surface et le volume du réservoir. Ces résultats montrent que la photogrammétrie SfM peut être utilisée avantageusement pour dériver des données bathymétriques à partir d'images de drones.

Over the past century, the Red River of the North has been the least stationary river in the continental United States. In Canada, historical and paleoenvironmental evidence indicates severe floods were common during the early 1800s, with the record ce 1826 flood having an estimated peak discharge 50% higher than the second-most severe flood ever observed. Unfortunately, the recorded history of flooding upstream in the United States does not begin until seven decades after this event. If 1826 was an equally exceptional flood on American reach of the river, then current flood-frequency curves for the river underestimate significantly the risks posed by future flooding. Alternatively, if the American stretch did not produce a major flood in 1826, then the recent spate of flooding that has occurred over the past two decades is exceptional within the context of the past 200 years. Communities in the Fargo-Moorhead metropolitan area are building a 58-km long, $2.75 billion (USD) diversion channel that would redirect floodwaters westward around the two cities before returning it to the main channel. Because this and other infrastructure in North Dakota and Minnesota is intended to provide protection against low-probability, high-magnitude floods, new paleoflood investigations in the region would help local, state, and federal policy-makers better understand the true flood threats posed by the Red River of the North.

Through water transfer, the hydrodynamic conditions of the river network can be improved, and the biochemical degradation of pollutants can be promoted, but at the same time, the endogenous release may be intensified. It is therefore possible to subdivide the response of nutrient content to water transfer into three components: (a) Direct Impact (DI) of dilution through water diversion, (b) Indirect Impact (II) by sediment release, and (c) Self Impact (SI) of nutrient degradation and attenuation of nutrients. By combining field investigation, laboratory experiment, and numerical simulation, the contribution weight of DI, II, and SI to the change of nutrient concentration was quantitatively analyzed. The results show that: (1) in the upper reaches of the river network, II plays a leading role in that the weight is more than 75%, and increasing the amount of water diversion increases the nutrient content; (2) SI plays a leading role in the tributary of the central part of the river network, the weight is more than 60%, and when the auxiliary pumping station is opened, the weight of II is less than 1%; (3) in the southeast of the river network, the nutrient release rate is sensitive to the change of hydrodynamics, and the weight of II is more than 90%. The results of this study can provide a reference for the formulation of a comprehensive hydrodynamic water quality management control scheme in the urban river network. HIGHLIGHTS Water transfer imposes direct and indirect impacts on nutrient concentration.; The response of nutrient to water transfer can be divided into three components.; The dilution weight of the downstream section is higher than that of the upstream section.; The control of endogenous pollution in Liangxi River and southeastern rivers is the key to improving the water quality of the river network.

International audience; The current study tries a new approach to simulating interactions between waves and seagrass through Smoothed Particle Hydrodynamics (SPH). In this model, the plants are defined as a solid that respects Hooke's law, and are assumed to have direct interaction with the fluid. Given the characteristics of the SPH method, especially in terms of computational time, the dimensions of the simulations were limited. The first goal of the current study was to optimize the approach to avoid reaching certain limits such as the rupture of the simulated plant. Plant movements under waves and/or currents have been studied by several authors in various in-situ, physical, and numerical experiments concerning various vegetation species, thus proving that plant movements can be successfully reproduced by SPH 2D/3D. Manning's roughness coefficient, n, was calculated to confirm that the results were in accordance with what had been measured in flume studies. Even though there is still room for improvement, it is shown that this method can be used to estimate Manning's coefficient for coastal vegetation (seagrass and saltmarsh vegetation) and to greatly improve the modeling and forecasting of coastal erosion and storm surge risks by including the effects of vegetation in integrated models.

Leakages cause real losses in water distribution systems (WDSs) from transmission lines, storage tanks, networks, and service connections. In particular, the amount of leakage increases in aging networks due to pressure effects, resulting in severe water losses. In this study, various artificial neural network (ANN) models are considered for determining monthly leakage rates and the variables that affect leakage. The monthly data, which are standardized by Z-score for the years 2016–2019, are used in these models by selecting four independent variables that affect the leakage rate regarding district metered areas and pressure metered areas in WDSs. The pressure effects are taken into consideration directly as input. The model accuracy is determined by comparing the predicted and measured data. Furthermore, the leakage rates are estimated by directly modelling the actual data with ANNs. Consequently, it is found that the model results after data standardization are somewhat better than the original nonstandardized data model results when 30 neurons are used in a single hidden layer. The reason for the higher accuracy in the standardized case compared with previous modelling studies is that the pressure effect is taken into consideration. The suggested models improve the model accuracy, and hence, the methodology of this paper supports an improved pressure management system and leakage reduction. HIGHLIGHTS The data standardized by Z-score.; Pressure effect has been directly taken into consideration for the first time.; The model accuracy has been developed by augmenting neurons numbers in a single hidden layer.; The highest accuracy has been achieved with the least input in models.; Pressure and age effect use directly in modelling.

Environmental flows are generally characterized by complex bed morphology and high current speeds. Such configurations favor the formation of vortex structures that strongly affect hydrody-namics and sediment transport. Large-Eddy Simulation (LES) enables investigation of the dynam-ics of the largest turbulence scales and, thanks to enhanced calculation resources, has now become applicable for simulating environmental flows. In this paper, a LES approach is developed in a CFD code (TELEMAC-3D), which was originally developed to simulate free surface flows using RANS methods. The present developments involve implementing subgrid models, boundary con-ditions and numerical schemes suitable for LES. The LES version of TELEMAC-3D was validated by comparing results on the model with experimental data for flow past a cylinder. Then, the model was applied to a test case representing flow over dunes. After validating the hydrodynamics, the model was used to assess the bottom shear stress, using both a RANS and a LES approach. Com-parison highlighted the potential contribution of LES to investigating the hydrodynamic forces acting on the bottom.

This study was designed to evaluate the ability of Artificial Intelligence (AI) methods including ANN, ANFIS, GRNN, SVM, GP, LR, and MLR to predict the relative energy dissipation (ΔE/Eu) for vertical drops equipped with a horizontal screen. For this study, 108 experiments were carried out to investigate energy dissipation. In the experiments, the discharge rate, drop height, and porosity of the screens were varied. Parameters yc/h, yd/yc, and p were input variables, and ΔE/Eu was the output variable. The efficiencies of the models were compared using the following metrics: correlation coefficient (CC), mean absolute error (MAE), root-mean-square error (RMSE), Normalized root mean square error (NRMSE) and Nash–Sutcliffe model efficiency (NSE). Results indicate that the performance of the ANFIS_gbellmf based model with a CC value of 0.9953, RMSE value of 0.0069, MAE value of 0.0042, NRMSE value as 0.0092 and NSE value as 0.9895 was superior to other applied models. Also, a linear regression yielded CC = 0.9933, RMSE = 0.0083, and MAE = 0.0067. This linear model outperformed multiple linear regression models. Results from a sensitivity study suggest that yc/h is the most effective parameter for predicting ΔE/Eu. HIGHLIGHTS In this study, 108 experiments were conducted to investigate the relative energy dissipation (ΔE/E0) for vertical drops equipped with a horizontal screen.; Intelligent models such as methods including ANN, ANFIS, GRNN, SVM, GP, LR, and MLR are applied to evaluate relative energy dissipation in vertical drops equipped with a horizontal screen.

Rainfall interception by vegetation plays an important role in the hydrological cycle. Next to rainfall characteristics, interception is influenced by tree size, crown structure and bark morphology. How tree traits determine interception across functionally and morphologically wide-ranging tree species is poorly understood. We determined interception ratios (interception:gross precipitation) and canopy storage capacities of seven temperate deciduous broadleaved (Acer pseudoplatanus L., Betula pendula Roth, Carpinus betulus L., Fagus sylvatica L., Populus tremula L., Sorbus aucuparia L.) and three evergreen coniferous tree species (Picea abies (L.) Karsten, Pinus sylvestris L., Pseudotsuga menziesii (Mirb.) Franco) as well as the influence of various tree traits on interception parameters. Interception was measured directly with natural rainfall by means of gravimetry on potted trees, 2–8 m tall, for seven consecutive months. Our results show that (a) the coniferous species had larger canopy storage capacities and larger interception ratios than the broadleaved species both during (summer) and outside the growing season (winter); (b) the absolute tree interception (in kg) of the broadleaved species was positively related to stem diameter at breast height, tree and crown height, maximum branch length, the total branch surface area and above ground dry weight; and (c) interception per unit crown projected area (in mm) of all species was positively related to branch length and branch surface area per unit crown projected area. These results can be used to estimate interception parameters from plant traits and to simulate interception losses of trees in a more reliable manner.

The magnitude and variation of the sediment loads transported by rivers have important implications for the functioning of river systems and changes in the sediment loads of rivers are driven by numerous factors. In this paper, the key drivers of changes in the sediment loads of the major rivers of China are identified by reviewing recent studies of changes in their sediment loads. Except for the Songhua River, which presents no clear tendency of change in runoff or sediment load, nearly all the major rivers of China are characterized by an apparent decline in annual sediment load. The total annual sediment load of major Chinese rivers transported to the coast decreased from 2.03 billion t/yr during the period 1955–1968 to 0.50 billion t/yr during the period 1997–2010. The primary drivers of changes in the sediment loads of the rivers are dam construction, implementation of soil and water conservation measures, catchment disturbance, agricultural practices, sand mining and climate change. Examples drawn from Chinese rivers are used to demonstrate the importance of these drivers. Construction of a large number of reservoirs in the Yangtze River basin represents the primary driver for the reduced sediment load of the Yangtze River. The implementation of soil and water conservation programmes is one of the key drivers for the sharp decline in the sediment load of the Yellow River. Catchment disturbance explains why the reduction of the sediment load of the Lancang-Mekong River at the Chiang Saen gauging station was much less than that at the Gajiu gauging station upstream. A reduction in sediment load resulting from the expansion of agricultural production may be the main driver for the reduced sediment load of the Huaihe River. The decrease in the sediment load of the Pearl River has been influenced by sand mining activities. Climate change is one of the key drivers responsible for the greatly reduced sediment load of the rivers in the Haihe River Basin.

International audience; In order to optimize ship navigation in the macrotidal Gironde Estuary, a recent project funded by the port of Bordeaux aims at better understand and forecast hydrodynamic and fine sediment transport within the estuary. In the framework of this project, a two-dimensional hydro-sedimentary model is built. The model includes hydrodynamic forcings, mixed-sediment transport, and consolidation processes. The harmonic analysis of the astronomical tides reveals a strong distortion of the tidal wave inducing the growth of overtide constituents and the non-significant effect of tide-surge interactions in annual-scale prediction. Depending on hydrological conditions, river discharge can considerably alter the model accuracy due to the migration of the turbidity maximum zone modifying the bottom roughness. Comparison with measurements shows the ability of the model to reproduce suspended-sediment concentrations in the central Estuary. Sensitivity of the model to sediment features has also been discussed in regard of suspended-sediment concentrations and fluid mud deposits. The model will be further coupled with ship squat predictions and a morphodynamic model.p { margin-bottom: 0.25 cm; line-height: 115%; }

Mesoscale convective systems (MCS) are known to develop under ideal conditions of temperature and humidity profiles and large-scale dynamic forcing. Recent work, however, has shown that summer MCS events can occur under weak synoptic forcing or even unfavorable large-scale environments. When baroclinic forcing is weak, convection may be triggered by anomalous conditions at the land surface. This work evaluates land surface conditions for summer MCS events forming in the U.S. Great Plains using an MCS database covering the contiguous United States east of the Rocky Mountains, in boreal summers 2004–16. After isolating MCS cases where synoptic-scale influences are not the main driver of development (i.e., only non-squall-line storms), antecedent soil moisture conditions are evaluated over two domain sizes (1.25° and 5° squares) centered on the mean position of the storm initiation. A negative correlation between soil moisture and MCS initiation is identified for the smaller domain, indicating that MCS events tend to be initiated over patches of anomalously dry soils of ∼100-km scale, but not significantly so. For the larger domain, soil moisture heterogeneity, with anomalously dry soils (anomalously wet soils) located southwest (northeast) of the initiation point, is associated with MCS initiation. This finding is similar to previous results in the Sahel and Europe that suggest that induced meso-β circulations from surface heterogeneity can drive convection initiation.

With the increasing effects of climate change and high costs of energy, many rural Alaska communities are working to implement local alternative energy solutions to improve energy security. Integrating renewable energy systems can reduce reliance on fossil fuels and subsequently improve food, energy, and water (FEW) security. In this study, wind energy modeling techniques using local airport meteorological data were convolved with community loads to determine the most cost-effective combinations of wind turbine technology and dispatchable loads for improving FEW security in a southwestern Alaska village. This approach is different from wind assessments that exclusively analyze wind resources. A 100 kW wind turbine was determined to be suitable for the community, resulting in a capacity factor of 16.7% and levelized cost of energy (LCOE) of $1.15/kWh, with diminishing returns for higher wind turbine capacity. The results from the dispatchability study indicated that dispatchable loads could handle the intermittency of the wind resource with up to 86% of their annual load met. More work is needed to understand the impact of integrating and scheduling dispatchable loads into the grid in practice.

Scientists have demonstrated the presence of microplastics (MPs) in tap and bottled water at various locations. On a global scale, there is still very limited information on MP pollution in drinking water. There are huge differences in reported MP concentration, but no clear conclusion can be drawn if MP content is higher in tap or bottled water. Up to date, it is not clear if these discrepancies arise from differences between the examined systems or from differences in quantification limits, the accuracy of the applied analytical techniques, or contamination during sampling, processing, and analysis. Furthermore, information on MP uptake and fate gained through animal and cell toxicity studies is very limited. To define a limit of tolerance for plastic pollution in drinking water, comparable data resulting from quality assured and controlled methods and more information on the potential uptake and fate of MPs in the human body are still needed.

The extent of reservoir sedimentation is an important index related to the functional operation of reservoirs. Therefore, it is vital to accurately conduct sedimentary assessment. In this paper, the analytic hierarchy process was used to determine subjective weights, gray correlation analysis and entropy weight method were used to determine objective weights. The combination weights obtained using optimized combination weighting method based on genetic algorithm were more suitable for the comprehensive analysis of the impact of reservoir sedimentation. This was then used to constructed a multi-level fuzzy comprehensive evaluation model based on improved cloud model. A reservoir was selected as the study object, and its sedimentation impact level was evaluated: the numerical characteristics of the stratus cloud of the comment on the impact of the reservoir sedimentation were (0.6372, 0.0664, 0.0795). The results showed that the reservoir sedimentation is considered as severe influence, and the sedimentation has become a major problem that needed to be solved urgently. The results of this paper could provide insight for reservoir research domestically and abroad. Furthermore, it could also enable managers to more accurately grasp the severity of reservoir sedimentation. HIGHLIGHTS The combination of the cloud model and genetic algorithm in computing was used to study and evaluate the influence of reservoir sedimentation. The calculation result was proved to be much accurate than that of the traditional method, and is more in line with the actual purpose of the project.; The multi-level fuzzy comprehensive evaluation model was constructed based on the improved cloud model for the sole purpose of analyzing the influence of sedimentation on reservoir function.; The improved combination weighting method based on genetic algorithm was used to solve the combination weight issues.

Typical continental, cold climate conditions were applied to four large, laboratory columns to simulate temperatures ranging from −20 to +20 °C over summer, winter, and spring runoff. The goal of this research was to assess the seasonal effectiveness of bioretention application in cold climate regions that are currently experiencing the impacts of climate change. 1.6 years’ worth of equivalent Edmonton precipitation volume was applied over a 10-month period to evaluate the water quality improvement through two soil types (i.e., loam and sandy loam) with and without amendments intended to enhance nutrient removal. During summer, excellent removal of total suspended solids (TSS), phosphate, and ammonium (i.e., ≥90% average concentration reduction) was observed in both the loam and sandy loam columns without the nutrient removal amendments. The columns containing the amendments also reduced TSS, ammonium, and phosphate, but not as effective as the non-amended columns for TSS and ammonium. During winter and spring runoff, if infiltration occurs, physical removal of TSS, phosphate, and ammonium was still achieved, only days after the complete freezing (and subsequent thawing) of bioretention media at −20 °C. After an initial maturation and leaching period, nitrate was well removed (≥65.2% average concentration reduction) via denitrification in the columns with the nutrient removal amendments and submerged zone. HIGHLIGHTS Four large bioretention columns with two soil media (loam and sandy loam) underwent simulated summer, winter, spring runoff, and another summer of stormwater applications.; All columns effectively reduced TSS, ammonium, and phosphate concentrations in the effluent during the summer.; If infiltration occurs during winter and spring runoff, physical removal of TSS, phosphate, and ammonium can still be achieved.

Drought is one of the natural disasters having the highest degrees in comparison to the other natural disasters in terms of rate, intensity, incident duration, region expansion, life losses, economic damages, and long-term effects. Hence, the prediction of drought as a meteorological phenomenon should be evaluated to determine the groundwater exploitation strategies in agriculture. The present study aims at investigating the impact of the drought duration and severity on soil moisture supplement for agricultural activities in Baghmalek plain, Khuzestan province, Iran. For this objective, a non-dimensional index of precipitation depth was defined for quantifying the drought characteristics. Furthermore, marginal distribution functions, correlation coefficients and joint functions were incorporated to a probabilistic decision-making framework to predict the variables in different return periods from 2-year to 100-year periods. Results showed that t copula was the best function for constructing the multivariate distribution in the study area based on the goodness-of-fit tests. Moreover, soil moisture content in the root zone achieved by the predetermined amounts of precipitation could be increased in the seasonal average. HIGHLIGHTS A new probabilistic framework was developed for sustainable water allocation.; Fuzzy particle swarm optimization was employed for generating the optimal solution.; A daily time-step model was simulated using mathematical formulation of crop growth process.; Developed framework increased the water use efficiency in the cropping pattern of Baghmalek as the study area.

The impact of giant sea salt aerosols released from breaking waves on rain formation in marine boundary layer clouds is studied using large-eddy simulations (LES). We perform simulations of marine cumuli and stratocumuli for various concentrations of cloud condensation nuclei (CCN) and giant CCN (GCCN). Cloud microphysics are modeled with a Lagrangian method that provides key improvements in comparison to previous LES of GCCN that used Eulerian bin microphysics. We find that GCCN significantly increase precipitation in stratocumuli. This effect is strongest for low and moderate CCN concentrations. GCCN are found to have a smaller impact on precipitation formation in cumuli. These conclusions are in agreement with field measurements. We develop a simple parameterization of the effect of GCCN on precipitation, accretion, and autoconversion rates in marine stratocumuli. Significance Statement Breaking sea waves release salt particles into the atmosphere. Cloud droplets formed on these salt particles can grow larger than droplets formed on other smaller particles. Therefore, sea salt particles can be important for rain formation over oceans. To investigate this effect, we performed idealized computer simulations of stratocumulus and cumulus clouds. Sea salt particles were modeled with an unprecedented precision thanks to the use of an emerging modeling method. In our simulations sea salt particles significantly enhance rain formation in stratocumuli, but not in cumuli. Our study has implications for climate models, because stratocumuli are important for Earth’s energy budget and for rain enhancement experiments.

Coastal lagoons are particularly vulnerable to climate change, in particular, Sea Level Rise (SLR) due to their shallowness. Lake Burullus provides a variety of socio-economic services as the second largest coastal lagoon in Egypt. Recently, it has experienced significant ecological deterioration. Thus, its ecosystem is fragile in the face of anthropogenic induced changes. The main objective of the current study is to investigate the climate change impacts on characteristics of Lake Burullus. A depth averaged hydro-ecological modeling system, MIKE21, was applied to develop an eco - hydrodynamic model for the lake. The developed model was calibrated and verified for two successive years: July 2011–June 2012 and July 2012–June 2013. The model simulations exhibited good agreement with the measurements during the calibration and verification processes. Six different Regional Climate Models (RCMs) were compared, using six different statistical metrics, to determine the most accurate one for the study area. The required meteorological input, including surface air temperature, precipitation, and evaporation were derived from the selected RCM. The meteorological input was extracted for two different years in the 21 st century considering one Representative Concentration Pathways (RCPs) scenario, based on the Intergovernmental Panel on Climate Change (IPCC) 5th Report. Regional SLR projections for the Mediterranean Sea for the selected RCP scenario and the two studied years were obtained. These future climate change estimates were used to modify the validated model of the lake. A sensitivity analysis was applied to assess effect of future climatic conditions and SLR, separately. The results revealed that the lake water depths will increase and it will be warmer and more saline. Significant spatial variability of the studied parameters under climate change forcing is expected. Consequently, climate change is going to restrict the lake's ability to preserve the present-day species. An urgent management plan involving adaptation works, should be implemented to reduce such potential species losses in Egyptian lagoons.

International audience; Two thirds of hydrological observation networks in developing countries are reported to be in poor or declining condition. At the same time innovation in sensor technologies and data processing are presenting opportunities for enhancing observation networks that are not being realized. The World Meteorological Organization’s Global Hydrometry Support Facility, or WMO HydroHub, was launched in 2016 to transform assistance to operational water monitoring agencies around the world. If successful, the initiative will increase the amount of hydrometric data available to researchers, catchment managers and water policy makers. To those unfamiliar with UN organizations, however, the nature of such initiatives, the reasoning behind the decisions taken to establish them and the mechanisms by which they try to deliver benefits for society, can be opaque. This paper adopts a novel dialogue-style format to explore the set-up of the WMO HydroHub and build awareness amongst those who ultimately may benefit from its approaches.

Nature-based solutions (NBS) support the provision of multiple benefits for the environment and society. First idealised in 2008, NBS are recommended by worldwide reports and guidelines as strategies to protect, sustainably manage and restore ecosystems. However, their operationalisation is still in the early stages, especially in developing countries, and only a few studies consider their full potential. This article contributes to this context by developing an integrated framework, with spatial and participatory tools, for analysing flood risk mitigation in Brazil. The approach enables a deep understanding of the societal challenges and vulnerabilities of the area (i.e., NEEDS) for subsequently planning the appropriate NBS (i.e., ACTIONS), with the participation of 255 stakeholders of Campina Grande municipality. Results show mappings of flood-prone areas, in which approximately 52% of the flooded areas will see an increase in the future. Hotspots (i.e., hazard, vulnerability, and exposure) are shown and discussed with four application cases. Finally, multiple benefits of seven NBS alternatives are analysed in 53 scenarios of application, in which the higher rates of reductions are found to combined alternatives. The discussion emphasizes the importance of spatially assessing the ‘needs’ and ‘multiple benefits’ of NBS, including reducing vulnerabilities and increment of resilience.

As part of the Springer Nature Content Sharing Initiative, you can publicly share full-text access to a view-only version of your paper by using thefollowing SharedIt link: https://rdcu.be/cCd8u; International audience; The study of groundwater resources using pumping test data is usually carried out with the Theis solution, which enables the hydraulic parameters of porous aquifers such as the transmissivity and storage coefficient, to be estimated from the water-level drawdown. However, the data fitting can fail and provide only an indication that the pumped aquifer has a complex structure. Here, a diagnostic plot on log-derivative drawdown is used to identify flow regimes and thus aquifer heterogeneities, leading to plausible conceptual models. Nevertheless, the diagnostic plot is insufficient and must be accompanied by further modelling because of the nonuniqueness of the drawdown log-derivative signal. The proposed approach is applied to an alluvial plain in France, known to be complex because the deposition processes change over time, resulting in channel belts limited by low-permeability deposits in the floodplain or three-dimensional (3D) interconnected structures. Six analytical models were used to simulate drawdown and its derivatives during a three-day transient pumping test. The diagnostic performed on the pumping well showed that four conceptual models, with highly contrasted hydrodynamic behaviours, may correspond to the diagnostic. The joint use of pumping-well and observation-well data allowed the only appropriate model to be identified—a dual-permeability model characterizing a multilayer aquifer. The conceptual model matched the geological observations in boreholes and corroborates the fluvial sequence stratigraphy of the alluvial plain. The pumping test used here is a tool to explore the 3D architecture of the fluvial reservoir at the scale of the depositional sequence in the floodplain.; El estudio de los recursos hídricos subterráneos a partir de los datos de los ensayos de bombeo suele realizarse con la solución de Theis, que permite estimar los parámetros hidráulicos de los acuíferos porosos, como la transmisividad y el coeficiente de almacenamiento, a partir del descenso del nivel del agua. Sin embargo, el ajuste de los datos puede no funcionar y proporcionar sólo una indicación de que el acuífero bombeado tiene una estructura compleja. En este caso, se utiliza un diagrama de diagnóstico de la depresión logarítmica derivada para identificar los regímenes de flujo y, por tanto, las heterogeneidades del acuífero, lo que conduce a modelos conceptuales plausibles. Sin embargo, el diagrama de diagnóstico es insuficiente y debe ir acompañado de una modelización adicional debido a la no unicidad de la señal log-derivada de la depresión. El enfoque propuesto se aplica a una llanura aluvial en Francia, conocida por su complejidad debido a que los procesos de deposición cambian con el tiempo, dando lugar a franjas de canales limitadas por depósitos de baja permeabilidad en la llanura de inundación o a estructuras tridimensionales (3D) interconectadas. Se utilizaron seis modelos analíticos para simular la depresión y sus derivados durante un ensayo de bombeo transitorio de tres días. El diagnóstico realizado en el pozo de bombeo mostró que pueden corresponder cuatro modelos conceptuales, con comportamientos hidrodinámicos muy contrastados. La utilización conjunta de los datos del pozo de bombeo y del pozo de observación permitió identificar el único modelo apropiado: un modelo de doble permeabilidad que caracteriza un acuífero multicapa. El modelo conceptual coincidió con las observaciones geológicas en pozos de sondeo y corrobora la estratigrafía de la secuencia fluvial de la llanura aluvial. El ensayo de bombeo utilizado aquí es una herramienta para explorar la arquitectura 3D del depósito fluvial a escala de la secuencia deposicional en la llanura aluvial.; L’étude des ressources en eau souterraine à partir de données d’essais de pompage est généralement réalisée avec la solution de Theis, qui permet d’estimer les paramètres hydrauliques des aquifères poreux, tels que la transmissivité et le coefficient d’emmagasinement, à partir du rabattement du niveau d’eau. Cependant, l’ajustement des données peut échouer et fournir seulement une indication relative à la complexité de la structure de l’aquifère sollicité par pompage. Ici, un tracé de diagnostic de la dérivé du rabattement selon une échelle logarithmique est utilisé pour identifier les régimes d’écoulement et donc les hétérogénéités de l’aquifère, conduisant à des modèles conceptuels plausibles. Néanmoins, le diagnostic de puits est insuffisant et doit être accompagné d’une modélisation plus poussée en raison de la non-unicité du signal de la dérivée du rabattement selon une échelle logarithmique. L’approche proposée est appliquée à une plaine alluviale en France, connue pour être complexe car les processus de dépôt ont évolué au cours du temps, donnant lieu à des zones de chenaux limitées par des dépôts peu perméables dans la plaine d’inondation ou à des structures tridimensionnelles (3D) interconnectées. Six modèles analytiques ont été utilisés pour simuler le rabattement et ses dérivés pendant un essai de pompage transitoire de trois jours. Le diagnostic réalisé sur le puits de pompage a montré que quatre modèles conceptuels, aux comportements hydrodynamiques très contrastés, peuvent correspondre au diagnostic. L’utilisation conjointe des données des puits de pompage et des puits d’observation a permis d’identifier le seul modèle approprié - un modèle à double perméabilité caractérisant un aquifère multicouche. Le modèle conceptuel correspond aux observations géologiques dans les forages et corrobore la stratigraphie séquentielle fluviale de la plaine alluviale. L’essai de pompage utilisé ici est un outil permettant d’explorer l’architecture 3D du réservoir fluvial à l’échelle de la séquence de dépôt dans la plaine d’inondation.; O estudo dos recursos hídricos subterrâneos utilizando dados de teste de vazão é comumente resolvido por meio da equação de Theis, o que permite que os parâmetros hidráulicos dos aquíferos porosos, como a transmissividade e o coeficiente de armazenamento, possam ser estimados a partir do rebaixamento do nível d’água. Porém, o ajuste dos dados pode falhar, indicando apenas que o aquífero bombeado apresenta uma estrutura complexa. Aqui, um gráfico de diagnóstico da derivada logarítmica do rebaixamento é usado para identificar o regime de fluxo e, portanto, a heterogeneidade do aquífero, levando a modelos conceituais plausíveis. Ainda assim, o gráfico de diagnóstico é insuficiente e deve ser acompanhado de mais modelos, devido ao sinal não único da derivada logarítmica do rebaixamento. A abordagem proposta foi utilizada em uma planície aluvial na França, conhecida por ser complexa, pois os processos de deposição mudam com o tempo, o que resulta em um cinturão de canais limitados por depósitos de baixa permeabilidade na planície de inundação ou por estruturas tridimensionais (3D) interconectadas. Seis modelos analíticos foram utilizados para simular o rebaixamento, e suas funções derivadas, durante um teste de bombeamento transiente de 3 dias. O diagnóstico simulado para o poço de bombeamento mostrou que quatro modelos conceituais, cada um com comportamento hidrodinâmico contrastante, podem corresponder ao diagnóstico. A junção dos dados do poço de bombeamento e dos dados de poço de observação permitiu a identificação do único modelo apropriado – um modelo de permeabilidade dual caracterizando um aquífero multicamadas. O modelo conceitual coincide com as observações da geologia dos poços e corrobora com a sequência estratigráfica fluvial da planície aluvial. O teste de bombeamento utilizado é uma ferramenta para explorar a arquitetura 3D do reservatório fluvial na escala da sequência deposicional da planície de inundação.; 利用抽水试验数据研究地下水资源通常采用 Theis 解, 它可以根据水位降深估算多孔介质含水层的水力参数, 如传导系数和蓄水系数。然而, 数据拟合可能会失败, 并且只能表明抽水含水层具有复杂的结构。在这里, 对数导数降深的诊断图用于识别流态, 从而识别含水层的异质性, 由此可形成合理的概念模型。然而, 由于降深对数导数信号的非唯一性, 仅用诊断图是不够的, 必须再建模分析。所提出的方法应用于法国众所周知复杂的冲积平原, 由于沉积过程随时间变化, 导致河岸带受到漫滩中低渗透性沉积物或三维 (3D) 互连结构的影响。在为期三天的非稳定抽水测试期间, 六个解析解模型用于模拟降深及其导数。抽水井上进行的诊断表明, 具有高度异质的水动力行为的四个概念模型可能与诊断相符。抽水井和观测井数据的联合使用可确定唯一合适的模型, 即表征多层含水层的双渗透模型。概念模型与钻孔中的地质观察相匹配, 并证实了冲积平原的河流相地层。此处使用的抽水试验是在漫滩沉积相尺度上探索冲积相储层 3D 结构的工具。

Lightweight sonar devices may be tethered to an unmanned aerial vehicle or drone and quickly deployed over water for real-time imaging in 2D and the on site creation of geolocated, interactive bathymetric maps without the need for a boat. We show how such data is useful in the preliminary stages of water searches, by providing geophysicists, hydrologists and divers with spatial depth information, the distribution of dive and equipment hazards such as entanglement objects (weed, discarded items) and sediment types. One bathymetry case study location is described in detail, with a further two summarized to demonstrate reconnaissance surveys. Limitations of drone-based sonar surveys are outlined, including dense water weed cover; limits on flight times and adverse weather conditions.

Extratropical cyclones play a major role in the atmospheric circulation and weather variability and can cause widespread damage and destruction. Extratropical cyclones in northern Europe, which is located at the end of the North Atlantic storm track, have been less studied than extratropical cyclones elsewhere. Our study investigates extratropical cyclones and windstorms in northern Europe (which in this study covers Norway; Sweden; Finland; Estonia; and parts of the Baltic, Norwegian, and Barents seas) by analysing their characteristics, spatial and temporal evolution, and precursors. We examine cold and warm seasons separately to determine seasonal differences. We track all extratropical cyclones in northern Europe, create cyclone composites, and use an ensemble sensitivity method to analyse the precursors. The ensemble sensitivity analysis is a novel method in cyclone studies where linear regression is used to statistically identify what variables possibly influence the subsequent evolution of extratropical cyclones. We investigate windstorm precursors for both the minimum mean sea level pressure (MSLP) and for the maximum 10 m wind gusts. The annual number of extratropical cyclones and windstorms has a large inter-annual variability and no significant linear trends during 1980–2019. Windstorms originate and occur over the Barents and Norwegian seas, whereas weaker extratropical cyclones originate and occur over land areas in northern Europe. During the windstorm evolution, the maximum wind gusts move from the warm sector to behind the cold front following the strongest pressure gradient. Windstorms in both seasons are located on the poleward side of the jet stream. The maximum wind gusts occur nearly at the same time as the minimum MSLP occurs. The cold-season windstorms have higher sensitivities and thus are potentially better predictable than warm-season windstorms, and the minimum MSLP has higher sensitivities than the maximum wind gusts. Of the four examined precursors, both the minimum MSLP and the maximum wind gusts are the most sensitive to the 850 hPa potential temperature anomaly, i.e. the temperature gradient. Hence, this parameter is likely important when predicting windstorms in northern Europe.

Tracing the origin of sediment is needed to improve our knowledge of hydro-sedimentary dynamics at the catchment scale. Several fingerprinting approaches have been developed to provide this crucial information. In particular, spectroscopy provides a rapid, inexpensive and non-destructive alternative technique to the conventional analysis of the geochemical properties. Here, we investigated the performance of four multi-proxy approaches based on (1) colour parameters, (2) geochemical properties, (3) colour parameters coupled with geochemical properties and (4) the entire visible spectrum to discriminate sediment source contributions in a mining catchment of New Caledonia. This French archipelago located in the south-west Pacific Ocean is the world's sixth largest producer of nickel. Open-cast nickel mining increases soil degradation and the downstream transfer of sediments in river systems, leading to the river system siltation. The sediment sources considered in the current research were therefore sediment eroded from mining sub-catchments and non-mining sub-catchments. To this end, sediment deposited during two cyclonic events (i.e. 2015 and 2017) was collected following a tributary design approach in one of the first areas exploited for nickel mining on the archipelago, the Thio River catchment (397 km2). Source (n=24) and river sediment (n=19) samples were analysed by X-ray fluorescence and spectroscopy in the visible spectra (i.e. 365–735 nm). The results demonstrated that the individual sediment tracing methods based on spectroscopy measurements (i.e. (1) and (4)) were not able to discriminate sources. In contrast, the geochemical approach (2) did discriminate sources, with 83.1 % of variance in sources explained. However, it is the inclusion of colour properties in addition to geochemical parameters (3) which provides the strongest discrimination between sources, with 92.6 % of source variance explained. For each of these approaches ((2) and (3)), the associated fingerprinting properties were used in an optimized mixing model. The predictive performance of the models was validated through tests with artificial mixture samples, i.e. where the proportions of the sources were known beforehand. Although with a slightly lower discrimination potential, the “geochemistry” model (2) provided similar predictions of sediment contributions to those obtained with the coupled “colour + geochemistry” model (3). Indeed, the geochemistry model (2) showed that mining tributary contributions dominated the sediments inputs, with a mean contribution of 68 ± 25 % for the 2015 flood event, whereas the colour + geochemistry model (3) estimated that the mining tributaries contributed 65 ± 27 %. In a similar way, the contributions of mining tributaries were evaluated to 83 ± 8 % by the geochemistry model (2) versus 88 ± 8 % by the colour + geochemistry model (3) for the 2017 flood event. Therefore, the use of these approaches based on geochemical properties only (2) or of those coupled to colour parameters (3) was shown to improve source discrimination and to reduce uncertainties associated with sediment source apportionment. These techniques could be extended to other mining catchments of New Caledonia but also to other similar nickel mining areas around the world.

In 1975 I was walking with Professor Ven Te Chow, the founding father of the International Water Resources Association (IWRA), asking about future water-related research directions to guide my inte...