Gridded meteorological products are generated with different spatial/data and methods, and it will be sensitive to different regions for hydrological models. Therefore variables including temperature and precipitation should be evaluated before applying them in studies. To improve knowledge of this matter, the potential of two reanalysis products (RPs) including the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) and Climate Forecast System Reanalysis (CFSR) is for the first time compared with the ground-based meteorological data in 5 years from 2008 to 2013 over Cau river basin (CRB), Northern of Vietnam. The statistical indicators, and the Soil and Water Assessment Tool (SWAT) model are employed to investigates the hydrological performance of the RPs against the 13 rain gauges placed across the CRB. The result showed that there is a strong correlation of the temperature reanalysis in both CMADS and CFSR with ground-observed (correlation coefficient-CC is from 0.92 to 0.97). The division indicated clearly when CFSR data overestimated precipitation (about 88%) at both daily and monthly scales, whereas a slight variation of CMADS product was found in the high terrain. The flow simulation results also show that the performance of CMADS-SWAT is more accurate than CFSR-SWAT on the monthly scale (with value R2 = 0.86 and NSE = 0.75). The assessment of the potential of RPs especially CMADS will further provide an additional quick alternative for water resource research and management in basins with similar hydro-meteorological conditions.

Due to increasing anthropogenic activities, trace elements remain a major concern for river water quality, particularly when waste effluents are not always constraint. The intensity of the contamination, the origin and the distribution of these elements were not frequently investigated, particularly in carbonated areas from the southern countries of limited water resources. In this context, the present study aimed at understanding the geochemistry of trace elements in bottom sediments from the Sebou basin, representing 1/3 of the surface water resources of Morocco. Four spatial sampling campaigns have been carried out in 2018 and 2019 during contrasted hydrological periods. Total and non-residual concentrations (EDTA extraction) of trace elements (As, Cd, Co, Cr, Cu, Ni, Pb, Zn) were measured in the fine fraction (< 63µm), as well as some physico-chemical parameters.

The order of abundance of the elements was as follows: Zn>Cr>Cu>Ni>Pb>Co>As>Cd. Several sediment indices of contamination and of toxicity risk were used to assess sediment quality. The results showed that 70% of the samples were naturally enriched in trace elements, specially As and Ni, as well as Cd and Pb, except in some stations. On the opposite, the most enriched elements were Cr, Zn and Cu. Chromium presented an enrichment higher than 5 and toxicity risks at some stations, such as downstream the Fez city known for its important tanneries activities. A multi-variate analysis of the datas evidenced the strong link between the identified natural elements (As, Co, Ni) with clays, Fe, Al oxides, whereas elements (Cd, Cu, Cr, Pb, Zn) mainly originating anthropogenic activities (industrial and domestic wastes, homemade, and agricultural practices), were linked to phosphorus, to a lesser extent to particulate organic carbon.

Hydrological variations hold a significant influence over the water chemistry in the karst systems within the critical zone. In this context, the Baget catchment (BC) was monitored at high-resolution over two hydrological years. The high-frequency survey at the outlet of BC displayed multiple hydrochemical patterns in response to hydrological variations, mixing water sources, and biogeochemical processes. Among the major elements, sulfate (205 ± 105 µeq/L, N=205) exhibited the widest relative variation during flooding and showed a significant dilution, whereas calcium (3.0 ± 0.2 meq/L) and bicarbonate (3.1 ± 0.3 meq/L) revealed a chemostatic behavior as a result of carbonate dissolution in the karst. Nitrate (29 ± 7 µeq/L) and chloride (46 ± 8 µeq/L) concentrations increased only during the rising limb of the hydrograph, suggesting a biogenic and rainfall origin, respectively, and a contribution for nitrates from scarce cow breeding in the upper catchment. Hysteretic analysis evidenced the control of different hydrological reservoirs compartments and antecedent moisture conditions over the stream transport processes of dissolved elements. The concentrations of suspended solids and dissolved organic carbon increased also during the hydrograph rising limb and were controlled by surface runoff and throughflow contributions. The relationships between Ca²⁺ and HCO₃^- concentrations and stream-discharge exhibited hysteresis patterns with counterclockwise loops, unlike all other elements, due to the carbonate weathering by biogenic CO₂-rich water. A slight increase of the dissolved element concentrations during the hydrograph rising limb was observed in the context of successive flood events, because of the epikarst and infiltrated-water contributions. Finally, high-frequency sampling during storm events improved the understanding of the factors controlling the hydrochemical dynamic of the Baget stream water. The relative contributions of the karst and epikarst zones, of rainwater, as well as the role of different biogeochemical processes and the hydrological conditions (past and successive floods), were highlighted.

Climate change and flood risk in urban areas has attracted growing attention to discussions over urban resilience and water quality improvement at urban drainage. Nature-based Solutions (NBS) as green infrastructures to urban drainage, when incorporated in urban planning, has proven to be an effective mitigation strategy both in terms of quantity and quality of runoff. The Real-time Control (RTC) applied in urban water can complement to both flood mitigation and improvement of water quality through the control of the elements of the drainage and sewage system to search for the optimal configurations. Although, it is required to have a quantitative and qualitative Real-time Monitoring (RTM) system and the application of actuators technology and intensive use of software to be able to use the RTC. This study assessed the improvement opportunities in NBS performances with RTC and the remaining challenges to integrating both methods. The requirements of RTC application were analyzed according to technologies already applied at the NBS systems. Additionally, our investigations showed that the devices related to NBS can benefit from RTC. However, the most significant potential gains with the application of RTC are the techniques that can operate as storages such as bioretention, green roofs and bioswales. Despite the potential increase in costs for the construction of NBS, the benefits of applying the RTC can assist both resilience to floods and water quality.

Currently, pesticides are massively used and end up in watercourses, mostly in agricultural areas, which are usually final receptacles of organic contamination. In agricultural catchments, there are a large number of ponds, which consist in a complex and dynamic environment. Indeed, today the role of such ponds is still poorly investigated. Ponds are composed of different compartments such as the water column, bottom sediments and vegetation. The Pestipond project aims to characterise the role of wetlands and more particularly natural or artificial ponds, in pesticides transfer and fate within agricultural catchments. More specifically, the objective of the work presented here was to understand the inherent processes in the different pond compartments, especially in sediments since they were indeed supposed to be highly involved in the storage and degradation of pesticides.

The Bassioué pond is located in an agricultural upper sub-catchment of the Auradé critical zone (Gers, France), with a wheat/sunflower crop rotation and a steep slope. It was investigated (i) to understand how and where pesticides are stored in the sediments, and (ii) to determine the physicochemical parameters and the environment characteristics, which influence the pesticides molecules behaviour. Two coring campaigns were conducted over two periods (autumn 2019 and summer 2020). Core samples of about thirty centimetres were taken following a regular quadrat of the pond in order to investigate the spatial variation and distribution of sediment characteristics and of the associated pesticides molecules. A set of pesticides molecules was quantified to evaluate the level of contamination, as well as sediment granulometry and physico-chemical parameters. The results highlighted that sediment texture varied between upstream and downstream of the pond, as did the spatial distribution of pesticides, which was partly controlled by their physicochemical properties. Hydrophilic pesticides had more affinity with the finest fractions of the sediments. This work provides new knowledge on the role of ponds in pesticide storage, dissipation and transfer downstream.

Background: Contamination of water bodies by phosphorus has caused ecological problems worldwide. Phosphate, an essential macro-nutrient for aquatic systems, causes eutrophication where industrial and household activities lead to excess amount of it to water bodies through wastewater. Modern and low-cost treatment technologies to remove phosphate from wastewater are sorely needed for developing countries. Objective: We investigated and evaluated design parameters to remove phosphate by sorption onto crushed volcanic rock common in Ethiopia where eutrophication of waters from waste streams is common. Methodology: Kinetic and equilibrium sorption experiments were conducted to evaluate removal of phosphate from aqueous solutions by crushed pumice and scoria volcanic rocks common in the main rift valley of Ethiopia. Washed and dried rocks was ground to 0.075 to 0.425mm particle size and variable amounts immersed in molal concentration of Phosphate for 240min to fully saturate the exchange sites at adjusted pH. We methodically evaluated contact time, solution pH, initial concentration of phosphate, ground rocks quantity, and particle size effects on the removal of phosphate. Phosphate was measured by molybdenum-blue ascorbic acid method using continuous flow analyzer. Zero point charges of the ground rocks were measured using solid addition method with KNO₃ as solution maker and impact of co-existing ions on the adsorption was also employed. Results: The values of point zero charge were measured to be 7.2 and 9.3 for pumice and scoria respectively at fine particle size. The maximum removal capacities of phosphate 294.30mg/Kg and 168.95mg/Kg were obtained for pumice and scoria respectively for a phosphate concentration of 10mg/L, fine particle size (0.075mm to 0.425mm), pH 6.05, crushed rock doze 40g/L and contact time of 240min. The experimental data are well described by the pseudo-second- order equation with a correlation value of R² > 0.99. Langmuir, Freundlich and Dubinin Radushkevich isotherm models were examined and fitted to the experimental data. Conclusion: kinetic and adsorption isotherm results showing it is practical to use volcanic pumice and scoria to remove phosphate from water, but additional testing in a flow-through set-up is required to reach efficiency of the approach for the practical application.

Pool filter backwash accounts for a significant share of wastewater generated in swimming pool facilities. Although rinsing water is taken from the expansion tank, it is necessary to replenish water loss on a regular basis. For example, the daily water consumption of a recreational swimming pool and a hydromassage tub with a total capacity of the water treatment system of 75.9m³/h is 9.88m³/d. The rising costs of water intake, wastewater discharge, and water scarcity necessitates that swimming pools seek solutions that would reduce the facility maintenance costs.

One of the options of limiting wastewater discharge is to recycle backwash. The main problem with this is the high content of suspended solids and elevated concentration of chlorine compounds in the backwash. Therefore, before it is discharged into the environment, it is necessary to conduct pre-treatment, in particular, sedimentation and dechlorination. In addition to compliance with the physicochemical standards, it is also necessary to take into account the ecotoxicological impact of wastewater discharge.

The presented studies have analysed the physicochemical and phytotoxicological parameters of backwash from two swimming pools. Ten independent samples were taken from each pool being tested in order to measure several chosen indicators and conduct bioassays using Lepidium sativum, Sinapis alba, and Lemna minor. The influence of dilution and the matrix of diluted backwash were also analysed. Solutions with 0, 5, 10, 25, 50, 75, and 100% of backwash diluted with deionised water, tap water, or rainwater were prepared and the influence of dilution on the obtained responses from plant indicators was determined. The objective of the study was to identify whether it might be possible to use backwash after pre-treatment for the purpose of irrigation.

Recent reports, according to international organizations, on the highly toxic presence of methylmercury (MeHg) in the environment, classify it among the other high priority pollutants. Mercury mainly released in its inorganic or elemental form through anthropogenic emissions. MeHg is formed through biotic and abiotic mechanisms when inorganic or elemental Hg enters water resources and seawater. Understanding the need to find new, but also safe, sources of usable water and to monitor the current ones, aim of this study is to investigate the determination of MeHg by cold vapor analysis, providing useful facts regarding methods optimization, in order to be adopted from other researchers. Since Hg regulation limit in drinking water is 1 μg/L, experimental pollutant’s concentration was in the range 0-10 μg/L, while as matrix was applied natural-like water, according to National Sanitation Foundation. During cold vapor analysis organic or/and inorganic mercury atomization takes place chemically by a reducing agent. The most known agent is SnCl₂, which however reduces only the inorganic Hg. Instead, NaBH₄ is capable to reduce both Hg modes but a pretreatment of the sample is required before the measurement, namely the addition of KMnO₄. So, in this work, reagents’ concentration was studied, and their role was clarified in every step of the proposed method analysis. According to the results, the addition of at least 0.005% w/v KMnO₄ and 0.05% w/v NaBH₄ is needed in the aquatic sample for a reliable MeHg measurement. Even if the KMnO₄ addition intended to transform organic mercury to inorganic, it was proved that this is only partially true. In fact, the formed MnO₂, that produced by the reduction of the residual KMnO₄ from NaBH₄, catalyzes the MeHg atomization reaction.

Acknowledgments: This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning» in the context of the project “Reinforcement of Postdoctoral Researchers - 2nd Cycle” (MIS-5033021), implemented by the State Scholarships Foundation (ΙΚΥ).

With the increased population in urban areas worldwide, the security of water supply is gaining in importance. Water scarcity accelerated by climate change poses additional stress to water supply infrastructures. Water consumption data transmitted by smart water meters form the foundation of advanced data analysis, such as water end-use classification, with which the resilience of water supply can be improved. Especially with large amounts of high-resolution data, the accurate categorization of data from smart water meters into different end-uses such as toilets, showers or dishwashers is challenging and cannot be performed by humans. To this end, machine-learning (ML) approaches provide several benefits, such as real-time capability, scalability and generalizability.

State-of-the-art methods to identify residential water end-uses include both unsupervised methods and supervised approaches. However, a comprehensive comparison of unsupervised and supervised techniques is still missing. In this study, we are aiming at a quantitative evaluation of various ML techniques for water end-use classification. Furthermore, we focus on deriving general implications on the setting and conduction of ML-based experiments for water end-use classification. For these purposes, a stochastic water consumption simulation tool with high capability to model the real-world water consumption pattern is applied to generate residential data. Subsequently, unsupervised clustering methods, such as dynamic time warping, k-means, DBSCAN, OPTICS and Hough transform, are compared to supervised methods based on SVM.

The quantitative results demonstrate that supervised approaches are capable to classify common residential end-uses (toilet, shower, faucet, dishwasher, washing machine, bathtub and mixed water-uses) with accuracies up to 0.99, whereas unsupervised methods fail to detect those consumption categories. The major implications drawn from the quantitative results are two-fold: clustering is not suitable to separate end-use categories. Hence, accurate labels are essential for the end-use classification of water events, where crowdsourcing and citizen science approaches pose feasible solutions for this purpose.

The St. Johns River, located in Northeast Florida, USA, is a large watershed characterized by relatively flat topography, porous soils, and increasing urbanization. The city of Jacksonville, Florida is located near the downstream terminus of the river near the Atlantic Ocean. The lower portion of the watershed located downstream of Lake George is subjected to tidal exchange and storm surge from tropical storms and hurricanes as well as extra-tropical winter storms. Extreme flood events in the Lower St. Johns River can be caused by rain-driven runoff, high tide, storm surge or any combination of the three. This study examines the range of potential extreme flood discharges caused by rain-driven runoff within six larger sub-basins located in the Lower St. Johns River. The study uses multiple methods including published flood insurance data, two statistical hydrology methods, and model simulations to estimate an array of flood discharges at varying return frequencies. The study also examines the potential effects on flood discharges from future land use changes and the temporal distribution of rainfall. The rain-driven flood discharge estimates are then fit to a normal distribution to convey the overall risk and uncertainty associated with the flood estimates. The study also proposes a new methodology to estimate rain-driven flood discharges using existing numerical models of each the six sub-basins prepared by the Saint Johns River Water Management District. Overall, the study revealed a wide range of reasonable rainfall-driven flood estimates are possible using the same data sets. The wide range of estimates will help inform future resiliency projects planned in the study area by providing a more realistic set of bounds with which planning can proceed. The estimates derived herein can be combined with the independent or dependent effects of tide and storm surge in order to characterize the total flood resiliency risk of the region.