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The upper part of a probability distribution, usually known as the tail, governs both the magnitude and the frequency of extreme events. The tail behaviour of all probability distributions may be, loosely speaking, categorized into two families: heavy-tailed and light-tailed distributions, with the latter generating \"milder\" and less frequent extremes compared to the former. This emphasizes how important for hydrological design it is to assess the tail behaviour correctly. Traditionally, the wet-day daily rainfall has been described by light-tailed distributions like the Gamma distribution, although heavier-tailed distributions have also been proposed and used, e.g., the Lognormal, the Pareto, the Kappa, and other distributions. Here we investigate the distribution tails for daily rainfall by comparing the upper part of empirical distributions of thousands of records with four common theoretical tails: those of the Pareto, Lognormal, Weibull and Gamma distributions. Specifically, we use 15 029 daily rainfall records from around the world with record lengths from 50 to 172 yr. The analysis shows that heavier-tailed distributions are in better agreement with the observed rainfall extremes than the more often used lighter tailed distributions. This result has clear implications on extreme event modelling and engineering design.

Hydroinformatics, as an interdisciplinary domain that blurs boundaries between water science, data science and computer science, is constantly evolving and reinventing itself. At the heart of this evolution, lies a continuous process of critical (self) appraisal of the discipline’s past, present and potential for further evolution, that creates a positive feedback loop between legacy, reality and aspirations. The power of this process is attested by the successful story of hydroinformatics thus far, which has arguably been able to mobilize wide ranging research and development and get the water sector more in tune with the digital revolution of the past 30 years. In this context, this paper attempts to trace the evolution of the discipline, from its computational hydraulics origins to its present focus on the complete socio-technical system, by providing at the same time, a functional framework to improve the understanding and highlight the links between different strands of the state-of-art hydroinformatic research and innovation. Building on this state-of-art landscape, the paper then attempts to provide an overview of key developments that are coming up, on the discipline’s horizon, focusing on developments relevant to urban water management, while at the same time, highlighting important legal, ethical and technical challenges that need to be addressed to ensure that the brightest aspects of this potential future are realized. Despite obvious limitations imposed by a single paper’s ability to report on such a diverse and dynamic field, it is hoped that this work contributes to a better understanding of both the current state of hydroinformatics and to a shared vision on the most exciting prospects for the future evolution of the discipline and the water sector it serves.

A participatory modelling approach is presented for effective groundwater management at the Mediterranean coastal plain of Marathon, Greece. The main objective was to identify groundwater problems in the area and to propose a viable groundwater management plan. Detailed investigation, using scientific literature and field work in the area, was conducted in order to specify the main hydrologic characteristics of the aquifer units and their quality and quantity status. Model application was accomplished with the FREEWAT platform, an open-source and public domain GIS integrated platform for effective groundwater management. SEAWAT code was utilized for variable-density groundwater flow and solute transport simulation. The participatory approach included several stakeholders’ groups from groundwater users, policymakers, environmental groups and other organizations involved in groundwater management in the area. The main issue recorded amongst all stakeholders was the high salinity of groundwater in Marathon. The outcomes of the participatory workshop were used to generate five different groundwater management scenarios and to promote the application of a managed aquifer recharge (MAR) setup that could be installed in the area. For the assessment of model results, an index was generated with the cooperation of the stakeholders in order to quantify the advantages and disadvantages of the several scenarios and to support the stakeholders in the decision-making process. The index suggested that the installation of the pilot MAR setup could facilitate salinity reduction in the shallow aquifer.

Operation of large-scale hydropower reservoirs is a complex problem that involves conflicting objectives, such as hydropower generation and water supply. Deriving optimal operational rules is a challenging task due to the non-linearity of the system dynamics and the uncertainty of future inflows and water demands. A common approach to derive optimal control policies is to couple simulation models with optimization algorithms. This paper in order to investigate the performance of a future reservoir and safely infer about its significance employs stochastic simulation, thus long synthetically generated time-series and a multi-objective version of the Parameterization-Simulation-Optimization (PSO) framework to develop uncertainty-aware operational rules. Furthermore, in order to handle the high computational effort that ensues from that coupling we investigate the potential of a surrogate-based multi-objective optimization algorithm, ParEGO. The PSO framework is deployed with WEAP21 water resources management model as simulation engine and MATLAB for the implementation of optimization algorithms. A comparison between NSGAII and ParEGO optimization algorithms is performed to assess the effectiveness of the proposed algorithm. The aforementioned comparison showed that ParEGO provides efficient approximations of the Pareto front while reducing the computational effort required. Finally, the potential benefit and the significance of the future reservoir is underlined.

The provision of high quality urban water services, the assets of which are often conceptualised as ‘blue infrastructure’, is essential for public health and quality of life in the cities. On the other hand, parks, recreation grounds, gardens, green roofs and in general ‘green infrastructure’, provide a range of (urban) ecosystem services (including quality of life and aesthetics) and could also be thought of as inter alia contributors to the mitigation of floods, droughts, noise, air pollution and urban heat island (UHI) effects, improvement of biodiversity, amenity values and human health. Currently, these ‘blue’ and ‘green’ assets/infrastructure are planned to operate as two separate systems despite the obvious interactions between them (for example, low runoff coefficient of green areas resulting in reduction of stormwater flows, and irrigation of green areas by potable water in increasing pressure on water supply systems). This study explores the prospects of a more integrated ‘blue-green’ approach – tested at the scale of a household. Specifically, UWOT (the Urban Water Optioneering Tool) was extended and used to assess the potential benefits of a scheme that employed locally treated greywater along with harvested rainwater for irrigating a green roof. The results of the simulations indicated that the blue-green approach combined the benefits of both ‘green’ and ‘blue’ technologies/services and at the same time minimised the disadvantages of each when installed separately.

Rapid urbanization affecting demand patterns, coupled with potential water shortages due to supply side impacts of climatic changes, has led to the emergence of new technologies for water and wastewater reuse. Sewer mining (SM) is a novel decentralized option that could potentially provide non-potable water for urban uses, including for example the irrigation of urban green spaces, providing a mid-scale solution to effective wastewater reuse. SM is based on extracting wastewater from local sewers and treatment at the point of demand and entails in some cases the return of treatment residuals back to the sewer system. Several challenges are currently in the way of such applications in Europe, including public perception, inadequate regulatory frameworks and engineering issues. In this paper we consider some of these engineering challenges, looking at the sewer network as a system where multiple physical, biological and chemical processes take place. We argue that prior to implementing SM, the dynamics of the sewer system should be investigated in order to identify optimum ways of deploying SM without endangering the reliability of the system. Specifically, both wastewater extraction and sludge return could result in altering the biochemical process of the network, thus unintentionally leading to degradation of the sewer infrastructure. We propose a novel Monte-Carlo based method that takes into account both spatial properties and water demand characteristics of a given area of SM deployment while simultaneously accounting for the variability of sewer network dynamics in order to identify potential locations for SM implementation. The outcomes of this study suggest that the method can provide rational results and useful guidelines for upscale SM technologies at a city level.

This paper presents an approach to enhance the role of local stakeholders in dealing with urban floods. The concept is based on the DIANE-CM project (Decentralised Integrated Analysis and Enhancement of Awareness through Collaborative Modelling and Management of Flood Risk) of the 2nd ERANET CRUE funding initiative. The main objective of the project was to develop and test an advanced methodology for enhancing the resilience of local communities to flooding. Through collaborative modelling, a social learning process was initiated that enhances the social capacity of the stakeholders due to the interaction process. The other aim of the project was to better understand how data from hazard and vulnerability analyses and improved maps, as well as from the near real-time flood prediction, can be used to initiate a public dialogue (i.e. collaborative mapping and planning activities) in order to carry out more informed and shared decision-making processes and to enhance flood risk awareness. The concept of collaborative modelling was applied in two case studies: (1) the Cranbrook catchment in the UK, with focus on pluvial flooding; and (2) the Alster catchment in Germany, with focus on fluvial flooding. As a result of the interactive and social learning process, supported by sociotechnical instruments, an understanding of flood risk was developed amongst the stakeholders and alternatives for flood risk management for the respective case study area were jointly developed and ranked as a basis for further planning and management.

The Water Framework Directive calls for strategic water resources planning at a catchment level, yet data and information are scarce in the areas where they are most needed: in the new EU Member States and Third Counties trying to assess the impact of EU environmental legislation in their water resources management policy. The research presented here proposes the coupling of a strategic scale water resources management simulation model (MIKE-Basin) and a finite difference groundwater model (ASM), as a tool to support decision making in data scarce environments. The models were applied in a particularly data scarce region, the Vrbas River basin, in Republic Srpska (RS) in Bosnia and Herzegovina (BiH) and the results are presented and discussed. It is argued that the approach adopted is valid and useful as an initial knowledge development and optioneering step, which can guide a national data collection exercise to support detailed modelling, and inform a strategic decision making process relevant to the application of the water framework directive.

This paper presents the life cycle impact assessment (LCIA) of four treatment technologies currently under investigation for recycling the greywater generated from households and describes the development of a new LCIA tool set produced in this study. The technologies investigated include reed beds, membrane bioreactors (MBR); membrane chemical reactors (MCR) and an innovative green roof water recycling system (GROW). The materials and energy required for the construction and operation phases of these technologies have been quantified for 20 development scales. All of the information gathered is used to prepare life cycle inventories for each technology. The inventories have been used as an input to Simapro Software for performing LCIA. Two assessment methods (CML-2 and Eco-indc-99) have been employed. For the CML method, the results were processed to express the environmental performance in ten impact categories including climate change/global warming, depletion of abiotic resources, acidification, eutrophication, and human toxicity. For the Eco-indc-99 method, results are shown in three generic environmental indicators: human health, eco system and natural resources. LCIA results obtained for 20 development scales have been used to develop a tool set using adaptive neuro-fuzzy inference system technique. The study results indicate that the technologies based on natural treatment processes (GROW and reed beds) have low environmental impact.

Efficient water and energy use in water distribution systems is being limited by the lack of sufficient data about water and related energy consumption. Therefore, it is crucial to provide updated and continuous feedback information to water users. This paper describes relevant use cases to improve efficient water use and related energy consumption by water utilities and consumers through the use of smart metering technologies. A systematic approach was established to obtain a comprehensive list of possible functionalities, using the concept of use case. For the consumer domain, six high-level and 18 detailed-level use cases were obtained. For the water utility domain, seven high-level and 20 detailed-level use cases were described. The high-level use cases with higher priority to be implemented in the iWIDGET system were also identified based on the contribution of different target audiences. The list of use cases covers a comprehensive range of possible usages that can be built upon the exploitation of data related to water and energy use in water distribution systems and in households, which may be of further use as a guide for similar studies.