The significant sources of wastewater are domestic households, industries and hospitals. This paper would cater to resolving critical issues arising due to the latter i.e., hospital wastewater. The onset of COVID-19 and its escalation to a global pandemic is reason enough to surveil hospital wastewater (HWW) owing to its epidemiology and ecotoxic nature and impact. The wastewater from hospitals is a hotbed of emerging contaminants like pharmaceutically active compounds (PhACs), heavy metals, surfactants, radioisotopes and other hazardous substances. Hospital effluent is characterized by a high chemical oxygen demand (COD) ranging between 120 – 500 mg/L and an average Biochemical Oxygen demand (BOD) is around 200 mg/L along with the presence of Nitrogenous compounds, total organic carbon, suspended solids, epidemic vectors and other emerging contaminants. A Core HWW has a very low biodegradability index along with having a low BOD: COD ratio ranging between 0.29 to 0.34, which is indicative of the ‘difficulty’ in treatment via the most economical treatment method i.e., biological pathway. The volume of wastewater generated from hospitals depends on its size and type, patient intake capacity, technical facilities and miscellaneous services provided to patients. The purpose of this paper would be to solely target the “ABC (Algal-Bacterial Consortia)-based MBBR as an onsite decentralized treatment system for hospital wastewater using microbial intelligence” such that any epidemiological or ecotoxicological risks are prevented, if not eliminated. The introduction of algal biomass along with “fragile” bacterial consortium may circumvent the above-presented challenges by prominently addressing a) PhAC shock load; b) sustainable pollutant removal requiring less oxygen support; c) Surfactant-Antibiotic removal without causing ecotoxicological and epidemiological by-product vectors. Hence, the basic intent of this research would be to hybridize MBBR technology by using algal bacterial consortium (ABC) and target the ‘FES (feasible, effective and sustainable’ onsite treatment facility of hospital wastewater.

Heavy metals are descried as environmental pollutants because their toxicity, longevity in the atmosphere, and unfortunately their ability to accumulate in the human body thru bio-accumulation. Also, the pollution of terrestrial and aquatic ecosystems with toxic heavy metals is a major environmental concern that has consequences for public health. These heavy metals are characterized by their high atomic mass and toxicity to all organisms. Most of them cause environmental and atmospheric pollution, and more drastic can be lethal to humans. Heavy metals can become very toxic in contact with different environmental elements (water, soil, air). Eco-friendly and low-cost methods become new perspectives for near future. Our research development a process for removal of nichel ions from waste water. Using Typha angustifolia plant, were made experiments to perform the Ni (II) ions removal. It was observed an increase using more than a plant via a long period of time, the yield being approximately 85% when 5 plants were used, compared to 77% yield when only one plant was used.

The objective of this paper is to analyse the economic feasibility of using rainwater for non-potable purposes in single-family houses in the city of Blumenau, Brazil. A house was used as a case study to estimate the water end-uses and water consumption. Residents were asked to register the frequency and time of use of water fixtures. Then, the daily water consumption and water end-uses for non-potable purposes were estimated. To account for houses of different characteristics in Blumenau, different roof areas, number of residents, daily per capita water consumption, and rainwater demand were adopted. The rainwater tank capacities, the potential for potable water savings and economic feasibility analysis were performed using the computer programme Netuno 4. For the different scenarios, the potential for potable water savings ranged from 18.76% to 58.06%, with an average equal to 37.90%. For the case-study house, the potential for potable water savings was 50.32%. The rainwater harvesting system was found to be economically feasible for 58.3% of the different scenarios and also for the case-study house. Thus, the implementation of rainwater harvesting systems for single-family houses in Blumenau proved to be economically feasible for most cases.

We propose an automatic and non-invasive system for monitoring the health of vine plants by measuring their water stress, with the goal of mitigating the increasingly frequent extreme meteorological events such as droughts. The envisioned system measures the spatial distribution of the Crop Water Stress Index (CWSI) on the crop field, to provide the farmers with a precise control on their vine’s health and, therefore, on the final quality of their product. To ensure the robust acquisition of parameters needed to compute the CWSI, data are collected by field sensors on the ground, by drones, and by exploiting satellite data. Data fusion then allows to obtain an associated georeferenced heatmap of the vineyard. The solution has been tested via a prototype, which allowed the collection of information in a vineyard.

Climate change has various impacts on different living conditions of societies. Climate change-induced environmental impacts have had an especially strong influence on water resources, which has had negative consequences for societies’ living conditions. Increasing global temperatures are bringing huge problems with surface water evaporation, while the warmer atmosphere is maintaining more moisture aloft that causes both heavy floods and induces extreme droughts in different parts of the world. Declining water availability not only is resulting in droughts but is also responsible for decreasing the quality of water in water-scarce regions, such as the South Caucasus. Countries cannot adopt to climate change by themselves and require international governance of water and other natural resources. Without sufficient water resources, the overall productivity of societies is decreasing, influencing demographic change, economic development, urbanization, and globalization, as well as intensifying conflicts over water use. In the Southern Caucasus, the long-standing Nagorno-Karabakh conflict (1988-present) between Azerbaijan and Armenia erupted again into war in 2020, resulting in Azerbaijan recapturing much of its territory from local Armenian separatists and Russia negotiating a new truce and installing troops to maintain the peace. In my paper, ask what the nexus is between conflict and insufficient water resources? How will intensifying climate change in the region affect the current political situation – is there any chance of multilateral cooperation on water management?

Hydraulic modeling of Water Distribution Networks (WDNs) is an important task towards the development of efficient water management practices and strategies, aiming at the reduction of water losses and the associated financial cost and environmental footprint.

In the current work, we develop an easily applicable methodology for effective modeling of WDNs, which seeks to minimize the computational load while maintaining a sufficient level of estimation accuracy, using the public domain EPANET software engine. To realistically describe a WDN, we use sensitivity analysis to determine the appropriate nodal density, which should be high enough as to effectively describe both topographic variability as well as the original connectivity of the network, while taking into account all necessary hydraulic parameters (e.g., pipe diameters and materials used). To conduct the hydraulic simulation, we firstly define the total water demand at each computational node of the network, as the sum of a demand-driven and a pressure-driven component. The demand-driven component depends on the flow time pattern, as users’ consumption varies during the day, while the pressure-driven component reflects the network’s leakages, which are an increasing function of the applied pressure. Modeling of leakages is conducted by borrowing concepts from Torricelli’s Law, assuming that the distribution of leakages is proportional to the square root of the excesses of the simulated nodal pressures above the minimum pressure required to meet the consumption standards.

The effectiveness of the proposed methodology is tested via a large-scale, real-world application to the 4 largest Pressure Management Areas of the WDN of the city of Patras, the third largest city in Greece.

History-long discussions on the IWRM are making the idea that the recipient stakeholders' poor participation is obstructing sustainable decision-making in urban flood management. Early works found dozens of negative reasons for the practical incorporation of recipients' perspectives in administrative decision-making. However, it found there is no in-depth study has been carried out to inductively explore the present situation. Then this work explored the present status of stakeholder integrations in IWRM. It carried out abductive research using a sequential multi-phase approach of the mixed method. It employed modified constructivist grounded theory, documentary research, and survey strategies to find and verify the main components and their integration depths in the scientific and management model of urban flood management. For the component identification, it studied the GIS2MUSCLE urban flood management tool, 4 hydro-GIS integration models, and 247 works of research and for calibration, it utilised 21 experts. The average integration depths among the components were calculated using 32 research works employing WAP of MCDA and evaluated the result with 70 experts using MCGDM. The present work found there are five main components in the urban flood management model namely, Hydro modellers, GIS modellers, HydroGIS modellers, decision-makers and recipients and at the present, all the components are integrated with low (value 2 out of 5) status. Further, those components are in two groups, scientific modellers (Hydro and GIS modellers) and management modellers (decision-makers and recipients) while HydroGIS modellers are developing the entire flood management model integrating the perspectives of both groups. Nevertheless, the research found that they are more biased toward the management model and maintain very low (0.94 out of 5) integration with the scientific model. Therefore, this work concludes by stating that in the present IWRM situation it should pay more attention to integrating scientific modellers’ perspectives when satisfying the recipients' requirements.

The planning, design and management of water resources projects require good estimates of flow and maximum discharge at certain points within a basin. Machine Learning (ML)-based Data-driven modelling is an efficient approach to achieve such an end. This paper is mainly aimed to determine if daily streamflow can be predicted satisfactorily using ML algorithms based on open source flow discharge and rainfall historical time series. In this sense, two modelling scenarios, without and with considering the antecedent hydrologic conditions, were evaluated. Three ML algorithms—Support Vector Machines, Random Forest (RF) and Gradient Boosting (GB) —compared to Multiple Linear Regression (MLR), were implemented and applied to the Besós River basin, Spain. The prediction results were compared to observed values, based on performance metrics (root mean square error, mean absolute error, coefficient of determination and Nash-Sutcliffe coefficient of efficiency) and graphical examination (observed and predicted hydrographs). The performance comparison of the results revealed that SVR model outperformed the other suggested models. Additionally, it was deduced that taking into account the preceding hydrologic conditions clearly improves the prediction results.

Emerging pollutants, in particular, organic pollutants in groundwater are not enough researched due to the absence of monitoring regulations, nevertheless, monitoring is on a voluntary base. Organophosphate esters (OPEs), triesters, are used as flame retardants and plasticizers to protect or enhance the properties of plastics, textiles, and many other materials. They are high-production volume chemicals with large variations in physical-chemical properties widely used in many human activities and can be detected in groundwater due to their insolubility in water, especially in wastewater. There are developed analytical methods for the determination of OPEs in water i.e., various extraction techniques followed the gas chromatography with mass spectrometry (GC-MS) and liquid chromatography with mass spectrometry (LC-MS). Sampling was carried out in groundwater from the karst aquifer Bokanjac – Poličnik near the city of Zadar, Croatia in order to detect some of the OPEs. To determine their continuous presence in the case study aquifer, samples were taken during the entire hydrological year, that is, once during each season through one year. Some of the OPEs were detected in samples of groundwater from the karst aquifer Bokanjac – Poličnik. Preparation of samples was made with the Solid Phase Extraction (SPE) method and analyzed with liquid chromatography with mass spectrometry and quadrupole time of flight (LC-MS/QTOF). In collected samples nine OPEs were identified with Water Screening Personal Compound Database and Library (PCDL): tris(2-butoxyethyl) phosphate - TBEP, tricresyl phosphate - TCP, triphenyl phosphate - TPPA, tris(1-chloro-2-propyl) phosphate - TCPP, (tris(2-chloroethyl) phosphate - TCEP, tris(1,3-dichloroisopropyl) phosphate - TDCPP, diethyl phthalate - DEP, tri-n-butyl phosphate - TBP, and di(2-ethylhexyl) adipate - DEHA.

Acknowledgment: KK.01.1.1.04.0006 - Otpad i Sunce u službi fotokatalitičke razgradnje mikroonečišćivala u vodama (OS-Mi) and KK.05.1.1.02.0022 – Upravljanje krškim priobalnim vodonosincima ugroženim klimatskim promjenama (UKV)

The Global Change Explorer (GCE) is an interactive web-based tool for investigating the complexities of global change (https://www.globalchange-uwo.ca/ ). The GCE is using the ANEMI simulation model developed at the University of Western Ontario. ANEMI simulates system dynamics to offer information on Earth's dynamic processes and the behaviours that instigate change. The main thrust of ANEMI is to explicitly integrate various sectors (natural, physical and socioeconomic) into a single model, providing effective consideration of the high-level feedback relationships between the physical environment and social adaptation. At lower levels, this relationship ends in thousands of feedbacks between various model sectors and variables. The ANEMI model is an integrated assessment model of global change that emphasizes the role of water resources. The model sectors that comprise the ANEMI3 (the current version of the model) are that of the climate system, carbon, nutrient, and hydrologic cycles, population dynamics, land use, food production, sea level rise, energy production, global economy, persistent pollution, water demand, and water supply development. The ANEMI3 model is developed using Vensim system dynamics simulation environment. The entire model code is archived using Zenodo (https://doi.org/10.5281/zenodo.4025424 ) and open access. Details on how to run the model, modify inputs, and view the outputs in graphical or table formats are provided in the repository. The GCE is designed to allow the use of ANEMI3 to simulate various future scenarios related to five main themes: climate change; population dynamics; food production; water quality and water quantity. The users are presented with the opportunity to ask different questions, select simulation runs, and evaluate model outputs.